Enhancing the nutritional value of rice grains is of particular interest because rice is a primary dietary component for more than half of the world’s population, and is a primary source of nutrients in many underdeveloped countries.  Because rice can be grown under both flooded and unflooded field conditions, and metal transporter proteins and genes have been shown orthologous between species as diverse as Arabidopsis, rice, and yeast, knowledge on the genetic and environmental factors affecting the rice grain elemental content (ionome) can have application well beyond rice. 

Chromosomal regions associated with increased grain concentrations of one or more of 16 elements were identified in several rice mapping populations.  In agreement with known shared transporters and element networks, many of the chromosomal regions were associated with grain concentrations of multiple elements.  These studies have identified a number of interesting genomic regions and candidate genes for further research.  The mapping populations were grown under both flooded and unflooded fields to further characterize the various genes under contrasting field management conditions.  As expected, grain accumulation of arsenic was higher under flooded conditions than unflooded, while cadmium accumulation showed an opposite trend.  Seed from 1700 highly diverse global rice varieties  grown in flooded and unflooded fields was evaluated for grain concentrations of 16 elements; from which 50 genotypes exhibiting extreme concentrations of one or more grain elements were selected for further genetic, agronomic, and physiological studies.  Rice cultivars in the indica ancestral lineage showed higher grain accumulation of most elements than other rice lineages, while japonica cultivars showed higher average grain concentrations of Cu, Fe, Mo, and Zn.  Principal component analysis identified the six elements (P, K, Mg, As, Cu and Fe) as key to explaining most of the variance among the 1700 diverse rice accessions, with the same six elements proving significant regardless of ancestral lineage, or flooding condition.  Comparison of 43 genotypes selected for extreme differences in grain ionomics revealed that for some elements (most notably molybdenum, cobalt, and cadimum) and some genotypes, seedling leaves can be used to predict the grain nutritional value. This will allow future breeding and genetics studies to be conducted more rapidly and cost effectively.