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. 2007 Oct;38(5):491-8.
doi: 10.1111/j.1365-2052.2007.01642.x.

Genome-wide association analysis reveals cryptic alleles as an important factor in heterosis for fatness in chicken F2 population

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Genome-wide association analysis reveals cryptic alleles as an important factor in heterosis for fatness in chicken F2 population

B Abasht et al. Anim Genet. 2007 Oct.

Abstract

Genome-wide association studies have become possible in the chicken because of the recent availability of the complete genome sequence, a polymorphism map and high-density single nucleotide polymorphism (SNP) genotyping platforms. We used these tools to study the genetic basis of a very high level of heterosis that was previously observed for fatness in two F(2) populations established by crossing one outbred broiler (meat-type) sire with dams from two unrelated, highly inbred, light-bodied lines (Fayoumi and Leghorn). In each F(2) population, selective genotyping was carried out using phenotypically extreme males for abdominal fat percentage (AF) and about 3000 SNPs. Single-point association analysis of about 500 informative SNPs per cross showed significant association (P < 0.01) of 15 and 24 markers with AF in the Broiler x Fayoumi and Broiler x Leghorn crosses respectively. These SNPs were on 10 chromosomes (GGA1, 2, 3, 4, 7, 8, 10, 12, 15 and 27). Interestingly, of the 39 SNPs that were significantly associated with AF, there were about twice as many homozygous genotypes associated with higher AF that traced back to the inbred lines alleles, although the broiler line had on average higher AF. These SNPs are considered to be associated with QTL with cryptic alleles. This study reveals cryptic alleles as an important factor in heterosis for fatness observed in two chicken F(2) populations, and suggests epistasis as the common underlying mechanism for heterosis and cryptic allele expression. The results of this study also demonstrate the power of high marker-density SNP association studies in discovering QTL that were not detected by previous microsatellite-based genotyping studies.

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