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Identification of genomic region(s) responsible for high iron and zinc content in rice

Micronutrient especially iron and zinc-enriched rice hold immense promise for sustainable and cost-effective solutions to overcome malnutrition. In this context, BC2F5 population derived from cross between RP-Bio226 and Sampada was used to localize genomic region(s)/QTL(s) for grain Fe (iron) and Zn...

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Main Authors: Dixit, Shilpi, Singh, Uma Maheshwar, Abbai, Ragavendran, Ram, T., Singh, Vikas Kumar, Paul, Amitava, Virk, P.S., Kumar, Arvind
Format: Journal Article
Language:Inglés
Published: Springer 2019
Online Access:https://hdl.handle.net/10568/164678
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author Dixit, Shilpi
Singh, Uma Maheshwar
Abbai, Ragavendran
Ram, T.
Singh, Vikas Kumar
Paul, Amitava
Virk, P.S.
Kumar, Arvind
author_browse Abbai, Ragavendran
Dixit, Shilpi
Kumar, Arvind
Paul, Amitava
Ram, T.
Singh, Uma Maheshwar
Singh, Vikas Kumar
Virk, P.S.
author_facet Dixit, Shilpi
Singh, Uma Maheshwar
Abbai, Ragavendran
Ram, T.
Singh, Vikas Kumar
Paul, Amitava
Virk, P.S.
Kumar, Arvind
author_sort Dixit, Shilpi
collection Repository of Agricultural Research Outputs (CGSpace)
description Micronutrient especially iron and zinc-enriched rice hold immense promise for sustainable and cost-effective solutions to overcome malnutrition. In this context, BC2F5 population derived from cross between RP-Bio226 and Sampada was used to localize genomic region(s)/QTL(s) for grain Fe (iron) and Zn (zinc) content together with yield and yield-related traits. Genotyping of mapping population with 108 SSR markers resulted in a genetic map of 2317.5 cM with an average marker distance of 21.5 cM. Mean grain mineral content in the mapping population across the two seasons ranged from 10.5–17.5 ppm for Fe and 11.3–22.1 ppm for Zn. Based on the multi-season phenotypic data together with genotypic data, a total of two major QTLs for Fe (PVE upto 17.1%) and three for Zn (PVE upto 34.2%) were identified. Comparative analysis across the two seasons has revealed four consistent QTLs for Fe (qFe1.1, qFe1.2, qFe6.1 and qFe6.2) and two QTL for Zn content (qZn1.1 and qZn6.2). Additionally, based on the previous and current studies three meta-QTLs for grain Fe and two for grain Zn have been identified. In-silico analysis of the identified QTL regions revealed the presence of potential candidate gene(s) such as, OsPOT, OsZIP4, OsFDR3, OsIAA5 etc., that were previously reported to influence grain Fe and Zn content. The identified QTLs could be utilized in developing high yielding, Fe and Zn denser varieties by marker assisted selection (MAS).
format Journal Article
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institution CGIAR Consortium
language Inglés
publishDate 2019
publishDateRange 2019
publishDateSort 2019
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spelling CGSpace1646782025-05-14T10:40:03Z Identification of genomic region(s) responsible for high iron and zinc content in rice Dixit, Shilpi Singh, Uma Maheshwar Abbai, Ragavendran Ram, T. Singh, Vikas Kumar Paul, Amitava Virk, P.S. Kumar, Arvind Micronutrient especially iron and zinc-enriched rice hold immense promise for sustainable and cost-effective solutions to overcome malnutrition. In this context, BC2F5 population derived from cross between RP-Bio226 and Sampada was used to localize genomic region(s)/QTL(s) for grain Fe (iron) and Zn (zinc) content together with yield and yield-related traits. Genotyping of mapping population with 108 SSR markers resulted in a genetic map of 2317.5 cM with an average marker distance of 21.5 cM. Mean grain mineral content in the mapping population across the two seasons ranged from 10.5–17.5 ppm for Fe and 11.3–22.1 ppm for Zn. Based on the multi-season phenotypic data together with genotypic data, a total of two major QTLs for Fe (PVE upto 17.1%) and three for Zn (PVE upto 34.2%) were identified. Comparative analysis across the two seasons has revealed four consistent QTLs for Fe (qFe1.1, qFe1.2, qFe6.1 and qFe6.2) and two QTL for Zn content (qZn1.1 and qZn6.2). Additionally, based on the previous and current studies three meta-QTLs for grain Fe and two for grain Zn have been identified. In-silico analysis of the identified QTL regions revealed the presence of potential candidate gene(s) such as, OsPOT, OsZIP4, OsFDR3, OsIAA5 etc., that were previously reported to influence grain Fe and Zn content. The identified QTLs could be utilized in developing high yielding, Fe and Zn denser varieties by marker assisted selection (MAS). 2019-05-31 2024-12-19T12:54:12Z 2024-12-19T12:54:12Z Journal Article https://hdl.handle.net/10568/164678 en Open Access Springer Dixit, Shilpi; Singh, Uma Maheshwar; Abbai, Ragavendran; Ram, T.; Singh, Vikas Kumar; Paul, Amitava; Virk, P. S. and Kumar, Arvind. 2019. Identification of genomic region(s) responsible for high iron and zinc content in rice. Sci Rep, Volume 9, no. 1
spellingShingle Dixit, Shilpi
Singh, Uma Maheshwar
Abbai, Ragavendran
Ram, T.
Singh, Vikas Kumar
Paul, Amitava
Virk, P.S.
Kumar, Arvind
Identification of genomic region(s) responsible for high iron and zinc content in rice
title Identification of genomic region(s) responsible for high iron and zinc content in rice
title_full Identification of genomic region(s) responsible for high iron and zinc content in rice
title_fullStr Identification of genomic region(s) responsible for high iron and zinc content in rice
title_full_unstemmed Identification of genomic region(s) responsible for high iron and zinc content in rice
title_short Identification of genomic region(s) responsible for high iron and zinc content in rice
title_sort identification of genomic region s responsible for high iron and zinc content in rice
url https://hdl.handle.net/10568/164678
work_keys_str_mv AT dixitshilpi identificationofgenomicregionsresponsibleforhighironandzinccontentinrice
AT singhumamaheshwar identificationofgenomicregionsresponsibleforhighironandzinccontentinrice
AT abbairagavendran identificationofgenomicregionsresponsibleforhighironandzinccontentinrice
AT ramt identificationofgenomicregionsresponsibleforhighironandzinccontentinrice
AT singhvikaskumar identificationofgenomicregionsresponsibleforhighironandzinccontentinrice
AT paulamitava identificationofgenomicregionsresponsibleforhighironandzinccontentinrice
AT virkps identificationofgenomicregionsresponsibleforhighironandzinccontentinrice
AT kumararvind identificationofgenomicregionsresponsibleforhighironandzinccontentinrice

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