ArticleBMC genomics2020
Genetic dissection of heat-responsive physiological traits to improve adaptation and increase yield potential in soft winter wheat.
Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.
- Meta-QTL analysis and in-silico transcriptome assessment for controlling chlorophyll traits in common wheat.The plant genome · 2023Pooled it
- Harnessing genomics approaches for heat stress resilience in wheat: from discovery to deployment.Journal of experimental botany · 2026Review
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- Decoding the heat stress resilience in Chickpea (Cicer arietinum L.): multi-trait analysis for genotypic adaptation.Scientific reports · 2025Article
- Discovering leaf and stripe rust resistance in soft red winter wheat through genome-wide association studies.The plant genome · 2025Article
- Dissecting the genetic basis of fruiting efficiency for genetic enhancement of harvest index, grain number, and yield in wheat.BMC plant biology · 2025Article
- Article
- Identifying the physiological traits associated with DNA marker using genome wide association in wheat under heat stress.Scientific reports · 2024Article
- Discovering novel genomic regions explaining adaptation of bread wheat to conservation agriculture through GWAS.Scientific reports · 2024Article
- Genome-wide association study for seedling heat tolerance under two temperature conditions in bread wheat (Triticum aestivum L.).BMC plant biology · 2024Article
- Article
- Multi-trait genomic prediction using in-season physiological parameters increases prediction accuracy of complex traits in US wheat.BMC genomics · 2022Article
- Wheat end-use quality: State of art, genetics, genomics-assisted improvement, future challenges, and opportunities.Frontiers in genetics · 2022Review
- Breeding for drought and heat tolerance in wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Review
- Major QTLs and Potential Candidate Genes for Heat Stress Tolerance Identified in Chickpea (Frontiers in plant science · 2021Article
Corrections and comments
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Authors and funding
16 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundClimate change, including higher temperatures (HT) has a detrimental impact on wheat productivity and modeling studies predict more frequent heat waves in the future. Wheat growth can be impaired by high daytime and nighttime temperature at any developmental stage, especially during the grain filling stage. Leaf chlorophyll content, leaf greenness, cell membrane thermostability, and canopy temperature have been proposed as candidate traits to improve crop adaptation and yield potential of wheat under HT. Nonetheless, a significant gap exists in knowledge of genetic backgrounds associated with these physiological traits. Identifying genetic loci associated with these traits can facilitate physiological breeding for increased yield potential under high temperature stress condition in wheat.
resultsWe conducted genome-wide association study (GWAS) on a 236 elite soft wheat association mapping panel using 27,466 high quality single nucleotide polymorphism markers. The panel was phenotyped for three years in two locations where heat shock was common. GWAS identified 500 significant marker-trait associations (MTAs) (p ≤ 9.99 × 10
conclusionsWe identified 500 significant MTAs in soft winter wheat under HT stress. We found several stable loci across environments and pleiotropic markers controlling physiological and agronomic traits. After further validation, these MTAs can be used in marker-assisted selection and breeding to develop varieties with high stability for grain yield under high temperature.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.