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.) is one of the most important cereal crops in the world. There have been landmark achievements in rice improvement over the past 50 y, especially in the indica subspecies. A major breakthrough resulted from the independent development of a series of semidwarf varieties in China and by the International Rice Research Institute (IRRI) in the 1950s and 1960s, leading to the "green revolution" in rice. Since then, semidwarfness has been a basic characteristic for almost all modern varieties. Based on semidwarf varieties, improvement for other traits, such as abiotic stress resistance, broad-spectrum resistances to biotic stresses, and better grain quality, has also been achieved. Another major breakthrough stemmed from the exploitation of hybrid vigor in China (1), resulting in the largescale adoption of hybrid rice since the 1970s. Jointly, these breakthroughs have greatly increased rice productivity in the past several decades globally.Genomic studies in recent years have identified a large number of loci that were under selection during rice domestication (2). However, there has been very limited study to identify loci or genomic regions that have been under selection due to breeding. Next-generation sequencing technologies have enabled sequencing of a large number of rice accessions at relatively low cost, providing opportunities to inspect the genomic regions selected in the history of crop improvement. Meanwhile, genome-wide association studies (GWAS) have provided an effective approach to analyze the genetic architecture of complex traits and allow identification of candidate genes for further improvement of agronomically important traits (3,4).In this study, we analyzed low-coverage sequencing data of 1,479 rice accessions, which revealed a large number of differentially selected regions associated with breeding efforts between two major subpopulations in indica. These selected regi...

Rice (Oryza sativa) is an important dietary source of both essential micronutrients and toxic trace elements for humans. The genetic basis underlying the variations in the mineral composition, the ionome, in rice remains largely unknown. Here, we describe a comprehensive study of the genetic architecture of the variation in the rice ionome performed using genome-wide association studies (GWAS) of the concentrations of 17 mineral elements in rice grain from a diverse panel of 529 accessions, each genotyped at ;6.4 million single nucleotide polymorphism loci. We identified 72 loci associated with natural ionomic variations, 32 that are common across locations and 40 that are common within a single location. We identified candidate genes for 42 loci and provide evidence for the causal nature of three genes, the sodium transporter gene Os-HKT1;5 for sodium, Os-MOLYBDATE TRANSPORTER1;1 for molybdenum, and Grain number, plant height, and heading date7 for nitrogen. Comparison of GWAS data from rice versus Arabidopsis (Arabidopsis thaliana) also identified well-known as well as new candidates with potential for further characterization. Our study provides crucial insights into the genetic basis of ionomic variations in rice and serves as an important foundation for further studies on the genetic and molecular mechanisms controlling the rice ionome.

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.

Rice cultivars have been adapted to favorable ecological regions and cropping seasons. Although several heading date genes have separately made contributions to this adaptation, the roles of gene combinations are still unclear. We employed a map-based cloning approach to isolate a heading date gene, which coordinated the interaction between Ghd7 and Ghd8 to greatly delay rice heading. We resequenced these three genes in a germplasm collection to analyze natural variation. Map-based cloning demonstrated that the gene largely affecting the interaction between Ghd7 and Ghd8 was Hd1. Natural variation analysis showed that a combination of loss-of-function alleles of Ghd7, Ghd8 and Hd1 contributes to the expansion of rice cultivars to higher latitudes; by contrast, a combination of pre-existing strong alleles of Ghd7, Ghd8 and functional Hd1 (referred as SSF) is exclusively found where ancestral Asian cultivars originated. Other combinations have comparatively larger favorable ecological scopes and acceptable grain yield. Our results indicate that the combinations of Ghd7, Ghd8 and Hd1 largely define the ecogeographical adaptation and yield potential in rice cultivars. Breeding varieties with the SSF combination are recommended for tropical regions to fully utilize available energy and light resources and thus produce greater yields.

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Understanding how plants respond to drought can benefit drought resistance (DR) breeding. Using a non-destructive phenotyping facility, 51 image-based traits (i-traits) for 507 rice accessions were extracted. These i-traits can be used to monitor drought responses and evaluate DR. High heritability and large variation of these traits was observed under drought stress in the natural population. A genome-wide association study (GWAS) of i-traits and traditional DR traits identified 470 association loci, some containing known DR-related genes. Of these 470 loci, 443 loci (94%) were identified using i-traits, 437 loci (93%) co-localized with previously reported DR-related quantitative trait loci, and 313 loci (66.6%) were reproducibly identified by GWAS in different years. Association networks, established based on GWAS results, revealed hub i-traits and hub loci. This demonstrates the feasibility and necessity of dissecting the complex DR trait into heritable and simple i-traits. As proof of principle, we illustrated the power of this integrated approach to identify previously unreported DR-related genes. OsPP15 was associated with a hub i-trait, and its role in DR was confirmed by genetic transformation experiments. Furthermore, i-traits can be used for DR linkage analyses, and 69 i-trait locus associations were identified by both GWAS and linkage analysis of a recombinant inbred line population. Finally, we confirmed the relevance of i-traits to DR in the field. Our study provides a promising novel approach for the genetic dissection and discovery of causal genes for DR.

BackgroundThe dispensable genome of a species, consisting of the dispensable sequences present only in a subset of individuals, is believed to play important roles in phenotypic variation and genome evolution. However, construction of the dispensable genome is costly and labor-intensive at present, and so the influence of the dispensable genome in genetic and functional genomic studies has not been fully explored.ResultsWe construct the dispensable genome of rice through a metagenome-like de novo assembly strategy based on low-coverage (1–3×) sequencing data of 1483 cultivated rice (Oryza sativa L.) accessions. Thousands of protein-coding genes are successfully assembled, including most of the known agronomically important genes absent from the Nipponbare rice reference genome. We develop an integration approach based on alignment and linkage disequilibrium, which is able to assign genomic positions relative to the reference genome for more than 78.2 % of the dispensable sequences. We carry out association mapping studies for rice grain width and 840 metabolic traits using 0.46 million polymorphisms between the dispensable sequences of different rice accessions. About 23.5 % of metabolic traits have more significant association signals with polymorphisms from dispensable sequences than with SNPs from the reference genome, and 41.6 % of trait-associated SNPs have concordant genomic locations with associated dispensable sequences.ConclusionsOur results suggest the feasibility of building a species’ dispensable genome using low-coverage population sequencing data. The constructed sequences will be helpful for understanding the rice dispensable genome and are complementary to the reference genome for identifying candidate genes associated with phenotypic variation.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0757-3) contains supplementary material, which is available to authorized users.

Tiller angle is one of the most important components of the ideal plant architecture that can greatly enhance rice grain yield. Understanding the genetic basis of tiller angle and mining favorable alleles will be helpful for breeding new plant-type varieties. Here, we performed genome-wide association studies (GWAS) to identify genes controlling tiller angle using 529 diverse accessions of Oryza sativa including 295 indica and 156 japonica accessions in two environments. We identified 7 common quantitative trait loci (QTLs), including the previously reported major gene Tiller Angle Control 1 (TAC1), in the two environments, 10 and 13 unique QTLs in Hainan and Wuhan, respectively. More QTLs were identified in indica than in japonica, and three major QTLs (qTA3, qTA1b/DWARF2 (D2) and qTA9c/TAC1) were fixed in japonica but segregating in indica, which explained the wider variation observed in indica compared with that in japonica. No common QTLs were identified between the indica and japonica subpopulations. Mutant analysis for the candidate gene of qTA3 on chromosome 3 indicated a novel gene, Tiller Angle Control 3 (TAC3), encoding a conserved hypothetical protein controlling tiller angle. TAC3 is preferentially expressed in the tiller base. The ebisu dwarf (d2) mutant exhibited a decreased tiller angle, in addition to its previously described abnormal phenotype. A nucleotide diversity analysis revealed that TAC3, D2 and TAC1 have been subjected to selection during japonica domestication. A haplotype analysis identified favorable alleles of TAC3, D2 and TAC1, which may be used for breeding plants with an ideal architecture. In conclusion, there is a diverse genetic basis for tiller angle between the two subpopulations, and it is the novel gene TAC3 together with TAC1, D2, and other newly identified genes in this study that controls tiller angle in rice cultivars.