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Published on: June 3, 2022
A joint genome-wide association study reveals candidate genes associated with egg production traits in chickens
Ming Fu1, Jinsong Pi1, Yaru Chen1
1Institute of Animal Sciences and Veterinary Medicine, Hubei Academy of Agricultural Sciences, Wuhan, 430064, China; Key Laboratory of Animal Embryo Engineering and Molecular Breeding of Hubei Province, Wuhan, 430064, China.
Abstract:
Egg production traits represent key economic determinants in the poultry industry, and unravelling their genetic architecture is essential for implementing genomic breeding in laying hens. Here, we performed a joint genome-wide association study (GWAS) with whole-genome sequencing data from 975 chickens (490 indigenous Jianghan chickens and 485 Rhode Island Red layers) to characterise the genetic basis of nine egg production traits: age at first egg (AFE), body weight at first egg (WFE), stage-specific egg number (EN) across the laying cycle, and maximum consecutive egg-laying days (MCD). Population genomic analyses revealed clear genetic differentiation between the two breeds. We further estimated moderate-to-high heritability for most assayed traits, as well as strong genetic correlations among stage-specific EN traits. A major shared quantitative trait locus (QTL) associated with WFE was mapped to chromosome 4 (GGA4), harboring key candidate genes LDB2 and PPARGC1A; IGF2BP1 on GGA27 was additionally identified as a promising candidate for this trait. For EN traits, three population-specific pleiotropic loci were detected, harboring candidate genes ZNF592, DENND1B, and WDPCP respectively. For MCD, BMPR1A and MYCBP2 were prioritized as prominent candidate genes in the two breeds. Candidate genes from selection signature analysis (SSA) were enriched in hormonal response and energy metabolism pathways, whereas GWAS-identified candidates were mainly associated with follicular development, calcium signaling, and apoptosis regulation. Taken together, our results reveal the layered genetic architecture of egg production traits in indigenous and commercial layer populations. The identified SNPs and candidate genes will provide molecular markers to support genetic improvement of laying performance in chicken breeding.
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