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Aggression in chickens is a serious economic and animal welfare issue in poultry farming. Pigmentation traits have been documented to be associated with animal behaviour. Chicken pecking behaviour has been found to be related to feather colour, with premelanosome protein 17 (PMEL17) being one of the candidate genes. In the present study, we performed a genotypic and phenotypic association analysis between chicken plumage colour (red and white) and aggressive behaviour in an F1 hybrid group generated by crossing the autosomal dominant white-feathered breed White Leghorn (WL) and the red-feathered breed Rhode Island Red (RIR). In genetic theory, all the progeny should have white feathers because WL is homozygous autosomal dominant for white feathers. However, we found a few red-feathered female chickens. We compared the aggressiveness between the red and white females to determine whether the feather colour alone affected the behaviour, given that the genetic background should be the same except for feather colour. The aggressiveness was recorded 5 days after sexual maturity at 26 weeks. Generally, white plumage hens showed significantly higher aggressiveness compared to the red ones in chasing, attacking, pecking, and threatening behaviour traits. We assessed three candidate feather colour genes-PMEL17, solute carrier family 45 member 2 (SLC45A2), and SRY-box 10 (SOX10)-to determine the genetic basis for the red and white feather colour in our hybrid population; there was no association between the three loci and feather colour. The distinct behavioural findings observed herein provide clues to the mechanisms underlying the association between phenotype and behaviour in chickens. We suggest that mixing red and white chickens together might reduce the occurrence of aggressive behaviours.

Background The quality of poultry eggshells is closely related to the profitability of egg production. Eggshell speckles reflect an important quality trait that influences egg appearance and customer preference. However, the mechanism of speckle formation remains poorly understood. In this study, we systematically compared serum immune and antioxidant indices of hens laying speckled and normal eggs. Transcriptome and methylome analyses were used to elucidate the mechanism of eggshell speckle formation. Results The results showed that seven differentially expressed genes (DEGs) were identified between the normal and speckle groups. Gene set enrichment analysis (GSEA) revealed that the expressed genes were mainly enriched in the calcium signaling pathway, focal adhesion, and MAPK signaling pathway. Additionally, 282 differentially methylated genes (DMGs) were detected, of which 15 genes were associated with aging, including ARNTL , CAV1 , and GCLC . Pathway analysis showed that the DMGs were associated with T cell-mediated immunity, response to oxidative stress, and cellular response to DNA damage stimulus. Integrative analysis of transcriptome and DNA methylation data identified BFSP2 as the only overlapping gene, which was expressed at low levels and hypomethylated in the speckle group. Conclusions Overall, these results indicate that aging- and immune-related genes and pathways play a crucial role in the formation of speckled eggshells, providing useful information for improving eggshell quality.

Background Eggshell speckle phenotype is an important trait in poultry production because they affect eggshell quality. However, the genetic architecture of speckled eggshells remains unclear. In this study, we determined the heritability of eggshell speckles and conducted a genome-wide association study (GWAS) on purebred Rhode Island Red (RIR) hens at 28 weeks to detect potential genomic loci and candidate genes associated with eggshell speckles. Results The heritability of eggshell speckles was 0.35 at 28 weeks, and the speckle level is not related to other eggshell quality traits in terms of phenotypic correlation. We detected 311 SNPs (6 significantly, and 305 suggestively associated) and 39 candidate genes associated with eggshell speckles. Based on the pathway analysis, the 39 candidate genes were mainly involved in alpha-linolenic acid metabolism, linoleic acid metabolism, ether lipid metabolism, GnRH signaling pathway, vascular smooth muscle contraction, and MAPK signaling pathway. Ultimately, ten genes, LOC423226, SPTBN5, EHD4, LOC77155, TYRO3, ITPKA, DLL4, PLA2G4B, PLA2G4EL5 , and PLA2G4EL6 were considered the most promising genes associated with eggshell speckles that were implicated in immunoregulation, calcium transport, and phospholipid metabolism, while its function in laying hens requires further studies. Conclusions This study provides new insights into understanding the genetic basis of eggshell speckles and has practical application value for the genetic improvement of eggshell quality.

Egg number (EN), egg laying rate (LR) and age at first egg (AFE) are important production traits related to egg production in poultry industry. To better understand the knowledge of genetic architecture of dynamic EN during the whole laying cycle and provide the precise positions of associated variants for EN, LR and AFE, laying records from 21 to 72 weeks of age were collected individually for 1,534 F2 hens produced by reciprocal crosses between White Leghorn and Dongxiang Blue-shelled chicken, and their genotypes were assayed by chicken 600 K Affymetrix high density genotyping arrays. Subsequently, pedigree and SNP-based genetic parameters were estimated and a genome-wide association study (GWAS) was conducted on EN, LR and AFE. The heritability estimates were similar between pedigree and SNP-based estimates varying from 0.17 to 0.36. In the GWA analysis, we identified nine genome-wide significant loci associated with EN of the laying periods from 21 to 26 weeks, 27 to 36 weeks and 37 to 72 weeks. Analysis of GTF2A1 and CLSPN suggested that they influenced the function of ovary and uterus, and may be considered as relevant candidates. The identified SNP rs314448799 for accumulative EN from 21 to 40 weeks on chromosome 5 created phenotypic differences of 6.86 eggs between two homozygous genotypes, which could be potentially applied to the molecular breeding for EN selection. Moreover, our finding showed that LR was a moderate polygenic trait. The suggestive significant region on chromosome 16 for AFE suggested the relationship between sex maturity and immune in the current population. The present study comprehensively evaluates the role of genetic variants in the development of egg laying. The findings will be helpful to investigation of causative genes function and future marker-assisted selection and genomic selection in chickens.

Background Since the domestication of chicken, various breeds have been developed for food production, entertainment, and so on. Compared to indigenous chicken breeds which generally do not show elite production performance, commercial breeds or lines are selected intensely for meat or egg production. In the present study, in order to understand the molecular mechanisms underlying the dramatic differences of egg number between commercial egg-type chickens and indigenous chickens, we performed a genome-wide association study (GWAS) in a mixed linear model. Results We obtained 148 single nucleotide polymorphisms (SNPs) associated with egg number traits (57 significantly, 91 suggestively). Among them, 4 SNPs overlapped with previously reported quantitative trait loci (QTL), including 2 for egg production and 2 for reproductive traits. Furthermore, we identified 32 candidate genes based on the function of the screened genes. These genes were found to be mainly involved in regulating hormones, playing a role in the formation, growth, and development of follicles, and in the development of the reproductive system. Some genes such as NELL2 (neural EGFL like 2), KITLG (KIT ligand), GHRHR (Growth hormone releasing hormone receptor), NCOA1 (Nuclear receptor coactivator 1), ITPR1 (inositol 1, 4, 5-trisphosphate receptor type 1), GAMT (guanidinoacetate N-methyltransferase), and CAMK4 (calcium/calmodulin-dependent protein kinase IV) deserve our attention and further study since they have been reported to be closely related to egg production, egg number and reproductive traits. In addition, the most significant genomic region obtained in this study was located at 48.61–48.84 Mb on GGA5. In this region, we have repeatedly identified four genes, in which YY1 (YY1 transcription factor) and WDR25 (WD repeat domain 25) have been shown to be related to oocytes and reproductive tissues, respectively, which implies that this region may be a candidate region underlying egg number traits. Conclusion Our study utilized the genomic information from various chicken breeds or populations differed in the average annual egg number to understand the molecular genetic mechanisms involved in egg number traits. We identified a series of SNPs, candidate genes, or genomic regions that associated with egg number, which could help us in developing the egg production trait in chickens.

Background Copy number variation (CNV) is important and widespread in the genome, and is a major cause of disease and phenotypic diversity. Herein, we performed a genome-wide CNV analysis in 12 diversified chicken genomes based on whole genome sequencing. Results A total of 8,840 CNV regions (CNVRs) covering 98.2 Mb and representing 9.4% of the chicken genome were identified, ranging in size from 1.1 to 268.8 kb with an average of 11.1 kb. Sequencing-based predictions were confirmed at a high validation rate by two independent approaches, including array comparative genomic hybridization (aCGH) and quantitative PCR (qPCR). The Pearson’s correlation coefficients between sequencing and aCGH results ranged from 0.435 to 0.755, and qPCR experiments revealed a positive validation rate of 91.71% and a false negative rate of 22.43%. In total, 2,214 (25.0%) predicted CNVRs span 2,216 (36.4%) RefSeq genes associated with specific biological functions. Besides two previously reported copy number variable genes EDN3 and PRLR , we also found some promising genes with potential in phenotypic variation. Two genes, FZD6 and LIMS1 , related to disease susceptibility/resistance are covered by CNVRs. The highly duplicated SOCS2 may lead to higher bone mineral density. Entire or partial duplication of some genes like POPDC3 may have great economic importance in poultry breeding. Conclusions Our results based on extensive genetic diversity provide a more refined chicken CNV map and genome-wide gene copy number estimates, and warrant future CNV association studies for important traits in chickens.

China is home to a rich diversity of goose genetic resources, with more than 30 distinct breeds. These breeds are widely distributed in various environments with high annual mean temperature differences ranging from about 3.5 °C to 23 °C and annual precipitation differences ranging from about 230 mm to 2200 mm, positioning them as excellent models for studying environmental adaptability. With three genetic–environment association methods, the LFMM, Samβada, and RDA analysis, a total of 447 genes were selected by at least two methods. These genes are significantly enriched in three pathways, including the polycomb repressive complex pathway, the alanine, aspartate, and glutamate metabolism pathway, and the GnRH signalling pathway. The scanning of all candidate single-nucleotide polymorphism variations found that only two variants located in a non-coding region (chr3:38968547, chr13:23863699) showed stronger positive selection in breeds living in a high-temperature environment. This research not only deepens our understanding of the genetic basis of goose adaptation to diverse environments but also provides a valuable resource for future selective breeding programs in the goose industry facing rapid global climate change.

Background Geese are among the most important poultry species in the world. The current generally accepted hypothesis is that the European domestic geese originated from greylag geese ( Anser anser ), and Chinese domestic geese have two origins, most of which originated from swan geese ( Anser cygnoides ), and the Yili goose originated from greylag geese. To explain the origin and demographic history of geese, we selected 14 goose breeds from Europe and China and wild populations of swan and greylag geese, and whole genome sequencing data were obtained for 74 samples. Results Population structure analysis and phylogenetic trees showed that the wild ancestor of Chinese domestic geese, except for Yili, is the swan geese, and the wild ancestor of Chinese Yili and European domestic geese is greylag geese. Analysis of the demographic history suggests that the domestication of Chinese geese occurred ~ 3499 years ago and that of the European geese occurred ~ 7552 years ago. Furthermore, gene flow was observed between domestic geese and their wild ancestors. Analysis of introgression showed that Yili geese had been introgressed by Chinese domestic geese, and the body size of Yili geese may be influenced by introgression events of some growth-related genes, including IGF-1 . Conclusions Our study provides evidence for the origin of geese at the genome-wide level and advances the understanding of the history of goose domestication and the traits affected by introgression events.

Since the feed cost is a major determinant of profitability in poultry industry, how to improve feed efficiency through genetic selection is an intriguing subject for breeders and producers. As a more suitable indicator assessing feed efficiency, residual feed intake (RFI) is defined as the difference between observed and expected feed intake based on maintenance and growth. However, the genetic mechanisms responsible for RFI in chickens are still less well appreciated. In this study, we investigated the duodenal transcriptome architecture of extreme RFI phenotypes in the six brown-egg dwarf hens (three per group) using RNA sequencing technology. Among all mapped reads, an average of 75.62% fell into annotated exons, 5.50% were located in introns, and the remaining 18.88% were assigned to intergenic regions. In total, we identified 41 promising candidate genes by differential expression analysis between the low and high RFI groups. Furthermore, qRT-PCR assays were designed for 10 randomly chosen genes, and nine (90.00%) were successfully validated. Functional annotation analyses revealed that these significant genes belong to several specific biological functions related to digestibility, metabolism and biosynthesis processes as well as energy homeostasis. We also predicted 253 intergenic coding transcripts, and these transcripts were mainly involved in fundamental biological regulation and metabolism processes. Our findings provided a pioneering exploration of biological basis underlying divergent RFI using RNA-Seq, which pinpoints promising candidate genes of functional relevance, is helpful to guide future breeding strategies to optimize feed efficiency and assists in improving the current gene annotation in chickens.

Insertion and deletion (INDEL) is one of the main events contributing to genetic and phenotypic diversity, which receives less attention than SNP and large structural variation. To gain a better knowledge of INDEL variation in chicken genome, we applied next generation sequencing on 12 diverse chicken breeds at an average effective depth of 8.6. Over 1.3 million non-redundant short INDELs (1-49 bp) were obtained, the vast majority (92.48%) of which were novel. Follow-up validation assays confirmed that most (88.00%) of the randomly selected INDELs represent true variations. The majority (95.76%) of INDELs were less than 10 bp. Both the detected number and affected bases were larger for deletions than insertions. In total, INDELs covered 3.8 Mbp, corresponding to 0.36% of the chicken genome. The average genomic INDEL density was estimated as 0.49 per kb. INDELs were ubiquitous and distributed in a non-uniform fashion across chromosomes, with lower INDEL density in micro-chromosomes than in others, and some functional regions like exons and UTRs were prone to less INDELs than introns and intergenic regions. Nearly 620,253 INDELs fell in genic regions, 1,765 (0.28%) of which located in exons, spanning 1,358 (7.56%) unique Ensembl genes. Many of them are associated with economically important traits and some are the homologues of human disease-related genes. We demonstrate that sequencing multiple individuals at a medium depth offers a promising way for reliable identification of INDELs. The coding INDELs are valuable candidates for further elucidation of the association between genotypes and phenotypes. The chicken INDELs revealed by our study can be useful for future studies, including development of INDEL markers, construction of high density linkage map, INDEL arrays design, and hopefully, molecular breeding programs in chicken.