Distinct patterns of feed intake and their association with growth performance in broilers.

Improving feed utilization is a vital strategy to meet the growing global demand for meat and promote sustainable food production. Over the past few decades, significant improvements in the feed intake (FI) and feed utilization efficiency of broilers have been achieved through advanced breeding procedures, although dynamic changes in FI and their effects on the feed conversion ratio (FCR) have remained unclear. In this study, we measured individual weekly FI and body weight of 274 male broilers to characterize the dynamic FI patterns and investigate their relationship with growth performance. The broilers were from 2 purebred lines and their crossbreed and measurements were collected from 4 to 6 wk of age. Overall, a continuous increase in the weekly FI occurred from 4 to 6 wk of age, whereas the body weight gain (BWG) reached an inflection point in wk 5. The dynamic change in weekly FI was observed to follow 3 distinct FI patterns: pattern 1, a continuous weekly increase in FI; pattern 2, an increase followed by a plateau; pattern 3, an increase followed by a decrease. The prevalence of these patterns was similar in the purebred and crossbred populations: pattern 2 was most frequent, followed by a moderate proportion of pattern 1, and the lowest proportion of pattern 3. Broilers following pattern 1 displayed significantly better growth performance and feed utilization efficiency than those following pattern 3, emphasizing the importance of maintaining good appetite in the last stage of broiler production. In summary, this study has characterized the dynamic patterns of FI and their association with growth performance. Our results offer a new foundation for improving feed utilization efficiency and investigating feeding regulation in broilers.

Variations in seminal microbiota and their functional implications in chickens adapted to high-altitude environments.

Seminal fluid, once believed to be sterile, is now recognized as constituting a complex and dynamic environment inhabited by a diverse community of micro-organisms. However, research on the seminal microbiota in chickens is limited, and microbiota variations among different chicken breeds remain largely unexplored. In this study, we collected semen samples from Beijing You Chicken (BYC) and Tibetan Chicken (TC) and explored the characteristics of the microbiota using 16S rRNA gene sequencing. Additionally, we collected cloacal samples from the TC to control for environmental contamination. The results revealed that the microbial communities in the semen were significantly different from those in the cloaca. Firmicutes and Actinobacteriota were the predominant phyla in BYC and TC semen, respectively, with Lactobacillus and Phyllobacterium being the dominant genera in each group. Additionally, the seminal microbiota of BYC exhibited greater richness and evenness than that of TC. Principal coordinate analysis (PCoA) indicated significant intergroup differences between the seminal microbiotas of BYC and TC. Subsequently, by combining linear discriminant analysis effect size and random forest analyses, we identified Lactobacillus as the predominant microorganism in BYC semen, whereas Phyllobacterium dominated in TC semen. Furthermore, co-occurrence network analysis revealed a more intricate network in the BYC group than in the TC group. Additionally, unique microbial functional characteristics were observed in each breed, with TC exhibiting metabolic features potentially associated with their ability to adapt to high-altitude environments. The results of this study emphasized the unique microbiota present in chicken semen, which may be influenced by genetics and evolutionary history. Significant variations were observed between low-altitude and high-altitude breeds, highlighting the breed-specific implications of the seminal microbiota for reproduction and high-altitude adaptation.

Transcriptomic and epigenomic landscapes of muscle growth during the postnatal period of broilers.

BACKGROUND: Broilers stand out as one of the fastest-growing livestock globally, making a substantial contribution to animal meat production. However, the molecular and epigenetic mechanisms underlying the rapid growth and development of broiler chickens are still unclear. This study aims to explore muscle development patterns and regulatory networks during the postnatal rapid growth phase of fast-growing broilers. We measured the growth performance of Cornish (CC) and White Plymouth Rock (RR) over a 42-d period. Pectoral muscle samples from both CC and RR were randomly collected at day 21 after hatching (D21) and D42 for RNA-seq and ATAC-seq library construction. RESULTS: The consistent increase in body weight and pectoral muscle weight across both breeds was observed as they matured, with CC outpacing RR in terms of weight at each stage of development. Differential expression analysis identified 398 and 1,129 genes in the two dimensions of breeds and ages, respectively. A total of 75,149 ATAC-seq peaks were annotated in promoter, exon, intron and intergenic regions, with a higher number of peaks in the promoter and intronic regions. The age-biased genes and breed-biased genes of RNA-seq were combined with the ATAC-seq data for subsequent analysis. The results spotlighted the upregulation of ACTC1 and FDPS at D21, which were primarily associated with muscle structure development by gene cluster enrichment. Additionally, a noteworthy upregulation of MUSTN1, FOS and TGFB3 was spotted in broiler chickens at D42, which were involved in cell differentiation and muscle regeneration after injury, suggesting a regulatory role of muscle growth and repair. CONCLUSIONS: This work provided a regulatory network of postnatal broiler chickens and revealed ACTC1 and MUSTN1 as the key responsible for muscle development and regeneration. Our findings highlight that rapid growth in broiler chickens triggers ongoing muscle damage and subsequent regeneration. These findings provide a foundation for future research to investigate the functional aspects of muscle development.

The Effects of Different Doses of Canthaxanthin in the Diet of Laying Hens on Egg Quality, Physical Characteristics, Metabolic Mechanism, and Offspring Health.

Currently, there is a dearth of in-depth analysis and research on the impact of canthaxanthin on the production performance, egg quality, physical characteristics, and offspring health of laying hens. Furthermore, the metabolic mechanism of cantharidin in the body remains unclear. Therefore, to solve the above issues in detail, our study was conducted with a control group (C group), a low-dose canthaxanthin group (L group), and a high-dose canthaxanthin group (H group), each fed for a period of 40 days. Production performance was monitored during the experiment, in which L and H groups showed a significant increase in ADFI. Eggs were collected for quality analysis, revealing no significant differences in qualities except for yolk color (YC). The YC of the C group almost did not change, ranging from 6.08 to 6.20; however, the trend in YC change in other groups showed an initial intense increase, followed by a decrease, and eventually reached dynamic equilibrium. By detecting the content of canthaxanthin in the yolk, the YC change trend was found to be correlated with canthaxanthin levels in the yolk. The content of unsaturated fatty acid increased slightly in L and H groups. Following the incubation period, the physical characteristics and blood biochemical indices of chicks were evaluated. It was observed that the shank color of chicks in the L and H groups was significantly higher than that in the C group at birth. However, by the 35th day, there were no significant differences in shank color among the three groups. Further investigation into the metabolic mechanism involving canthaxanthin revealed that the substance underwent incomplete metabolism upon entering the body, resulting in its accumulation as well as metabolic by-product accumulation in the yolk. In summary, this study highlighted the importance of understanding canthaxanthin's role in production performance, egg quality, and offspring health, providing valuable insights for breeders to optimize feeding strategies.

Runs of homozygosity and selection signature analyses reveal putative genomic regions for artificial selection in layer breeding.

BACKGROUND: The breeding of layers emphasizes the continual selection of egg-related traits, such as egg production, egg quality and eggshell, which enhance their productivity and meet the demand of market. As the breeding process continued, the genomic homozygosity of layers gradually increased, resulting in the emergence of runs of homozygosity (ROH). Therefore, ROH analysis can be used in conjunction with other methods to detect selection signatures and identify candidate genes associated with various important traits in layer breeding. RESULTS: In this study, we generated whole-genome sequencing data from 686 hens in a Rhode Island Red population that had undergone fifteen consecutive generations of intensive artificial selection. We performed a genome-wide ROH analysis and utilized multiple methods to detect signatures of selection. A total of 141,720 ROH segments were discovered in whole population, and most of them (97.35%) were less than 3 Mb in length. Twenty-three ROH islands were identified, and they overlapped with some regions bearing selection signatures, which were detected by the De-correlated composite of multiple signals methods (DCMS). Sixty genes were discovered and functional annotation analysis revealed the possible roles of them in growth, development, immunity and signaling in layers. Additionally, two-tailed analyses including DCMS and ROH for 44 phenotypes of layers were conducted to find out the genomic differences between subgroups of top and bottom 10% phenotype of individuals. Combining the results of GWAS, we observed that regions significantly associated with traits also exhibited selection signatures between the high and low subgroups. We identified a region significantly associated with egg weight near the 25 Mb region of GGA 1, which exhibited selection signatures and has higher genomic homozygosity in the low egg weight subpopulation. This suggests that the region may be play a role in the decline in egg weight. CONCLUSIONS: In summary, through the combined analysis of ROH, selection signatures, and GWAS, we identified several genomic regions that associated with the production traits of layers, providing reference for the study of layer genome.

Transcriptomic and epigenomic insights into pectoral muscle fiber formation at the late embryonic development in pure chicken lines.

Long-term intensive genetic selection has led to significant differences between broiler and layer chickens, which are evident during the embryonic period. Despite this, there is a paucity of research on the genetic regulation of the initial formation of muscle fiber morphology in chick embryos. Embryonic d 17 (E17) is the key time point for myoblast fusion completion and muscle fiber morphology formation in chickens. This study aimed to explore the genetic regulatory mechanisms underlying the early muscle fiber morphology establishment in broiler chickens of Cornish (CC) and White Plymouth Rock (RR) and layer chickens of White Leghorn (WW) at E17 using the transcriptomic and chromatin accessibility sequencing of pectoral major muscles. The results showed that broiler chickens exhibited significant higher embryo weight and pectoral major muscle weight at E17 compared to layer chickens (P = 0.000). A total of 1,278, 1,248, and 892 differentially expressed genes (DEGs) of RNA-seq data were identified between CC vs. WW, RR vs. WW, and CC vs. RR, separately. All DEGs were combined for cluster analysis and they were divided into 6 clusters, including cluster 1 with higher expression in broilers and cluster 6 with higher expression in layers. DEGs in cluster 1 were enriched in terms related to macrophage activation (P = 0.002) and defense response to bacteria (P = 0.002), while DEGs in cluster 6 showed enrichment in protein-DNA complex (P = 0.003) and monooxygenase activity (P = 0.000). ATAC-seq data analysis identified a total of 38,603 peaks, with 13,051 peaks for CC, 18,780 peaks for RR, and 6,772 peaks for WW. Integrative analysis of transcriptomic and chromatin accessibility data revealed GOLM1, ISLR2, and TOPAZ1 were commonly upregulated genes in CC and RR. Furthermore, screening of all upregulated DEGs in cluster 1 from CC and RR identified GOLM1, ISLR2, and HNMT genes associated with neuroimmune functions and MYOM3 linked to muscle morphology development, showing significantly elevated expression in broiler chickens compared to layer chickens. These findings suggest active neural system connectivity during the initial formation of muscle fiber morphology in embryonic period, highlighting the early interaction between muscle fiber formation morphology and the nervous system. This study provides novel insights into late chick embryo development and lays a deeper foundation for further research.

Integrating Bioinformatics and Machine Learning for Genomic Prediction in Chickens.

Genomic prediction plays an increasingly important role in modern animal breeding, with predictive accuracy being a crucial aspect. The classical linear mixed model is gradually unable to accommodate the growing number of target traits and the increasingly intricate genetic regulatory patterns. Hence, novel approaches are necessary for future genomic prediction. In this study, we used an illumina 50K SNP chip to genotype 4190 egg-type female Rhode Island Red chickens. Machine learning (ML) and classical bioinformatics methods were integrated to fit genotypes with 10 economic traits in chickens. We evaluated the effectiveness of ML methods using Pearson correlation coefficients and the RMSE between predicted and actual phenotypic values and compared them with rrBLUP and BayesA. Our results indicated that ML algorithms exhibit significantly superior performance to rrBLUP and BayesA in predicting body weight and eggshell strength traits. Conversely, rrBLUP and BayesA demonstrated 2-58% higher predictive accuracy in predicting egg numbers. Additionally, the incorporation of suggestively significant SNPs obtained through the GWAS into the ML models resulted in an increase in the predictive accuracy of 0.1-27% across nearly all traits. These findings suggest the potential of combining classical bioinformatics methods with ML techniques to improve genomic prediction in the future.

Mechanisms of hepatic steatosis in chickens: integrated analysis of the host genome, molecular phenomics and gut microbiome.

Hepatic steatosis is the initial manifestation of abnormal liver functions and often leads to liver diseases such as nonalcoholic fatty liver disease in humans and fatty liver syndrome in animals. In this study, we conducted a comprehensive analysis of a large chicken population consisting of 705 adult hens by combining host genome resequencing; liver transcriptome, proteome, and metabolome analysis; and microbial 16S ribosomal RNA gene sequencing of each gut segment. The results showed the heritability (h2 = 0.25) and duodenal microbiability (m2 = 0.26) of hepatic steatosis were relatively high, indicating a large effect of host genetics and duodenal microbiota on chicken hepatic steatosis. Individuals with hepatic steatosis had low microbiota diversity and a decreased genetic potential to process triglyceride output from hepatocytes, fatty acid ß-oxidation activity, and resistance to fatty acid peroxidation. Furthermore, we revealed a molecular network linking host genomic variants (GGA6: 5.59-5.69 Mb), hepatic gene/protein expression (PEMT, phosphatidyl-ethanolamine N-methyltransferase), metabolite abundances (folate, S-adenosylmethionine, homocysteine, phosphatidyl-ethanolamine, and phosphatidylcholine), and duodenal microbes (genus Lactobacillus) to hepatic steatosis, which could provide new insights into the regulatory mechanism of fatty liver development.

Single-nucleus transcriptional and chromatin accessible profiles reveal critical cell types and molecular architecture underlying chicken sex determination.

INTRODUCTION: Understanding the sex determination mechanisms in birds has great significance for the biological sciences and production in the poultry industry. Sex determination in chickens is a complex process that involves fate decisions of supporting cells such as granulosa or Sertoli cells. However, a systematic understanding of the genetic regulation and cell commitment process underlying sex determination in chickens is still lacking. OBJECTIVES: We aimed to dissect the molecular characteristics associated with sex determination in the gonads of chicken embryos. METHODS: Single-nucleus RNA-seq (snRNA-seq) and ATAC-seq (snATAC-seq) analysis were conducted on the gonads of female and male chickens at embryonic day 3.5 (E3.5), E4.5, and E5.5. RESULTS: Here, we provided a time-course transcriptional and chromatin accessible profiling of gonads during chicken sex determination at single-cell resolution. We uncovered differences in cell composition and developmental trajectories between female and male gonads and found that the divergence of transcription and accessibility in gonadal cells first emerged at E5.5. Furthermore, we revealed key cell-type-specific transcription factors (TFs) and regulatory networks that drive lineage commitment. Sex determination signaling pathways, dominated by BMP signaling, are preferentially activated in males during gonadal development. Further pseudotime analysis of the supporting cells indicated that granulosa cells were regulated mainly by the TEAD gene family and that Sertoli cells were driven by the DMRT1 regulons. Cross-species analysis suggested high conservation of both cell types and cell-lineage-specific TFs across the six vertebrates. CONCLUSIONS: Overall, our study will contribute to accelerating the development of sex manipulation technology in the poultry industry and the application of chickens as a unique model for studying cell fate decisions.

Paternity bias and cryptic female choice in chickens.

Sperm competition and cryptic female choice (CFC) are 2 significant mechanisms of postcopulatory sexual selection that greatly impact fertilization success in various species. Despite extensive research has conducted on sperm competition and the evolution of sperm traits in internal fertilization, our understanding of the female preferences in selecting sperm is still limited. Here, we aimed to investigate the characteristics of CFC in chickens by utilizing artificial insemination with mixed semen to control for variations in male fertilization success caused by female perception of male quality and mating order. Our results revealed that the offspring from multiple-mated females exhibited mixed paternity. Although the males had an equal number of viable sperm, 1 male consistently exhibited a 15% higher success rate on average, regardless of whether the insemination was performed with fresh or diluted semen. This result suggested that this male demonstrates superior performance in sperm competition, and exhibited a potential advantage in fertilization success. While the dominant male generally made a greater genetic contribution to most offspring, the degree of this advantage varied greatly, ranging from 11.11 to 75%. Furthermore, our study provided evidence of female preferences influenced the precedence of sperm from certain males over others. Interestingly, this bias is not consistently observed among all individuals, as offspring derived from some females were predominantly sired by an overall disadvantaged male while others were predominantly by a different disadvantaged male. Overall, these results underscored the complex processes involved in sperm selection and emphasized the importance of females in sexual selection theory.

Genetic patterns and genome-wide association analysis of eggshell quality traits of egg-type chicken across an extended laying period.

The industry of egg-type chicken has shown a trend of extending the rearing period, with the goal of breeding chicken breeds capable of producing 500 qualified eggs by 700 d of age. However, the rapid decline in eggshell quality during the late laying period is one of the major challenges. In this study, a total of 3,261 Rhode Island Red chickens were used to measure eggshell quality traits including eggshell strength (ESS), eggshell thickness (EST), eggshell color (ESC) and eggshell gloss (ESG) at seven age points ranging from 36 to 90 wk of age. Phenotypic variations increased with the aging process, especially during the late laying period (> 55 wk), and the heritability during this period decreased by 22.7 to 81.4% compared to the initial and peak laying periods. Then we performed genome-wide association study (GWAS) to identify the genomic variants that associated with eggshell quality, with a custom Illumina 50K BeadChip, named PhenoixChip-I. The results indicated that 2 genomic regions on GGA1(23.24-25.15Mb; 175.95-176.05 Mb) were significantly (P < 4.48E-06) or suggestively (P < 8.97E-05) associated with ESS, which can explain 9.59% and 0.48% of the phenotypic variations of ESS46 and ESS36, respectively. Three genes, FRY, PCNX2, and ENSGALG00000052468, were considered to be the candidate genes for ESS. For other traits, the genome-wide suggestive SNPs were identified at each age point, exhibiting a certain trend with aging process. Additionally, SNP enrichment analysis and functional annotation of cross-tissue regulatory elements to ESS36 revealed a high concentration of enhancer elements specific to shell gland and kidney tissues. This study, deepened our knowledge of eggshells and laying a valued scientific foundation for chicken molecular breeding.

MyoV: a deep learning-based tool for the automated quantification of muscle fibers.

Accurate approaches for quantifying muscle fibers are essential in biomedical research and meat production. In this study, we address the limitations of existing approaches for hematoxylin and eosin-stained muscle fibers by manually and semiautomatically labeling over 660 000 muscle fibers to create a large dataset. Subsequently, an automated image segmentation and quantification tool named MyoV is designed using mask regions with convolutional neural networks and a residual network and feature pyramid network as the backbone network. This design enables the tool to allow muscle fiber processing with different sizes and ages. MyoV, which achieves impressive detection rates of 0.93-0.96 and precision levels of 0.91-0.97, exhibits a superior performance in quantification, surpassing both manual methods and commonly employed algorithms and software, particularly for whole slide images (WSIs). Moreover, MyoV is proven as a powerful and suitable tool for various species with different muscle development, including mice, which are a crucial model for muscle disease diagnosis, and agricultural animals, which are a significant meat source for humans. Finally, we integrate this tool into visualization software with functions, such as segmentation, area determination and automatic labeling, allowing seamless processing for over 400 000 muscle fibers within a WSI, eliminating the model adjustment and providing researchers with an easy-to-use visual interface to browse functional options and realize muscle fiber quantification from WSIs.

Genetic improvement of duration of fertility in chickens and its commercial application for extending insemination intervals.

The growth rate of chickens has made remarkable progress in recent decades through continuous breeding efforts. However, this advancement has also led to a decline in fertility among commercially bred chickens. Therefore, it is crucial to understand and improve factors that influence fertility to ensure the continued success of the industry. Here, we conduct a 3-generation selection experiment within 2 purebred female lines, with the aim of increasing the duration of fertility (DF). Duration of fertility refers to the length of time hens remain capable of producing fertilized eggs and is a crucial factor that directly impacts chick output. The results showed that significant genetic progress was achieved in embryo survival rates and the fertility duration day during both the peak and late laying periods. Moreover, after 3 generations of selective breeding, the disparities in embryo survival and chick health rates from setting eggs between 8-d and 5-d insemination intervals in the grandparent stock were significantly reduced. The rates decreased from 1.83% and 2.39 to 0.72% and 0.33%, respectively. Surprisingly, the hatching performances of hens with an 8-d interval were comparable to those hens that had not undergone genetic selection for DF and had a 5-d interval. We further discussed the possibility of extending the insemination interval to 8 d in parent stock for commercial practices. The parental populations exhibited remarkable performance in terms of percentages of embryo survival and healthy chicks from the setting eggs, with rates exceeding 94 and 90%, respectively. Thus, it can be inferred that an extended insemination interval is feasible by genetic selection for DF. These findings will provide valuable insights into the efficacy of genetic selection in enhancing DF and its practical application in commercial breeding programs.

A chromosome-level genome assembly for the Silkie chicken resolves complete sequences for key chicken metabolic, reproductive, and immunity genes.

A set of high-quality pan-genomes would help identify important genes that are still hidden/incomplete in bird reference genomes. In an attempt to address these issues, we have assembled a de novo chromosome-level reference genome of the Silkie (Gallus gallus domesticus), which is an important avian model for unique traits, like fibromelanosis, with unclear genetic foundation. This Silkie genome includes the complete genomic sequences of well-known, but unresolved, evolutionarily, endocrinologically, and immunologically important genes, including leptin, ovocleidin-17, and tumor-necrosis factor-α. The gap-less and manually annotated MHC (major histocompatibility complex) region possesses 38 recently identified genes, with differentially regulated genes recovered in response to pathogen challenges. We also provide whole-genome methylation and genetic variation maps, and resolve a complex genetic region that may contribute to fibromelanosis in these animals. Finally, we experimentally show leptin binding to the identified leptin receptor in chicken, confirming an active leptin ligand-receptor system. The Silkie genome assembly not only provides a rich data resource for avian genome studies, but also lays a foundation for further functional validation of resolved genes.

Host genetics and gut microbiota jointly regulate blood biochemical indicators in chickens.

Blood biochemical indicators play a crucial role in assessing an individual's overall health status and metabolic function. In this study, we measured five blood biochemical indicators, including total cholesterol (CHOL), low-density lipoprotein cholesterol (LDL-CH), triglycerides (TG), high-density lipoprotein cholesterol (HDL-CH), and blood glucose (BG), as well as 19 growth traits of 206 male chickens. By integrating host whole-genome information and 16S rRNA sequencing of the duodenum, jejunum, ileum, cecum, and feces microbiota, we assessed the contributions of host genetics and gut microbiota to blood biochemical indicators and their interrelationships. Our results demonstrated significant negative phenotypic and genetic correlations (r = - 0.20 ~ - 0.67) between CHOL and LDL-CH with growth traits such as body weight, abdominal fat content, muscle content, and shin circumference. The results of heritability and microbiability indicated that blood biochemical indicators were jointly regulated by host genetics and gut microbiota. Notably, the heritability of HDL-CH was estimated to be 0.24, while the jejunal microbiability for BG and TG reached 0.45 and 0.23. Furthermore, by conducting genome-wide association study (GWAS) with the single-nucleotide polymorphism (SNPs), insertion/deletion (indels), and structural variation (SV), we identified RAP2C, member of the RAS oncogene family (RAP2C), dedicator of cytokinesis 11 (DOCK11), neurotensin (NTS) and BOP1 ribosomal biogenesis factor (BOP1) as regulators of HDL-CH, and glycerophosphodiester phosphodiesterase domain containing 5 (GDPD5), dihydrodiol dehydrogenase (DHDH), and potassium voltage-gated channel interacting protein 1 (KCNIP1) as candidate genes of BG. Moreover, our findings suggest that cecal RF39 and Clostridia_UCG_014 may be linked to the regulation of CHOL, and jejunal Streptococcaceae may be involved in the regulation of TG. Additionally, microbial GWAS results indicated that the presence of gut microbiota was under host genetic regulation. Our findings provide valuable insights into the complex interaction between host genetics and microbiota in shaping the blood biochemical profile of chickens. KEY POINTS: • Multiple candidate genes were identified for the regulation of CHOL, HDL-CH, and BG. • RF39, Clostridia_UCG_014, and Streptococcaceae were implicated in CHOL and TG modulation. • The composition of gut microbiota is influenced by host genetics.

Hepatic steatosis is associated with dysregulated cholesterol metabolism and altered protein acetylation dynamics in chickens.

BACKGROUND: Hepatic steatosis is a prevalent manifestation of fatty liver, that has detrimental effect on the health and productivity of laying hens, resulting in economic losses to the poultry industry. Here, we aimed to systematically investigate the genetic regulatory mechanisms of hepatic steatosis in laying hens. METHODS: Ninety individuals with the most prominent characteristics were selected from 686 laying hens according to the accumulation of lipid droplets in the liver, and were graded into three groups, including the control, mild hepatic steatosis and severe hepatic steatosis groups. A combination of transcriptome, proteome, acetylome and lipidome analyses, along with bioinformatics analysis were used to screen the key biological processes, modifications and lipids associated with hepatic steatosis. RESULTS: The rationality of the hepatic steatosis grouping was verified through liver biochemical assays and RNA-seq. Hepatic steatosis was characterized by increased lipid deposition and multiple metabolic abnormalities. Integration of proteome and acetylome revealed that differentially expressed proteins (DEPs) interacted with differentially acetylated proteins (DAPs) and were involved in maintaining the metabolic balance in the liver. Acetylation alterations mainly occurred in the progression from mild to severe hepatic steatosis, i.e., the enzymes in the fatty acid oxidation and bile acid synthesis pathways were significantly less acetylated in severe hepatic steatosis group than that in mild group (P < 0.05). Lipidomics detected a variety of sphingolipids (SPs) and glycerophospholipids (GPs) were negatively correlated with hepatic steatosis (r ≤ -0.5, P < 0.05). Furthermore, the severity of hepatic steatosis was associated with a decrease in cholesterol and bile acid synthesis and an increase in exogenous cholesterol transport. CONCLUSIONS: In addition to acquiring a global and thorough picture of hepatic steatosis in laying hens, we were able to reveal the role of acetylation in hepatic steatosis and depict the changes in hepatic cholesterol metabolism. The findings provides a wealth of information to facilitate a deeper understanding of the pathophysiology of fatty liver and contributes to the development of therapeutic strategies.

An atlas of regulatory elements in chicken: A resource for chicken genetics and genomics.

A comprehensive characterization of regulatory elements in the chicken genome across tissues will have substantial impacts on both fundamental and applied research. Here, we systematically identified and characterized regulatory elements in the chicken genome by integrating 377 genome-wide sequencing datasets from 23 adult tissues. In total, we annotated 1.57 million regulatory elements, representing 15 distinct chromatin states, and predicted about 1.2 million enhancer-gene pairs and 7662 super-enhancers. This functional annotation of the chicken genome should have wide utility on identifying regulatory elements accounting for gene regulation underlying domestication, selection, and complex trait regulation, which we explored. In short, this comprehensive atlas of regulatory elements provides the scientific community with a valuable resource for chicken genetics and genomics.

Integrated analysis of methylation profiles and transcriptome of Marek's disease virus-infected chicken spleens reveal hypomethylation of CD4 and HMGB1 genes might promote Marek's disease tumorigenesis.

Marek's disease (MD) is a lymphoproliferative neoplastic disease caused by Marek's disease virus (MDV). Previous studies have showed that DNA methylation was involved in MD development, but systematic studies are still lacking. Herein, we performed whole genome bisulfite sequencing (WGBS) and RNA-seq in MDV-infected tumorous spleens (IN), noninfected spleens (NoIN), and survivor (SUR) spleens of chickens to identify the genes playing important roles in MD tumor transformation. We generated the first genome-wide DNA methylation profile of MDV-infected, noninfected, and survivor chickens. Combined the WGBS and RNA-Seq, we found that the expression of 25% differential expression genes (DEGs) were significantly correlated with methylation of CpG sites in their gene bodies or promoters. Further, we focused on the DEGs with differentially methylated regions (DMRs) on genes' body and promoter, and it showed the expression of 60% DEGs were significantly correlated with methylation of CpG sites in DMRs. Finally, we identified 8 genes, including CD4, CTLA4, DTL, HMGB1, LGMN, NUP210, RAD52, and ZAP70, and their expression was negatively correlated with methylation of DMRs in their promoters in both IN vs. NoIN and IN vs. SUR. These 8 genes showed specifically high expression in IN groups and clustered in module turquoise analyzed by WGCNA. Out of 8 genes, CD4 and HMGB1 were drop in QTLs associated with MD resistance. Thus, we overexpressed the 2 genes to simulate their high expression in the IN group and found they significantly promoted MDCC-MSB-1 cell proliferation, which revealed they might play promoting roles in MD tumorigenesis in IN due to their high expression induced by hypomethylation.

The cecal ecosystem is a great contributor to intramuscular fat deposition in broilers.

Intramuscular fat (IMF) content is a meat quality trait of major economic importance in animal production. Emerging evidence has demonstrated that meat quality can be improved by regulating the gut microbiota. However, the organization and ecological properties of the gut microbiota and its relationship with the IMF content remain unclear in chickens. Here, we investigated the microbial communities of 206 cecal samples from broilers with excellent meat quality. We noted that the cecal microbial ecosystem obtained from hosts reared under the same management and dietary conditions showed clear compositional stratification. Two enterotypes, in which the ecological properties, including diversity and interaction strengths, were significantly different, described the microbial composition pattern. Compared with enterotype 2, enterotype 1, distinguished by the Clostridia_vadinBB60_group, had a higher fat deposition, although no discrepancy was found in growth performance and meat yield. A moderate correlation was observed in the IMF content between 2 muscle tissues, despite the IMF content of thigh muscle was 42.76% greater than that of breast muscle. Additionally, the lower abundance of cecal vadinBE97 was related to higher IMF levels in both muscle tissues. Although vadinBE97 accounted for 0.40% of the total abundance of genera in the cecum, it exhibited significant and positive correlations with other genera (accounting for 25.3% of the tested genera). Our results highlight important insights into the cecal microbial ecosystem and its association with meat quality. Microbial interactions should be carefully considered when developing approaches to improve the IMF content by regulating the gut microbiota in broilers.

Temperature-induced embryonic diapause in chickens is mediated by PKC-NF-κB-IRF1 signaling.

BACKGROUND: Embryonic diapause (dormancy) is a state of temporary arrest of embryonic development that is triggered by unfavorable conditions and serves as an evolutionary strategy to ensure reproductive survival. Unlike maternally-controlled embryonic diapause in mammals, chicken embryonic diapause is critically dependent on the environmental temperature. However, the molecular control of diapause in avian species remains largely uncharacterized. In this study, we evaluated the dynamic transcriptomic and phosphoproteomic profiles of chicken embryos in pre-diapause, diapause, and reactivated states. RESULTS: Our data demonstrated a characteristic gene expression pattern in effects on cell survival-associated and stress response signaling pathways. Unlike mammalian diapause, mTOR signaling is not responsible for chicken diapause. However, cold stress responsive genes, such as IRF1, were identified as key regulators of diapause. Further in vitro investigation showed that cold stress-induced transcription of IRF1 was dependent on the PKC-NF-κB signaling pathway, providing a mechanism for proliferation arrest during diapause. Consistently, in vivo overexpression of IRF1 in diapause embryos blocked reactivation after restoration of developmental temperatures. CONCLUSIONS: We concluded that embryonic diapause in chicken is characterized by proliferation arrest, which is the same with other spices. However, chicken embryonic diapause is strictly correlated with the cold stress signal and mediated by PKC-NF-κB-IRF1 signaling, which distinguish chicken diapause from the mTOR based diapause in mammals.