RNA sequencing identifies key genes involved in intramuscular fat deposition in chickens at different developmental stages.

BACKGROUND: Intramuscular fat (IMF) is an important factor in meat quality, and triglyceride (TG) and Phospholipids (PLIP), as the main components of IMF, are of great significance to the improvement of meat quality. RESULTS: In this study, we used 30 RNA sequences generated from the transcriptome of chicken breast muscle tissues at different developmental stages to construct a gene expression matrix to map RNA sequence reads to the chicken genome and identify the transcript of origin. We used weighted gene co-expression network analysis (WGCNA) and identified 27 co-expression modules, 10 of which were related to TG and PLIP. We identified 150 highly-connected hub genes related to TG and PLIP, respectively, which were found to be mainly enriched in the adipocytokine signaling pathway, MAPK signaling pathway, mTOR signaling pathway, FoxO signaling pathway, and TGF-beta signaling pathway. Additionally, using the BioMart database, we identified 134 and 145 candidate genes related to fat development in the TG-related module and PLIP-related module, respectively. Among them, RPS6KB1, BRCA1, CDK1, RPS3, PPARGC1A, ACSL1, NDUFAB1, NDUFA9, ATP5B and PRKAG2 were identified as candidate genes related to fat development and highly-connected hub genes in the module, suggesting that these ten genes may be important candidate genes affecting IMF deposition. CONCLUSIONS: RPS6KB1, BRCA1, CDK1, RPS3, PPARGC1A, ACSL1, NDUFAB1, NDUFA9, ATP5B and PRKAG2 may be important candidate genes affecting IMF deposition. The purpose of this study was to identify the co-expressed gene modules related to chicken IMF deposition using WGCNA and determine key genes related to IMF deposition, so as to lay a foundation for further research on the molecular regulation mechanism underlying chicken fat deposition.

Estimates of genomic inbreeding and identification of candidate regions in Beijing-You chicken populations.

Runs of homozygosity (ROHs) has become an effective method for analysing inbreeding in livestock populations. Moreover, ROHs is well-suited to detect signatures of selection via ROH islands. This study aimed to investigate the occurrence and distribution of ROHs, compare the genomic inbreeding coefficients and identify the genomic regions with high ROH frequencies in different Beijing-You chicken (BY) populations, including a random conservation population (BY_R), a pedigree conservation population (BY_P), and a commercial population obtained from the market (BY_C). Among them, BY_R in 2010 and 2019 were BY_R1 and BY_R2 respectively. A total of 27 916 ROHs were identified. The average number of ROHs per individual across the three BY populations ranged from 213 (BY_P) to 161 (BY_C), and the average length of ROHs ranged from 0.432 Mb (BY_R2) to 0.451 Mb (BY_P). The highest inbreeding coefficient calculated based on ROHs (FROH ) was 0.1 in BY_P, whereas the lowest FROH was 0.0743 in BY_C. In addition, the inbreeding coefficient of BY_R2 (FROH  = 0.0798) was higher than that of BY_R1 (FROH  = 0.0579). Furthermore, the highest proportion of long ROH fragments (>4 Mb) was observed in BY_P and BY_C. This study showed the top 10 ROH islands of each population, and these ROH islands harboured 53 genes, some of which were related to limb development, body size and immune response. These findings contribute to the understanding of genetic diversity and population demography, and might help improve breeding and conservation strategies for BY populations.

SPOP promotes ubiquitination and degradation of MyD88 to suppress the innate immune response.

As a canonical adaptor for the Toll-like receptor (TLR) family, myeloid differentiation primary response protein 88 (MyD88) has crucial roles in host defense against infection by microbial pathogens, and its dysregulation might induce autoimmune diseases. Here, we demonstrate that the chicken Cullin 3-based ubiquitin ligase adaptor Speckle-type BTB-POZ protein (chSPOP) recognizes the intermediate domain of chicken MyD88 (chMyD88) and degrades it through the proteasome pathway. Knockdown or genetic ablation of chSPOP leads to aberrant elevation of chMyD88 protein. Through this interaction, chSPOP negatively regulates NF-κB pathway activity and thus the production of IL-1ß upon LPS challenge in chicken macrophages. Furthermore, Spop-deficient mice are more susceptible to infection with Salmonella typhimurium. Collectively, these findings demonstrate MyD88 as a bona fide substrate of SPOP and uncover a mechanism by which SPOP regulates MyD88 abundance and disease susceptibility.

Comparison of genomic prediction methods for residual feed intake in broilers.

Residual feed intake (RFI) is a measure of the feed efficiency of animals. Previous studies have identified SNPs associated with RFI. The objective of this study was to compare the GBLUP model with the GA-BLUP model including previously identified associated SNPs. The nine associated SNPs were obtained from the genome-wide association study on a discovery population as preselection information. These models were analysed using ASREML software using a 5-fold cross-validation method on a validation population. With the genetic architecture (GA) matrix used, which was conducted with the nine RFI-associated SNPs, the prediction accuracy of RFI was improved compared with the original GBLUP model. The calculated optimal ω was 0.981 for RFI, which is in line with the optimal range from 0.9 to 1.0 in the gradient test. The prediction accuracy increased by 2% in the GA-BLUP model with ω being 0.981 compared with the GBLUP model. In conclusion, the GA-BLUP with the nine RFI-associated SNPs and an optimal ω can improve the prediction accuracy for a specific trait compared with GBLUP.

Integrated analysis of the methylome and transcriptome of chickens with fatty liver hemorrhagic syndrome.

BACKGROUND: DNA methylation, a biochemical modification of cytosine, has an important role in lipid metabolism. Fatty liver hemorrhagic syndrome (FLHS) is a serious disease and is tightly linked to lipid homeostasis. Herein, we compared the methylome and transcriptome of chickens with and without FLHS. RESULTS: We found genome-wide dysregulated DNA methylation pattern in which regions up- and down-stream of gene body were hypo-methylated in chickens with FLHS. A total of 4155 differentially methylated genes and 1389 differentially expressed genes were identified. Genes were focused when a negative relationship between mRNA expression and DNA methylation in promoter and gene body were detected. Based on pathway enrichment analysis, we found expression of genes related to lipogenesis and oxygenolysis (e.g., PPAR signaling pathway, fatty acid biosynthesis, and fatty acid elongation) to be up-regulated with associated down-regulated DNA methylation. In contrast, genes related to cellular junction and communication pathways (e.g., vascular smooth muscle contraction, phosphatidylinositol signaling system, and gap junction) were inhibited and with associated up-regulation of DNA methylation. CONCLUSIONS: In the current study, we provide a genome-wide scale landscape of DNA methylation and gene expression. The hepatic hypo-methylation feature has been identified with FLHS chickens. By integrated analysis, the results strongly suggest that increased lipid accumulation and hepatocyte rupture are central pathways that are regulated by DNA methylation in chickens with FLHS.

Identification of QTL regions and candidate genes for growth and feed efficiency in broilers.

BACKGROUND: Feed accounts for about 70% of the total cost of poultry meat production. Residual feed intake (RFI) has become the preferred measure of feed efficiency because it is phenotypically independent of growth rate and body weight. In this study, our aim was to estimate genetic parameters and identify quantitative trait loci (QTL) for feed efficiency in 3314 purebred broilers using a genome-wide association study. Broilers were genotyped using a custom 55 K single nucleotide polymorphism (SNP) array. RESULTS: Estimates of genomic heritability for seven growth and feed efficiency traits, including body weight at 28 days of age (BW28), BW42, average daily feed intake (ADFI), RFI, and RFI adjusted for weight of abdominal fat (RFIa), ranged from 0.12 to 0.26. Eleven genome-wide significant SNPs and 15 suggestively significant SNPs were detected, of which 19 clustered around two genomic regions. A region on chromosome 16 (2.34-2.66 Mb) was associated with both BW28 and BW42, and the most significant SNP in this region, AX_101003762, accounted for 7.6% of the genetic variance of BW28. The other region, on chromosome 1 (91.27-92.43 Mb) was associated with RFI and ADFI, and contains the NSUN3 and EPHA6 as candidate genes. The most significant SNP in this region, AX_172588157, accounted for 4.4% of the genetic variance of RFI. In addition, a genomic region containing the gene AGK on chromosome 1 was found to be associated with RFIa. The NSUN3 and AGK genes were found to be differentially expressed in breast muscle, thigh muscle, and abdominal fat between male broilers with high and low RFI. CONCLUSIONS: We identified QTL regions for BW28 and BW42 (spanning 0.32 Mb) and RFI (spanning 1.16 Mb). The NSUN3, EPHA6, and AGK were identified as the most likely candidate genes for these QTL. These genes are involved in mitochondrial function and behavioral regulation. These results contribute to the identification of candidate genes and variants for growth and feed efficiency in poultry.

Identification of diverse cell populations in skeletal muscles and biomarkers for intramuscular fat of chicken by single-cell RNA sequencing.

BACKGROUND: The development of skeletal muscle is closely related to the efficiency of meat production and meat quality. Chicken skeletal muscle development depends on myogenesis and adipogenesis and occurs in two phases-hyperplasia and hypertrophy. However, cell profiles corresponding to the two-phase muscle development have yet to be determined. Single-cell RNA-sequencing (scRNA-seq) can elucidate the cell subpopulations in tissue and capture the gene expression of individual cells, which can provide new insights into the myogenesis and intramuscular adipogenesis. RESULTS: Ten cell clusters at the post-hatching developmental stage at Day 5 and seven cell clusters at the late developmental stage at Day 100 were identified in chicken breast muscles by scRNA-seq. Five myocyte-related clusters and two adipocyte clusters were identified at Day 5, and one myocyte cluster and one adipocyte cluster were identified at Day 100. The pattern of cell clustering varied between the two stages. The cell clusters showed clear boundaries at the terminal differentiation stage at Day 100; by contrast, cell differentiation was not complete at Day 5. APOA1 and COL1A1 were selected from up-regulated genes in the adipocyte cluster and found to be co-expressed with the ADIPOQ adipocyte marker gene in breast muscles by RNA in situ hybridization. CONCLUSIONS: This study is the first to describe the heterogeneity of chicken skeletal muscle at two developmental stages. The genes APOA1 and COL1A1 were identified as biomarkers for chicken intramuscular fat cells.

Genome-Wide Detection of Key Genes and Epigenetic Markers for Chicken Fatty Liver.

Chickens are one of the most important sources of meat worldwide, and the occurrence of fatty liver syndrome (FLS) is closely related to production efficiency. However, the potential mechanism of FLS remains poorly understood. An integrated analysis of data from whole-genome bisulfite sequencing and long noncoding RNA (lncRNA) sequencing was conducted. A total of 1177 differentially expressed genes (DEGs) and 1442 differentially methylated genes (DMGs) were found. There were 72% of 83 lipid- and glucose-related genes upregulated; 81% of 150 immune-related genes were downregulated in fatty livers. Part of those genes was within differentially methylated regions (DMRs). Besides, sixty-seven lncRNAs were identified differentially expressed and divided into 13 clusters based on their expression pattern. Some lipid- and glucose-related lncRNAs (e.g., LNC_006756, LNC_012355, and LNC_005024) and immune-related lncRNAs (e.g., LNC_010111, LNC_010862, and LNC_001272) were found through a co-expression network and functional annotation. From the expression and epigenetic profiles, 23 target genes (e.g., HAO1, ABCD3, and BLMH) were found to be hub genes that were regulated by both methylation and lncRNAs. We have provided comprehensive epigenetic and transcriptomic profiles on FLS in chicken, and the identification of key genes and epigenetic markers will expand our understanding of the molecular mechanism of chicken FLS.

A new chicken 55K SNP genotyping array.

BACKGROUND: China has the richest local chicken breeding resources in the world and is the world's second largest producer of meat-type chickens. Development of a moderate-density SNP array for genetic analysis of chickens and breeding of meat-type chickens taking utility of those resources is urgently needed for conventional farms, breeding industry, and research areas. RESULTS: Eight representative local breeds or commercial broiler lines with 3 pools of 48 individuals within each breed/line were sequenced and supplied the major SNPs resource. There were 7.09 million - 9.41 million SNPs detected in each breed/line. After filtering using multiple criteria such as preferred incorporation of trait-related SNPs and uniformity of distribution across the genome, 52.18 K SNPs were selected in the final array. It consists of: (i) 19.22 K SNPs from the genomes of yellow-feathered, cyan-shank partridge and white-feathered chickens; (ii) 5.98 K SNPs related to economic traits from the Illumina 60 K SNP Bead Chip, which were found as significant associated SNPs with 15 traits in a Beijing-You crossed Cobb F2 resource population by genome-wide association study analysis; (iii) 7.63 K SNPs from 861 candidate genes of economic traits; (iv) the 0.94 K SNPs related to residual feed intake; and (v) 18.41 K from chicken SNPdb. The polymorphisms of 9 extra local breeds and 3 commercial lines were examined with this array, and 40 K - 47 K SNPs were polymorphic (with minor allele frequency > 0.05) in those breeds. The MDS result showed that those breeds can be clearly distinguished by this newly developed genotyping array. CONCLUSIONS: We successfully developed a 55K genotyping array by using SNPs segregated from typical local breeds and commercial lines. Compared to the existing Affy 600 K and Illumina 60 K arrays, there were 21,41 K new SNPs included on our Affy 55K array. The results of the 55K genotyping data can therefore be imputed to high-density SNPs genotyping data. The array offers a wide range of potential applications such as genomic selection breeding, GWAS of interested traits, and investigation of diversity of different chicken breeds.

Identification of differentially expressed genes and pathways for intramuscular fat metabolism between breast and thigh tissues of chickens.

BACKGROUND: Intramuscular fat (IMF) is one of the important factors influencing meat quality, however, for chickens, the molecular regulatory mechanisms underlying this trait have not yet been clear. In this study, a systematic identification of differentially expressed genes (DEGs) and molecular regulatory mechanism related to IMF metabolism between Beijing-you chicken breast and thigh at 42 and 90 days of age was performed. RESULTS: IMF contents, Gene Ontology (GO) terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed, The results showed that both IMF contents in breast at 42 and 90 d were significantly lower (P < 0.05 or P < 0.01) than those in thigh. By microarray, 515 common known DEGs and 36 DEGs related to IMF metabolism were identified between the breast and thigh at 42 and 90 d. Compared to thigh, the expression levels of PPARG had significantly down-regulated (P < 0.01) in breast, but the expression levels of RXRA and CEBPB had significantly up-regulated (P < 0.01). However, the expression levels of LPL, FABP4, THRSP, RBP7, LDLR, FABP3, CPT2 and PPARGC1A had significantly down-regulated in breast (P < 0.01), supporting that PPARG and its down-stream genes had the important regulatory function to IMF deposition. In addition, based on of DEGs, KEGG analysis revealed that PPAR signaling pathway and cell junction-related pathways (focal adhesion and ECM-receptor interaction, which play a prominent role in maintaining the integrity of tissues), might contribute to the IMF metabolism in chicken. CONCLUSIONS: Our data had screened the potential candidate genes associated with chicken IMF metabolism, and imply that IMF metabolism in chicken is regulated and mediated not only by related functional genes and PPAR pathway, but also by others involved in cell junctions. These findings establish the groundwork and provide new clues for deciphering the molecular mechanisms underlying IMF deposition in poultry. Further studies at the translational and posttranslational level are now required to validate the genes and pathways identified here.

Intramuscular preadipocytes impede differentiation and promote lipid deposition of muscle satellite cells in chickens.

BACKGROUND: Skeletal muscle satellite cells (MSC) are crucial for postnatal growth and regeneration of skeletal muscle. An interaction exists between MSC and intramuscular preadipocytes (IMPA). This study is the first to investigate the effects of IMPA on MSC in chickens and unveil the molecular mechanisms by transcriptome analysis. RESULTS: Primary MSC and IMPA were isolated from the pectoralis major muscle of 7-day-old chickens. After both cell types reached confluence, MSC were cultured alone or co-cultured with IMPA for 2 or 4 d. MSC treated for 2 d were subjected to RNA-seq. A total of 1653 known differentially expressed genes (DEG) were identified between co-cultured and mono-cultured MSC (|log2 FC| ≥ 1, FDR < 0.01). Based on Gene Ontology analysis, 48 DEG related to muscle development were screened, including the key genes MYOD1, MYOG, PAX7, and TMEM8C. The 44 DEG related to lipid deposition included the key genes CD36, FABP4, ACSBG2, CYP7A1 and PLIN2. Most of the DEG related to muscle development were downregulated in co-cultured MSC, and DEG related to lipid deposition were upregulated. Immunofluorescence of MHC supported IMPA impeding differentiation of MSC, and Oil Red O staining showed concurrent promotion of lipid deposition. Pathway analysis found that several key genes were enriched in JNK/MAPK and PPAR signaling, which may be the key pathways regulating differentiation and lipid deposition in MSC. Additionally, pathways related to cell junctions may also contribute to the effect of IMPA on MSC. CONCLUSIONS: The present study showed that IMPA impeded differentiation of MSC while promoting their lipid deposition. Pathway analysis indicated that IMPA might inhibit differentiation via the JNK/MAPK pathway, and promote lipid deposition via the PPAR pathway. This study supplies insights into the effect of IMPA on MSC, providing new clues on exposing the molecular mechanisms underlying the interplay between skeletal muscle and intramuscular fat in chickens.

Decreased testosterone levels after caponization leads to abdominal fat deposition in chickens.

BACKGROUND: Caponization results in reduced androgen levels, which leads to abdominal fat accumulation in capons. In this study, we sought to understand the molecular mechanisms behind this fat accumulation. RESULTS: Abdominal fat (AF) content increased significantly (P < 0.05) and serum and AF testosterone levels decreased significantly (P < 0.05 or P < 0.01) after caponization. In AF tissue, 90 differentially expressed genes related to lipid metabolism were screened by gene expression profiling in caponized and sham-treated chickens. Among these, six representative genes were significantly up-regulated (APOA1, SCD, FABP7, RXRG, and FADS2) or down-regulated (FABP3) (P < 0.05 or P < 0.01) and were strongly associated with the PPAR pathway. In addition, cell junction pathways were also enriched. In vitro, Fat content was significantly lower in cells treated with testosterone compared with control cells (P < 0.01), and mRNA levels of RXRG, FABP7, and FABP3 changed accordingly, confirming the effect of testosterone on fat deposition. CONCLUSIONS: The results of this study indicate that testosterone reduction likely regulates gene expression through PPAR and cell junction pathways resulting in increased fat accumulation. These results provide increase our understanding of the biological mechanisms by which caponization induces greater fat accumulation.

Genome-Wide Linkage Analysis Identifies Loci for Testicle and Ovary Traits in Chickens.

Development of testes or ovaries is critical to chicken breeders. Understanding the genetic mechanisms influencing the development of the testes and ovaries could enhance selection efforts which target reproductive traits. The linkage analysis was conducted within an F2 population derived from Beijing-You chickens and a commercial broiler line. The results have identified one quantitative trait loci (QTL, designated T1) for bilateral testicular weight (TW) and the percentage of TW to carcass weight, and five QTLs (designated O1-O5) for ovary weight (follicle-free, OW) and the percentage of OW to carcass weight. For the testes traits, QTL T1 is located between 6.55 and 8.56 Mb on GGA13. Especially, the gene gamma-amino butyric acid A receptor, alpha 1 (GABRA1) located near the T1 peak. For ovarian traits, QTL O2 was located at 29.31 Mb on GGA7. G protein-coupled receptor 39 (GPR39) present at the O2 peak was expressed at higher levels within the reproductive tract. It is also involved in the regulation of several reproductive functions. Other QTL peaks and the genes' function in the ovary and testes need to be evaluated. The QTLs and the genes identified in this study could provide valuable information for establishing reproductive traits in chickens, and need further investigation.

Uncovering the embryonic development-related proteome and metabolome signatures in breast muscle and intramuscular fat of fast-and slow-growing chickens.

BACKGROUND: Skeletal muscle development is closely linked to meat production and its quality. This study is the first to quantify the proteomes and metabolomes of breast muscle in two distinct chicken breeds at embryonic day 12 (ED 12), ED 17, post-hatch D 1 and D 14 using mass spectrometry-based approaches. RESULTS: Results found that intramuscular fat (IMF) accumulation increased from ED 17 to D 1 and that was exactly the opposite of when most obvious growth of muscle occurred (ED 12 - ED 17 and D 1 - D 14). For slow-growing Beijing-You chickens, Ingenuity Pathway Analysis of 77-99 differential abundance (DA) proteins and 63-72 metabolites, indicated significant enrichment of molecules and pathways related to protein processing and PPAR signaling. For fast-growing Cobb chickens, analysis of 68-95 DA proteins and 56-59 metabolites demonstrated that molecules and pathways related to ATP production were significantly enriched after ED12. For IMF, several rate-limiting enzymes for beta-oxidation of fatty acid (ACADL, ACAD9, HADHA and HADHB) were identified as candidate biomarkers for IMF deposition in both breeds. CONCLUSIONS: This study found that ED 17 - D 1 was the earliest period for IMF accumulation. Pathways related to protein processing and PPAR signaling were enriched to support high capacity of embryonic IMF accumulation in Beijing-You. Pathways related to ATP production were enriched to support the fast muscle growth in Cobb. The beta-oxidation of fatty acid is identified as the key pathway regulating chicken IMF deposition at early stages.

Identification of Histone Deacetylase 2 as a Functional Gene for Skeletal Muscle Development in Chickens.

A previous genome-wide association study (GWAS) exposed histone deacetylase 2 (HDAC2) as a possible candidate gene for breast muscle weight in chickens. The present research has examined the possible role of HDAC2 in skeletal muscle development in chickens. Gene expression was measured by quantitative polymerase chain reaction in breast and thigh muscles during both embryonic (four ages) and post-hatch (five ages) development and in cultures of primary myoblasts during both proliferation and differentiation. The expression of HDAC2 increased significantly across embryonic days (ED) in breast (ED 14, 16, 18, and 21) and thigh (ED 14 and 18, and ED 14 and 21) muscles suggesting that it possibly plays a role in myoblast hyperplasia in both breast and thigh muscles. Transcript abundance of HDAC2 identified significantly higher in fast growing muscle than slow growing in chickens at d 90 of age. Expression of HDAC2 during myoblast proliferation in vitro declined between 24 h and 48 h when expression of the marker gene paired box 7 (PAX7) increased and cell numbers increased throughout 72 h of culture. During induced differentiation of myoblasts to myotubes, the abundance of HDAC2 and the marker gene myogenic differentiation 1 (MYOD1), both increased significantly. Taken together, it is suggested that HDAC2 is most likely involved in a suppressive fashion in myoblast proliferation and may play a positive role in myoblast differentiation. The present results confirm the suggestion that HDAC2 is a functional gene for pre-hatch and post-hatch (fast growing muscle) development of chicken skeletal muscle.

A genome-wide detection of copy number variation using SNP genotyping arrays in Beijing-You chickens.

Copy number variation (CNV) has been recently examined in many species and is recognized as being a source of genetic variability, especially for disease-related phenotypes. In this study, the PennCNV software, a genome-wide CNV detection system based on the 60 K SNP BeadChip was used on a total sample size of 1,310 Beijing-You chickens (a Chinese local breed). After quality control, 137 high confidence CNVRs covering 27.31 Mb of the chicken genome and corresponding to 2.61 % of the whole chicken genome. Within these regions, 131 known genes or coding sequences were involved. Q-PCR was applied to verify some of the genes related to disease development. Results showed that copy number of genes such as, phosphatidylinositol-5-phosphate 4-kinase II alpha, PHD finger protein 14, RHACD8 (a CD8α- like messenger RNA), MHC B-G, zinc finger protein, sarcosine dehydrogenase and ficolin 2 varied between individual chickens, which also supports the reliability of chip-detection of the CNVs. As one source of genomic variation, CNVs may provide new insight into the relationship between the genome and phenotypic characteristics.

Folate supplementation modifies CCAAT/enhancer-binding protein α methylation to mediate differentiation of preadipocytes in chickens.

Folate, an essential vitamin participating in 1-carbon metabolism leading to a methyl donor function, is a key factor inducing epigenetic changes. This study sought to determine if folate influences the methylation level of cytosine-guanine (CpG) islands in the promoters of critical adipogenic genes in chickens, and how this might affect gene expression and differentiation of preadipocytes in vitro. Preadipocytes were treated with 0 to 16 mg/L of folate during the induction of differentiation, and cell proliferation and lipid accumulation were assessed. The folate supplementation resulted in enhanced cell proliferation and decreased content of lipid per adipocyte at d 6 of differentiation. The effects of folate on relative expression of genes critical for adipocyte differentiation and 1-carbon metabolism were measured by quantitative reverse-transcription PCR. Folate caused a dose-dependent decrease in transcript abundance of peroxisome proliferator-activated receptor γ (PPARγ), CCAAT/enhancer-binding protein α (C/EBPα) gene expression, and the downstream enzyme fatty acid synthase; in contrast, expression of DNA (cytosine-5)-methyltransferase and methylenetetrahydrofolate reductase was obviously upregulated at d 6 of differentiation (P < 0.05). The DNA methylation was examined with the bisulfite sequencing PCR method. Overall CpG methylation in the C/EBPα gene promoter region was 21.8% lower (P < 0.05) and the gene's expression was 2.7-fold higher in the absence of folate, compared with cells treated with 16 mg/L of folate, whereas methylation of the PPARγ promoter was not affected. Overall, the results show that folate increased the proliferation of adipocytes but reduced per-cell lipid accumulation, thereby influencing differentiation; it increased expression of genes involved in 1-carbon metabolism resulting in greater methylation of the C/EBPα promoter during differentiation and decreased that gene's expression, perhaps accounting for decreased expression of PPARγ.

Integrative multiomics analysis identifies key genes regulating intramuscular fat deposition during development.

Intramuscular fat (IMF) content is an important indicator of livestock and poultry meat quality. Enhancing IMF deposition can significantly improve meat quality. Focusing on the core process of IMF deposition, this study used the Jingxing Yellow (JXY) chickens as a model organism and employed multi-omics approaches, including RNA-sequencing (RNA-seq), Whole-genome bisulfite sequencing (WGBS), and metabolomics, to identify the key genes influencing IMF deposition in chickens during development. The results indicated that the contents of triglycerides (TG) and phospholipids (PLIP) exhibited an upward trend. The TG content did not differ significantly between day 1 (D1) and day 7 (D7), but increased significantly after 35 days (D35) of age. The WGBS results revealed that CpG methylation was the predominant methylation type in the breast muscle tissue of JXY chickens. Integrative analysis of RNA-seq and WGBS identified 50 genes, including PLA2G4F, PALMD, PLSCR5, ARHGEF26, LUM, DCN, TNRC6B, CACNA1C, ROBO1, and MBTPS2, whose methylation levels were significantly negatively correlated with their expression levels. In addition, the combined Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially-expressed metabolites (DEM) and differentially-expressed genes (DEG) converged on the glycerophospholipid metabolism pathway, which was significantly enriched in DEGs such as PLA2G4F, PLA2G15, LPIN1, MBOAT2, DGKH, AGPAT2, and CHKA, as well as DEM like glycerophosphocholine and phosphocholine. Notably, PLA2G4F was identified as a DEG by DNA methylation, suggesting that PLA2G4F could be a key candidate gene influencing IMF deposition during chicken development. These findings are expected to provide a solid theoretical foundation for improving meat quality through targeted genetic and epigenetic interventions.

Large-scale genomic and transcriptomic analyses elucidate the genetic basis of high meat yield in chickens.

INTRODUCTION: Investigating the genetic markers and genomic signatures related to chicken meat production by combing multi-omics methods could provide new insights into modern chicken breeding technology systems. OBJECT: Chicken is one of the most efficient and environmentally friendly livestock, especially the fast-growing white-feathered chicken (broiler), which is well known for high meat yield, but the underlying genetic basis is poorly understood. METHOD: We generated whole-genome resequencing of three purebred broilers (n = 748) and six local breeds/lines (n = 114), and sequencing data of twelve chicken breeds (n = 199) were obtained from the NCBI database. Additionally, transcriptome sequencing of six tissues from two chicken breeds (n = 129) at two developmental stages was performed. A genome-wide association study combined with cis-eQTL mapping and the Mendelian randomization was applied. RESULT: We identified > 17 million high-quality SNPs, of which 21.74% were newly identified, based on 21 chicken breeds/lines. A total of 163 protein-coding genes underwent positive selection in purebred broilers, and 83 genes were differentially expressed between purebred broilers and local chickens. Notably, muscle development was proven to be the major difference between purebred broilers and local chickens, or ancestors, based on genomic and transcriptomic evidence from multiple tissues and stages. The MYH1 gene family showed the top selection signatures and muscle-specific expression in purebred broilers. Furthermore, we found that the causal gene SOX6 influenced breast muscle yield and also related to myopathy occurrences. A refined haplotype was provided, which had a significant effect on SOX6 expression and phenotypic changes. CONCLUSION: Our study provides a comprehensive atlas comprising the typical genomic variants and transcriptional characteristics for muscle development and suggests a new regulatory target (SOX6-MYH1s axis) for breast muscle yield and myopathy, which could aid in the development of genome-scale selective breeding aimed at high meat yield in broiler chickens.

The identification of 14 new genes for meat quality traits in chicken using a genome-wide association study.

BACKGROUND: Meat quality is an important economic trait in chickens. To identify loci and genes associated with meat quality traits, we conducted a genome-wide association study (GWAS) of F2 populations derived from a local Chinese breed (Beijing-You chickens) and a commercial fast-growing broiler line (Cobb-Vantress). RESULTS: In the present study, 33 association signals were detected from the compressed mixed linear model (MLM) for 10 meat quality traits: dry matter in breast muscle (DMBr), dry matter in thigh muscle (DMTh), intramuscular fat content in breast muscle (IMFBr), meat color lightness (L*) and yellowness (b*) values, skin color L*, a* (redness) and b* values, abdominal fat weight (AbFW) and AbFW as a percentage of eviscerated weight (AbFP). Relative expressions of candidate genes identified near significant signals were compared using samples of chickens with High and Low phenotypic values. A total of 14 genes associated with IMFBr, meat color L*, AbFW, and AbFP, were differentially expressed between the High and Low phenotypic groups. These genes are, therefore, prospective candidate genes for meat quality traits: protein tyrosine kinase (TYRO3) and microsomal glutathione S-transferase 1 (MGST1) for IMFBr; collagen, type I, alpha 2 (COL1A2) for meat color L*; and RET proto-oncogene (RET), natriuretic peptide B (NPPB) and sterol regulatory element binding transcription factor 1 (SREBF1) for the abdominal fat (AbF) traits. CONCLUSIONS: Based on the association signals and differential expression of nearby genes, 14 candidate loci and genes for IMFBr, meat L* and b* values, and AbF are identified. The results provide new insight into the molecular mechanisms underlying meat quality traits in chickens.