Analysis of a genetic factors contributing to feathering phenotype in chickens

Artificial selection footprints in indigenous and commercial chicken genomes

BACKGROUND

Although many studies have been done to reveal artificial selection signatures in commercial and indigenous chickens, a limited number of genes have been linked to specific traits. To identify more trait-related artificial selection signatures and genes, we re-sequenced a total of 85 individuals of five indigenous chicken breeds with distinct traits from Yunnan Province, China.

RESULTS

We found 30 million non-redundant single nucleotide variants and small indels (< 50 bp) in the indigenous chickens, of which 10 million were not seen in 60 broilers, 56 layers and 35 red jungle fowls (RJFs) that we compared with. The variants in each breed are enriched in non-coding regions, while those in coding regions are largely tolerant, suggesting that most variants might affect cis-regulatory sequences. Based on 27 million bi-allelic single nucleotide polymorphisms identified in the chickens, we found numerous selective sweeps and affected genes in each indigenous chicken breed and substantially larger numbers of selective sweeps and affected genes in the broilers and layers than previously reported using a rigorous statistical model. Consistent with the locations of the variants, the vast majority (~ 98.3%) of the identified selective sweeps overlap known quantitative trait loci (QTLs). Meanwhile, 74.2% known QTLs overlap our identified selective sweeps. We confirmed most of previously identified trait-related genes and identified many novel ones, some of which might be related to body size and high egg production traits. Using RT-qPCR, we validated differential expression of eight genes (GHR, GHRHR, IGF2BP1, OVALX, ELF2, MGARP, NOCT, SLC25A15) that might be related to body size and high egg production traits in relevant tissues of relevant breeds.

CONCLUSION

We identify 30 million single nucleotide variants and small indels in the five indigenous chicken breeds, 10 million of which are novel. We predict substantially more selective sweeps and affected genes than previously reported in both indigenous and commercial breeds. These variants and affected genes are good candidates for further experimental investigations of genotype-phenotype relationships and practical applications in chicken breeding programs.

A pangenome graph reference of 30 chicken genomes allows genotyping of large and complex structural variants

BACKGROUND

The red junglefowl, the wild outgroup of domestic chickens, has historically served as a reference for genomic studies of domestic chickens. These studies have provided insight into the etiology of traits of commercial importance. However, the use of a single reference genome does not capture diversity present among modern breeds, many of which have accumulated molecular changes due to drift and selection. While reference-based resequencing is well-suited to cataloging simple variants such as single-nucleotide changes and short insertions and deletions, it is mostly inadequate to discover more complex structural variation in the genome.

METHODS

We present a pangenome for the domestic chicken consisting of thirty assemblies of chickens from different breeds and research lines.

RESULTS

We demonstrate how this pangenome can be used to catalog structural variants present in modern breeds and untangle complex nested variation. We show that alignment of short reads from 100 diverse wild and domestic chickens to this pangenome reduces reference bias by 38%, which affects downstream genotyping results. This approach also allows for the accurate genotyping of a large and complex pair of structural variants at the K feathering locus using short reads, which would not be possible using a linear reference.

CONCLUSIONS

We expect that this new paradigm of genomic reference will allow better pinpointing of exact mutations responsible for specific phenotypes, which will in turn be necessary for breeding chickens that meet new sustainability criteria and are resilient to quickly evolving pathogen threats.

dPRLR causes differences in immune responses between early and late feathering chickens after ALV-J infection

To understand the differences in immune responses between early feathering (EF) and late feathering (LF) chickens after infection with avian leukosis virus, subgroup J (ALV-J), we monitored the levels of prolactin, growth hormone and the immunoglobulins IgG and IgM in the serum of LF and EF chickens for 8 weeks. Moreover, we analysed the expression of immune-related genes in the spleen and the expression of PRLR, SPEF2 and dPRLR in the immune organs and DF-1 cells by qRT–PCR. The results showed that ALV-J infection affected the expression of prolactin, growth hormone, IgG and IgM in the serum. Regardless of whether LF and EF chickens were infected with ALV-J, the serum levels of the two hormones and two immunoglobulins in EF chickens were higher than those in LF chickens (P  < 0.05). However, the expression of immune-related genes in the spleen of positive LF chickens was higher than that in the spleen of positive EF chickens. In the four immune organs, PRLR and SPEF2 expression was also higher in LF chickens than in EF chickens. Furthermore, the dPRLR expression of positive LF chickens was higher than that of negative LF chickens. After infection with ALV-J, the expression of PRLR in DF-1 cells significantly increased. In addition, overexpression of PRLR or dPRLR in DF-1 cells promoted replication of ALV-J. These results suggested that the susceptibility of LF chickens to ALV-J might be induced by dPRLR.