Recommendations for Choosing the Genotyping Method and Best Practices for Quality Control in Crop Genome-Wide Association Studies

Abstract

High-throughput genotyping boosts genome-wide association studies (GWAS) in crop species, leading to the identification of single-nucleotide polymorphisms (SNPs) associated with economically important traits. Choosing a cost-effective genotyping method for crop GWAS requires careful examination of several aspects, namely, the purpose and the scale of the study, crop-specific genomic features, and technical and economic matters associated with each genotyping option. Once genotypic data have been obtained, quality control (QC) procedures must be applied to avoid bias and false signals in genotype-phenotype association tests. QC for human GWAS has been extensively reviewed; however, QC for crop GWAS may require different actions, depending on the GWAS population type. Here, we review most popular genotyping methods based on next-generation sequencing (NGS) and array hybridization, and report observations that should guide the investigator in the choice of the genotyping method for crop GWAS. We provide recommendations to perform QC in crop species, and deliver an overview of bioinformatics tools that can be used to accomplish all needed tasks. Overall, this work aims to provide guidelines to harmonize those procedures leading to SNP datasets ready for crop GWAS.

Almond diversity and homozygosity define structure, kinship, inbreeding, and linkage disequilibrium in cultivated germplasm, and reveal genomic associations with nut and seed weight

“…So far, studies aiming at the characterization of the almond genetic structure used a few simple sequence repeat (SSR) markers [5][6][7][8][9] . Nowadays, high-throughput genotyping methods, such as genotyping-by-sequencing (GBS), are routinely applied in agrigenomics research for the fine-scale characterization of genetic structure with thousands of single-nucleotide polymorphism (SNP) markers [10][11][12] .…”

“…The recent publication of the almond genome sequence 28,29 provides the opportunity to carry out genome-wide association studies (GWASs), identifying associations between phenotypes and markers with the known chromosomal locations. Information on the average linkage disequilibrium (LD) decay in the organism on which a GWAS is performed is of main importance, as this parameter influences, for a given number of markers, the chance to reveal significant associations 12,30 . In addition, rapid LD decay increases the possibility that GWAS experiments lead to the identification of marker loci residing within, or in the proximity of, genes causally related to the phenotype.…”

Concordance rate in cattle and sheep between genotypes differing in Illumina GenCall quality score

“…Many approaches and thresholds to quality control of genomic data have been proposed in studies relating to humans (Grove et al 2013;Coleman et al 2016), plants (Pavan et al 2020), cattle (Wiggans et al 2012;Purfield et al 2016;McClure et al 2018), and sheep (Auvray et al 2014;Berry et al 2019). These metrics include minimum sample (Cooper et al 2013;Berry et al 2016;Purfield et al 2016) and single nucleotide polymorphism (SNP) call rate (Auvray et al 2014;Zhao et al 2015;Berry et al 2019), the extent of heterozygosity (Erbe et al 2012;Meredith et al 2013;Pavan et al 2020), genotype clustering score (Zhao et al 2015;Judge et al 2016;Bouwman et al 2018;Berry et al 2019), as well as parent-offspring genotype concordance rate (Wiggans et al 2012;Zhao et al 2015;Berry et al 2019;O'Brien et al 2019). A minimum threshold on minor allele frequency (Erbe et al 2012;Coleman et al 2016;Purfield et al 2020) as well as deviation of the (sub-)population genotype frequency from Hardy-Weinberg equilibrium (Coleman et al 2016;O'Brien et al 2019;Pavan et al 2020) have also been undertaken.…”

“…These metrics include minimum sample (Cooper et al 2013;Berry et al 2016;Purfield et al 2016) and single nucleotide polymorphism (SNP) call rate (Auvray et al 2014;Zhao et al 2015;Berry et al 2019), the extent of heterozygosity (Erbe et al 2012;Meredith et al 2013;Pavan et al 2020), genotype clustering score (Zhao et al 2015;Judge et al 2016;Bouwman et al 2018;Berry et al 2019), as well as parent-offspring genotype concordance rate (Wiggans et al 2012;Zhao et al 2015;Berry et al 2019;O'Brien et al 2019). A minimum threshold on minor allele frequency (Erbe et al 2012;Coleman et al 2016;Purfield et al 2020) as well as deviation of the (sub-)population genotype frequency from Hardy-Weinberg equilibrium (Coleman et al 2016;O'Brien et al 2019;Pavan et al 2020) have also been undertaken. While some of the thresholds imposed are based on empirical evidence (Cooper et al 2013;Eldriss et al 2013b;Purfield et al 2016), others are not.…”

“…2019; Pavan et al . 2020) have also been undertaken. While some of the thresholds imposed are based on empirical evidence (Cooper et al .…”