ArticleBMC plant biology2020
Linkage disequilibrium mapping for grain Fe and Zn enhancing QTLs useful for nutrient dense rice breeding.
Article in BMC plant biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
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Who cites it
35 citing papers in PubMed, 1 synthesis or guideline pooled it, 109 citations in OpenAlex.
- Meta-QTL s and haplotypes for efficient zinc biofortification of rice.The plant genome · 2023Pooled it
- Unveiling genetic loci and natural alleles for seed iron accumulation in adzuki bean via genome-wide association study.BMC plant biology · 2026Article
- Elite donors and stable marker-trait associations for grain iron and zinc biofortification in rice under organic and inorganic production systems.Frontiers in plant science · 2026Article
- Multivariate stability analysis to select elite rice (Oryza sativa L.) genotypes for grain yield, zinc and Iron.Scientific reports · 2025Article
- Genome-Wide Diversity in Lowland and Highland Maize Landraces From Southern South America: Population Genetics Insights to Assist Conservation.Evolutionary applications · 2024Article
- Deciphering the genetic basis of agronomic, yield, and nutritional traits in rice (Oryza sativa L.) using a saturated GBS-based SNP linkage map.Scientific reports · 2024Article
- Genomic prediction and QTL analysis for grain Zn content and yield inJournal of plant biochemistry and biotechnology · 2024Article
- Mineral nutrients in plants under changing environments: A road to future food and nutrition security.The plant genome · 2023Review
- Dissecting genomic regions and underlying sheath blight resistance traits in rice (Plant direct · 2023Article
- Transfer of Stress Resilient QTLs and Panicle Traits into the Rice Variety, Reeta through Classical and Marker-Assisted Breeding Approaches.International journal of molecular sciences · 2023Article
- Mapping the Genomic Regions Controlling Germination Rate and Early Seedling Growth Parameters in Rice.Genes · 2023Article
- Molecular Breeding for Incorporation of Submergence Tolerance and Durable Bacterial Blight Resistance into the Popular Rice Variety 'Ranidhan'.Biomolecules · 2023Article
- Rice biofortification: breeding and genomic approaches for genetic enhancement of grain zinc and iron contents.Frontiers in plant science · 2023Review
- Molecular dissection of connected rice populations revealed important genomic regions for agronomic and biofortification traits.Frontiers in plant science · 2023Article
- Association mapping for protein, total soluble sugars, starch, amylose and chlorophyll content in rice.BMC plant biology · 2022Article
- Identification of Genomic Regions Associated with High Grain Zn Content in Polished Rice Using Genotyping-by-Sequencing (GBS).Plants (Basel, Switzerland) · 2022Article
- Deciphering environmental factors and defense response of rice genotypes against sheath blight disease.Physiological and molecular plant pathology · 2022Article
- Detection of Genomic Regions Controlling the Antioxidant Enzymes, Phenolic Content, and Antioxidant Activities in Rice Grain through Association Mapping.Plants (Basel, Switzerland) · 2022Article
- Genetic analysis toward more nutritious barley grains for a food secure world.Botanical studies · 2022Article
- Identification of genomic loci regulating grain iron content inFood and energy security · 2022Article
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHigh yielding rice varieties are usually low in grain iron (Fe) and zinc (Zn) content. These two micronutrients are involved in many enzymatic activities, lack of which cause many disorders in human body. Bio-fortification is a cheaper and easier way to improve the content of these nutrients in rice grain.
resultsA population panel was prepared representing all the phenotypic classes for grain Fe-Zn content from 485 germplasm lines. The panel was studied for genetic diversity, population structure and association mapping of grain Fe-Zn content in the milled rice. The population showed linkage disequilibrium showing deviation of Hardy-Weinberg's expectation for Fe-Zn content in rice. Population structure at K = 3 categorized the panel population into distinct sub-populations corroborating with their grain Fe-Zn content. STRUCTURE analysis revealed a common primary ancestor for each sub-population. Novel quantitative trait loci (QTLs) namely qFe3.3 and qFe7.3 for grain Fe and qZn2.2, qZn8.3 and qZn12.3 for Zn content were detected using association mapping. Four QTLs, namely qFe3.3, qFe7.3, qFe8.1 and qFe12.2 for grain Fe content were detected to be co-localized with qZn3.1, qZn7, qZn8.3 and qZn12.3 QTLs controlling grain Zn content, respectively. Additionally, some Fe-Zn controlling QTLs were co-localized with the yield component QTLs, qTBGW, OsSPL14 and qPN. The QTLs qFe1.1, qFe3.1, qFe5.1, qFe7.1, qFe8.1, qZn6, qZn7 and gRMm9-1 for grain Fe-Zn content reported in earlier studies were validated in this study.
conclusionNovel QTLs, qFe3.3 and qFe7.3 for grain Fe and qZn2.2, qZn8.3 and qZn12.3 for Zn content were detected for these two traits. Four Fe-Zn controlling QTLs and few yield component QTLs were detected to be co-localized. The QTLs, qFe1.1, qFe3.1, qFe5.1, qFe7.1, qFe8.1, qFe3.3, qFe7.3, qZn6, qZn7, qZn2.2, qZn8.3 and qZn12.3 will be useful for biofortification of the micronutrients. Simultaneous enhancement of Fe-Zn content may be possible with yield component traits in rice.
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