Weighted Single-Step GWAS Identified Candidate Genes Associated with Growth Traits in a Duroc Pig Population.
Donglin RuanZhanwei ZhuangRongrong DingYibin QiuShenping ZhouJie WuCineng XuLinjun HongSixiu HuangEnqin ZhengGengyuan CaiZhenfang WuJie YangPublished in: Genes (2021)
Growth traits are important economic traits of pigs that are controlled by several major genes and multiple minor genes. To better understand the genetic architecture of growth traits, we performed a weighted single-step genome-wide association study (wssGWAS) to identify genomic regions and candidate genes that are associated with days to 100 kg (AGE), average daily gain (ADG), backfat thickness (BF) and lean meat percentage (LMP) in a Duroc pig population. In this study, 3945 individuals with phenotypic and genealogical information, of which 2084 pigs were genotyped with a 50 K single-nucleotide polymorphism (SNP) array, were used for association analyses. We found that the most significant regions explained 2.56-3.07% of genetic variance for four traits, and the detected significant regions (>1%) explained 17.07%, 18.59%, 23.87% and 21.94% for four traits. Finally, 21 genes that have been reported to be associated with metabolism, bone growth, and fat deposition were treated as candidate genes for growth traits in pigs. Moreover, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses implied that the identified genes took part in bone formation, the immune system, and digestion. In conclusion, such full use of phenotypic, genotypic, and genealogical information will accelerate the genetic improvement of growth traits in pigs.
Keyphrases
- genome wide
- dna methylation
- copy number
- magnetic resonance
- genome wide association study
- genome wide identification
- gene expression
- healthcare
- adipose tissue
- mass spectrometry
- physical activity
- epstein barr virus
- genome wide analysis
- bioinformatics analysis
- postmenopausal women
- network analysis
- optical coherence tomography
- transcription factor