Deciphering the transcription regulation of bovine papillomavirus (BPV)-associated equine sarcoids through OMIC integrated approach

Deciphering the transcription regulation of bovine papillomavirus (BPV)-associated equine sarcoids through OMIC integrated approach | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Deciphering the transcription regulation of bovine papillomavirus (BPV)-associated equine sarcoids through OMIC integrated approach S. Mecocci, S. Capomaccio, I. Porcellato, F. Dell’Anno, R. Ratto, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6975941/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Sarcoids are the most common cutaneous tumors in horses, representing up to 90% (35–90%) of skin neoplasms. Mostly caused by Bovine Papillomavirus (BPVs) infections, sarcoids are highly resistant to therapy and prone to recurring, posing a significant threat to equine health. The aim of this study is to explore molecular pathogenetic mechanisms underlying the development of BPVs-associated sarcoids, by applying transcriptomic approach. After testing samples for viral DNA, both mRNA and small RNA expression was analyzed via high-throughput Illumina sequencing comparing 12 sarcoids and 12 healthy skin samples as controls. Differentially expressed genes (DEGs), DE miRNAs (sarcoids vs controls) and miRNA-DEG couples with opposite expression trends, were retrieved and subjected to a functional analysis. Over 6K DEGs emerged, 3620 down-regulated and 2415 up-regulated along with 145 DE miRNAs, 56 down-regulated and 89 up-regulated. Among the enriched biological processes for DEGs, some were related to growth factors production and collagen binding, cell migration and proliferation, tissue morphogenesis and inflammatory response. Interestingly, “ Pathways in cancer ” and “ Hippo signaling pathway ” were enriched KEGG pathways for the miRNA-DEG couples. Our data identified a great transcription discrepancy between sarcoid lesions and healthy skin with an overall enrichment for processes related to cellular transformation. Biological sciences/Cancer Biological sciences/Computational biology and bioinformatics Biological sciences/Molecular biology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1 INTRODUCTION Equine sarcoids are locally aggressive, non-metastatic skin tumors, affecting up to 12% of horses worldwide. They are the most common neoplastic disease in horses and other equids such as donkeys, mules, or zebras, representing up to 90% of all equine cutaneous tumors 1 . Bovine papillomavirus (BPV) type 1, 2, and 13 (BPV1, BPV2, BPV13) play a central role in the etiology of equine sarcoid and the disease is considered the result of a non-productive infection 2 . The viral type and the epidemiological proportion between types involved depends on the country in which the horse live 3 – 6 . The main way of transmission is by direct contact, contaminated fomites, and shared living environments, but also vertical transmission has been suggested in equids by evidence of BPV gene expression in the blood and semen of healthy horses, as well as in the placenta. Moreover, it has been shown that co-stabling of sarcoid-affected and healthy donkeys can result in the transmission of BPV1, with insects suspected as possible transmission vectors 2 . Papillomaviruses (PVs) belong to the large family of animal and human Papillomaviridae that normally infect epithelial cells, mostly causing benign proliferative lesions known as warts. On the other hand, some types of PVs can induce benign and malignant tumors in both humans and animals, including BPV types 1 and 2. These viral types can also infect fibroblasts and induce fibroepithelial tumours, like benign fibropapillomas in cattle 7 , 8 . Among the most common and specie-specific equine PVs is EcPV2, which is related to equine genital squamous cell carcinomas 9 – 12 . Although PVs are normally strictly species-specific and are characterized by a pronounced tropism for cutaneous and mucosal keratinocytes, equine and feline sarcoids are a well known case of natural cross-species PV infection 13 , 14 . Although biology, morphology, and epidemiology of equine sarcoids are known, the pathogenic events leading to the development of tumors and the mechanisms used by BPV to induce the lesions are poorly understood. Tumorigenesis is a complex process that involves numerous molecules and pathways; in equine sarcoids BPV1 and BPV2 may be responsible for the abnormal fibroblast proliferation and the alterations in the metabolism of extracellular matrix (ECM) and its main components (e.g. collagen) 15 . Sarcoids are typically diagnosed through a combination of clinical presentation and histopathological evaluation. Polymerase chain reaction (PCR) from superficial swabs, skin scrapings, or the tumour mass can be helpful for the identification of BPV DNA that is thought to be diagnostic for equine sarcoid, although BPV DNA can only be demonstrated in 70% of equine sarcoids 16 , 17 . Recently, hypotheses have emerged suggesting also a potential role of ovine papillomavirus in the development of equine sarcoids 18 . The equine sarcoid remains a clinical challenge since the high risk of treatment failure and local invasion is a major constraint to therapy. The likelihood of recurrence (in the same origin site or growth of a new sarcoid) is highest wheb surgical therapeutic methods are applied and it seems to be correlated with the presence of BPV DNA on the surgical margins 3 , 19 . Natural immunity against BPV1 and 2 in equids appears to be poor and sarcoid-affected horses show no measurable anti-BPV1 L1 antibodies. This circumstance may help to explain why sarcoids are usually present as persistent lesions; BPV may escape from immune surveillance because of its paramount localization in cutaneous cells, yet also because of its capacity to inhibit MHC class I-mediated antigen presentation via its major oncoprotein, E5 20 . Given the current challenges in establishing effective therapies, the identification of the key cellular drivers of sarcoid growth paves the way for the future development of brand-new targeted therapeutic approaches 15 . In this study, deep RNA and miRNA sequencing were applied to better understand host-pathogen interactions and the tumor microenvironment in equine sarcoid, taking advantage of Next Generation Sequencing (NGS) technologies. RNA-seq indeed is a gold standard technology for investigating transcriptomic patterns detecting and large number of genes and regulatory regions in specific physiological and pathological conditions quantifying the expression profile. 21 . 2 METHODS 2.1 SAMPLE COLLECTION Horses and donkeys enrolled for this study (Table 1 ) were examined at the Didactic Veterinary Hospital (OVUD) of the Veterinary Medicine’s Department of the University of Perugia. Written informed consent was obtained from the animal owners prior to their inclusion in the study and sample collection. Table 1 Recruited horses and donkeys. F: female; M: male; G: gelding. Cases Lab ID Spieces/Race Sex Age Lesions’ site 1 T1 Equus Asinus F Adult Periocular 2 T2 Equus Caballus, Thoroughbred F 12 Abdomen Udder 3 T3 Equus Caballus, Italian saddle G 7 Periocular 4 T4 Equus Caballus, Italian saddle M 5 Periocular 5 T5 Equus Caballus, Arab F 14 Paramammary 6 T6 Equus Caballus, Akal teeke G 13 Abdomen 7 T7 Equus Caballus, Belgian horse M 5 Scrotum and ear 8 T9 Equus Caballus, Pony F 9 Right rear hock 9 T10 Equus Asinus G 5 Periocular 10 T12 Equus Caballus, Pony F 21 Abdomen 11 T14 Equus Caballus, Italian saddle G 7 Abdomen inner thigh 12 T15 Equus Caballus, Italian saddle F 6 Inner thigh and chest Animals with concomitant diseases or poor clinical conditions were excluded. The lesions were surgically removed with a 3 cm lateral margin. The excised lesion and margin were subjected to histopathological evaluation and polymerase chain reaction (PCR) to assess the presence of viral DNA. After sampling for histology and and margin assessment, part of the residual tissues of tumor samples and tumor-free margin samples (potential paired controls from the same animal) were stored at -80°. The inclusion parameters were: clinical and confirmed histopathological diagnosis of sarcoid, lesions > 2 cm in diameter. After histological confirmation of diagnosis and assessment of margin status, samples meeting the selection criteria were used for NGS, together with ten cutaneous tissues collected from heathy donors at slaughterhouse that tested negative for viral DNA (control group). 2.2 HISTOPATHOLOGICAL CHARACTERIZATION Surgical samples were submitted to routine processing for histopathology, with evaluation of surgical margins. Margins were sampled using a combined evaluation using cross-sectioning for smaller samples (< 4 cm as major diameter) and a combination of cross and “bread loaf” sectioning for larger samples 22 . The histopathological diagnosis of equine sarcoid, with variable degree of diagnostic certainty, was based on the presence of one or more of the following features: - spindle cell neoplastic proliferation; - presence of epidermal hyperplasia with deep rete ridges (rete pegs) interdigitating with the dermal proliferation; - “picket fence” arrangement of neoplastic cells in the subepithelial area (rows of fibroblasts with a perpendicular orientation of the epidermal basement membrane). 2.3 DNA EXTRACTION AND PCR ASSAY FOR BPV DETECTION DNA was extracted starting from frozen and grinded samples using RecoverAll Total Nucleic Acid Isolation Kit (Termo Ficher Scientific, Waltham, Massachusetts, United States) and following manufacturer's instructions. The presence/absence of BPV DNA was assessed for all the samples (sarcoid lesions, margins and controls) by applying a Taqman assay on the L1 genomic region of the 3 BPVs (BPV1, BPV2 and BPV13) using primers and probes (Table 2 ) designed through Primer3 web-tool ( https://primer3.ut.ee ). Table 2 Primer sequences and probes used for the detection of BPV1, -2, -13 DNA in Real Time PCR (BPV1, BPV2, BPV13). Beta-2-Microglobulin (B2M) was used as the reference gene. Target Primer pairs Probe Amplicon size Accession number BPV1-L1 For -5’-CAGGACTGTTCACAACCCAAG-3’ Rev -5’-CCCAGTTACAGTACCTCCAAGA-3’ FAM -TGCAGGTGTCCAGAGGGCAG- TAMRA 97 JX678969 BPV2-L1 For -5’-ACAGCCCGTCCATGTGTTA-3’ Rev -5’-TCAGCAGCACCAAACCCTAT-3’ FAM -AGAAAATGGTGCGTGTCCTCCT- TAMRA 116 M20219 BPV13-L1 For -5’-GCACCCCACTTTTAATGCCT-3’ Rev -5’-TCCTGTTTGCTTCCTGTCATC-3’ FAM -AGGAAAGTGACCAGCCAAACAACA- TAMRA 88 NC_030795 B2M For -5’-CTGATGTTCTCCAGGTGTTCC-3’ Rev -5’-TCAATCTCAGGCGGATGGAA-3’ FAM -ACTCACGTCACCCAGCAGAGA- TAMRA 136 NM_001082502.3 For Real Time qPCR detection, 5 µl of template were added to the reaction including 1X CustomProbe, 2x qPCR Master Mix (Canvax Reagents SL, Valladolid, Spain), 200 nM of probe and100 nM of each primer combination. The thermal protocol used for amplification in a CFX96 TM Real- Time (Bio-Rad, California, USA) was: 95°C for 10 min, followed by 40 cycles of 95°C for 15 seconds, 60°C for 60 seconds. 2.4 RNA EXTRACTION AND SEQUENCING OF SMALL RNA AND mRNA The 12 samples of tumour tissue, 2 histologically healthy portions of the T1 and T5 sarcoid margin and the 10 samples of healthy skin were subjected to total RNA extraction with a commercial kit (miRNeasy Kit, Qiagen, Hilden, Germania), following the manufacturer's instructions. The extracted RNA was qualitatively and quantitatively evaluated by spectrophotometric measurement with NanoDrop 2000 (Thermo Fisher Scientific, Waltham, MA, USA) and by microfluidic electrophoresis (Bioanalyzer 2100 Agilent Technologies). RNA samples were used to produce two different sequencing libraries, one for mRNA using the TruSeq RNA Library Prep Kit and the other for small RNA through the TruSeq® Small RNA Library Prep kit, following the manufacturer's instructions. For small RNA sequencing, unique molecular identifiers (UMIs) were introduced during the library preparation allowing error correction and increased accuracy during sequencing. Libraries were sequenced on a NextSeq500 instrument producing 150 bp pair-end fragments. 2.5 BIOINFORMATIC ANALYSIS Raw sequences were first checked for quality with FastQC ( http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ ), and trimmed from low-quality/adapter sequences using Trim Galore 0.6.6 software ( https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/ ). Trimmed reads were used for the alignment procedure and downstream analysis, which differed for mRNAs and small RNAs. 2.5.1 FROM READS TO GENES For smallRNAs libraries were prepared with UMIs, to accurately account for PCR duplicates and enhance quantification precision. The umitools package was used to process these data 23 . Following UMI extraction the reads were used to perform a two-step alignment: first, on miRBase 22 hairpin (horse) 24 , to recover micro RNA (miRNA) information; second, the unmapped reads from the previous step, on EquCab3.0 25 genome, to recover additional information on miRNAs and on the other small RNA typologies. The Bowtie2 algorithm with very sensitive local flag 26 was used as aligner 27 . After alignment steps, reads were deduplicated based on UMIs. Uniquely mapped reads were used for downstream analysis: for miRNAs from miRBase, a homemade script was applied for counting, while reads aligned to the genome were counted through FeatureCounts 28 using the horse annotation (Equus_caballus - Ensembl genes 109) and obtaining four count matrices (miRNAs, protein-coding RNAs, lncRNAs and all the other as miscellaneous RNAs). Last, the two miRNA matrices (miRBase and genome) were merged in order to build a unique count matrix for miRNAs. For mRNAs, the STAR algorithm 29 was used to align reads to the reference genome EquCab3.0. The data generated from the alignment were then used to identify the genes expressed in our samples using the horse annotation (Equus_caballus - Ensembl genes 109), while their expression level was assessed by counting reads uniquely aligned with the FeatureCounts software. 2.5.2 RETRIVING GENE EXPRESSION DIFFERENCES BETWEEN SARCOIDS AND CONTROLS The count matrices were imported into R environment and a preliminary exploratory analysis was carried out applying the hierarchical clustering hclust function of the “stats” package ( https://rdocumentation.org/packages/stats/versions/3.6.2 ) and performing a principal component analysis (PCA) through the plotPCA function in DESeq2 package 30 . The latter was also used to identify differentially expressed miRNAs and genes (DEGs) between samples derived from sarcoids (T) and those derived from margin(M)/healthy(X) tissues (considered as control group). The R package ggplot2 31 was used to produce volcano plots. Genes/miRNAs were considered differentially expressed (T vs M/X) if they had a |log2FoldChange| (|log2FC|) > 1 and an adjusted p-value (FDR) < 0.05 and were then subjected to the functional analysis. 2.5.3 FUNCTIONAL ANALYSIS For DEGs, the Cytoscape 32 suite was used to construct a protein-protein interaction network (PPI) using the STRING application 33 , which also allows for enrichment analysis by Gene Ontology (GO) categories (Biological Processes and Molecular Functions) and KEGG pathways. For miRNAs, the top up-regulated and down-regulated (|log2FC| >2) were divided into two lists and used separately for target retrieval. First, the most represented form, in terms of the sequences of each miRNA, was used as a reference to search for the corresponding human miRNA on the mirWalk3.0 database 34 . Then, predicted and validated target genes were identified, also specifying the site of action of the miRNA: 3'UTR, 5'UTR or CDS (coding region). To limit the extent of the analysis while keeping it informative, target genes common to the majority (at least 20%) of the input miRNAs were selected (keeping divided the targets of up-regulated and down-regulated miRNAs) and crossed with one-to-one human orthologues of DEGs (retrieved through the BioMart tool of Ensembl database, https://www.ensembl.org/biomart/martview/305776dd82c7aeb43d22c2e342dbfee5 ). In this way, we were able to identify DEGs that were also targets of DE miRNAs, selecting the miRNA-DEGs couples with opposite expression differences (up-regulated miRNAs – down-regulated target gene; down-regulated miRNAs – up-regulated target gene). At last, DEGs from these selected couples were used for a KEGG pathway enrichment analysis. The two mainly interesting enriched KEGG pathways are highlighted basing on KEGG graph. 3 RESULTS 3.1 HISTOPATHOLOGICAL CHARACTERIZATION In all 12 cases, histopathological diagnosis confirmed a spindle cell neoplasm, characterized by mild to moderate anysocytosis and anysokariosis within the cellular neoplastic population. Nine out of 12 cases (75%) where characterized by the presence of rete pegs, whereas only in 3/12 cases (25%), a “picket fence” arrangement of neoplastic fibroblasts was highlighted in the subepithelial areas (Supplementary figure S1 ). Three cases did not show picket fence arrangement nor rete pegs (one of these three cases was diffusely ulcerated, not allowing the evaluation of this histological feature). One case was characterized by the presence of “crown cells”, which are frequently observed in perivascular tumors. 3.2 DNA EXTRACTION AND PCR ASSAY FOR BPV DETECTION Eighteen (18) out of 19 samples were positive for BPV1 DNA, while no positivity was found for BPV2 and BPV13 DNA. Of the enrolled animals, only T1 and T5 had peritumor margins that were not infiltrated by neoplastic tissue; both were positive for BPV1. Of the ten cases used as controls, 9/10 (90%) were negative for BPV1, BPV2 and BPV13; one sample was positive for BPV1 (Table 3 ). Table 3 Real Time qPCR results: data are expressed as Mean ± Standard Deviation (SD). Sample B2M (Mean ± SD) BPV1 (Mean ± SD) BPV2 (Mean ± SD) BPV13 (Mean ± SD) T1 20.95 ± 0.02 19.17 ± 0.79 40.00 40.00 T2 23.67 ± 0.80 19.20 ± 0.80 40.00 40.00 T3 24.37 ± 0.21 18.88 ± 0.18 40.00 40.00 T4 22.86 ± 1.05 19.99 ± 0.14 40.00 40.00 T5 22.89 ± 0.91 18.30 ± 0.80 40.00 40.00 T6 24.48 ± 0.48 40.00 40.00 40.00 T7 27.58 ± 0.37 24.25 ± 0.04 40.00 40.00 T8 22.04 ± 0.85 15.51 ± 0.38 40.00 40.00 T9 25.40 ± 0.01 19.08 ± 0.20 40.00 40.00 T10 25.62 ± 0.41 18.27 ± 0.27 40.00 40.00 T11 24.27 ± 0.63 22.78 ± 0.33 40.00 40.00 T12 25.84 ± 0.52 18.18 ± 0.03 40.00 40.00 T13 25.68 ± 0.25 24.00 ± 0.47 40.00 40.00 T14 23.70 ± 0.13 17.30 ± 0.31 40.00 40.00 T15 25.41 ± 0.22 20.00 ± 0.42 40.00 40.00 M1 24.49 ± 0.04 28.09 ± 0.02 40.00 40.00 M5 24.05 ± 0.06 26.44 ± 0.08 40.00 40.00 X1 24.26 ± 0.37 27.97 ± 0.20 40.00 40.00 X2 23.53 ± 0.11 40.00 40.00 40.00 X3 24.55 ± 0.09 40.00 40.00 40.00 X4 24.95 ± 0.14 40.00 40.00 40.00 X5 25.06 ± 0.08 40.00 40.00 40.00 X6 24.23 ± 0.09 40.00 40.00 40.00 X7 23.93 ± 0.26 40.00 40.00 40.00 X8 24.15 ± 0.10 40.00 40.00 40.00 X9 24.89 ± 0.10 40.00 40.00 40.00 X10 24.72 ± 0.05 40.00 40.00 40.00 3.3 SEQUENCING RESULTS All samples were subjected to RNA and small RNA sequencing regardless of their viral DNA positivity/negativity. The experimental group assignment was then verified during the bioinformatics analysis of the sequencing data based on clustering resulting from the principal component analysis (PCA). Except for sample T12, which was excluded from the RNA-seq data due to library preparation failure, both data types revealed clear clustering of edge samples with the other control group samples, which were therefore considered as such. Moreover, the healthy tissue positive for BPV1 (X1) still clustered with the other healthy samples and was classified as a control, while the sarcoid negative for viral DNA (T6) exhibited a similar behavior to the other sarcoids and was thus retained in the tumor group. The sequencing of small RNAs produced an average of over 20 million reads per sample, which were first filtered out by eliminating those of poor quality and then aligned to the microRNA database (miRbase-22) to obtain the most in-depth information for this type of small RNA (Supplementary table S1 ). The 33% of cleaned reads were uniquely aligned to miRBase, and another 45% kept from the genome mapping. For mRNA sequencing, a large number of sequences were generated for each sample, averaging over 63 million, of which the vast majority (over 89%) were suitable for downstream analysis (uniquely mapped), following clean-up of poor-quality sequences (Supplementary table S2). The T12 sarcoid sample was subjected to two sequencing runs due to the poor quality of reads generated from the first run (hereafter referred to as T12_old). Unfortunately, the second sequencing (T12_new) also showed issues: although the total number of reads was comparable to that of the other samples, a high number of sequences (over 4 million) failed to align to the reference genome. Exploratory analysis of the count distribution (Supplementary figure S2A) further confirmed the poor quality of the T12 sample in both sequencing attempts, leading to its exclusion from downstream analyses. Moreover, a discrepancy between the sarcoid sample T3 and the other samples belonging to the same experimental group was revealed (only in RNA-Seq). Despite samples belonging to the same experimental group (sarcoid group (T) and control group (X) and margins (M)) clustered within each other, the dendrogram (Supplementary figure S2B) shows T3 closer to the control group samples. Form both the heatmap analysis of correlations (Supplementary figure S2C) and the principal components analysis (PCA) carried out on the first 500 features (Supplementary figure S2D), intra-group similarities are highlighted, confirming greater homogeneity between the control samples with respect to the sarcoids and the sample T3 as an outlier, differing markedly from all the other samples. We also excluded this sample from the downstream analysis only in RNA-seq. By repeating the exploratory analysis after the exclusion of the above-mentioned samples, it is possible to observe a clear division between the two experimental groups, confirming the excellent quality of the selected dataset (Fig. 1 A and B). The same result was obtained for small RNA data (Fig. 1 C and D). In general, both dendrograms highlight the proximity of the two margins (M1 and M5) with control healthy skins (X), while the heatmaps show a high intra-group correlation, which was lower for sarcoid samples, highlighting inhomogeneity with the formation of several clusters. These results were confirmed by the principal component analysis carried out on the first 200 and 1000 features (Fig. 2 A and C) for small RNA and mRNA, respectively. The two groups are perfectly divided with respect to the first component explaining over 50% of the variance, with control samples being closer. 3.4 DIFFERENTIAL EXPRESSION ANALYSIS The differential expression analysis revealed 145 differentially expressed miRNAs (log2FoldChange >|1| and an adjusted p-value < 0.05), with 56 down-regulated and 89 up-regulated miRNAs in sarcoids compared to controls (Fig. 2 B). For mRNA, over 6K DEGs emerged, 3620 down-regulated and 2415 up-regulated (Fig. 2 D) in sarcoids vs controls. Supplementary tables S3 and S4 report the complete lists of DE miRNAs and DEGs, while in Table 4 are reported the top 20 up-regulated and down-regulated genes in sarcoids compared to controls. Table 4 Top 20 up-regulated and down-regulated genes in sarcoids compared to controls. Gene name log2FoldChange p-value FDR Up-regulated genes in sarcoids ETV1 3.70 1.78E-68 3.97E-64 HSP90B1 2.14 2.63E-50 2.94E-46 RCN1 3.16 2.74E-49 2.04E-45 GPX8 2.99 5.06E-49 2.83E-45 PPIB 1.76 2.43E-48 1.08E-44 PDIA6 2.13 5.70E-47 2.12E-43 PRDX4 1.77 1.73E-45 5.54E-42 TUSC3 2.14 4.10E-45 1.02E-41 OLFML3 2.70 1.52E-44 3.39E-41 LUM 4.20 3.16E-44 6.43E-41 B3GNT9 2.01 6.02E-44 1.12E-40 ZMAT3 3.18 3.42E-43 5.87E-40 ERP29 1.59 1.24E-41 1.85E-38 OSTC 2.10 1.20E-40 1.67E-37 GPR141 2.17 1.30E-40 1.71E-37 PDIA4 1.85 4.46E-40 5.54E-37 GPX7 3.20 4.80E-40 5.64E-37 SEC61A1 1.46 1.79E-39 2.00E-36 TXNDC5 2.04 4.97E-38 5.05E-35 KDELR2 1.26 1.34E-37 1.30E-34 Down-regulated genes in sarcoids ITPRID2 -1.56 4.00E-45 1.02E-41 SGSM1 -2.40 1.56E-42 2.50E-39 PPP1R12B -2.07 2.24E-36 1.79E-33 FBXL22 -2.74 8.40E-36 5.87E-33 PIEZO2 -2.20 1.37E-35 9.31E-33 FOXC1 -2.54 2.92E-32 1.28E-29 PELI2 -2.01 4.92E-32 2.11E-29 HID1 -2.17 6.13E-31 2.36E-28 ISM1 -3.96 8.10E-31 3.07E-28 TANC1 -1.03 1.36E-29 4.05E-27 CLDN5 -2.94 5.90E-29 1.65E-26 ID4 -2.98 7.97E-29 2.20E-26 RYR2 -3.87 3.14E-28 8.25E-26 TMEM164 -1.65 3.25E-28 8.45E-26 PPT2 -1.03 6.43E-28 1.63E-25 PRR36 -2.52 1.68E-27 3.96E-25 HES4 -2.25 1.98E-27 4.60E-25 EFHD1 -2.67 4.68E-27 1.08E-24 AGO4 -1.43 5.22E-27 1.19E-24 RORC -3.70 8.88E-27 2.00E-24 3.5 FUNCTIONAL ANALYSIS FOR DIFFERENTIALLY EXPRESSED miRNA To retrieve up and down regulated miRNAs targets for the downstream functional analysis, a selection was made according to the criteria described in Fig. 3 . In brief, top up and down regulated miRNAs (log2FC >|2|, Table 7 ) were chosen as input for miRWalk software to retrieve the putative (validated and not validated) targets which were then selected for the number of miRNA hits. Table 7 Enriched “Biological Processes” for genes found to be down-regulated in the sarcoid group compared to the control group Go term category FDR Background genes Down regulated genes Multicellular organism development 3.87E-14 4228 449 Regulation of biological quality 7.77E-12 3271 357 Ion transport 5.04E-09 1244 166 Cell adhesion 1.65E-07 771 114 Regulation of ion transport 2.05E-07 528 88 Neurogenesis 2.08E-07 1428 176 Cell-cell signaling 7.30E-07 753 106 Anatomical structure morphogenesis 7.90E-07 1829 204 Modulation of chemical synaptic transmission 7.90E-07 355 64 Regulation of membrane potential 1.96E-06 349 65 Cell development 9.65E-06 1392 165 Skin development 1.62E-05 220 47 Regulation of multicellular organismal process 1.72E-05 2566 264 Tissue development 5.23E-05 1375 160 Chemical homeostasis 1.27E-04 880 113 Regulation of system process 1.36E-04 390 64 Lipid metabolic process 1.63E-04 982 122 Behavior 3.62E-04 440 68 Multicellular organismal water homeostasis 1.10E-03 37 15 Blood circulation 1.30E-03 246 42 Trans-synaptic signaling 1.50E-03 341 52 Regulation of cell development 1.60E-03 811 97 Regulation of transmembrane transporter activity 2.20E-03 190 35 Regulation of synaptic plasticity 2.40E-03 157 31 Localization 2.40E-03 4640 403 Cell junction organization 2.52E-03 399 61 Positive regulation of synaptic transmission 2.70E-03 110 25 Animal organ morphogenesis 2.83E-03 780 98 Cellular component morphogenesis 2.83E-03 500 71 Regulation of cell communication 2.90E-03 2755 257 Multicellular organismal homeostasis 2.90E-03 247 41 Regulation of hormone levels 3.10E-03 343 51 Axon ensheathment 3.90E-03 98 23 Cell-cell adhesion via plasma-membrane adhesion molecules 4.46E-03 189 37 Regulation of nervous system process 4.57E-03 103 26 Regulation of localization 4.70E-03 2250 215 Positive regulation of developmental process 4.70E-03 1126 122 Olefinic compound metabolic process 4.70E-03 57 17 Divalent inorganic cation homeostasis 4.90E-03 372 53 Adenylate cyclase-modulating G protein-coupled receptor signaling pathway 5.40E-03 193 34 Glial cell differentiation 5.68E-03 135 30 Central nervous system development 5.97E-03 733 92 Cell surface receptor signaling pathway 6.45E-03 1682 175 Positive regulation of ion transport 6.60E-03 178 32 Multicellular organismal signaling 6.70E-03 88 21 Tissue morphogenesis 7.10E-03 461 61 Epithelial cell differentiation 7.98E-03 458 65 Unsaturated fatty acid metabolic process 7.98E-03 72 21 Regulation of body fluid levels 8.04E-03 240 42 3.6 FUNCTIONAL ANALYSIS FOR DEGs A functional analysis for enriched vocabularies of Gene Ontology (GO), “biological processes” and “molecular function”, was performed for DEGs using STRINGdb software in the Cytoscape suite. Enriched biological processes found for up-regulated genes in the sarcoid group compared to the control group are reported in Table 5 , while Table 6 shows those for down-regulated genes. Results for molecular function are reported in supplementary tables S5 and S6. Table 5 Top DE miRNAs used to retrieve human orthologues to be submitted on miRWalk for target identification. miRNA log2FoldChange p-value FDR Up-regulated miRNAs in sarcoids eca-mir-337 7.07 7.96E-14 7.71E-13 eca-mir-503 7.03 2.37E-35 1.75E-33 eca-mir-424 6.27 2.66E-59 9.77E-57 eca-mir-542 6.09 2.20E-54 2.70E-52 eca-mir-450a 6.01 1.62E-56 2.98E-54 eca-mir-431 5.65 4.94E-22 2.60E-20 eca-mir-450b 5.61 1.64E-34 1.01E-32 eca-mir-541 5.57 2.66E-13 2.39E-12 eca-mir-134 5.40 1.97E-17 3.29E-16 eca-mir-487a 5.12 2.23E-12 1.91E-11 eca-mir-376b 5.11 6.12E-21 1.96E-19 eca-mir-1185 5.09 1.52E-20 4.30E-19 eca-mir-376a 5.01 3.18E-19 7.31E-18 eca-mir-493b 4.89 5.28E-20 1.39E-18 eca-mir-381 4.73 3.79E-17 6.06E-16 eca-mir-485 4.59 1.16E-10 8.41E-10 eca-mir-432 4.55 2.32E-18 4.28E-17 eca-mir-376c 4.49 2.15E-19 5.27E-18 eca-mir-655 4.49 1.44E-08 8.41E-08 eca-mir-409 4.44 6.39E-21 1.96E-19 eca-mir-1193 4.43 2.46E-08 1.39E-07 eca-mir-127 4.37 7.40E-16 8.51E-15 eca-mir-299 4.23 1.60E-18 3.10E-17 eca-mir-487b 4.20 8.78E-17 1.24E-15 eca-mir-410 4.20 2.28E-09 1.52E-08 eca-mir-370 4.19 1.21E-12 1.06E-11 eca-mir-329a 4.15 1.26E-10 8.92E-10 eca-mir-379 4.14 7.43E-17 1.09E-15 eca-mir-369 4.07 4.12E-18 7.22E-17 eca-mir-411 4.02 9.63E-17 1.31E-15 eca-mir-495 3.99 9.33E-09 5.63E-08 eca-mir-377 3.99 6.35E-08 3.20E-07 eca-mir-889 3.98 2.15E-21 9.91E-20 eca-mir-494 3.84 2.31E-16 2.74E-15 eca-mir-154a 3.81 3.74E-11 2.75E-10 eca-mir-323 3.78 3.77E-19 8.16E-18 eca-mir-382 3.71 1.31E-13 1.23E-12 eca-mir-136 3.65 4.10E-15 4.44E-14 eca-mir-758 3.62 9.65E-12 7.40E-11 eca-mir-539 3.60 6.81E-12 5.45E-11 eca-mir-543 3.57 1.03E-11 7.71E-11 eca-mir-544-2 3.50 1.06E-07 5.21E-07 eca-mir-433 3.41 5.66E-12 4.73E-11 eca-mir-380 3.36 5.51E-05 1.81E-04 eca-mir-412 3.16 5.93E-12 4.85E-11 eca-mir-656 3.07 2.85E-09 1.84E-08 eca-mir-496 2.83 5.89E-09 3.67E-08 eca-mir-92b 2.57 4.50E-06 1.72E-05 eca-mir-1197 2.53 2.34E-04 6.74E-04 eca-mir-615 2.21 9.59E-04 2.34E-03 eca-mir-218-1 2.12 5.78E-05 1.87E-04 eca-mir-216b 2.00 2.35E-06 9.61E-06 Down-regulated miRNAs in sarcoids eca-mir-486 -2.11 9.02E-04 2.24E-03 eca-mir-488 -2.13 5.33E-03 1.10E-02 eca-mir-95 -2.22 2.43E-06 9.81E-06 eca-mir-205 -2.27 3.86E-03 8.35E-03 eca-mir-216a -2.27 1.87E-03 4.31E-03 eca-mir-1248 -2.28 3.23E-08 1.72E-07 eca-mir-451 -2.38 2.63E-03 5.86E-03 eca-mir-184 -2.38 9.18E-06 3.38E-05 eca-mir-708 -2.44 2.46E-07 1.17E-06 eca-mir-141 -2.49 6.32E-05 2.00E-04 eca-mir-135b -2.53 2.47E-06 9.87E-06 eca-mir-96 -2.71 4.90E-06 1.86E-05 eca-mir-200c -2.71 3.21E-05 1.10E-04 eca-mir-200b -2.74 3.10E-04 8.58E-04 eca-mir-182 -2.80 6.93E-07 3.07E-06 eca-mir-135a-2 -2.93 4.27E-08 2.21E-07 eca-mir-1291a -2.98 1.40E-04 4.14E-04 eca-mir-183 -3.01 2.22E-08 1.27E-07 eca-mir-204b-2 -3.12 6.35E-21 1.96E-19 eca-mir-375 -3.49 3.85E-05 1.30E-04 eca-mir-489 -3.49 7.62E-07 3.34E-06 eca-mir-653 -4.09 4.13E-05 1.38E-04 Table 6 Enriched “Biological Processes” for genes found to be up-regulated in the sarcoid group compared to the control group Go term category FDR Background genes UP-regulated genes Collagen fibril organization 2.40E-14 38 14 Regulation of multicellular organismal process 8.22E-11 2566 58 Anatomical structure morphogenesis 1.30E-10 1829 47 Response to organic substance 1.90E-08 2152 47 Regulation of response to stimulus 1.81E-06 3258 57 Tube development 2.97E-06 700 25 Locomotion 3.00E-06 1001 28 Collagen metabolic process 1.25E-05 49 9 Regulation of protein metabolic process 2.02E-05 2442 46 Regulation of cell migration 2.80E-05 710 22 Cell adhesion 6.37E-05 771 24 Skeletal system development 1.02E-04 382 17 Vasculature development 1.02E-04 434 18 Reg. of transmembrane receptor protein serine/threonine kinase signaling path 1.02E-04 198 13 Regulation of cell population proliferation 3.79E-04 1232 29 Chondrocyte development 4.21E-04 36 7 Inflammatory response 5.75E-04 386 16 Negative regulation of developmental process 7.93E-04 768 22 Response to wounding 8.10E-04 265 12 Collagen biosynthetic process 1.20E-03 8 4 Regulation of response to external stimulus 1.74E-03 672 20 Reproductive structure development 1.74E-03 316 14 Ossification 1.80E-03 191 10 Enzyme linked receptor protein signaling pathway 1.84E-03 486 17 Regulation of angiogenesis 1.91E-03 223 12 Cellular component organization 2.20E-03 4673 59 Extracellular matrix assembly 2.60E-03 27 5 Negative regulation of wound healing 3.00E-03 52 6 Cellular response to endogenous stimulus 3.30E-03 854 20 Regulation of cell adhesion 3.70E-03 570 16 Response to external stimulus 3.84E-03 1843 34 Tissue morphogenesis 4.03E-03 461 16 Negative regulation of signal transduction 4.70E-03 960 21 Positive regulation of cell differentiation 5.00E-03 809 19 Protein maturation 5.00E-03 175 9 Positive regulation of nervous system development 5.20E-03 458 14 Positive regulation of protein phosphorylation 5.53E-03 809 21 Response to stress 5.53E-03 2744 43 Regulation of ERK1 and ERK2 cascade 5.60E-03 228 10 Regulation of intracellular signal transduction 5.60E-03 1310 25 Transmembrane receptor protein serine/threonine kinase signaling pathway 6.30E-03 137 8 Epithelial cell proliferation 6.92E-03 62 7 Regulation of body fluid levels 8.10E-03 240 10 Negative regulation of reproductive process 9.20E-03 39 5 Nervous system development 9.90E-03 1921 31 3.7 FUNCTIONAL ANALYSIS FOR DIFFERENTIALLY EXPRESSED (miRNA- DEG COUPLES) ACCORDING TO THE EXPRESSION LEVELS The putative targets of at least the 20% of input miRNAs were crossed with human orthologues corresponding to our DEGs, identifying miRNA-DEG couples (with opposite expression trends in sarcoids vs controls) used for the functional analysis (Supplementary tables S7 and S8). The strategy used to identify differentially expressed genes (DEGs) that are also targets of differentially expressed (DE) miRNAs was to select miRNA–mRNA pairs with opposite expression trends (i.e., up-regulated miRNAs paired with down-regulated target genes, and vice versa). These were used for a KEGG pathway enrichment analysis. The statistically significant enriched KEGG pathways for the selected DEGs are reported in Table 8 . Table 8 Enriched KEGG pathways for selected DEGs from the miRNA-DEG couples according to expression changes in sarcoids. Functional grup Term p-value FDR Associated Genes Found One carbon pool by folate One carbon pool by folate 3.25E-03 1.92E-02 ALDH1L1, ALDH1L2, MTHFD1L, MTHFD2, SHMT2 ABC transporters ABC transporters 2.22E-03 1.39E-02 ABCA4, ABCA5, ABCA9, ABCC11, ABCC6, ABCC8, ABCG1, CFTR Protein digestion and absorption Protein digestion and absorption 6.41E-06 1.04E-04 ATP1A1, ATP1A4, COL11A1, COL12A1, COL14A1, COL16A1, COL19A1, COL22A1, COL4A1, COL4A3, COL4A5, COL4A6, COL5A2, COL6A3, COL6A6, COL8A2, PRCP, SLC8A3 Mineral absorption Mineral absorption 4.01E-03 2.17E-02 ATP1A1, ATP1A4, ATP2B2, ATP7B, CYBRD1, SLC5A1, SLC8A3, STEAP2, TF Cholesterol metabolism Cholesterol metabolism 4.96E-03 2.55E-02 ANGPTL4, CYP27A1, LRP1, LRP2, LRPAP1, PLTP, SCARB1, SORT1 Pathways in cancer Pathways in cancer 1.05E-07 2.94E-06 ADCY5, ADCY6, ADCY7, ALK, APC2, AR, AXIN2, CALML4, CAMK2A, CAMK2B, CDH1, CDK6, COL4A1, COL4A3, COL4A5, COL4A6, CSF3R, CTNNA3, DAPK2, DCC, E2F3, EGF, ERBB2, FGF1, FGFR4, FLT4, FN1, FZD3, FZD6, GLI1, IFNAR1, IFNAR2, IGF2, IL23R, ITGA2, ITGB1, JAG1, KIT, LAMA2, LAMB1, LAMB3, LAMC1, MECOM, MET, NOTCH1, PAX8, PLCB4, PTCH1, RASGRP1, RASGRP2, RUNX1T1, TGFB3, TGFBR1, TRAF5, WNT5A, WNT9B, ZBTB16 Proteoglycans in cancer Proteoglycans in cancer 9.00E-05 9.75E-04 ANK2, ANK3, CAMK2A, CAMK2B, CD63, CTSL, ERBB2, ERBB3, ERBB4, FN1, FZD3, FZD6, GPC3, HCLS1, IGF2, ITGA2, ITGB1, KDR, MET, PLCE1, PTCH1, TIAM1, VAV1, WNT5A, WNT9B Rap1 signaling pathway Rap1 signaling pathway 8.37E-04 6.80E-03 ADCY5, ADCY6, ADCY7, CALML4, CDH1, EGF, FGF1, FGFR4, FLT4, GRIN2B, ITGB1, KDR, KIT, MAGI1, MAGI2, MET, PDGFC, PLCB4, PLCE1, RAPGEF4, RASGRP2, TIAM1, VAV1 Calcium signaling pathway Calcium signaling pathway 4.41E-08 1.72E-06 ADCY7, ADRA1A, ASPH, ATP2B2, CACNA1D, CACNA1E, CACNA1H, CALML4, CAMK2A, CAMK2B, CAMK4, EGF, ERBB2, ERBB3, ERBB4, FGF1, FGFR4, FLT4, GNAL, GRIN2B, ITPKB, KDR, MET, MST1R, NOS1, NTRK2, NTRK3, ORAI2, P2RX5, PDGFC, PLCB4, PLCE1, RYR2, RYR3, SLC8A3, TACR1 Axon guidance Axon guidance 7.44E-11 7.25E-09 ABLIM1, ABLIM2, CAMK2A, CAMK2B, DCC, EPHA1, EPHA3, EPHA8, EPHB1, FES, FZD3, GDF7, ITGB1, L1CAM, MET, NTN4, NTNG1, PAK5, PLXNA4, PLXNB1, PLXNB3, PLXNC1, PTCH1, ROBO1, ROBO2, SEMA4A, SEMA4G, SEMA5A, SLIT2, SLIT3, SRGAP1, SRGAP3, TRPC4, WNT5A Hippo signaling pathway Hippo signaling pathway 1.76E-03 1.27E-02 AJUBA, APC2, AXIN2, CDH1, CTNNA3, DLG4, FGF1, FRMD1, FZD3, FZD6, GDF7, LLGL2, NKD1, RASSF6, TGFB3, TGFBR1, WNT5A, WNT9B Cell adhesion molecules Cell adhesion molecules 8.67E-06 1.21E-04 CADM3, CD86, CD99, CD99L2, CDH1, CDH3, CDH4, ITGB1, L1CAM, MPZL1, NECTIN1, NEGR1, NFASC, NLGN1, NRCAM, NRXN1, NRXN3, NTNG1, PTPRD, PTPRF, PTPRS, SIGLEC1, VCAN Adherens junction Adherens junction 3.52E-03 2.02E-02 BAIAP2, CDH1, CTNNA3, ERBB2, LMO7, MET, NECTIN1, NECTIN4, PTPRB, PTPRF, SORBS1, TGFBR1 Regulation of actin cytoskeleton Regulation of actin cytoskeleton 3.83E-03 2.14E-02 ABI2, APC2, BAIAP2, C6, DIAPH3, EGF, FGF1, FGFR4, FN1, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, MYH10, MYH11, PAK5, PDGFC, PIP5K1B, SCIN, SPATA13, TIAM1, VAV1 PPAR signaling pathway PPAR signaling pathway 1.84E-03 1.28E-02 ACOX1, ACSL1, ACSL5, ANGPTL4, CPT1B, CYP27A1, HMGCS1, PLTP, PPARA, SCD, SORBS1 MAPK signaling pathway MAPK signaling pathway 1.80E-04 1.76E-03 CACNA1D, CACNA1E, CACNA1H, CACNA2D4, CACNB2, CACNB4, CACNG5, DUSP6, EGF, ERBB2, ERBB3, ERBB4, FGF1, FGFR4, FLT4, IGF2, KDR, KIT, MAP3K9, MAP4K2, MAP4K4, MAPT, MECOM, MET, NTRK2, PDGFC, PLA2G4F, PTPRR, RASGRP1, RASGRP2, TGFB3, TGFBR1 Dilated cardiomyopathy Cardiac muscle contraction 5.96E-03 2.83E-02 ASPH, ATP1A1, ATP1A4, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, MYH6, RYR2, SLC8A3 Adrenergic signaling in cardiomyocytes 1.62E-06 3.15E-05 ADCY5, ADCY6, ADCY7, ADRA1A, ATP1A1, ATP1A4, ATP2B2, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, CALML4, CAMK2A, CAMK2B, CREB3L2, MYH6, PLCB4, RAPGEF4, RYR2, SCN4B, SCN5A, SCN7A, SLC8A3 Oxytocin signaling pathway 5.23E-03 2.61E-02 ADCY5, ADCY6, ADCY7, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, CALML4, CAMK2A, CAMK2B, CAMK4, GUCY1A2, PLA2G4F, PLCB4, RYR2, RYR3 Hypertrophic cardiomyopathy 8.39E-07 1.82E-05 CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, DMD, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, LAMA2, MYH6, RYR2, SGCD, SLC8A3, TGFB3, TTN Arrhythmogenic right ventricular cardiomyopathy 2.01E-06 3.57E-05 CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, CTNNA3, DMD, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, LAMA2, RYR2, SGCD, SLC8A3 Dilated cardiomyopathy 1.94E-08 1.26E-06 ADCY5, ADCY6, ADCY7, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, DMD, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, LAMA2, MYH6, RYR2, SGCD, SLC8A3, TGFB3, TTN ECM-receptor interaction PI3K-Akt signaling pathway 3.82E-07 9.32E-06 CDK6, COL4A1, COL4A3, COL4A5, COL4A6, COL6A3, COL6A6, CREB3L2, CSF3R, EGF, ERBB2, ERBB3, ERBB4, FGF1, FGFR4, FLT4, FN1, IFNAR1, IFNAR2, IGF2, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, KDR, KIT, LAMA2, LAMB1, LAMB3, LAMB4, LAMC1, MAGI1, MAGI2, MET, NTRK2, PDGFC, PRLR, RELN, THBS4, TNR, TNXB, VWF Focal adhesion 2.18E-08 1.06E-06 COL4A1, COL4A3, COL4A5, COL4A6, COL6A3, COL6A6, EGF, EMP2, ERBB2, FLT4, FN1, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, KDR, LAMA2, LAMB1, LAMB3, LAMB4, LAMC1, MET, PAK5, PDGFC, PIP5K1B, RELN, THBS4, TNR, TNXB, VAV1, VWF ECM-receptor interaction 2.33E-12 4.55E-10 AGRN, COL4A1, COL4A3, COL4A5, COL4A6, COL6A3, COL6A6, FN1, FRAS1, FREM2, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, LAMA2, LAMB1, LAMB3, LAMB4, LAMC1, RELN, THBS4, TNR, TNXB, VWF AGE-RAGE signaling pathway in diabetic complications 6.35E-03 2.95E-02 COL4A1, COL4A3, COL4A5, COL4A6, CYBB, FN1, NOX1, NOX4, PLCB4, PLCE1, TGFB3, TGFBR1 Amoebiasis 9.12E-04 7.11E-03 COL4A1, COL4A3, COL4A5, COL4A6, FN1, GNAL, IL1R2, LAMA2, LAMB1, LAMB3, LAMB4, LAMC1, PLCB4, TGFB3 Human papillomavirus infection 6.85E-06 1.03E-04 APC2, ATP6V0A4, AXIN2, CDK6, COL4A1, COL4A3, COL4A5, COL4A6, COL6A3, COL6A6, CREB3L2, EGF, FN1, FZD3, FZD6, IFNAR1, IFNAR2, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, JAG1, LAMA2, LAMB1, LAMB3, LAMB4, LAMC1, LLGL2, MAGI1, NOTCH1, RELN, THBS4, TNR, TNXB, VWF, WNT5A, WNT9B Small cell lung cancer 8.67E-05 9.95E-04 CDK6, COL4A1, COL4A3, COL4A5, COL4A6, E2F3, FN1, ITGA2, ITGB1, LAMA2, LAMB1, LAMB3, LAMB4, LAMC1, TRAF5 Insulin secretion cGMP-PKG signaling pathway 1.40E-03 1.05E-02 ADCY5, ADCY6, ADCY7, ADRA1A, ATP1A1, ATP1A4, ATP2B2, CACNA1D, CALML4, CREB3L2, GTF2IRD1, GUCY1A2, IRS4, KCNMA1, KCNU1, MYH6, OPRD1, PLCB4, SLC8A3 cAMP signaling pathway 2.40E-05 3.12E-04 ACOX1, ADCY5, ADCY6, ADCY7, ATP1A1, ATP1A4, ATP2B2, CACNA1D, CALML4, CAMK2A, CAMK2B, CAMK4, CFTR, CREB3L2, GLI1, GLP1R, GRIA1, GRIN2B, PDE10A, PDE4C, PDE4D, PLCE1, PPARA, PTCH1, RAPGEF4, RYR2, TIAM1, VAV1 Cardiac muscle contraction 5.96E-03 2.83E-02 ASPH, ATP1A1, ATP1A4, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, MYH6, RYR2, SLC8A3 Adrenergic signaling in cardiomyocytes 1.62E-06 3.15E-05 ADCY5, ADCY6, ADCY7, ADRA1A, ATP1A1, ATP1A4, ATP2B2, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, CALML4, CAMK2A, CAMK2B, CREB3L2, MYH6, PLCB4, RAPGEF4, RYR2, SCN4B, SCN5A, SCN7A, SLC8A3 Circadian entrainment 1.61E-04 1.65E-03 ADCY5, ADCY6, ADCY7, CACNA1D, CACNA1H, CALML4, CAMK2A, CAMK2B, GRIA1, GRIN2B, GUCY1A2, NOS1, PLCB4, RYR2, RYR3 Glutamatergic synapse 4.75E-03 2.50E-02 ADCY5, ADCY6, ADCY7, CACNA1D, DLG4, GRIA1, GRIK3, GRIN2B, PLA2G4F, PLCB4, SHANK1, SHANK2, SLC1A2, SLC1A3 Insulin secretion 7.85E-08 2.55E-06 ABCC8, ADCY5, ADCY6, ADCY7, ATP1A1, ATP1A4, CACNA1D, CAMK2A, CAMK2B, CREB3L2, GLP1R, KCNMA1, KCNN3, KCNU1, PCLO, PLCB4, RAPGEF4, RIMS2, RYR2 Melanogenesis 8.25E-04 7.00E-03 ADCY5, ADCY6, ADCY7, CALML4, CAMK2A, CAMK2B, CREB3L2, DCT, FZD3, FZD6, KIT, PLCB4, WNT5A, WNT9B Thyroid hormone synthesis 5.89E-03 2.87E-02 ADCY5, ADCY6, ADCY7, ATP1A1, ATP1A4, CREB3L2, DUOX2, LRP2, PAX8, PLCB4 Oxytocin signaling pathway 5.23E-03 2.61E-02 ADCY5, ADCY6, ADCY7, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, CALML4, CAMK2A, CAMK2B, CAMK4, GUCY1A2, PLA2G4F, PLCB4, RYR2, RYR3 Aldosterone synthesis and secretion 4.98E-05 6.07E-04 ADCY5, ADCY6, ADCY7, ATP1A1, ATP1A4, ATP2B2, CACNA1D, CACNA1H, CALML4, CAMK2A, CAMK2B, CAMK4, CREB3L2, KCNK3, PLCB4, SCARB1 Cortisol synthesis and secretion 2.04E-03 1.37E-02 ADCY5, ADCY6, ADCY7, CACNA1D, CACNA1H, CREB3L2, KCNA4, KCNK3, PLCB4, SCARB1 Cushing syndrome 1.86E-04 1.73E-03 ADCY5, ADCY6, ADCY7, APC2, AXIN2, CACNA1D, CACNA1H, CAMK2A, CAMK2B, CDK6, CREB3L2, E2F3, FZD3, FZD6, KCNA4, KCNK3, PLCB4, SCARB1, WNT5A, WNT9B Salivary secretion 3.51E-04 3.12E-03 ADCY5, ADCY6, ADCY7, ADRA1A, ATP1A1, ATP1A4, ATP2B2, CALML4, GUCY1A2, KCNMA1, LPO, NOS1, PLCB4, RYR3 Gastric acid secretion 2.05E-03 1.33E-02 ADCY5, ADCY6, ADCY7, ATP1A1, ATP1A4, CALML4, CAMK2A, CAMK2B, CFTR, KCNK10, PLCB4 Bile secretion 7.07E-03 3.21E-02 ADCY5, ADCY6, ADCY7, AQP4, ATP1A1, ATP1A4, CFTR, SCARB1, SLC4A5, SLC5A1, SLCO1A2 Amphetamine addiction 3.20E-03 1.95E-02 ADCY5, CACNA1D, CALML4, CAMK2A, CAMK2B, CAMK4, CREB3L2, DDC, GRIA1, GRIN2B Dilated cardiomyopathy 1.94E-08 1.26E-06 ADCY5, ADCY6, ADCY7, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, DMD, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, LAMA2, MYH6, RYR2, SGCD, SLC8A3, TGFB3, TTN Figures 4 and 5 illustrate two of the mainly interesting enriched KEGG pathways basing on KEGG graphs. 4 DISCUSSION In this study, a deep RNA and miRNA seq analysis was conducted on 12 sarcoid tissue samples, two paired skin samples from histologically healthy margins, and 10 healthy skin samples harvested from healthy horses. We set-up a Real-Time PCR protocol for the detection of BPV 1, 2, and 13 with a high degree of sensitivity and specificity which allowed us to evaluate the positivity of samples to the most common type of bovine papillomavirus (BPV1). As expected, BPV infection was demonstrated in most of the examined cases. In particular, the only viral type present was BPV1, with invariable negativity for BPV2 and BPV13, which have been reported in Brazil, Austria, New Zealand and also other areas of Italy 35 . Regarding the RNA sequencing results, we aimed to explore the deep characterization of the sarcoid cell transcriptome by integrating data from both small-RNA and mRNA sequencing. To this end, we performed a differential analysis of both transcriptomes, as detailed in the Materials and Methods section. Subsequently, we performed an analysis incorporating differentially expressed miRNAs, their predicted target genes, and differentially expressed mRNAs, creating miRNA-DEG pairs (Supplementary tables S7 and S8). This approach enabled a functional analysis of the modulated pathways across the entire expressed transcriptome. The identification of up-regulated and down-regulated genes, along with their regulatory non-coding elements, highlighted pathways closely associated with tumor progression, as summarized in our enriched KEGG pathways for selected DEGs from the miRNA-DEG couples analysis (Table 8 ). The differential expression analysis of miRNAs in tumor tissues compared to healthy skin revealed many well-known oncomiRs, both up- and down-regulated. Nine out of the 20 most up-regulated miRNA and 7 out of the 20 most down-regulated miRNA were also identified by Pawlina and collaborators 36 in the only study, to our knowledge, on miRNA dysregulation in equine sarcoids 36 . For instance, miR-450a, which results up-regulated in both studies, is similarly up-regulated in human oral squamous cell carcinoma, where it is likely involved in promoting cell motility, a process essential for cancer invasion 37 . Hence, also in sarcoids, despite their embryological differences with squamous cell carcinomas, miR-450a might act as an onco-miRNA, with its upregulation contributing to local invasiveness 38 . Another shared result is a significant downregulation of miR-200b and miR-141, both part of the miR-200 miRNA family. A similar result has been reported in some human virus-related cancers, such as Epstein-Barr virus-induced gastric carcinoma and HPV-induced cervical cancer 39 , 40 . Generally, the downregulation of miR-200 family members is associated with increased cell invasiveness and, overall, reduced survival. We also identified uniquely modulated miRNAs not previously reported in sarcoids. Some of these miRNAs can have dual roles in tumor progression, invasion, and malignancy—functions that may vary depending on the cellular and neoplastic context. MiR-337, miR-503, miR-542, and miR-431-5p have all been shown to act both as tumor suppressors or promoters in different neoplasms. More in detail, miR-337-3p - the most highly expressed miRNA in our study- has been previously reported as overexpressed in human liposarcomas, a tumor that shares a mesenchymal origin, similarly to equine sarcoids 41 . On the other hand, miR-337-3p was downregulated both in tumor and serum of patients with osteosarcoma, with levels reverting to normal after excisional surgery 42 . It is thought to inhibit migration and invasion in breast cancer while promoting apoptosis 43 . Additionally, miR-337 targets PIK3CA and PIK3CB , thereby reducing PI3K/AKT signaling activation 44 . The second and third most up-regulated miRNAs in our study, respectively miR-503 and miR-427, have also been identified as tumor suppressors in several malignancies, but they have also been reported to exhibit oncogenic functions in specific cancer types, suggesting a tissue- or disease-specific role 45 . Notably, miR-424 and miR-503, both members of the miR-16 family, are clustered on the same chromosome in humans and horses. These miRNAs are often dysregulated in cancers and play crucial yet paradoxical roles in tumor initiation and progression by targeting different genes and molecular pathways. Furthermore, these miRNAs are often co-expressed in cancer cells, indicating a potential coordinated function as a cluster 45 . Another interesting observation was the strong upregulation of miR-542. A similar result has been observed in human osteosarcoma, both in cell cultures and neoplastic tissue, where it is recognized as a cellular proliferation promoter, and as a circulating biomarker. A higher miR-542-3p concentration has been indeed associated with advanced tumor stage and short overall survival 46 , 47 . MiR-542 regulates multiple cancer-related behaviors like cell apoptosis, metastasis, proliferation, cell cycle, and glycolysis, through the targeting of at least 18 genes and key signaling pathways such as Wnt/β-catenin, ERK1/2, JAK2, and PI3K/AKT 48 .Additional future studies may help to evaluate the prognostic relevance of this circulating miRNA, especially in relation to recurrence in equine sarcoids. Similarly, miR-431-5p, which was also up-regulated in our study, has been implicated in various cancers, regulating processes such as proliferation, apoptosis, autophagy, migration, invasion, and angiogenesis 49 . Taken together, these results might reflect the unique nature of sarcoids, which are locally aggressive but non-metastatic and also support the hypothesis that a tumor-specific profile of mi-RNA expression, with different roles in tumorigenesis, tumor biology and phenotyping should be better described. The analyses of differential mRNA expression between sarcoid and healthy skin also revealed substantial differences in both gene expression and active pathways. Genes involved in phosphorylation ( PPP1R12B, PELI2 ), cell adhesion ( CLDN5 ), virus-host interactions ( HSP90B1 , PDIA6, PPIB, AGO4 ), cell differentiation ( FOXC1, ID4, ETV1, RORC ), actin-cytoskeleton organization with lamellipodium assembly ( PPP1R12B, PIEZO2, TANC1 ), and cellular movement ( HSP90B1, PPP1R12B, PIEZO2, TANC1, RYR2 ) were significantly altered (Tables 4 ). In particular HSP90B1 acts as a molecular chaperone, facilitating the folding of viral proteins and modulating host immune responses, PDIA6 is involved in protein folding interacting with viral proteins, PPIB has been implicated in viral replication processes, AGO4 contribute to antiviral defense. Of extreme interest, since we are dealing with a mesenchymal neoplasm, is also the modulation of SMAD2 and HIF1AN , suggesting a complex regulatory system in the tumor microenvironment. Notably, enriched KEGG pathways for selected DEGs from the miRNA-DEG couples analysis included critical processes such as “Pathways in Cancer” (Fig. 4 ) and the “Hippo signaling pathway” (Fig. 5 ). A plethora of key regulators of tissue invasion and metastasis modulated in our sarcoids samples are outlined in cancer-related pathways (Fig. 4 ). Of particular interest in papillomavirus-related cancers in horses is the modulation of the alternative Wnt signaling pathway 9 , which seems involved also in sarcoids. Indeed, WNT5a and WNT9b genes were up-regulated likely due to the activation of the Wnt/β-catenin-independent pathway. A crucial protein in this alternative Wnt signaling pathway is YAP/TAZ, recently identified as part of the Wnt-YAP/TAZ signal transduction mechanism 50 . This complex can promote the expression of Notch receptors and ligands, further integrating multiple signaling pathways. Interestingly, Wnt5a/b ligands serve as both upstream activators and downstream targets of the YAP/TAZ-TEAD complex, suggesting a potential positive feedback loop that stimulates the other particularly modulated and interesting pathway in our sarcoids, the Hippo signaling pathway 51 . The Hippo signaling pathway, detailed in Fig. 5 , is an evolutionarily conserved signaling cascade initially identified in Drosophila melanogaster for its role in restricting tissue overgrowth 52 . In mammals, it regulates cell proliferation, differentiation, apoptosis, organ size control, and tissue homeostasis 50 . Hippo signaling pathway dysregulation is linked to several diseases, including cancer, as it interferes with upstream regulatory mechanisms that are normally controlled by a complex interplay of intrinsic and extrinsic signals—such as mechanical stress, cell–cell contact, polarity, energy levels, cellular stress, and various diffusible hormonal factors, many of which signal through G protein–coupled receptors 53 . The Hippo signaling pathway exerts its effects through its core effectors, YAP/TAZ. When the pathway is inactive, unphosphorylated YAP/TAZ accumulate in the nucleus, where they interact with TEAD transcription factors to drive gene expression. Conversely, when the Hippo signaling pathway is active, YAP/TAZ are phosphorylated by LATS1/2 leading to their sequestration in the cytoplasm. In our study, several down-regulated miRNAs (miR-200c-3p, miR-204-5p, miR-216a-5p, miR-375-3p, miR-486-3p, miR-653-5p) target and modulate DLG4 gene, that encodes signaling protein known to suppress Hippo signaling pathway activation by inhibiting YAP/TAZ phosphorylation 50 . Moreover, our results indicate that LATS1/2 activity may have been enhanced through miRNA-mediated repression of AJUBA gene, a negative regulator of Hippo signaling pathway, and its upstream inhibitor, RASSF6 (Fig. 5 ). Given that Hippo signaling pathway components interact with other key signaling pathways such as Wnt, AMPK, TGF-β, and Notch, its role in cancer progression is highly complex 50 . Furthermore, our study revealed that FZD3 and FZD6 genes were down-regulated due to the upregulation of several miRNAs on this pathway (Fig. 5 ). Frizzled receptors (FZDs) regulate both the canonical β-catenin pathway and various non-canonical β-catenin-independent pathways. Aberrant FZD signaling is implicated in numerous diseases, including cancer, although the role of non-canonical Wnt pathways can play either tumor-promoting or tumor-suppressing roles. Interestingly, we observed both Hippo activation and repression signals, suggesting a dynamic balance between tumor proliferation, infiltration, and malignancy—reflecting the unique non-metastatic behavior of sarcoid tumors. The cGAS-STING pathway, which triggers the innate immune system in presence of pathogens or of damaged cells through NF-κB and IRF3, leading to the production of type I interferons (IFN-I) and pro-inflammatory cytokines 54 , can deeply influence the tumor microenvironment (TME). In our study, we observed a significant modulation of the Hippo pathway, which aligns with literature findings that link cGAS-STING signaling to PV infection. A functional connection between cGAS-STING and the Hippo pathway has been previously observed in PV-induced tumors, where PV exploits the E6/E7 oncoproteins to deactivate Hippo signaling 55 . This promotes YAP/TAZ activity, which, in turn, suppresses cGAS-STING, reducing interferon production and supporting immune evasion, thereby blocking the innate immune response and promoting tumor transformation 56 . Although the Hippo signaling pathway has been extensively studied in vitro as a potential therapeutic target, its in vivo roles remain less understood. In our study we demonstrated for the first time in horses, the downregulation of cGAS/STING signaling in sarcoids; this is an important finding that showed as equine BPV1-induced sarcoids have an immune evasion mechanism similar to high risk human PV 57 , 58 . The Hippo signaling pathway plays a vital role in fibroblast activation, stem cell maintenance, ECM remodeling, immune infiltration, and angiogenesis. Through these processes, it modulates the secretion of molecules that impact tumor development via interactions with TME components. Increasing evidence suggests that the Hippo signaling pathway can exert both pro- and anti-tumor effects, depending on the tumor type and context 50 . In this type of cancer, the pathway appears to be uniquely activated, as it is linked to immune evasion, fibroblast activation, and increased cell mobility, while still being associated with low metastatic potential. Conclusion In this study, for the first time to the authors' knowledge, both coding and non-coding transcript-regulated metabolic pathways were simultaneously investigated in equine sarcoids and overall, underscores the complex regulatory interplay between miRNAs, mRNAs, and key oncogenic pathways in sarcoid tumors, providing novel insights into their molecular pathogenesis. This comprehensive and effective global analysis enabled the identification of highly regulated pathways, providing deeper insight into the pathogenesis of a tumor with a peculiar behavior in terms of invasiveness and low metastatic potential, and paving the way for the identification of novel therapeutic targets. Declarations Competing interests The authors declare no competing interests. Funding This work was supported by RC IZS PLV 12/19 and RC IZS PLV 03/23 funded by the Italian Ministry of Health. Author Contribution Conceptualization: E.R, K.C. Methodology: S.M., S.C., K.C., I.P., R.G., M.P., E.R. Formal analysis: S.M., S.C., I.P Investigation: S.M., I.P., F.D.A, L.D.P, F.F., R.R., R.G., M.P., Writing – original draft preparation: S.M., K.C., I.P. Writing – review and editing: E.R, L.M., B.P, A.G. Supervision: K.C., E.R. Project administration: E.R. Funding acquisition: E.R. Data Availability The raw sequencing datasets generated during and analysed during the current study are available in the Sequence Read Archive (SRA) repository 59, under the BioProject ID: PRJNA1273441 (BioSample accessions from SAMN48946045 to SAMN48946068 for small RNA-seq and from SAMN48946069 to SAMN48946091 for mRNA-seq). References Ogłuszka, M., Starzyński, R. R., Pierzchała, M., Otrocka-Domagała, I. & Raś, A. Equine Sarcoids—Causes, Molecular Changes, and Clinicopathologic Features: A Review. Vet. Pathol. 58 , 472–482 (2021). Trewby, H. et al. Analysis of the long control region of bovine papillomavirus type 1 associated with sarcoids in equine hosts indicates multiple cross-species transmission events and phylogeographical structure. J. Gen. Virol. 95 , 2748–2756 (2014). Goodrich, L., Gerber, H., Marti, E. & Antczak, D. F. Equine Sarcoids. Vet. Clin. North Am. Equine Pract. 14 , 607–623 (1998). Hainisch, E. K. et al. 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Cappelli","email":"","orcid":"","institution":"University of Perugia","correspondingAuthor":false,"prefix":"","firstName":"K.","middleName":"","lastName":"Cappelli","suffix":""}],"badges":[],"createdAt":"2025-06-25 14:53:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6975941/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6975941/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88001475,"identity":"543c3bc3-4ed3-4a23-8feb-4d9e81192704","added_by":"auto","created_at":"2025-07-31 10:23:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":32934,"visible":true,"origin":"","legend":"\u003cp\u003eCluster analysis: dendrograms of sample clusters for small RNA (A) and mRNA (C), showing the clustering of margins (M1 and M5) with controls (X); heatmap of the correlations between the samples for small RNA (B) and mRNA (D), indicating a correlation coefficient close to 1 between controls and differences within sarcoids\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6975941/v1/7bc018c1192b9dd771e7c94a.png"},{"id":87999926,"identity":"6fce7bb0-314d-4248-ad34-dccb7361b98c","added_by":"auto","created_at":"2025-07-31 10:15:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":37903,"visible":true,"origin":"","legend":"\u003cp\u003eAssessing the difference between sarcoids and controls. Principal component analysis performed on the top 200 and 1000 genes for small RNA (A) and mRNA (C), respectively. Volcano plots representing statistically significant (log2FoldChange \u0026gt; |1| and an adjusted p-value \u0026lt; 0.05) DE miRNA (B) and DEGs (D) (turquoise dots); red boxes enclose down-regulated features, while green boxes the up-regulated ones.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6975941/v1/65969b087e584e482d69e647.png"},{"id":88001476,"identity":"ff6314fc-02b6-4486-87ed-70972666b2f8","added_by":"auto","created_at":"2025-07-31 10:23:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":31968,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of the strategy used to identify differentially expressed genes (DEGs) that are also targets of differentially expressed (DE) miRNAs, and that were selected for functional analysis. DEGs shown in blue represent miRNA–mRNA pairs with opposite expression trends (i.e., up-regulated miRNAs paired with down-regulated target genes, and vice versa). These were used for a KEGG pathway enrichment analysis. The red circle includes human orthologues of genes found to be down-regulated in sarcoids compared to controls, while the green circle includes up-regulated orthologues. The grey circles enclose the putative targets (retrieved from miRWalk) of at least 20% of DE miRNAs. Rectangles indicate DE miRNAs: green for up-regulated and red for down-regulated miRNAs.\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6975941/v1/99c68483fc8b36ae69406ebd.png"},{"id":87999924,"identity":"b68a05b1-fe0b-42e7-bb30-5b4b1bea22aa","added_by":"auto","created_at":"2025-07-31 10:15:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":180971,"visible":true,"origin":"","legend":"\u003cp\u003e“Pathways in cancer” illustration highlighting DEGs (red for down-regulated, green for up-regulated and yellow when isoforms with an opposite trend of expression are present) and reporting related DE miRNAs (with an opposite expression modulation with respect to the mRNA). Figure modified starting from Kanehisa Laboratories KEGG map. Regular map notation is available at \u003ca href=\"https://www.kegg.jp/kegg/document/help_pathway.html\"\u003ehttps://www.kegg.jp/kegg/document/help_pathway.html\u003c/a\u003e.\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6975941/v1/233eca805484f531b64c21fa.png"},{"id":87999935,"identity":"ff560f23-b9dc-40fa-9380-c6dc32079ee3","added_by":"auto","created_at":"2025-07-31 10:15:47","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":141947,"visible":true,"origin":"","legend":"\u003cp\u003e“Hippo signaling pathway” illustration highlighting DEGs (red for down-regulated and green for up-regulated) and reporting related DE miRNAs (with an opposite expression modulation with respect to the mRNA). Figure modified starting from Kanehisa Laboratories KEGG map. Regular map notation is available at \u003ca href=\"https://www.kegg.jp/kegg/document/help_pathway.html\"\u003ehttps://www.kegg.jp/kegg/document/help_pathway.html\u003c/a\u003e.\u003c/p\u003e","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6975941/v1/f6b58d316df9a7d110e31536.png"},{"id":88856196,"identity":"14404909-9cf8-4448-ac6f-65383fd8e479","added_by":"auto","created_at":"2025-08-12 06:39:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2742036,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6975941/v1/4f860933-aeae-4c01-a8b8-d709133747f7.pdf"},{"id":87999928,"identity":"2a94aeec-3724-4d54-9329-e05104533336","added_by":"auto","created_at":"2025-07-31 10:15:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":4813266,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6975941/v1/646784ed1a2db5198c10a4c8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Deciphering the transcription regulation of bovine papillomavirus (BPV)-associated equine sarcoids through OMIC integrated approach","fulltext":[{"header":"1 INTRODUCTION","content":"\u003cp\u003eEquine sarcoids are locally aggressive, non-metastatic skin tumors, affecting up to 12% of horses worldwide. They are the most common neoplastic disease in horses and other equids such as donkeys, mules, or zebras, representing up to 90% of all equine cutaneous tumors\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Bovine papillomavirus (BPV) type 1, 2, and 13 (BPV1, BPV2, BPV13) play a central role in the etiology of equine sarcoid and the disease is considered the result of a non-productive infection \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The viral type and the epidemiological proportion between types involved depends on the country in which the horse live \u003csup\u003e\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. The main way of transmission is by direct contact, contaminated fomites, and shared living environments, but also vertical transmission has been suggested in equids by evidence of BPV gene expression in the blood and semen of healthy horses, as well as in the placenta. Moreover, it has been shown that co-stabling of sarcoid-affected and healthy donkeys can result in the transmission of BPV1, with insects suspected as possible transmission vectors \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Papillomaviruses (PVs) belong to the large family of animal and human Papillomaviridae that normally infect epithelial cells, mostly causing benign proliferative lesions known as warts. On the other hand, some types of PVs can induce benign and malignant tumors in both humans and animals, including BPV types 1 and 2. These viral types can also infect fibroblasts and induce fibroepithelial tumours, like benign fibropapillomas in cattle \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Among the most common and specie-specific equine PVs is EcPV2, which is related to equine genital squamous cell carcinomas \u003csup\u003e\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Although PVs are normally strictly species-specific and are characterized by a pronounced tropism for cutaneous and mucosal keratinocytes, equine and feline sarcoids are a well known case of natural cross-species PV infection \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Although biology, morphology, and epidemiology of equine sarcoids are known, the pathogenic events leading to the development of tumors and the mechanisms used by BPV to induce the lesions are poorly understood. Tumorigenesis is a complex process that involves numerous molecules and pathways; in equine sarcoids BPV1 and BPV2 may be responsible for the abnormal fibroblast proliferation and the alterations in the metabolism of extracellular matrix (ECM) and its main components (e.g. collagen)\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSarcoids are typically diagnosed through a combination of clinical presentation and histopathological evaluation. Polymerase chain reaction (PCR) from superficial swabs, skin scrapings, or the tumour mass can be helpful for the identification of BPV DNA that is thought to be diagnostic for equine sarcoid, although BPV DNA can only be demonstrated in 70% of equine sarcoids \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Recently, hypotheses have emerged suggesting also a potential role of ovine papillomavirus in the development of equine sarcoids \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe equine sarcoid remains a clinical challenge since the high risk of treatment failure and local invasion is a major constraint to therapy. The likelihood of recurrence (in the same origin site or growth of a new sarcoid) is highest wheb surgical therapeutic methods are applied and it seems to be correlated with the presence of BPV DNA on the surgical margins \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Natural immunity against BPV1 and 2 in equids appears to be poor and sarcoid-affected horses show no measurable anti-BPV1 L1 antibodies. This circumstance may help to explain why sarcoids are usually present as persistent lesions; BPV may escape from immune surveillance because of its paramount localization in cutaneous cells, yet also because of its capacity to inhibit MHC class I-mediated antigen presentation via its major oncoprotein, E5 \u003csup\u003e20\u003c/sup\u003e. Given the current challenges in establishing effective therapies, the identification of the key cellular drivers of sarcoid growth paves the way for the future development of brand-new targeted therapeutic approaches \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn this study, deep RNA and miRNA sequencing were applied to better understand host-pathogen interactions and the tumor microenvironment in equine sarcoid, taking advantage of Next Generation Sequencing (NGS) technologies. RNA-seq indeed is a gold standard technology for investigating transcriptomic patterns detecting and large number of genes and regulatory regions in specific physiological and pathological conditions quantifying the expression profile.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"2 METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 SAMPLE COLLECTION\u003c/h2\u003e\u003cp\u003eHorses and donkeys enrolled for this study (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were examined at the Didactic Veterinary Hospital (OVUD) of the Veterinary Medicine\u0026rsquo;s Department of the University of Perugia. Written informed consent was obtained from the animal owners prior to their inclusion in the study and sample collection.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRecruited horses and donkeys. F: female; M: male; G: gelding.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCases\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLab ID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpieces/Race\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLesions\u0026rsquo; site\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eEquus Asinus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAdult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePeriocular\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eEquus Caballus, Thoroughbred\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAbdomen Udder\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eEquus Caballus, Italian saddle\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePeriocular\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eEquus Caballus, Italian saddle\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePeriocular\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eEquus Caballus, Arab\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eParamammary\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eEquus Caballus, Akal teeke\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAbdomen\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eEquus Caballus, Belgian horse\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eScrotum and ear\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eEquus Caballus, Pony\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRight rear hock\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eEquus Asinus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePeriocular\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eEquus Caballus, Pony\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAbdomen\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eEquus Caballus, Italian saddle\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAbdomen inner thigh\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eEquus Caballus, Italian saddle\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eInner thigh and chest\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAnimals with concomitant diseases or poor clinical conditions were excluded. The lesions were surgically removed with a 3 cm lateral margin. The excised lesion and margin were subjected to histopathological evaluation and polymerase chain reaction (PCR) to assess the presence of viral DNA. After sampling for histology and and margin assessment, part of the residual tissues of tumor samples and tumor-free margin samples (potential paired controls from the same animal) were stored at -80\u0026deg;.\u003c/p\u003e\u003cp\u003eThe inclusion parameters were:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eclinical and confirmed histopathological diagnosis of sarcoid,\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003elesions\u0026thinsp;\u0026gt;\u0026thinsp;2 cm in diameter.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eAfter histological confirmation of diagnosis and assessment of margin status, samples meeting the selection criteria were used for NGS, together with ten cutaneous tissues collected from heathy donors at slaughterhouse that tested negative for viral DNA (control group).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 HISTOPATHOLOGICAL CHARACTERIZATION\u003c/h2\u003e\u003cp\u003eSurgical samples were submitted to routine processing for histopathology, with evaluation of surgical margins. Margins were sampled using a combined evaluation using cross-sectioning for smaller samples (\u0026lt;\u0026thinsp;4 cm as major diameter) and a combination of cross and \u0026ldquo;bread loaf\u0026rdquo; sectioning for larger samples\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe histopathological diagnosis of equine sarcoid, with variable degree of diagnostic certainty, was based on the presence of one or more of the following features:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e- spindle cell neoplastic proliferation;\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e- presence of epidermal hyperplasia with deep rete ridges (rete pegs) interdigitating with the dermal proliferation;\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e- \u0026ldquo;picket fence\u0026rdquo; arrangement of neoplastic cells in the subepithelial area (rows of fibroblasts with a perpendicular orientation of the epidermal basement membrane).\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 DNA EXTRACTION AND PCR ASSAY FOR BPV DETECTION\u003c/h2\u003e\u003cp\u003eDNA was extracted starting from frozen and grinded samples using RecoverAll Total Nucleic Acid Isolation Kit (Termo Ficher Scientific, Waltham, Massachusetts, United States) and following manufacturer's instructions. The presence/absence of BPV DNA was assessed for all the samples (sarcoid lesions, margins and controls) by applying a Taqman assay on the L1 genomic region of the 3 BPVs (BPV1, BPV2 and BPV13) using primers and probes (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) designed through Primer3 web-tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://primer3.ut.ee\u003c/span\u003e\u003cspan address=\"https://primer3.ut.ee\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePrimer sequences and probes used for the detection of BPV1, -2, -13 DNA in Real Time PCR (BPV1, BPV2, BPV13). Beta-2-Microglobulin (B2M) was used as the reference gene.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTarget\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimer pairs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProbe\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAmplicon size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAccession number\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBPV1-L1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eFor\u003c/em\u003e-5\u0026rsquo;-CAGGACTGTTCACAACCCAAG-3\u0026rsquo;\u003c/p\u003e\u003cp\u003e\u003cem\u003eRev\u003c/em\u003e-5\u0026rsquo;-CCCAGTTACAGTACCTCCAAGA-3\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eFAM\u003c/em\u003e-TGCAGGTGTCCAGAGGGCAG-\u003cem\u003eTAMRA\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eJX678969\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBPV2-L1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eFor\u003c/em\u003e-5\u0026rsquo;-ACAGCCCGTCCATGTGTTA-3\u0026rsquo;\u003c/p\u003e\u003cp\u003e\u003cem\u003eRev\u003c/em\u003e-5\u0026rsquo;-TCAGCAGCACCAAACCCTAT-3\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eFAM\u003c/em\u003e-AGAAAATGGTGCGTGTCCTCCT-\u003cem\u003eTAMRA\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eM20219\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBPV13-L1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eFor\u003c/em\u003e-5\u0026rsquo;-GCACCCCACTTTTAATGCCT-3\u0026rsquo;\u003c/p\u003e\u003cp\u003e\u003cem\u003eRev\u003c/em\u003e-5\u0026rsquo;-TCCTGTTTGCTTCCTGTCATC-3\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eFAM\u003c/em\u003e-AGGAAAGTGACCAGCCAAACAACA-\u003cem\u003eTAMRA\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNC_030795\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eB2M\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eFor\u003c/em\u003e-5\u0026rsquo;-CTGATGTTCTCCAGGTGTTCC-3\u0026rsquo;\u003c/p\u003e\u003cp\u003e\u003cem\u003eRev\u003c/em\u003e-5\u0026rsquo;-TCAATCTCAGGCGGATGGAA-3\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eFAM\u003c/em\u003e-ACTCACGTCACCCAGCAGAGA-\u003cem\u003eTAMRA\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNM_001082502.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFor Real Time qPCR detection, 5 \u0026micro;l of template were added to the reaction including 1X CustomProbe, 2x qPCR Master Mix (Canvax Reagents SL, Valladolid, Spain), 200 nM of probe and100 nM of each primer combination. The thermal protocol used for amplification in a CFX96 TM Real- Time (Bio-Rad, California, USA) was: 95\u0026deg;C for 10 min, followed by 40 cycles of 95\u0026deg;C for 15 seconds, 60\u0026deg;C for 60 seconds.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 RNA EXTRACTION AND SEQUENCING OF SMALL RNA AND mRNA\u003c/h2\u003e\u003cp\u003eThe 12 samples of tumour tissue, 2 histologically healthy portions of the T1 and T5 sarcoid margin and the 10 samples of healthy skin were subjected to total RNA extraction with a commercial kit (miRNeasy Kit, Qiagen, Hilden, Germania), following the manufacturer's instructions. The extracted RNA was qualitatively and quantitatively evaluated by spectrophotometric measurement with NanoDrop 2000 (Thermo Fisher Scientific, Waltham, MA, USA) and by microfluidic electrophoresis (Bioanalyzer 2100 Agilent Technologies). RNA samples were used to produce two different sequencing libraries, one for mRNA using the TruSeq RNA Library Prep Kit and the other for small RNA through the TruSeq\u0026reg; Small RNA Library Prep kit, following the manufacturer's instructions. For small RNA sequencing, unique molecular identifiers (UMIs) were introduced during the library preparation allowing error correction and increased accuracy during sequencing. Libraries were sequenced on a NextSeq500 instrument producing 150 bp pair-end fragments.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 BIOINFORMATIC ANALYSIS\u003c/h2\u003e\u003cp\u003eRaw sequences were first checked for quality with FastQC (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.bioinformatics.babraham.ac.uk/projects/fastqc/\u003c/span\u003e\u003cspan address=\"http://www.bioinformatics.babraham.ac.uk/projects/fastqc/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and trimmed from low-quality/adapter sequences using Trim Galore 0.6.6 software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.babraham.ac.uk/projects/trim_galore/\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Trimmed reads were used for the alignment procedure and downstream analysis, which differed for mRNAs and small RNAs.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.5.1 FROM READS TO GENES\u003c/h2\u003e\u003cp\u003eFor smallRNAs libraries were prepared with UMIs, to accurately account for PCR duplicates and enhance quantification precision. The \u003cem\u003eumitools\u003c/em\u003e package was used to process these data \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Following UMI extraction the reads were used to perform a two-step alignment: first, on miRBase 22 hairpin (horse) \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, to recover micro RNA (miRNA) information; second, the unmapped reads from the previous step, on EquCab3.0 \u003csup\u003e25\u003c/sup\u003e genome, to recover additional information on miRNAs and on the other small RNA typologies. The Bowtie2 algorithm with very sensitive local flag \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e was used as aligner \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. After alignment steps, reads were deduplicated based on UMIs. Uniquely mapped reads were used for downstream analysis: for miRNAs from miRBase, a homemade script was applied for counting, while reads aligned to the genome were counted through FeatureCounts \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e using the horse annotation (Equus_caballus - Ensembl genes 109) and obtaining four count matrices (miRNAs, protein-coding RNAs, lncRNAs and all the other as miscellaneous RNAs). Last, the two miRNA matrices (miRBase and genome) were merged in order to build a unique count matrix for miRNAs.\u003c/p\u003e\u003cp\u003eFor mRNAs, the STAR algorithm \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e was used to align reads to the reference genome EquCab3.0. The data generated from the alignment were then used to identify the genes expressed in our samples using the horse annotation (Equus_caballus - Ensembl genes 109), while their expression level was assessed by counting reads uniquely aligned with the FeatureCounts software.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.5.2 RETRIVING GENE EXPRESSION DIFFERENCES BETWEEN SARCOIDS AND CONTROLS\u003c/h2\u003e\u003cp\u003eThe count matrices were imported into R environment and a preliminary exploratory analysis was carried out applying the hierarchical clustering \u003cem\u003ehclust\u003c/em\u003e function of the \u0026ldquo;stats\u0026rdquo; package (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://rdocumentation.org/packages/stats/versions/3.6.2\u003c/span\u003e\u003cspan address=\"https://rdocumentation.org/packages/stats/versions/3.6.2\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and performing a principal component analysis (PCA) through the \u003cem\u003eplotPCA\u003c/em\u003e function in DESeq2 package \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. The latter was also used to identify differentially expressed miRNAs and genes (DEGs) between samples derived from sarcoids (T) and those derived from margin(M)/healthy(X) tissues (considered as control group). The R package ggplot2 \u003csup\u003e31\u003c/sup\u003e was used to produce volcano plots. Genes/miRNAs were considered differentially expressed (T vs M/X) if they had a |log2FoldChange| (|log2FC|)\u0026thinsp;\u0026gt;\u0026thinsp;1 and an adjusted p-value (FDR)\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and were then subjected to the functional analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.5.3 FUNCTIONAL ANALYSIS\u003c/h2\u003e\u003cp\u003eFor DEGs, the Cytoscape \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e suite was used to construct a protein-protein interaction network (PPI) using the STRING application \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, which also allows for enrichment analysis by Gene Ontology (GO) categories (Biological Processes and Molecular Functions) and KEGG pathways.\u003c/p\u003e\u003cp\u003eFor miRNAs, the top up-regulated and down-regulated (|log2FC| \u0026gt;2) were divided into two lists and used separately for target retrieval. First, the most represented form, in terms of the sequences of each miRNA, was used as a reference to search for the corresponding human miRNA on the mirWalk3.0 database \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Then, predicted and validated target genes were identified, also specifying the site of action of the miRNA: 3'UTR, 5'UTR or CDS (coding region). To limit the extent of the analysis while keeping it informative, target genes common to the majority (at least 20%) of the input miRNAs were selected (keeping divided the targets of up-regulated and down-regulated miRNAs) and crossed with one-to-one human orthologues of DEGs (retrieved through the BioMart tool of Ensembl database, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ensembl.org/biomart/martview/305776dd82c7aeb43d22c2e342dbfee5\u003c/span\u003e\u003cspan address=\"https://www.ensembl.org/biomart/martview/305776dd82c7aeb43d22c2e342dbfee5\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). In this way, we were able to identify DEGs that were also targets of DE miRNAs, selecting the miRNA-DEGs couples with opposite expression differences (up-regulated miRNAs \u0026ndash; down-regulated target gene; down-regulated miRNAs \u0026ndash; up-regulated target gene). At last, DEGs from these selected couples were used for a KEGG pathway enrichment analysis.\u003c/p\u003e\u003cp\u003eThe two mainly interesting enriched KEGG pathways are highlighted basing on KEGG graph.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"3 RESULTS","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.1 HISTOPATHOLOGICAL CHARACTERIZATION\u003c/h2\u003e\u003cp\u003eIn all 12 cases, histopathological diagnosis confirmed a spindle cell neoplasm, characterized by mild to moderate anysocytosis and anysokariosis within the cellular neoplastic population.\u003c/p\u003e\u003cp\u003eNine out of 12 cases (75%) where characterized by the presence of rete pegs, whereas only in 3/12 cases (25%), a \u0026ldquo;picket fence\u0026rdquo; arrangement of neoplastic fibroblasts was highlighted in the subepithelial areas (Supplementary figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Three cases did not show picket fence arrangement nor rete pegs (one of these three cases was diffusely ulcerated, not allowing the evaluation of this histological feature). One case was characterized by the presence of \u0026ldquo;crown cells\u0026rdquo;, which are frequently observed in perivascular tumors.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.2 DNA EXTRACTION AND PCR ASSAY FOR BPV DETECTION\u003c/h2\u003e\u003cp\u003eEighteen (18) out of 19 samples were positive for BPV1 DNA, while no positivity was found for BPV2 and BPV13 DNA. Of the enrolled animals, only T1 and T5 had peritumor margins that were not infiltrated by neoplastic tissue; both were positive for BPV1. Of the ten cases used as controls, 9/10 (90%) were negative for BPV1, BPV2 and BPV13; one sample was positive for BPV1 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eReal Time qPCR results: data are expressed as Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;Standard Deviation (SD).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB2M (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBPV1 (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBPV2 (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eBPV13 (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e20.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e23.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e24.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e22.86\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e22.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e24.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e27.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e22.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e25.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e25.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e24.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e25.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e25.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e23.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e25.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e24.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e24.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e24.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e23.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e24.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e24.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e25.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e24.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e23.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e24.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e24.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e24.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.3 SEQUENCING RESULTS\u003c/h2\u003e\u003cp\u003eAll samples were subjected to RNA and small RNA sequencing regardless of their viral DNA positivity/negativity. The experimental group assignment was then verified during the bioinformatics analysis of the sequencing data based on clustering resulting from the principal component analysis (PCA). Except for sample T12, which was excluded from the RNA-seq data due to library preparation failure, both data types revealed clear clustering of edge samples with the other control group samples, which were therefore considered as such. Moreover, the healthy tissue positive for BPV1 (X1) still clustered with the other healthy samples and was classified as a control, while the sarcoid negative for viral DNA (T6) exhibited a similar behavior to the other sarcoids and was thus retained in the tumor group. The sequencing of small RNAs produced an average of over 20\u0026nbsp;million reads per sample, which were first filtered out by eliminating those of poor quality and then aligned to the microRNA database (miRbase-22) to obtain the most in-depth information for this type of small RNA (Supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The 33% of cleaned reads were uniquely aligned to miRBase, and another 45% kept from the genome mapping. For mRNA sequencing, a large number of sequences were generated for each sample, averaging over 63\u0026nbsp;million, of which the vast majority (over 89%) were suitable for downstream analysis (uniquely mapped), following clean-up of poor-quality sequences (Supplementary table S2). The T12 sarcoid sample was subjected to two sequencing runs due to the poor quality of reads generated from the first run (hereafter referred to as T12_old). Unfortunately, the second sequencing (T12_new) also showed issues: although the total number of reads was comparable to that of the other samples, a high number of sequences (over 4\u0026nbsp;million) failed to align to the reference genome. Exploratory analysis of the count distribution (Supplementary figure S2A) further confirmed the poor quality of the T12 sample in both sequencing attempts, leading to its exclusion from downstream analyses. Moreover, a discrepancy between the sarcoid sample T3 and the other samples belonging to the same experimental group was revealed (only in RNA-Seq). Despite samples belonging to the same experimental group (sarcoid group (T) and control group (X) and margins (M)) clustered within each other, the dendrogram (Supplementary figure S2B) shows T3 closer to the control group samples. Form both the heatmap analysis of correlations (Supplementary figure S2C) and the principal components analysis (PCA) carried out on the first 500 features (Supplementary figure S2D), intra-group similarities are highlighted, confirming greater homogeneity between the control samples with respect to the sarcoids and the sample T3 as an outlier, differing markedly from all the other samples. We also excluded this sample from the downstream analysis only in RNA-seq.\u003c/p\u003e\u003cp\u003eBy repeating the exploratory analysis after the exclusion of the above-mentioned samples, it is possible to observe a clear division between the two experimental groups, confirming the excellent quality of the selected dataset (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and B). The same result was obtained for small RNA data (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and D). In general, both dendrograms highlight the proximity of the two margins (M1 and M5) with control healthy skins (X), while the heatmaps show a high intra-group correlation, which was lower for sarcoid samples, highlighting inhomogeneity with the formation of several clusters.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThese results were confirmed by the principal component analysis carried out on the first 200 and 1000 features (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and C) for small RNA and mRNA, respectively. The two groups are perfectly divided with respect to the first component explaining over 50% of the variance, with control samples being closer.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.4 DIFFERENTIAL EXPRESSION ANALYSIS\u003c/h2\u003e\u003cp\u003eThe differential expression analysis revealed 145 differentially expressed miRNAs (log2FoldChange \u0026gt;|1| and an adjusted p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with 56 down-regulated and 89 up-regulated miRNAs in sarcoids compared to controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). For mRNA, over 6K DEGs emerged, 3620 down-regulated and 2415 up-regulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD) in sarcoids vs controls.\u003c/p\u003e\u003cp\u003eSupplementary tables S3 and S4 report the complete lists of DE miRNAs and DEGs, while in Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e are reported the top 20 up-regulated and down-regulated genes in sarcoids compared to controls.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTop 20 up-regulated and down-regulated genes in sarcoids compared to controls.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGene name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003elog2FoldChange\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFDR\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"19\" rowspan=\"20\"\u003e\u003cp\u003e\u003cb\u003eUp-regulated genes in sarcoids\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eETV1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.78E-68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.97E-64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eHSP90B1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.63E-50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.94E-46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eRCN1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.74E-49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.04E-45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eGPX8\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.06E-49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.83E-45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePPIB\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.43E-48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.08E-44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePDIA6\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.70E-47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.12E-43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePRDX4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.73E-45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.54E-42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eTUSC3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.10E-45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.02E-41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eOLFML3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.52E-44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.39E-41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eLUM\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.16E-44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.43E-41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB3GNT9\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.02E-44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.12E-40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eZMAT3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.42E-43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.87E-40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eERP29\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.24E-41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.85E-38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eOSTC\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.20E-40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.67E-37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eGPR141\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.30E-40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.71E-37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePDIA4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.46E-40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.54E-37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eGPX7\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.80E-40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.64E-37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eSEC61A1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.79E-39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.00E-36\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eTXNDC5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.97E-38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.05E-35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eKDELR2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.34E-37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.30E-34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"19\" rowspan=\"20\"\u003e\u003cp\u003e\u003cb\u003eDown-regulated genes in sarcoids\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eITPRID2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.00E-45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.02E-41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eSGSM1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.56E-42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.50E-39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePPP1R12B\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.24E-36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.79E-33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eFBXL22\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.40E-36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.87E-33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePIEZO2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.37E-35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.31E-33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eFOXC1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.92E-32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.28E-29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePELI2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.92E-32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.11E-29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eHID1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.13E-31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.36E-28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eISM1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-3.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.10E-31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.07E-28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eTANC1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.36E-29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.05E-27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eCLDN5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.90E-29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.65E-26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eID4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.97E-29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.20E-26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eRYR2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-3.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.14E-28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.25E-26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eTMEM164\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-1.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.25E-28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.45E-26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePPT2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.43E-28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.63E-25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePRR36\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.68E-27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.96E-25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eHES4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.98E-27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.60E-25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eEFHD1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.68E-27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.08E-24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eAGO4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-1.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.22E-27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.19E-24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eRORC\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-3.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.88E-27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.00E-24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.5 FUNCTIONAL ANALYSIS FOR DIFFERENTIALLY EXPRESSED miRNA\u003c/h2\u003e\u003cp\u003eTo retrieve up and down regulated miRNAs targets for the downstream functional analysis, a selection was made according to the criteria described in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In brief, top up and down regulated miRNAs (log2FC \u0026gt;|2|, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e7\u003c/span\u003e) were chosen as input for miRWalk software to retrieve the putative (validated and not validated) targets which were then selected for the number of miRNA hits.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEnriched \u0026ldquo;Biological Processes\u0026rdquo; for genes found to be down-regulated in the sarcoid group compared to the control group\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGo term category\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFDR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBackground\u003c/p\u003e\u003cp\u003egenes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDown\u003c/p\u003e\u003cp\u003eregulated genes\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMulticellular organism development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.87E-14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4228\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e449\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of biological quality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.77E-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3271\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e357\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIon transport\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.04E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1244\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e166\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCell adhesion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.65E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e771\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e114\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of ion transport\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.05E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e528\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeurogenesis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.08E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1428\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e176\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCell-cell signaling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.30E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e753\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e106\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnatomical structure morphogenesis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.90E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1829\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e204\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModulation of chemical synaptic transmission\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.90E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e355\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of membrane potential\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.96E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e349\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCell development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.65E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1392\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e165\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSkin development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.62E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of multicellular organismal process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.72E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2566\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e264\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTissue development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.23E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e160\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChemical homeostasis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.27E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e880\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e113\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of system process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.36E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e390\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLipid metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.63E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e982\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e122\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBehavior\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.62E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e440\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMulticellular organismal water homeostasis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.10E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlood circulation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.30E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e246\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrans-synaptic signaling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.50E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e341\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of cell development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.60E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e811\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of transmembrane transporter activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.20E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e190\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of synaptic plasticity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.40E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e157\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocalization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.40E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4640\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e403\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCell junction organization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.52E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e399\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive regulation of synaptic transmission\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.70E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnimal organ morphogenesis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.83E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e780\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCellular component morphogenesis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.83E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of cell communication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.90E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2755\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e257\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMulticellular organismal homeostasis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.90E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of hormone levels\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.10E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAxon ensheathment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.90E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCell-cell adhesion via plasma-membrane adhesion molecules\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.46E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of nervous system process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.57E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e103\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of localization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.70E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e215\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive regulation of developmental process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.70E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e122\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOlefinic compound metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.70E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDivalent inorganic cation homeostasis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.90E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e372\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdenylate cyclase-modulating G protein-coupled receptor signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.40E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlial cell differentiation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.68E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCentral nervous system development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.97E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e733\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e92\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCell surface receptor signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.45E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1682\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e175\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive regulation of ion transport\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.60E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e178\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMulticellular organismal signaling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.70E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTissue morphogenesis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.10E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e461\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEpithelial cell differentiation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.98E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e458\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnsaturated fatty acid metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.98E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of body fluid levels\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.04E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e3.6 FUNCTIONAL ANALYSIS FOR \u003cem\u003eDEGs\u003c/em\u003e\u003c/h2\u003e\u003cp\u003eA functional analysis for enriched vocabularies of Gene Ontology (GO), \u0026ldquo;biological processes\u0026rdquo; and \u0026ldquo;molecular function\u0026rdquo;, was performed for DEGs using STRINGdb software in the Cytoscape suite. Enriched biological processes found for up-regulated genes in the sarcoid group compared to the control group are reported in Table \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e, while Table \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows those for down-regulated genes. Results for molecular function are reported in supplementary tables S5 and S6.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTop DE miRNAs used to retrieve human orthologues to be submitted on miRWalk for target identification.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003emiRNA\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003elog2FoldChange\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFDR\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"51\" rowspan=\"52\"\u003e\u003cp\u003eUp-regulated miRNAs in sarcoids\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-337\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.96E-14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.71E-13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-503\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.37E-35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.75E-33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-424\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.66E-59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.77E-57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-542\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.20E-54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.70E-52\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-450a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.62E-56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.98E-54\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-431\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.94E-22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.60E-20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-450b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.64E-34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.01E-32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.66E-13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.39E-12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.97E-17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.29E-16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-487a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.23E-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.91E-11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-376b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.12E-21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.96E-19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-1185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.52E-20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.30E-19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-376a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.18E-19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.31E-18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-493b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.28E-20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.39E-18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-381\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.79E-17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.06E-16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-485\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.16E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.41E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-432\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.32E-18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.28E-17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-376c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.15E-19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.27E-18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-655\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.44E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.41E-08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-409\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.39E-21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.96E-19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-1193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.46E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.39E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.40E-16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.51E-15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-299\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.60E-18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.10E-17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-487b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.78E-17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.24E-15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-410\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.28E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.52E-08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-370\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.21E-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.06E-11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-329a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.26E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.92E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-379\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.43E-17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.09E-15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-369\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.12E-18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.22E-17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-411\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.63E-17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.31E-15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-495\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.33E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.63E-08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-377\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.35E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.20E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.15E-21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.91E-20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-494\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.31E-16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.74E-15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-154a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.74E-11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.75E-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-323\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.77E-19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.16E-18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-382\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.31E-13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.23E-12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.10E-15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.44E-14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-758\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.65E-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.40E-11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-539\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.81E-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.45E-11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-543\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.03E-11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.71E-11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-544-2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.06E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.21E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-433\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.66E-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.73E-11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-380\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.51E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.81E-04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-412\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.93E-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.85E-11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-656\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.85E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.84E-08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-496\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.89E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.67E-08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-92b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.50E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.72E-05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-1197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.34E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.74E-04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-615\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.59E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.34E-03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-218-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.78E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.87E-04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-216b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.35E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.61E-06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"21\" rowspan=\"22\"\u003e\u003cp\u003eDown-regulated miRNAs in sarcoids\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-486\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.02E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.24E-03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-488\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.33E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.10E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.43E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.81E-06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-205\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.86E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.35E-03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-216a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.87E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.31E-03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-1248\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.23E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.72E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-451\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.63E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.86E-03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-184\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.18E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.38E-05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-708\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.46E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.17E-06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-141\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.32E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.00E-04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-135b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.47E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.87E-06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.90E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.86E-05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-200c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.21E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.10E-04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-200b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.10E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.58E-04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-182\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.93E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.07E-06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-135a-2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.27E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.21E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-1291a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.40E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.14E-04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-3.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.22E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.27E-07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-204b-2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-3.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.35E-21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.96E-19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-3.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.85E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.30E-04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-489\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-3.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.62E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.34E-06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeca-mir-653\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-4.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.13E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.38E-04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEnriched \u0026ldquo;Biological Processes\u0026rdquo; for genes found to be up-regulated in the sarcoid group compared to the control group\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGo term category\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFDR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBackground genes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUP-regulated genes\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollagen fibril organization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.40E-14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of multicellular organismal process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.22E-11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2566\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnatomical structure morphogenesis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.30E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1829\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResponse to organic substance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.90E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2152\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of response to stimulus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.81E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3258\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTube development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.97E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e700\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocomotion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.00E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollagen metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.25E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of protein metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.02E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2442\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of cell migration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.80E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e710\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCell adhesion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.37E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e771\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSkeletal system development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.02E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e382\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVasculature development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.02E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e434\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReg. of transmembrane receptor protein serine/threonine kinase signaling path\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.02E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of cell population proliferation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.79E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1232\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChondrocyte development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.21E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInflammatory response\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.75E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e386\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative regulation of developmental process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.93E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e768\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResponse to wounding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.10E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollagen biosynthetic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.20E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of response to external stimulus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.74E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e672\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReproductive structure development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.74E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e316\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOssification\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.80E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e191\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnzyme linked receptor protein signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.84E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e486\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of angiogenesis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.91E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e223\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCellular component organization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.20E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4673\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExtracellular matrix assembly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.60E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative regulation of wound healing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.00E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCellular response to endogenous stimulus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.30E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e854\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of cell adhesion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.70E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e570\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResponse to external stimulus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.84E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1843\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTissue morphogenesis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.03E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e461\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative regulation of signal transduction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.70E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e960\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive regulation of cell differentiation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.00E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e809\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtein maturation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.00E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e175\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive regulation of nervous system development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.20E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e458\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive regulation of protein phosphorylation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.53E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e809\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResponse to stress\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.53E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2744\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of ERK1 and ERK2 cascade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.60E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e228\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of intracellular signal transduction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.60E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1310\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTransmembrane receptor protein serine/threonine kinase signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.30E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e137\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEpithelial cell proliferation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.92E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of body fluid levels\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.10E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative regulation of reproductive process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.20E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNervous system development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.90E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1921\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e3.7 FUNCTIONAL ANALYSIS FOR DIFFERENTIALLY EXPRESSED (miRNA-\u003cem\u003eDEG\u003c/em\u003e COUPLES) ACCORDING TO THE EXPRESSION LEVELS\u003c/h2\u003e\u003cp\u003eThe putative targets of at least the 20% of input miRNAs were crossed with human orthologues corresponding to our DEGs, identifying miRNA-DEG couples (with opposite expression trends in sarcoids vs controls) used for the functional analysis (Supplementary tables S7 and S8).\u003c/p\u003e\u003cp\u003eThe strategy used to identify differentially expressed genes (DEGs) that are also targets of differentially expressed (DE) miRNAs was to select miRNA\u0026ndash;mRNA pairs with opposite expression trends (i.e., up-regulated miRNAs paired with down-regulated target genes, and vice versa). These were used for a KEGG pathway enrichment analysis. The statistically significant enriched KEGG pathways for the selected DEGs are reported in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEnriched KEGG pathways for selected DEGs from the miRNA-DEG couples according to expression changes in sarcoids.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFunctional grup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTerm\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFDR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eAssociated Genes Found\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOne carbon pool by folate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOne carbon pool by folate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.25E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.92E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eALDH1L1, ALDH1L2, MTHFD1L, MTHFD2, SHMT2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eABC transporters\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eABC transporters\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.22E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.39E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eABCA4, ABCA5, ABCA9, ABCC11, ABCC6, ABCC8, ABCG1, CFTR\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtein digestion and absorption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProtein digestion and absorption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.41E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.04E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eATP1A1, ATP1A4, COL11A1, COL12A1, COL14A1, COL16A1, COL19A1, COL22A1, COL4A1, COL4A3, COL4A5, COL4A6, COL5A2, COL6A3, COL6A6, COL8A2, PRCP, SLC8A3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMineral absorption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMineral absorption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.01E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.17E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eATP1A1, ATP1A4, ATP2B2, ATP7B, CYBRD1, SLC5A1, SLC8A3, STEAP2, TF\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCholesterol metabolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCholesterol metabolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.96E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.55E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eANGPTL4, CYP27A1, LRP1, LRP2, LRPAP1, PLTP, SCARB1, SORT1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePathways in cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePathways in cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.05E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.94E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, ALK, APC2, AR, AXIN2, CALML4, CAMK2A, CAMK2B, CDH1, CDK6, COL4A1, COL4A3, COL4A5, COL4A6, CSF3R, CTNNA3, DAPK2, DCC, E2F3, EGF, ERBB2, FGF1, FGFR4, FLT4, FN1, FZD3, FZD6, GLI1, IFNAR1, IFNAR2, IGF2, IL23R, ITGA2, ITGB1, JAG1, KIT, LAMA2, LAMB1, LAMB3, LAMC1, MECOM, MET, NOTCH1, PAX8, PLCB4, PTCH1, RASGRP1, RASGRP2, RUNX1T1, TGFB3, TGFBR1, TRAF5, WNT5A, WNT9B, ZBTB16\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProteoglycans in cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProteoglycans in cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.00E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.75E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eANK2, ANK3, CAMK2A, CAMK2B, CD63, CTSL, ERBB2, ERBB3, ERBB4, FN1, FZD3, FZD6, GPC3, HCLS1, IGF2, ITGA2, ITGB1, KDR, MET, PLCE1, PTCH1, TIAM1, VAV1, WNT5A, WNT9B\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRap1 signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRap1 signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.37E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.80E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, CALML4, CDH1, EGF, FGF1, FGFR4, FLT4, GRIN2B, ITGB1, KDR, KIT, MAGI1, MAGI2, MET, PDGFC, PLCB4, PLCE1, RAPGEF4, RASGRP2, TIAM1, VAV1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCalcium signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCalcium signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.41E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.72E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY7, ADRA1A, ASPH, ATP2B2, CACNA1D, CACNA1E, CACNA1H, CALML4, CAMK2A, CAMK2B, CAMK4, EGF, ERBB2, ERBB3, ERBB4, FGF1, FGFR4, FLT4, GNAL, GRIN2B, ITPKB, KDR, MET, MST1R, NOS1, NTRK2, NTRK3, ORAI2, P2RX5, PDGFC, PLCB4, PLCE1, RYR2, RYR3, SLC8A3, TACR1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAxon guidance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAxon guidance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.44E-11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.25E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eABLIM1, ABLIM2, CAMK2A, CAMK2B, DCC, EPHA1, EPHA3, EPHA8, EPHB1, FES, FZD3, GDF7, ITGB1, L1CAM, MET, NTN4, NTNG1, PAK5, PLXNA4, PLXNB1, PLXNB3, PLXNC1, PTCH1, ROBO1, ROBO2, SEMA4A, SEMA4G, SEMA5A, SLIT2, SLIT3, SRGAP1, SRGAP3, TRPC4, WNT5A\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHippo signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHippo signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.76E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.27E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eAJUBA, APC2, AXIN2, CDH1, CTNNA3, DLG4, FGF1, FRMD1, FZD3, FZD6, GDF7, LLGL2, NKD1, RASSF6, TGFB3, TGFBR1, WNT5A, WNT9B\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCell adhesion molecules\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCell adhesion molecules\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.67E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.21E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eCADM3, CD86, CD99, CD99L2, CDH1, CDH3, CDH4, ITGB1, L1CAM, MPZL1, NECTIN1, NEGR1, NFASC, NLGN1, NRCAM, NRXN1, NRXN3, NTNG1, PTPRD, PTPRF, PTPRS, SIGLEC1, VCAN\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdherens junction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAdherens junction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.52E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.02E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eBAIAP2, CDH1, CTNNA3, ERBB2, LMO7, MET, NECTIN1, NECTIN4, PTPRB, PTPRF, SORBS1, TGFBR1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulation of actin cytoskeleton\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRegulation of actin cytoskeleton\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.83E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.14E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eABI2, APC2, BAIAP2, C6, DIAPH3, EGF, FGF1, FGFR4, FN1, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, MYH10, MYH11, PAK5, PDGFC, PIP5K1B, SCIN, SPATA13, TIAM1, VAV1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePPAR signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePPAR signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.84E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.28E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eACOX1, ACSL1, ACSL5, ANGPTL4, CPT1B, CYP27A1, HMGCS1, PLTP, PPARA, SCD, SORBS1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMAPK signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMAPK signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.80E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.76E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eCACNA1D, CACNA1E, CACNA1H, CACNA2D4, CACNB2, CACNB4, CACNG5, DUSP6, EGF, ERBB2, ERBB3, ERBB4, FGF1, FGFR4, FLT4, IGF2, KDR, KIT, MAP3K9, MAP4K2, MAP4K4, MAPT, MECOM, MET, NTRK2, PDGFC, PLA2G4F, PTPRR, RASGRP1, RASGRP2, TGFB3, TGFBR1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eDilated cardiomyopathy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCardiac muscle contraction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.96E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.83E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eASPH, ATP1A1, ATP1A4, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, MYH6, RYR2, SLC8A3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAdrenergic signaling in cardiomyocytes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.62E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.15E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, ADRA1A, ATP1A1, ATP1A4, ATP2B2, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, CALML4, CAMK2A, CAMK2B, CREB3L2, MYH6, PLCB4, RAPGEF4, RYR2, SCN4B, SCN5A, SCN7A, SLC8A3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOxytocin signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.23E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.61E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, CALML4, CAMK2A, CAMK2B, CAMK4, GUCY1A2, PLA2G4F, PLCB4, RYR2, RYR3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHypertrophic cardiomyopathy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.39E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.82E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eCACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, DMD, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, LAMA2, MYH6, RYR2, SGCD, SLC8A3, TGFB3, TTN\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eArrhythmogenic right ventricular cardiomyopathy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.01E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.57E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eCACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, CTNNA3, DMD, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, LAMA2, RYR2, SGCD, SLC8A3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDilated cardiomyopathy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.94E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.26E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, DMD, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, LAMA2, MYH6, RYR2, SGCD, SLC8A3, TGFB3, TTN\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e\u003cp\u003eECM-receptor interaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePI3K-Akt signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.82E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.32E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eCDK6, COL4A1, COL4A3, COL4A5, COL4A6, COL6A3, COL6A6, CREB3L2, CSF3R, EGF, ERBB2, ERBB3, ERBB4, FGF1, FGFR4, FLT4, FN1, IFNAR1, IFNAR2, IGF2, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, KDR, KIT, LAMA2, LAMB1, LAMB3, LAMB4, LAMC1, MAGI1, MAGI2, MET, NTRK2, PDGFC, PRLR, RELN, THBS4, TNR, TNXB, VWF\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFocal adhesion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.18E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.06E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eCOL4A1, COL4A3, COL4A5, COL4A6, COL6A3, COL6A6, EGF, EMP2, ERBB2, FLT4, FN1, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, KDR, LAMA2, LAMB1, LAMB3, LAMB4, LAMC1, MET, PAK5, PDGFC, PIP5K1B, RELN, THBS4, TNR, TNXB, VAV1, VWF\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eECM-receptor interaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.33E-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.55E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eAGRN, COL4A1, COL4A3, COL4A5, COL4A6, COL6A3, COL6A6, FN1, FRAS1, FREM2, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, LAMA2, LAMB1, LAMB3, LAMB4, LAMC1, RELN, THBS4, TNR, TNXB, VWF\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAGE-RAGE signaling pathway in diabetic complications\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.35E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.95E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eCOL4A1, COL4A3, COL4A5, COL4A6, CYBB, FN1, NOX1, NOX4, PLCB4, PLCE1, TGFB3, TGFBR1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAmoebiasis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.12E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.11E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eCOL4A1, COL4A3, COL4A5, COL4A6, FN1, GNAL, IL1R2, LAMA2, LAMB1, LAMB3, LAMB4, LAMC1, PLCB4, TGFB3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHuman papillomavirus infection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.85E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.03E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eAPC2, ATP6V0A4, AXIN2, CDK6, COL4A1, COL4A3, COL4A5, COL4A6, COL6A3, COL6A6, CREB3L2, EGF, FN1, FZD3, FZD6, IFNAR1, IFNAR2, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, JAG1, LAMA2, LAMB1, LAMB3, LAMB4, LAMC1, LLGL2, MAGI1, NOTCH1, RELN, THBS4, TNR, TNXB, VWF, WNT5A, WNT9B\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSmall cell lung cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.67E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.95E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eCDK6, COL4A1, COL4A3, COL4A5, COL4A6, E2F3, FN1, ITGA2, ITGB1, LAMA2, LAMB1, LAMB3, LAMB4, LAMC1, TRAF5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"17\" rowspan=\"18\"\u003e\u003cp\u003eInsulin secretion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ecGMP-PKG signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.40E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.05E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, ADRA1A, ATP1A1, ATP1A4, ATP2B2, CACNA1D, CALML4, CREB3L2, GTF2IRD1, GUCY1A2, IRS4, KCNMA1, KCNU1, MYH6, OPRD1, PLCB4, SLC8A3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ecAMP signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.40E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.12E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eACOX1, ADCY5, ADCY6, ADCY7, ATP1A1, ATP1A4, ATP2B2, CACNA1D, CALML4, CAMK2A, CAMK2B, CAMK4, CFTR, CREB3L2, GLI1, GLP1R, GRIA1, GRIN2B, PDE10A, PDE4C, PDE4D, PLCE1, PPARA, PTCH1, RAPGEF4, RYR2, TIAM1, VAV1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCardiac muscle contraction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.96E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.83E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eASPH, ATP1A1, ATP1A4, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, MYH6, RYR2, SLC8A3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAdrenergic signaling in cardiomyocytes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.62E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.15E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, ADRA1A, ATP1A1, ATP1A4, ATP2B2, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, CALML4, CAMK2A, CAMK2B, CREB3L2, MYH6, PLCB4, RAPGEF4, RYR2, SCN4B, SCN5A, SCN7A, SLC8A3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCircadian entrainment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.61E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.65E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, CACNA1D, CACNA1H, CALML4, CAMK2A, CAMK2B, GRIA1, GRIN2B, GUCY1A2, NOS1, PLCB4, RYR2, RYR3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGlutamatergic synapse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.75E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.50E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, CACNA1D, DLG4, GRIA1, GRIK3, GRIN2B, PLA2G4F, PLCB4, SHANK1, SHANK2, SLC1A2, SLC1A3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInsulin secretion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.85E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.55E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eABCC8, ADCY5, ADCY6, ADCY7, ATP1A1, ATP1A4, CACNA1D, CAMK2A, CAMK2B, CREB3L2, GLP1R, KCNMA1, KCNN3, KCNU1, PCLO, PLCB4, RAPGEF4, RIMS2, RYR2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMelanogenesis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.25E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.00E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, CALML4, CAMK2A, CAMK2B, CREB3L2, DCT, FZD3, FZD6, KIT, PLCB4, WNT5A, WNT9B\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThyroid hormone synthesis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.89E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.87E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, ATP1A1, ATP1A4, CREB3L2, DUOX2, LRP2, PAX8, PLCB4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOxytocin signaling pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.23E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.61E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, CALML4, CAMK2A, CAMK2B, CAMK4, GUCY1A2, PLA2G4F, PLCB4, RYR2, RYR3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAldosterone synthesis and secretion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.98E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.07E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, ATP1A1, ATP1A4, ATP2B2, CACNA1D, CACNA1H, CALML4, CAMK2A, CAMK2B, CAMK4, CREB3L2, KCNK3, PLCB4, SCARB1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCortisol synthesis and secretion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.04E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.37E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, CACNA1D, CACNA1H, CREB3L2, KCNA4, KCNK3, PLCB4, SCARB1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCushing syndrome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.86E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.73E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, APC2, AXIN2, CACNA1D, CACNA1H, CAMK2A, CAMK2B, CDK6, CREB3L2, E2F3, FZD3, FZD6, KCNA4, KCNK3, PLCB4, SCARB1, WNT5A, WNT9B\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSalivary secretion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.51E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.12E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, ADRA1A, ATP1A1, ATP1A4, ATP2B2, CALML4, GUCY1A2, KCNMA1, LPO, NOS1, PLCB4, RYR3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGastric acid secretion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.05E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.33E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, ATP1A1, ATP1A4, CALML4, CAMK2A, CAMK2B, CFTR, KCNK10, PLCB4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBile secretion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.07E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.21E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, AQP4, ATP1A1, ATP1A4, CFTR, SCARB1, SLC4A5, SLC5A1, SLCO1A2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAmphetamine addiction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.20E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.95E-02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, CACNA1D, CALML4, CAMK2A, CAMK2B, CAMK4, CREB3L2, DDC, GRIA1, GRIN2B\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDilated cardiomyopathy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.94E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.26E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eADCY5, ADCY6, ADCY7, CACNA1D, CACNA2D4, CACNB2, CACNB4, CACNG5, DMD, ITGA11, ITGA2, ITGA7, ITGB1, ITGB4, LAMA2, MYH6, RYR2, SGCD, SLC8A3, TGFB3, TTN\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFigures \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e illustrate two of the mainly interesting enriched KEGG pathways basing on KEGG graphs.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4 DISCUSSION","content":"\u003cp\u003eIn this study, a deep RNA and miRNA seq analysis was conducted on 12 sarcoid tissue samples, two paired skin samples from histologically healthy margins, and 10 healthy skin samples harvested from healthy horses. We set-up a Real-Time PCR protocol for the detection of BPV 1, 2, and 13 with a high degree of sensitivity and specificity which allowed us to evaluate the positivity of samples to the most common type of bovine papillomavirus (BPV1).\u003c/p\u003e\u003cp\u003eAs expected, BPV infection was demonstrated in most of the examined cases. In particular, the only viral type present was BPV1, with invariable negativity for BPV2 and BPV13, which have been reported in Brazil, Austria, New Zealand and also other areas of Italy \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eRegarding the RNA sequencing results, we aimed to explore the deep characterization of the sarcoid cell transcriptome by integrating data from both small-RNA and mRNA sequencing. To this end, we performed a differential analysis of both transcriptomes, as detailed in the Materials and Methods section. Subsequently, we performed an analysis incorporating differentially expressed miRNAs, their predicted target genes, and differentially expressed mRNAs, creating miRNA-DEG pairs (Supplementary tables S7 and S8). This approach enabled a functional analysis of the modulated pathways across the entire expressed transcriptome.\u003c/p\u003e\u003cp\u003eThe identification of up-regulated and down-regulated genes, along with their regulatory non-coding elements, highlighted pathways closely associated with tumor progression, as summarized in our enriched KEGG pathways for selected DEGs from the miRNA-DEG couples analysis (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe differential expression analysis of miRNAs in tumor tissues compared to healthy skin revealed many well-known oncomiRs, both up- and down-regulated. Nine out of the 20 most up-regulated miRNA and 7 out of the 20 most down-regulated miRNA were also identified by Pawlina and collaborators \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e in the only study, to our knowledge, on miRNA dysregulation in equine sarcoids \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFor instance, miR-450a, which results up-regulated in both studies, is similarly up-regulated in human oral squamous cell carcinoma, where it is likely involved in promoting cell motility, a process essential for cancer invasion \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Hence, also in sarcoids, despite their embryological differences with squamous cell carcinomas, miR-450a might act as an onco-miRNA, with its upregulation contributing to local invasiveness \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAnother shared result is a significant downregulation of miR-200b and miR-141, both part of the miR-200 miRNA family. A similar result has been reported in some human virus-related cancers, such as Epstein-Barr virus-induced gastric carcinoma and HPV-induced cervical cancer \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Generally, the downregulation of miR-200 family members is associated with increased cell invasiveness and, overall, reduced survival.\u003c/p\u003e\u003cp\u003eWe also identified uniquely modulated miRNAs not previously reported in sarcoids. Some of these miRNAs can have dual roles in tumor progression, invasion, and malignancy—functions that may vary depending on the cellular and neoplastic context. MiR-337, miR-503, miR-542, and miR-431-5p have all been shown to act both as tumor suppressors or promoters in different neoplasms.\u003c/p\u003e\u003cp\u003eMore in detail, miR-337-3p - the most highly expressed miRNA in our study- has been previously reported as overexpressed in human liposarcomas, a tumor that shares a mesenchymal origin, similarly to equine sarcoids \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. On the other hand, miR-337-3p was downregulated both in tumor and serum of patients with osteosarcoma, with levels reverting to normal after excisional surgery \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. It is thought to inhibit migration and invasion in breast cancer while promoting apoptosis\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Additionally, miR-337 targets \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003ePIK3CB\u003c/em\u003e, thereby reducing PI3K/AKT signaling activation\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe second and third most up-regulated miRNAs in our study, respectively miR-503 and miR-427, have also been identified as tumor suppressors in several malignancies, but they have also been reported to exhibit oncogenic functions in specific cancer types, suggesting a tissue- or disease-specific role\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Notably, miR-424 and miR-503, both members of the miR-16 family, are clustered on the same chromosome in humans and horses. These miRNAs are often dysregulated in cancers and play crucial yet paradoxical roles in tumor initiation and progression by targeting different genes and molecular pathways. Furthermore, these miRNAs are often co-expressed in cancer cells, indicating a potential coordinated function as a cluster \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAnother interesting observation was the strong upregulation of miR-542. A similar result has been observed in human osteosarcoma, both in cell cultures and neoplastic tissue, where it is recognized as a cellular proliferation promoter, and as a circulating biomarker. A higher miR-542-3p concentration has been indeed associated with advanced tumor stage and short overall survival \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. MiR-542 regulates multiple cancer-related behaviors like cell apoptosis, metastasis, proliferation, cell cycle, and glycolysis, through the targeting of at least 18 genes and key signaling pathways such as Wnt/β-catenin, ERK1/2, JAK2, and PI3K/AKT \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e.Additional future studies may help to evaluate the prognostic relevance of this circulating miRNA, especially in relation to recurrence in equine sarcoids.\u003c/p\u003e\u003cp\u003eSimilarly, miR-431-5p, which was also up-regulated in our study, has been implicated in various cancers, regulating processes such as proliferation, apoptosis, autophagy, migration, invasion, and angiogenesis \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTaken together, these results might reflect the unique nature of sarcoids, which are locally aggressive but non-metastatic and also support the hypothesis that a tumor-specific profile of mi-RNA expression, with different roles in tumorigenesis, tumor biology and phenotyping should be better described.\u003c/p\u003e\u003cp\u003eThe analyses of differential mRNA expression between sarcoid and healthy skin also revealed substantial differences in both gene expression and active pathways. Genes involved in phosphorylation (\u003cem\u003ePPP1R12B, PELI2\u003c/em\u003e), cell adhesion (\u003cem\u003eCLDN5\u003c/em\u003e), virus-host interactions (\u003cem\u003eHSP90B1\u003c/em\u003e, \u003cem\u003ePDIA6, PPIB, AGO4\u003c/em\u003e), cell differentiation (\u003cem\u003eFOXC1, ID4, ETV1, RORC\u003c/em\u003e), actin-cytoskeleton organization with lamellipodium assembly (\u003cem\u003ePPP1R12B, PIEZO2, TANC1\u003c/em\u003e), and cellular movement (\u003cem\u003eHSP90B1, PPP1R12B, PIEZO2, TANC1, RYR2\u003c/em\u003e) were significantly altered (Tables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In particular \u003cem\u003eHSP90B1\u003c/em\u003e acts as a molecular chaperone, facilitating the folding of viral proteins and modulating host immune responses, \u003cem\u003ePDIA6\u003c/em\u003e is involved in protein folding interacting with viral proteins, \u003cem\u003ePPIB\u003c/em\u003e has been implicated in viral replication processes, \u003cem\u003eAGO4\u003c/em\u003e contribute to antiviral defense. Of extreme interest, since we are dealing with a mesenchymal neoplasm, is also the modulation of \u003cem\u003eSMAD2\u003c/em\u003e and \u003cem\u003eHIF1AN\u003c/em\u003e, suggesting a complex regulatory system in the tumor microenvironment.\u003c/p\u003e\u003cp\u003eNotably, enriched KEGG pathways for selected DEGs from the miRNA-DEG couples analysis included critical processes such as “Pathways in Cancer” (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) and the “Hippo signaling pathway” (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA plethora of key regulators of tissue invasion and metastasis modulated in our sarcoids samples are outlined in cancer-related pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Of particular interest in papillomavirus-related cancers in horses is the modulation of the alternative Wnt signaling pathway \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, which seems involved also in sarcoids. Indeed, WNT5a and WNT9b genes were up-regulated likely due to the activation of the Wnt/β-catenin-independent pathway. A crucial protein in this alternative Wnt signaling pathway is YAP/TAZ, recently identified as part of the Wnt-YAP/TAZ signal transduction mechanism \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. This complex can promote the expression of Notch receptors and ligands, further integrating multiple signaling pathways. Interestingly, Wnt5a/b ligands serve as both upstream activators and downstream targets of the YAP/TAZ-TEAD complex, suggesting a potential positive feedback loop that stimulates the other particularly modulated and interesting pathway in our sarcoids, the Hippo signaling pathway \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe Hippo signaling pathway, detailed in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, is an evolutionarily conserved signaling cascade initially identified in \u003cem\u003eDrosophila melanogaster\u003c/em\u003e for its role in restricting tissue overgrowth \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. In mammals, it regulates cell proliferation, differentiation, apoptosis, organ size control, and tissue homeostasis \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. Hippo signaling pathway dysregulation is linked to several diseases, including cancer, as it interferes with upstream regulatory mechanisms that are normally controlled by a complex interplay of intrinsic and extrinsic signals—such as mechanical stress, cell–cell contact, polarity, energy levels, cellular stress, and various diffusible hormonal factors, many of which signal through G protein–coupled receptors \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe Hippo signaling pathway exerts its effects through its core effectors, YAP/TAZ. When the pathway is inactive, unphosphorylated YAP/TAZ accumulate in the nucleus, where they interact with TEAD transcription factors to drive gene expression. Conversely, when the Hippo signaling pathway is active, YAP/TAZ are phosphorylated by LATS1/2 leading to their sequestration in the cytoplasm. In our study, several down-regulated miRNAs (miR-200c-3p, miR-204-5p, miR-216a-5p, miR-375-3p, miR-486-3p, miR-653-5p) target and modulate \u003cem\u003eDLG4\u003c/em\u003e gene, that encodes signaling protein known to suppress Hippo signaling pathway activation by inhibiting YAP/TAZ phosphorylation \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eMoreover, our results indicate that LATS1/2 activity may have been enhanced through miRNA-mediated repression of \u003cem\u003eAJUBA\u003c/em\u003e gene, a negative regulator of Hippo signaling pathway, and its upstream inhibitor, \u003cem\u003eRASSF6\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Given that Hippo signaling pathway components interact with other key signaling pathways such as Wnt, AMPK, TGF-β, and Notch, its role in cancer progression is highly complex\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFurthermore, our study revealed that \u003cem\u003eFZD3\u003c/em\u003e and \u003cem\u003eFZD6\u003c/em\u003e genes were down-regulated due to the upregulation of several miRNAs on this pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Frizzled receptors (FZDs) regulate both the canonical β-catenin pathway and various non-canonical β-catenin-independent pathways. Aberrant FZD signaling is implicated in numerous diseases, including cancer, although the role of non-canonical Wnt pathways can play either tumor-promoting or tumor-suppressing roles.\u003c/p\u003e\u003cp\u003eInterestingly, we observed both Hippo activation and repression signals, suggesting a dynamic balance between tumor proliferation, infiltration, and malignancy—reflecting the unique non-metastatic behavior of sarcoid tumors.\u003c/p\u003e\u003cp\u003eThe cGAS-STING pathway, which triggers the innate immune system in presence of pathogens or of damaged cells through NF-κB and IRF3, leading to the production of type I interferons (IFN-I) and pro-inflammatory cytokines \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e, can deeply influence the tumor microenvironment (TME). In our study, we observed a significant modulation of the Hippo pathway, which aligns with literature findings that link cGAS-STING signaling to PV infection. A functional connection between cGAS-STING and the Hippo pathway has been previously observed in PV-induced tumors, where PV exploits the E6/E7 oncoproteins to deactivate Hippo signaling \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. This promotes YAP/TAZ activity, which, in turn, suppresses cGAS-STING, reducing interferon production and supporting immune evasion, thereby blocking the innate immune response and promoting tumor transformation \u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAlthough the Hippo signaling pathway has been extensively studied \u003cem\u003ein vitro\u003c/em\u003e as a potential therapeutic target, its \u003cem\u003ein vivo\u003c/em\u003e roles remain less understood. In our study we demonstrated for the first time in horses, the downregulation of cGAS/STING signaling in sarcoids; this is an important finding that showed as equine BPV1-induced sarcoids have an immune evasion mechanism similar to high risk human PV\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e,\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe Hippo signaling pathway plays a vital role in fibroblast activation, stem cell maintenance, ECM remodeling, immune infiltration, and angiogenesis. Through these processes, it modulates the secretion of molecules that impact tumor development via interactions with TME components. Increasing evidence suggests that the Hippo signaling pathway can exert both pro- and anti-tumor effects, depending on the tumor type and context \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn this type of cancer, the pathway appears to be uniquely activated, as it is linked to immune evasion, fibroblast activation, and increased cell mobility, while still being associated with low metastatic potential.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, for the first time to the authors' knowledge, both coding and non-coding transcript-regulated metabolic pathways were simultaneously investigated in equine sarcoids and overall, underscores the complex regulatory interplay between miRNAs, mRNAs, and key oncogenic pathways in sarcoid tumors, providing novel insights into their molecular pathogenesis.\u003c/p\u003e\u003cp\u003eThis comprehensive and effective global analysis enabled the identification of highly regulated pathways, providing deeper insight into the pathogenesis of a tumor with a peculiar behavior in terms of invasiveness and low metastatic potential, and paving the way for the identification of novel therapeutic targets.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was supported by RC IZS PLV 12/19 and RC IZS PLV 03/23 funded by the Italian Ministry of Health.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: E.R, K.C. Methodology: S.M., S.C., K.C., I.P., R.G., M.P., E.R. Formal analysis: S.M., S.C., I.P Investigation: S.M., I.P., F.D.A, L.D.P, F.F., R.R., R.G., M.P., Writing \u0026ndash; original draft preparation: S.M., K.C., I.P. Writing \u0026ndash; review and editing: E.R, L.M., B.P, A.G. Supervision: K.C., E.R. Project administration: E.R. Funding acquisition: E.R.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe raw sequencing datasets generated during and analysed during the current study are available in the Sequence Read Archive (SRA) repository 59, under the BioProject ID: PRJNA1273441 (BioSample accessions from SAMN48946045 to SAMN48946068 for small RNA-seq and from SAMN48946069 to SAMN48946091 for mRNA-seq).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOgłuszka, M., Starzyński, R. R., Pierzchała, M., Otrocka-Domagała, I. \u0026amp; Raś, A. 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The Sequence Read Archive. \u003cem\u003eNucleic Acids Res.\u003c/em\u003e \u003cstrong\u003e39\u003c/strong\u003e, D19\u0026ndash;D21 (2011).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6975941/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6975941/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSarcoids are the most common cutaneous tumors in horses, representing up to 90% (35\u0026ndash;90%) of skin neoplasms. Mostly caused by Bovine Papillomavirus (BPVs) infections, sarcoids are highly resistant to therapy and prone to recurring, posing a significant threat to equine health. The aim of this study is to explore molecular pathogenetic mechanisms underlying the development of BPVs-associated sarcoids, by applying transcriptomic approach. After testing samples for viral DNA, both mRNA and small RNA expression was analyzed via high-throughput Illumina sequencing comparing 12 sarcoids and 12 healthy skin samples as controls. Differentially expressed genes (DEGs), DE miRNAs (sarcoids vs controls) and miRNA-DEG couples with opposite expression trends, were retrieved and subjected to a functional analysis. Over 6K DEGs emerged, 3620 down-regulated and 2415 up-regulated along with 145 DE miRNAs, 56 down-regulated and 89 up-regulated. Among the enriched biological processes for DEGs, some were related to growth factors production and collagen binding, cell migration and proliferation, tissue morphogenesis and inflammatory response. Interestingly, \u0026ldquo;\u003cem\u003ePathways in cancer\u003c/em\u003e\u0026rdquo; and \u0026ldquo;\u003cem\u003eHippo signaling pathway\u003c/em\u003e\u0026rdquo; were enriched KEGG pathways for the miRNA-DEG couples. Our data identified a great transcription discrepancy between sarcoid lesions and healthy skin with an overall enrichment for processes related to cellular transformation.\u003c/p\u003e","manuscriptTitle":"Deciphering the transcription regulation of bovine papillomavirus (BPV)-associated equine sarcoids through OMIC integrated approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-31 10:15:42","doi":"10.21203/rs.3.rs-6975941/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6e8db1e4-2c58-40f2-b72b-da4695135e15","owner":[],"postedDate":"July 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":52396278,"name":"Biological sciences/Cancer"},{"id":52396279,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":52396280,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2025-08-12T06:38:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-31 10:15:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6975941","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6975941","identity":"rs-6975941","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}