Abstract Background Blackness and growth traits are regarded as crucial economic traits in black-bone chicken production. In order to meet consumers’ demand for black-bone chickens, it is necessary to study the mechanisms of body weight growth and melanin deposition in black-bone chickens. The genetic variations in growth traits, blackness traits, breast muscle transcriptome, and metabolism were compared between the Yanjin black-bone (YJ) chicken group (n = 20) and Jinling Partridge black-bone (JL) chicken group (n = 20). In addition, very high-melanin content (HB) individuals (n = 6) and very low-melanin content individuals (LB) (n = 6) were selected from the JL chicken group to investigate the melanin synthesis mechanism. Results Comparison between the breast muscle transcriptomes of YJ chickens and JL chickens, as well as between HB and LB of JL chickens, revealed that 81 common differentially expressed genes (DEGs) were significantly enriched in melanosomes, pigment particles, and melanogenesis pathways. Among them, four candidate genes, namely TYRP1, KIT, PRKCB and EDNRB2, may be significantly associated with melanin production in black-bone chicken breast muscle. Also, 2 of the marker metabolites among the 16 common differential metabolites (DMs) identified, namely tetrahydrobiopterin (BH[4]) and N-acetylneuraminic acid, significantly contribute to melanin synthesis in the breast muscle of black-bone chickens. Conclusion Our research presents complex regulatory networks of DEGs and DMs in melanin synthesis pathways. The results establish a basis for raising black-bone chickens with optimal melanin levels and offer a theoretical framework for investigating the mechanisms of melanin formation in these hens. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-025-11803-7. Keywords: Transcriptomics, Metabolomics, Melanin synthesis, Black-bone chicken Introduction Black-bone chicken has unique nutritional and medicinal values, which makes it a functional food under the concept of “medicine and food” from the same source [[42]1]. Both traditional Chinese and Western folk medicine have long tradition of using black-bone chicken for medicinal purposes [[43]2]. China has abundant natural resources and a diverse array of chicken breeds. Among them, the Jinling Partridge black-bone (JL) chicken and the Yanjin black-bone (YJ) chicken are two representative local breeds. The ‘YJ chicken’ originating from Yanjin County in Yunnan Province, China, is a distinctive, high-quality local breed, that has been reported to contain high levels of calcium, iron, zinc, selenium, and other trace elements [[44]3]. Known for its tender meat and delicious taste, the YJ chicken is popular in culinary and medicinal applications, especially in traditional Chinese medicine and dietary therapy, where it is believed to be beneficial for health. However, YJ chickens have slow growth rate, reaching market age at 300 days. The skin of Yanjin black-boned chicken is dark black. Roosters achieve a market weight of 2.5–3.5 kg, while hens reach 2.2–2.6 kg (standard number: DB5306T4-2019). Jinling black-bone chicken is produced by the combination of three lines: Guangxi black-bone chicken serves as the terminal paternal parent, Hunan Jingzhou black-bone chicken as the terminal maternal parent, and recessive white chicken as the terminal maternal parent. The JL chicken is a fast-growing meat breed characterized by moderately dark skin color, fast growth, and high adaptability. It is suitable for breeding in diverse regions across China. These chickens reach market age in just 60 days, with roosters weighing 2.5–3.5 kg and hens reaching 2–2.5 kg [[45]4]. The melanin content serves as a significant predictor of the nutritional quality of black-bone chicken meat [[46]5]. Numerous studies have shown that melanin has biological effects, such as antioxidant [[47]6], anti-inflammatory [[48]7], immune regulation [[49]8], lowering blood sugar and lipid levels [[50]9], and blood enrichment [[51]10]. However, there are different levels of darkness in black-bone chicken meat on the market, and some pieces are even white. The variations in the degree of pigmentation in black-bone chicken meat impact its economic value, affecting the quality and market competitiveness of black-bone chicken products. Therefore, controlling the level of pigmentation in black-bone chicken meat is crucial for improving its quality. The deposition of melanin in black-bone chicken meat is primarily determined by genetic and nutritional factors. Genes such as MC1R, MITF, TYRP1, and EDN3 are significantly more highly expressed in the darker breast muscles of Guangxi W black-bone chickens compared to their lighter counterparts [[52]11]. The addition of L-tyrosine to the diet can increase the expression of melanin deposition-related genes, such as EDNRB2, DCT, and MLANA, in Xichuan black-bone chickens, thereby promoting melanocyte proliferation and enhancing melanin deposition in the breast muscle [[53]12]. Additionally, some studies have focused on regulating the degree of skin darkness in black-bone chickens. Eighteen miRNAs, including gga-miR-204, have been found to be differentially expressed between the dark and light skin of Xichuan black-bone chickens [[54]12]. Genes such as DCT, TYR, EDNRB2, MC1R, cAMP, and KIT show significantly higher expression in black skin tissues of Xichuan black-bone chickens compared to yellow skin tissues [[55]13]. These studies have revealed that the aforementioned genes primarily affect the melanin synthesis pathway across various species and tissues. Understanding the molecular mechanisms underlying the differences in melanin deposition is essential for improving the nutritional quality of the meat, functional value of meat quality, and the breed of black-bone chickens. The present study combines transcriptomics and metabolomics analyses to investigate candidate genes and metabolites potentially involved in the melanin synthesis pathway of Chinese local black-bone chickens (YJ chickens) and hybrid black-bone chickens (JL chickens) through multivariate data analysis. Additionally, metabolic pathways that may be influenced by melanin synthesis are also explored. Materials and methods Animals and sample collection A total of 120 Yanjin black-bone (YJ) chickens and 120 Jinling Partridge black-bone (JL) chickens (half male and half female) were provided by the Guangxi Jinling Husbandry Group Co., Ltd. (Nanning, China). The chickens were raised under the same conditions from birth to slaughter. This study was conducted in accordance with the Guidelines for the Use of Experimental Animals issued by the Ministry of Science and Technology (Beijing, China). The experimental protocols were approved by the Ethics committee the Science Research Department of the Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS; Beijing, China). Chickens were euthanized through cervical dislocation, and their carcasses were weighed post-slaughter. The right breast muscle was carefully removed, quickly weighed with an electronic scale and the lightness (L) value of the right breast muscle was measured with a by a Minolta CR-400 Colorimeter (Konica Minolta Inc., Tokyo, Japan). The growth characteristics of YJ and JL chickens at 60 days of age to slaughter are shown in Table [56]1. The left breast muscle was excised using sterile scissors, and the visible fascia, fat, and connective tissue were removed. After collecting 1 cubic centimeter of breast muscle in a cryopreservation tube, it was frozen in liquid nitrogen for LC–MS/MS and RNA-seq analysis. Table 1. Comparative analysis of growth and blackness traits in 240 black-bone chickens YJ (n = 120) JL (n = 120) SEX MALE (n = 60) CV% FEMALE (n = 60) CV% MALE (n = 60) CV% FEMALE (n = 60) CV% Live weight before slaughter (g) 1831.9 ± 81.9 4.5% 1500.1 ± 74.6 5.0% 2382.0 ± 180.3 7.6% 2114.9 ± 103.1 4.9% Dressed weight (g) 1630.9 ± 117.7 7.2% 1353.5 ± 68.6 5.1% 2188.6 ± 168.5 7.7% 1933.5 ± 96.5 5.0% Breast muscle weight (g) 212.3 ± 19.4 9.1% 176.9 ± 18.7 10.6% 365.8 ± 35.4 9.7% 330.2 ± 32.3 9.8% Lightness (L) 42.2 ± 4.4 10.4% 40.1 ± 4.2 10.5% 48.7 ± 2.9 6.0% 46.2 ± 3.6 7.6% [57]Open in a new tab YJ Yanjin black-bone chicken, JL Jinling Partridge black-bone chicken Blackness traits and grouping After slaughtering, the same area of breast muscle of all black-bone chickens was measured by a Minolta CR-400 Colorimeter. The colorimeter was calibrated with a whiteboard before the determination, and the measurement scale was adjusted to lightness (L), green–red axis (a), blue-yellow axis (b) mode, with the L value representing the lightness of the breast muscle, ranging from 0 to 100. We randomly selected 30 YJ and 30 JL from female individuals to measure L value and melanin content, and also verified the relationship between them. From the perspective of breeds, the first comparison group was 20 YJ female chickens and 20 JL female chickens for multi-omics analysis. Since the JL chicken is a hybrid black chicken, and the YJ chicken is a pure line, during the production, we observed that the variation of melanin content in JL chickens was large. Therefore, we analyzed the difference of melanin deposition in JL female chickens. Six individuals with extremely high melanin content were selected as the HB group and 6 individuals with extremely low melanin content were selected as the LB group among 20 individuals. Determination of melanin content Melanin was oxidized and hydrolyzed to 1 h-pyrrolio-2, 3-dicarboxylic acid (PDCA) and 1 h-pyrrolio-2,3, 5-tricarboxylic acid (PTCA) by hydrogen peroxide under alkaline environment. After purification by anion exchange solid phase extraction column, the contents of PDCA and PTCA were determined by liquid chromatoc-multiple heavy ion method. The content of melanin in different tissues was obtained indirectly by the correction coefficient of melanin alkalolysis [[58]14]. Detailed sample pre-processing procedures and LC–MS/MS (MRM) testing conditions can be found in the supplementary materials (Table S12). Total RNA extraction, cDNA library construction, and sequencing RNA-seq libraries were created from 1 μg of total RNA using the TruSeq™ RNA Sample Preparation Kit (Illumina Inc., San Diego, CA, USA). An Agilent 2100 Bioanalyzer/Agilent 4200 TapeStation (Agilent Technologies Inc.) examined RNA integrity, while a Qubit 2.0 Fluorometer and NanoDrop ND-2000 spectrophotometer measured RNA concentration and purity. PolyA selection with oligo (dT) beads isolated and fragmented mRNA. RNAClean XP Kit (Beckman Coulter Inc.) and RNase-Free DNase Set (QIAGEN GmbH) were employed to purify mRNA. The sequencing library was created using cDNA synthesis, adapter ligation, and enrichment after purification and fragmentation. The Qubit 2.0 Fluorometer monitored library concentration and the Agilent 4200 TapeStation evaluated fragment distribution. The Illumina NovaSeq6000 generated paired-end 150 bp reads in PE150 mode. Analysis of RNA-seq data Raw data were analyzed using FastQC (v0.10.1) software to assess Q20 (the percentage of bases with a Phred quality score of 20 or higher, indicating 99% accuracy for each base call) and GC content. Only high-quality clean data were used for downstream analyses. All clean reads were aligned to the chicken genome (GRCg6a) utilizing Hisat2 (v2.0.4). Additionally, gene fragments were counted using StringTie (v1.3.3b), followed by normalization of the trimmed mean of M (TMM) values. Differential gene expression analysis between groups was performed using the DESeq2 R package (1.20.0) in the R software Bioconductor [[59]15]. Genes with P-value < 0.05 in DESeq2 were considered DEGs. Gene ontology (GO) term enrichment analysis of DEGs was conducted using the clusterProfiler R package, with gene length bias corrected. GO terms with P-value < 0.05 were considered significantly enriched. KEGG pathway enrichment analysis was also performed using the clusterProfiler R package, testing for statistical enrichment of DEGs in the KEGG pathway database. Metabolite extraction Following the precise measurement of a suitable sample quantity in a 2 mL centrifuge tube, 1,000 µL of tissue extraction solution, consisting of 75% reagent (9:1 methanol: chloroform) and 25% H[2]O, was introduced, accompanied by steel balls. The tube was positioned in a tissue grinder, and the tissue was processed at 50 Hz for 60 s, with the procedure conducted twice. The sample underwent ultrasound treatment at room temperature for 30 min, subsequently followed by incubation in an ice bath for an additional 30 min. The sample was subsequently centrifuged for 10 min at 12,000 rpm and 4 °C. The supernatant was collected and transferred to a new 2 mL centrifuge tube for concentration and drying. The sample was redissolved in 200 µL of a 50% acetonitrile solution containing 2-chloro-l-phenylalanine at a concentration of 4 parts per million (ppm). The supernatant was filtered through a 0.22 μm membrane and subsequently transferred to a detection vial for LC–MS/MS analysis [[60]16]. LC–MS/MS detection Liquid chromatography (LC) analysis was conducted using a Vanquish ultra-high performance liquid chromatography system paired with quadrupole time-of-flight mass spectrometry (MS) from Thermo Fisher Scientific Inc. Chromatographic separation was performed using an ACQUITY Ultra Performance LC (UPLC)® HSS T3 column (Waters Corporation, Milford, MA, USA), which was maintained at a temperature of 40 °C. The flow rate was established at 0.3 mL/min, with an injection volume of 2 μL. Detection of metabolites was performed using an Orbitrap Exploris 120 high-resolution mass spectrometer (Thermo Fisher Scientific Inc.) equipped with an electrospray ionization source. MS1 and MS/MS data were obtained concurrently in Full MS-ddMS2 mode, which is characterized by data-dependent MS/MS [[61]17]. Analysis of metabolomic data Metabolites were identified through the comparison of accurate mass and MS/MS data with various databases, including HMDB, MassBank, KEGG, LipidMaps, mzCloud, and a metabolite database created by Panomix Biomedical Tech Co., Ltd. (Suzhou, China). The molecular weight of metabolites was assessed based on the m/z (mass-to-charge ratio) of parent ions in the mass spectrometry data. The molecular formula was predicted using ppm and adduct ion data, subsequently matched with the database. Biomarker metabolites were selected based on P-value, variable importance in projection (VIP) from orthogonal projections to latent structures-discriminant analysis (OPLS-DA), and fold change (FC). Metabolites with P-value < 0.05 and VIP > 1 were considered significantly differentially expressed. Pathway enrichment analysis was performed using the hypergeometric distribution method to analyze functional pathways and metabolite topologies. Identified metabolites were mapped to KEGG pathways for biological interpretation, and the results were visualized using the KEGG Mapper tool. Statistical analysis All data, except for RNA-seq and metabolomic data, were analyzed using a t-test with SPSS 22.0 statistical software. Spearman correlation analysis was performed to examine the relationship between L value and melanin content. It was also conducted to assess the relationship between melanin content and the expression of DEGs. Results are presented as mean ± SD (standard deviation), with P < 0.05 considered statistically significant. The network path diagram was generated using Figdraw software ([62]https://www.figdraw.com/static/index.html). Quantitative polymerase chain reaction (qPCR) of RNA-seq data Four DEGs were chosen at random for qPCR gene expression investigation in order to confirm the accuracy of the transcriptome data. The primers listed in Table S[63]1 were synthesized by BGI Genomics Co., Ltd., located in Beijing, China. Gene expression analysis for each sample was conducted in replicate using qPCR. The RNA samples utilized for RNAseq analysis were reverse transcribed into cDNA with a cDNA Synthesis kit (Vazyme Biotech Co., Ltd., Nanjing, China) in accordance with the manufacturer's protocol. The qPCR reaction system and thermal cycling parameters used were as instructed by the manufacturer of the SYBR qPCR Master Mix (Vazyme Biotech Co., Ltd.). Gene expression was calculated using the 2^−ΔΔCt method, using the 18S rRNA gene as an internal control [[64]18]. Data were analyzed using the GraphPad Prism (v9.5) software. Results Comparison and correlation analysis of breast muscle color and melanin content The statistics of meat color traits and melanin content of different black-bone chicken varieties are shown in Table [65]2. Significant differences in L and melanin content were observed between the HB group and the LB group of JL chickens (P < 0.05). Additionally, significant differences in L value and melanin content were also observed between the YJ chicken group and the JL chicken group (P < 0.05). The melanin content of YJ chickens was approximately 2.5 times higher than that of JL chickens. The melanin content in the HB group was approximately 1.33 times higher than that in the LB group. Table 2. Comparative analysis of blackness traits in YJ vs. JL group and HB vs. LB group Groups P-value YJ (n = 20) JL (n = 20) HB (n = 6) LB (n = 6) YJ vs. JL HB vs. LB Live weight before slaughter (g) 1513.55 ± 79.14 2087.05 ± 105.67 2123.67 ± 122.88 2054.83 ± 96.78 < 0.001 0.31 Dressed weight (g) 1374.96 ± 68.65 1913.00 ± 96.92 1947.58 ± 133.41 1887.92 ± 88.52 < 0.001 0.33 breast muscle weight (g) 187.09 ± 18.99 324.50 ± 30.69 322.67 ± 30.56 315.00 ± 14.68 < 0.001 0.59 L 38.76 ± 1.94 48.03 ± 3.73 46.73 ± 3.86 48.74 ± 3.64 < 0.001 0.021 Melanin content (mg/g) 8.84 ± 2.87 3.22 ± 0.56 3.67 ± 0.22 2.75 ± 0.44 < 0.001 < 0.001 [66]Open in a new tab L Lightness YJ Yanjin black-bone chicken group, JL Jinling Partridge black-bone group, HB High blackness group, LB Low blackeness group Also, the L value was significantly negatively correlated with melanin content (P < 0.01), with a correlation coefficient of −0.770 (Table S[67]2). Using L as the horizontal coordinate and melanin content (μg/g) as the vertical coordinate, the relationship between melanin content and blackness was determined. The regression equation is as follows: y = 26.94–0.49x, R^2 = 0.504 (Figure S1). Sequencing results and DEGs Forty cDNA libraries were constructed using total RNA extracted from chicken breast, followed by high-throughput RNA-seq detection. Each library yielded an average of 40,178,153.6 raw reads. Following the removal of low-quality reads and adapter sequences, clean data ranging from 31,963,842 to 53,750,748 reads per library were obtained. The Q20 content exceeded 96.44%, with around 84.58% to 90.47% of clean reads successfully mapped to the reference genome for each library (Table S[68]3). The results demonstrated that the sequencing data were high quality, making them appropriate for further study. A total of 4,183 DEGs were identified between YJ chickens vs. JL chickens, including 2,137 upregulated and 2,046 downregulated genes (Fig. [69]1A). Among them, a total of 379 DEGs, comprising 279 upregulated and 100 downregulated genes, were detected in HB vs. LB (Fig. [70]1B). In addition, 81 co-expressed DEGs were identified from two comparisons (Fig. [71]1C). Fig. 1. [72]Fig. 1 [73]Open in a new tab Volcano plot and Venn diagram of the DEGs. A Volcano plot of DEGs between YJ chicken vs. JL chicken groups (B) Volcano plot of DEGs between HB vs. LB groups (C) Venn diagram of the co-expressed DEGs in two comparisons (YJ chicken vs. JL chicken groups and HB vs. LB groups). Red dots indicate upregulated genes; blue dots indicate downregulated genes; Grey dots indicate DEGs that are not significant GO term enrichment analysis GO term enrichment analysis was conducted using 81 DEGs, resulting in a list of the top 20 most significantly enriched terms. The findings indicated that these DEGs were significantly enriched in 345 GO terms (Table S[74]4). Specifically, they were enriched to positive regulation of lipid biosynthetic process, lipid transport across blood brain barrier, fatty acid transport, energy homeostasis, etc. (Fig. [75]2A). According to the secondary classification of GO entries, more DEGs were significantly enriched in ‘biological process’, and ‘molecular function’ (Fig. [76]2B). As shown in Table [77]3, we focused on the pathways involved in melanin synthesis and metabolism, including melanocyte migration (P = 0.005), melanocyte adhesion (P = 0.005), retinal pigment epithelium development (P = 0.018), positive regulation of melanin biosynthetic process (P = 0.023), and regulation of melanin biosynthetic process (P = 0.044). We identified two upregulated genes (TYRP1, KIT) and one downregulated gene (MFSD2A) involved in melanin-related pathways that may affect blackness traits in black-bone chickens. Fig. 2. [78]Fig. 2 [79]Open in a new tab The Gene Ontology (GO) terms in the two comparisons. A The 20 most significantly enriched GO pathway in the two comparisons; B GO term functional enrichment analysis of DEGs in the two comparisons Table 3. GO terms related to melanin synthesis Category GO ID Description Gene name P-value BP GO:0097324 melanocyte migration UP:KIT 0.005 BP GO:0097326 melanocyte adhesion UP:KIT 0.005 BP GO:0003406 retinal pigment epithelium development DOWN:MFSD2A 0.018 BP GO:0048023 positive regulation of melanin biosynthetic process UP:TYRP1 0.023 BP GO:0048021 regulation of melanin biosynthetic process UP:TYRP1 0.044 [80]Open in a new tab BP Biological process KEGG pathway enrichment analysis of DEGs KEGG pathway enrichment analysis was conducted to identify the primary biochemical and signaling pathways associated with the 4,183 DEGs between YJ and JL chickens (Table S[81]5) and the 379 DEGs between HB and LB (Table S[82]6). The significantly enriched KEGG pathways between YJ chickens vs. JL chickens, which are shown in Fig. [83]3A, include Metabolic pathways (P = 2.36E-07), Oxidative phosphorylation (P = 7.15E-06), mTOR signaling pathway (P = 3.81E-05), Fanconi anemia pathway (P = 6.00E-05), pyruvate metabolism (P = 1.72E-04), autophagy—animal (P = 4.56E-04), etc. In the YJ chicken vs. JL chicken group, 30 DEGs were enriched in pathways related to melanin biosynthesis, including ENSGALG00000028530, MAP2K2, CAMK2D, FZD4, MAP2K1, PLCB4, WNT11, TYRP1, FZD7, KIT, WNT9A, EDNRB, CAMK2B, TCF7L1, WNT2B, GNAQ, KRAS, EP300, CALM2, PRKCB, FZD2, EDN1, GNAO1, EDNRB2, GNAI1, ADCY6, WNT4, CREBBP, FZD1, GSK3B. Figure [84]3B shows The significantly enriched KEGG pathways between HB vs. LB, which are shown in Fig. [85]3B, include PD-L1 expression and PD-1 checkpoint pathway in cancer (P = 2.42E-05), Metabolism of xenobiotics by cytochrome P450 (P = 9.66E-04), Melanogenesis (P = 1.09E-03), etc. In the HB vs. LB group, 6 DEGs (TCF7, TYRP1, KIT, PRKCB, EDNRB2, and ADCY7) were enriched in the melanin synthesis pathway. Overlapping the DEGs from both groups revealed 4 genes (TYRP1, KIT, PRKCB, and EDNRB2) associated with melanin synthesis pathways. In addition, 81 co-expressed DEGs were found to be enriched by KEGG pathway enrichment analysis (Table S[86]7), and these 4 genes (TYRP1, KIT, PRKCB, and EDNRB2) were significantly enriched in the melanin synthesis pathway (Fig. [87]3C). Fig. 3. [88]Fig. 3 [89]Open in a new tab KEGG pathway enrichment in the two comparisons. A The 25 most significantly enriched KEGG pathways between the YJ chicken vs. JL chicken groups; B The 25 most significantly enriched KEGG pathways between the HB vs. LB groups; C The 25 most significantly enriched KEGG pathways of the co-expressed DEGs in the two comparisons Metabolome data analysis and differential metabolites (DMs) To understand the changes in the metabolome of black-bone chickens with different melanin content, UHPLC-Q-TOF MS was used to perform a non-targeted metabolome analysis of black-bone chicken breast muscle. We identified a total of 1,390 differential metabolites (DMs), including 984 positive ion and 406 negative ion. Between the YJ chicken vs. JL chicken groups, there were 399 DMs (271 upregulated and 128 downregulated) (Fig. [90]4A) and between the HB vs. LB groups there were 62 DMs (39 upregulated and 23 downregulated) (Fig. [91]4B). The two groups had 16 significant DMs in common (Fig. [92]4C). The OPLS-DA of the metabolites in each comparison group revealed that there were some differences in the overall metabolic profile of pectoralis muscle in each comparison group (Figure S2). Fig. 4. [93]Fig. 4 [94]Open in a new tab Volcano plot and Venn diagram of the DMs. A Volcano plot of DMs between the YJ chicken vs. JL chicken groups; B Volcano plot of DMs between the high-blackness (HB) vs. the low-blackness (LB) groups in JL chicken; C Venn diagram of the common DMs in two comparisons (YJ chicken vs. JL chicken groups and HB vs. LB groups). Red dots indicate upregulated DMs; blue dots indicate downregulated DMs;Grey dots indicate DMs that are not significant KEGG pathway enrichment analysis of DMs The molecular function of DMs in black-bone chickens was further evaluated by mapping all the DMs in each group into the KEGG database. Between the YJ chicken vs. JL chicken groups, these DMs were mainly enriched in the following metabolic pathways (Table S[95]8): Thiamine metabolism, mTOR signaling pathway, Phenylalanine, tyrosine and tryptophan biosynthesis (Fig. [96]5A). Between the HB vs. LB groups, DMs were predominantly enriched in the metabolic pathways (Table S[97]9) such as Folate biosynthesis, Pantothenate and CoA biosynthesis, Galactose metabolism, Valine, leucine and isoleucine degradation, Steroid biosynthesis (Fig. [98]5B). Two of the 16 common DMs were enriched in the following KEGG metabolic pathway (Table S[99]10), tetrahydrobiopterin (BH[4]) was enriched in Folate biosynthesis pathway, N-acetylneuraminic acid was enriched in Amino sugar and nucleotide sugar metabolism pathway (Fig. [100]5C). Fig. 5. [101]Fig. 5 [102]Open in a new tab KEGG pathway enrichment in two comparisons. A KEGG pathway enrichment analysis of DMs between the YJ chicken vs. JL chicken groups. B KEGG pathway enrichment analysis of DMs between the HB vs. LB groups Correlation analysis of melanin content and the expression of DEGs, and qPCR validation The genes EDNRB2, TYRP1, and KIT were positively correlated with the melanin content, with correlation coefficients of 0.77, 0.63, and 0.67, respectively, whereas PRKCB was negatively correlated with the melanin content, with a correlation coefficient of −0.21 (Table [103]S11). The RNA-seq data were validated using qPCR to analyze the mRNA levels of 4 DEGs (Figure S3), including 1 downregulated gene (PRKCB) and 3 upregulated genes (EDNRB2, KIT, and TYRP1). The gene expression patterns identified through qRT-PCR analysis aligned with the RNA-Seq results, thereby validating the reliability of the transcriptome findings. Discussion The blackness trait of black-bone chickens, an economically important characteristic, is influenced by various factors, including environmental, nutritional, and genetic [[104]19–[105]21]. Under identical feeding conditions, the body weight of YJ chickens at 60 days was significantly lower than that of JL chickens. This difference is attributed to the hybrid nature of JL chickens, in which the male parent line includes fast-growing large recessive white feather broilers, leading to a substantial increase in body weight. In addition, the study indicated that variations in blackness did not affect the growth efficiency of black-bone chickens, implying that selective breeding for increased blackness does not compromise the initial economic value of the trait. [[106]22]. JL chicken is a three-line hybrid black-bone chicken. The melanin variability of JL chicken is essentially the result of the combined effects of dynamic interaction of dominant-recessive alleles, epigenetic reprogramming and developmental plasticity during the three-line hybridization process. This hybrid architecture not only disrupted the genetic balance of the parental strain, but ultimately led to the destabilization of the regulatory network of the melanin synthesis pathway [[107]23]. In this study, we established the relationship between the L value and melanin content, which can indirectly infer its melanin content through the L value, so as to help producers evaluate the appearance quality of products according to color, especially consumers'demand for the blackness characteristics of black-bone chickens. The L value, being more readily measurable during conventional feeding, may function as a practical criterion for evaluating the blackness of black-bone chickens [[108]24–[109]26]. Y = 26.94–0.49 indicate that the lightness value (L*) is significantly negatively correlated with the melanin content (slope: −0.49, p < 0.001), that is, the lower the lightness value, the higher the melanin content. R^2 = 0.504 indicates that the L can explain approximately 50.4% of the variation in melanin content. It is suggested that there are other regulatory factors (such as melanin type, distribution location or non-pigment components) jointly affecting the color of the breast muscles. Transcriptome sequencing analysis was conducted on breast muscle tissues from black-bone chickens, and found 4,183 and 879 DEGs between YJ chicken vs. JL chicken groups and HB vs. LB groups, respectively. However, only 81 co-expressed DEGs were identified across the two comparisons, possibly due to the variation between breeds. Among these DEGs, four candidate genes (TYRP1, EDNRB2, KIT, and PRKCB) were identified as enriched in the melanin synthesis pathway. Our experimental results indicate that TYRP1 expression in the YJ chicken group was 1.85 times greater than in the JL chicken group, while expression in the HB group was 3.48 times greater than in the LB group. The considerable variation in melanin content observed in JL chickens may be attributed to their hybrid nature, as these chickens have not undergone multiple generations of selective breeding, leading to significant variability in melanin content. Tyrosinase-related protein 1 (TYRP1) is a transmembrane glycoprotein belonging to the tyrosinase-related protein (TRP) family. It is synthesized in the endoplasmic reticulum and subsequently transported to the interior of melanocytes. It is crucial in the melanin biosynthetic pathway, primarily facilitating the catalytic oxidation of DHICA to produce 5,6-dihydroxyindoquinone [[110]27]. Studies have also measured the expression levels of the TYRP1 gene in black and gray horses, finding that TYRP1 expression in black horses was 6.54 times higher than that in gray horses [[111]28]. Our study also found that the expression of endothelin receptor subtype B2 (EDNRB2) was positively correlated with melanin content (r = 0.77, p < 0.001). Numerous studies have shown that Normal high expression of EDNRB2 promotes the production of melanin, but abnormal EDNRB2 expression affects pigmentation primarily by inhibiting the migration of melanocytes [[112]29–[113]31]. Additionally, binding of EDN1 to EDNRB mediates melanocyte proliferation, melanin production, and migration [[114]32] and activates the hydrolysis of polyphosphorylated inositol, which results in the accumulation of intracellular Ca^2+ and activation of PKC. Activated PKC directly phosphorylates RAF1, which leads to the activation of the MAPK pathway [[115]33, [116]34]. Analysis of the signaling pathways enriched by co-expressed DEGs in the two comparison groups revealed that the KIT and PRKCB genes were enriched in the MAPK/ERK signaling pathway. In this study, PRKCB was identified as a downregulated gene, and it is hypothesized that it may inhibit TYR activity, leading to reduced melanin production. PRKCB belongs to the PRKC family of serine and threonine-specific protein kinases, which participate in multiple intracellular signaling pathways, such as NF-κB, MAPK, and PI3K/Akt [[117]35]. In this study, PRKCB is suggested to be implicated in regulating biochemical processes such as pigmentation through these pathways [[118]36]. Additionally, in this study, the KIT gene was significantly enriched in important pathways such as melanin synthesis and MAPK/ERK. The KIT signaling pathway directly influences melanin production by regulating the expression and activity of tyrosinase (TYR) and other melanin synthesis enzymes. The MAPK/ERK pathway plays a crucial regulatory role in melanin production. Moreover, KIT signaling is essential for maintaining normal melanocyte function and pigment distribution [[119]37]. Also, loss of KIT signaling results in abnormal pigmentation, which manifests as depigmentation disorders, such as vitiligo or other pigmentary diseases [[120]38]. In the comparison between the YJ chicken vs. JL chicken groups, tyrosine was identified as a DM enriched in the melanin synthesis pathway. However, in the comparison between the HB vs. LB groups, no DMs were enriched in the melanin synthesis pathway, including L-tyrosine, which is an essential amino acid that serves as a precursor in melanin synthesis. Melanocytes convert L-tyrosine into dihydroxyphenylalanine (DOPA) and DOPA-quinone via tyrosinase, which is the initial and critical steps in melanin production [[121]39]. L-tyrosine is converted to melanin through a series of chemical reactions catalyzed by tyrosinase. Tyrosinase plays a crucial catalytic role in this process, regulating both the rate and quantity of melanin production. Melanin production significantly influences the color of the skin, hair, and eyes and serves as a natural protective mechanism against ultraviolet (UV) radiation damage [[122]40]. Sixteen common DMs were identified between the two comparisons, among which BH[4], a metabolite that promotes melanin synthesis. BH4 plays a crucial role in melanin production by acting as a cofactor for tyrosinase. Tyrosinase is an essential enzyme in melanin synthesis, catalyzing the conversion of L-tyrosine to DOPA, which serves as the precursor for melanin. By acting as an electron donor during the tyrosinase-catalyzed reaction, BH[4] helps regulate the reaction rate and enzyme activity. The mechanism for the de novo biosynthesis and recycling of BH4 in the regulation of L-tyrosine production by phenylalanine hydroxylase has been documented in prior studies [[123]41]. L-tyrosine is the substrate for melanin biosynthesis by melanocytes. In vitiligo, it is proposed that decreased activity of 4a-hydroxy-BH[4] dehydratase results in the accumulation of 7-BH4 in the epidermis, thus leading to the inhibition of phenylalanine hydroxylase. Phenylalanine accumulates and, through the feedback regulator P35, induces GTP cyclohydrolase 1, which represents the rate-limiting step in BH4 synthesis, leading to increased production of 7-BH[4] and subsequent depigmentation [[124]42]. Therefore, BH[4] is essential for maintaining normal melanin synthesis, with its concentration and availability directly affecting the rate and quantity of melanin production (Fig. [125]6). Fig. 6. [126]Fig. 6 [127]Open in a new tab Pathway map of melanin regulation by identified candidate DEGs (TYRP1, EDNRB2, KIT, and PRKCB) and marker DMs (BH[4], and N-acetylneuraminic acid) In this study, N-acetylneuraminic acid was identified as a downregulated metabolite, which functions to inhibit melanin production. It was reported that free N-acetylneuramic acid, which was fully digested from the edible bird’s nest (EBN) of different colors, significantly inhibited tyrosinase activity [[128]43]. N-acetylneuraminic acid was added to the culture medium of B16 mouse melanoma cells and A375 human melanoma cells for a period of time, and the measured melanin concentration decreased significantly [[129]44]. The inhibitory effect of N-acetylneuramic acid on the apparent intensity of skin color was confirmed in a three-dimensional human skin model [[130]44]. The skin lightening efficiency of N-acetylneuraminic acid indicated a non-competitive inhibition of tyrosinase activity, in which the inhibitor binds exclusively to the enzyme–substrate complex [[131]45]. N-acetylneuraminic acid binds to sites other than the active site of the enzyme, altering its conformation and rendering it less active or ineffective. Non-competitive inhibitors have no direct competition with the substrate, thus increasing substrate concentration does not reverse the inhibitory effect. Therefore, the concentration of tyrosine does not influence the efficiency of N-acetylneuraminic acid in inhibiting melanin synthesis (Fig. [132]6). In this study, BH[4] and N-acetylneuraminic acid were found to jointly influence tyrosinase activity, thereby affecting melanin production. Both compounds occur naturally as influencing factors in black-bone chickens. The influence of these two compounds on melanin synthesis could be further investigated and verified through additional experiments and measurements of tyrosinase activity. Conclusion This study established the relationship between the blackness value and melanin content in YJ chickens and JL chickens. The L value can be used as a criterion for selecting black-bone chicken coloration. Integrated transcriptomics and metabolomics analysis identified a numerous DEGs and DMs. Regarding melanin synthesis, the functional genes TYRP1, KIT, PRKCB, and EDNRB2, along with the candidate marker metabolites BH[4] and N-acetylneuraminic acid, were found to be significantly enriched in the melanin synthesis pathway, thereby influencing the melanin content in chicken breast muscle. Overall, these findings provide valuable information and additional evidence regarding the marker metabolites of black-bone chickens, contributing to a deeper understanding of the biological mechanisms underlying melanin synthesis in the breast muscles of black-bone chickens. Supplementary Information [133]12864_2025_11803_MOESM1_ESM.docx^ (11.8KB, docx) Supplementary Material 1. Table S1 Primer pairs used for quantitative real-time polymerase chain reaction (qPCR). [134]12864_2025_11803_MOESM2_ESM.docx^ (16.7KB, docx) Supplementary Material 2. Table S2 L value and melanin content in the YJ chickens (n=30) and JL chickens (n=30). [135]12864_2025_11803_MOESM3_ESM.docx^ (22.9KB, docx) Supplementary Material 3. Table S3 Quality control of mRNA sequencing data. [136]12864_2025_11803_MOESM4_ESM.xlsx^ (30.3KB, xlsx) Supplementary Material 4. Table S4 Gene ontology (GO) terms of 81 co-expressed DEGs between the YJ chicken vs. JL chicken groups and HB vs. LB groups. [137]12864_2025_11803_MOESM5_ESM.xlsx^ (23.2KB, xlsx) Supplementary Material 5. Table S5 KEGG pathways of DEGs between YJ chicken vs. JL chicken groups. [138]12864_2025_11803_MOESM6_ESM.xlsx^ (12.7KB, xlsx) Supplementary Material 6. Table S6 KEGG pathways of DEGs between HB vs. LB groups. [139]12864_2025_11803_MOESM7_ESM.xlsx^ (10.6KB, xlsx) Supplementary Material 7. Table S7 KEGG pathways of 81 co-expressed DEGs between the YJ chicken vs. JL chicken groups and HB vs. LB groups. [140]12864_2025_11803_MOESM8_ESM.xlsx^ (15.4KB, xlsx) Supplementary Material 8. Table S8 KEGG pathways of DMs between the YJ chicken vs. JL chicken groups. [141]12864_2025_11803_MOESM9_ESM.xlsx^ (8.1KB, xlsx) Supplementary Material 9. Table S9 KEGG pathways of DMs between the HB vs. LB groups. [142]12864_2025_11803_MOESM10_ESM.xlsx^ (6.6KB, xlsx) Supplementary Material 10. Table S10 KEGG pathways of DMs between the YJ chicken vs. JL chicken groups and HB vs. LB groups. [143]12864_2025_11803_MOESM11_ESM.txt^ (346B, txt) Supplementary Material 11. Table S11 Correlation analysis between 4 DEGs and melanin content. [144]12864_2025_11803_MOESM12_ESM.docx^ (11.8KB, docx) Supplementary Material 12. Table S12 Specific method for determination of melanin content. [145]12864_2025_11803_MOESM13_ESM.pdf^ (30.7KB, pdf) Supplementary Material 13. Figure S1 The linear relationship of the L value and melanin content of breast muscle. [146]12864_2025_11803_MOESM14_ESM.pdf^ (303.4KB, pdf) Supplementary Material 14. Figure S2 Plot of OPLS-DA scores of metabolite between the YJ chicken vs. JL chicken groups, and HB vs. LB groups. (A) Plot of OPLS-DA scores of positive metabolites between the YJ chicken vs. JL chicken groups; (B) Plot of OPLS-DA scores of negative metabolite between the YJ chicken vs. JL chicken groups; (C) Plot OPLS-DA scores of positive metabolites between the HB vs. LB groups; (D) Plot of OPLS-DA scores of negative metabolite between the HB vs. LB groups. [147]12864_2025_11803_MOESM15_ESM.pdf^ (151.6KB, pdf) Supplementary Material 15. Figure S3 Validation of DEGs by qPCR analysis. Acknowledgements