Although genetic diversity has a cardinal role in domestication, abundant natural allelic variations across the rice genome that cause agronomically important differences between diverse varieties have not been fully explored. Here we implement an approach integrating genome-wide association testing with functional analysis on grain size in a diverse rice population. We report that a major quantitative trait locus, GLW7, encoding the plant-specific transcription factor OsSPL13, positively regulates cell size in the grain hull, resulting in enhanced rice grain length and yield. We determine that a tandem-repeat sequence in the 5' UTR of OsSPL13 alters its expression by affecting transcription and translation and that high expression of OsSPL13 is associated with large grains in tropical japonica rice. Further analysis indicates that the large-grain allele of GLW7 in tropical japonica rice was introgressed from indica varieties under artificial selection. Our study demonstrates that new genes can be effectively identified on the basis of genome-wide association data.

The rich genetic diversity in Oryza sativa and Oryza rufipogon serves as the main sources in rice breeding. Large-scale resequencing has been undertaken to discover allelic variants in rice, but much of the information for genetic variation is often lost by direct mapping of short sequence reads onto the O. sativa japonica Nipponbare reference genome. Here we constructed a pan-genome dataset of the O. sativa-O. rufipogon species complex through deep sequencing and de novo assembly of 66 divergent accessions. Intergenomic comparisons identified 23 million sequence variants in the rice genome. This catalog of sequence variations includes many known quantitative trait nucleotides and will be helpful in pinpointing new causal variants that underlie complex traits. In particular, we systemically investigated the whole set of coding genes using this pan-genome data, which revealed extensive presence and absence of variation among rice accessions. This pan-genome resource will further promote evolutionary and functional studies in rice.