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, 9 (1), 8136

Identification of Genomic Region(s) Responsible for High Iron and Zinc Content in Rice


Identification of Genomic Region(s) Responsible for High Iron and Zinc Content in Rice

Shilpi Dixit et al. Sci Rep.


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).

Conflict of interest statement

The authors declare no competing interests.


Figure 1
Figure 1
Box plot depicting the phenotypic variance for grain Fe and Zn content. Mean values for Fe and Zn content across DS2015 and WS2015 in BC2F5 population derived from a cross between RP-Bio226 and Sampada was utilized to develop boxplot. Significant variation among the population was observed for both the micro-nutrients.
Figure 2
Figure 2
SSR based genetic map and distribution of QTLs associated with grain Fe and grain Zn (RP-Bio226 × Sampada). The scale on the left indicates genetic distance (centiMorgan; cM as unit). The black lines in the linkage groups represent the genetic position of the markers. A total of three linkage groups, namely Chr 01, Chr 06 and Chr 11 possess 14 QTLs for grain Fe, Zn and yield and yield-related traits. Note: *represent QTL identified in one season and ** represents stable QTL (identified in both seasons, 2015 DS & 2015 WS).
Figure 3
Figure 3
Functional annotation and categorization of genes present within (a) qFe1.2; qZn1.1 and (b) qFe6.1. Several genes associated with cell division, DNA repair, DNA synthesis, cell organization, vesicle transport, protein targeting, stress responsiveness, RNA synthesis, regulation of transcription, RNA processing, protein synthesis, development, hormones, regulation, protein modification & degradation, enzyme families, redox and transport were present in both the QTLs. Based on previous reports, about 34 potential candidates associated with Zn, Fe transport, homeostasis and grain content were short-listed.

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