Abstract
Chicken growth traits are economically important, but the relevant genetic mechanisms have not yet been elucidated. Herein, we performed a genome-wide association study to identify the variants associated with growth traits. In total, 860 chickens from a Gushi-Anka F2 resource population were phenotyped for 68 growth and carcass traits, and 768 samples were genotyped based on the genotyping-by-sequencing (GBS) method. Finally, 734 chickens and 321,314 SNPs remained after quality control and removal of the sex chromosomes, and these data were used to carry out a GWAS analysis. A total of 470 significant single-nucleotide polymorphisms (SNPs) for 43 of the 68 traits were detected and mapped on chromosomes (Chr) 1–6, -9, -10, -16, -18, -23, and -27. Of these, the significant SNPs in Chr1, -4, and -27 were found to be associated with more than 10 traits. Multiple traits shared significant SNPs, indicating that the same mutation in the region might have a large effect on multiple growth or carcass traits. Haplotype analysis revealed that SNPs within the candidate region of Chr1 presented a mosaic pattern. The significant SNPs and pathway enrichment analysis revealed that the MLNR, MED4, CAB39L, LDB2, and IGF2BP1 genes could be putative candidate genes for growth and carcass traits. The findings of this study improve our understanding of the genetic mechanisms regulating chicken growth and carcass traits and provide a theoretical basis for chicken breeding programs.
Highlights
Maynard Smith and Haigh (1974) demonstrated that the occurrence and fixation of a selectively favorable mutation in a population will alter the frequencies of closely linked alleles
A relatively weak correlation was observed in both the body weight (BW) and partial body size traits (PA, chest depth (CD), and pelvis breadth (PB)) between the early- and late-growth stages
A strong correlation occurred between the carcass weight (CWe) trait and parts of the CWe, such as the breast muscle weight (BMW), leg muscle weight (LMW), HW1, leg weight (LW), CW1, evisceration weight (EW), and semievisceration weight (SEW) (Fig. 1b), a weak correlation occurred between the CWe and the organ weights or fat weights
Summary
Maynard Smith and Haigh (1974) demonstrated that the occurrence and fixation of a selectively favorable mutation in a population will alter the frequencies of closely linked alleles. The frequency of alleles present in the chromosome where the original mutation occurs will increase, whereas the frequency of other alleles will decrease We call this the “hitch-hiking effect” because an allele can increase in frequency from selection acting on an adjacent allele (Smith and Haigh 1974). Current QTL mapping methods, such as linkage analysis (LA) and genome-wide association study (GWAS), are based on the LD in the flanking region of one allele to be selected. Polygenic adaptation is a process in which selection leads to a new or optimum phenotype by changing the frequencies of modest alleles. Polygenic adaptation can accelerate the genomic response to environmental changes, no selective signatures were produced (Pritchard et al 2010). A range of adaptive events led by polygenic adaptation are not detected by conventional methods (Pritchard and Anna 2010)
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