Accelerated deciphering of the genetic architecture of agricultural economic traits in pigs using a low-coverage whole-genome sequencing strategy

Abstract

Background Uncovering the genetic architecture of economic traits in pigs is important for agricultural breeding. However, high-density haplotype reference panels are unavailable in most agricultural species, limiting accurate genotype imputation in large populations. Moreover, the infinitesimal model of quantitative traits implies that weak association signals tend to be spread across most of the genome, further complicating the genetic analysis. Hence, there is a need to develop new methods for sequencing large cohorts without large reference panels. Results We describe a Tn5-based highly accurate, cost- and time-efficient, low-coverage sequencing method to obtain 11.3 million whole-genome single-nucleotide polymorphisms in 2,869 Duroc boars at a mean depth of 0.73×. On the basis of these single-nucleotide polymorphisms, a genome-wide association study was performed, resulting in 14 quantitative trait loci (QTLs) for 7 of 21 important agricultural traits in pigs. These QTLs harbour genes, such as ABCD4 for total teat number and HMGA1 for back fat thickness, and provided a starting point for further investigation. The inheritance models of the different traits varied greatly. Most follow the minor-polygene model, but this can be attributed to different reasons, such as the shaping of genetic architecture by artificial selection for this population and sufficiently interconnected minor gene regulatory networks. Conclusions Genome-wide association study results for 21 important agricultural traits identified 14 QTLs/genes and showed their genetic architectures, providing guidance for genetic improvement harnessing genomic features. The Tn5-based low-coverage sequencing method can be applied to large-scale genome studies for any species without a good reference panel and can be used for agricultural breeding.

Cost-effectively dissecting the genetic architecture of complex wool traits in rabbits by low-coverage sequencing

“…At a sequencing depth of 1.0X, the high imputation accuracy by BaseVar + STITCH could be reached and remain stable with genotypic concordance >98.84% and genotypic accuracy >0.97 when a sample size was larger than 300. The patterns of imputation accuracy in different strategies and with several levels of sequencing coverages and sample sizes in this study are in line with previous studies (Davies et al, 2016, Yang et al, 2021, Zhao et al, 2021b).…”

Assessment of the performance of different imputation methods for low-coverage sequencing in Holstein cattle

“…This strategy is more pronounced for species without commercially available SNP array (Buerkle and Gompert, 2013). The LCS is a cost-effective strategy for getting whole-genome variants (Pasaniuc et al, 2012;VanRaden et al, 2015;Gilly et al, 2019;Davies et al, 2021) and has been successfully applied in GWAS, genomic prediction, and population genetics analysis in human (Cai et al, 2015;Gilly et al, 2016;Liu et al, 2018), mice (Nicod et al, 2016), pig (Yang et al, 2021), coral (Fuller et al, 2020), large yellow croaker (Zhang et al, 2021), and maize (Zheng et al, 2018).…”

“…It is based on a Hidden Markov model and adapts to the fact that SNPs in sequences are not independent of each other. Thus far, these imputation methods have been successfully applied to LCS data in human and other species (Davies et al, 2016;Nicod et al, 2016;Liu et al, 2018;Jiang et al, 2021;Yang et al, 2021;Zhang et al, 2021), but whether they are suitable for livestock, especially Holstein cattle, has received less attention.…”

Genome-Wide Association Study Identified a Quantitative Trait Locus and Two Candidate Genes on Sus scrofa Chromosome 2 Affecting Vulvar Traits of Suhuai Pigs

“…Recently, genome-wide association studies (GWAS) characterized by a high density of single nucleotide polymorphism (SNP) markers have been widely used to identify genetic mutations and QTLs for various traits, especially reproductive traits with low heritability. A large number of SNPs which are significantly related to reproductive traits, such as teat number [ 4 ], litter size [ 5 ] and sperm quality [ 6 ], have been detected. Up to date, few studies on the vulvar traits of pigs were reported and few QTLs related to the vulvar traits of pigs have been identified at the genome-wide level based on the public database of QTLdb ( (accessed on 1 June 2022)).…”