Analysis of histology and long noncoding RNAs involved in the rabbit hair follicle density using RNA sequencing

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However, molecular mechanisms regulating hair follicle density have remained elusive. Results: In this study, hair follicle density at different body sites of Wan strain Angora rabbits with high and low wool production (HWP and LWP) was investigated by histological analysis. Haematoxylin-eosin staining showed a higher hair follicle density in the skin of the HWP rabbits. The long noncoding RNA (lncRNA) profile was investigated by RNA sequencing, and 50 and 38 differentially expressed (DE) lncRNAs and genes, respectively, were screened between the HWP and LWP groups. A gene ontology analysis revealed that phospholipid, lipid metabolic, apoptotic, lipid biosynthetic, and lipid and fatty acid transport processes were significantly enriched. Potential functional lncRNAs that regulate lipid metabolism, amino acid synthesis, as well as the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) and hedgehog signalling pathways, were identified. Consequently, five lncRNAs (LNC_002171, LNC_000797, LNC_005567, LNC_013595, and LNC_020367) were considered to be potential regulators of hair follicle density and development. Three DE lncRNAs and genes were validated by quantitative real-time polymerase chain reaction (q-PCR). Conclusions: LncRNA profiles provide information on lncRNA expression to improve the understanding of molecular mechanisms involved in the regulation of hair follicle density. Epigenetics & Genomics Skin Hair follicle density Wool production Histological analysis LncRNA expression RNA sequencing Angora rabbit Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background The Angora rabbit is an economically important livestock breed in several countries, especially in China and France. Wool production is one of the most important traits in Angora rabbits. The fur quality of rabbits is largely dependent on hair density, and hair follicle density determines hair density [1, 2]. For Angora rabbits under the same environmental conditions, gender, body site, and the month of age are closely related to wool fibre production [3]. Genetic factors that influence wool fibre production are fibre diameter, length, fineness, and the fibre density [3-7]. The mean hair follicle density depends on the skin area. The development of wool follicles occurs during prenatal life and no new hair follicles are formed after birth, implying that hair density in an adult rabbit will depend on how much that particular body part grows after the formation of the hair follicles [7, 8]. Correspondingly, hair follicle density and other wool characteristics are highly variable over the human and rabbit body [7, 9, 10]. The molecular mechanism underlying hair follicle density in rabbit skin and hair follicle development remains unclear. Hair follicle development is a complex morphogenetic process and undergoes periodic stages of growth (anagen), regression (catagen), and relative quiescence (telogen) [11-13]. The process of hair follicle formation and differentiation relies on many regulating molecules including messenger RNAs (mRNAs) and micro RNAs (miRNAs) [14-16], as well as a variety of signalling systems, such as the Wnt, Notch, bone morphogenetic protein (BMP), and fibroblast growth factor (FGF) pathways [17-22]. LncRNAs are RNA transcripts longer than 200 nucleotides that lack open reading frames (ORF) and protein-coding capabilities [23]. They regulate protein-coding gene expression at posttranscriptional and transcriptional levels [24, 25]. It is generally known that lncRNAs are also involved in the regulation of the hair follicle development and skin homeostasis [26-28]. RP11-766N7.3, H19 and HOTAIR are specific lncRNAs that are involved in Wnt signalling to regulate hair follicle development [29]. Strand-specific RNA sequencing (ssRNA-seq) also showed that lncRNAs may be considered as potential candidate markers for further study on the molecular mechanisms of hair follicle initiation [30]. However, hair follicle density-related lncRNAs in rabbits have not been profiled so far. In this study, the RNA-seq based approach was used to determine lncRNA expression levels in Angora rabbits with high wool production (HWP) and low wool production (LWP) after hair follicle density analysis. The results should provide fundamental resources to reveal the regulatory function of lncRNAs in hair follicle density in rabbits, as well as supply information for understanding human hair disorders such as hypotrichosis. Results Comparison of hair follicle density in high and low wool production rabbits To characterize the hair follicle density, the follicle densities of the backs, abdomens, sides, and hips of Wan strain Angora rabbits with HWP and LWP were compared (Fig. 1). A morphological analysis showed that the hair follicle densities of backs, abdomens, sides, and hips were higher in the HWP group (Fig. 1a, b, c, d) than in the LWP group (Fig. 1e, f, g, h). The results demonstrate that a high hair follicle density leads to high wool production in Wan strain Angora rabbits. Sequencing and assembly Eight libraries of the HWP groups (H1, H2, H3, and H4) and LWP groups (L1, L2, L3, and L4) were constructed. For the HWP and LWP libraries, above 84,456,770 and 94,769,312 clean reads per sample were obtained, respectively (Table 1). Above 89.19% and 89.02% of the reads were aligned with the rabbit reference genome uniquely located by above 77.55% and 75.67% of the clean reads for the HWP and LWP libraries, respectively. Above 17,380,601 (52.78%) and 21,898,377 (46.66%) reads, respectively, were identified as protein-coding mRNAs of the HWP and LWP groups (Additional file 1: Table S1). The other types of reads amounted to 12,349,910 (36.07%) and 16,461,100 (39.19%) for HWP and LWP groups, respectively, and these reads may include lncRNAs (Additional file 1: Table S1). Table 1. The analyses of reads mapped to the rabbit reference genome Sample name H1 H2 H3 H4 L1 L2 L3 L4 Total reads 95,426,664 84,456,770 149,301,000 89,038,716 123,865,064 94,769,312 109,570,388 130,245,954 Total mapped 85,943,449 (90.06%) 75,328,473 (89.19%) 133,972,487 (89.73%) 79,823,704 (89.65%) 110,263,589 (89.02%) 84,819,962 (89.5%) 99,272,110 (90.6%) 117,162,667 (89.95%) Multiple mapped 11,938,587 (12.51%) 9,315,870 (11.03%) 13,827,931 (9.26%) 10,659,938 (11.97%) 16,534,984 (13.35%) 9,777,660 (10.32%) 14,500,967 (13.23%) 11,066,700 (8.5%) Uniquely mapped 74,004,862 (77.55%) 66,012,603 (78.16%) 120,144,556 (80.47%) 69,163,766 (77.68%) 93,728,605 (75.67%) 75,042,302 (79.18%) 84,771,143 (77.37%) 106,095,967 (81.46%) Reads map to '+' 36,872,804 (38.64%) 32,897,302 (38.95%) 60,000,375 (40.19%) 34,636,589 (38.9%) 46,454,860 (37.5%) 37,454,686 (39.52%) 42,357,439 (38.66%) 52,928,464 (40.64%) Reads map to '-' 37,132,058 (38.91%) 33,115,301 (39.21%) 60,144,181 (40.28%) 34,527,177 (38.78%) 47,273,745 (38.17%) 37,587,616 (39.66%) 42,413,704 (38.71%) 53,167,503 (40.82%) Non-splice reads 56,778,516 (59.5%) 51,943,073 (61.5%) 89,625,539 (60.03%) 51,395,189 (57.72%) 74,099,166 (59.82%) 57,787,882 (60.98%) 65,280,836 (59.58%) 79,655,006 (61.16%) Splice reads 17,226,346 (18.05%) 14,069,530 (16.66%) 30,519,017 (20.44%) 17,768,577 (19.96%) 19,629,439 (15.85%) 17,254,420 (18.21%) 19,490,307 (17.79%) 26,440,961 (20.3%) Reads mapped in proper pairs 69,994,050 (73.35%) 62,138,530 (73.57%) 113,304,356 (75.89%) 65,315,796 (73.36%) 88,424,106 (71.39%) 70,592,926 (74.49%) 80,480,580 (73.45%) 100,326,142 (77.03%) Characterization of lncRNAs in rabbit skin tissue The RNA-seq analysis produced 22,136 lncRNAs (Additional file 2: Table S2). The lncRNA transcripts included 10,692 lincRNAs (48.3%), 2,612 antisense lncRNAs (11.8%), and 8,832 intronic lncRNAs (39.9%) (Fig. 2a). The average length of the novel lncRNAs was considerably shorter than the mRNAs, but longer than the known lncRNAs (Fig. 2b). The exon numbers of the novel lncRNAs were less than the mRNAs while greater than the known lncRNAs (Fig. 2c). In addition, ORF size in novel lncRNAs was longer than that in annotated lncRNAs, but shorter than that in protein-coding genes (Fig. 2d). Long noncoding RNAs and mRNAs expression profiles in rabbit skin tissue The results showed that the expression levels of mRNAs were higher than those of lncRNAs (Additional file 3: Figure S1). 50 and 38 differentially expressed (DE) lncRNAs and genes, respectively, were screened in the LWP and HWP groups (Additional file 4: Table S3, Table S4). Of these lncRNAs and genes, 15 lncRNAs and 21 genes were upregulated, and 35 lncRNAs and 17 genes were downregulated in the LWP group. Hierarchical cluster analysis of lncRNA and mRNA expression levels between LWP and HWP groups revealed distinct expression patterns (Fig. 3). Long noncoding RNA target prediction and functional analysis The potential target genes of lncRNAs were predicted accordingly their position (co-location) and expression correlation (co-expression) with the protein-coding genes. Gene ontology (GO) analysis was applied to investigate the potential functions of the lncRNAs’ co-location and co-expression mRNAs on the regulation of hair follicle development and wool production (Fig. 4). The significance of enrichment of each GO term was assessed by P -value < 0.05, and then the GO terms were filtered by the enrichment scores (-Lg P -value). The GO enrichment analysis showed that the lncRNAs’ co-location mRNAs were significantly enriched in phospholipid, lipid metabolic, and epithelial cell apoptotic processes in the biological process category (Fig. 4a), while co-expression mRNAs were significantly enriched in the cellular metabolic, lipoprotein, lipid biosynthetic, lipid, and fatty acid transport processes (Fig. 4b). The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis offered a reliable way of elucidating the candidate biological pathways that the integrated target genes were enriching. The cytokine-cytokine receptor interaction, chemokine signalling pathway and JAK-STAT signalling pathway were significantly involved in lncRNAs’ co-location mRNAs (Fig. 5a). In addition, pathways related to the biosynthesis of amino acids, arginine and proline metabolism, ether lipid metabolism, and the hedgehog signalling pathway were highly enriched by lncRNAs’ co-expression mRNAs (Fig. 5b). Therefore, the target genes of the DE lncRNAs between the LWP and HWP groups were related to lipid metabolism, amino acid synthesis, JAK-STAT, and the hedgehog signalling pathway. According to the functional enrichment analyses, five DE lncRNAs (LNC_002171, LNC_000797, LNC_005567, LNC_013595, and LNC_020367) were selected to construct regulatory networks (Fig. 6). LNC_002171 and LNC_000797 were involved in JAK-STAT and the hedgehog signalling pathway. Validation of DE lncRNAs and mRNAs with quantitative real-time polymerase chain reaction To validate the RNA-Seq results, LNC_000797, LNC_013595, LNC_020367, KRTAP15-1 , TCHHL1 , and ALOX15B were selected and their expression patterns in the LWP and HWP groups were examined by q-PCR. The results showed that the three DE lncRNAs and mRNAs were differentially expressed in the LWP and HWP groups. In addition, they exhibited a similar trend in the results of the RNA-seq and the q-PCR (Fig. 7). Therefore, the fragments per kilobase of transcript per million mapped reads (FPKM) obtained from RNA-seq could be reliably used to determine lncRNA and mRNA expression in the LWP and HWP groups. Discussion Wool density is one of the most important indices to evaluate the quality of the fur of the Wan strain Angora rabbit [6]. Hair follicle density determines wool density [1]. The quality of fur is associated mainly with the traits of the hair follicles [31]. To characterize the hair follicle density, the follicle density of the backs, abdomens, sides, and hips of Wan Strain Angora rabbits with HWP and LWP was compared (Fig. 1). A morphological analysis showed that the hair follicle density of backs, abdomens, sides, and hips of the HWP group was higher compared to the LWP group (Fig. 1). The results demonstrated that high hair follicle density contributed to high wool production in the Wan strain Angora rabbit. In French Angora rabbits, divergent selection of total fleece weight led to a positive difference of 0.55 genetic standard deviation for secondary to primary follicle ratio (S/P), although a low genetic correlation existed between them [32]. The formation of hair follicles is divided into prenatal hair morphogenesis and the postnatal hair cycle [33]. Once established during embryogenesis, hair follicle density is permanently fixed in postnatal life, and the hair follicle location eventually becomes fixed as a result of anchoring in the subcutis [34]. LncRNAs are widely involved in various biological processes, including the hair follicle cycle [35, 36]. The lncRNA and mRNA expression profiles were compared in the dorsal skin of LWP and HWP rabbits, and 50 and 38 DE lncRNAs and genes were obtained, respectively. These lncRNAs and genes might play crucial roles in regulating hair follicle density, and their differential expression might be the reason for differences in hair follicle density and wool production between HWP and LWP rabbits. Liu et al. (2020) analysed the miRNA effect on hair follicle density in the Rex rabbit [37], but lncRNA related to hair density in rabbits has only been done in the present study. The GO analysis showed that the DE lncRNAs are potential regulators of phospholipid, lipid metabolic, epithelial cell apoptotic, lipid biosynthetic, and lipid and fatty acid transport processes. Keratin-associated proteins (KRTAPs) play a critical role in cross-linking the keratin intermediate filaments to build a hair shaft [38]. KRTAP7-1 , KRTAP8-1 , and KRTAP15-1 were predicted as the targets of LNC_005567 in this study. KRTAP7-1 is involved in supporting the mechanical strength and shape of hair [38]. KRTAP15-1 is expressed in secondary follicles in the skin and associated with fibre diameter [39]. COL3A1 and LOXL4 were the target genes of LNC_013595 and LNC_020367, respectively. COL3A1 is one of collagens forming different extracellular matrix (ECM) components [40]. The lysyl oxidase like 4 (LOLX4) enzyme is responsible for initiating covalent cross-linking in collagen fibrils and is involved in providing additional mechanical strength to the ECM [41, 42]. The amount of ECM per cell contributes to the volume of the dermal papilla [43]. Hedgehog and JAK-STAT signalling pathway were significantly enriched by target genes ENSOCUG00000021211 and ENSOCUG00000023782 of LNC_002171 and LNC_000797, respectively. The hedgehog signalling pathway is correlated to the initiation of hair follicle formation and is a pivotal growth signal for dermal papilla maturation and growth [34, 44, 45]. The JAK-STAT signalling pathway is involved in maintaining the quiescence of hair follicles during telogen [46], and JAK-STAT inhibition contributes to the promotion of hair growth and the activation of hair follicle stem cells [47]. These findings demonstrate that LNC_002171, LNC_000797, LNC_005567, LNC_013595, and LNC_020367 are potentially important regulators of hair follicle density and development. TCHHL1 is a hair-specific protein given its high expression in scalp and chin skin [48]. TCHHL1 was identified in a genome-wide association study (GWAS) to have a significant association with hair shape within the top-associated single nucleotide polymorphisms (SNPs) (rs17646946), and showed nominally significant association with hair curliness [49]. ALOX15B is restricted to terminally differentiating keratinocytes (in particular the stratum granulosum) and 8(S)-lipoxygenase activity seems to be involved in terminal differentiation of mouse epidermis [50]. Clements et al. (2012) identified reduced expression of ALOX15B gene in ankyloblepharon–ectodermal defects–clefting (AEC) syndrome skin, with downregulated genes ( KRT25 and KRT27 ) encoding keratins involved in the morphogenesis of hair follicles [51]. Thus, in combination with the current research, three genes may participate in the regulation of hair follicle density in Angora rabbits. The results of q-PCR of LNC_000797, LNC_013595, LNC_020367, KRTAP15-1 , TCHHL1 , and ALOX15B showed similar expression patterns between RNA-Seq and q-PCR, demonstrating the reliability of these data. Conclusions In conclusion, differences in the histology and lncRNA profiles of skin were identified in HWP and LWP rabbits. The histological analysis showed a higher hair follicle density in HWP rabbits. The analyses of lncRNA profiles identified candidate lncRNAs involved in lipid metabolism, apoptosis, and hair follicle development. Further studies are required to investigate the roles of candidate lncRNAs in hair follicle density to improve rabbit breeding programmes. Methods Animals All animals were procured from the rabbit farm and acquired an approval from the farm owner in the Animal Husbandry and Veterinary Medicine Institute of Anhui Academy of Agriculture Sciences, Hefei, Anhui, China. 60 Wan Strain Angora rabbits (about one year old) were reared in the same conditions with regular pellets and water ad libtum. The wool weight of five successive collections using electric shears in one year from adult rabbits were determined. The sixty rabbits were divided into two populations designated as high wool production (HWP) and low wool production (LWP) according to wool production. The average wool weights showed remarkable difference (HWP: 401.3 ± 36.5 g vs LWP: 314.4 ± 29.2 g, P < 0.001). Finally, four rabbits with high and low wool production (430.1 ± 16.5 g vs 291.6 ± 13.3 g, P < 0.0001) were selected for the present study, respectively (Additional file 5: Table S5). The 52 remaining rabbits were reared like ordinary rabbits for wool production. Sample collection, preparation for histological examination The eight rabbits selected (four rabbits with high wool production, four rabbits with low wool production) were anesthetized by injecting 0.7% pentobarbital sodium (6 ml/kg) into ear vein of the rabbits before sampling. Skin tissue samples (1 cm 2 ) were collected from the backs, abdomens, sides and hips at the fourth week after plucking for histological analysis. Each skin sample was cut apart into two and then one piece was prepared and then subjected to histological analysis as our previous study [14]. The iodine solution was smeared on the resultant lesion to prevent bacterial infection. After the experiment, the rabbits were retained in the rabbit farm and reared and protected from external stimuli. cDNA library construction and sequencing Under anesthesia, skin samples from the back of the eight rabbits selected (four rabbits with high wool production and four rabbits with low wool production; 430.1 ± 16.5 g vs 291.6 ± 13.3 g, P < 0.0001) were collected at the fourth week after plucking for RNA-seq. The skin samples were firstly frozen in liquid nitrogen immediatelly after cutting and then stored at -80℃ before RNA extration. Whole RNA was extracted from the skin of HWP rabbits (designated as H1, H2, H3, and H4) and LWP rabbits (designated as L1, L2, L3, and L4) using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. The samples were sent to the Beijing Novogene Co., LTD with drikold. The purity and integrity of RNA was evaluated using the NanoPhotometer spectrophotometer (Implen, CA, USA) and Agilent 2100 Bioanalyzer (Agilent Technologies, CA, USA). The RNA was purified by removing rRNA, fragmented randomly, and converted to double cDNA, then were ligated with NEBNext adaptors. Finally, eight libraries were created by PCR using the NEBNext® Ultra™ Directional RNA Library Prep Kit (NEB, USA), quantified with Qubit2.0, and sequenced on an Illumina HiSeq 2500 platform (Illumina, San Diego, CA, USA). Mapping, assembling and screening Impurity data were removed from the raw reads and more than 12 Gb clean reads per sample were generated. The clean reads with high quality were then aligned using HISAT2 to the rabbit reference genome (https://www.ncbi.nlm.nih.gov/genome/?term=Rabbit) sequence. The mapped reads of each sample were assembled by StringTie (v2.0.4) [52]. The candidate lncRNAs were distinguished according to its sequence charecteristics (length>200 nt and noncoding potential) and meantime transcripts predicted with coding potential were filtered out by multiple tools. Conservative and comparative analyses were done between lncRNAs and mRNAs, and classification of lncRNAs was also analyzed. Quantification, target prediction and function analysis The expression levels of the lncRNAs and mRNAs in each sample were calculated by fragments per kilobase of transcript per million fragments mapped (FPKM). Differential expression between LWP and HWP groups was analyzed by using cuffdiff (https://www.genepattern.org/modules/docs/Cuffdiff/7), and the threshold was set as |log2 (Fold Change)| ≥ 1 and P value < 0.05. Target prediction was conducted by searching coding genes 100 kb up- and down-stream of lncRNAs (co-location) and analyzing co-expression relationship (pearson correlation) of mRNAs to lncRNAs. Then, GO and KEGG enrichment analyses were performed on targets and the function of key lncRNAs were predicted. GOseq R package [53] and KOBAS (http://www.genome.jp/kegg/) were used to conduct GO and KEGG enrichment analyses. Quantitative real-time polymerase chain reaction Three candidate lncRNAs and mRNAs were selected from the list of DE lncRNAs and DEGs for validation, and the relative expression level was determined by q-PCR on LightCycler 96 (Roche, Switzerland) using TransStart Green qPCR SuperMix (Transgen, Beijing, China) as our previous study [14]. The primers for q-PCR are listed in Additional file 6: Table S6. The reaction was performed in triplicates for each sample (HWP group: H1, H2, H3, and H4; LWP group: L1, L2, L3, and L4). The 2 -ΔΔCT method was used to determine the relative expression level of each gene. Statistical analyses Student’s t -test with two-sided was used in statistical comparisons in wool weight between HWP and LWP groups and RNA expression. Error bars represent the mean ± standard deviation (SD) as determined using GraphPad Prism 5 (GraphPad Sofware, Inc., La Jolla, CA, USA). A P value < 0.05 were considered the criterion for statistical significance. Abbreviations BMP: Bone morphogenetic protein; DE: Differentially expressed; ECM: Extracellular matrix; FDR: False discovery rate; FGF: Fibroblast growth factor; FPKM: Fragments per kilobase of transcript per million fragments mapped; GO: Gene Ontology; HE: Haematoxylin-eosin; HWP: High wool production; JAK: Janus kinase; KEGG: Kyoto Encyclopedia of Genes and Genomes; lncRNA: long noncoding RNA; LWP: Low wool production; ORF: Open reading frames; q-PCR: Quantitative real-time polymerase chain reaction; SD: Standard deviation; ssRNA-seq: Strand-specific RNA sequencing; STAT: signal transducer and activator of transcription; Declarations Acknowledgments Not Applicable Funding This work was supported by the earmarked fund for China Agriculture Research System (Grant No.: CARS-43-A-4) and Anhui Provincial Natural Science Foundation (Grant No.: 2008085QC137). These funding bodies had no role in the design of the study, sample collection, analysis or interpretation of data and in writing the manuscript. Availability of data and materials The data was presented in the manuscript and the supporting materials. The raw reads data was submitted to the Short Read Archive (SRA) under the accession number SRP299630 and BioProject accession number PRJNA688082 (https://www.ncbi.nlm.nih.gov/sra/PRJNA688082). Authors ´ contributions HLZ, DWH, and HSD conceived the study. HLZ, DWH, and XFW performed sample collection and total RNA preparation. XWZ and YXQ performed the q-PCR validation. HSD and DWH conducted the data analysis and prepared figures and tables. HSD and DWH wrote the manuscript. All authors read and approved the final manuscript. Ethics approval and consent to participate The present study was carried out in strict accordance with relevant guidelines and regulations by the Ministry of Agriculture of the People’s Republic of China. 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Sonic hedgehog signaling is essential for hair development. Curr Biol. 1998;8(19):1058-1068. Wang E, Harel S, Christiano AM. JAK-STAT signaling jump starts the hair cycle. J Invest Dermatol. 2016;136(11):2131–2132. Harel S, Higgins CA, Cerise JE, Dai Z, Chen JC, Clynes R, et al. Pharmacologic inhibition of JAK-STAT signaling promotes hair growth. Sci Adv. 2015;1(9):e1500973. Liu F, Chen Y, Zhu G, Hysi PG, Wu S, Adhikari K, et al. Meta-analysis of genome-wide association studies identifies 8 novel loci involved in shape variation of human head hair. Hum Mol Genet. 2018;27(3):559–575. Wu Z, Latendorf T, Meyer-Hoffert U, Schroder JM. Identification of trichohyalin-like 1, an s100 fused-type protein selectively expressed in hair follicles. J Invest Dermatol. 2011;131(8):1761–1763. Furstenberger G, Marks F, Krieg P. Arachidonate 8(S)-lipoxygenase. Prostaglandins Other Lipid Mediat 2002;68–69:235–243. Clements SE, Techanukul T, Lai-Cheong JE, Mee JB, South AP, Pourreyron C, et al. Mutations in AEC syndrome skin reveal a role for p63 in basement membrane adhesion, skin barrier integrity and hair follicle biology. Brit J Dermatol. 2012;167(1):134–144. Pertea M, Kim D, Pertea GM, Leek JT, Salzberg SL. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat Protoc. 2016;11(9):1650–1667. Young MD, Wakefield MJ, Smyth GK, Oshlack A. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol. 2010;11(2):R14. Supplementary Files AuthorChecklist.pdf checklists.docx SupplementaryData2.xlsx SupplementaryData1.xlsx Additionalfile1.pdf Additional file 1: Table S1. The analyses of reads mapped to the Rabbit reference genome. Additionalfile2.xlsx Additional file 2: Table S2. List of 22136 annotated lncRNA. Additionalfile3.pdf Additional file 3: Figure S1. Expression level analysis of the lncRNAs and protein-coding genes. Additionalfile4.xlsx Additional file 4: Table S3, Table S4. Differentially expressed lncRNAs and genes between the LWP and HWP groups, respectively. HWP, High wool production; LWP, Low wool production. Additionalfile5.pdf Additional file 5: Table S5. The wool production of the rabbits. “L” and “H” represent low wool production and high wool production groups, respectively. Additionalfile6.pdf Additional file 6: Table S6. Primers for q-PCR. F1, forward primer. R2, reverse primer. Cite Share Download PDF Status: Published Journal Publication published 28 Jan, 2021 Read the published version in BMC Genomics → Version 3 posted Editorial decision: Accept 17 Jan, 2021 Editor assigned by journal 16 Jan, 2021 Submission checks completed at journal 16 Jan, 2021 Editor invited by journal 16 Jan, 2021 You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-43570","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":8457031,"identity":"468e89be-4e6b-4fec-af5f-76995ca6ff8c","order_by":0,"name":"Haisheng Ding","email":"","orcid":"","institution":"Anhui Academy of Agricultural Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Haisheng","middleName":"","lastName":"Ding","suffix":""},{"id":8457032,"identity":"b44d7198-2c45-45e6-9078-eea5c2fcef19","order_by":1,"name":"Huiling Zhao","email":"","orcid":"","institution":"Anhui Academy of Agricultural Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Huiling","middleName":"","lastName":"Zhao","suffix":""},{"id":8457033,"identity":"1e92091f-c33a-4667-930e-0534c9a2ea8c","order_by":2,"name":"Xiaowei Zhao","email":"","orcid":"","institution":"Anhui Academy of Agricultural Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaowei","middleName":"","lastName":"Zhao","suffix":""},{"id":8457034,"identity":"d860ce9c-edee-4b3a-9d75-00a6e23ce9e0","order_by":3,"name":"Yunxia Qi","email":"","orcid":"","institution":"Anhui Academy of Agricultural Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yunxia","middleName":"","lastName":"Qi","suffix":""},{"id":8457035,"identity":"24f21446-0295-4173-936b-3108ab975279","order_by":4,"name":"Xiaofei Wang","email":"","orcid":"","institution":"Anhui Academy of Agricultural Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaofei","middleName":"","lastName":"Wang","suffix":""},{"id":8457036,"identity":"123d6cb3-65ca-495d-a44d-059854993d9b","order_by":5,"name":"Dongwei Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYBACA4YEMAkEzAcOfPhBmha2xIMze4jWAgY8xoc52IjQYs6eY/zhR4FNHn97z4fDDDwM8vxiB/Brsex5YybZY5BWLHHm7IbDBRYMhjNnJ+DXYnAjdxszg8HhxA0SuRsOz+BhSDC4TVjL5s8MBv8TN8i/eXCYh404LRukGQwOAG3hYSBSy5n334B+SU6ccSbNABjIEkT45Xha8ocff+wS+9sPP/7w4YeNPL80AS3oQII05aNgFIyCUTAKsAMAWqRJUtmIR20AAAAASUVORK5CYII=","orcid":"","institution":"Anhui Academy of Agricultural Sciences","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Dongwei","middleName":"","lastName":"Huang","suffix":""}],"badges":[],"createdAt":"2020-07-15 10:50:55","currentVersionCode":3,"declarations":"","doi":"10.21203/rs.3.rs-43570/v3","doiUrl":"https://doi.org/10.21203/rs.3.rs-43570/v3","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12864-021-07398-4","type":"published","date":"2021-01-28T15:00:47+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":5188129,"identity":"bdc8acb9-7bf4-42de-b3a3-d1788ae89543","added_by":"auto","created_at":"2021-01-22 15:01:40","extension":"tif","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":7414588,"visible":true,"origin":"","legend":"The histological observation of skin tissue from Wan strain Angora rabbits with HWP and LWP. a, b, c, d Transverse section of the backs, abdomens, sides, and hips of Wan strain Angora rabbits with HWP. e, f, g, h Transverse section of the backs, abdomens, sides, and hips of Wan strain Angora rabbits with LWP. HWP, High wool production; LWP, Low wool production. Bars = 200 μm","description":"","filename":"Figure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/3a43ad3cb542df32d488ff60.tif"},{"id":5188031,"identity":"3a2fa6ee-dfb9-4bc4-8900-40eb15a3175a","added_by":"auto","created_at":"2021-01-22 14:58:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":100286,"visible":true,"origin":"","legend":"Characterization of lncRNAs transcribed from Wan strain Angora rabbits. a The lncRNA classification in Wan strain Angora rabbits. b Length distribution of lncRNAs and protein-coding transcripts. c Exon number distribution per the transcript of lncRNAs and protein-coding transcripts. d ORF number distribution per the transcript of lncRNAs and protein-coding transcripts. ORF, open reading frames.","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/67fdf6af1c68b7b05b8b02a6.png"},{"id":5188043,"identity":"2b664acc-bb38-45a3-81d7-dbc861927d50","added_by":"auto","created_at":"2021-01-22 14:58:41","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":89474,"visible":true,"origin":"","legend":"Heatmaps of differentially expressed lncRNAs and mRNAs between HWP and LWP rabbits. a lncRNAs. b mRNAs. “L” and “H” represent low wool production and high wool production groups, respectively. “Red” and “blue” indicate up-regulated and down-regulated transcripts, respectively. HWP, High wool production; LWP, Low wool production.","description":"","filename":"OnlineFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/14886c8fbb8d4dc6638c42fa.png"},{"id":5188041,"identity":"b2124243-e5c1-40c7-893c-5b516e89e89e","added_by":"auto","created_at":"2021-01-22 14:58:41","extension":"tif","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":485154,"visible":true,"origin":"","legend":"GO enrichment analysis of cis-regulated target genes. a GO analysis of lncRNA co-location mRNAs according to biological process b GO analysis of lncRNA co-expression mRNAs according to biological process. The hierarchical category of the GO terms is biological process. The significance of enrichment of each GO term was assessed by P-value \u003c 0.05, and GO terms were subsequently filtered by the enrichment scores (-LgP-value). ","description":"","filename":"Figure4.tif","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/5c353833496e2c358724f6ec.tif"},{"id":5188184,"identity":"e4f4db9d-7f6c-4364-88ae-059f8e18f0e9","added_by":"auto","created_at":"2021-01-22 15:04:40","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":77307,"visible":true,"origin":"","legend":"KEGG pathway enrichment analysis of the cis-regulated target genes. a Pathway enrichment for lncRNA co-location mRNAs. b Pathway enrichment for lncRNA co-expression mRNAs. The dot plots present the enrichment of these mRNAs in every pathway. The colour of each dot corresponds to the P-value which indicates the significant level of change of each pathway. The size of each dot shows the number of mRNAs involved in the corresponding pathway. The horizontal axis represents the enrichment level of the pathways. ","description":"","filename":"OnlineFigure5.png","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/646e44243cb83b8665d16c20.png"},{"id":5188136,"identity":"c3211eb9-e0a8-4dd2-8448-25a6a2ef8690","added_by":"auto","created_at":"2021-01-22 15:01:41","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":195379,"visible":true,"origin":"","legend":"Regulatory networks between lncRNA and mRNA. The purple ellipse represents mRNAs targeted by lncRNAs, the rectangle represents lncRNAs, and the green ellipse represents pathways enriched by mRNAs.","description":"","filename":"OnlineFigure6.png","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/4c191efa8141254acf1dc223.png"},{"id":5188127,"identity":"e5512088-2cbf-4fb4-871d-9511f54f9b1c","added_by":"auto","created_at":"2021-01-22 15:01:40","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":31751,"visible":true,"origin":"","legend":"Validation of DE lncRNAs and mRNAs by q-PCR. a LNC_000797 b LNC_013595 c LNC_020367 d KRTAP15-1 e TCHHL1 f ALOX15B. The black and grey columns represent the q-PCR and sequencing results, respectively. LWP represents Wan strain Angora rabbits with low wool production; HWP represents Wan strain Angora rabbits with high wool production. FPKM, fragments per kilobase of transcript per million fragments mapped. DE lncRNAs, differentially expressed lncRNAs. q-PCR, quantitative real-time polymerase chain reaction. GAPDH was used as a reference gene to normalize q-PCR data. Bars represent the standard error. **P \u003c 0.01, *P \u003c 0.05.","description":"","filename":"OnlineFigure7.png","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/5666a1bd255ee623adde4534.png"},{"id":13650459,"identity":"95ca5874-4272-4701-ba20-a731023cd1d4","added_by":"auto","created_at":"2021-09-17 09:41:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":11439046,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/89f8ce04-6284-4760-a445-47ace7ae70b4.pdf"},{"id":5188126,"identity":"9edeaaef-ef6e-48cf-95ab-96624cbc8356","added_by":"auto","created_at":"2021-01-22 15:01:40","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":122055,"visible":true,"origin":"","legend":"","description":"","filename":"AuthorChecklist.pdf","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/f9a9ad7dee05a26371286788.pdf"},{"id":5188124,"identity":"2b0b373b-4d52-419d-89bd-840b67ed0737","added_by":"auto","created_at":"2021-01-22 15:01:40","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":24855,"visible":true,"origin":"","legend":"","description":"","filename":"checklists.docx","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/e4728f6e85543f9d39c5d4b1.docx"},{"id":5188123,"identity":"1cbb8c5c-4343-4191-b1cb-8f08cc65676a","added_by":"auto","created_at":"2021-01-22 15:01:40","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":18866,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryData2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/562e30fc63bd3f28f12afb39.xlsx"},{"id":5188040,"identity":"b86c286a-ebbd-4350-b53b-bbd3c89b4a00","added_by":"auto","created_at":"2021-01-22 14:58:41","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":398975,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryData1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/41811e0962cc7f53a25f6975.xlsx"},{"id":5188047,"identity":"372acde3-5988-4bc1-8535-879ecf8df45d","added_by":"auto","created_at":"2021-01-22 14:58:42","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":108899,"visible":true,"origin":"","legend":"Additional file 1: Table S1. The analyses of reads mapped to the Rabbit reference genome.","description":"","filename":"Additionalfile1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/f51957834aaf77bab8ebacf9.pdf"},{"id":5188187,"identity":"1545b9ba-7e2e-490d-8902-75d471fb7347","added_by":"auto","created_at":"2021-01-22 15:04:42","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":403911,"visible":true,"origin":"","legend":"Additional file 2: Table S2. List of 22136 annotated lncRNA. ","description":"","filename":"Additionalfile2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/fb48afb0a9a8dfd0cc7b0e65.xlsx"},{"id":5188039,"identity":"b77180bb-7efd-4c6b-adcf-a63dbcc1a191","added_by":"auto","created_at":"2021-01-22 14:58:41","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":100956,"visible":true,"origin":"","legend":"Additional file 3: Figure S1. Expression level analysis of the lncRNAs and protein-coding genes.","description":"","filename":"Additionalfile3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/4156abe9f1ab70fb71eab020.pdf"},{"id":5188042,"identity":"dfca3dee-1de8-422e-bb61-a0accaf7c4da","added_by":"auto","created_at":"2021-01-22 14:58:41","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":18621,"visible":true,"origin":"","legend":"Additional file 4: Table S3, Table S4. Differentially expressed lncRNAs and genes between the LWP and HWP groups, respectively. HWP, High wool production; LWP, Low wool production.","description":"","filename":"Additionalfile4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/84e7459f1000552c1c57dc26.xlsx"},{"id":5188137,"identity":"b8658892-070f-4931-bec0-bbd3e2bdcfaf","added_by":"auto","created_at":"2021-01-22 15:01:42","extension":"pdf","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":86505,"visible":true,"origin":"","legend":"Additional file 5: Table S5. The wool production of the rabbits. “L” and “H” represent low wool production and high wool production groups, respectively.","description":"","filename":"Additionalfile5.pdf","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/df3becbcfb9f02858e542330.pdf"},{"id":5188212,"identity":"f376cfd6-5daf-4a24-907f-0f4bb2ba9b8f","added_by":"auto","created_at":"2021-01-22 15:07:40","extension":"pdf","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":93019,"visible":true,"origin":"","legend":"Additional file 6: Table S6. Primers for q-PCR. F1, forward primer. R2, reverse primer.","description":"","filename":"Additionalfile6.pdf","url":"https://assets-eu.researchsquare.com/files/rs-43570/v3/5faac4072dc36509dd43476f.pdf"}],"financialInterests":"","formattedTitle":"Analysis of histology and long noncoding RNAs involved in the rabbit hair follicle density using RNA sequencing","fulltext":[{"header":"Background","content":"\u003cp\u003eThe Angora rabbit is an economically important livestock breed in several countries, especially in China and France. Wool production is one of the most important traits in Angora rabbits. The fur quality of rabbits is largely dependent on hair density, and hair follicle density determines hair density\u0026nbsp;[1, 2].\u0026nbsp;For Angora rabbits under the same environmental conditions, gender, body site, and the month of age are closely related to wool fibre production\u0026nbsp;[3]. Genetic factors that influence wool fibre production are fibre diameter, length, fineness, and the fibre density [3-7].\u0026nbsp;The mean hair follicle density depends on the skin area.\u0026nbsp;The development of wool follicles occurs during\u0026nbsp;prenatal\u0026nbsp;life and no new hair follicles are formed after birth, implying that hair density in an adult rabbit will depend on how much that particular body part grows after the formation of the hair follicles [7, 8]. Correspondingly, hair follicle density and other wool characteristics are highly variable over the human and rabbit body [7, 9, 10]. The molecular mechanism underlying hair follicle density in rabbit skin and hair follicle development remains unclear.\u003c/p\u003e\n\u003cp\u003eHair follicle development is a complex morphogenetic process and undergoes periodic stages of growth (anagen), regression (catagen), and relative quiescence (telogen) [11-13]. The process of hair follicle formation and differentiation relies on many regulating molecules including\u0026nbsp;messenger RNAs (mRNAs) and micro RNAs (miRNAs)\u0026nbsp;[14-16],\u0026nbsp;as well as a variety of signalling systems, such as the Wnt, Notch, bone morphogenetic protein (BMP), and fibroblast growth factor (FGF) pathways\u0026nbsp;[17-22]. LncRNAs are RNA transcripts\u0026nbsp;longer than 200 nucleotides that lack open reading frames (ORF) and\u0026nbsp;protein-coding capabilities\u0026nbsp;[23].\u0026nbsp;They regulate protein-coding gene expression at\u0026nbsp;posttranscriptional and transcriptional levels\u0026nbsp;[24, 25]. It is generally known that lncRNAs are also involved in the regulation of the hair follicle development and skin homeostasis [26-28].\u0026nbsp;RP11-766N7.3, H19 and HOTAIR are specific lncRNAs that are involved in Wnt signalling to regulate hair follicle development [29]. Strand-specific RNA sequencing (ssRNA-seq) also showed that lncRNAs may be considered as potential candidate markers for further study on the molecular mechanisms of hair follicle initiation [30]. However, hair follicle density-related lncRNAs in rabbits have not been profiled so far.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this study, the RNA-seq based approach was used to determine lncRNA expression levels in Angora rabbits with high wool production (HWP) and low wool production (LWP) after hair follicle density analysis. The results should provide fundamental resources to reveal the regulatory function of lncRNAs in hair follicle density in rabbits, as well as supply information for understanding human hair disorders such as hypotrichosis.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eComparison of hair follicle density in high and low wool production rabbits\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo characterize the hair follicle density, the follicle densities of the backs, abdomens, sides, and hips of Wan strain Angora rabbits\u0026nbsp;with HWP and LWP were compared (Fig. 1).\u0026nbsp;A morphological analysis showed that the hair follicle densities of backs, abdomens, sides, and hips\u0026nbsp;were higher\u0026nbsp;in the\u0026nbsp;HWP group (Fig. 1a, b, c, d) than in the LWP group (Fig. 1e, f, g, h). The results demonstrate that a high hair follicle density leads to high wool production in\u0026nbsp;Wan strain Angora rabbits.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSequencing and assembly\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEight libraries of the HWP groups (H1, H2, H3, and H4) and LWP groups (L1, L2, L3, and L4) were constructed. For the HWP and LWP libraries, above 84,456,770 and 94,769,312 clean reads per sample were obtained, respectively (Table 1). Above 89.19% and 89.02% of the reads were aligned with the rabbit reference genome uniquely located by above 77.55% and 75.67% of the clean reads\u0026nbsp;for the HWP and LWP libraries, respectively. Above 17,380,601 (52.78%) and 21,898,377 (46.66%) reads, respectively, were identified as protein-coding mRNAs\u0026nbsp;of the HWP and LWP groups\u0026nbsp;(Additional file 1: Table S1).\u0026nbsp;The other types of reads amounted to 12,349,910 (36.07%) and 16,461,100 (39.19%) for HWP and LWP groups, respectively, and these reads may include lncRNAs (Additional file 1: Table S1).\u003c/p\u003e\n\u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:200%;'\u003e\u003cspan style='font-family:\"DnyvssAdvTT86d47313\",serif;color:#131413;'\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;line-height:200%;font-family:\"Times New Roman\",serif;'\u003eTable 1.\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003cspan style='font-family:\"DnyvssAdvTT86d47313\",serif;color:#131413;'\u003e\u003cspan style='font-size:15px;line-height:200%;font-family:\"Times New Roman\",serif;'\u003eThe analyses of reads mapped to the rabbit reference genome\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cdiv align=\"center\" style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\n \u003ctable style=\"width:458.85pt;border-collapse:collapse;border:none;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:67.8pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003eSample name\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border-top:solid windowtext 1.5pt;border-left: none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003eH1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border-top:solid windowtext 1.5pt;border-left: none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003eH2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003eH3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border-top:solid windowtext 1.5pt;border-left: none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003eH4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003eL1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border-top:solid windowtext 1.5pt;border-left: none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003eL2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003eL3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:51.45pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003eL4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:67.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003eTotal reads\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e95,426,664\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e84,456,770\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e149,301,000\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e89,038,716\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e123,865,064\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e94,769,312\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e109,570,388\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:51.45pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e130,245,954\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:67.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003eTotal mapped\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e85,943,449 (90.06%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e75,328,473 (89.19%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e133,972,487 (89.73%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e79,823,704 (89.65%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e110,263,589 (89.02%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e84,819,962 (89.5%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e99,272,110 (90.6%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:51.45pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e117,162,667 (89.95%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:67.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003eMultiple mapped\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e11,938,587 (12.51%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e9,315,870 (11.03%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e13,827,931 (9.26%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e10,659,938 (11.97%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e16,534,984 (13.35%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e9,777,660 (10.32%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e14,500,967 (13.23%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:51.45pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e11,066,700 (8.5%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:67.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003eUniquely mapped\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e74,004,862 (77.55%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e66,012,603 (78.16%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e120,144,556 (80.47%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e69,163,766 (77.68%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e93,728,605 (75.67%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e75,042,302 (79.18%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e84,771,143 (77.37%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:51.45pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e106,095,967 (81.46%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:67.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003eReads map to \u0026apos;+\u0026apos;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e36,872,804 (38.64%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e32,897,302 (38.95%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e60,000,375 (40.19%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e34,636,589 (38.9%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e46,454,860 (37.5%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e37,454,686 (39.52%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e42,357,439 (38.66%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:51.45pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e52,928,464 (40.64%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:67.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003eReads map to \u0026apos;-\u0026apos;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e37,132,058 (38.91%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e33,115,301 (39.21%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e60,144,181 (40.28%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e34,527,177 (38.78%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e47,273,745 (38.17%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e37,587,616 (39.66%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e42,413,704 (38.71%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:51.45pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e53,167,503 (40.82%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:67.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003eNon-splice reads\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e56,778,516 (59.5%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e51,943,073 (61.5%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e89,625,539 (60.03%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e51,395,189 (57.72%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e74,099,166 (59.82%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e57,787,882 (60.98%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e65,280,836 (59.58%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:51.45pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e79,655,006 (61.16%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:67.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003eSplice reads\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e17,226,346 (18.05%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e14,069,530 (16.66%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e30,519,017 (20.44%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e17,768,577 (19.96%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e19,629,439 (15.85%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e17,254,420 (18.21%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e19,490,307 (17.79%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:51.45pt;border:none;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e26,440,961 (20.3%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:67.8pt;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003eReads mapped in proper pairs\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e69,994,050 (73.35%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e62,138,530 (73.57%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e113,304,356 (75.89%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e65,315,796 (73.36%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e88,424,106 (71.39%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:.65in;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e70,592,926 (74.49%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:50.8pt;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e80,480,580 (73.45%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:51.45pt;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-size:11px;line-height:150%;font-family:\"Times New Roman\",serif;color:#262626;'\u003e100,326,142 (77.03%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;line-height:150%;'\u003e\u003cspan style='font-family:\"DnyvssAdvTT86d47313\",serif;color:#131413;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;line-height:150%;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacterization of lncRNAs in rabbit skin tissue\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe RNA-seq analysis produced 22,136 lncRNAs (Additional file 2: Table S2). The lncRNA transcripts included 10,692 lincRNAs (48.3%), 2,612 antisense lncRNAs (11.8%), and 8,832 intronic lncRNAs (39.9%) (Fig. 2a). The average length of the novel lncRNAs was considerably shorter than the mRNAs, but longer than the known lncRNAs (Fig. 2b). The exon numbers of the novel lncRNAs were less than the mRNAs while greater than the known lncRNAs (Fig. 2c). In addition, ORF size in novel lncRNAs was longer than that in annotated lncRNAs, but shorter than that in protein-coding genes\u0026nbsp;(Fig. 2d).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLong noncoding RNAs and mRNAs expression profiles in rabbit skin tissue\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results showed that the expression levels of mRNAs were higher than those of lncRNAs (Additional file 3: Figure S1).\u0026nbsp;50 and 38 differentially expressed (DE) lncRNAs and genes, respectively, were screened in the LWP and HWP groups (Additional file 4:\u0026nbsp;Table S3, Table S4). Of these lncRNAs and genes, 15 lncRNAs and 21 genes were upregulated, and 35 lncRNAs and 17 genes were downregulated in the LWP group. Hierarchical cluster analysis of lncRNA and mRNA expression levels between LWP and HWP groups revealed distinct expression patterns (Fig. 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLong noncoding RNA target prediction and functional analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe potential target genes of lncRNAs were predicted accordingly their position (co-location) and expression correlation (co-expression) with the protein-coding genes. Gene ontology (GO) analysis was applied to investigate the potential functions of the lncRNAs\u0026rsquo; co-location and co-expression mRNAs on the regulation of hair follicle development and wool production (Fig. 4). The significance of enrichment of each GO term was assessed by \u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.05, and then the GO terms were filtered by the enrichment scores (-Lg\u003cem\u003e\u0026nbsp;P\u003c/em\u003e-value). The GO enrichment analysis showed that the lncRNAs\u0026rsquo; co-location mRNAs were significantly enriched in phospholipid, lipid metabolic, and epithelial cell apoptotic processes\u0026nbsp;in the biological process category\u0026nbsp;(Fig. 4a), while co-expression mRNAs were significantly enriched in the cellular metabolic, lipoprotein, lipid biosynthetic, lipid, and fatty acid transport processes (Fig. 4b).\u0026nbsp;The Kyoto Encyclopedia of Genes and Genomes (KEGG)\u0026nbsp;pathway analysis offered a reliable way of elucidating the candidate biological pathways that the integrated target genes were enriching.\u0026nbsp;The cytokine-cytokine receptor interaction,\u0026nbsp;chemokine signalling pathway and\u0026nbsp;JAK-STAT signalling pathway were significantly involved in lncRNAs\u0026rsquo; co-location mRNAs (Fig. 5a). In addition, pathways related to the biosynthesis of amino acids,\u0026nbsp;arginine and proline metabolism,\u0026nbsp;ether lipid metabolism, and the hedgehog signalling pathway were highly enriched by lncRNAs\u0026rsquo; co-expression mRNAs (Fig. 5b). Therefore, the target genes of the DE lncRNAs between the LWP and HWP groups were related to lipid metabolism, amino acid synthesis, JAK-STAT, and the hedgehog signalling pathway. According to the functional enrichment analyses, five DE lncRNAs (LNC_002171, LNC_000797, LNC_005567, LNC_013595, and LNC_020367) were selected to construct regulatory networks (Fig. 6). LNC_002171 and LNC_000797 were involved in JAK-STAT and the hedgehog signalling pathway.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eValidation of DE lncRNAs and mRNAs with quantitative real-time polymerase chain reaction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo validate the RNA-Seq results, LNC_000797, LNC_013595, LNC_020367,\u0026nbsp;\u003cem\u003eKRTAP15-1\u003c/em\u003e, \u003cem\u003eTCHHL1\u003c/em\u003e, and \u003cem\u003eALOX15B\u003c/em\u003e were selected and their expression patterns in the LWP and HWP groups were examined by q-PCR. The results showed that the three DE lncRNAs and mRNAs were differentially expressed in the LWP and HWP groups. In addition, they exhibited a similar trend in the results of the RNA-seq and the q-PCR (Fig. 7). Therefore, the fragments per kilobase of transcript per million mapped reads (FPKM) obtained from RNA-seq could be reliably used to determine lncRNA and mRNA expression in the LWP and HWP groups.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWool density is one of the most important indices to evaluate the quality of the fur of the\u0026nbsp;Wan strain Angora rabbit\u0026nbsp;[6]. Hair follicle density determines wool density [1]. The quality of fur is associated mainly with the traits of the hair follicles\u0026nbsp;[31].\u0026nbsp;To characterize the hair follicle density, the follicle density of the backs, abdomens, sides, and hips of Wan Strain Angora rabbits\u0026nbsp;with HWP and LWP was compared (Fig. 1).\u0026nbsp;A morphological analysis showed that the hair follicle density of backs, abdomens, sides, and hips of the\u0026nbsp;HWP group was higher compared to the LWP group (Fig. 1). The results demonstrated that high hair follicle density contributed to high wool production in\u0026nbsp;the Wan strain Angora rabbit.\u0026nbsp;In French Angora rabbits, divergent selection of total fleece weight led to a positive difference of 0.55 genetic standard deviation for secondary to primary follicle ratio (S/P), although a low genetic correlation existed between them\u0026nbsp;[32].\u003c/p\u003e\n\u003cp\u003eThe formation of hair follicles is divided into prenatal hair morphogenesis and the postnatal hair cycle [33].\u0026nbsp;Once established during embryogenesis, hair follicle\u0026nbsp;density\u0026nbsp;is permanently fixed in postnatal life, and the hair follicle location eventually becomes fixed as a result of anchoring in the subcutis [34].\u0026nbsp;LncRNAs are widely involved in various biological processes, including the hair follicle cycle [35, 36]. The lncRNA and mRNA expression profiles were compared in the dorsal skin of LWP and HWP rabbits, and 50 and 38 DE lncRNAs and genes were obtained, respectively. These lncRNAs and genes might play crucial roles in regulating hair follicle density, and their differential expression might be the reason for differences in hair follicle density and wool production between HWP and LWP rabbits.\u0026nbsp;Liu et al. (2020) analysed the miRNA effect on hair follicle density in the Rex rabbit\u0026nbsp;[37],\u0026nbsp;but lncRNA related to hair density in rabbits has only been done in the present study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe GO analysis showed that\u0026nbsp;the\u0026nbsp;DE lncRNAs\u0026nbsp;are potential regulators\u0026nbsp;of phospholipid, lipid metabolic, epithelial cell apoptotic, lipid biosynthetic, and lipid and fatty acid transport processes. Keratin-associated proteins (KRTAPs) play a critical role in cross-linking the keratin intermediate filaments to build a hair shaft [38].\u003cem\u003e\u0026nbsp;KRTAP7-1\u003c/em\u003e, \u003cem\u003eKRTAP8-1\u003c/em\u003e, and \u003cem\u003eKRTAP15-1\u003c/em\u003e were predicted as the targets of\u0026nbsp;LNC_005567 in this study.\u0026nbsp;\u003cem\u003eKRTAP7-1\u003c/em\u003e is involved in supporting the mechanical strength and shape of hair [38]. \u003cem\u003eKRTAP15-1\u003c/em\u003e is expressed in secondary follicles in the skin and associated with fibre diameter [39].\u003cem\u003e\u0026nbsp;COL3A1\u003c/em\u003e and \u003cem\u003eLOXL4\u003c/em\u003e were the target genes of LNC_013595 and LNC_020367, respectively. COL3A1 is one of collagens forming different extracellular matrix\u0026nbsp;(ECM)\u0026nbsp;components\u0026nbsp;[40]. The lysyl oxidase like 4 (LOLX4)\u0026nbsp;enzyme is responsible for initiating covalent cross-linking in collagen fibrils\u0026nbsp;and is involved in providing\u0026nbsp;additional mechanical strength to the ECM\u0026nbsp;[41, 42].\u0026nbsp;The amount of ECM per cell contributes to the volume of the dermal papilla [43].\u0026nbsp;Hedgehog\u0026nbsp;and JAK-STAT signalling pathway were significantly enriched by target genes \u003cem\u003eENSOCUG00000021211\u003c/em\u003e and\u0026nbsp;\u003cem\u003eENSOCUG00000023782\u003c/em\u003e of LNC_002171 and LNC_000797, respectively. The hedgehog signalling pathway is correlated to the initiation of hair follicle formation and is a pivotal growth signal for dermal papilla maturation and growth\u0026nbsp;[34, 44, 45]. The\u0026nbsp;JAK-STAT signalling pathway is involved in maintaining the quiescence of hair follicles during telogen [46], and\u0026nbsp;JAK-STAT inhibition contributes to the promotion of hair growth and the activation of hair follicle stem cells [47].\u0026nbsp;These findings demonstrate that\u0026nbsp;LNC_002171, LNC_000797, LNC_005567, LNC_013595, and LNC_020367\u0026nbsp;are potentially important regulators of hair follicle\u0026nbsp;density\u0026nbsp;and development.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTCHHL1 is a hair-specific protein given its high expression in scalp and chin skin\u0026nbsp;[48].\u0026nbsp;TCHHL1 was identified in a genome-wide association study (GWAS)\u0026nbsp;to have a significant association with hair shape within the top-associated\u0026nbsp;single nucleotide polymorphisms (SNPs)\u0026nbsp;(rs17646946), and\u0026nbsp;showed nominally significant association with hair\u0026nbsp;curliness\u0026nbsp;[49].\u0026nbsp;ALOX15B\u0026nbsp;is restricted to terminally differentiating keratinocytes\u0026nbsp;(in particular the stratum granulosum)\u0026nbsp;and 8(S)-lipoxygenase activity seems to be involved in terminal differentiation of mouse\u0026nbsp;epidermis\u0026nbsp;[50]. Clements et al. (2012) identified reduced expression of\u0026nbsp;\u003cem\u003eALOX15B\u003c/em\u003e gene in ankyloblepharon\u0026ndash;ectodermal defects\u0026ndash;clefting (AEC)\u0026nbsp;syndrome skin,\u0026nbsp;with downregulated\u0026nbsp;genes (\u003cem\u003eKRT25\u003c/em\u003e and \u003cem\u003eKRT27\u003c/em\u003e)\u0026nbsp;encoding keratins involved in the morphogenesis of hair\u0026nbsp;follicles\u0026nbsp;[51].\u0026nbsp;Thus,\u0026nbsp;in combination with the current research,\u0026nbsp;three genes may participate in\u0026nbsp;the\u0026nbsp;regulation of hair follicle density in\u0026nbsp;Angora rabbits. The results of\u0026nbsp;q-PCR of LNC_000797, LNC_013595, LNC_020367,\u0026nbsp;\u003cem\u003eKRTAP15-1\u003c/em\u003e, \u003cem\u003eTCHHL1\u003c/em\u003e, and \u003cem\u003eALOX15B\u003c/em\u003e showed similar expression patterns between RNA-Seq and q-PCR, demonstrating the reliability of these data.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, differences in the histology and lncRNA profiles of skin were identified in HWP and LWP rabbits. The histological analysis showed a higher hair follicle density in HWP rabbits. The analyses of lncRNA profiles identified candidate lncRNAs involved in lipid metabolism, apoptosis, and hair follicle development. Further studies are required to investigate the roles of candidate lncRNAs in hair follicle density to improve rabbit breeding programmes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eAnimals\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animals were procured from the\u0026nbsp;rabbit farm and acquired an approval from the farm owner in the\u0026nbsp;Animal\u0026nbsp;Husbandry and Veterinary Medicine\u0026nbsp;Institute of Anhui Academy of Agriculture Sciences, Hefei, Anhui, China. 60 Wan Strain Angora rabbits (about one year old) were reared in the same conditions with regular pellets and water \u003cem\u003ead libtum.\u0026nbsp;\u003c/em\u003eThe wool weight of five successive collections\u0026nbsp;using electric shears\u0026nbsp;in one year from adult rabbits were determined. The sixty rabbits were divided into two populations designated as high wool production (HWP) and low wool production (LWP) according to wool production. The average wool weights showed remarkable difference (HWP: 401.3 \u0026plusmn; 36.5 g vs LWP: 314.4 \u0026plusmn; 29.2 g, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001). Finally, four rabbits with high and low wool production (430.1 \u0026plusmn; 16.5 g vs 291.6 \u0026plusmn; 13.3 g, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.0001) were selected for the present study, respectively (Additional file 5: Table S5).\u0026nbsp;The 52 remaining rabbits were reared like ordinary rabbits for wool production.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample collection, preparation for histological examination\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe eight rabbits selected (four rabbits with high wool production, four rabbits with low wool production) were anesthetized by injecting 0.7% pentobarbital sodium (6 ml/kg) into ear vein of the rabbits before sampling. Skin tissue samples (1 cm\u003csup\u003e2\u003c/sup\u003e) were collected from the\u0026nbsp;backs, abdomens, sides and hips\u0026nbsp;at the fourth week after plucking for histological analysis.\u0026nbsp;Each skin sample was cut apart into two and then one piece was prepared and then subjected to histological analysis as our previous study\u0026nbsp;[14].\u0026nbsp;The iodine solution was smeared on the resultant lesion to prevent bacterial infection. After the experiment, the rabbits were retained in the rabbit farm\u0026nbsp;and reared and protected from external stimuli.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ecDNA library construction and sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnder anesthesia, skin samples from the back of the eight rabbits selected (four rabbits with high wool production and four rabbits with low wool production;\u0026nbsp;430.1 \u0026plusmn; 16.5 g vs 291.6 \u0026plusmn; 13.3 g, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001) were collected at the fourth week after plucking for RNA-seq. The skin samples were firstly frozen in liquid nitrogen immediatelly after cutting and then stored at -80℃\u0026nbsp;before RNA extration. Whole RNA was extracted from the skin of HWP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; rabbits (designated as H1, H2, H3, and H4) and LWP rabbits (designated as L1, L2, L3, and L4) using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer\u0026rsquo;s instructions. The samples were sent to the Beijing Novogene Co., LTD with drikold. The purity and integrity of RNA was evaluated using the NanoPhotometer spectrophotometer (Implen, CA, USA) and Agilent 2100 Bioanalyzer (Agilent Technologies, CA, USA). The RNA was purified by removing rRNA, fragmented randomly, and converted to double cDNA, then were ligated with NEBNext adaptors. Finally, eight libraries were created by PCR using the NEBNext\u0026reg; Ultra\u0026trade; Directional RNA Library Prep Kit (NEB, USA), quantified with Qubit2.0, and sequenced on an Illumina HiSeq 2500 platform (Illumina, San Diego, CA, USA).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMapping, assembling and screening\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eImpurity data were removed from the raw reads and more than 12 Gb clean reads per sample were generated. The clean reads with high quality were then aligned using HISAT2 to the rabbit reference genome (https://www.ncbi.nlm.nih.gov/genome/?term=Rabbit) sequence. The mapped reads of each sample were assembled by StringTie (v2.0.4) \u0026nbsp;[52]. The candidate lncRNAs were distinguished according to its sequence charecteristics (length\u0026gt;200 nt and noncoding potential) and meantime transcripts predicted with coding potential were filtered out by multiple tools. Conservative and comparative analyses were done between lncRNAs and mRNAs, and classification of lncRNAs was also analyzed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantification, target prediction and function analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe expression levels of the lncRNAs and mRNAs in each sample were calculated by fragments per kilobase of transcript per million fragments mapped (FPKM). Differential expression between LWP and HWP groups was analyzed by using cuffdiff (https://www.genepattern.org/modules/docs/Cuffdiff/7), and the threshold was set as |log2 (Fold Change)|\u0026nbsp;\u0026ge;\u0026nbsp;1 and \u003cem\u003eP\u003c/em\u003e value \u0026lt; 0.05. Target prediction was conducted by searching coding genes 100 kb up- and down-stream of lncRNAs (co-location) and analyzing co-expression relationship (pearson correlation) of mRNAs to lncRNAs. Then, GO\u0026nbsp;and KEGG\u003csup\u003e\u0026nbsp;\u003c/sup\u003eenrichment analyses were performed on targets and the function of key lncRNAs were predicted.\u0026nbsp;GOseq R package [53] and KOBAS\u0026nbsp;(http://www.genome.jp/kegg/) were used to conduct\u0026nbsp;GO\u0026nbsp;and KEGG\u003csup\u003e\u0026nbsp;\u003c/sup\u003eenrichment analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative real-time polymerase chain reaction\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThree candidate lncRNAs and mRNAs were selected from the list of DE lncRNAs and DEGs for validation, and the relative expression level was determined by q-PCR on LightCycler 96 (Roche, Switzerland) using TransStart Green qPCR SuperMix (Transgen, Beijing, China) as our previous study\u0026nbsp;[14]. The primers for q-PCR are listed in\u0026nbsp;Additional file 6: Table S6. The reaction was performed in triplicates for each sample (HWP group: H1, H2, H3, and H4; LWP group: L1, L2, L3, and L4). The 2\u003csup\u003e-\u0026Delta;\u0026Delta;CT\u003c/sup\u003e method was used to determine the relative expression level of each gene.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudent\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test with\u0026nbsp;two-sided\u0026nbsp;was used in statistical comparisons in wool weight between HWP and LWP groups and RNA expression. Error bars represent the mean \u0026plusmn; standard deviation (SD) as determined using GraphPad Prism 5 (GraphPad Sofware, Inc., La Jolla, CA, USA). A \u003cem\u003eP\u003c/em\u003e value \u0026lt; 0.05 were considered the criterion for statistical significance.\u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBMP: Bone morphogenetic protein; DE: Differentially expressed; ECM: Extracellular matrix; FDR: False discovery rate; FGF: Fibroblast growth factor; FPKM: Fragments per kilobase of transcript per million fragments mapped; GO: Gene Ontology; HE: Haematoxylin-eosin; HWP: High wool production; JAK: Janus kinase; KEGG: Kyoto Encyclopedia of Genes and Genomes; lncRNA: long noncoding RNA; LWP: Low wool production; ORF: Open reading frames; q-PCR: Quantitative real-time polymerase chain reaction; SD: Standard deviation; ssRNA-seq: Strand-specific RNA sequencing; STAT: signal transducer and activator of transcription;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the earmarked fund for China Agriculture Research System (Grant No.: CARS-43-A-4)\u0026nbsp;and\u0026nbsp;Anhui Provincial Natural Science Foundation (Grant No.: 2008085QC137).\u0026nbsp;These funding bodies had no role in the design of the study, sample collection, analysis or interpretation of data and in writing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data was presented in the manuscript and the supporting materials. The raw reads data was submitted to the Short Read Archive (SRA) under the accession number SRP299630 and BioProject accession number \u003ca href=\"https://dataview.ncbi.nlm.nih.gov/object/PRJNA688082\"\u003ePRJNA688082\u003c/a\u003e (https://www.ncbi.nlm.nih.gov/sra/PRJNA688082).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u003c/strong\u003e\u003cstrong\u003e\u0026acute;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003econtributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHLZ, DWH, and HSD conceived the study. HLZ, DWH, and XFW performed sample collection and total RNA preparation. XWZ and YXQ performed the q-PCR validation. HSD and DWH conducted the data analysis and prepared figures and tables. HSD and DWH wrote the manuscript.\u0026nbsp;All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study was carried out in strict accordance with relevant guidelines and regulations by the Ministry of Agriculture of the People\u0026rsquo;s Republic of China. All experimental protocols were approved by the Ethics Committee of Anhui Academy of Agricultural Sciences.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePaus R, Cotsarelis G. The biology of hair follicles. 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Sci Rep. 2017;7(1):2499.\u003c/li\u003e\n\u003cli\u003eStenn KS, Paus R. Controls of hair follicle cycling. Physiol Rev. 2001;81(1):449\u0026ndash;494.\u003c/li\u003e\n\u003cli\u003eTamura Y, Takata K, Eguchi A, Kataoka Y. In vivo monitoring of hair cycle stages via bioluminescence imaging of hair follicle NG2 cells. Sci Rep. 2018;8(1):393.\u003c/li\u003e\n\u003cli\u003eSchneider MR, Ruth SU, Ralf P. The hair follicle as a dynamic miniorgan. Curr Biol. 2009;19(3):R132\u0026ndash;R142.\u003c/li\u003e\n\u003cli\u003eDing H, Zhao H, Cheng G, Yang Y, Wang X, Zhao X, et al. Analyses of histological and transcriptome differences in the skin of short-hair and long-hair rabbits. BMC genomics. 2019;20(1):140.\u003c/li\u003e\n\u003cli\u003eZhao B, Chen Y, Yan X, Hao Y, Zhu J, Weng Q, et al. Gene expression profiling analysis reveals fur development in rex rabbits (Oryctolagus cuniculus). 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BMC Biol. 2013;11(1):59.\u003c/li\u003e\n\u003cli\u003eWang S, Ge W, Luo Z, Guo Y, Jiao B, Qu L, et al. Integrated analysis of coding genes and non-coding RNAs during hair follicle cycle of cashmere goat ( Capra hircus ). BMC Genomics. 2017;18(1):767.\u003c/li\u003e\n\u003cli\u003eSong S, Yang M, Li Y, Rouzi M, Zhao Q, Pu Y, et al. Genome-wide discovery of lincRNAs with spatiotemporal expression patterns in the skin of goat during the cashmere growth cycle. BMC Genomics. 2018;19(1):495.\u003c/li\u003e\n\u003cli\u003eZhu YB, Wang ZY, Yin RH, Jiao Q, Zhao SJ, Cong YY, et al. A lncRNA-H19 transcript from secondary hair follicle of Liaoning cashmere goat: Identification, regulatory network and expression regulated potentially by its promoter methylation. Gene. 2018;641:S0378111917308533.\u003c/li\u003e\n\u003cli\u003eChang-Min L, Yang L, Keng H, Xian-Cai C, Bo-Zhi C, Hai-Hong L, et al. Long noncoding RNA expression in dermal papilla cells contributes to hairy gene regulation. Biochem Biophys Res Commun. 2014;453(3):508\u0026ndash;514.\u003c/li\u003e\n\u003cli\u003eYue Y, Guo T, Yuan C, Liu J, Guo J, Feng R, et al. Integrated analysis of the roles of long noncoding RNA and coding RNA expression in sheep (Ovis aries) skin during initiation of secondary hair follicle. PLoS One. 2016;11(6):e0156890.\u003c/li\u003e\n\u003cli\u003eChen S, Liu T, Liu Y, Dong B, Gu Z. Gene Expression Patterns in Different Wool Densities of Rex Rabbit Using cDNA Microarray. Agr Sci China. 2011;10(4):595\u0026ndash;601.\u003c/li\u003e\n\u003cli\u003eRafat SA, Rochambeau HD, Th\u0026eacute;bault RG, David I, Deretz S, Bonnet M, et al. Divergent selection for total fleece weight in Angora rabbits: Correlated responses in wool characteristics. Livest Sci. 2008;113(1):0\u0026ndash;13.\u003c/li\u003e\n\u003cli\u003eChoi BY. Hair-growth potential of ginseng and its major metabolites: a review on its molecular mechanisms. Int J Mol Sci. 2018;19(9).\u003c/li\u003e\n\u003cli\u003eSchneider MR, Schmidt-Ullrich R, Paus R. The hair follicle as a dynamic miniorgan. Curr Biol. 2009;19(3):R132-R142.\u003c/li\u003e\n\u003cli\u003eLin CM, Liu Y, Huang K, Chen XC, Cai BZ, Li HH, et al. Long noncoding RNA expression in dermal papilla cells contributes to hairy gene regulation. Biochem Bioph Res Co. 2014;453(3):508\u0026ndash;514.\u003c/li\u003e\n\u003cli\u003eZhao B, Chen Y, Hu S, Yang N, Wang M, Liu M, et al. Systematic analysis of non-coding RNAs involved in the angora rabbit (Oryctolagus cuniculus) hair follicle cycle by RNA sequencing. Front Genet. 2019;10:407.\u003c/li\u003e\n\u003cli\u003eLiu G, Li S, Liu H, Zhu Y, Bai L, Sun H, et al. The functions of ocu-miR-205 in regulating hair follicle development in Rex rabbits. BMC Dev Biol. 2020;20(1):8.\u003c/li\u003e\n\u003cli\u003eArlud S, He N, Sari EM, Ma ZJ, Zhang H, An TW, et al. Highly conserved keratin-associated protein 7-1 gene in yak, taurine and zebu cattle. Folia biol. 2017;63(4):139\u0026ndash;145.\u003c/li\u003e\n\u003cli\u003eZhao M, Zhou H, Hickford JGH, Gong H, Wang J, Hu J, et al. Variation in the caprine keratin-associated protein 15-1 (KAP15-1) gene affects cashmere fibre diameter. Arch Anim Breed. 2019;62(1):125\u0026ndash;133.\u003c/li\u003e\n\u003cli\u003eLi B, Qiao L, An L, Wang W, Liu J, Ren Y, et al. Transcriptome analysis of adipose tissues from two fat-tailed sheep breeds reveals key genes involved in fat deposition. BMC genomics. 2018;19(1):338.\u003c/li\u003e\n\u003cli\u003eClarke DL, Carruthers AM, Mustelin T, Murray LA. Matrix regulation of idiopathic pulmonary fibrosis: the role of enzymes. Fibrogenesis Tissue Repair. 2013;6(1):20.\u003c/li\u003e\n\u003cli\u003eLeask A. Matrix remodeling in systemic sclerosis. Semin Immunopathol. 2015;37(5):559\u0026ndash;563.\u003c/li\u003e\n\u003cli\u003eElliott K, Stephenson TJ, Messenger AG. Differences in hair follicle dermal papilla volume are due to extracellular matrix volume and cell number: implications for the control of hair follicle size and androgen responses. J Invest Dermatol. 2000;113(6):873\u0026ndash;877.\u003c/li\u003e\n\u003cli\u003eChiang C, Swan RZ, Grachtchouk M, Bolinger M, Litingtung Y, Robertson EK, et al. Essential role for Sonic hedgehog during hair follicle morphogenesis. Dev Biol. 1999;205(1):1\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eSt-Jacques B, Dassule HR, Karavanova I, Botchkarev VA, Li J, Danielian PS, et al. Sonic hedgehog signaling is essential for hair development. Curr Biol. 1998;8(19):1058-1068.\u003c/li\u003e\n\u003cli\u003eWang E, Harel S, Christiano AM. JAK-STAT signaling jump starts the hair cycle. J Invest Dermatol. 2016;136(11):2131\u0026ndash;2132.\u003c/li\u003e\n\u003cli\u003eHarel S, Higgins CA, Cerise JE, Dai Z, Chen JC, Clynes R, et al. Pharmacologic inhibition of JAK-STAT signaling promotes hair growth. Sci Adv. 2015;1(9):e1500973.\u003c/li\u003e\n\u003cli\u003eLiu F, Chen Y, Zhu G, Hysi PG, Wu S, Adhikari K, et al. Meta-analysis of genome-wide association studies identifies 8 novel loci involved in shape variation of human head hair. Hum Mol Genet. 2018;27(3):559\u0026ndash;575.\u003c/li\u003e\n\u003cli\u003eWu Z, Latendorf T, Meyer-Hoffert U, Schroder JM. Identification of trichohyalin-like 1, an s100 fused-type protein selectively expressed in hair follicles. J Invest Dermatol. 2011;131(8):1761\u0026ndash;1763.\u003c/li\u003e\n\u003cli\u003eFurstenberger G, Marks F, Krieg P. Arachidonate 8(S)-lipoxygenase. Prostaglandins Other Lipid Mediat 2002;68\u0026ndash;69:235\u0026ndash;243.\u003c/li\u003e\n\u003cli\u003eClements SE, Techanukul T, Lai-Cheong JE, Mee JB, South AP, Pourreyron C, et al. Mutations in AEC syndrome skin reveal a role for p63 in basement membrane adhesion, skin barrier integrity and hair follicle biology. Brit J Dermatol. 2012;167(1):134\u0026ndash;144.\u003c/li\u003e\n\u003cli\u003ePertea M, Kim D, Pertea GM, Leek JT, Salzberg SL. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat Protoc. 2016;11(9):1650\u0026ndash;1667.\u003c/li\u003e\n\u003cli\u003eYoung MD, Wakefield MJ, Smyth GK, Oshlack A. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol. 2010;11(2):R14.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Skin, Hair follicle density, Wool production, Histological analysis, LncRNA expression, RNA sequencing, Angora rabbit","lastPublishedDoi":"10.21203/rs.3.rs-43570/v3","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-43570/v3","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eHair follicle density influences wool fibre production, which is one of the most important traits of the Wan strain Angora rabbit. However, molecular mechanisms regulating hair follicle density have remained elusive. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eIn this study, hair follicle density at different body sites of Wan strain Angora rabbits with high and low wool production (HWP and LWP) was investigated by histological analysis. Haematoxylin-eosin staining showed a higher hair follicle density in the skin of the HWP rabbits. The long noncoding RNA (lncRNA) profile was investigated by RNA sequencing, and 50 and 38 differentially expressed (DE) lncRNAs and genes, respectively, were screened between the HWP and LWP groups. A gene ontology analysis revealed that phospholipid, lipid metabolic, apoptotic, lipid biosynthetic, and lipid and fatty acid transport processes were significantly enriched. Potential functional lncRNAs that regulate lipid metabolism, amino acid synthesis, as well as the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) and hedgehog signalling pathways, were identified. Consequently, five lncRNAs (LNC_002171, LNC_000797, LNC_005567, LNC_013595, and LNC_020367) were considered to be potential regulators of hair follicle density and development. Three DE lncRNAs and genes were validated by quantitative real-time polymerase chain reaction (q-PCR). \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eLncRNA profiles provide information on lncRNA expression to improve the understanding of molecular mechanisms involved in the regulation of hair follicle density.\u003c/p\u003e","manuscriptTitle":"Analysis of histology and long noncoding RNAs involved in the rabbit hair follicle density using RNA sequencing","msid":"","msnumber":"","nonDraftVersions":[{"code":3,"date":"2021-01-22 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