Genetic dissection of grain architecture-related traits in a winter wheat population

Matías Schierenbeck,María Rosa Simón,Ahmad M Alqudah,Rasha A Tarawneh,Ulrike Lohwasser,Andreas Börner

doi:10.1186/s12870-021-03183-3

Abstract

BackgroundThe future productivity of wheat (T. aestivum L.) as the most grown crop worldwide is of utmost importance for global food security. Thousand kernel weight (TKW) in wheat is closely associated with grain architecture-related traits, e.g. kernel length (KL), kernel width (KW), kernel area (KA), kernel diameter ratio (KDR), and factor form density (FFD). Discovering the genetic architecture of natural variation in these traits, identifying QTL and candidate genes are the main aims of this study. Therefore, grain architecture-related traits in 261 worldwide winter accessions over three field-year experiments were evaluated.ResultsGenome-wide association analysis using 90K SNP array in FarmCPU model revealed several interesting genomic regions including 17 significant SNPs passing false discovery rate threshold and strongly associated with the studied traits. Four of associated SNPs were physically located inside candidate genes within LD interval e.g. BobWhite_c5872_589 (602,710,399 bp) found to be inside TraesCS6A01G383800 (602,699,767–602,711,726 bp). Further analysis reveals the four novel candidate genes potentially involved in more than one grain architecture-related traits with a pleiotropic effects e.g. TraesCS6A01G383800 gene on 6A encoding oxidoreductase activity was associated with TKW and KA. The allelic variation at the associated SNPs showed significant differences betweeen the accessions carying the wild and mutated alleles e.g. accessions carying C allele of BobWhite_c5872_589, TraesCS6A01G383800 had significantly higher TKW than the accessions carying T allele. Interestingly, these genes were highly expressed in the grain-tissues, demonstrating their pivotal role in controlling the grain architecture.ConclusionsThese results are valuable for identifying regions associated with kernel weight and dimensions and potentially help breeders in improving kernel weight and architecture-related traits in order to increase wheat yield potential and end-use quality.

Highlights

The future productivity of wheat (T. aestivum L.) as the most grown crop worldwide is of utmost importance for global food security
This study explores the power of Genome-wide association scan (GWAS) to identify genomic regions associated with six-grain architecture related-traits in a novel set of 261 winter wheat genotypes, using 17,093 Single nucleotide polymorphism (SNP) markers in three environments
We found that the allelic variation at the locus of the gene TraesCS1B01G303200 that annotated as Protein of unknown function DUF1677 (O. sativa) showed its influence on Thousand-kernel weight (TKW) and Kernel area (KA)

Summary

Introduction

The future productivity of wheat (T. aestivum L.) as the most grown crop worldwide is of utmost importance for global food security. The trade-off between the grain number and TKW is well known [7,8,9], no differences in TKW have been found in some genotypes with a high spikelet number [10] indicating that a high TKW can be achieved keeping the grain number unmodified and potentially increasing grain yield. This suggests that selection for heavier grains could be highly effective for improving wheat yields [11]. TKW and kernel size are complex genetic traits controlled by multiple loci/genes with the influnce of environmental cues and genotype × environment (G × E) interactions [12, 13]

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Discussion

Conclusion