ArticleScientific reports2022
Genome-wide association mapping for wheat morphometric seed traits in Iranian landraces and cultivars under rain-fed and well-watered conditions.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 22 citations in OpenAlex.
- Identification of Iranian bread wheat with superior performance under well-watered and rain-fed conditions using linear selection indices.BMC plant biology · 2026Article
- Evaluation of genetic diversity and population structure of wheat core collection using SNP and KASP markers for major agronomic traits.BMC plant biology · 2025Article
- Genome-wide association studies and candidate genes networks affecting reproductive traits using Iranian Holstein sequence data.BMC genomics · 2025Article
- Unraveling the genetic basis of heat tolerance and yield in bread wheat: QTN discovery and Its KASP-assisted validation.BMC plant biology · 2025Article
- Article
- Genome-Wide Association Study on Seedling Phenotypic Traits of Wheat under Different Nitrogen Conditions.Plants (Basel, Switzerland) · 2023Article
- Genome wide association in Spanish bread wheat landraces identifies six key genomic regions that constitute potential targets for improving grain yield related traits.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Analysis of genetic diversity and genome-wide association study for drought tolerance related traits in Iranian bread wheat.BMC plant biology · 2023Article
- Genome-wide association mapping and genomic prediction of agronomical traits and breeding values in Iranian wheat under rain-fed and well-watered conditions.BMC genomics · 2022Article
- Genome-Wide Association Study (GWAS) and genome prediction of seedling salt tolerance in bread wheat (Triticum aestivum L.).BMC plant biology · 2022Article
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5 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Seed traits in bread wheat are valuable to breeders and farmers, thus it is important exploring putative QTLs responsible for key traits to be used in breeding programs. GWAS was carried out using 298 bread wheat landraces and cultivars from Iran to uncover the genetic basis of seed characteristics in both rain-fed and well-watered environments. The analyses of linkage disequilibrium (LD) between marker pairs showed that the largest number of significant LDs in landraces (427,017) and cultivars (370,359) was recorded in genome B, and the strongest LD was identified on chromosome 4A (0.318). LD decay was higher in the B and A genomes, compared to the D genome. Mapping by using mrMLM (LOD > 3) and MLM (0.05/m, Bonferroni) led to 246 and 67 marker-trait associations (MTAs) under rain-fed, as well as 257 and 74 MTAs under well-watered conditions, respectively. The study found that 3VmrMLM correctly detected all types of loci and estimated their effects in an unbiased manner, with high power and accuracy and a low false positive rate, which led to the identification of 140 MTAs (LOD > 3) in all environments. Gene ontology revealed that 10 and 10 MTAs were found in protein-coding regions for rain-fed and well-watered conditions, respectively. The findings suggest that landraces studied in Iranian bread wheat germplasm possess valuable alleles, which are responsive to water-limited conditions. MTAs uncovered in this study can be exploited in the genome-mediated development of novel wheat cultivars.
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