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

Luigi Ricciardi,Stefano Pavan,Elena Ciani,Nunzio D’Agostino,Concetta Lotti,Chiara Delvento

doi:10.3389/fgene.2020.00447

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.

Highlights

High-throughput genotyping, which leads to the identification of a large number of singlenucleotide polymorphisms (SNPs) is boosting the implementation of genome-wide association studies (GWAS), linking DNA variants to phenotypes of interest (Taranto et al, 2018)
For application in GWAS, widely adopted genotyping options fall into three categories: whole genome resequencing (WGR), reduced representation sequencing (RRS), and single-nucleotide polymorphisms (SNPs) arrays
WGR and RRS are based on next-generation sequencing (NGS) technologies and bioinformatics pipelines that align reads to a reference genome and call both SNPs and genotypes (Nielsen et al, 2011)

Summary

Introduction

High-throughput genotyping, which leads to the identification of a large number of singlenucleotide polymorphisms (SNPs) is boosting the implementation of genome-wide association studies (GWAS), linking DNA variants to phenotypes of interest (Taranto et al, 2018). GWAS enabled the mapping of genomic loci associated with economically important traits, including yield, resistance to biotic and abiotic stresses, and quality (Boyles et al, 2016; Pavan et al, 2017; Hou et al, 2018; Liu et al, 2018; He et al, 2019). This information has been further used to perform marker-assisted selection (MAS) in breeding programs and discover genes underlying phenotypic variation (Liu and Yan, 2019). Choosing the most appropriate (cost-effective) genotyping method for crop GWAS requires careful examination of several aspects, namely, the purpose and the scale of the study, cropspecific genomic features, and technical and economic matters associated with each genotyping method

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Conclusion