|Zhang, Min -|
|Tarpley, Lee -|
|Huang, Xinyuan -|
|Lahner, Brett -|
|Yakubova, Elena -|
|Guerinot, Mary Lou -|
|Salt, David -|
Submitted to: Theoretical and Applied Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 1, 2013
Publication Date: February 26, 2014
Citation: Zhang, M., Pinson, S.R., Tarpley, L., Huang, X., Lahner, B., Yakubova, E., Baxter, I.R., Guerinot, M., Salt, D.E. 2014. Mapping and validation of quantitative trait loci associated with concentrations of 16 elements in unmilled rice grain. Theoretical and Applied Genetics. 127(1):137-165. Interpretive Summary: Research into the mineral content of cereal grains and vegetables is motivated by interest in the nutritional value of the eaten grain. Biofortification refers to natural enhancement of the grain/food product through traditional breeding. Since it does not require genetic engineering, it is acceptable to many consumers, and is able to acquire organic certification if grown under organic field conditions. Enhancing the nutritional value of rice is of particular interest because rice is a primary dietary component for more than half of the world’s population, and especially so in underdeveloped parts of the world with higher rates of malnutrition. Here we report the identification and characterization of genes that affect the grain concentration of 16 elements in unmilled rice grain. To enhance our ability to identify, confirm, and characterize grain element QTLs, we studied two different rice mapping populations, one of which was grown under two diverse field environments, flooded and unflooded. This study is thus the first to identify putative QTLs for grain minerals of rice grown under unflooded conditions. We identified 134 QTLs that affect the grain concentration of individual elements. The 134 elemental QTLs tended to be located located near each other along the chromosomes forming 39 "gene clusters" which were generally associated with (contained genes affecting) more than one element. Further research would be required to comment further as to whether each cluster is due to a single gene affecting many elements, or due to clustering of different genes per element, but in light of reports in the literature about element networks, it seems probable that at least in some cases, uptake and accumulation of one element can directly affect the uptake and accumulation of other elements. This further suggests that, when studying grain nutritional value, it is important to study multiple elements at a time, and to carefully control factors such as soil fertility, temperature, and pH that can affect uptake the ability of plants to take nutrients up from the soil. Several plant characteristics, namely grain shape, heading time and plant height, proved to have much less direct influence on rice grain mineral concentrations than was anticipated. To get a mineral from the soil to the grain, it must be taken up by the plant’s roots and transported upward to the shoot. Minerals then get diverted into leaf tissues where they may be stored for later translocation to the grain, or may instead be chemically bound, no longer available for grain acquisition. Minerals must pass through a membrane to enter the grain, and this membrane is selective, it does not allow all chemicals and elements to cross. There are many points within the plant that a gene can act on to enhance grain nutritional value. Gene-identification studies such as this one are considered preliminary studies. Learning which chromosomal regions contain genes affecting grain element content is a critical first step toward understanding how those genes can be most effectively used to improve grain nutritional value.
Technical Abstract: 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’ x ‘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 content 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.