Linkage disequilibrium mapping for grain Fe and Zn enhancing QTLs useful for nutrient dense rice breeding
Autor: | Swapnil Pawar, Elssa Pandit, SP Mohanty, R. Naveenkumar, Saumya Ranjan Barik, S. S. C. Patnaik, S. K. Ghritlahre, J. N. Reddy, Sharat Kumar Pradhan, Deepak Kumar Nayak, D. Sanjiba Rao |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
0106 biological sciences
0301 basic medicine Germplasm Linkage disequilibrium Grain Fe content Iron Quantitative Trait Loci Population Biofortification Plant Science Biology Quantitative trait locus 01 natural sciences 03 medical and health sciences Nutrient Grain Zn content lcsh:Botany Association mapping education education.field_of_study Linkage Disequilibrium Mapping Genetic Variation Oryza Nutrients lcsh:QK1-989 Association study Plant Breeding Zinc 030104 developmental biology Agronomy Edible Grain Research Article 010606 plant biology & botany |
Zdroj: | BMC Plant Biology, Vol 20, Iss 1, Pp 1-24 (2020) BMC Plant Biology |
ISSN: | 1471-2229 |
Popis: | 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) namelyqFe3.3andqFe7.3for grain Fe andqZn2.2,qZn8.3andqZn12.3for Zn content were detected using association mapping. Four QTLs, namelyqFe3.3,qFe7.3,qFe8.1andqFe12.2for grain Fe content were detected to be co-localized withqZn3.1,qZn7,qZn8.3andqZn12.3QTLs controlling grain Zn content, respectively. Additionally, some Fe-Zn controlling QTLs were co-localized with the yield component QTLs,qTBGW,OsSPL14andqPN. The QTLsqFe1.1,qFe3.1,qFe5.1, qFe7.1, qFe8.1, qZn6, qZn7 and gRMm9–1for grain Fe-Zn content reported in earlier studies were validated in this study.ConclusionNovel QTLs,qFe3.3andqFe7.3for grain Fe andqZn2.2,qZn8.3andqZn12.3for 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, qZn8.3andqZn12.3will be useful for biofortification of the micronutrients. Simultaneous enhancement of Fe-Zn content may be possible with yield component traits in rice. |
Databáze: | OpenAIRE |
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