ArticlePloS one2020
Mapping QTLs underpin nutrition components in aromatic rice germplasm.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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17 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- Meta-QTL s and haplotypes for efficient zinc biofortification of rice.The plant genome · 2023Pooled it
- Comprehensive Evaluation of Varietal Differences in Glutinous Rice: Multidimensional Assessment of Cooking Quality and Processing Characteristics.Foods (Basel, Switzerland) · 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
- Genome-wide association studies for identification of QTLs and key candidate genes to improve grain quality in rice (Food chemistry. Molecular sciences · 2025Article
- A Genome‑wide Association Study of the Grain Ionome in Rice Oryza Sativa Ssp. Japonica under Two Diverse Water Management Systems.Rice (New York, N.Y.) · 2025Article
- Rice QTL hotspots related with seed grain size, shape, weight, and color based on genome wide association study and linkage mapping.Scientific reports · 2025Article
- From Gene to Plate: Molecular Insights into and Health Implications of Rice (International journal of molecular sciences · 2025Review
- Mapping Genomic Regions for Grain Protein Content and Quality Traits in Milled Rice (Plants (Basel, Switzerland) · 2025Article
- 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
- Multi-environment GWAS identifies genomic regions underlying grain nutrient traits in foxtail millet (Setaria italica).Plant cell reports · 2023Article
- Unraveling the genetics underlying micronutrient signatures of diversity panel present in brown rice through genome-ionome linkages.The Plant journal : for cell and molecular biology · 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
- Review
- GWAS to spot candidate genes associated with grain quality traits in diverse rice accessions of North East India.Molecular biology reports · 2022Article
- Enhancing the Nutritional Quality of Major Food Crops Through Conventional and Genomics-Assisted Breeding.Frontiers in nutrition · 2020Review
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Authors and funding
9 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As rice is an important staple food globally, research for development and enhancement of its nutritional value it is an imperative task. Identification of nutrient enriched rice germplasm and exploiting them for breeding programme is the easiest way to develop better quality rice. In this study, we analyzed 113 aromatic rice germplasm in order to identify quantitative trait loci (QTL) underpinning nutrition components and determined by measuring the normal frequency distribution for Fe, Zn, amylose, and protein content in those rice germplasm. Comparatively, the germplasm Radhuni pagal, Kalobakri, Thakurbhog (26.6 ppm) and Hatisail exhibited the highest mean values for Fe (16.9 ppm), Zn (34.1 ppm), amylose (26.6 ppm) and protein content (11.0 ppm), respectively. Moreover, a significant linear relationship (R2 = 0.693) was observed between Fe and Zn contents. Cluster analysis based on Mahalanobis D2 distances revealed four major clusters of 113 rice germplasm, with cluster III containing a maximum 37 germplasm and a maximum inter-cluster distance between clusters III and IV. The 45 polymorphic SSRs and four trait associations exhibited eight significant quantitative trait loci (QTL) located on eight different chromosomes using composite interval mapping (CIM). The highly significant QTL (variance 7.89%, LOD 2.02) for protein content (QTL.pro.1) was observed on chromosome 1 at 94.9cM position. Also, four QTLs for amylose content were observed with the highly significant QTL.amy.8 located on chromosome 8 exhibiting 7.2% variance with LOD 1.83. Only one QTL (QTL.Fe.9) for Fe content was located on chromosome 9 (LOD 1.24), and two (QTL.Zn.4 and QTL.Zn.5) for Zn on chromosome 4 (LOD 1.71) and 5 (LOD 1.18), respectively. Overall, germplasm from clusters III and IV might offer higher heterotic response with the identified QTLs playing a significant role in any rice biofortification breeding program and released with development of new varieties.
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