Abstract

Spike fertility and associated traits are key factors in deciding the grain yield potential of wheat. Genome-wide association study (GWAS) interwoven with advanced post-GWAS analysis such as a genotype-phenotype network (geno-pheno network) for spike fertility, grain yield, and associated traits allow to identify of novel genomic regions and represents attractive targets for future marker-assisted wheat improvement programs. In this study, GWAS was performed on 200 diverse wheat genotypes using Breeders’ 35K Axiom array that led to the identification of 255 significant marker-trait associations (MTAs) (–log10P ≥ 3) for 15 metric traits phenotyped over three consecutive years. MTAs detected on chromosomes 3A, 3D, 5B, and 6A were most promising for spike fertility, grain yield, and associated traits. Furthermore, the geno-pheno network prioritised 11 significant MTAs that can be utilised as a minimal marker system for improving spike fertility and yield traits. In total, 119 MTAs were linked to 81 candidate genes encoding different types of functional proteins involved in various key pathways that affect the studied traits either way. Twenty-two novel loci were identified in present GWAS, twelve of which overlapped by candidate genes. These results were further validated by the gene expression analysis, Knetminer, and protein modelling. MTAs identified from this study hold promise for improving yield and related traits in wheat for continued genetic gain and in rapidly evolving artificial intelligence (AI) tools to apply in the breeding program.

Highlights

  • Wheat is an important cereal providing 20% of calories and protein for the human diet globally (Shiferaw et al, 2013)

  • The phenotypic performance of 200 genotypes based on investigated traits in three environments and Best linear unbiased predictions (BLUP) is summarised in Figure 1A and Supplementary Table 2

  • Substantial phenotypic variations among genotypes and datasets were reported for all the studied traits excluding spike length (SL), chaff weight (CW), spike dry weight (SDW), grain weight per spike (GWS), grain number per spike (GNS), and BM for which the mean sum of squares (MSS) for the environments and BLUP

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Summary

Introduction

Wheat is an important cereal providing 20% of calories and protein for the human diet globally (Shiferaw et al, 2013). Adverse impacts of climate change, diminishing natural resources, rapidly evolving new threats of pests and pathotypes, and genetic erosion would further add obstacles to the achievement of doubling the yield potential in the stipulated time. Grain yield has a complex underlying genetic architecture that depends on several related traits. High genotype x environment (GxE) interaction and low heritability of this ultimate trait in most cases, make the selection process most challenging. In such a situation, indirect selection of grain yield via highly heritable (h2) correlated traits would be practically more feasible. One of the key contributing traits for keeping the high yields are spike-related traits such as spike fertility

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