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. 2008 Nov 7:9:70.
doi: 10.1186/1471-2156-9-70.

Polymorphisms of the IGF1R gene and their genetic effects on chicken early growth and carcass traits

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Polymorphisms of the IGF1R gene and their genetic effects on chicken early growth and carcass traits

Mingming Lei et al. BMC Genet. .

Abstract

Background: The insulin-like growth factor I receptor (IGF1R) has an important effect on growth, carcass, and meat quality traits in many species. However, few studies on associations of the IGF1R gene with growth and carcass traits have been reported in chickens. The objectives of the present study were to study the associations of the IGF1R gene with chicken early growth and carcass traits using a neutral test, variation scan of the gene, genetic diversity, linkage disequilibrium and association analyses.

Results: The tree generated from the amino acid sequences of 15 species showed that the IGF1R gene was conservative in the whole evolution among the mammalian animals and chickens. In a total of 10,818 bp of sequence, 70 single nucleotide polymorphisms were identified in the chicken IGF1R gene. The allelic and genotypic frequency distribution, genetic diversity and linkage disequilibrium of 18 single nucleotide polymorphisms (SNPs) in the Xinghua and White Recessive Rock chickens showed that six of them were possibly associated with growth traits. Association analyses showed that the A17299834G SNP was significantly associated with chicken carcass body weight, eviscerated weight with giblets, eviscerated weight, body weights at 28, 35, and 56 d of age, leg length at 56 d of age, and daily weight gain at 0-4 weeks. The haplotypes of the A17307750G and A17307494G were associated with early growth traits. The haplotypes of the A17299834G and C17293932T were significantly associated with most of the early growth traits and carcass traits.

Conclusion: There were rich polymorphisms in the chicken IGF1R gene. Several SNPs associated with chicken early growth traits and carcass traits were identified in the IGF1R gene by genetic diversity, linkage disequilibrium, and association analyses in the present study.

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Figures

Figure 1
Figure 1
The ω value and UPGMA tree from CODEML arithmetic.

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