Fine mapping and single nucleotide polymorphism effects estimation on pig chromosomes 1, 4, 7, 8, 17 and X

André M Hidalgo,Débora M Paixão,Samuel R Paiva,Danielle A Faria,Simone E.F Guimarães,Fabyano F Silva,Paulo S Lopes,John W.M Bastiaansen

doi:10.1590/s1415-47572013000400009

Abstract

Fine mapping of quantitative trait loci (QTL) from previous linkage studies was performed on pig chromosomes 1, 4, 7, 8, 17, and X which were known to harbor QTL. Traits were divided into: growth performance, carcass, internal organs, cut yields, and meat quality. Fifty families were used of a F2 population produced by crossing local Brazilian Piau boars with commercial sows. The linkage map consisted of 237 SNP and 37 microsatellite markers covering 866 centimorgans. QTL were identified by regression interval mapping using GridQTL. Individual marker effects were estimated by Bayesian LASSO regression using R. In total, 32 QTL affecting the evaluated traits were detected along the chromosomes studied. Seven of the QTL were known from previous studies using our F2 population, and 25 novel QTL resulted from the increased marker coverage. Six of the seven QTL that were significant at the 5% genome-wide level had SNPs within their confidence interval whose effects were among the 5% largest effects. The combined use of microsatellites along with SNP markers increased the saturation of the genome map and led to smaller confidence intervals of the QTL. The results showed that the tested models yield similar improvements in QTL mapping accuracy.

Highlights

Quantitative trait loci (QTL) mapping efforts often result in detection of genomic regions that explain part of the quantitative trait variation
QTL analysis that were found in previous studies on this F2 population, and 25 novel QTL were detected by applying linkage analysis with the increased marker coverage
A QTL mapping study was carried out and QTL confidence intervals were inspected for harboring the positions of any of the top 5% single nucleotide polymorphism (SNP) by means of the Bayesian LASSO method

Summary

Introduction

Quantitative trait loci (QTL) mapping efforts often result in detection of genomic regions that explain part of the quantitative trait variation. These regions are usually so large that they do not allow accurate identification of the responsible genes or variants. By using single nucleotide polymorphism (SNP) in the analysis, the genome can be saturated with more markers and the interval of these QTL may become narrowed. Making QTL regions as small as possible is a first step in the process towards the identification of the relevant gene(s) and the respective causative mutation(s). Previous studies from our research group were conducted on the same population and detected QTL by means of microsatellite markers. A combined total of 40 QTL for growth performance, meat quality, internal organs, cut yield, and carcass composition were found in studies by Paixão et al (2008, 2012, 2013), Silva et al (2008), and

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