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

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.

Genome-wide association study for grain yield and component traits in bread wheat (Triticum aestivum L.)

“…The highest number of MTAs were identified for A subgenome (11) followed by the D subgenome (10) and the B subgenome (6). A similar trend on MTAs identified in the A subgenome for yield and yield-contributing traits (Ain et al, 2015;Godoy et al, 2018;Alemu et al, 2021). A high level of stringency through Bonferroni-correction has been followed to consider MTA as significant, therefore, these MTAs could be valuable for their further validation in different genetic backgrounds to use them in MAS.…”

“…Previous studies also identified on same chromosomes i.e. 1A (Edae et al, 2014;Jamil et al, 2019), 2B (Jamil et al, 2019), 5B (Edae et al, 2014;Jamil et al, 2019;Alemu et al, 2021) but different positions and different chromosomes (Godoy et al, 2018;Rahimi et al, 2019) for GFD.…”

“…Three MTAs for PH were identified on 2D (88.9 Mb), 3B (824.4 Mb), and 5D (294.5 Mb) chromosomes. Previous reports also identified MTAs on the same chromosomes 2D (Ward et al, 2019;Alemu et al, 2021), 3B (Edae et al, 2014;Gahlaut et al, 2019) and also on different chromosomes (Ain et al, 2015;Sun et al, 2017;Godoy et al, 2018;Li et al, 2019;Russell et al, 2020) for PH. Jamil et al (2019) identified an MTA on the same chromosome 3B at 824.6 Mb, which was similar to that of AX-94498579 located on the 3B chromosome and mapped at 824.4 Mb.…”

“…(AX-94709904) on the 7A chromosome, which was mapped at 728.2 Mb. Furthermore, MTAs for GY were also identified in different chromosomes in different GWAS studies with diverse genetic material (Edae et al, 2014;Ain et al, 2015;Godoy et al, 2018;Li et al, 2019;Rahimi et al, 2019;Alemu et al, 2021;Suliman et al, 2021).…”

“…Several drought-tolerance QTLs associated with grain yield and its component traits have been identified (Edae et al, 2014;Ain et al, 2015;Gahlaut et al, 2019;Suliman et al, 2021;Bennani et al, 2022;Said et al, 2022). Similarly, genomic regions governing yield and its attributing traits in normal irrigated production conditions were also identified (Sukumaran et al, 2015;Sun et al, 2017;Godoy et al, 2018;Liu et al, 2018;Ma et al, 2018;Sukumaran et al, 2018;Bajgain et al, 2019;Jamil et al, 2019;Li et al, 2019;Rahimi et al, 2019;Sheoran et al, 2019;Ward et al, 2019;Ali et al, 2020;Alqudah et al, 2020;Pang et al, 2020;Alemu et al, 2021;Eltaher et al, 2021;Gao et al, 2021;Malik et al, 2021;Saini et al, 2022;Zhang et al, 2022). Also, QTLs were identified in hostile soils under salt stress conditions for yield and related traits (Hu et al, 2021).…”