Trends of genetic changes uncovered by Env- and Eigen-GWAS in wheat and barley

Rajiv Sharma,James Cockram,Luke Ramsay,Joanne Russell,Keith A Gardner,Ian J Mackay,William T B Thomas,Donal M O’Sullivan,Wayne Powell

doi:10.1007/s00122-021-03991-z

Abstract

Key messageVariety age and population structure detect novel QTL for yield and adaptation in wheat and barley without the need to phenotype.The process of crop breeding over the last century has delivered new varieties with increased genetic gains, resulting in higher crop performance and yield. However, in many cases, the alleles and genomic regions underpinning this success remain unknown. This is partly due to the difficulty of generating sufficient phenotypic data on large numbers of historical varieties to enable such analyses. Here we demonstrate the ability to circumvent such bottlenecks by identifying genomic regions selected over 100 years of crop breeding using age of a variety as a surrogate for yield. Rather than collecting phenotype data, we deployed ‘environmental genome-wide association scans’ (EnvGWAS) based on variety age in two of the world’s most important crops, wheat and barley, and detected strong signals of selection across both genomes. EnvGWAS identified 16 genomic regions in barley and 10 in wheat with contrasting patterns between spring and winter types of the two crops. To further examine changes in genome structure, we used the genomic relationship matrix of the genotypic data to derive eigenvectors for analysis in EigenGWAS. This detected seven major chromosomal introgressions that contributed to adaptation in wheat. EigenGWAS and EnvGWAS based on variety age avoid costly phenotyping and facilitate the identification of genomic tracts that have been under selection during breeding. Our results demonstrate the potential of using historical cultivar collections coupled with genomic data to identify chromosomal regions under selection and may help guide future plant breeding strategies to maximise the rate of genetic gain and adaptation.

Highlights

In the last century, significant improvements in yield and quality have been reported in almost all crop species as a result of plant breeding driven by market demand (Fischer and Edmeades 2010)
We demonstrate for the first time the utility of treating variety age as a surrogate trait for crop productivity when combined with environmental genome-wide association scans’ (EnvGWAS) and EigenGWAS to identify target regions and quantitative trait loci (QTL) underpinning genetic improvements in crop performance that have occurred during modern plant breeding
We found that the three major genomic regions previously identified by EnvGWAS of variety age on chromosomes 1A, 2A and 6A were significant in the multi-parent advanced generation inter cross (MAGIC) population for several yield and grain-related traits as well as for agronomic traits (Supplementary Table S4)

Summary

Introduction

Significant improvements in yield and quality have been reported in almost all crop species as a result of plant breeding driven by market demand (Fischer and Edmeades 2010). Food, feed and fibre to meet the expanding global human population requires an acceleration in the pace of crop genetic improvement (Varshney et al 2018). Identification of the genetic loci responsible for these changes will help accelerate the genetic gains required to meet future food security needs, via their incorporation in marker-assisted selection breeding strategies (Chiurugwi et al 2019). GWAS require trait data on large collections of varieties or accessions, which are typically expensive to collect and can result in underpowered studies with relatively low numbers of lines (Macarthur 2012; Mackay et al 2019). An alternative is to exploit the availability of historical data, such as that collected during varietal development programmes

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Conclusion