A selective genotyping approach identifies QTL in a simulated population.

BACKGROUND: Identification of QTLs for important phenotypic traits, through the use of medium-density genome-wide SNP panels, is one of the most challenging areas in animal genetics, for preventing the time-consuming direct sequencing of putative candidate genes, when searching for the mutations that affect the trait. Appropriate statistical analyses allow the identification of genomic regions associated with the investigated trait in the genotyped population.

METHODS: The selective genotyping technique was applied to 1000 genotyped animals with known phenotype. Sliding windows composed of five consecutive SNPs were created for each chromosome; we assumed that the QTLs were encoded by the windows showing the highest difference in the frequency of the same alleles between the most divergent productive groups (the two tails of the distribution).

RESULTS: Ten windows affected at least one trait. For five of these windows, the highest and significant effect was given by one only SNP, which could therefore be taken as the QTL itself.

CONCLUSIONS: In this study we proposed a simple method to identify genomic regions associated to the phenotype under study. The identification of the DNA region is the first step to search for the mutation which is really responsible for the trait variability, through the direct sequencing of the genome regions that encode the QTL.