Bayesian GWAS and network analysis revealed new candidate genes for number of teats in pigs

Abstract

The genetic improvement of reproductive traits such as the number of teats is essential to the success of the pig industry. As opposite to most SNP association studies that consider continuous phenotypes under Gaussian assumptions, this trait is characterized as a discrete variable, which could potentially follow other distributions, such as the Poisson. Therefore, in order to access the complexity of a counting random regression considering all SNPs simultaneously as covariate under a GWAS modeling, the Bayesian inference tools become necessary. Currently, another point that deserves to be highlighted in GWAS is the genetic dissection of complex phenotypes through candidate genes network derived from significant SNPs. We present a full Bayesian treatment of SNP association analysis for number of teats assuming alternatively Gaussian and Poisson distributions for this trait. Under this framework, significant SNP effects were identified by hypothesis tests using 95% highest posterior density intervals. These SNPs were used to construct associated candidate genes network aiming to explain the genetic mechanism behind this reproductive trait. The Bayesian model comparisons based on deviance posterior distribution indicated the superiority of Gaussian model. In general, our results suggest the presence of 19 significant SNPs, which mapped 13 genes. Besides, we predicted gene interactions through networks that are consistent with the mammals known breast biology (e.g., development of prolactin receptor signaling, and cell proliferation), captured known regulation binding sites, and provided candidate genes for that trait (e.g., TINAGL1 and ICK).

Genomic prediction for additive and dominance effects of censored traits in pigs

“…These SNPs were selected according to QTL positions that were previously identified in this population using meta-analyses and fine mapping (Verardo et al, 2015). Therefore, although a small number of markers were used, the customized SNPchip based on previously identified QTL positions ensures appropriate coverage of the relevant genome regions in this population.…”

Identification of novel candidate genes for the inverted teat defect in sows using a genome-wide marker panel

“…QTLs for the number of teats have previously been reported across all autosomes and a total of 167 QTLs for the total number of teats, ten QTLs for the number of teats on the left side and seven QTLs for the number of teats on the right side have been assembled on the PigQTL database (Hu et al 2013, 2016). Especially recent genome-wide association studies have added more significant markers to the database (Arakawa et al 2015; Duijvesteijn et al 2014; Hernandez et al 2014; Verardo et al 2014). We extracted the information on traits and QTL positions from the PigQTL database to compare the results with our findings (Supplementary files).…”

The optimal number of partial least squares components in genomic selection for pork pH

“…These SNPs were selected according to QTL positions previously identified for this population using meta-analyses and fine mapping (HIDALGO et al, 2013;VERARDO et al, 2015). Thus, although a small number of markers were used, this customized SNPchip ensured an appropriate coverage of the relevant genomic regions in this population.…”