Weighted Single-Step GWAS Identified Candidate Genes Associated with Growth Traits in a Duroc Pig Population

Abstract

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.

A large‐scale genome‐wide association analysis reveals QTL and candidate genes for intramuscular fat content in Duroc pigs

“…Windows with an additive genetic variance >1% were presented in the results (Gao et al ., 2019; Ruan et al ., 2021), and consequently 19 genomic windows were highlighted as associated with IMF, together with 54 genes (Fig. 1 and Table 1).…”

Genome-wide association study identifying genetic variants associated with carcass backfat thickness, lean percentage and fat percentage in a four-way crossbred pig population using SLAF-seq technology

“…For complex traits, such as BFT, CLP and CFP, large-scale analysis is necessary to detect trait-associated SNPs. Genome-wide association study (GWAS) [13] represents a powerful approach to correlate SNPs and functional genes with quantitative traits, and has been widely applied in important economic traits of pigs, including carcass [14][15][16][17][18][19], meat quality [14,15,19,20], growth [15,21], immunity [22], and reproductive traits [23]. For species with larger genomes, such as pigs, the cost of GWAS using whole-genome sequencing (WGS) is still high at present.…”

Applications of Omics Technology for Livestock Selection and Improvement

“…The past three decades have seen tremendous advancements in molecular genetics that have provided a better genetic understanding of quantitative economic traits (Dekkers and Hospital 2002). A number of genes and gene combinations have been found to directly correlate with animal performance and production efficiency (Rexroad et al, 2019;Ruan et al, 2021). Many quantitative trait loci (QTL)-gene loci responsible for trait diversity-have been identified for various production and reproductive traits and used for selection and breeding decisions (Zhang et al, 2021;Al-Sharif et al, 2022).…”

“…More recently, with advancements in high throughput omics technologies, genome selection is becoming widely accepted for the selection of animals for breeding (Tan et al, 2017;Yang et al, 2020). The application of omics tools in livestock improvement may provide a more accurate technology for animal selection and breeding and therefore has become a hot spot of research (Pedrosa et al, 2021;Ruan et al, 2021). This manuscript provides an overview of various omics tools and technologies for their application in livestock selection and improvement programs.…”