Gametic phase disequilibrium between the syntenic multiallelic HTG4 and HMS3 markers widely used for parentage testing in Thoroughbred horses

Validation of parentage and horse breed registries through DNA typing relies on estimates of random match probabilities with DNA profiles generated from multiple polymorphic loci. Of the twenty-seven microsatellite loci recommended by the International Society for Animal Genetics for parentage testing in Thoroughbred horses, eleven are located on five chromosomes. An important aspect in determining combined exclusion probabilities is the ascertainment of the genetic linkage status of syntenic markers, which may affect reliable use of the product rule in estimating random match probabilities. In principle, linked markers can be in gametic phase disequilibrium (GD). We aimed at determining the extent, by frequency and strength, of GD between the HTG4 and HMS3 multiallelic loci, syntenic on chromosome 9. We typed the qualified offspring (n (1) = 27; n (2) = 14) of two Quarter Bred stallions (registered by the Brazilian Association of Quarter Horse Breeders) and 121 unrelated horses from the same breed. In the 41 informative meioses analyzed, the frequency of recombination between the HTG4 and HMS3 loci was 0.27. Consistent with genetic map distances, this recombination rate does not fit to the theoretical distribution for independently segregated markers. We estimated sign-based D' coefficients as a measure of GD, and showed that the HTG4 and HMS3 loci are in significant, yet partial and weak, disequilibrium, with two allele pairs involved (HTG4*M/HMS3*P, D'(+) = 0.6274; and HTG4*K/HMS3*P, D'(-) = -0.6096). These results warn against the inadequate inclusion of genetically linked markers in the calculation of combined power of discrimination for Thoroughbred parentage validation.

Gene by environment QTL mapping through multiple trait analyses in blood pressure salt-sensitivity: identification of a novel QTL in rat chromosome 5

Background The genetic mechanisms underlying interindividual blood pressure variation reflect the complex interplay of both genetic and environmental variables. The current standard statistical methods for detecting genes involved in the regulation mechanisms of complex traits are based on univariate analysis. Few studies have focused on the search for and understanding of quantitative trait loci responsible for gene × environmental interactions or multiple trait analysis. Composite interval mapping has been extended to multiple traits and may be an interesting approach to such a problem. Methods We used multiple-trait analysis for quantitative trait locus mapping of loci having different effects on systolic blood pressure with NaCl exposure. Animals studied were 188 rats, the progenies of an F2 rat intercross between the hypertensive and normotensive strain, genotyped in 179 polymorphic markers across the rat genome. To accommodate the correlational structure from measurements taken in the same animals, we applied univariate and multivariate strategies for analyzing the data. Results We detected a new quantitative train locus on a region close to marker R589 in chromosome 5 of the rat genome, not previously identified through serial analysis of individual traits. In addition, we were able to justify analytically the parametric restrictions in terms of regression coefficients responsible for the gain in precision with the adopted analytical approach. Conclusion Future work should focus on fine mapping and the identification of the causative variant responsible for this quantitative trait locus signal. The multivariable strategy might be valuable in the study of genetic determinants of interindividual variation of antihypertensive drug effectiveness.