Literature DB >> 18704695

Genome-wide association analysis in domestic animals: a powerful approach for genetic dissection of trait loci.

Leif Andersson1.   

Abstract

Domestic animals have a sufficiently old history (thousands of generations) to allow evolution of phenotypes, but also a sufficiently young history (approximately 10,000 years) to allow powerful genetic dissection of phenotypic diversity. Domestic animals are therefore a unique resource for exploring genotype-phenotype relationships. Quantitative Trait Locus (QTL) mapping has been very successful in domestic animals but the identification of Quantitative Trait Mutations (QTMs) has been hard although a few prominent success histories have been reported. Genome-wide association analysis is now emerging as a powerful method for high-resolution mapping of loci controlling phenotypic traits in domestic animals. In two recent proof-of-principle studies we have used this approach to identify the mutations underlying two monogenic trait loci in dogs, white spotting and the hair ridge in Ridgeback dogs. In each case, we used only about 10 cases and 10 controls and mapped the locus to a region of about one mega base pair. In both cases the underlying mutations were non-coding underscoring the significance of regulatory mutations as a source for phenotypic diversity. Furthermore, we were able to shed light on the evolution of the allelic series at the white spotting (S) locus in dogs which encodes the microphthalmia-associated transcription factor (MITF). Our data showed that the three variant alleles described at this locus (Irish spotting, piebald and extreme white) do not represent three independent mutations but rather different combinations of a set of regulatory mutations affecting MITF expression. This is an excellent illustration of how the characterization of alleles selected during animal domestication contributes to an improved understanding of genotype-phenotype relationships.

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Year:  2008        PMID: 18704695     DOI: 10.1007/s10709-008-9312-4

Source DB:  PubMed          Journal:  Genetica        ISSN: 0016-6707            Impact factor:   1.082


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