Genome-wide association study to identify genomic loci associated with early vigor in bread wheat under simulated water deficit complemented with quantitative trait loci meta-analysis

Abstract

A genome-wide association study (GWAS) was used to identify associated loci with early vigour under simulated water deficit and grain yield under field drought in a diverse collection of Iranian bread wheat landraces. In addition, a meta-quantitative trait loci (MQTL) analysis was used to further expand our approach by retrieving already published QTLs from recombinant inbred lines (RILs), double haploids (DH), back-crosses (BC), and F2 mapping populations. In the current study, around 16%, 14%, and 16% of SNPs were in significant linkage disequilibrium (LD) in the A, B, and D genomes, respectively, and varied between 5.44% (4A) and 21.85% (6A). Three main subgroups were identified among the landraces with different degrees of admixture, and population structure was further explored through principal component analysis (PCA). Our GWAS identified 54 marker-trait associations (MTAs) that were located across the wheat genome but with the highest number found in the B sub-genome. The gene ontology (GO) analysis of MTAs revealed that around 75 percent were located within or closed to protein-coding genes. In the MQTL analysis 23 MQTLs, from a total of 215 QTLs, were identified and successfully projected onto the reference map. MQT-YLD4, MQT-YLD9, MQT-YLD13, MQT-YLD17, MQT-YLD18, MQT-YLD19, and MQTL-RL1 contributed to the highest number of projected QTLs and were therefore regarded as the most reliable and stable QTLs under water deficit conditions. These MQTLs greatly facilitate the identification of putative candidate genes underlying at each MQTL interval due to the reduced confidence of intervals (CI) associated with MQTLs. These findings provide important information on the genetic basis of early vigour traits and grain yield under water deficit conditions and set the foundation for future investigations into adaptation to water deficit in bread wheat.

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“…They characterize the unique and shared genetic architecture across traits and environments, and identify a number of robust and environmentally stable alleles contributed from the emmer wheat parent. Similarly, Rahimi et al . (2023) use genome-wide association studies (GWAS) and a meta-analysis of existing QTL data to study early vigor and grain yield QTL under simulated water deficit in bread wheat.…”

A novel method for irrigating plants, tracking water use, and imposing water deficits in controlled environments

“…As a result of these technical challenges, most controlled environment high-throughput phenotypic screenings of traits related to drought stress have concentrated on easily evaluated traits, measured on seedlings or seeds ( Zeng et al., 2017 ; Khan et al., 2018 ; Khan et al., 2019 ; Yu et al., 2019 ; Liu et al., 2020 ; Sharmin et al., 2021 ; Rahimi et al., 2022 ). These traits may not be useful for assessing genetic control of drought effects on seed yield and yield components, which are expressed much later in the developmental cycle ( Doss et al., 1974 ; Pandey et al., 1984 ; Desclaux et al., 2000 ; Zatybekov et al., 2017 ).…”

Dissection of QTLs underlying the genetic basis of drought resistance in wheat: A Meta-Analysis

“…al. 2014; Arriagada et al 2022; Kumar et al 2020; Kumar et al 2023; Liu et al 2020;Rahimi et al 2023; Raj and Nadarajah 2022). Among the three studies of meta-QTL for drought resistance conducted in wheat, one and two involved with durum and bread wheat, respectively(Arriagada et al 2022;Kumar et al , 2023.…”