Genome-wide Association Study of Porcine Hematological Parameters in a Large White × Minzhu F2 Resource Population

Abstract

Hematological traits, which are important indicators of immune function in animals, have been commonly examined as biomarkers of disease and disease severity in humans and animals. Genome-wide significant quantitative trait loci (QTLs) provide important information for use in breeding programs of animals such as pigs. QTLs for hematological parameters (hematological traits) have been detected in pig chromosomes, although these are often mapped by linkage analysis to large intervals making identification of the underlying mutation problematic. Single nucleotide polymorphisms (SNPs) are the common form of genetic variation among individuals and are thought to account for the majority of inherited traits. In this study, a genome-wide association study (GWAS) was performed to detect regions of association with hematological traits in a three-generation resource population produced by intercrossing Large White boars and Minzhu sows during the period from 2007 to 2011. Illumina PorcineSNP60 BeadChip technology was used to genotype each animal and seven hematological parameters were measured (hematocrit (HCT), hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), mean corpuscular volume (MCV), red blood cell count (RBC) and red blood cell volume distribution width (RDW)). Data were analyzed in a three step Genome-wide Rapid Association using the Mixed Model and Regression-Genomic Control (GRAMMAR-GC) method. A total of 62 genome-wide significant and three chromosome-wide significant SNPs associated with hematological parameters were detected in this GWAS. Seven and five SNPs were associated with HCT and HGB, respectively. These SNPs were all located within the region of 34.6-36.5 Mb on SSC7. Four SNPs within the region of 43.7-47.0 Mb and fifty-five SNPs within the region of 42.2-73.8 Mb on SSC8 showed significant association with MCH and MCV, respectively. At chromosome-wide significant level, one SNP at 29.2 Mb on SSC1 and two SNPs within the region of 26.0-26.2 Mb were found to be significantly associated with RBC and RDW, respectively. Many of the SNPs were located within previously reported QTL regions and appeared to narrow down the regions compared with previously described QTL intervals. In current research, a total of seven significant SNPs were found within six candidate genes SCUBE3, KDR, TDO, IGFBP7, ADAMTS3 and AFP. In addition, the KIT gene, which has been previously reported to relate to hematological parameters, was located within the region significantly associated with MCH and MCV and could be a candidate gene. These results of this study may lead to a better understanding of the molecular mechanisms of hematological parameters in pigs.

Genome-Wide Copy Number Variations Inferred from SNP Genotyping Arrays Using a Large White and Minzhu Intercross Population

“…In our previous studies, genome-wide association studies (GWAS) with meat quality, production and health traits were performed using the same population [24], [25]. Combining analyses found that a total number of 27, 22, 4, 3, 10, 3, and 2 genome-wide significant SNPs associated with intramuscular fat (IMF), marbling, moisture, color score, lean meat in ham, lean meat weight, and mean corpuscular volume (MCV), respectively (Table S8–S14 in File S1), were located in 6 CNVRs identified in this study.…”

“…A little program named overlapping was written by Visual Basic to retrieve the QTLs within the CNVRs from the pig QTLdb (http://www.animalgenome.org/cgi-bin/QTLdb/SS/index). Some of the GWAS data we used in this paper was retrieved from the paper of LUO et al [24]; the others were calculated using the method reported in the paper of LUO et al [24], [25]. All gene positions were transformed to fit the style of Ensembl Genes 64.…”

“…In the present study, weconstructed a Large White × Minzhu intercross population and measured various traits [24], [25]. Each individual was genotyped using an Illumina PorcineSNP60 Beadchip.…”

Genome-Wide Association Study Reveals Constant and Specific Loci for Hematological Traits at Three Time Stages in a White Duroc × Erhualian F2 Resource Population

“…Compared to traditional QTL mapping strategies, GWAS based on high-density markers is a more powerful tool to identify genomic regions for phenotypic traits. To our knowledge, only two very recent studies have reported the GWAS for hematological parameters in pigs [15], [16]. The two studies identified 10 and 62 genome-wide significant loci for hematological traits.…”

It's more than stamp collecting: how genome sequencing can unify biological research

“…Genome-wide association studies (GWAS) based on SNP, exome, and genome sequencing of cohorts have contributed to our understanding of complex disease genetics identifying over 15,000 regions associated with the majority of common human diseases [11]. GWAS is also applicable to quantitative traits in non-model species including crops [12] and farm animals for agricultural traits such as fertility and milk production [13, 14]. Single-cell sequencing and alignment of resultant short reads to the human reference has primarily been used to understand how mutation variation and mutant cell lineage within human tumors affects cancer treatment [15].…”