The Aberrant Migration and Differentiation of Neural Crest Cells Led to the Production of HVP in Bearded Chicken

The Aberrant Migration and Differentiation of Neural Crest Cells Led to the Production of HVP in Bearded Chicken | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Aberrant Migration and Differentiation of Neural Crest Cells Led to the Production of HVP in Bearded Chicken Zhengyang Chen, Changbin Zhao, Xiaoyin Zeng, Xueyin He, Chengyue Yuan, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7241140/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Nov, 2025 Read the published version in Functional & Integrative Genomics → Version 1 posted 15 You are reading this latest preprint version Abstract Hyperpigmentation of the visceral peritoneum (HVP) critically impacts carcass quality in yellow-feathered broilers, yet its mechanisms remain unclear. This study employed single-cell RNA sequencing to profile black, faded, and normal peritoneal tissues from bearded chickens at 40 and 120 d of age, functionally validating findings with fibroblast lines and primary melanocytes. We identified nine cell types, with melanocytes significantly elevated in HVP tissue. UMAP projections revealed near-overlapping melanocyte and Schwann cell clusters, indicating HVP melanocytes originate primarily from the ventromedial migratory pathway of neural crest cells (NCCs), differentiating via Schwann cell precursors. Aberrant melanocyte aggregation and migration drive HVP pathogenesis. CellChat analysis demonstrated pivotal roles for the SEMA3C-PLXND1 axis, which directs NCCs migration, and the TNC-SDC1 axis, which enhances melanocytes adhesion, in fibroblasts-melanocytes crosstalk. Transcription factor analysis highlighted HOX family regulation of NCCs to melanocytes differentiation. Experimentally, SDC1 downregulation reduced melanin synthesis but increased migration, while estradiol promoted melanogenesis and modulated extracellular matrix. HVP development involves four interconnected mechanisms: RA-HOX-mediated aberrant NCCs differentiation, SEMA3C-PLXND1-driven melanocyte barrier breaching, TNC-SDC1-mediated peritoneal colonization, and estrogen-coordinated melanin deposition. These findings elucidate HVP's molecular basis and provide theoretical support for broiler breeding. Hyperpigmentation of the visceral peritoneum Neural crest cells HOX family bearded chickens Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Background Hyperpigmentation of the visceral peritoneum (HVP), characterized by localized melanin deposition predominantly in the peritoneal region, significantly compromises broiler growth performance and carcass yield—yet remains poorly investigated(Wang et al. 2024). Genome-wide association analysis identified CYP2D6 as a key genetic determinant underlying HVP formation(Zhou et al. 2022). As a critical enzyme in retinoic acid biosynthesis(Ning et al. 2019), CYP2D6 functionally implicates retinoic acid levels in HVP pathogenesis. HVP recapitulates the systemic melanosis of Silky fowl (SF), showing ectopic pigmentation across 7 organ systems. GWAS analyses implicate coordinated actions of FM-CNVs and the Z-linked ID locus in driving this phenotype(Leng et al. 2025). Retrospective analyses from the 1960s revealed significantly higher HVP prevalence in hens versus roosters, leading early investigators to postulate sex-linked and sex-limited inheritance mechanisms underlying this phenotype(Huntsman et al. 1959, 1960; Kuit 1967). In our previous study, we found that the formation of HVP is due to the delamination and migration of neural crest cells (NCCs)mediated by Wnt signaling pathway and retinoic acid signaling pathway(Chen et al. 2025). NCCs were found in chick embryos by William Heath in 1868 and described as ' Zwischenstrang ', a group of migrating cells that appear between the ectoderm and the neural tube(Huang and Saint-Jeannet 2004). NCCs originate from closed neural tubes and are a group of pluripotent stem cells with migration ability. This short-lived group consists of four subgroups along the body axis from the beak to the tail: skull, vagus nerve, trunk, and sacrum(Jacobs-Li et al. 2023). NCCs undergo epithelial-to-mesenchymal transition and migrate along defined pathways throughout the embryo to reach specific destinations within various tissues and organs, where they complete their differentiation. The development of the neural crest involves several critical steps: induction, delamination, specification, and migration. NCCs have the potential to differentiate into multiple cell types, including melanocytes, most peripheral neurons, glial cells, and craniofacial chondrocytes(Vandamme and Berx 2019). Through mesenchymal migration during embryonic development, NCCs differentiate into Schwann cell precursors (SCPs), which subsequently further differentiate into melanocytes(Adameyko et al. 2009). In this study, we employed scRNA-seq on peritoneal samples from Huiyang bearded chickens at 40 and 120 d of age to generate single-cell atlases of different peritoneal layers, aiming to identify key pathways and candidate genes associated with HVP formation. Methods Sample collection and cell source Experimental animals used for sample collection were provided by Xingtai Modern Agriculture Co., Ltd., located in Longmen County, Huizhou City, Guangdong Province, and were all fed under the same husbandry conditions. The study included 30 hens at 40 d of age and 30 hens at 120 d of age. Blood was drawn from the jugular vein of the hens, followed by the collection of peritoneal samples, which were immediately placed on ice for HVP grading. Collected samples were promptly snap-frozen in liquid nitrogen and stored at -80℃. The peritoneum was classified into three categories: normal (N), transitional (F), and black (B), and named according to age and phenotype as 40B, 40F, 40N, 120B, 120F, and 120N. Samples were used for scRNA-seq, with three biological replicates per group. After pooling, single-cell suspensions were prepared (Fig 1a). Silky fowl fertilized eggs used for isolating primary melanocytes were obtained from Taihe, Jiangxi Province. The chicken fibroblast cell line (DF-1) was obtained from the laboratory’s frozen stocks. Single-cell Suspension Preparation The peritoneal samples were digested with collagenase I and trypsin until flocculent within 12 h of collection to prepare single-cell suspensions. Cell viability was assessed using AO/PI dual-fluorescence staining on the Countstar Rigel system, with a viability threshold > 90% for qualification. Single-cell GEMs (Gel Bead-in-Emulsions) were prepared using the Chromium Next GEM Single Cell 3ʹ GEM, Library & Gel Bead Kit v3.1 (10× Genomics #1000121) on the Chromium Controller platform (10× Genomics). Subsequently, reverse transcription was performed on the GEMs, followed by cDNA recovery (using Beckman magnetic beads #B23318) and purification to construct cDNA libraries. Sequencing was conducted on the Illumina NovaSeq 6000 platform with a PE150 strategy. Bioinformatic Analysis of Sequencing Data The raw FASTQ files were processed using CellRanger for pre-processing, including barcode extraction, UMI identification, and gene sequence alignment. The sequencing reads were mapped to the reference genome (Red Jungle Fowl, Gallus gallus, GRCg6a assembly) obtained from the Ensembl database. This pipeline generated a gene expression matrix along with cell barcode information, which was subsequently used for downstream bioinformatic analyses. Based on the R package Seurat, a single-cell transcriptome analysis pipeline was constructed. Double cells were removed from six samples individually using the R package DoubletFinder, with a doublet rate of approximately 5.5%. The downstream analysis pipeline included quality control, clustering and dimensionality reduction, cell type annotation, differential expression genes (DEGs) analysis, and visualization. To ensure high-quality cells were retained for downstream analysis, genes expressed in fewer than 3 cells and cells expressing fewer than 200 genes were excluded. The R package clustree was used to select an appropriate clustering resolution. Clustering analysis was performed using the RunUMAP function, and clustering was identified using the FindClusters function with an enhanced resolution parameter of 0.1. Marker genes for each cell cluster were identified using the FindAllMarkers function (min.pct = 0.25, logfc.threshold = 0.25). DEGs between B and N cell clusters were calculated using the FindMarkers function with thresholds of |log2FC| > 1 and P -value < 0.05. Cellchat Analysis The R package CellChat was employed to construct a CellChat object using the count matrices extracted from Seurat objects of each sample, based on a ligand-receptor (L-R) interaction database. This framework enables systematic inference of: L-R interaction strength at the cellular level, signaling pathway activity across cell populations, and global communication probability between samples. Special emphasis was placed on investigating fibroblast-melanocyte crosstalk. The likelihood and biological relevance of intercellular ligand-receptor interactions were visualized via heatmaps, highlighting key cell cluster-specific communication events. GO and KEGG Enrichment Analysis Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on DEGs identified by FindMarkers using the R package clusterProfiler. Specifically, the enrichGO and enrichKEGG functions were employed to systematically characterize the biological functions and pathways associated with the DEGs. pySCENIC Analysis The count matrix was extracted from the Seurat object, and the pySCENIC environment was configured using Python 3.7 to generate loom files. Based on the GRNBoost2 algorithm, co-expression modules between transcription factors (TFs) and target genes were constructed. The authenticity of the regulatory networks between TFs and target genes was validated using RcisTarget, and the regulatory networks were filtered by calculating the AUC curve. Subsequent visualization was performed using the R package SCENIC. Pseudotime Analysis Pseudotime analysis of melanocytes was performed based on the R package monocle. After filtering out low-quality cells, differential gene analysis was conducted using the built-in functions of monocle. The results were visualized using the plot_cell_trajectory, BEAM, and clusterAndVisualize functions. hdWGCNA Analysis The weighted gene co-expression network analysis (WGCNA) of Schwann cells and melanocytes was performed using the R package hdWGCNA, with visualization conducted using built-in functions from hdWGCNA. Cell Culture Newly hatched (1 d) Silky fowl chicks were selected for melanocyte isolation. The black peritoneal tissue was carefully dissected and washed three times with PBS. Tissue digestion was performed using a dual-enzyme approach (trypsin: dispase Ⅱ= 1:1 ratio) for 45 min, followed by sequential filtration through 100 μm and 70 μm cell strainers to obtain melanocytes. When cells reached 80-90% confluency, they were detached using 0.25% trypsin for 5 min, followed by centrifugation and resuspension to obtain purified melanocytes. The cells were maintained at 37℃ with 5% CO₂ in human primary melanocytes complete medium (254 Medium (M254500), Human Melanocyte Growth Supplement-2 (S0165), Thermo Fisher). DF-1 was cultured in a complete medium consisting of 10% FBS (10099-141C, Thermo Fisher) and 1% penicillin-streptomycin (Gibco) at 37℃ with 5% CO₂. Transfection Melanocytes were seeded in 12-well plates and transfected using Lipofectamine® 3000 according to the manufacturer's instructions when reaching 80% confluence. SiRNA targeting chicken SDC1 (XM_419972.7) was synthesized by Gene Create Biotechnology Co., Ltd (Wuhan, China) based on the mRNA sequences from the NCBI database, with negative control siRNA used for control transfection. The siRNA sequences are listed in Table 1. Treatment of DF-1 and Melanocytes with 17β-estradiol. Cells were treated with 17β-estradiol (E2, Psaitong, China) at concentrations of 0, 1, 5, and 10 μM for DF-1 cells, and 0 and 5 μM for melanocytes, respectively. After 24 h of treatment, cellular RNA was extracted for quantitative experiments. Detection of Cell Melanin Content Cells were seeded into the plates and allowed to adhere. Following experimental treatments, the supernatant was discarded after 24 h, and the cells were washed twice with PBS. Subsequently, 1 mL of NaOH (1 mol/L, containing 10% DMSO) was added to each well to lyse the cells. The plates were then incubated in a metal water bath at 80℃ for 30 min. After incubation, 100 μL of the lysate from each well was transferred to a 96-well plate, and the absorbance was measured at a wavelength of 405 nm. Determination of Tyrosinase Activity Cells were seeded into the plates and allowed to adhere. After experimental treatments, the supernatant was discarded at 24 h, and the cells were washed twice with PBS. Subsequently, 100 μL of 0.1% Triton X-100 solution was added to each well to lyse the cells for 30 min, followed by centrifugation at 4℃. Then, 40 μL of the supernatant was mixed with 160 μL of 5 mM L-DOPA and incubated at 37℃ for 1 h. The absorbance was measured at a wavelength of 475 nm. Wound Healing Assay The cell culture inserts were first placed into 6-well plates to ensure tight adhesion. Subsequently, melanocytes with SDC1 interference were digested and centrifuged after 48 h, then seeded into the cell insert. After cell attachment, the inserts were carefully removed using sterile forceps, creating two separate cell populations with a "wound" gap in between. The plate was tilted to slowly add PBS, then tilted in the opposite direction to allow PBS to flow across the cell surface without dislodging cells, repeated twice. A complete medium was added using the same technique for subsequent culture. Images covering the wound area were captured at 0, 24, and 48 h post-attachment. Micrographs were taken using a CCD camera connected to an inverted stage-contrast microscope at 5× magnification. Western blot After treating DF-1 cells with E2, proteins were extracted and their concentrations measured. Following denaturation, proteins were separated by SDS-PAGE and transferred onto PVDF membranes. The membranes were blocked with 5% skimmed milk for 1 h. Subsequently, they were incubated overnight with primary antibodies: Rabbit Anti-DCN antibody (A1669) and Rabbit Anti-VCAN antibody (A19655, ABclonal, China). Then incubate with the secondary antibody for 1 hour. Prepare the detection solution according to the instructions of the Chemiluminescent HRP Substrate (Millipore, America), and visualize the results using an ECL chemiluminescence imaging system. Quantitative Real-time PCR The relative gene expression levels were measured, and the effects of various treatments on extracellular matrix (ECM)-related genes and melanin synthesis genes were evaluated using quantitative real-time PCR. Cells were harvested at indicated times, and cells were lysed by Trizol Reagent. Total RNA reverse transcription was performed following the instructions of the HiScript Ⅲ All-in-one RT SuperMix Perfect for qPCR kit (Vazyme, China). The real-time fluorescence quantitative analysis was conducted according to the ChamQ SYBR qPCR Master Mix kit instructions (Vazyme, China). The specific primers for qPCR were designed using the NCBI online website. All primers were synthesized by Tsingke Biotech Technology Co., Ltd. (Guangzhou, China). The data from quantitative real-time PCR were analyzed using the 2 −ΔΔCt method, with the chicken GAPDH gene serving as the housekeeping gene. Statistical analysis and graph plotting were performed using GraphPad Prism 5 software. Differences between groups were assessed with an unpaired Student’s t-test. Each group included at least three replicates (n ≥ 3). A P -value > 0.05 was considered not statistically significant (ns), while P -value < 0.05 was considered statistically significant (*). P -value < 0.01 and P -value < 0.001 were considered highly significant (** and ***, respectively). The primer sequences used in qRT-PCR are shown in Table 2. Results Single-cell Atlas of Chicken Black Peritoneum The single-cell atlas of HVP comprised 41,395 quality-controlled cells (Fig 1b), comprising 6,338 (40B), 5,659 (40F) and 12,967 (40N) cells for the 40-series samples, along with 6,547 (120B), 6,518 (120F) and 3,719 (120N) cells for the 120-series samples. Based on gene expression similarity within clusters and statistically significant differential expression between clusters through PCA/UMAP analysis in Seurat, we developed a UMAP plot comprising nine distinct cell clusters (Fig 1c). A list of biomarkers for each cluster was generated using t-tests in Seurat (FDR < 0.05). By combining the most highly DEGs and established cell-specific markers, we identified and annotated nine cell populations in chicken HVP: fibroblasts were characterized by LUM , DCN , and COL3A1 expression; Schwann cells by specific expression of CDH19 , PLP1 , and CD9 ; and melanocytes by MLPH , PMEL , and MLANA . Additionally, endothelial cells, oligodendrocytes, myofibroblasts, macrophages, T cells, and muscle satellite cells were identified through their characteristic gene expression patterns (Fig 1d, Table 3). The comparative proteomic screening revealed that fibroblasts expressed VCAN and DCN , while DHRS3 was co-expressed in melanocytes, Schwann cells, and fibroblasts (Fig 1e). UMAP projection distances between melanocytes and Schwann cells suggested that HVP melanocytes originate from the ventromedial migration pathway of NCCs and differentiate from SCPs, with varying SCPs lineage proportions across samples. Black peritoneal samples exhibited higher total SCPs lineage cells than normal peritoneal samples, containing the highest proportion of melanocytes (Fig 1f), whereas normal peritoneum showed the lowest melanocytes percentage. Although the maximum proportion reached only approximately 0.8%, compared to 3.6-4.9% in SF skin transcriptomes, and considering the < 0.2% melanocytes proportion in normal peritoneum, we speculate that minimal melanocytes aggregation suffices for HVP formation. This may explain our previous difficulty in isolating sufficient primary melanocytes from bearded chicken hyperpigmented peritoneum, prompting subsequent primary melanocytes isolations from SF samples with higher melanocytes abundance. GO and KEGG Enrichment Analysis of Melanocytes The melanocytes proportions exhibited substantial variation across different samples, prompting further functional analysis of their DEGs to elucidate their potential roles in HVP. The 40B-N group displayed 1,301 DEGs (971 upregulated and 330 downregulated), while the 120B-N group contained 765 DEGs (35 upregulated and 730 downregulated) (Fig 2a). Comparative analysis identified 22 co-expressed genes shared between both groups (12 upregulated and 10 downregulated) (Fig 2b). KEGG pathway enrichment analysis of upregulated DEGs in 40B-N melanocytes revealed significant enrichment in cellular senescence, melanogenesis, Wnt signaling pathway, and MAPK signaling pathway, while downregulated DEGs showed prominent enrichment in ribosome, cytoskeleton in myocytes, and extracellular matrix-receptor interactions ( P -value < 0.05) (Fig 2c). GO analysis demonstrated that the 1,301 DEGs were primarily enriched in MF including mRNA binding and protein kinase activity, CC involving anchoring junctions and ATPase complexes, and BP involving calcium ion-mediated signaling and melanin synthesis (Fig 2d). These findings collectively indicate that the melanocytes were in a state of highly active metabolism and proliferation. KEGG pathway enrichment analysis of upregulated DEGs in 120B-N melanocytes demonstrated predominant enrichment in melanogenesis, apoptosis, Toll-like receptor signaling pathway, and focal adhesion, while downregulated DEGs were primarily associated with amino sugar and nucleotide sugar metabolism, bacterial invasion of epithelial cells, and butanoate metabolism ( P -value < 0.05) (Fig 2e). GO analysis revealed that the 765 DEGs were significantly enriched in MF including GTPase regulator activity, nucleoside-triphosphatase regulator activity, and isomerase activity; CC involving comprising synaptic membrane and postsynaptic specialization membrane; and BP involving regulation of defense response, negative regulation of response, and tube size regulation (Fig 2f). These findings collectively indicate that the melanocytes were undergoing enhanced immune response while maintaining viability, with this immunomodulatory activity potentially facilitating melanin deposition. Analysis of Cell-cell Communication in HVP Identifying cellular subpopulations that exhibit close communication with melanocytes constitutes a critical step in elucidating the pathological mechanisms of HVP. Cell-cell interaction network analysis revealed that compared to the normal peritoneum, the melanocytes in the black peritoneum demonstrated a significant increase in both the number of incoming pathways and signal intensity (Fig 3a, c). In 2D spatial analysis, melanocytes in the black peritoneum received substantially more cross-cluster regulatory signals than they emitted. Notably, fibroblasts displayed a distinctive bidirectional communication signature within the interaction network—their coordinates for both outgoing and incoming signals ranked among the highest (Fig 3b, d), suggesting that this cellular subpopulation may function as a signaling hub. This hypothesis was corroborated by differential interaction analysis: in black peritoneum, the interaction strength and pathway diversity between fibroblasts and melanocytes exhibited marked differences compared to normal peritoneum (Fig 3e-h). Quantification of key signaling pathway differences across samples was performed through ligand-receptor (L-R) interaction network analysis. The results demonstrated that the communication strength of the ANGPTL, SEMA3, and TENASCIN pathways in 40B was significantly higher than in 40N (Fig 3i), while the CD99 and TENASCIN pathways in 120B exhibited significantly stronger communication intensity compared to 120N (Fig 3j). The SEMA3 pathway, which is closely related to NCCs migration, has 30 pairs of L-R in 40B samples. Signal flow analysis revealed that fibroblasts acted as the primary signal source, transmitting SEMA3 ligands to PLXNA/D receptors on the surface of melanocytes (Fig 3k). Among these interactions, the SEMA3C-PLXND1 axis exhibited the highest communication probability, suggesting that fibroblasts may predominantly drive the chemotactic migration of melanocytes through this axis. Fibroblasts similarly relied on the SEMA3C-PLXND1 axis to regulate Schwann cells migration (Fig 3n). However, the increased proportion of melanocytes within the SCPs lineage did not stem from migration selectivity, implying that fibroblasts may regulate the differentiation fate of SCPs through alternative mechanisms. Further analysis revealed that the TENASCIN pathway, as a core co-upregulated pathway during HVP progression, displayed cell type-specific activation patterns for its seven L-R pairs in disease samples: fibroblasts established adhesion-related signaling with melanocytes via the TNC-SDC1 axis (Fig 3l-m), whereas the TNC-SDC4 axis specifically modulated Schwann cells migration and exhibited dynamic switching within the developmental time window (activated in the HVP group at 40 d but shifted to the normal group at 120 d) (Fig 3o-p). Investigation into the Differentiation of SCPs Lineage Cells The specific differentiation of SCPs is primarily achieved through the selective expression of transcription factors. We constructed the transcriptional regulatory networks of melanocytes and Schwann cells using pySCENIC. Cross-group comparisons revealed that early-response transcription factors such as JUN , ATF3 , and FOS exhibited significant transcriptional activity across all cell clusters in each group (Fig 4a). Through stringent screening criteria (Z-score>2), characteristic transcriptional regulators were identified for different treatment groups: IRF7 specifically regulated melanocytes in the B/F groups, HOXD8 selectively dominated melanocytes in 40B/40F, while HOXA4 was specifically activated in 120B/120F melanocytes (Fig 4b-d). Notably, the expression of HOX gene family members in melanocytes displayed age-dependent specificity. Functional predictions of TFs were inferred based on their downstream regulatory networks, revealing that IRF7 is associated with pathways such as NF-κB, CDK, and TGF-β, as well as dopachrome tautomerase DCT (Fig 4e). HOXA4 and HOXD8 were found to regulate genes implicated in melanocytes function and differentiation, including OCA2 , HPGDS , and PAX3 (Fig 4f-g), indicating their involvement in melanocytes differentiation processes. These findings suggest that differential expression of HOX family genes may represent one of the regulatory mechanisms underlying HVP. Cytotrace analysis revealed that melanocytes in the B group exhibited the highest stemness potential, while those in the N group showed the lowest (Fig 5a-b). Pseudotime analysis reconstructed the differentiation progression of melanocytes (Fig 5c-d), with 40N melanocytes positioned at the origin of differentiation, while 40B, 40F, 120B, and 120F melanocytes were distributed along the trajectory (Fig 5e). During pseudotime progression, the expression of Cluster 2 genes increased, correlating positively with differentiation advancement. GO enrichment analysis revealed their significant enrichment in melanogenesis, as well as participation in ribosome biogenesis and ErbB signaling pathways, among others. Notably, among HOX family members, HOXD8 and HOXB5 were upregulated, whereas HOXC6 was downregulated at the observed differentiation stages (Fig. 5f). At branch point 1, the melanocytes state of 40N diverged into B and F melanocyte states (Pre-branch cluster representing State 1, Cell fate 1 comprising State 2, 3, 4, and Cell fate 2 representing State 5). Genes in Cluster 4 were highly expressed in Cell fate 1, including retinoic acid receptor beta RARB , while Cluster 5 genes PDGFC and ZNF521 showed elevated expression in Cell fate 2, suggesting a potential association of these melanocytes with angiogenesis (Fig 5g). WGCNA was performed on Schwann cells and melanocytes, yielding five distinct modules (Fig 6a). Among these, Module 1 exhibited predominant expression in melanocytes (Fig 6b, d) and demonstrated strong correlations with 40B, 40F, 120B, and 120F samples (Fig 6c). Examination of hub genes within Module 1 revealed that the majority were associated with melanin synthesis, with most showing preferential expression in melanocytes. Notably, it was found that the candidate gene SDC1 obtained in CellChat analysis was also the core gene of Module 1. Given the high expression of SDC1 in melanocytes, we hypothesize that SDC1 may not only influence melanocytes migration but also participate in the biological process of melanin biosynthesis. Furthermore, the downstream genes OCA2 and HPGDS of HOXA4 and HOXD8 in pySCENIC analysis also appeared in Module 1. (Fig 6e). Identification Subpopulations of Fibroblasts in HVP KEGG enrichment analysis of fibroblasts identified the glycosaminoglycan biosynthesis—chondroitin sulfate/dermatan sulfate pathway as the top enriched pathway in 40B-N (Fig. 7a), whereas in 120B-N, it was retinol metabolism (Fig. 7b). These findings are consistent with the proteomic analysis results. ECM components and retinoic acid, respectively. Subcluster analysis of fibroblasts identified four distinct subpopulations (Fig 7c): Fib1 expressed cell adhesion factors such as NEGR1 , TNXB , and FGL2 , potentially involved in melanocytes adhesion and colonization. Fib2 specifically expressed ROBO2 and EPHA7 , which may promote NCCs migration. Fib3 expressed immune-related genes, including JCHAIN , GNLY , IGLL1 , and CD74 . Fib4 was characterized by collagen genes ( COL22A1 , COL13A1 ) and integrin ITGA8 . Notably, Fib1 expressed ECM-related genes ( VCAN , DCN ) and DHRS3 identified in the proteomic screening (Fig 7d). In 40B-N, VCAN was upregulated in Fib1, Fib2, and Fib3 at the transcriptional level (consistent with RT-qPCR results) (Fig 7e-g), but downregulated at the protein level. This discrepancy suggests potential post-translational regulatory mechanisms leading to reduced VCAN protein abundance. CellChat analysis revealed that the Fib2 subpopulation exhibited the most significant interactions with melanocytes. Visualization of the SEMA3 signaling pathway in 40B-N showed that both Fib1 and Fib2 subpopulations transmitted signals to melanocytes, with the SEMA3C-PLXND1 axis demonstrating the strongest signaling intensity (Fig 7h). Among the DEGs in fibroblast subpopulations of 40B-N, SEMA3C expression was significantly upregulated (Fib1: log2FC=1.29; Fib2: log2FC=1.80), while PLXND1 expression was markedly elevated in melanocytes (log2FC=5.86). In the TENASCIN pathway, Fib2 and Fib4 subpopulations communicated with melanocytes via the TNC-SDC1 signaling axis (Fig 7i, j). In 40B-N, TNC expression was significantly upregulated in Fib2 (log2FC=2.22) and Fib4 (log2FC=1.82), whereas no significant difference was observed in 120B-N. Similarly, SDC1 expression was notably increased in melanocytes of 40B-N (log2FC=3.39) but remained unchanged in 120B-N. Integrated dual-omics analysis The R package edgeR was used to analyze the DEGs between HVP and normal peritoneal (bcv=0.2), followed by KEGG and GO analyses. In the 40B-N group, there are 2,362 upregulated genes and 1,490 downregulated genes. In the 120B-N group, there are 270 upregulated genes and 282 downregulated genes. At the 40B-N intersection, we identified 63 DEGs and DAPs, comprising 30 upregulated, 7 downregulated, and 26 with discordant mRNA-protein expression (Fig. 8a). In contrast, the 120B-N intersection contained only 3 genes: 2 upregulated and 1 with discordant expression (Fig. 8b, Table 4). The KEGG enrichment analysis of genes with consistent expression trends revealed seven significantly co-expressed pathways. The upregulated pathways included tyrosine metabolism, steroid hormone biosynthesis, melanogenesis, primary bile acid biosynthesis, and fatty acid elongation, while the downregulated pathways were lysine degradation and insulin signaling pathway (Fig 8c). Our dual-omics analyses consistently indicated that steroid hormones may play a crucial role in the HVP process. Notably, in the 40B-N group, we observed coordinated upregulation of the HSD17B12 gene, which encodes a key enzyme in estradiol (E2) biosynthesis. Gene function verification Based on the above bioinformatic analysis results, we hypothesize that SDC1 genes and E2 play crucial regulatory roles in HVP formation. To validate this hypothesis, we conducted RNA interference experiments targeting SDC1 in primary melanocytes. We characterized the isolated chicken primary melanocytes using two melanocyte-specific markers, TYR and Melan-A, via immunofluorescence staining. The results confirmed the high purity of the isolated melanocytes (Fig. 9a-e). SDC1 gene interference produced dual regulatory effects: (1) Regarding melanogenesis, it led to significant downregulation of mRNA expression levels in key regulatory genes such as DCT , EDNRB , and MITF (Fig 9f), accompanied by decreased tyrosinase activity and reduced melanin production (Fig 9g, h); (2) In terms of cell migration, it induced upregulation of homologous genes SDC2 and SDC4 expression (Fig 9i, j), thereby significantly enhancing the migratory capacity of melanocytes (Fig 9k, l). These results suggest that SDC1 may participate in HVP formation through a dual regulatory mechanism: it not only regulates pigment synthesis through the classical melanogenic pathway but also affects cell migration behavior by activating homologous genes via a bypass mechanism. Given that fibroblasts are the predominant cell type in peritoneal tissue, we treated both DF-1 cells and chicken primary melanocytes with 17β-estradiol to test this hypothesis. Following 17β-estradiol treatment, DF-1 cells exhibited upregulated mRNA expression of ECM genes (including DCN and VCAN ) (Figure 10a); however, no significant differences were observed in the protein abundance of DCN and VCAN (Figure 10b). Therefore, we propose that other factors may act in conjunction with 17β-estradiol to contribute to the ECM alterations observed in HVP. Upon 17β-estradiol treatment, the melanocytes showed upregulated expression of melanogenesis-related genes ( DCT , TYR , and MLPH ), while MITF expression was downregulated. This suggested that 17β-estradiol might inhibit melanocytes proliferation while promoting melanin synthesis (Fig. 10c). To further validate this hypothesis, we supplemented the culture medium with 1 μM Tyr and treated the cells with 17β-estradiol for 24 h before measuring melanin content. Compared to the control group, 5 μM 17β-estradiol treatment significantly enhanced melanin synthesis (Fig. 10d). Discussion The occurrence of HVP can suppress the growth and development of broilers(Wang et al. 2024), yet current limited research has not elucidated the genetic mechanisms underlying HVP formation. In previous laboratory studies, both the Wnt signaling pathway and retinoic acid (RA) signaling pathway were found to participate in the delamination and migration of NCCs, ultimately contributing to HVP formation(Chen et al. 2025). In this study, we performed scRNA-seq analysis on peritoneal tissues with varying degrees of melanin deposition and employed analytical methods such as CellChat and pySCENIC to reveal the genetic mechanisms driving HVP development. CellChat analysis revealed that the abnormal aggregation of melanocytes in the B/F group is closely associated with regulatory effects from fibroblasts in their microenvironment. We identified the TNC-SDC1 L-R axis in the TENASCIN pathway as the critical pathway through which fibroblasts influence melanocytes adhesion and migration. Both TNC and SDC1 play roles in cell adhesion and migration processes: TNC serves as a melanoma marker that enhances the migratory capacity of melanoma cells through interactions with integrins and ECM components(Fukunaga-Kalabis et al. 2010; Grahovac et al. 2013; Aguera-Lorente et al. 2024), while also exhibiting anti-adhesive molecule functionality(Hagedorn et al. 2016); SDC1 is a transmembrane heparan sulfate proteoglycan that regulates cell proliferation, migration, angiogenesis, and cell-cell/extracellular matrix adhesion(Mitselou et al. 2012), homologous gene SDC2 can enhance the migration and invasion of melanoma cells(Lee et al. 2009). Evidence suggests that axon guidance factors, including ephrins and semaphorins, function to guide and pathfind during NCCs migration. Semaphorins are a family of secreted or transmembrane proteins, initially identified as axon guidance factors during neural development(Huber et al. 2003). Notably, the signaling of Class 3 Semaphorins is essential for the developmental migration of NCCs(High and Epstein 2007). Neuropilins (NRPs), comprising NRP1 and NRP2 subtypes, serve as receptors for Class 3 Semaphorins. They typically bind to PLXNDA or PLXND1 to transduce signals; however, SEMA3C can signal directly via PLXND1 independently of NRP(Smolkin et al. 2018). SEMA3A and NRP1 participate in neural crest patterning in chickens(Schwarz et al. 2008), preventing trunk NCCs from migrating through somite clefts while maintaining their ventromedial migratory route. Knockout of SEMA3E causes severe craniofacial defects(Liu et al. 2019); SEMA3F and SEMA3G are critical for segregating migrating cranial NCCs in zebrafish(Yu and Moens 2005); while SEMA3D may regulate NCCs proliferation downstream of the transcription factor TCF in the zebrafish hindbrain(Berndt and Halloran 2006). A mutation impairing Semaphorin signaling induces excessive dorsolateral migration of NCCs via NRP1 (Schwarz et al. 2009); moreover, NRP1 also promotes melanoma cell migration(Lu et al. 2015). Experimental evidence demonstrates that SEMA3C chemoattracts NCCs in both in vivo and in vitro settings, knockdown of PLXND1 or NRP1 in NCCs attenuates the chemoattractive effect of SEMA3C (Toyofuku et al. 2008). In fact, fibroblasts guide directionally migrating melanocyte-fated NCCs through the SEMA3C-PLXND1 signaling axis, while reduced abundance of proteoglycans such as VCAN and DCN may facilitate NCCs penetration through migratory barriers. Following NCCs entry into the peritoneum, the TNC-SDC1 signaling axis promotes their colonization, ultimately driving the formation of HVP. In our previous study, RA was identified as a critical inducer for HVP formation. Endogenous RA is essential for the normal stratification of NCCs(Rekler et al. 2024) and stimulates their differentiation toward melanocyte precursors by inducing tyrosinase expression(Huang et al. 2016). This differentiation is proposed to result from distinct HOX gene expression profiles, whose expression is regulated by factors including RA and FGF(Wilkinson 1993; Weicksel et al. 2014; Gomez et al. 2019).Through pySCENIC analysis, multiple HOX genes were identified as being activated. HOX genes encode a conserved family of TFs that play crucial roles in regulating regional tissue identity along the anterior-posterior axis and exert regulatory effects during embryonic development(Afzal et al. 2023; Peraldi and Kmita 2024). Different HOX genes can drive trunk NCCs to differentiate into distinct cell lineages(Howard et al. 2021; Cooper and Tsakiridis 2022), the spatiotemporally specific expression of HOX genes in HVP establishes the molecular basis for NCCs differentiation into melanocytes. Low expression of HOXA2 and HOXB2 in embryos can lead to melanocytes deficiency(Knight et al. 2004). Notably, the direct regulatory link between RA signaling and HOX expression may represent an ancient feature of core gene regulatory networks, evolutionarily coupled with anteroposterior patterning in all chordates(Bedois et al. 2023; Bedois et al. 2024). In our preliminary surveys, while HVP occurs in most broiler breeds, its incidence frequency is significantly higher in Huiyang Bearded Chickens compared to other broiler varieties. Huiyang Bearded Chickens are renowned for the elongated feathers collected from both sides of their face and below the beak, whose molecular basis involves specific expression patterns of HOX family genes and differential RA levels(Guo et al. 2016; Yang et al. 2020; Zheng et al. 2023). This study similarly identified HOX gene family members and RA signaling, suggesting potential connections between beard feather formation and HVP development. Bioinformatic prediction of TFs in proteomic profiles of HVP samples revealed significant enrichment of zinc finger domain-containing TFs. Studies demonstrate that zinc finger proteins, particularly CTCF of the C2H2 family, maintain chromatin boundary integrity at HOX gene, thereby establishing their differentiation-associated expression patterns(Kyrchanova et al. 2020; Ortabozkoyun et al. 2022; Ortabozkoyun et al. 2024). Furthermore, RA signaling modulates HOX-specific expression patterns by regulating bZIP domain-containing transcription factors, thereby contributing to neuronal fate specification(Hernandez et al. 2004). Therefore, we propose that RA participates in NCCs' directional differentiation toward melanocytes by modulating HOX gene family-specific expression, indirectly contributing to melanin synthesis and ultimately HVP formation. This regulation of HOX specificity may be mediated through zinc finger proteins. Additionally, the frequency of HVP in hens of Bearded chickens is also significantly higher than in roosters. Evidence suggests a physiological link between ovarian activity and pigmentary changes in both skin and abdominal regions(Kim et al. 2010; Kumar and Joy 2015). The HSD17B12 gene, along with the GnRH signaling pathway and steroid hormone biosynthesis pathway, was consistently identified through integrated dual-omics analysis and multiple bioinformatics analysis methods. The HSD17B12 gene is responsible for E2 synthesis and participates in lipid metabolism(Lima et al. 2013; Bertin et al. 2014). The upregulation of this gene and associated pathways indicates that the E2-dominated hormonal microenvironment facilitates HVP formation. Comparative metabolomic and lipidomic profiling of SF versus common chicken strains revealed a significant association between differential HSD17B1 gene expression and altered E2 metabolic flux, suggesting their coordinated regulation of dermal pigmentation(Yang et al. 2024). Mechanistically, E2 directly stimulates melanogenesis in melanocytes(Natale et al. 2016). Cross-species evidence demonstrates that E2 promotes systemic hair pigmentation in female mice while suppressing it in males(Hirobe et al. 2010). This concentration-dependent regulatory paradigm implies that variations in E2 abundance may underlie phenotypic divergence in melanin synthesis and deposition dynamics(Tian et al. 2021).We therefore propose that ovarian development in hens may contribute to the higher HVP incidence rate observed in females compared to roosters. Conclusion Based on the above analysis, we propose that the formation of HVP results from the combined effects of multiple factors (Fig 11): (1) Melanocytes in the HVP region originate from aberrant differentiation of NCCs migrating from the ventromedial pathway. RA signaling regulates the specific expression of HOX genes, inducing NCCs to differentiate into SCPs before committing to melanocyte lineage. (2) Post-transcriptional dysregulation of DCN and VCAN in the Fib1 cluster leads to loss of barrier molecules. Through the SEMA3C-PLXND1 axis, Fib1 and Fib2 cell clusters in the peritoneal region attract melanocytes, enabling them to breach the normal migratory barrier and enter the peritoneum. (3) Upon melanocyte migration to the peritoneal region, Fib2 and Fib4 clusters enhance cellular adhesion via the TNC-SDC1 axis, facilitating melanocyte colonization in the peritoneal tissue. (4) While participating in ECM remodeling, estradiol concurrently promotes the substantial synthesis and deposition of melanin by melanocytes, ultimately driving the formation of the HVP phenotype. This regulatory mechanism, associated with ovarian development, likely represents a feature specific to hens. Abbreviations HVP: Hyperpigmentation of the visceral peritoneum; NCCs: Neural crest cells; SCPs: Schwann cell precursors; scRNA-seq: single-cell RNA sequencing; ECM: Extracellular matrix; DEGs: Differential expression genes; E2: Estradiol; SF: Silky fowl; L-R: Ligand-receptor. Declarations Data availability The original sequencing data of scRNA-seq has been uploaded to the GSA database, Bioproject number: CRA026581, and can be accessed directly at https://ngdc.cncb.ac.cn/gsa/s/ulg7q0Ea. Acknowledgements We thank Xingtai Modern Agriculture Co., Ltd. (Longmen, Huizhou, Guangdong) for technical support in sample collection. Funding This study was supported by the ''China Agriculture Research System (Grant No. CARS-41) '', and the National Key Research and Development Program of China（2021YFD1300102). Author information Authors and Affiliations Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong Province, China. Zhengyang Chen, Changbin Zhao, Xiaoyin Zeng, Xueyin He, Chengyue Yuan & Xiquan Zhang Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China. Zhengyang Chen, Changbin Zhao, Xiaoyin Zeng, Xueyin He, Chengyue Yuan & Xiquan Zhang State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, China. Zhengyang Chen, Changbin Zhao, Xiaoyin Zeng, Xueyin He, Chengyue Yuan & Xiquan Zhang Contributions Zhengyang Chen conceived and performed the experiments, analyzed the scRNA-seq data, and wrote the manuscript. Changbin Zhao formulated the strategy of bioinformatic analysis. Xiaoyin Zeng, Xueyin He, and Chengyue Yuan participated in the experiment and proofread the manuscript. Xiquan Zhang conceived this study, revised and approved the final manuscript. All authors contributed to the article and approved the submitted version. Corresponding author Correspondence to Xiquan Zhang. Ethics approval All animal experiments were performed according to the protocols approved by the South China Agriculture University Institutional Animal Care and Use Committee (approval number: SCAU#0106; 25 November 2018). All animal procedures followed the regulations and guidelines established by this committee and minimized the suffering of animals. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. References Adameyko I, Lallemend F, Aquino JB, Pereira JA, Topilko P, Muller T, Fritz N, Beljajeva A, Mochii M, Liste I, Usoskin D, Suter U, Birchmeier C, Ernfors P. 2009. Schwann cell precursors from nerve innervation are a cellular origin of melanocytes in skin. Cell 139(2): 366-379. https://doi.org/10.1016/j.cell.2009.07.049. 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Primer Sequences Gene Forward primer Reverse primer TM (℃) Product size (bp) MITF ATCCTTGGCTTGATGGACCC GCTCTCGCTTCTGACTCTGT 60 176 TYRP1 CCAAGCCAAGGTGACAAT CCTGACGGAATAATAATGAGA 55 145 DCT CAGAGACACACTCCTAGGGC CATTGCCCATCAATCGCTGC 60 134 DHRS3 CCACACGAGCACAGAGATGT GGCCTGAGGGAGAATGCTTTT 60 181 DACT1 GTCGTCCAAGTTCAGGGTTTT TGCAGATTTAGGGCGTCCAT 60 170 VCAN CGCTGGCTGTTGATGGTGTGTA ATGCTGCCTTCAGTTGCTCT 60 100 DCN GCATCGCAGACACCAACATT AAGCTGAGACCCAATTTAGCCA 60 145 EDNRB TGGCCCTTTGGTGTCGAAAT CAACTGCTCGGTACCTGTCT 60 112 TYR TGGAAGGCTTTGCTGATCCA CCACCGCTCAAAAATGCTGTC 60 170 COL1A1 CCAAAGGGAACAGCGGTGAA CTCCTCTCTCTTGCCTTCCTCG 60 126 COL1A2 CTGGTAACCGTGGTGCTAGT GACCTGGGGGAGACCTCTTGGA 60 105 TNC CGGCTACAACAGAGGCAGAA CGCTCATGGCCTGGTACTAT 60 178 SDC1 CCGGGAGACTTCATCTTGGT GTCCTCCAGCAATAACACCTCC 60 151 FN1 ACCAAGTTGGAGAGCAGTGG GCAGTTGACGTTGGTGTTTG 60 197 MLPH AGGTGGTTCAGCGTGACTTC ACCGATCTTCACCACCCTGG 60 290 MYO5A GCCTGGACACAAAAGAACGG CTCACTTGGCTCCTCCATCC 60 115 RAB27A CCTAGCACTTGGTGACTCTGG TGGGTCTGTACACCACTCTCT 60 131 SDC2 TGCCTGCACAAACAAAGTCAC ACCAATAACTCCGCCAGCAA 60 179 SDC4 CGCCGAGTCGGTGAGA ACAGTGGTCAGGTATATGGCA 60 192 SDCBP CTCAGCCACAAGGTCAACTG TCCAATTTTTCCGTCTTGATCTTT 60 149 GAPDH TCGGAGTCAACGGATTTGGC TTCCCGTTCTCAGCCTTGAC 60 181 Table 3. Celltype Marker Cluster Celltype Marker 0 Fibroblasts LUM 、 DCN 、 COL3A1 1 Endothelial cells VWF 、 ADGRL4 、 FLT1 2 Oligodendrocytes SOX6 、 CA2 、 MOG 3 Myofibroblasts MLYK 、 MYL9 、 MYH11 4 Macrophages CCL4 、 SPI1 、 C1QC 、 C1QB 5 T cells CD3D 、 CD3E 、 CD247 6 Muscle satellite cells MYF5 、 PAX7 7 Schwann cells SOX10 、 PLP1 、 CD9 8 Melanocytes MLANA 、 MLPH 、 PMEL Table 4. The intersection of DAPs and DEGs 40B-N 120B-N UP DOWN CHANGE UP DOWN CHANGE CYP7B1 BMPER BF2 SLC16A12 SULT1B DACT1 CAMKMT CD74 TENM1 DCT EVA1CL CDK EPB41L3 LY86 CDK2 EPB42 MRPL50 CHPF FBX042 PRKAR2B CPNE8 FMNL2 TRAPPC2L G6PC3 FOXP2 GOLIM4 GDA ME3 GPNMB P2RX7 HBAD PIPTNC1 HMGA1 POLA2 HOMER1 PTPRS HSD17B12 RAB18L IGSF3 RNF41 KRT10 ROR1 KRT13 RPL32 KRT17 RPL8 LRRC47 SLC25A1 OSBPL8 SMCR8 PES1 SURF2 PPP2R5D TBX3 SLC37A4 TMX2 ST14 VCAN SUN2 WRB TRAPPC5 YEATS2 TYRP1 UGCG VANGL1 YIPF6 Additional Declarations No competing interests reported. Supplementary Files DCN10S.tif VCAN30S.tif GAPDH5S1.tif Cite Share Download PDF Status: Published Journal Publication published 14 Nov, 2025 Read the published version in Functional & Integrative Genomics → Version 1 posted Editorial decision: Revision requested 27 Aug, 2025 Reviews received at journal 26 Aug, 2025 Reviews received at journal 23 Aug, 2025 Reviews received at journal 21 Aug, 2025 Reviews received at journal 21 Aug, 2025 Reviewers agreed at journal 15 Aug, 2025 Reviewers agreed at journal 13 Aug, 2025 Reviewers agreed at journal 13 Aug, 2025 Reviewers agreed at journal 13 Aug, 2025 Reviewers agreed at journal 13 Aug, 2025 Reviewers agreed at journal 12 Aug, 2025 Reviewers invited by journal 11 Aug, 2025 Editor assigned by journal 06 Aug, 2025 Submission checks completed at journal 06 Aug, 2025 First submitted to journal 29 Jul, 2025 You are reading this latest preprint version 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-7241140","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":501803781,"identity":"44cbf800-9028-4eb8-b99b-83d5a6c84e04","order_by":0,"name":"Zhengyang Chen","email":"","orcid":"","institution":"South China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Zhengyang","middleName":"","lastName":"Chen","suffix":""},{"id":501803782,"identity":"8e0f8bc3-8fdf-4158-ac2a-b0de16afc6f7","order_by":1,"name":"Changbin Zhao","email":"","orcid":"","institution":"South China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Changbin","middleName":"","lastName":"Zhao","suffix":""},{"id":501803783,"identity":"2a12b0b8-1d9d-4775-b55a-5a6c4140fdb4","order_by":2,"name":"Xiaoyin Zeng","email":"","orcid":"","institution":"South China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyin","middleName":"","lastName":"Zeng","suffix":""},{"id":501803784,"identity":"700aab4d-1a99-4370-b5d8-8ad1fe6e6d00","order_by":3,"name":"Xueyin He","email":"","orcid":"","institution":"South China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xueyin","middleName":"","lastName":"He","suffix":""},{"id":501803785,"identity":"63618959-e7ba-4ad8-8ece-b36ae071a621","order_by":4,"name":"Chengyue Yuan","email":"","orcid":"","institution":"South China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Chengyue","middleName":"","lastName":"Yuan","suffix":""},{"id":501803786,"identity":"a19fcffd-97c3-410a-851d-24e06c81046e","order_by":5,"name":"Xiquan Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1klEQVRIiWNgGAWjYHACNhAhB+UwE6/FmHQtiQ1EazE4nv7swc8dtenz2w8/k2CosE5sYD97AK8WyZ4H6Ya9Z47nbjiTZibBcCY9sYEnLwGvFn6JhGMSvG3HcjdIMJhJMLYdTmyQ4DHA7xGJxDbJv23H0uVnsH+TYPxHhBZ+iWQ2ad62mgSGGzxAWxqI0CLZ84xNWrbtgOGGMznFFgnH0o3beHLwawGFmOTbtjp5+fbjG298qLGW7Wc/g18LA0MCiDiMYLMRUA/TUkdY3SgYBaNgFIxcAADkwUHVYAPOOAAAAABJRU5ErkJggg==","orcid":"","institution":"South China Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Xiquan","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-07-29 08:53:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7241140/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7241140/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10142-025-01726-7","type":"published","date":"2025-11-14T15:58:05+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89399137,"identity":"e8613c69-63cc-4136-83f4-9aa6771ef73c","added_by":"auto","created_at":"2025-08-19 13:58:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":5694542,"visible":true,"origin":"","legend":"\u003cp\u003eDimensionality reduction clustering (a) Single-cell sequencing process. (b) Violin plots showing the total number of cell mRNA molecules (UMI), number of detected genes per cell, and mitochondrial gene percentage; quality control filters applied are 200 \u0026lt; nFeature \u0026lt; 2000, and percent.mt \u0026lt; 15%. (c) UMAP plot for dimensionality reduction of individual samples. (d) Cell cluster-specific marker gene expression. (e) Expression levels of candidate proteins from proteomics. (f) Proportion of cell clusters among samples.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/8d058bac921676c7d4938e2a.png"},{"id":89396752,"identity":"a24cf9b7-6ce5-4956-b19d-988d57c117f5","added_by":"auto","created_at":"2025-08-19 13:42:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2613983,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of DEGs in melanocytes (a) Volcano plots showing DEGs in melanocytes across multiple groups, with |log2FC| \u0026gt; 1 and P-value \u0026lt; 0.05. Red indicates upregulated genes, green indicates downregulated genes, and gray indicates no significant difference genes. (b) Intersection of DEGs, with red representing upregulated genes, green indicating downregulated genes, and gray showing inconsistent trend genes. (c-d) Functional enrichment analysis of DEGs in the 40B-N group: left for KEGG enrichment analysis (red for upregulated pathways, blue for downregulated pathways); right for GO enrichment analysis. (e-f) Functional enrichment analysis of DEGs in the 120B-N group: left for KEGG, right for GO.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/67dacfd15db1fa6ce70b3ee4.png"},{"id":89396753,"identity":"43236448-dc5b-4fe1-ac65-05cd9bb427d0","added_by":"auto","created_at":"2025-08-19 13:42:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3938631,"visible":true,"origin":"","legend":"\u003cp\u003eCell-cell communication analysis (a) Global communication patterns in 40B-N. Left: number of communication pathways; right: communication strength. (b) 2D plot of outgoing/incoming signal strength between 40B and N cell clusters (Y-axis: incoming signals; X-axis: outgoing signals). (c) Global communication patterns in 120B-N. (d) 2D plot of outgoing/incoming signal strength between 120B and N cell clusters. (e) Inter-cluster communication in 40B-N. Red lines indicate upregulated quantity/strength; blue lines indicate downregulated quantity/strength. (f) Heatmap of inter-cluster communication in 40B-N (red: upregulation; blue: downregulation; all relative to N group as control). (g) Inter-cluster communication in 120B-N. (h) Heatmap of inter-cluster communication in 120B-N. (i) Pathway-level comparison in 40B-N. Top red pathways are enriched in the B group; bottom green pathways are enriched in the N group. (j) Pathway-level comparison in 120B-N. (k) Visualization of L-R communication probability for SEMA3 pathway in 40B-N (fibroblasts to melanocytes). (l) Visualization of L-R communication probability for TNC pathway in 40B-N (fibroblasts to melanocytes). (m) Visualization of L-R communication probability for TNC pathway in 120B-N (fibroblasts to melanocytes). (n) Visualization of L-R communication probabilities for SEMA3 pathway in 40B-N (fibroblasts to Schwann cells). (o) Visualization of L-R communication probabilities for TNC pathway in 40B-N (fibroblasts to Schwann cells). (p) Visualization of L-R communication probabilities for TNC pathway in 120B-N (fibroblasts to Schwann cells).\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/ed2cd9d7dca8dcf566664319.png"},{"id":89396756,"identity":"cb278cbf-7301-47df-8db9-98a1415844dd","added_by":"auto","created_at":"2025-08-19 13:42:16","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":3397331,"visible":true,"origin":"","legend":"\u003cp\u003eTranscription factor prediction in SCPs lineage cells (a) TF activity heatmap: Red indicates upregulated expression in corresponding cell clusters; blue indicates no expression/downregulation. \"+\" denotes activated TFs; \"-\" denotes inactive TFs. (b) Top 5 TFs ranked by regulon specificity score (RSS) per sample. (c) RSS scores of TFs with Z-score \u0026gt; 2. (d) Bubble plot showing expression levels of activated TFs (Z-score \u0026gt; 2) across cell clusters. (e-g) Downstream gene regulatory networks for IRF7, HOXD8, and HOXA4.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/30fe3269f320541008cef230.png"},{"id":89396763,"identity":"f557b240-abce-4b92-9172-32186f7ef3c8","added_by":"auto","created_at":"2025-08-19 13:42:16","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":6353013,"visible":true,"origin":"","legend":"\u003cp\u003ePseudotemporal analysis of melanocytes (a) CytoTRACE score UMAP projection of melanocytes and Schwann cells. (b) Boxplot of CytoTRACE scores for melanocytes and Schwann cells. (c) Pseudotime trajectory of melanocytes. (d) State distribution along the pseudotime axis. (e) Sample distribution of melanocytes across pseudotime stages. (f) Cluster heatmap of temporally-regulated genes with associated KEGG enrichment analysis. (g) BEAM analysis for the branch point 1.\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/d5a6533c38b00070a48e3633.png"},{"id":89397818,"identity":"b0ad7e75-3909-4558-870f-b69d676617ab","added_by":"auto","created_at":"2025-08-19 13:50:16","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2991325,"visible":true,"origin":"","legend":"\u003cp\u003eWeighted gene co-expression network analysis (a) Hierarchical clustering dendrogram of isolated modules shown in different colors, where the gray module represents a set of genes that do not cluster into other modules. (b) Expression levels of modules in Schwann cells and melanocytes. (c) Module expression within samples. (d) Visualization of module expression on UMAP plots. (e) PPI network of genes within Module 1.\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/a2e23956e668e86cd75e612c.png"},{"id":89396759,"identity":"4c7f4017-5649-4e15-af65-ce9d5f2a863c","added_by":"auto","created_at":"2025-08-19 13:42:16","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":6538536,"visible":true,"origin":"","legend":"\u003cp\u003eFibroblast subclusters analysis (a) KEGG enrichment analysis of fibroblast clusters in 40B-N. (b) KEGG enrichment analysis of fibroblast clusters in 120B-N. (c) Cluster-specific expressed genes in fibroblast subpopulations. (d) Expression profiles of candidate proteins within subclusters. (e) Volcano plot of DEGs in fibroblasts for 40B-N, with |log2FC| \u0026gt; 1 and P-value \u0026lt; 0.05; red indicates upregulation, green indicates downregulation, gray indicates no significant difference. (f) Volcano plot of DEGs in fibroblast subclusters for 120B-N. (g) Quantification of proteoglycan-related genes. (h) Visualizing L-R communication probability for SEAM3 pathway in 40B-N (fibroblast subclusters to melanocytes). (i) Visualizing L-R communication probability for TNC pathway in 40B-N (fibroblast subclusters to melanocytes). (j) Visualizing L-R communication probability for TNC pathway in 120B-N (fibroblast subclusters to melanocytes).\u003c/p\u003e","description":"","filename":"Fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/afd933520a3ee7ef09835ae8.png"},{"id":89397815,"identity":"b203f198-ad60-423d-8641-130936b9b720","added_by":"auto","created_at":"2025-08-19 13:50:16","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":436839,"visible":true,"origin":"","legend":"\u003cp\u003eDual-omics analysis (a) Co-expression gene-protein network in 40B-N, with red indicating upregulation, green indicating downregulation, and gray representing inconsistent trends. (b) Co-expression gene-protein network in 120B-N. (c) KEGG enrichment analysis of co-expressed genes in 40B-N, with red representing upregulated pathways and blue representing downregulated pathways.\u003c/p\u003e","description":"","filename":"Fig8.png","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/df85dabfec02219e034bb9b2.png"},{"id":89396764,"identity":"fe7b7e70-be80-4d8e-aeae-7eb4e4984666","added_by":"auto","created_at":"2025-08-19 13:42:16","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":4128651,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional validation of \u003cem\u003eSDC1\u003c/em\u003e (a) Cell suspension obtained after peritoneal digestion. (b) Adherent morphology of purified cells after 24 h in culture. (c) Endogenous Tyr depletion – melanin synthesis is halted. (d) Melanin resynthesis upon exogenous Tyr supplementation (Scale bar: 200 μm). (e) Immunofluorescence identification using melanocyte-specific markers Melan-A and TYR (Scale bar: 100 μm). (f) Melanogenesis-related gene expression after \u003cem\u003eSDC1\u003c/em\u003einterference. (g) Intracellular melanin content under different treatments after \u003cem\u003eSDC1\u003c/em\u003e interference. (h) Tyrosinase enzyme activity changes after \u003cem\u003eSDC1\u003c/em\u003einterference. (i) The interaction genes of \u003cem\u003eSDC1\u003c/em\u003e from GeneMANIA database. (j) mRNA expression changes of interacting genes after SDC1 interference. (k) Migration capability comparison of melanocytes after SDC1 interference. (l) Wound healing assay demonstrating migration effects after SDC1 interference.\u003c/p\u003e","description":"","filename":"Fig9.png","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/f1dbc3ff551d4612a89f83a2.png"},{"id":89397825,"identity":"939bfa40-0de6-4595-a76d-0ee907adf221","added_by":"auto","created_at":"2025-08-19 13:50:16","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":1349692,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of E2 treatment on melanocytes and DF-1 cells. (a) Quantification of ECM-related genes in DF-1 cells after E2 treatment. (b) Sulfated proteoglycans abundance in DF-1 cells after E2 treatment by Western blot. (c) Quantification of melanogenesis-related genes in melanocytes after E2 treatment. (d) Changes in intracellular melanin content.\u003c/p\u003e","description":"","filename":"Fig10.png","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/442244fbcf7d5a963c1b9e38.png"},{"id":89397819,"identity":"9263c6a9-94ff-462b-96fb-0b075644a4b5","added_by":"auto","created_at":"2025-08-19 13:50:16","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":2459256,"visible":true,"origin":"","legend":"\u003cp\u003eThe molecular mechanism of HVP formation was speculated based on the results of our study\u003c/p\u003e","description":"","filename":"Fig11.png","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/3661e95fd078b52237aec09d.png"},{"id":96105238,"identity":"464672ec-3ef4-4d0b-8db5-f5374c71a2bf","added_by":"auto","created_at":"2025-11-17 16:10:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":40499820,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/1b6f1491-74e3-4215-b7fa-5f2e9fe7e16e.pdf"},{"id":89396761,"identity":"bc182780-17f6-4e45-97fd-a65e015c6365","added_by":"auto","created_at":"2025-08-19 13:42:16","extension":"tif","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":380208,"visible":true,"origin":"","legend":"","description":"","filename":"DCN10S.tif","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/ce90f6ce2ffd215401bdd884.tif"},{"id":89396754,"identity":"2956410c-ef8c-445a-987a-0c57ea3d5d98","added_by":"auto","created_at":"2025-08-19 13:42:16","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":380208,"visible":true,"origin":"","legend":"","description":"","filename":"VCAN30S.tif","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/9812616332906f4fe911c6ab.tif"},{"id":89397814,"identity":"243b213e-5c29-4da2-bbe9-2ab5ab5db4ea","added_by":"auto","created_at":"2025-08-19 13:50:16","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":380208,"visible":true,"origin":"","legend":"","description":"","filename":"GAPDH5S1.tif","url":"https://assets-eu.researchsquare.com/files/rs-7241140/v1/c6ef531654a2522eacfd5001.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Aberrant Migration and Differentiation of Neural Crest Cells Led to the Production of HVP in Bearded Chicken","fulltext":[{"header":"Background","content":"\u003cp\u003eHyperpigmentation of the visceral peritoneum (HVP), characterized by localized melanin deposition predominantly in the peritoneal region, significantly compromises broiler growth performance and carcass yield\u0026mdash;yet remains poorly investigated(Wang et al. 2024). Genome-wide association analysis identified \u003cem\u003eCYP2D6\u003c/em\u003e as a key genetic determinant underlying HVP formation(Zhou et al. 2022). As a critical enzyme in retinoic acid biosynthesis(Ning et al. 2019), \u003cem\u003eCYP2D6\u003c/em\u003e functionally implicates retinoic acid levels in HVP pathogenesis. HVP recapitulates the systemic melanosis of Silky fowl (SF), showing ectopic pigmentation across 7 organ systems. GWAS analyses implicate coordinated actions of FM-CNVs and the Z-linked ID locus in driving this phenotype(Leng et al. 2025). Retrospective analyses from the 1960s revealed significantly higher HVP prevalence in hens versus roosters, leading early investigators to postulate sex-linked and sex-limited inheritance mechanisms underlying this phenotype(Huntsman et al. 1959, 1960; Kuit 1967). In our previous study, we found that the formation of HVP is due to the delamination and migration of neural crest cells (NCCs)mediated by Wnt signaling pathway and retinoic acid signaling pathway(Chen et al. 2025).\u003c/p\u003e\n\u003cp\u003eNCCs were found in chick embryos by William Heath in 1868 and described as \u0026apos;\u003cem\u003eZwischenstrang\u003c/em\u003e\u0026apos;, a group of migrating cells that appear between the ectoderm and the neural tube(Huang and Saint-Jeannet 2004). NCCs originate from closed neural tubes and are a group of pluripotent stem cells with migration ability. This short-lived group consists of four subgroups along the body axis from the beak to the tail: skull, vagus nerve, trunk, and sacrum(Jacobs-Li et al. 2023). NCCs undergo epithelial-to-mesenchymal transition and migrate along defined pathways throughout the embryo to reach specific destinations within various tissues and organs, where they complete their differentiation. The development of the neural crest involves several critical steps: induction, delamination, specification, and migration. NCCs have the potential to differentiate into multiple cell types, including melanocytes, most peripheral neurons, glial cells, and craniofacial chondrocytes(Vandamme and Berx 2019). Through mesenchymal migration during embryonic development, NCCs differentiate into Schwann cell precursors (SCPs), which subsequently further differentiate into melanocytes(Adameyko et al. 2009).\u003c/p\u003e\n\u003cp\u003eIn this study, we employed scRNA-seq on peritoneal samples from Huiyang bearded chickens at 40 and 120 d of age to generate single-cell atlases of different peritoneal layers, aiming to identify key pathways and candidate genes associated with HVP formation.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eSample collection and cell source\u003c/h2\u003e\n\u003cp\u003eExperimental animals used for sample collection were provided by Xingtai Modern Agriculture Co., Ltd., located in Longmen County, Huizhou City, Guangdong Province, and were all fed under the same husbandry conditions. The study included 30 hens at 40 d of age and 30 hens at 120 d of age. Blood was drawn from the jugular vein of the hens, followed by the collection of peritoneal samples, which were immediately placed on ice for HVP grading. Collected samples were promptly snap-frozen in liquid nitrogen and stored at -80℃. The peritoneum was classified into three categories: normal (N), transitional (F), and black (B), and named according to age and phenotype as 40B, 40F, 40N, 120B, 120F, and 120N. Samples were used for scRNA-seq, with three biological replicates per group. After pooling, single-cell suspensions were prepared (Fig 1a).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSilky fowl fertilized eggs used for isolating primary melanocytes were obtained from Taihe, Jiangxi Province. The chicken fibroblast cell line (DF-1) was obtained from the laboratory\u0026rsquo;s frozen stocks.\u003c/p\u003e\n\u003ch2\u003eSingle-cell Suspension Preparation\u003c/h2\u003e\n\u003cp\u003eThe peritoneal samples were digested with collagenase I and trypsin until flocculent within 12 h of collection to prepare single-cell suspensions. Cell viability was assessed using AO/PI dual-fluorescence staining on the Countstar Rigel system, with a viability threshold \u0026gt; 90% for qualification. Single-cell GEMs (Gel Bead-in-Emulsions) were prepared using the Chromium Next GEM Single Cell 3ʹ GEM, Library \u0026amp; Gel Bead Kit v3.1 (10\u0026times; Genomics #1000121) on the Chromium Controller platform (10\u0026times; Genomics). Subsequently, reverse transcription was performed on the GEMs, followed by cDNA recovery (using Beckman magnetic beads #B23318) and purification to construct cDNA libraries. Sequencing was conducted on the Illumina NovaSeq 6000 platform with a PE150 strategy.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eBioinformatic Analysis of Sequencing Data\u003c/h2\u003e\n\u003cp\u003eThe raw FASTQ files were processed using CellRanger for pre-processing, including barcode extraction, UMI identification, and gene sequence alignment. The sequencing reads were mapped to the reference genome (Red Jungle Fowl, Gallus gallus, GRCg6a assembly) obtained from the Ensembl database. This pipeline generated a gene expression matrix along with cell barcode information, which was subsequently used for downstream bioinformatic analyses.\u003c/p\u003e\n\u003cp\u003eBased on the R package Seurat, a single-cell transcriptome analysis pipeline was constructed. Double cells were removed from six samples individually using the R package DoubletFinder, with a doublet rate of approximately 5.5%. The downstream analysis pipeline included quality control, clustering and dimensionality reduction, cell type annotation, differential expression genes (DEGs) analysis, and visualization. To ensure high-quality cells were retained for downstream analysis, genes expressed in fewer than 3 cells and cells expressing fewer than 200 genes were excluded. The R package clustree was used to select an appropriate clustering resolution. Clustering analysis was performed using the RunUMAP function, and clustering was identified using the FindClusters function with an enhanced resolution parameter of 0.1. Marker genes for each cell cluster were identified using the FindAllMarkers function (min.pct = 0.25, logfc.threshold = 0.25). DEGs between B and N cell clusters were calculated using the FindMarkers function with thresholds of |log2FC| \u0026gt; 1 and \u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.05.\u003c/p\u003e\n\u003ch3\u003eCellchat Analysis\u003c/h3\u003e\n\u003cp\u003eThe R package CellChat was employed to construct a CellChat object using the count matrices extracted from Seurat objects of each sample, based on a ligand-receptor (L-R) interaction database. This framework enables systematic inference of: L-R interaction strength at the cellular level, signaling pathway activity across cell populations, and global communication probability between samples. Special emphasis was placed on investigating fibroblast-melanocyte crosstalk. The likelihood and biological relevance of intercellular ligand-receptor interactions were visualized via heatmaps, highlighting key cell cluster-specific communication events.\u003c/p\u003e\n\u003ch3\u003eGO and KEGG Enrichment Analysis\u003c/h3\u003e\n\u003cp\u003eGene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on DEGs identified by FindMarkers using the R package clusterProfiler. Specifically, the enrichGO and enrichKEGG functions were employed to systematically characterize the biological functions and pathways associated with the DEGs.\u003c/p\u003e\n\u003ch3\u003epySCENIC Analysis\u003c/h3\u003e\n\u003cp\u003eThe count matrix was extracted from the Seurat object, and the pySCENIC environment was configured using Python 3.7 to generate loom files. Based on the GRNBoost2 algorithm, co-expression modules between transcription factors (TFs) and target genes were constructed. The authenticity of the regulatory networks between TFs and target genes was validated using RcisTarget, and the regulatory networks were filtered by calculating the AUC curve. Subsequent visualization was performed using the R package SCENIC.\u003c/p\u003e\n\u003ch3\u003ePseudotime Analysis\u003c/h3\u003e\n\u003cp\u003ePseudotime analysis of melanocytes was performed based on the R package monocle. After filtering out low-quality cells, differential gene analysis was conducted using the built-in functions of monocle. The results were visualized using the plot_cell_trajectory, BEAM, and clusterAndVisualize functions.\u003c/p\u003e\n\u003ch3\u003ehdWGCNA Analysis\u003c/h3\u003e\n\u003cp\u003eThe weighted gene co-expression network analysis (WGCNA) of Schwann cells and melanocytes was performed using the R package hdWGCNA, with visualization conducted using built-in functions from hdWGCNA.\u003c/p\u003e\n\u003ch2\u003eCell Culture\u003c/h2\u003e\n\u003cp\u003eNewly hatched (1 d) Silky fowl chicks were selected for melanocyte isolation. The black peritoneal tissue was carefully dissected and washed three times with PBS. Tissue digestion was performed using a dual-enzyme approach (trypsin: dispase Ⅱ= 1:1 ratio) for 45 min, followed by sequential filtration through 100 \u0026mu;m and 70 \u0026mu;m cell strainers to obtain melanocytes. When cells reached 80-90% confluency, they were detached using 0.25% trypsin for 5 min, followed by centrifugation and resuspension to obtain purified melanocytes. The cells were maintained at 37℃\u0026nbsp;with 5% CO₂ in human primary melanocytes complete medium (254 Medium (M254500), Human Melanocyte Growth Supplement-2 (S0165), Thermo Fisher).\u003c/p\u003e\n\u003cp\u003eDF-1 was cultured in a complete medium consisting of 10% FBS (10099-141C, Thermo Fisher) and 1% penicillin-streptomycin (Gibco) at 37℃\u0026nbsp;with 5% CO₂.\u003c/p\u003e\n\u003ch2\u003eTransfection\u003c/h2\u003e\n\u003cp\u003eMelanocytes were seeded in 12-well plates and transfected using Lipofectamine\u0026reg; 3000 according to the manufacturer\u0026apos;s instructions when reaching 80% confluence. SiRNA targeting chicken \u003cem\u003eSDC1\u003c/em\u003e (XM_419972.7) was synthesized by Gene Create Biotechnology Co., Ltd (Wuhan, China) based on the mRNA sequences from the NCBI database, with negative control siRNA used for control transfection. The siRNA sequences are listed in Table 1.\u003c/p\u003e\n\u003ch2\u003eTreatment of DF-1 and Melanocytes with 17\u0026beta;-estradiol.\u003c/h2\u003e\n\u003cp\u003eCells were treated with 17\u0026beta;-estradiol (E2, Psaitong, China) at concentrations of 0, 1, 5, and 10 \u0026mu;M for DF-1 cells, and 0 and 5 \u0026mu;M for melanocytes, respectively. After 24 h of treatment, cellular RNA was extracted for quantitative experiments.\u003c/p\u003e\n\u003ch2\u003eDetection of Cell Melanin Content\u003c/h2\u003e\n\u003cp\u003eCells were seeded into the plates and allowed to adhere. Following experimental treatments, the supernatant was discarded after 24 h, and the cells were washed twice with PBS. Subsequently, 1 mL of NaOH (1 mol/L, containing 10% DMSO) was added to each well to lyse the cells. The plates were then incubated in a metal water bath at 80℃ for 30 min. After incubation, 100 \u0026mu;L of the lysate from each well was transferred to a 96-well plate, and the absorbance was measured at a wavelength of 405 nm.\u003c/p\u003e\n\u003ch2\u003eDetermination of Tyrosinase Activity\u003c/h2\u003e\n\u003cp\u003eCells were seeded into the plates and allowed to adhere. After experimental treatments, the supernatant was discarded at 24 h, and the cells were washed twice with PBS. Subsequently, 100 \u0026mu;L of 0.1% Triton X-100 solution was added to each well to lyse the cells for 30 min, followed by centrifugation at 4℃. Then, 40 \u0026mu;L of the supernatant was mixed with 160 \u0026mu;L of 5 mM L-DOPA and incubated at 37℃\u0026nbsp;for 1 h. The absorbance was measured at a wavelength of 475 nm.\u003c/p\u003e\n\u003ch2\u003eWound Healing Assay\u003c/h2\u003e\n\u003cp\u003eThe cell culture inserts were first placed into 6-well plates to ensure tight adhesion. Subsequently, melanocytes with \u003cem\u003eSDC1\u003c/em\u003e interference were digested and centrifuged after 48 h, then seeded into the cell insert. After cell attachment, the inserts were carefully removed using sterile forceps, creating two separate cell populations with a \u0026quot;wound\u0026quot; gap in between. The plate was tilted to slowly add PBS, then tilted in the opposite direction to allow PBS to flow across the cell surface without dislodging cells, repeated twice. A complete medium was added using the same technique for subsequent culture. Images covering the wound area were captured at 0, 24, and 48 h post-attachment. Micrographs were taken using a CCD camera connected to an inverted stage-contrast microscope at 5\u0026times; magnification.\u003c/p\u003e\n\u003ch2\u003eWestern blot\u003c/h2\u003e\n\u003cp\u003eAfter treating DF-1 cells with E2, proteins were extracted and their concentrations measured. Following denaturation, proteins were separated by SDS-PAGE and transferred onto PVDF membranes. The membranes were blocked with 5% skimmed milk for 1 h. Subsequently, they were incubated overnight with primary antibodies: Rabbit Anti-DCN antibody (A1669) and Rabbit Anti-VCAN antibody (A19655, ABclonal, China). Then incubate with the secondary antibody for 1 hour. Prepare the detection solution according to the instructions of the Chemiluminescent HRP Substrate (Millipore, America), and visualize the results using an ECL chemiluminescence imaging system.\u003c/p\u003e\n\u003ch2\u003eQuantitative Real-time PCR\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe relative gene expression levels were measured, and the effects of various treatments on extracellular matrix (ECM)-related genes and melanin synthesis genes were evaluated using quantitative real-time PCR. Cells were harvested at indicated times, and cells were lysed by Trizol Reagent. Total RNA reverse transcription was performed following the instructions of the HiScript Ⅲ All-in-one RT SuperMix Perfect for qPCR kit (Vazyme, China). The real-time fluorescence quantitative analysis was conducted according to the ChamQ SYBR qPCR Master Mix kit instructions (Vazyme, China). The specific primers for qPCR were designed using the NCBI online website. All primers were synthesized by Tsingke Biotech Technology Co., Ltd. (Guangzhou, China). The data from quantitative real-time PCR were analyzed using the 2\u003csup\u003e\u0026minus;\u0026Delta;\u0026Delta;Ct\u003c/sup\u003e method, with the chicken \u003cem\u003eGAPDH\u003c/em\u003e gene serving as the housekeeping gene. Statistical analysis and graph plotting were performed using GraphPad Prism 5 software. Differences between groups were assessed with an unpaired Student\u0026rsquo;s t-test. Each group included at least three replicates (n \u0026ge; 3). A \u003cem\u003eP\u003c/em\u003e-value \u0026gt; 0.05 was considered not statistically significant (ns), while \u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.05 was considered statistically significant (*). \u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.01 and \u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.001 were considered highly significant (** and ***, respectively). The primer sequences used in qRT-PCR are shown in Table 2.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eSingle-cell Atlas of Chicken Black Peritoneum\u003c/h2\u003e\n\u003cp\u003eThe single-cell atlas of HVP comprised 41,395 quality-controlled cells (Fig 1b), comprising 6,338 (40B), 5,659 (40F) and 12,967 (40N) cells for the 40-series samples, along with 6,547 (120B), 6,518 (120F) and 3,719 (120N) cells for the 120-series samples.\u003c/p\u003e\n\u003cp\u003eBased on gene expression similarity within clusters and statistically significant differential expression between clusters through PCA/UMAP analysis in Seurat, we developed a UMAP plot comprising nine distinct cell clusters (Fig 1c). A list of biomarkers for each cluster was generated using t-tests in Seurat (FDR \u0026lt; 0.05). By combining the most highly DEGs and established cell-specific markers, we identified and annotated nine cell populations in chicken HVP: fibroblasts were characterized by \u003cem\u003eLUM\u003c/em\u003e, \u003cem\u003eDCN\u003c/em\u003e, and \u003cem\u003eCOL3A1\u003c/em\u003e expression; Schwann cells by specific expression of \u003cem\u003eCDH19\u003c/em\u003e, \u003cem\u003ePLP1\u003c/em\u003e, and \u003cem\u003eCD9\u003c/em\u003e; and melanocytes by \u003cem\u003eMLPH\u003c/em\u003e, \u003cem\u003ePMEL\u003c/em\u003e, and \u003cem\u003eMLANA\u003c/em\u003e. Additionally, endothelial cells, oligodendrocytes, myofibroblasts, macrophages, T cells, and muscle satellite cells were identified through their characteristic gene expression patterns (Fig 1d, Table 3). The comparative proteomic screening revealed that fibroblasts expressed \u003cem\u003eVCAN\u003c/em\u003e and \u003cem\u003eDCN\u003c/em\u003e, while \u003cem\u003eDHRS3\u003c/em\u003e was co-expressed in melanocytes, Schwann cells, and fibroblasts (Fig 1e). UMAP projection distances between melanocytes and Schwann cells suggested that HVP melanocytes originate from the ventromedial migration pathway of NCCs and differentiate from SCPs, with varying SCPs lineage proportions across samples. Black peritoneal samples exhibited higher total SCPs lineage cells than normal peritoneal samples, containing the highest proportion of melanocytes (Fig 1f), whereas normal peritoneum showed the lowest melanocytes percentage. Although the maximum proportion reached only approximately 0.8%, compared to 3.6-4.9% in SF skin transcriptomes, and considering the \u0026lt; 0.2% melanocytes proportion in normal peritoneum, we speculate that minimal melanocytes aggregation suffices for HVP formation. This may explain our previous difficulty in isolating sufficient primary melanocytes from bearded chicken hyperpigmented peritoneum, prompting subsequent primary melanocytes isolations from SF samples with higher melanocytes abundance.\u003c/p\u003e\n\u003ch2\u003eGO and KEGG Enrichment Analysis of Melanocytes\u003c/h2\u003e\n\u003cp\u003eThe melanocytes proportions exhibited substantial variation across different samples, prompting further functional analysis of their DEGs to elucidate their potential roles in HVP. The 40B-N group displayed 1,301 DEGs (971 upregulated and 330 downregulated), while the 120B-N group contained 765 DEGs (35 upregulated and 730 downregulated) (Fig 2a). Comparative analysis identified 22 co-expressed genes shared between both groups (12 upregulated and 10 downregulated) (Fig 2b).\u003c/p\u003e\n\u003cp\u003eKEGG pathway enrichment analysis of upregulated DEGs in 40B-N melanocytes revealed significant enrichment in cellular senescence, melanogenesis, Wnt signaling pathway, and MAPK signaling pathway, while downregulated DEGs showed prominent enrichment in ribosome, cytoskeleton in myocytes, and extracellular matrix-receptor interactions (\u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.05) (Fig 2c). GO analysis demonstrated that the 1,301 DEGs were primarily enriched in MF including mRNA binding and protein kinase activity, CC involving anchoring junctions and ATPase complexes, and BP involving calcium ion-mediated signaling and melanin synthesis (Fig 2d). These findings collectively indicate that the melanocytes were in a state of highly active metabolism and proliferation.\u003c/p\u003e\n\u003cp\u003eKEGG pathway enrichment analysis of upregulated DEGs in 120B-N melanocytes demonstrated predominant enrichment in melanogenesis, apoptosis, Toll-like receptor signaling pathway, and focal adhesion, while downregulated DEGs were primarily associated with amino sugar and nucleotide sugar metabolism, bacterial invasion of epithelial cells, and butanoate metabolism (\u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.05) (Fig 2e). GO analysis revealed that the 765 DEGs were significantly enriched in MF including GTPase regulator activity, nucleoside-triphosphatase regulator activity, and isomerase activity; CC involving comprising synaptic membrane and postsynaptic specialization membrane; and BP involving regulation of defense response, negative regulation of response, and tube size regulation (Fig 2f). These findings collectively indicate that the melanocytes were undergoing enhanced immune response while maintaining viability, with this immunomodulatory activity potentially facilitating melanin deposition.\u003c/p\u003e\n\u003ch2\u003eAnalysis of Cell-cell Communication in HVP\u003c/h2\u003e\n\u003cp\u003eIdentifying cellular subpopulations that exhibit close communication with melanocytes constitutes a critical step in elucidating the pathological mechanisms of HVP. Cell-cell interaction network analysis revealed that compared to the normal peritoneum, the melanocytes in the black peritoneum demonstrated a significant increase in both the number of incoming pathways and signal intensity (Fig 3a, c). In 2D spatial analysis, melanocytes in the black peritoneum received substantially more cross-cluster regulatory signals than they emitted. Notably, fibroblasts displayed a distinctive bidirectional communication signature within the interaction network\u0026mdash;their coordinates for both outgoing and incoming signals ranked among the highest (Fig 3b, d), suggesting that this cellular subpopulation may function as a signaling hub. This hypothesis was corroborated by differential interaction analysis: in black peritoneum, the interaction strength and pathway diversity between fibroblasts and melanocytes exhibited marked differences compared to normal peritoneum (Fig 3e-h).\u003c/p\u003e\n\u003cp\u003eQuantification of key signaling pathway differences across samples was performed through ligand-receptor (L-R) interaction network analysis. The results demonstrated that the communication strength of the ANGPTL, SEMA3, and TENASCIN pathways in 40B was significantly higher than in 40N (Fig 3i), while the CD99 and TENASCIN pathways in 120B exhibited significantly stronger communication intensity compared to 120N (Fig 3j). The SEMA3 pathway, which is closely related to NCCs migration, has 30 pairs of L-R in 40B samples. Signal flow analysis revealed that fibroblasts acted as the primary signal source, transmitting \u003cem\u003eSEMA3\u003c/em\u003e ligands to \u003cem\u003ePLXNA/D\u003c/em\u003e receptors on the surface of melanocytes (Fig 3k). Among these interactions, the SEMA3C-PLXND1 axis exhibited the highest communication probability, suggesting that fibroblasts may predominantly drive the chemotactic migration of melanocytes through this axis. Fibroblasts similarly relied on the SEMA3C-PLXND1 axis to regulate Schwann cells migration (Fig 3n). However, the increased proportion of melanocytes within the SCPs lineage did not stem from migration selectivity, implying that fibroblasts may regulate the differentiation fate of SCPs through alternative mechanisms. Further analysis revealed that the TENASCIN pathway, as a core co-upregulated pathway during HVP progression, displayed cell type-specific activation patterns for its seven L-R pairs in disease samples: fibroblasts established adhesion-related signaling with melanocytes via the TNC-SDC1 axis (Fig 3l-m), whereas the TNC-SDC4 axis specifically modulated Schwann cells migration and exhibited dynamic switching within the developmental time window (activated in the HVP group at 40 d but shifted to the normal group at 120 d) (Fig 3o-p).\u003c/p\u003e\n\u003ch2\u003eInvestigation into the Differentiation of SCPs Lineage Cells\u003c/h2\u003e\n\u003cp\u003eThe specific differentiation of SCPs is primarily achieved through the selective expression of transcription factors. We constructed the transcriptional regulatory networks of melanocytes and Schwann cells using pySCENIC. Cross-group comparisons revealed that early-response transcription factors such as \u003cem\u003eJUN\u003c/em\u003e, \u003cem\u003eATF3\u003c/em\u003e, and \u003cem\u003eFOS\u003c/em\u003e exhibited significant transcriptional activity across all cell clusters in each group (Fig 4a). Through stringent screening criteria (Z-score\u0026gt;2), characteristic transcriptional regulators were identified for different treatment groups: \u003cem\u003eIRF7\u003c/em\u003e specifically regulated melanocytes in the B/F groups, \u003cem\u003eHOXD8\u003c/em\u003e selectively dominated melanocytes in 40B/40F, while \u003cem\u003eHOXA4\u003c/em\u003e was specifically activated in 120B/120F melanocytes (Fig 4b-d). Notably, the expression of \u003cem\u003eHOX\u003c/em\u003e gene family members in melanocytes displayed age-dependent specificity.\u003c/p\u003e\n\u003cp\u003eFunctional predictions of TFs were inferred based on their downstream regulatory networks, revealing that \u003cem\u003eIRF7\u003c/em\u003e is associated with pathways such as NF-\u0026kappa;B, CDK, and TGF-\u0026beta;, as well as dopachrome tautomerase \u003cem\u003eDCT\u003c/em\u003e (Fig 4e). \u003cem\u003eHOXA4\u003c/em\u003e and \u003cem\u003eHOXD8\u003c/em\u003e were found to regulate genes implicated in melanocytes function and differentiation, including \u003cem\u003eOCA2\u003c/em\u003e, \u003cem\u003eHPGDS\u003c/em\u003e, and \u003cem\u003ePAX3\u003c/em\u003e (Fig 4f-g), indicating their involvement in melanocytes differentiation processes. These findings suggest that differential expression of \u003cem\u003eHOX\u003c/em\u003e family genes may represent one of the regulatory mechanisms underlying HVP.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCytotrace analysis revealed that melanocytes in the B group exhibited the highest stemness potential, while those in the N group showed the lowest (Fig 5a-b). Pseudotime analysis reconstructed the differentiation progression of melanocytes (Fig 5c-d), with 40N melanocytes positioned at the origin of differentiation, while 40B, 40F, 120B, and 120F melanocytes were distributed along the trajectory (Fig 5e). During pseudotime progression, the expression of Cluster 2 genes increased, correlating positively with differentiation advancement. GO enrichment analysis revealed their significant enrichment in melanogenesis, as well as participation in ribosome biogenesis and ErbB signaling pathways, among others. Notably, among HOX family members, HOXD8 and HOXB5 were upregulated, whereas HOXC6 was downregulated at the observed differentiation stages (Fig. 5f). At branch point 1, the melanocytes state of 40N diverged into B and F melanocyte states (Pre-branch cluster representing State 1, Cell fate 1 comprising State 2, 3, 4, and Cell fate 2 representing State 5). Genes in Cluster 4 were highly expressed in Cell fate 1, including retinoic acid receptor beta \u003cem\u003eRARB\u003c/em\u003e, while Cluster 5 genes \u003cem\u003ePDGFC\u003c/em\u003e and \u003cem\u003eZNF521\u003c/em\u003e showed elevated expression in Cell fate 2, suggesting a potential association of these melanocytes with angiogenesis (Fig 5g).\u003c/p\u003e\n\u003cp\u003eWGCNA was performed on Schwann cells and melanocytes, yielding five distinct modules (Fig 6a). Among these, Module 1 exhibited predominant expression in melanocytes (Fig 6b, d) and demonstrated strong correlations with 40B, 40F, 120B, and 120F samples (Fig 6c). Examination of hub genes within Module 1 revealed that the majority were associated with melanin synthesis, with most showing preferential expression in melanocytes. Notably, it was found that the candidate gene \u003cem\u003eSDC1\u003c/em\u003e obtained in CellChat analysis was also the core gene of Module 1. Given the high expression of \u003cem\u003eSDC1\u003c/em\u003e in melanocytes, we hypothesize that \u003cem\u003eSDC1\u003c/em\u003e may not only influence melanocytes migration but also participate in the biological process of melanin biosynthesis. Furthermore, the downstream genes \u003cem\u003eOCA2\u003c/em\u003e and \u003cem\u003eHPGDS\u003c/em\u003e of \u003cem\u003eHOXA4\u003c/em\u003e and \u003cem\u003eHOXD8\u003c/em\u003e in pySCENIC analysis also appeared in Module 1. (Fig 6e).\u003c/p\u003e\n\u003ch2\u003eIdentification Subpopulations of Fibroblasts in HVP\u003c/h2\u003e\n\u003cp\u003eKEGG enrichment analysis of fibroblasts identified the glycosaminoglycan biosynthesis\u0026mdash;chondroitin sulfate/dermatan sulfate pathway as the top enriched pathway in 40B-N (Fig. 7a), whereas in 120B-N, it was retinol metabolism (Fig. 7b). These findings are consistent with the proteomic analysis results. ECM components and retinoic acid, respectively. Subcluster analysis of fibroblasts identified four distinct subpopulations (Fig 7c): Fib1 expressed cell adhesion factors such as \u003cem\u003eNEGR1\u003c/em\u003e, \u003cem\u003eTNXB\u003c/em\u003e, and \u003cem\u003eFGL2\u003c/em\u003e, potentially involved in melanocytes adhesion and colonization. Fib2 specifically expressed \u003cem\u003eROBO2\u003c/em\u003e and \u003cem\u003eEPHA7\u003c/em\u003e, which may promote NCCs migration. Fib3 expressed immune-related genes, including \u003cem\u003eJCHAIN\u003c/em\u003e, \u003cem\u003eGNLY\u003c/em\u003e, \u003cem\u003eIGLL1\u003c/em\u003e, and \u003cem\u003eCD74\u003c/em\u003e. Fib4 was characterized by collagen genes (\u003cem\u003eCOL22A1\u003c/em\u003e, \u003cem\u003eCOL13A1\u003c/em\u003e) and integrin \u003cem\u003eITGA8\u003c/em\u003e. Notably, Fib1 expressed ECM-related genes (\u003cem\u003eVCAN\u003c/em\u003e, \u003cem\u003eDCN\u003c/em\u003e) and \u003cem\u003eDHRS3\u003c/em\u003e identified in the proteomic screening (Fig 7d). In 40B-N, \u003cem\u003eVCAN\u003c/em\u003e was upregulated in Fib1, Fib2, and Fib3 at the transcriptional level (consistent with RT-qPCR results) (Fig 7e-g), but downregulated at the protein level. This discrepancy suggests potential post-translational regulatory mechanisms leading to reduced VCAN protein abundance.\u003c/p\u003e\n\u003cp\u003eCellChat analysis revealed that the Fib2 subpopulation exhibited the most significant interactions with melanocytes. Visualization of the SEMA3 signaling pathway in 40B-N showed that both Fib1 and Fib2 subpopulations transmitted signals to melanocytes, with the SEMA3C-PLXND1 axis demonstrating the strongest signaling intensity (Fig 7h). Among the DEGs in fibroblast subpopulations of 40B-N, \u003cem\u003eSEMA3C\u003c/em\u003e expression was significantly upregulated (Fib1: log2FC=1.29; Fib2: log2FC=1.80), while \u003cem\u003ePLXND1\u003c/em\u003e expression was markedly elevated in melanocytes (log2FC=5.86). In the TENASCIN pathway, Fib2 and Fib4 subpopulations communicated with melanocytes via the TNC-SDC1 signaling axis (Fig 7i, j). In 40B-N, \u003cem\u003eTNC\u003c/em\u003e expression was significantly upregulated in Fib2 (log2FC=2.22) and Fib4 (log2FC=1.82), whereas no significant difference was observed in 120B-N. Similarly, \u003cem\u003eSDC1\u003c/em\u003e expression was notably increased in melanocytes of 40B-N (log2FC=3.39) but remained unchanged in 120B-N.\u003c/p\u003e\n\u003ch2\u003eIntegrated dual-omics analysis\u003c/h2\u003e\n\u003cp\u003eThe R package edgeR was used to analyze the DEGs between HVP and normal peritoneal (bcv=0.2), followed by KEGG and GO analyses. In the 40B-N group, there are 2,362 upregulated genes and 1,490 downregulated genes. In the 120B-N group, there are 270 upregulated genes and 282 downregulated genes. At the 40B-N intersection, we identified 63 DEGs and DAPs, comprising 30 upregulated, 7 downregulated, and 26 with discordant mRNA-protein expression (Fig. 8a). In contrast, the 120B-N intersection contained only 3 genes: 2 upregulated and 1 with discordant expression (Fig. 8b, Table 4). The KEGG enrichment analysis of genes with consistent expression trends revealed seven significantly co-expressed pathways. The upregulated pathways included tyrosine metabolism, steroid hormone biosynthesis, melanogenesis, primary bile acid biosynthesis, and fatty acid elongation, while the downregulated pathways were lysine degradation and insulin signaling pathway (Fig 8c). Our dual-omics analyses consistently indicated that steroid hormones may play a crucial role in the HVP process. Notably, in the 40B-N group, we observed coordinated upregulation of the \u003cem\u003eHSD17B12\u003c/em\u003e gene, which encodes a key enzyme in estradiol (E2) biosynthesis.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eGene function verification\u003c/h2\u003e\n\u003cp\u003eBased on the above bioinformatic analysis results, we hypothesize that \u003cem\u003eSDC1\u003c/em\u003e genes and E2 play crucial regulatory roles in HVP formation. To validate this hypothesis, we conducted RNA interference experiments targeting \u003cem\u003eSDC1\u003c/em\u003e in primary melanocytes. We characterized the isolated chicken primary melanocytes using two melanocyte-specific markers, TYR and Melan-A, via immunofluorescence staining. The results confirmed the high purity of the isolated melanocytes (Fig. 9a-e). \u003cem\u003eSDC1\u003c/em\u003e gene interference produced dual regulatory effects: (1) Regarding melanogenesis, it led to significant downregulation of mRNA expression levels in key regulatory genes such as \u003cem\u003eDCT\u003c/em\u003e, \u003cem\u003eEDNRB\u003c/em\u003e, and \u003cem\u003eMITF\u003c/em\u003e (Fig 9f), accompanied by decreased tyrosinase activity and reduced melanin production (Fig 9g, h); (2) In terms of cell migration, it induced upregulation of homologous genes \u003cem\u003eSDC2\u003c/em\u003e and \u003cem\u003eSDC4\u003c/em\u003e expression (Fig 9i, j), thereby significantly enhancing the migratory capacity of melanocytes (Fig 9k, l). These results suggest that \u003cem\u003eSDC1\u003c/em\u003e may participate in HVP formation through a dual regulatory mechanism: it not only regulates pigment synthesis through the classical melanogenic pathway but also affects cell migration behavior by activating homologous genes via a bypass mechanism.\u003c/p\u003e\n\u003cp\u003eGiven that fibroblasts are the predominant cell type in peritoneal tissue, we treated both DF-1 cells and chicken primary melanocytes with 17\u0026beta;-estradiol to test this hypothesis. Following 17\u0026beta;-estradiol treatment, DF-1 cells exhibited upregulated mRNA expression of ECM genes (including \u003cem\u003eDCN\u003c/em\u003e and \u003cem\u003eVCAN\u003c/em\u003e) (Figure 10a); however, no significant differences were observed in the protein abundance of DCN and VCAN (Figure 10b). Therefore, we propose that other factors may act in conjunction with 17\u0026beta;-estradiol to contribute to the ECM alterations observed in HVP. Upon 17\u0026beta;-estradiol treatment, the melanocytes showed upregulated expression of melanogenesis-related genes (\u003cem\u003eDCT\u003c/em\u003e, \u003cem\u003eTYR\u003c/em\u003e, and \u003cem\u003eMLPH\u003c/em\u003e), while \u003cem\u003eMITF\u003c/em\u003e expression was downregulated. This suggested that 17\u0026beta;-estradiol might inhibit melanocytes proliferation while promoting melanin synthesis (Fig. 10c). To further validate this hypothesis, we supplemented the culture medium with 1 \u0026mu;M Tyr and treated the cells with 17\u0026beta;-estradiol for 24 h before measuring melanin content. Compared to the control group, 5 \u0026mu;M 17\u0026beta;-estradiol treatment significantly enhanced melanin synthesis (Fig. 10d).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe occurrence of HVP can suppress the growth and development of broilers(Wang et al. 2024), yet current limited research has not elucidated the genetic mechanisms underlying HVP formation. In previous laboratory studies, both the Wnt signaling pathway and retinoic acid (RA) signaling pathway were found to participate in the delamination and migration of NCCs, ultimately contributing to HVP formation(Chen et al. 2025). In this study, we performed scRNA-seq analysis on peritoneal tissues with varying degrees of melanin deposition and employed analytical methods such as CellChat and pySCENIC to reveal the genetic mechanisms driving HVP development.\u003c/p\u003e\n\u003cp\u003eCellChat analysis revealed that the abnormal aggregation of melanocytes in the B/F group is closely associated with regulatory effects from fibroblasts in their microenvironment. We identified the TNC-SDC1 L-R axis in the TENASCIN pathway as the critical pathway through which fibroblasts influence melanocytes adhesion and migration. Both \u003cem\u003eTNC\u003c/em\u003e and \u003cem\u003eSDC1\u003c/em\u003e play roles in cell adhesion and migration processes: \u003cem\u003eTNC\u003c/em\u003e serves as a melanoma marker that enhances the migratory capacity of melanoma cells through interactions with integrins and ECM components(Fukunaga-Kalabis et al. 2010; Grahovac et al. 2013; Aguera-Lorente et al. 2024), while also exhibiting anti-adhesive molecule functionality(Hagedorn et al. 2016); \u003cem\u003eSDC1\u003c/em\u003e is a transmembrane heparan sulfate proteoglycan that regulates cell proliferation, migration, angiogenesis, and cell-cell/extracellular matrix adhesion(Mitselou et al. 2012), homologous gene SDC2 can enhance the migration and invasion of melanoma cells(Lee et al. 2009).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEvidence suggests that axon guidance factors, including ephrins and semaphorins, function to guide and pathfind during NCCs migration. Semaphorins are a family of secreted or transmembrane proteins, initially identified as axon guidance factors during neural development(Huber et al. 2003). Notably, the signaling of Class 3 Semaphorins is essential for the developmental migration of NCCs(High and Epstein 2007). Neuropilins (NRPs), comprising NRP1 and NRP2 subtypes, serve as receptors for Class 3 Semaphorins. They typically bind to \u003cem\u003ePLXNDA\u003c/em\u003e or \u003cem\u003ePLXND1\u003c/em\u003e to transduce signals; however, \u003cem\u003eSEMA3C\u003c/em\u003e can signal directly via \u003cem\u003ePLXND1\u003c/em\u003e independently of NRP(Smolkin et al. 2018). \u003cem\u003eSEMA3A\u003c/em\u003e and \u003cem\u003eNRP1\u003c/em\u003e participate in neural crest patterning in chickens(Schwarz et al. 2008), preventing trunk NCCs from migrating through somite clefts while maintaining their ventromedial migratory route. Knockout of \u003cem\u003eSEMA3E\u003c/em\u003e causes severe craniofacial defects(Liu et al. 2019); \u003cem\u003eSEMA3F\u003c/em\u003e and \u003cem\u003eSEMA3G\u003c/em\u003e are critical for segregating migrating cranial NCCs in zebrafish(Yu and Moens 2005); while \u003cem\u003eSEMA3D\u003c/em\u003e may regulate NCCs proliferation downstream of the transcription factor TCF in the zebrafish hindbrain(Berndt and Halloran 2006). A mutation impairing Semaphorin signaling induces excessive dorsolateral migration of NCCs via \u003cem\u003eNRP1\u003c/em\u003e(Schwarz et al. 2009); moreover, \u003cem\u003eNRP1\u003c/em\u003e also promotes melanoma cell migration(Lu et al. 2015). Experimental evidence demonstrates that SEMA3C chemoattracts NCCs in both in vivo and in vitro settings, knockdown of \u003cem\u003ePLXND1\u003c/em\u003e or \u003cem\u003eNRP1\u003c/em\u003e in NCCs attenuates the chemoattractive effect of \u003cem\u003eSEMA3C\u003c/em\u003e(Toyofuku et al. 2008). In fact, fibroblasts guide directionally migrating melanocyte-fated NCCs through the SEMA3C-PLXND1 signaling axis, while reduced abundance of proteoglycans such as VCAN and DCN may facilitate NCCs penetration through migratory barriers. Following NCCs entry into the peritoneum, the TNC-SDC1 signaling axis promotes their colonization, ultimately driving the formation of HVP.\u003c/p\u003e\n\u003cp\u003eIn our previous study, RA was identified as a critical inducer for HVP formation. Endogenous RA is essential for the normal stratification of NCCs(Rekler et al. 2024)\u0026nbsp;and stimulates their differentiation toward melanocyte precursors by inducing tyrosinase expression(Huang et al. 2016). This differentiation is proposed to result from distinct HOX gene expression profiles, whose expression is regulated by factors including RA and FGF(Wilkinson 1993; Weicksel et al. 2014; Gomez et al. 2019).Through pySCENIC analysis, multiple \u003cem\u003eHOX\u003c/em\u003e genes were identified as being activated. \u003cem\u003eHOX\u003c/em\u003e genes encode a conserved family of TFs that play crucial roles in regulating regional tissue identity along the anterior-posterior axis and exert regulatory effects during embryonic development(Afzal et al. 2023; Peraldi and Kmita 2024). Different \u003cem\u003eHOX\u003c/em\u003e genes can drive trunk NCCs to differentiate into distinct cell lineages(Howard et al. 2021; Cooper and Tsakiridis 2022), the spatiotemporally specific expression of \u003cem\u003eHOX\u003c/em\u003e genes in HVP establishes the molecular basis for NCCs differentiation into melanocytes. Low expression of \u003cem\u003eHOXA2\u003c/em\u003e and \u003cem\u003eHOXB2\u003c/em\u003e in embryos can lead to melanocytes deficiency(Knight et al. 2004). Notably, the direct regulatory link between RA signaling and \u003cem\u003eHOX\u003c/em\u003e expression may represent an ancient feature of core gene regulatory networks, evolutionarily coupled with anteroposterior patterning in all chordates(Bedois et al. 2023; Bedois et al. 2024).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn our preliminary surveys, while HVP occurs in most broiler breeds, its incidence frequency is significantly higher in Huiyang Bearded Chickens compared to other broiler varieties. Huiyang Bearded Chickens are renowned for the elongated feathers collected from both sides of their face and below the beak, whose molecular basis involves specific expression patterns of \u003cem\u003eHOX\u003c/em\u003e family genes and differential RA levels(Guo et al. 2016; Yang et al. 2020; Zheng et al. 2023). This study similarly identified \u003cem\u003eHOX\u003c/em\u003e gene family members and RA signaling, suggesting potential connections between beard feather formation and HVP development. Bioinformatic prediction of TFs in proteomic profiles of HVP samples revealed significant enrichment of zinc finger domain-containing TFs. Studies demonstrate that zinc finger proteins, particularly CTCF of the C2H2 family, maintain chromatin boundary integrity at \u003cem\u003eHOX\u003c/em\u003e gene, thereby establishing their differentiation-associated expression patterns(Kyrchanova et al. 2020; Ortabozkoyun et al. 2022; Ortabozkoyun et al. 2024). Furthermore, RA signaling modulates HOX-specific expression patterns by regulating bZIP domain-containing transcription factors, thereby contributing to neuronal fate specification(Hernandez et al. 2004). Therefore, we propose that RA participates in NCCs\u0026apos; directional differentiation toward melanocytes by modulating \u003cem\u003eHOX\u003c/em\u003e gene family-specific expression, indirectly contributing to melanin synthesis and ultimately HVP formation. This regulation of \u003cem\u003eHOX\u003c/em\u003e specificity may be mediated through zinc finger proteins.\u003c/p\u003e\n\u003cp\u003eAdditionally, the frequency of HVP in hens of Bearded chickens is also significantly higher than in roosters. Evidence suggests a physiological link between ovarian activity and pigmentary changes in both skin and abdominal regions(Kim et al. 2010; Kumar and Joy 2015). The \u003cem\u003eHSD17B12\u003c/em\u003e gene, along with the GnRH signaling pathway and steroid hormone biosynthesis pathway, was consistently identified through integrated dual-omics analysis and multiple bioinformatics analysis methods. The \u003cem\u003eHSD17B12\u003c/em\u003e gene is responsible for E2 synthesis and participates in lipid metabolism(Lima et al. 2013; Bertin et al. 2014). The upregulation of this gene and associated pathways indicates that the E2-dominated hormonal microenvironment facilitates HVP formation. Comparative metabolomic and lipidomic profiling of SF versus common chicken strains revealed a significant association between differential \u003cem\u003eHSD17B1\u003c/em\u003e gene expression and altered E2 metabolic flux, suggesting their coordinated regulation of dermal pigmentation(Yang et al. 2024). Mechanistically, E2 directly stimulates melanogenesis in melanocytes(Natale et al. 2016). Cross-species evidence demonstrates that E2 promotes systemic hair pigmentation in female mice while suppressing it in males(Hirobe et al. 2010). This concentration-dependent regulatory paradigm implies that variations in E2 abundance may underlie phenotypic divergence in melanin synthesis and deposition dynamics(Tian et al. 2021).We therefore propose that ovarian development in hens may contribute to the higher HVP incidence rate observed in females compared to roosters.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eBased on the above analysis, we propose that the formation of HVP results from the combined effects of multiple factors (Fig 11):\u003c/p\u003e\n\u003cp\u003e(1) Melanocytes in the HVP region originate from aberrant differentiation of NCCs migrating from the ventromedial pathway. RA signaling regulates the specific expression of \u003cem\u003eHOX\u003c/em\u003e genes, inducing NCCs to differentiate into SCPs before committing to melanocyte lineage.\u003c/p\u003e\n\u003cp\u003e(2) Post-transcriptional dysregulation of \u003cem\u003eDCN\u003c/em\u003e and \u003cem\u003eVCAN\u003c/em\u003e in the Fib1 cluster leads to loss of barrier molecules. Through the SEMA3C-PLXND1 axis, Fib1 and Fib2 cell clusters in the peritoneal region attract melanocytes, enabling them to breach the normal migratory barrier and enter the peritoneum.\u003c/p\u003e\n\u003cp\u003e(3) Upon melanocyte migration to the peritoneal region, Fib2 and Fib4 clusters enhance cellular adhesion via the TNC-SDC1 axis, facilitating melanocyte colonization in the peritoneal tissue.\u003c/p\u003e\n\u003cp\u003e(4) While participating in ECM remodeling, estradiol concurrently promotes the substantial synthesis and deposition of melanin by melanocytes, ultimately driving the formation of the HVP phenotype. This regulatory mechanism, associated with ovarian development, likely represents a feature specific to hens.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eHVP: Hyperpigmentation of the visceral peritoneum; NCCs: Neural crest cells; SCPs: Schwann cell precursors; scRNA-seq: single-cell RNA sequencing; ECM: Extracellular matrix; DEGs: Differential expression genes; E2: Estradiol; SF: Silky fowl; L-R: Ligand-receptor.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eData availability\u003c/h2\u003e\n\u003cp\u003eThe original sequencing data of scRNA-seq has been uploaded to the GSA database, Bioproject number: CRA026581, and can be accessed directly at https://ngdc.cncb.ac.cn/gsa/s/ulg7q0Ea.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe thank Xingtai Modern Agriculture Co., Ltd. (Longmen, Huizhou, Guangdong) for technical support in sample collection.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was supported by the \u0026apos;\u0026apos;China Agriculture Research System (Grant No. CARS-41)\u0026nbsp;\u0026apos;\u0026apos;, and the National Key Research and Development Program of China（2021YFD1300102).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAuthor information\u003c/h2\u003e\n\u003ch2\u003eAuthors and Affiliations\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong Province, China.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZhengyang Chen, Changbin Zhao, Xiaoyin Zeng, Xueyin He, Chengyue Yuan\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u0026amp; Xiquan Zhang\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZhengyang Chen, Changbin Zhao, Xiaoyin Zeng, Xueyin He, Chengyue Yuan\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u0026amp; Xiquan Zhang\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eState Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, China.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZhengyang Chen, Changbin Zhao, Xiaoyin Zeng, Xueyin He, Chengyue Yuan\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u0026amp; Xiquan Zhang\u003c/p\u003e\n\u003ch2\u003eContributions\u003c/h2\u003e\n\u003cp\u003eZhengyang Chen conceived and performed the experiments, analyzed the scRNA-seq data, and wrote the manuscript. Changbin Zhao formulated the strategy of bioinformatic analysis. Xiaoyin Zeng, Xueyin He, and Chengyue Yuan participated in the experiment and proofread the manuscript. Xiquan Zhang conceived this study, revised and approved the final manuscript. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003eCorresponding author\u003c/p\u003e\n\u003cp\u003eCorrespondence to Xiquan Zhang.\u003c/p\u003e\n\u003ch2\u003eEthics approval\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eAll animal experiments were performed according to the protocols approved by the South China Agriculture University Institutional Animal Care and Use Committee (approval number: SCAU#0106; 25 November 2018). All animal procedures followed the regulations and guidelines established by this committee and minimized the suffering of animals.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAdameyko I, Lallemend F, Aquino JB, Pereira JA, Topilko P, Muller T, Fritz N, Beljajeva A, Mochii M, Liste I, Usoskin D, Suter U, Birchmeier C, Ernfors P. 2009. Schwann cell precursors from nerve innervation are a cellular origin of melanocytes in skin. Cell 139(2): 366-379. https://doi.org/10.1016/j.cell.2009.07.049.\u003c/li\u003e\n \u003cli\u003eAfzal Z, Lange JJ, Nolte C, Mckinney S, Wood C, Paulson A, De Kumar B, Unruh J, Slaughter BD, Krumlauf R. 2023. 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Increased expression of neuropilin 1 in melanoma progression and its prognostic significance in patients with melanoma. Molecular Medicine Reports 12(2): 2668-2676. https://doi.org/10.3892/mmr.2015.3752.\u003c/li\u003e\n \u003cli\u003eMitselou A, Skoufi U, Tsimogiannis KE, Briasoulis E, Vougiouklakis T, Arvanitis D, Ioachim E. 2012. Association of syndecan-1 with angiogenesis-related markers, extracellular matrix components, and clinicopathological features in colorectal carcinoma. Anticancer Research 32(9): 3977-3985.\u003c/li\u003e\n \u003cli\u003eNatale CA, Duperret EK, Zhang J, Sadeghi R, Dahal A, O\u0026apos;Brien KT, Cookson R, Winkler JD, Ridky TW. 2016. Sex steroids regulate skin pigmentation through nonclassical membrane-bound receptors. Elife 5. https://doi.org/10.7554/eLife.15104.\u003c/li\u003e\n \u003cli\u003eNing M, Duarte JD, Stevison F, Isoherranen N, Rubin LH, Jeong H. 2019. Determinants of cytochrome p450 2d6 mrna levels in healthy human liver tissue. Cts-Clinical and Translational Science 12(4): 416-423. https://doi.org/10.1111/cts.12632.\u003c/li\u003e\n \u003cli\u003eOrtabozkoyun H, Huang P, Cho H, Narendra V, Leroy G, Gonzalez-Buendia E, Skok JA, Tsirigos A, Mazzoni EO, Reinberg D. 2022. Crispr and biochemical screens identify maz as a cofactor in ctcf-mediated insulation at hox clusters.\u0026nbsp;Nature Genetics 54(2): 202-212. https://doi.org/10.1038/s41588-021-01008-5.\u003c/li\u003e\n \u003cli\u003eOrtabozkoyun H, Huang P, Gonzalez-Buendia E, Cho H, Kim SY, Tsirigos A, Mazzoni EO, Reinberg D. 2024.\u0026nbsp;Members of an array of zinc-finger proteins specify distinct hox chromatin boundaries. Molecular Cell 84(18): 3406-3422. https://doi.org/10.1016/j.molcel.2024.08.007.\u003c/li\u003e\n \u003cli\u003ePeraldi R, Kmita M. 2024.\u0026nbsp;40 years of the homeobox: mechanisms of hox spatial-temporal collinearity in vertebrates. Development 151(16). https://doi.org/10.1242/dev.202508.\u003c/li\u003e\n \u003cli\u003eRekler D, Ofek S, Kagan S, Friedlander G, Kalcheim C. 2024. Retinoic acid, an essential component of the roof plate organizer, promotes the spatiotemporal segregation of dorsal neural fates. Development 151(19). https://doi.org/10.1242/dev.202973.\u003c/li\u003e\n \u003cli\u003eSchwarz Q, Maden CH, Vieira JM, Ruhrberg C. 2009. Neuropilin 1 signaling guides neural crest cells to coordinate pathway choice with cell specification. Proceedings of the National Academy of Sciences of the United States of America 106(15): 6164-6169. https://doi.org/10.1073/pnas.0811521106.\u003c/li\u003e\n \u003cli\u003eSchwarz Q, Vieira JM, Howard B, Eickholt BJ, Ruhrberg C. 2008. Neuropilin 1 and 2 control cranial gangliogenesis and axon guidance through neural crest cells. Development 135(9): 1605-1613. https://doi.org/10.1242/dev.015412.\u003c/li\u003e\n \u003cli\u003eSmolkin T, Nir-Zvi I, Duvshani N, Mumblat Y, Kessler O, Neufeld G. 2018. Complexes of plexin-a4 and plexin-d1 convey semaphorin-3c signals to induce cytoskeletal collapse in the absence of neuropilins. Journal of Cell Science 131(9). https://doi.org/10.1242/jcs.208298.\u003c/li\u003e\n \u003cli\u003eTian X, Cui Z, Liu S, Zhou J, Cui R. 2021. Melanosome transport and regulation in development and disease. Pharmacology \u0026amp; Therapeutics 219: 107707. https://doi.org/10.1016/j.pharmthera.2020.107707.\u003c/li\u003e\n \u003cli\u003eToyofuku T, Yoshida J, Sugimoto T, Yamamoto M, Makino N, Takamatsu H, Takegahara N, Suto F, Hori M, Fujisawa H, Kumanogoh A, Kikutani H. 2008. Repulsive and attractive semaphorins cooperate to direct the navigation of cardiac neural crest cells. Developmental Biology 321(1): 251-262. https://doi.org/10.1016/j.ydbio.2008.06.028.\u003c/li\u003e\n \u003cli\u003eVandamme N, Berx G. 2019. From neural crest cells to melanocytes: cellular plasticity during development and beyond. Cellular and Molecular Life Sciences 76(10): 1919-1934. https://doi.org/10.1007/s00018-019-03049-w.\u003c/li\u003e\n \u003cli\u003eWang Y, Liu T, Liu S, Luo W, Tang L, Li Y, He Y, Shu D, Qu H, Luo C. 2024. Research note: effects of hyperpigmentation of the visceral peritoneum on body weight and selection method in chinese yellow-feathered broilers. Poultry Science 103(11): 104164. https://doi.org/10.1016/j.psj.2024.104164.\u003c/li\u003e\n \u003cli\u003eWeicksel SE, Gupta A, Zannino DA, Wolfe SA, Sagerstrom CG. 2014. Targeted germ line disruptions reveal general and species-specific roles for paralog group 1 hox genes in zebrafish. Bmc Dev Biol 14: 25. https://doi.org/10.1186/1471-213X-14-25.\u003c/li\u003e\n \u003cli\u003eWilkinson DG. 1993. Molecular mechanisms of segmental patterning in the vertebrate hindbrain and neural crest. Bioessays 15(8): 499-505. https://doi.org/10.1002/bies.950150802.\u003c/li\u003e\n \u003cli\u003eYang KX, Zhou H, Ding JM, He C, Niu Q, Gu CJ, Zhou ZX, Meng H, Huang QZ. 2020. Copy number variation in hoxb7 and hoxb8 involves in the formation of beard trait in chickens. Animal Genetics 51(6): 958-963. https://doi.org/10.1111/age.13011.\u003c/li\u003e\n \u003cli\u003eYang X, Tang C, Ma B, Zhao Q, Jia Y, Meng Q, Qin Y, Zhang J. 2024. Identification of characteristic bioactive compounds in silkie chickens, their effects on meat quality, and their gene regulatory network. Foods 13(6). https://doi.org/10.3390/foods13060969.\u003c/li\u003e\n \u003cli\u003eYu H, Moens CB. 2005. Semaphorin signaling guides cranial neural crest cell migration in zebrafish. Developmental Biology 280(2): 373-385. https://doi.org/10.1016/j.ydbio.2005.01.029.\u003c/li\u003e\n \u003cli\u003eZheng X, Zhang Y, Zhang Y, Chen J, Nie R, Li J, Zhang H, Wu C. 2023. Hoxb8 overexpression induces morphological changes in chicken mandibular skin: an rna-seq analysis. Poultry Science 102(10): 102971. https://doi.org/10.1016/j.psj.2023.102971.\u003c/li\u003e\n \u003cli\u003eZhou G, Liu T, Wang Y, Qu H, Shu D, Jia X, Luo C. 2022. Genome-wide association studies provide insight into the genetic determination for hyperpigmentation of the visceral peritoneum in broilers. Frontiers in Genetics 13: 820297. https://doi.org/10.3389/fgene.2022.820297.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. siRNA Sequence\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 267px;\"\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003eSequence (5\u0026prime;\u0026minus;\u0026gt;3\u0026prime;)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 267px;\"\u003e\n \u003cp\u003e\u003cem\u003eSDC1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003eGAGCCGAACUGAAAAGAAA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 267px;\"\u003e\n \u003cp\u003eNegative control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003eUUCUCCGAACGUGUCACGUTT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2.\u0026nbsp;Primer Sequences\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"98%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eForward primer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eReverse primer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003eTM (℃)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eProduct size (bp)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eMITF\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eATCCTTGGCTTGATGGACCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eGCTCTCGCTTCTGACTCTGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eTYRP1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCCAAGCCAAGGTGACAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCCTGACGGAATAATAATGAGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e145\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eDCT\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCAGAGACACACTCCTAGGGC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCATTGCCCATCAATCGCTGC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eDHRS3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCCACACGAGCACAGAGATGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eGGCCTGAGGGAGAATGCTTTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eDACT1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eGTCGTCCAAGTTCAGGGTTTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eTGCAGATTTAGGGCGTCCAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eVCAN\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCGCTGGCTGTTGATGGTGTGTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eATGCTGCCTTCAGTTGCTCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eDCN\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eGCATCGCAGACACCAACATT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eAAGCTGAGACCCAATTTAGCCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e145\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eEDNRB\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eTGGCCCTTTGGTGTCGAAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCAACTGCTCGGTACCTGTCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e112\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eTYR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eTGGAAGGCTTTGCTGATCCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCCACCGCTCAAAAATGCTGTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eCOL1A1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCCAAAGGGAACAGCGGTGAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCTCCTCTCTCTTGCCTTCCTCG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eCOL1A2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCTGGTAACCGTGGTGCTAGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eGACCTGGGGGAGACCTCTTGGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eTNC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCGGCTACAACAGAGGCAGAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCGCTCATGGCCTGGTACTAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e178\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eSDC1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCCGGGAGACTTCATCTTGGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eGTCCTCCAGCAATAACACCTCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eFN1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eACCAAGTTGGAGAGCAGTGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eGCAGTTGACGTTGGTGTTTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e197\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eMLPH\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eAGGTGGTTCAGCGTGACTTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eACCGATCTTCACCACCCTGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e290\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eMYO5A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eGCCTGGACACAAAAGAACGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCTCACTTGGCTCCTCCATCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eRAB27A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCCTAGCACTTGGTGACTCTGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eTGGGTCTGTACACCACTCTCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eSDC2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eTGCCTGCACAAACAAAGTCAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eACCAATAACTCCGCCAGCAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e179\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eSDC4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCGCCGAGTCGGTGAGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eACAGTGGTCAGGTATATGGCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e192\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eSDCBP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCTCAGCCACAAGGTCAACTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eTCCAATTTTTCCGTCTTGATCTTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cem\u003eGAPDH\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eTCGGAGTCAACGGATTTGGC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eTTCCCGTTCTCAGCCTTGAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e181\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\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3. Celltype Marker\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"95%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eCluster\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003eCelltype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eMarker\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003eFibroblasts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cem\u003eLUM\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eDCN\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eCOL3A1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003eEndothelial cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cem\u003eVWF\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eADGRL4\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eFLT1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003eOligodendrocytes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cem\u003eSOX6\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eCA2\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eMOG\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003eMyofibroblasts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cem\u003eMLYK\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eMYL9\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eMYH11\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003eMacrophages\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cem\u003eCCL4\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eSPI1\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eC1QC\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eC1QB\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003eT cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cem\u003eCD3D\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eCD3E\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eCD247\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003eMuscle satellite cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cem\u003eMYF5\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003ePAX7\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003eSchwann cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cem\u003eSOX10\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003ePLP1\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eCD9\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003eMelanocytes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cem\u003eMLANA\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003eMLPH\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003ePMEL\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4.\u0026nbsp;The intersection of DAPs and DEGs\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e40B-N\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e120B-N\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDOWN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHANGE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDOWN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHANGE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eCYP7B1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eBMPER\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eBF2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cem\u003eSLC16A12\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eSULT1B\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eDACT1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eCAMKMT\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eCD74\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cem\u003eTENM1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eDCT\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eEVA1CL\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eCDK\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eEPB41L3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eLY86\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eCDK2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eEPB42\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eMRPL50\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eCHPF\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eFBX042\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003ePRKAR2B\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eCPNE8\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eFMNL2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cem\u003eTRAPPC2L\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eG6PC3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eFOXP2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eGOLIM4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eGDA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eME3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eGPNMB\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eP2RX7\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eHBAD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003ePIPTNC1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eHMGA1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003ePOLA2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eHOMER1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003ePTPRS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eHSD17B12\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eRAB18L\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eIGSF3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eRNF41\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eKRT10\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eROR1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eKRT13\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eRPL32\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cem\u003eKRT17\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 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Genomics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Hyperpigmentation of the visceral peritoneum, Neural crest cells, HOX family, bearded chickens","lastPublishedDoi":"10.21203/rs.3.rs-7241140/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7241140/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Hyperpigmentation of the visceral peritoneum (HVP) critically impacts carcass quality in yellow-feathered broilers, yet its mechanisms remain unclear. This study employed single-cell RNA sequencing to profile black, faded, and normal peritoneal tissues from bearded chickens at 40 and 120 d of age, functionally validating findings with fibroblast lines and primary melanocytes. We identified nine cell types, with melanocytes significantly elevated in HVP tissue. UMAP projections revealed near-overlapping melanocyte and Schwann cell clusters, indicating HVP melanocytes originate primarily from the ventromedial migratory pathway of neural crest cells (NCCs), differentiating via Schwann cell precursors. Aberrant melanocyte aggregation and migration drive HVP pathogenesis. CellChat analysis demonstrated pivotal roles for the SEMA3C-PLXND1 axis, which directs NCCs migration, and the TNC-SDC1 axis, which enhances melanocytes adhesion, in fibroblasts-melanocytes crosstalk. Transcription factor analysis highlighted HOX family regulation of NCCs to melanocytes differentiation. Experimentally, SDC1 downregulation reduced melanin synthesis but increased migration, while estradiol promoted melanogenesis and modulated extracellular matrix. HVP development involves four interconnected mechanisms: RA-HOX-mediated aberrant NCCs differentiation, SEMA3C-PLXND1-driven melanocyte barrier breaching, TNC-SDC1-mediated peritoneal colonization, and estrogen-coordinated melanin deposition. These findings elucidate HVP's molecular basis and provide theoretical support for broiler breeding.","manuscriptTitle":"The Aberrant Migration and Differentiation of Neural Crest Cells Led to the Production of HVP in Bearded Chicken","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-19 13:42:11","doi":"10.21203/rs.3.rs-7241140/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-27T12:52:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-26T16:11:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-23T06:12:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-22T01:53:02+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-21T13:52:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"124524306805978029036531116679939615216","date":"2025-08-15T11:36:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"230282478602747369914420365892862725677","date":"2025-08-13T15:12:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"177160419630887306421424781959745545310","date":"2025-08-13T13:34:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"123780016918443522278372628618014377054","date":"2025-08-13T09:36:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"88642999426012563652805136539028903890","date":"2025-08-13T04:23:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"275324534441792944973931765113628864914","date":"2025-08-12T05:49:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-11T13:04:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-06T22:03:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-06T22:02:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"Functional \u0026 Integrative Genomics","date":"2025-07-29T08:47:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"functional-and-integrative-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"fige","sideBox":"Learn more about [Functional \u0026 Integrative Genomics](http://link.springer.com/journal/10142)","snPcode":"10142","submissionUrl":"https://submission.nature.com/new-submission/10142/3","title":"Functional \u0026 Integrative Genomics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"2f39b6b0-7e60-4a00-9dd5-62b8d13c03a2","owner":[],"postedDate":"August 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T16:05:21+00:00","versionOfRecord":{"articleIdentity":"rs-7241140","link":"https://doi.org/10.1007/s10142-025-01726-7","journal":{"identity":"functional-and-integrative-genomics","isVorOnly":false,"title":"Functional \u0026 Integrative Genomics"},"publishedOn":"2025-11-14 15:58:05","publishedOnDateReadable":"November 14th, 2025"},"versionCreatedAt":"2025-08-19 13:42:11","video":"","vorDoi":"10.1007/s10142-025-01726-7","vorDoiUrl":"https://doi.org/10.1007/s10142-025-01726-7","workflowStages":[]},"version":"v1","identity":"rs-7241140","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7241140","identity":"rs-7241140","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}