Rice Variation Map (RiceVarMap, http:/ricevarmap.ncpgr.cn) is a database of rice genomic variations. The database provides comprehensive information of 6 551 358 single nucleotide polymorphisms (SNPs) and 1 214 627 insertions/deletions (INDELs) identified from sequencing data of 1479 rice accessions. The SNP genotypes of all accessions were imputed and evaluated, resulting in an overall missing data rate of 0.42% and an estimated accuracy greater than 99%. The SNP/INDEL genotypes of all accessions are available for online query and download. Users can search SNPs/INDELs by identifiers of the SNPs/INDELs, genomic regions, gene identifiers and keywords of gene annotation. Allele frequencies within various subpopulations and the effects of the variation that may alter the protein sequence of a gene are also listed for each SNP/INDEL. The database also provides geographical details and phenotype images for various rice accessions. In particular, the database provides tools to construct haplotype networks and design PCR-primers by taking into account surrounding known genomic variations. These data and tools are highly useful for exploring genetic variations and evolution studies of rice and other species.

Summary: Creation of Circos plot is one of the most efficient approaches to visualize genomic data. However, the installation and use of existing tools to make Circos plot are challenging for users lacking of coding experiences. To address this issue, we developed an R/Shiny application shinyCircos, a graphical user interface for interactive creation of Circos plot. shinyCircos can be easily installed either on computers for personal use or on local or public servers to provide online use to the community. Furthermore, various types of Circos plots could be easily generated and decorated with simple mouse-click. Availability and implementation: shinyCircos and its manual are freely available at https://github.com/venyao/shinyCircos. shinyCircos is deployed at https://yimingyu.shinyapps.io/shinycircos/ and http://shinycircos.ncpgr.cn/ for online use.

Grains from cereals contribute an important source of protein to human food, and grain protein content (GPC) is an important determinant of nutritional quality in cereals. Here we show that the quantitative trait locus (QTL)qPC1in rice controls GPC by regulating the synthesis and accumulation of glutelins, prolamins, globulins, albumins and starch.qPC1encodes a putative amino acid transporterOsAAP6, which functions as a positive regulator of GPC in rice, such that higher expression ofOsAAP6is correlated with higher GPC.OsAAP6greatly enhances root absorption of a range of amino acids and has effects on the distribution of various amino acids. Two common variations in the potentialcis-regulatory elements of theOsAAP65′-untranslated region seem to be associated with GPC diversity mainly inindicacultivars. Our results represent the first step toward unravelling the mechanism of regulation underlying natural variation of GPC in rice.

Intensive rice breeding over the past 50 y has dramatically increased productivity especially in the indica subspecies, but our knowledge of the genomic changes associated with such improvement has been limited. In this study, we analyzed low-coverage sequencing data of 1,479 rice accessions from 73 countries, including landraces and modern cultivars. We identified two major subpopulations, indica I (IndI) and indica II (IndII), in the indica subspecies, which corresponded to the two putative heterotic groups resulting from independent breeding efforts. We detected 200 regions spanning 7.8% of the rice genome that had been differentially selected between IndI and IndII, and thus referred to as breeding signatures. These regions included large numbers of known functional genes and loci associated with important agronomic traits revealed by genome-wide association studies. Grain yield was positively correlated with the number of breeding signatures in a variety, suggesting that the number of breeding signatures in a line may be useful for predicting agronomic potential and the selected loci may provide targets for rice improvement. Significance Intensive rice breeding over the past 50 y has produced many high-performing cultivars, but our knowledge of the genomic changes associated with such improvement remains limited. By analyzing sequences of 1,479 rice accessions, this study identified genomic changes associated with breeding efforts, referred to as breeding signatures, involving 7.8% of the rice genome. Accumulation of selected regions is positively correlated with yield improvement. The number of selected regions in a line may be used for predicting agronomic potential, and the selected loci may provide useful targets for rice improvement.

Heterosis refers to the superior performance of hybrids relative to the parents. Utilization of heterosis has contributed tremendously to the increased productivity in many crops for decades. Although there have been a range of studies on various aspects of heterosis, the key to understanding the biological mechanisms of heterotic performance in crop hybrids is the genetic basis, much of which is still uncharacterized. In this study, we dissected the genetic composition of yield and yield component traits using data of replicated field trials of an “immortalized F₂” population derived from an elite rice hybrid. On the basis of an ultrahigh-density SNP bin map constructed with population sequencing, we calculated single-locus and epistatic genetic effects in the whole genome and identified components pertaining to heterosis of the hybrid. The results showed that the relative contributions of the genetic components varied with traits. Overdominance/pseudo-overdominance is the most important contributor to heterosis of yield, number of grains per panicle, and grain weight. Dominance × dominance interaction is important for heterosis of tillers per plant and grain weight and has roles in yield and grain number. Single-locus dominance has relatively small contributions in all of the traits. The results suggest that cumulative effects of these components may adequately explain the genetic basis of heterosis in the hybrid.