SynthesisG3 (Bethesda, Md.)2023
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.
Synthesis in G3 (Bethesda, Md.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Genetic dissection of cold stress tolerance and yield potential under cold stress in nested synthetic wheat (Triticum aestivum L.) introgression libraries using multi-locus genome-wide association and haplotype analysis.Functional & integrative genomics · 2026Article
- Uncover the genetic basis of processing quality related traits in common wheat (Frontiers in plant science · 2026Article
- Uncovering the genetic architecture of pungency, carotenoids, and flavor inHorticulture research · 2025Article
- Unraveling the genetic basis of heat tolerance and yield in bread wheat: QTN discovery and Its KASP-assisted validation.BMC plant biology · 2025Article
- Reviewing the essential roles of remote phenotyping, GWAS and explainable AI in practical marker-assisted selection for drought-tolerant winter wheat breeding.Frontiers in plant science · 2024Review
- Highlighting plant science with a GENETICS and G3 series on Plant Genetics and Genomics.G3 (Bethesda, Md.) · 2023Article
- Highlighting plant science with a GENETICS and G3 series on Plant Genetics and Genomics.Genetics · 2023Article
- A novel method for irrigating plants, tracking water use, and imposing water deficits in controlled environments.Frontiers in plant science · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A genome-wide association study (GWAS) was used to identify associated loci with early vigor 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 quantitative trait loci (QTL) from recombinant inbred lines, double haploids, back-crosses, 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. 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% 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 associated with MQTLs. These findings provide important information on the genetic basis of early vigor 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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