Multi-model genome-wide association and genomic prediction analysis of 16 agronomic, physiological and quality related traits in ICARDA spring wheat

Admas Alemu,Sherif Thabet,Adel Hagras,Ayed Al-Abdallat,Sufian Suliman,Awadalla Abdalla Abdelmula,Wuletaw Tadesse

doi:10.1007/s10681-021-02933-6

Abstract

Identification and exploration of the genetic architecture of traits related to yield, quality, and drought and heat tolerance is important for yield and quality improvement of wheat through marker-assisted selection. One hundred and ninety-two spring wheat genotypes were tested at two heat-stress locations in Sudan (Wad Medani and Dongula), a drought stress site in Morocco (Marchouch) and a site with high yield potential in Egypt (Sids) in replicated trials during the 2015–2016 and 2016–2017 cropping seasons. A total of 10,577 single nucleotide polymorphism markers identified from the 15 K wheat SNP assay were used in a genome-wide association (GWA) study and genomic prediction for 16 phenotypic traits related to yield, quality and drought and heat tolerance. Significant marker-trait associations were detected across GWAS models for all traits. Most detected marker-trait associations (MTAs) were environment-specific, signifying the presence of high quantitative trait loci-by-environment (QTL x E) interaction. Chromosome arm 5AL had significant multi-model MTAs for grain yield and yield-related traits at the heat-stress locations. Highly significant QTLs were detected on chromosome 2D for waxiness. Homoeologous group 2 and 6 chromosomes were with significant MTAs for grain protein content, gluten content, alveograph strength and Zeleny sedimentation test while chromosome arm 3BL was significant for both Z and W traits. Genomic prediction analysis with ridge regression-best linear unbiased prediction model estimated the breeding values of the studied traits with prediction accuracies ranging from 0.16 for leaf rolling to 0.72 for peduncle length. The identified QTLs could be targeted for marker-assisted selection or further studies aimed at fine mapping and cloning the causative genes and detecting favorable haplotypes with positive effects for agronomic, physiological or quality-related traits.

Highlights

IntroductionMeeting the demand of wheat production for the ever-increasing world population is a challenging task
Bread wheat (Triticum aestivum L., 2n = 6x = 42), as one of the major food crops, providing approximately 19% of calory and 21% of protein needs of human populations (Braun et al 2010)
The box plot distribution clearly shows that the Sids location outperformed others in yield and yield-related traits whereas Wad Medani was a better performing for grain quality traits than Dongula and Marchouch (Fig. S2)

Summary

Introduction

Meeting the demand of wheat production for the ever-increasing world population is a challenging task. The challenge of meeting the increasing demand for wheat in developing countries is increasing due to rapid population growth coupled with the effects of climate change (Lobell et al 2011). Drought and heat stresses are the two most important environmental constraints that curtail wheat production globally. These stresses cause various physiological changes in plants leading to accelerated growth and premature senescence which in turn reduce yield potential. Various physiological traits, including chlorophyll content, canopy temperature, stomatal conductance, waxiness (glaucousness), and leaf rolling have been targeted as adaptive traits in abiotically stressed environments

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