Abstract

The task of identifying genomic regions conferring yield stability is challenging in any crop and requires large experimental data sets in conjunction with complex analytical approaches. We report findings of a first attempt to identify genomic regions with stable expression and their individual epistatic interactions for grain yield and yield stability in a large elite panel of wheat under multiple environments via a genome wide association mapping (GWAM) approach. Seven hundred and twenty lines were genotyped using genotyping-by-sequencing technology and phenotyped for grain yield and phenological traits. High gene diversity (0.250) and a moderate genetic structure (five groups) in the panel provided an excellent base for GWAM. The mixed linear model and multi-locus mixed model analyses identified key genomic regions on chromosomes 2B, 3A, 4A, 5B, 7A and 7B. Further, significant epistatic interactions were observed among loci with and without main effects that contributed to additional variation of up to 10%. Simple stepwise regression provided the most significant main effect and epistatic markers resulting in up to 20% variation for yield stability and up to 17% gain in yield with the best allelic combination.

Highlights

  • Yield and yield components in irrigated or stress environments[12,13,14,15,16,17,18], hitherto no study has reported genomic regions associated with yield stability using this approach

  • Previous association studies in wheat have been conducted using gene bank accessions including lines of different geographic origin and adaptions to distinct environments[14,22,23]. The use of such panels maximizes the genetic diversity and reduces the population structure which is ideal for GWAM, but for quantitative traits such as yield, multiple, small effect marker-trait associations (MTA) are difficult to be directly applied in breeding programs as time consuming and complex gene introgression strategies are required

  • The size of the panel made the study of multi-locus epistatic interactions feasible as reasonable statistical power could be obtained with such a large experimental data set, the lack of which has often been a limitation in GWAM studies[24]

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Summary

Introduction

Yield and yield components in irrigated or stress environments[12,13,14,15,16,17,18], hitherto no study has reported genomic regions associated with yield stability using this approach. To extract the best out of the association and epistatic scans, we integrated the most stable main effect and epistatic loci into a forward stepwise regression analysis and identified the best marker and allelic combinations conferring highest yield stability. In this way, the current study led to the identification of genetic markers that tag genomic regions, which confer reliable yields across multiple irrigated and stress environments as well as 21 wheat lines that express the beneficial alleles

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