Mapping and validation of quantitative trait loci associated with concentrations of 16 elements in unmilled rice grain

Min Zhang, Shannon R M Pinson, Lee Tarpley, Xin-Yuan Huang, Brett Lahner, Elena Yakubova, Ivan Baxter, Mary Lou Guerinot, David E Salt

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In this study, quantitative trait loci (QTLs) affecting the concentrations of 16 elements in whole, unmilled rice (Oryza sativa L.) grain were identified. Two rice mapping populations, the ‘Lemont’ × ‘TeQing’ recombinant inbred lines (LT-RILs), and the TeQing-into-Lemont backcross introgression lines (TILs) were used. To increase opportunity to detect and characterize QTLs, the TILs were grown under two contrasting field conditions, flooded and irrigated-but-unflooded. Correlations between the individual elements and between each element with grain shape, plant height, and time of heading were also studied. Transgressive segregation was observed among the LT-RILs for all elements. The 134 QTLs identified as associated with the grain concentrations of individual elements were found clustered into 39 genomic regions, 34 of which were found associated with grain element concentration in more than one population and/or flooding treatment. More QTLs were found significant among flooded TILs (92) than among unflooded TILs (47) or among flooded LT-RILs (40). Twenty-seven of the 40 QTLs identified among the LT-RILs were associated with the same element among the TILs. At least one QTL per element was validated in two or more population/environments. Nearly all of the grain element loci were linked to QTLs affecting additional elements, supporting the concept of element networks within plants. Several of the grain element QTLs co-located with QTLs for grain shape, plant height, and days to heading; but did not always differ for grain elemental concentration as predicted by those traits alone. A number of interesting patterns were found, including a strong Mg–P–K complex.
Original languageEnglish
Pages (from-to)137-165
Number of pages29
JournalTheoretical and Applied Genetics
Issue number1
Early online date15 Nov 2013
Publication statusPublished - Jan 2014

Bibliographical note

Acknowledgments This research was supported in part by the
US National Science Foundation, Plant Genome Research Program
(Grant #IOS 0701119) awarded to D.E.S, M.L.G and S.R.M.P. We
acknowledge Dr. Kathleen Yeater for consultation on analyzing
marker-trait associations using SAS JMP Genomics. Mention of a
trademark or proprietary product does not constitute a guarantee
or warranty of the product by the US Department of Agriculture or
Texas A&M AgriLife Research, and does not imply its approval to
the exclusion of other products that also can be suitable. USDA is an
equal opportunity provider and employer.


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