SNP- and haplotype-based genome-wide association studies for growth, carcass, and meat quality traits in a Duroc multigenerational populationReportar como inadecuado




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BMC Genetics

, 17:60

Complex traits and quantitative genetics

Abstract

BackgroundThe aim of the present study was to compare the power of single nucleotide polymorphism SNP-based genome-wide association study GWAS and haplotype-based GWAS for quantitative trait loci QTL detection, and to detect novel candidate genes affecting economically important traits in a purebred Duroc population comprising seven-generation pedigree. First, we performed a simulation analysis using real genotype data of this population to compare the power based on the null hypothesis of the two methods. We then performed GWAS using both methods and real phenotype data comprising 52 traits, which included growth, carcass, and meat quality traits.

ResultsIn total, 836 animals were genotyped using the Illumina PorcineSNP60 BeadChip and 14 customized SNPs from regions of known candidate genes related to the traits of interest. The power of SNP-based GWAS was greater than that of haplotype-based GWAS in a simulation analysis. In real data analysis, a larger number of significant regions was obtained by SNP-based GWAS than by haplotype-based GWAS. For SNP-based GWAS, 23 genome-wide significant SNP regions were detected for 17 traits, and 120 genome-wide suggestive SNP regions were detected for 27 traits. For haplotype-based GWAS, 6 genome-wide significant SNP regions were detected for four traits, and 11 genome-wide suggestive SNP regions were detected for eight traits. All genome-wide significant SNP regions detected by haplotype-based GWAS were located in regions also detected by SNP-based GWAS. Four regions detected by SNP-based GWAS were significantly associated with multiple traits: on Sus scrofa chromosome SSC 1 at 304 Mb; and on SSC7 at 35–39 Mb, 41–42 Mb, and 103 Mb. The vertnin gene VRTN in particular, was located on SSC7 at 103 Mb and was significantly associated with vertebrae number and carcass lengths. Mapped QTL regions contain some candidate genes involved in skeletal formation FUBP3; far upstream element binding protein 3 and fat deposition METTL3; methyltransferase like 3.

ConclusionOur results show that a multigenerational pig population is useful for detecting QTL, which are typically segregated in a purebred population. In addition, a novel significant region could be detected by SNP-based GWAS as opposed to haplotype-based GWAS.

KeywordsDuroc pigs Haplotype-based GWAS Known candidate genes Production traits SNP-based GWAS AbbreviationsASAP1ArfGAP with SH3 domain, ankyrin repeat, and PH domain 1

BLUPbest liner unbiased prediction

CNVcopy number variant

DEF-1differentiation-enhancing factor

DGaverage daily gain

FUBP3far upstream element FUSE binding protein 3

GEMMAgenome-wide efficient mixed-model association

GWASgenome-wide association study

HIPK2homeodomain-interacting protein kinase 2

LDlinkage disequilibrium

LEPRleptin receptor

LIMLin-11, IsI-I, and Mec3

MAFminor allele frequency

METTL3methyltransferase like 3

miR-33microRNA-33

mAN-methyladenosine

QTLquantitative trait locus

SCDstearoyl-CoA desaturase

SNPsingle nucleotide polymorphism

SSCSus Scrofa chromosome

TPK1thiamine pyrophosphokinase

TPPthiamine pyrophosphate

TREM2triggering receptor expressed on myeloid cells 2

VRTNvertnin

ZNF281zinc finger protein 281

ZYXzyxin

Electronic supplementary materialThe online version of this article doi:10.1186-s12863-016-0368-3 contains supplementary material, which is available to authorized users.

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