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. 2024 May 16;103(8):103864. doi: 10.1016/j.psj.2024.103864

Transcriptome and proteome revealed the differences in 3 colors of earlobe in Jiangshan Black-bone chicken

Shiru Li ⁎, Yu Du †, Xue Du *, Xiangying Ding †, Ayong Zhao *, Zhijun Wang *,1
PMCID: PMC11190713  PMID: 38838590

Abstract

The earlobe is a featherless, exposed thickening located beneath the ear canal of chickens, which plays a visual signaling role in age, performance, mental vitality, reproduction, and other aspects. However, despite its importance, there have been few studies on the color differences and formation mechanisms of chicken earlobes, particularly the structurally blue earlobes characteristic of the Jiangshan black-bone chicken. In this study, we explored the physiological mechanisms that may influence the formation of differently colored earlobes using 3 types of earlobes from Jiangshan black-bone chickens: light peacock green (Green group), dark peacock green (Blue group), and dark reddish purple (Black group). All 3 earlobe colors exhibited positive melanin Masson-Fontana staining, and the thickness of collagen fibers in the dermis decreased in the order of Green, Blue, and Black groups. A total of 1,953 differentially expressed genes (DEGs) were detected in the 3 earlobes through mRNA sequencing, among which the GO term “collagen trimer” was significantly enriched in DEGs between groups. Additionally, 716 differentially expressed proteins (DEPs) were identified in the 3 earlobes using 4D-DIA proteomics, with the term “collagen fibril organization” being significantly enriched in DEPs between the Green and Black groups. Integrated analysis of transcriptome and proteome data revealed that 12 DEGs and DEPs were commonly differentially expressed between the Green and Black groups, including the gene LUM (corneal keratan sulfate proteoglycan), which was significantly enriched in the "collagen fibril organization" GO term. In conclusion, our study suggests that LUM plays a crucial role in the formation of peacock green earlobes in Jiangshan black-bone chickens. The high level of LUM in peacock green (Green and Blue groups) may affect collagen nanostructures, leading to a stronger effect of melanin-supported dermal collagen on the production of non-iridescent structural colors through coherent scattering, resulting in a bright structural blue color in Jiangshan black-bone chickens. In contrast, the low expression of LUM in dark reddish purple (Black group) reduces the reflection of non-iridescent structural colors, making the earlobe color appear almost black, similar to melanin.

Key words: Jiangshan black-bone chicken, earlobe color, transcriptome, proteome, collagen

INTRODUCTION

The chicken's head features numerous exposed, non-scaly skin structures, including the crown, wattle, earlobes, and others. These structures have a thickened integument that grows outward, and their color often contrasts starkly with that of adjacent feathers. The earlobes of chickens hang pendulously below the external auditory canal and are featherless, exposed internal thickeners with a soft, semi-oval, or semicircular shape, characterized by numerous lines and irregularities (Luo et al., 2018). The earlobes are often regarded as the same visual signal as the crown. Their size or color may be correlated with the age, performance strengths, mental vigor, physical condition, and reproductive activity of chickens (Friedmann, 1960). Furthermore, research has shown that the earlobes of chickens can utilize pigmentation absorption and radiation of solar energy to achieve thermoregulation (Egahi et al., 2010). At the histological level, some studies have found that the earlobes exhibit histological similarities to wattle, but with more abundant collagen substances in the dermis and greater amounts of lipids in the epidermis (Lucas and Stettenheim, 1974).

Similar to beak color, feather color, and skin color, earlobe color is a pigment trait in chickens, and it is also a characteristic of chicken breeds (Guo et al., 2024). There are numerous kinds of earlobe colors, and the color of the earlobe varies significantly from one breed to another. Even the inner earlobe color of a breed can differ substantially. Roughly 5 common colors of chicken earlobes have been identified: red, white, yellow, blue, and black (Nie et al., 2016; Habimana et al., 2020; Muluneh et al., 2023; Prakash et al., 2023). Among these, red earlobes and white earlobes are characteristic of most chicken breeds, such as Qingyuan chicken (red or white earlobe), Hy-line brown laying chicken (red earlobe), and White Leghorns chicken (white earlobe) (Nie et al., 2016; Habimana et al., 2020; Muluneh et al., 2023). Some chicken groups exhibit yellow earlobe phenotypes, such as 3-yellow chicken and Xianju chicken. The distinctive blue earlobes are primarily found in Jiangshan black-bone chicken and Silk-feathered black-bone chicken, which is a signature feature of these breeds (Nie et al., 2016; Habimana et al., 2020; Muluneh et al., 2023). Black earlobes are mainly associated with black-bone chickens, such as Yanjin black-bone chicken and Ayam Cemani chicken (Prakash et al., 2023).

Jiangshan black-bone chicken is a native chicken breed originating from Jiangshan City, Zhejiang Province (Guo et al., 2024). The breed is characterized by white feathers, while its beak, tongue, plantar body, toes, skin, and internal organs are all uniformly black, and this black color remains unchanged even after cooking. The breed's basic appearance is further defined by its distinctive dark reddish purple crown and wattle, as well as its signature peacock green earlobes (Zhu et al., 2014). What sets Jiangshan black-bone chicken apart from other breeds is its unique peacock green earlobes, which serve as both a breed symbol and a germplasm characteristic of Jiangshan black-bone chicken.

The earlobe color of Jiangshan black-bone chicken appears blueish to the naked eye, which is why most studies categorize it as a blue earlobe (Chen et al., 2019). Currently, research on blue earlobes is limited, but blue skin has garnered more attention. Some studies suggest that the formation of blue skin may be attributed to the combined effects of melanin and collagen fibers (Rootman et al., 2014). Blue skin is a type of structural color, and most studies in the last century have attributed it to the incoherent scattering hypotheses, including Rayleigh, Tyndall, and Mie scattering (Kasukawa and Oshima, 1987; Friedmann, 1960). This scattering phenomenon occurs when light passes through a colloidal solution containing uniformly spherical particles, causing short-wave (blue, violet) light to scatter back to the surface, resulting in a visually blue color (Rootman et al., 2014). However, some studies (Edwards and Duntley, 1939; Prum and Torres, 2004) have criticized Tyndall scattering, arguing that blue skin is actually produced by the superficial collagen nano-structures above the typical layer of melanocytes. They propose that the dermal collagen arrays are nanostructured at the appropriate spatial scale by coherent scattering, which constitutes the quasi-ordered type of organization that produces a non-iridescent structural color through coherent scattering. These arrays are precisely convergent with color-producing collagen that has evolved numerous independent times in the skin of birds (Prum and Torres, 2003). Furthermore, the underlying melanosomes absorb light waves that are transmitted through the superficial color-producing collagen (Prum and Torres, 2004). However, while these studies have shed light on the visual, reflective, and structural aspects of blue skin, the genetic mechanisms underlying its formation remain unknown.

Following our observation and statistical analysis of Jiangshan black-bone chicken, we identified 3 primary phenotypic variations in earlobe color: dark peacock green, light peacock green, and dark reddish purple. Notably, the dark peacock green earlobes exhibit a pure peacock green color, while the light peacock green earlobes display a relatively white or yellowish hue. In contrast, the color of the dark reddish purple earlobes is similar to that of the bare epidermis on the head, such as the crown and wattle. To date, research on the causes of blue earlobe formation in poultry has been limited, and there has been a lack of studies on the differences in earlobe color among Jiangshan black-bone chickens.

In this study, we employed a multi-omics approach, combining tissue section staining, RNA sequencing, and 4D-DIA proteomics, to investigate the differences between earlobes of distinct colors in Jiangshan black-bone chicken. Through integrative analysis of these datasets, we revealed the underlying variations between earlobes of different colors, providing a valuable reference for elucidating the mechanisms of earlobe color formation in Jiangshan black-bone chicken.

MATERIALS AND METHODS

Animal

A total of 12 Jiangshan black-bone hens, each 360-days-old, were used in this study, with 4 individuals exhibiting dark reddish purple earlobes (Black group), 4 displaying dark peacock green earlobes (Blue group), and 4 showcasing light peacock green earlobes (Green group). The euthanasia protocol and tissue collection scheme employed in this study were approved by the Animal Health Committee of Zhejiang Agricultural and Forestry University (Hangzhou, China), with approval number ZAFUAC202401.

Hematoxylin-Eosin Staining and Melanin Masson-Fontana Staining

The earlobe tissue from each of the 3 groups (n = 4) was fixed in a 4% paraformaldehyde solution and then embedded in paraffin. Subsequently, the paraffin sections were deparaffinized to water, followed by staining. For Hematoxylin-Eosin (H&E) staining, the sections were treated with a high-definition constant staining pretreatment solution, then stained with H&E HD (Servicebio, Hubei, Wuhan, China), and finally dehydrated and mounted. The nucleus was stained blue, while the cytoplasm was stained red. For Melanin Masson-Fontana staining, the sections were stained using the Masson Fontana Stain Kit (Servicebio, Hubei, Wuhan, China) and finally cleared and sealed with xylene and neutral gum. Melanin was stained black, while collagen fibers were stained red. Following staining, the slides were digitally scanned using the PANNORAMIC 250 FLASH (3Dhistech, Budapest, Hungary).

RNA Sequencing

Total RNA was extracted from earlobe tissue using TRIzol Reagent, and its concentration and purity were assessed using Nanodrop2000 (Thermo Fisher, Waltham, MA). The integrity of the RNA was evaluated by agarose gel electrophoresis (Biowest, Nuaillé, France), and the RNA Integrity Number (RIN) values were determined using Agilent5300 (Agilent, Santa Clara, CA). The concentrations of all samples were ≥ 30 ng/μL, with RIN values > 6.5 and OD260/280 ratios ranging from 1.8 to 2.2, indicating that all RNA samples were suitable for constructing sequencing libraries. For RNA transcriptome sequencing, 1 μg of RNA per sample was used. Sequencing libraries were generated using Illumina NovaSeq Reagent (Illumina, San Jose, CA), and an index code was added to the attribute sequence for each sample. Messenger RNA was isolated using oligo (dT) magnetic beads and then fragmented using fragmentation buffer.

Next, double-stranded cDNA was synthesized using the SuperScript double-stranded cDNA Synthesis Kit (Invitrogen, Carlsbad, CA) with random hexamer primers. Subsequently, paired-end RNA-seq sequencing libraries were generated and sequenced using the NovaSeq 6000 sequencer (2 × 150 bp read length) (Illumina, San Jose, CA).

The fastp tool (https://github.com/OpenGene/fastp) was employed for comprehensive quality control of the RNA-sequencing raw reads. Following this, the clean reads from each sample were aligned to the chicken reference genome GRCg7b (Gallus_gallus, http://asia.ensembl.org/Gallus_gallus/Info/Index) using the HiSat2 tool (http://ccb.jhu.edu/software/hisat2/index.shtml), and the quality of the sequencing alignment results was evaluated.

The gene expression levels were quantified in terms of fragments per kilobase per million reads (FPKM) using RSEM (http://deweylab.github.io/RSEM/) (Li and Dewey, 2011). Under the condition that the screening threshold for differentially expressed genes (DEGs) was set at a significance level of P < 0.05 and an absolute |log2 fold change (FC)| ≥ 1, we employed DEGSeq (v1.38.0) differential analysis software for comparison. To account for multiple testing, the P-values were adjusted using the Benjamini and Hochberg's approach to control the false discovery rate (Benjamini and Hochberg, 1995).

cDNA Synthesis and Quantitative Real-Time PCR

The reverse transcription of total RNA from earlobe samples in 3 groups was carried out using 5X All-in-One RT MasterMix (Applied Biological Materials, Vancouver, Canada) to synthesize cDNA. All primers were designed based on NCBI (https://www.ncbi.nlm.nih.gov/) and are listed in Supplementary Table 1. We performed QRT-PCR on the StepOneTM Real-Time PCR System (Thermo Fisher, Waltham, MA) with 3 biological replicates and 3 technical replicates, respectively. The relative expression level was calculated using the 2–ΔΔCt method (Livak and Schmittgen, 2001).

4D-DIA Proteomics

Total protein was extracted from earlobe tissues using a protein lysis buffer (8M urea, 1% SDS) and quantified using the Pierce BCA Protein Assay Kit (Thermo Fisher) for SDS-PAGE electrophoresis. All samples had concentrations ≥ 0.7 μg/μL, thereby meeting the requirements for constructing sequencing libraries.

Following the manufacturer's guidelines, peptide digestion was performed with Modified Trypsin protease (Promega, Madison, WI), peptide desalting with HLB, and peptide quantification with the Pierce Peptide Quantitation Kit (Thermo Fisher). Equal amounts of peptide were then dissolved in the mass spectrometry loading buffer, and the fraction was collected using an EASY-nLC 1200 chromatograph (Thermo Fisher). Subsequently, LC-MS/MS analysis was performed using a timsTOF Pro2 mass spectrometer (Bruker, Germany).

The established spectral library was imported into Spectronaut 18, and product ion peaks were extracted from the DIA raw data. For quantitative analysis, 6 peptides per protein and 3 product ions per peptide were selected. Using the T test function in Rstudio (v4.1.0), we calculated the P-value and fold change (FC) of the differences between groups. With a screening threshold set at P < 0.05 and |log2FC| ≥ 0.263, we identified differentially expressed proteins (DEPs).

GO and KEGG Annotation and Enrichment

The detected genes and proteins were functionally annotated using the gene ontology (GO, http://www.geneontology.org) and Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.genome.jp/kegg) databases. We performed enrichment analysis using the Goatools software and Python's scipy package, and employed the Benjamini-Hochberg (BH) method to correct for multiple testing and control the false positive rate. Terms with a P-value < 0.05 were considered significantly enriched.

Cluster Analysis

Following the generation of heatmaps for DEGs and DEPs in RStudio (v4.1.0), we compared the average expression levels between groups. Using the average linkage distance algorithm, we employed RStudio (v4.1.0) to perform hierarchical clustering and standardized the data by z-score.

Protein-Protein Interaction Analysis

We conducted protein-protein interaction analysis using String (v11.5), which was then visualized using Cytoscape (v3.10.1) to generate a protein-protein interaction network map.

Statistical Analysis

All experimental results are presented as mean ± S.E.M, with a minimum of 3 independent replicates. We used independent sample T tests to compare 2 groups and One-way ANOVA to compare 3 groups, and considered differences statistically significant at P < 0.05. The following notation is used to indicate levels of significance: * P < 0.05; ** P < 0.01; *** P < 0.001; **** P < 0.0001.

RESULTS

Comparison of HE Staining and Melanin Masson-Fontana Staining of 3 Different Earlobe Colors

To investigate the structural characteristics of earlobes in 3 different colors, as well as the distribution of melanin in the tissues, we prepared longitudinal (cut in half at the plane of the earlobe, Figures 1A and 1B) and transverse (cut along the contour of the earlobe, Figures 2A and 2B) sections of earlobes from Jiangshan black-bone chickens (n = 4) using HE staining and melanin Masson-Fontana staining. Both longitudinal and transverse sections exhibited positive staining for melanin, confirming the presence of melanin in all 3 earlobe colors (Figures 1B and 2B). We observed an increase in the thickness of collagen fibers in the dermis from the Black, Blue, to Green group, respectively (Figures 1A and 1B, 50 ×). Measurement of the dermal collagen fiber thickness in all 12 samples (7 positions per sample) revealed that the Green group had significantly thicker fibers than the Blue group, while the Black group had significantly thinner fibers than the Blue group (Figure 1C). To gain a better understanding of melanin distribution, we generated transverse sections of both dermal and subcutaneous tissues (Figures 2A and 2B), which showed that both tissues contained a certain amount of melanin in all groups.

Figure 1.

Figure 1

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Comparison of HE staining and melanin Masson-Fontana staining of earlobe tissues of Jiangshan black-bone chickens with different earlobe colors for longitudinal sections. (A) HE staining of earlobe tissues of Jiangshan black-bone chickens with different earlobe colors; (B) Melanin Masson-Fontana staining of earlobe tissues of Jiangshan black-bone chickens with different earlobe colors. The melanin and cytoplasm of silverphiles cells is black, the collagen fibers are red, and the background is yellow; (C) The thickness of collagen fibers in the dermis between groups. Data were presented as means ± SEM. *P < 0.05, ****P < 0.0001 as indicated by One-way ANOVA. a: Epidermis; b: Dermis; c: Subcutaneous tissue; d: Melanin.

Figure 2.

Figure 2

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Comparison of HE staining and melanin Masson-Fontana staining of earlobe tissues of Jiangshan black-bone chickens with different earlobe colors for transverse sections. (A) HE staining of earlobe tissues of Jiangshan black-bone chickens with different earlobe colors; (B) Melanin Masson-Fontana staining of earlobe tissues of Jiangshan black-bone chickens with different earlobe colors. The melanin and cytoplasm of silverphiles cells is black, the collagen fibers are red, and the background is yellow. a: Epidermis; b: Dermis; c: Subcutaneous tissue; d: Melanin.

Differentially Expressed Genes of Jiangshan Black-Bone Chickens With Different Earlobe Colors

We performed RNA sequencing on earlobe tissues from the Black, Blue, and Green groups to investigate mRNA differences between earlobes of different colors (n = 4). All raw data were deposited in the CNCB GSA database (accession number CRA013279). In the RNA-Seq results, we obtained approximately 94.97 billion raw bases (628.9 million raw reads) and 93.26 billion clean bases (623.4 million clean reads) in total (Supplementary Table 2). The clean data were aligned to the chicken GRCg7b (GCA_016699485.1) reference genome, with a mapping rate ranging from 89.72 to 93.07% (Supplementary Table 2). We detected a total of 25,096 genes, comprising 23,911 known genes and 1,185 novel genes (Supplementary Table 3). The Q20 (The percentage of bases with sequencing quality above 99% in total bases) and Q30 (The percentage of bases with sequencing quality above 99.9% in total bases) of each sample were above 95%, indicating high-quality sequencing data suitable for subsequent analysis (Supplementary Table 2). Compared to the Black group, we identified 702 up-regulated and 197 down-regulated DEGs in the Green group, and 601 up-regulated and 489 down-regulated DEGs in the Blue group. In contrast to the Blue group, we found 498 up-regulated and 203 down-regulated DEGs in the Green group (Figures 3A–3C). Notably, there were overlapping DEGs among the comparisons between different groups, with 18 genes commonly differentially expressed in all 3 groups, including 10 functionally known genes (Figure 3D).

Figure 3.

Figure 3

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Differentially expressed genes (DEGs) of Jiangshan black-bone chickens with different earlobe colors. (A-C) Volcano plots of DEGs in Green_vs_Black (A), Blue_vs_Black (B) and Green_vs_Blue (C). The screening threshold of DEGs was P < 0.05 and |log2FC| ≥ 1; (D) Venn Diagram shows common and unique DEGs between groups; (E-G) GO functional enrichment analysis of DEGs in Green_vs_Black (E), Blue_vs_Black (F) and Green_vs_Blue (G). Biological Process (BP), Molecular Function (MF) and Cellular Component (CC).

All DEGs were subsequently used for gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Our GO enrichment results revealed that the "collagen trimer" term was significantly enriched between the Green and Black groups, as well as between the Blue and Black groups, with associated DEGs including LUM, COL4A3, COL4A4, COL6A1, COL6A2, COL6A3, COL9A1, COL12A1, and COL28A1 (Figures 3E and 3F, Supplementary Table 4). We also observed significant enrichment of terms related to muscle development and contraction between the Green and Black groups (Figure 3E, Supplementary Table 4), and cell cycle and cell signaling terms between the Blue and Black groups (Figure 3F, Supplementary Table 4). The significantly enriched GO terms between the Green and Blue groups were primarily related to muscle development, differentiation, and contraction (Figure 3G, Supplementary Table 4). The significantly enriched pathways among the 3 groups included neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction, JAK-STAT signaling pathway, chemical carcinogenesis - reactive oxygen species, PI3K-Akt signaling pathway, and others (Supplementary Figure 1A–C, Supplementary Table 5).

Gene Expression Pattern Analysis for Jiangshan Black-Bone Chickens With Different Earlobe Colors

To identify potential trends among the Black, Blue, and Green groups, we performed cluster analysis on all 1953 DEGs, which were divided into 10 subclusters based on gene expression (Figures 4C and 4D, Supplementary Table 6). As the earlobe color gradually lightens, we focused on genes that exhibited continuous increases (subclusters 3 and 9) or decreases (subcluster 7) in expression from Black to Blue and Green groups, and conducted GO and KEGG analyses on these 3 subclusters. In subcluster 3, the enriched terms were primarily related to muscle development, differentiation, and contraction (Supplementary Figure 2A and 2B), similar to the enrichment terms in subcluster 9 (Figures 4E and 4F, Supplementary Tables 7 and 8). Notably, both subcluster 7 and subcluster 9 showed significant enrichment of terms related to collagen fibers (Figures 4A and 4E, Supplementary Tables 7). In subcluster 7, the significantly enriched GO terms were collagen fibril organization and collagen-containing extracellular matrix, featuring DEGs such as LUM, ACAN, COL28A1, THBS2, and GREM1 (Figure 4A, Supplementary Tables 7). In subcluster 9, the significantly enriched term was collagen trimer, associated with COL4A4 (Figure 4E, Supplementary Tables 7). The significantly enriched KEGG pathways in subcluster 7 included Estrogen signaling pathway, cytokine-cytokine receptor interaction, and others (Figure 4B, Supplementary Table 8). In subcluster 9, the significantly enriched KEGG pathways comprised neurodegeneration - multiple diseases, Alzheimer disease, Oxidative phosphorylation, Chemical carcinogenesis - reactive oxygen species, Glycine, serine and threonine metabolism, and others (Figure 4F, Supplementary Table 8). The cluster analysis results suggest that collagen and muscle may be trending between the Black, Blue, and Green groups.

Figure 4.

Figure 4

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Gene expression pattern analysis for Jiangshan black-bone chickens with different earlobe colors. (A and E) GO functional enrichment analysis of DEGs in subcluster_7 (A) and subcluster_9 (E); (B and F) KEGG pathway analysis of DEGs in subcluster_7 (B) and subcluster_9 (F); (C) Cluster Analysis Heatmap of all 1953 DEGs clustered according to the average of the group; (D) 10 subclusters of cluster analysis. Y-axis: log10(expression).

The Validation of DEGs in RNA-Seq by qRT-PCR

We randomly selected 4 of the 18 DEGs that were differentially expressed across all 3 groups for qRT-PCR verification, specifically NDUFB6, SYPL2, ID1, and SDK2AP2 (Figure 5). Additionally, we chose DEGs related to collagen fibers that were significantly enriched in GO terms for expression verification, including COL6A1, COL6A2, COL6A3, COL12A1, LUM, and DPT (Figure 5). We also selected several DEGs from the significant KEGG pathways for verification, such as NFKBIA and PIK3CD (Figure 5).

Figure 5.

Figure 5

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The expression of some key DEGs were verified by qRT-PCR. The FPKM value was taken as the relative expression level of DEGs, which is shown as the red line, corresponding to the Y-axis on the right side. The qRT-PCR validation used the black bar chart, corresponding to the Y-axis on the left side, and GAPDH was used for each sample as an endogenous control. Three independent biologicals and 3 technical replicates were employed. Data were presented as means ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001 as indicated by One-way ANOVA.

Differentially Expressed Proteins of Jiangshan Black-Bone Chickens With Different Earlobe Colors

While transcriptome data provide a wealth of information at the transcriptional level, they only represent an intermediate state of gene expression and potential protein expression and functional significance. It is the protein that ultimately exerts a real functional effect. To investigate protein differences in earlobes of different colors, we performed 4D-DIA proteomics on earlobe tissues from the Black, Blue, and Green groups (n = 4). All raw data were deposited on the iProX platform (PXD number PXD047687). We identified 31,820 peptides and 4,138 proteins, indicating good sequencing quality and suitability for subsequent analysis (Supplementary Table 9). Compared to the Black group, we found 115 up-regulated and 137 down-regulated proteins in the Green group, and 230 up-regulated and 250 down-regulated proteins in the Blue group. In contrast to the Blue group, we observed 107 up-regulated and 111 down-regulated proteins in the Green group (Figure 6A-C). Notably, there were overlapping DEPs among the comparisons between different groups, with 7 proteins commonly differentially expressed in all 3 groups, including 6 annotated proteins (Figure 6D).

Figure 6.

Figure 6

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Differentially expressed proteins (DEPs) of Jiangshan black-bone chickens with different earlobe colors. (A-C) Volcano plots of DEPs in Green_vs_Black (A), Blue_vs_Black (B) and Green_vs_Blue (C). The screening threshold of DEPs was P < 0.05 and |log2FC| ≥ 0.263; (D) Venn Diagram shows common and unique DEPs between groups; (E–G) GO functional enrichment analysis of DEPs in Green_vs_Black (E), Blue_vs_Black (F) and Green_vs_Blue (G).

We screened the top 20 significant enriched GO terms and found that the collagen fibril organization term was significantly enriched between the Green and Black groups, with associated DEPs LUM and DPT (Figure 6E, Supplementary Table 10). The significantly enriched GO terms between the Blue and Black groups were primarily related to supramolecular fiber organization and actin binding (Figure 3E, Supplementary Table 10), while those between the Green and Blue groups were mainly related to cell adhesion (Figure 3F, Supplementary Table 10). Directed acyclic diagrams were used to represent the relationships between the GO terms (Supplementary Figures 3A–3C). The significantly enriched pathways among the 3 groups included neuroactive ligand-receptor interaction, ECM-receptor interaction, cell adhesion molecules, ErbB signaling pathway, p53 signaling pathway, nicotinate and nicotinamide metabolism, and others (Supplementary Figures 3D–3F, Supplementary Table 11).

Protein Expression Pattern Analysis for Jiangshan Black-Bone Chickens With Different Earlobe Colors

We also conducted a cluster analysis of all 716 DEPs. This analysis divided the DEPs into 10 subclusters based on their expression patterns (Figures 7C and 7D, Supplementary Table 12). We focused on the subclusters that exhibited successive increases (subclusters 2 and 9) or decreases (subcluster 5) in average expression levels from the Black to Blue and Green groups, and performed GO and KEGG analyses on these 3 subclusters. In subcluster 2, the significantly enriched GO terms were collagen fibril organization and collagen-containing extracellular matrix, with GPC1 and PRELP being the key DEPs (Figure 7A, Supplementary Table 13). Subcluster 9 was characterized by enriched terms related to muscle function (Supplementary Figures 4A and 4B), similar to those in subcluster 2 (Figures 7A and 7B, Supplementary Tables 13 and 14). In contrast, subcluster 5 was enriched for terms related to oxidative and antioxidant activity (Figure 7E, Supplementary Tables 13). The KEGG pathways significantly enriched in subcluster 2 included Phenylalanine, tyrosine and tryptophan biosynthesis, Phenylalanine metabolism, Cytokine-cytokine receptor interaction, and others (Figure 7B, Supplementary Table 14). Subcluster 9 was enriched for pathways such as Neuroactive ligand-receptor interaction, Apelin signaling pathway, and Phenylalanine, tyrosine and tryptophan biosynthesis (Supplementary Figure 4B). Meanwhile, subcluster 5 was enriched for pathways involved in Base excision repair and p53 signaling (Figure 7F, Supplementary Table 14). The results of our cluster analysis suggest that collagen, muscle function, and oxidative and antioxidant activity may be trending from the Black to Blue and Green groups.

Figure 7.

Figure 7

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Proteins expression pattern analysis for Jiangshan black-bone chickens with different earlobe colors. (A and E) GO functional enrichment analysis of DEPs in subcluster_9 (A) and subcluster_5 (E); (B and F) KEGG pathway analysis of DEPs in subcluster_9 (B) and subcluster_5 (F); (C) Cluster Analysis Heatmap of all 716 DEPs clustered according to the average of the group; (D) 10 subclusters of cluster analysis. Y-axis: log10(expression).

Conjoint Analysis of DEGs and DEPs and Protein-Protein Interaction Network

Conjoint analysis can further validate DEGs and DEPs, overcoming the limitations of relying on a single omics analysis. We identified 12 DEGs and DEPs associated with the Green vs. Black group, of which 8 DEGs (7 up-regulated and 1 down-regulated) showed consistent expression with their corresponding DEPs (Figure 8A). Similarly, we found 24 DEGs and DEPs associated with the Blue vs. Black group, with 23 DEGs (8 up-regulated and 15 down-regulated) exhibiting consistent expression with their corresponding DEPs (Figure 8B). Additionally, 6 DEGs and DEPs were associated with the Green vs. Blue group, with consistent expression observed (Figure 8C). To further explore the relationships between the 3 groups, we performed GO analysis on all genes and proteins obtained from the association analysis between the groups. The results revealed that the collagen fibril organization term was significantly enriched between the Green and Black groups, with the representative DEG and DEP LUM also included in this term (Figure 8D, Supplementary Table 15). We also conducted KEGG analysis between the Green and Black groups, which identified 4 significantly enriched pathways: steroid hormone biosynthesis (SRD5A2), adrenergic signaling in cardiomyocytes (PPP1R1A), purine metabolism (AMPD1), and cell adhesion molecules (MPZ) (Figure 8F, Supplementary Table 16).

Figure 8.

Figure 8

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Conjoint analysis of DEGs and DEPs and protein-protein interaction (PPI) network. (A–C) Quantitative Venn diagrams of the transcriptome and proteome in Green_vs_Black (A), Blue_vs_Black (B) and Green_vs_Blue (C); (D) GO functional enrichment analysis of all 12 DEGs and DEPs in Green_vs._Black; (E) PPI network diagram of 21 DEGs and DEPs associated in the 3 groups; (F) Four KEGG pathways based on the association analysis of DEGs and DEPs between Green and Black group.

Finally, we used STRING analysis to examine the potential interaction network of all 27 named DEGs and DEPs associated with the 3 groups. The analysis revealed a protein-protein interaction (PPI) network consisting of 21 DEGs and DEPs (Figure 8E). Notably, ITGB2 was located at the core of the network and was linked to 6 proteins: LUM, HCLS1, ZAP70, CSK, CYFIP2, and GFAP (Figure 8E). This suggests that ITGB2 may be a potential candidate gene that interacts with these 6 genes to affect earlobe color differences, particularly in the context of the representative gene LUM.

DISCUSSION

Several studies have classified the peacock green earlobes of the Jiangshan black-bone chicken as blue earlobes (Chen et al., 2019). By analogy with blue earlobes and blue skin, we hypothesize that the mechanism underlying earlobe color formation in the Jiangshan black-bone chicken may be similar to that of blue skin. Notably, our study detected melanin and collagen in all 3 colors of earlobes (Figure 1B), suggesting that the 3 earlobe colors of the Jiangshan black-bone chicken are likely attributed to coherently scattering dermal collagen arrays. The tonal differences between different structurally colored skin are known to be due to the size and spacing of dermal collagen fibers (Prum et al., 1999; Prum and Torres, 2003). Interestingly, Prum and Torres (2004) found that light blue skin (1,600 μm) in Mandrillus sphinx had nearly twice as much collagen layer as dark blue skin (800 μm), indicating that light-colored structural colors are associated with thicker collagen layers. Our results are surprisingly consistent, with a significant difference in thickness of the collagen fiber layer observed between the 3 earlobe colors. Specifically, the light peacock green (Green group) earlobes had the thickest collagen fibers layer, followed by the dark peacock green (Blue group) earlobes, and then the dark reddish purple (Black group) earlobes (Figure 1). Furthermore, based on the number of individuals (n = 4), we found that the light peacock green (Green group) earlobes were thicker than the other 2 earlobes, while the dark reddish purple (Black group) earlobes were the thinnest (Figure 1A and 1B, 17 ×). However, due to the limited sample size, it is necessary to increase the number of individuals studied to verify these findings and exclude the influence of individual differences.

The dark reddish purple earlobes (Black group) exhibited a color profile similar to that of black earlobes, which are often attributed to an excess of melanin or melanocytes, a condition commonly observed in black-bone chickens. However, we found that most of the melanin in the dark reddish purple (Black group) earlobes was concentrated in the dermis near the epidermis (Figure 1B). This observation led us to speculate that the formation of the dark reddish purple (Black group) earlobes may be influenced by the distribution of melanin.

The results of our RNA-seq and 4D-DIA proteomics analyses revealed significant enrichment of collagen fiber-related terms, including LUM, DPT, COL4A3, COL4A4, COL6A1, COL6A2, COL6A3, COL9A1, COL12A1, and COL28A1 (Figures 3E, 3F, and 6E), across the 3 colors of earlobes. Furthermore, cluster analysis of the 2 sequencing methods showed that genes and proteins related to collagen fibers, such as LUM, ACAN, COL4A4, COL28A1, GREM1, THBS2, GPC1, and PRELP, exhibited expression gradients among the dark reddish purple (Black group), dark peacock green (Blue group), and light peacock green (Green group) earlobes (Figures 4A, 4E, and 7A). These findings are more indicative of the differences associated with collagen fibers between the 3 colors of earlobes, consistent with the research of Edwards and Duntley (1939) and Prum and Torres (2004). This suggests that the formation of the 3 earlobe colors in Jiangshan black-bone chickens is likely attributed to coherently scattering dermal collagen arrays. Notably, except for ID1, DPT, and PIK3CD, the qRT-PCR results were largely consistent with the RNA sequencing results, further validating the reliability of the RNA sequencing data (Figure 5).

The RNA-seq and protein-seq results revealed that the most significantly enriched pathways were related to neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction, JAK-STAT signaling, PI3K-Akt signaling, p53 signaling, and cell adhesion, among others (Supplementary Figures 1A–1C and 3D–3F). Notably, the JAK-STAT signaling pathway (Xu et al., 2023; Yan et al., 2023), PI3K-Akt signaling pathway (Liu et al., 2022; Zhang et al., 2023), and p53 signaling pathway (Modaghegh et al., 2022) were implicated in collagen fiber formation. This suggests that there were differences in collagen fiber production between the 3 colors of earlobes. Interestingly, Li et al. (2018) used collagen to establish a liver culture system and found that differentially expressed genes (DEGs) from monolayer culture were involved in neuroactive ligand-receptor interaction. Similarly, Ruvalcaba-Ontiveros et al. (2022) reported that DEGs were enriched in the cytokine-cytokine receptor interaction term when comparing collagen-induced arthritis with the treatment group. Therefore, we hypothesize that neuroactive ligand-receptor interaction and cytokine-cytokine receptor interaction may influence the formation of the 3 color differences in earlobes by modulating collagen production, but further in-depth research is still required to confirm this.

Notably, 2 subclusters with opposing expression patterns emerged from the RNA-seq cluster analysis, and we were surprised to find that terms related to collagen fibers (LUM, ACAN, COL4A4, COL28A1, GREM1, THBS2) were enriched in both subclusters (Figures 4A and 4E). This may be attributed to the opposite effects of DEGs on collagen fiber production. Interestingly, Colon-Caraballo et al. (2022) reported that structural defects in collagen fiber tissue in leucine-deficient nonpregnant mice were associated with lumican (LUM). Aggrecan (ACAN) expression was found to decrease, accompanied by a decrease in the expression of partial collagen-related genes (Xu et al., 2017). Furthermore, Müller et al. (2021) demonstrated that Gremlin-1 (GREM1) reduced collagen production in TGF-β-induced cardiac fibroblasts by approximately 20%. Kozumi et al. (2021) showed that Thrombospondin 2 (THBS2) may cause structural abnormalities in collagen fibers. These findings suggest that DEGs such as LUM, ACAN, GREM1, and THBS2 in Figure 4A can influence collagen production. The expression of these DEGs decreased sequentially from the Black to Blue and Green groups, implying that the effect of collagen was weakened in a stepwise manner. As a gene encoding one of the 6 subunits of type IV collagen, COL4A4 (Collagen type IV alpha 4 chain) plays a crucial role in collagen synthesis (Abreu-Velez and Howard, 2012; Sargazi et al., 2019). In this study, COL4A4 expression was found to increase from the Black to Blue and Green groups (Figure 4E), whereas COL28A1 (collagen type XXVIII alpha 1 chain) expression decreased (Figure 4A). Although we observed differences in the thickness of dermal collagen fibers, further experimental verification is needed to determine whether there are differences in collagen content. Consistently, protein sequencing results revealed similar patterns, with 2 subclusters emerging in the protein sequencing cluster analysis (Figures 7A and 7E), and terms related to collagen fibers, including GPC1 and PRELP, were also enriched (Figure 7A). Notably, Glypican-1 (GPC1) and proline and arginine rich end leucine rich repeat protein (PRELP) are involved in collagen fibers (Ullah et al., 2013; Li et al., 2016; Lee et al., 2020; Cai et al., 2023).

We performed an association analysis of the 2 omics datasets, focusing on the overlapping DEGs and differentially expressed proteins (DEPs) (Figures 8A–8C). Notably, the relationship between the dark reddish purple (Black group) and light peacock green (Green group) was associated with collagen-related terms, specifically lumican (LUM) (Figure 8D). However, it is worth noting that the expression trends of DEGs and DEPs in LUM are inversely correlated: gene expression is higher in the dark reddish purple (Black group) than in the light peacock green (Green group), whereas protein expression is higher in the light peacock green (Green group) than in the dark reddish purple (Black group). We hypothesize that this may be related to the sedimentation of LUM, as similar observations have been reported in previous studies (Svensson et al., 1999). In contrast, no collagen-related terms were found between the other 2 earlobe colors, which may be attributed to the uneven color distribution of the earlobes in the same area, with other colors scattered throughout. Alternatively, this may be due to translational regulation between the transcriptome and proteome. The dark reddish purple (Black group) and light peacock green (Green group) are linked to the cell adhesion molecules (CAMs) pathway (Figure 8F). CAMs are cell surface molecules that promote cell-to-cell or cell-matrix binding, exerting adhesion and triggering intracellular signaling, thereby regulating various cellular activities (Ruan et al., 2022). The light peacock green (Green group) may exhibit a stronger cell adhesion effect through myelin protein zero (MPZ).

When we analyzed all DEGs and DEPs for PPI, we identified ITGB2 as a potential candidate gene that interacts with LUM, HCLS1, ZAP70, CSK, CYFIP2, and GFAP (Figure 8E). This suggests that ITGB2 may play a crucial role in earlobe color differences. The Integrin subunit beta 2 gene (ITGB2) encodes an integrin β chain, which forms different integrin heterodimers by binding to several distinct α chains (Conley and Sheats, 2023). ITGB2 is involved in cell adhesion as well as cell surface-mediated signaling (Swaim et al., 2017). Our results imply that further research on ITGB2 is warranted, and it is currently suggested that collagen production and deposition may influence ITGB2 expression (Namous et al., 2023; Qian and Li, 2023). Notably, Bagnara et al. (2007) proposed that the study of blue skin should focus on the collagen aggregation system due to its ability to alter the light reflection pattern of the collagen array, which is consistent with our findings that LUM, a member of the small proteoglycan (SLRP) family, can interact with multiple proteins (Figure 8E), indicating that LUM may be a hub gene.

Through multiple analyses, we have consistently identified LUM as a key gene potentially responsible for the color differences between the 3 earlobes. LUM, also known as corneal keratan sulfate proteoglycan, is an ECM-secreted proteoglycan that regulates collagen fibrillogenesis (Dupuis et al., 2015). Studies have shown that LUM inhibits the spontaneous formation of collagen fibers in vitro by collagen molecules, resulting in collagen fibers with significantly smaller diameters (Vogel et al., 1984; Hedbom and Heinegard, 1993; Rada et al., 1993). And LUM may promote the formation of thicker, longer, but fewer collagen fibers through the accumulation of collagen protein (Rixon et al., 2023). Therefore, compared to the dark reddish purple (Black group), LUM protein was highly expressed in the light peacock green (Green group), which may lead to the production of thicker but fewer collagen fibers in the light peacock green (Green group), thereby affecting the production of collagen nanostructures. These results were consistent with our melanin staining results, which revealed differences in collagen fiber thickness between the 3 groups. Under the influence of melanin, the collagen protein array can generate sufficient fibers to present color by affecting the size of collagen fibers and the distance between them (Prum and Torres 2004). Ultimately, the dark peacock green (Blue group) and light peacock green (Green group) presented structural colors and became lighter as the collagen layers turned thicker. Additionally, collagen family genes (COL4A3, COL4A4, COL6A1, COL6A2, COL6A3, COL9A1, COL12A1, COL28A1), multifunctional glycan proteoglycan family gene (ACAN), and extracellular matrix proteins (DPT) may also be key genes worthy of further investigation. They may have co-regulated the production of collagen fibers by assisting LUM, which in turn caused the difference in the color of the 3 earlobes.

Some studies on blue skin corroborate our speculations. For instance, Quinn and Hews (2003) observed a significant increase in skin melaninization under the iris of blue skin, suggesting that melanin plays a crucial role in absorbing wavelengths other than blue. Similarly, Jeon et al. (2023) discovered that keratin cortex thickness influences the main reflection peak of feather nanostructured melanosomes, resulting in a structural blue color. Notably, Prum et al. (1994) found that non-iridescent green and blue skin colors in birds are produced by coherent scattering of dermal collagen fiber arrays in hexagonal tissues. Furthermore, Prum and Torres (2004) demonstrated that in the dermis of mammals, collagen arrays are indeed responsible for the source of coherent light scattering in blue. These studies, along with our results, consistently indicate that blue skin is formed through the interaction of melanin and collagen fibers.

CONCLUSIONS

The peacock green earlobes in Jiangshan black-bone chickens are formed through the interaction of melanin and collagen fibers. A series of key differentially expressed genes/proteins (DEGs/DEPs) associated with collagen fibers, such as LUM, may influence the collagen nanostructures, thereby enhancing the effect of melanin-supported dermal collagen on the production of non-iridescent structural colors through coherent scattering. As a result, a bright structural blue color is presented in Jiangshan black-bone chickens.

DISCLOSURES

The authors declare no conflicts of interest.

ACKNOWLEDGMENTS

This research was funded by A Project Supported by Scientific Research Fund of Zhejiang Provincial Education Department (Y202249637), Jiangshan Agriculture and Rural Bureau (2023110), Zhejiang A&F University Talent Initiative Project (2023LFR090).

Footnotes

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.psj.2024.103864.

Appendix. Supplementary materials

mmc1.docx (6.3MB, docx)

Supplementary Table 1: The primers used for qRT-PCR.

mmc2.xlsx (5.4MB, xlsx)

Supplementary Table 2: The information of RNA sequencing in each sample.

mmc3.xlsx (52.9KB, xlsx)

Supplementary Table 3: Details of all DEGs between 3 groups.

mmc4.xlsx (38.9KB, xlsx)

Supplementary Table 4: Enriched GO terms of DEGs between 3 groups.

mmc5.xlsx (18.4KB, xlsx)

Supplementary Table 5: Enriched KEGG of DEGs between 3 groups.

mmc6.xlsx (36.4KB, xlsx)

Supplementary Table 6: Cluster analysis for DEGs in 3 groups.

mmc7.xlsx (23.8KB, xlsx)

Supplementary Table 7: Enriched GO terms of DEGs in cluster analysis.

mmc8.xlsx (1.1MB, xlsx)

Supplementary Table 8: Enriched KEGG of DEGs in cluster analysis.

mmc9.xlsx (37.6KB, xlsx)

Supplementary Table 9: Details of all DEPs between 3 groups.

mmc10.xlsx (53.4KB, xlsx)

Supplementary Table 10: Enriched GO terms of DEPs between 3 groups.

mmc11.xlsx (98.2KB, xlsx)

Supplementary Table 11: Enriched KEGG of DEPs between 3 groups.

mmc12.xlsx (107KB, xlsx)

Supplementary Table 12: Cluster analysis for DEPs between 3 groups.

mmc13.xlsx (21.2KB, xlsx)

Supplementary Table 13: Enriched GO terms of DEPs in cluster analysis.

mmc14.xlsx (11.3KB, xlsx)

Supplementary Table 14: Enriched KEGG of DEPs in cluster analysis.

mmc15.xlsx (12.5KB, xlsx)

Supplementary Table 15: Enriched GO terms of DEGs&DEPs in Green_vs_Black.

mmc16.xlsx (3.6MB, xlsx)

Supplementary Table 16: Enriched KEGG of DEGs&DEPs in Green_vs_Black.

mmc17.xlsx (210.2KB, xlsx)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

mmc1.docx (6.3MB, docx)

Supplementary Table 1: The primers used for qRT-PCR.

mmc2.xlsx (5.4MB, xlsx)

Supplementary Table 2: The information of RNA sequencing in each sample.

mmc3.xlsx (52.9KB, xlsx)

Supplementary Table 3: Details of all DEGs between 3 groups.

mmc4.xlsx (38.9KB, xlsx)

Supplementary Table 4: Enriched GO terms of DEGs between 3 groups.

mmc5.xlsx (18.4KB, xlsx)

Supplementary Table 5: Enriched KEGG of DEGs between 3 groups.

mmc6.xlsx (36.4KB, xlsx)

Supplementary Table 6: Cluster analysis for DEGs in 3 groups.

mmc7.xlsx (23.8KB, xlsx)

Supplementary Table 7: Enriched GO terms of DEGs in cluster analysis.

mmc8.xlsx (1.1MB, xlsx)

Supplementary Table 8: Enriched KEGG of DEGs in cluster analysis.

mmc9.xlsx (37.6KB, xlsx)

Supplementary Table 9: Details of all DEPs between 3 groups.

mmc10.xlsx (53.4KB, xlsx)

Supplementary Table 10: Enriched GO terms of DEPs between 3 groups.

mmc11.xlsx (98.2KB, xlsx)

Supplementary Table 11: Enriched KEGG of DEPs between 3 groups.

mmc12.xlsx (107KB, xlsx)

Supplementary Table 12: Cluster analysis for DEPs between 3 groups.

mmc13.xlsx (21.2KB, xlsx)

Supplementary Table 13: Enriched GO terms of DEPs in cluster analysis.

mmc14.xlsx (11.3KB, xlsx)

Supplementary Table 14: Enriched KEGG of DEPs in cluster analysis.

mmc15.xlsx (12.5KB, xlsx)

Supplementary Table 15: Enriched GO terms of DEGs&DEPs in Green_vs_Black.

mmc16.xlsx (3.6MB, xlsx)

Supplementary Table 16: Enriched KEGG of DEGs&DEPs in Green_vs_Black.

mmc17.xlsx (210.2KB, xlsx)

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