Genome-wide Association Studies For Hematological Traits And Visualization Of The Mapping Results In Chinese Sutai Pigs

Part I: It has been shown that hematological traits are strongly associated with themetabolism and the immune system in domestic pig. However, little is known about thegenetic architecture of hematological traits. To identify quantitative trait loci (QTL)controlling hematological traits, we performed single marker Genome-wide associationstudies (GWAS) and haplotype analysis for15hematological traits in495Chinese Sutai pigs.We identified161significant SNPs including44genome-wide significant SNPsassociated with11hematological traits by single marker GWAS. Most of them were locatedon SSC2. Meanwhile, we detected499significant SNPs containing154genome-widesignificant SNPs associated with9hematological traits by haplotype analysis. Most of theidentified loci were located on SSC7and SSC9.We detected4SNPs with pleiotropic effects on SSC2by single marker GWAS and (or)on SSC7by haplotype analysis. Furthermore, through checking the gene functionalannotations, positions and their expression variation, we finally selected7genes as potentialcandidates. Specially, we found that three genes (TRIM58, TRIM26and TRIM21) of themoriginated from the same gene family and executed similar function of innate and adaptiveimmune. The findings will contribute to dissection the immune gene network, furtheridentification of causative mutations underlying the identified QTLs and providing insightsinto the molecular basis of hematological trait in domestic pig.BMC genetics,2014.15(1)Part II: Genome-wide association studies (GWAS) have revealed hundreds of lociassociated with genetic diseases and traits in pig. Combining additional biologicalinformation (such as local linkage disequilibrium (LD), recombination patterns, SNPsannotations and the structures and positions of genes in the region of interesting) for theidentified top SNPs would benefit potential causal locus identification. However, it is a greatchallenge to integrate all these information together for visualization. We implemented an Rpackage, RPARP, to simultaneously extract/calculate the LD, recombination rate andannotated gene in target region in GWAS study of pig from all different kinds of database,and then automatically produce a graph for profile or information visualization. Thereference genome can be either Duroc or Wuzhishan pig (WZSP) based on the researcher’spopulation. The RPARP package only requires one necessary GWAS result containing thename and P-value of SNPs, and then the package will automatically combine all otherinformation to produce the publication quality graphics. It is very easy and convenient touse, and also allows you to draw personally figures by assigning special parameters.We also show the utility of the simple and flexible RPARP by plotting a real exampleGWAS example of mean corpuscular volume (MCV) in Zhang et.al. It can fast,comprehensively and user-friendly display regional information by different optional feature.