Here we analyse genetic variation, population structure and diversity among 3,010 diverse Asian cultivated rice (Oryza sativa L.) genomes from the 3,000 Rice Genomes Project. Our results are consistent with the five major groups previously recognized, but also suggest several unreported subpopulations that correlate with geographic location. We identified 29 million single nucleotide polymorphisms, 2.4 million small indels and over 90,000 structural variations that contribute to within-and between-population variation. Using pan-genome analyses, we identified more than 10,000 novel full-length protein-coding genes and a high number of presence-absence variations. The complex patterns of introgression observed in domestication genes are consistent with multiple independent rice domestication events. The public availability of data from the 3,000 Rice Genomes Project provides a resource for rice genomics research and breeding.Asian cultivated rice is grown worldwide and comprises the staple food for half of the global population. It is envisaged that by the year 2035 1 feeding this growing population will necessitate that an additional 112 million metric tons of rice be produced on a smaller area of land, using less water and under more fluctuating climatic conditions, which will require that future rice cultivars be higher yielding and resilient to multiple abiotic and biotic stresses. The foundation of the continued improvement of rice cultivars is the rich genetic diversity within domesticated populations and wild relatives [2][3][4] . For over 2,000 years, two major types of O. sativa-O. sativa Xian group (here referred to as Xian/Indica (XI) and also known as , Hsien or Indica) and O. sativa Geng Group (here referred to as Geng/Japonica (GJ) and also known as , Keng or Japonica)-have historically been recognized [5][6][7] . Varied degrees of post-reproductive barriers exist between XI and GJ rice accessions 8 ; this differentiation between XI and GJ rice types and the presence of different varietal groups are well-documented at isozyme and DNA levels 6,9 . Two other distinct groups have also been recognized using molecular markers 10 ; one of these encompasses the Aus, Boro and Rayada ecotypes from Bangladesh and India (which we term the circum-Aus group (cA)) and the other comprises the famous Basmati and Sadri aromatic varieties (which we term the circum-Basmati group (cB)).Approximately 780,000 rice accessions are available in gene banks worldwide 11 . To enable the more efficient use of these accessions in future rice improvement, the Chinese Academy of Agricultural Sciences, BGI-Shenzhen and International Rice Research Institute sequenced over 3,000 rice genomes (3K-RG) as part of the 3,000 Rice Genomes Project 12. Here we present analyses of genetic variation in the 3K-RG that focus on important aspects of O. sativa diversity, single nucleotide polymorphisms (SNPs) and structural variation (deletions, duplications, inversions and translocations). We also construct a species pangenome consisting of 'core...

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To genetically dissect drought resistance associated with japonica upland rice, we evaluated a doubled haploid (DH) population from a cross between two japonica cultivars for seven root traits under three different growing conditions (upland, lowland and upland in PVC pipe). The traits included basal root thickness (BRT), total root number (RN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW), ratio of root fresh weight to shoot fresh weight (RFW/SFW) and ratio of root dry weight to shoot dry weight (RDW/SDW). The BRT was significantly correlated with the index of drought resistance, which was defined as the ratio of yield under the stress of the upland condition to that under the normal lowland condition. A complete genetic linkage map with 165 molecular markers covering 1,535 cM was constructed. Seven additive quantitative trait loci (QTLs) and 15 pairs of epistatic loci for BRT and RN were identified under upland and lowland conditions, and 12 additive QTLs and 17 pairs of epistatic QTLs for BRT, RN, MRL, RFW, RFW/SFW and RDW/SDW were identified under the PVC pipe condition. Four additive QTLs and one pair of epistatic QTLs controlling IDR were also found. These QTLs individually explained up to 25.6% of the phenotypic variance. QTL x environment (Q x E) interactions were detected for all root traits, and the contributions of these interactions ranged from 1.1% to 19.9%. Five co-localized QTLs controlling RFW and RDW, RFW/SFW, RDW/SDW and IDR, BRT and RN, RN, MRL and IDR were found. Four types of QTLs governing BRT and RN were classified by their detection in the upland and lowland conditions. Some common QTLs for root traits across different backgrounds were also revealed. These co-localized QTLs and common QTLs will facilitate marker-assisted selection for root traits in rice breeding programs.

Tremendous efforts have been taken worldwide to develop genome-wide genetic stocks for rice functional genomic (FG) research since the rice genome was completely sequenced. To facilitate FG research of complex polygenic phenotypes in rice, we report the development of over 20,000 introgression lines (ILs) in three elite rice genetic backgrounds for a wide range of complex traits, including resistances/tolerances to many biotic and abiotic stresses, morpho-agronomic traits, physiological traits, etc., by selective introgression. ILs within each genetic background are phenotypically similar to their recurrent parent but each carries one or a few traits introgressed from a known donor. Together, these ILs contain a significant portion of loci affecting the selected complex phenotypes at which allelic diversity exists in the primary gene pool of rice. A forward genetics strategy was proposed and demonstrated with examples on how to use these ILs for large-scale FG research. Complementary to the genome-wide insertional mutants, these ILs opens a new way for highly efficient discovery, candidate gene identification and cloning of important QTLs for specific phenotypes based on convergent evidence from QTL position, expression profiling, functional and molecular diversity analyses of candidate genes, highlights the importance of genetic networks underlying complex phenotypes in rice that may ultimately lead to more complete understanding of the genetic and molecular bases of quantitative trait variation in rice.

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BackgroundMost agronomic traits in rice are complex and polygenic. The identification of quantitative trait loci (QTL) for grain length is an important objective of rice genetic research and breeding programs.ResultsHerein, we identified 99 QTL for grain length by GWAS based on approximately 10 million single nucleotide polymorphisms from 504 cultivated rice accessions (Oryza sativa L.), 13 of which were validated by four linkage populations and 92 were new loci for grain length. We scanned the Ho (observed heterozygosity per locus) index of coupled-parents of crosses mapping the same QTL, based on linkage and association mapping, and identified two new genes for grain length. We named this approach as Ho-LAMap. A simulation study of six known genes showed that Ho-LAMap could mine genes rapidly across a wide range of experimental variables using deep-sequencing data. We used Ho-LAMap to clone a new gene, OsLG3, as a positive regulator of grain length, which could improve rice yield without influencing grain quality. Sequencing of the promoter region in 283 rice accessions from a wide geographic range identified four haplotypes that seem to be associated with grain length. Further analysis showed that OsLG3 alleles in the indica and japonica evolved independently from distinct ancestors and low nucleotide diversity of OsLG3 in indica indicated artificial selection. Phylogenetic analysis showed that OsLG3 might have much potential value for improvement of grain length in japonica breeding.ConclusionsThe results demonstrated that Ho-LAMap is a potential approach for gene discovery and OsLG3 is a promising gene to be utilized in genomic assisted breeding for rice cultivar improvement.Electronic supplementary materialThe online version of this article (doi:10.1186/s12915-017-0365-7) contains supplementary material, which is available to authorized users.

Roots are a vital organ for absorbing soil moisture and nutrients and influence drought resistance. The identification of quantitative trait loci (QTLs) with molecular markers may allow the estimation of parameters of genetic architecture and improve root traits by molecular marker-assisted selection (MAS). A mapping population of 120 recombinant inbred lines (RILs) derived from a cross between japonica upland rice 'IRAT109' and paddy rice 'Yuefu' was used for mapping QTLs of developmental root traits. All plant material was grown in PVC-pipe. Basal root thickness (BRT), root number (RN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW) and root volume (RV) were phenotyped at the seedling (I), tillering (II), heading (III), grain filling (IV) and mature (V) stages, respectively. Phenotypic correlations showed that BRT was positively correlated to MRL at the majority of stages, but not correlated with RN. MRL was not correlated to RN except at the seedling stage. BRT, MRL and RN were positively correlated to RFW, RDW and RV at all growth stages. QTL analysis was performed using QTLMapper 1.6 to partition the genetic components into additive-effect QTLs, epistatic QTLs and QTL-by-year interactions (Q x E) effect. The results indicated that the additive effects played a major role for BRT, RN and MRL, while for RFW, RDW and RV the epistatic effects showed an important action and Q x E effect also played important roles in controlling root traits. A total of 84 additive-effect QTLs and 86 pairs of epistatic QTLs were detected for the six root traits at five stages. Only 12 additive QTLs were expressed in at least two stages. This indicated that the majority of QTLs were developmental stage specific. Two main effect QTLs, brt9a and brt9b, were detected at the heading stage and explained 19% and 10% of the total phenotypic variation in BRT without any influence from the environment. These QTLs can be used in breeding programs for improving root traits.

A large set of 254 introgression lines in an elite indica genetic background were evaluated for grain yield (GY) and related traits under the irrigated (control) and drought (stress) conditions in two consecutive years for genetic dissection of adaptive strategies of rice to water stress. A total of 36 quantitative trait loci (QTLs) affecting heading date (HD), plant height (PH), GY and yield components were identified and most QTLs showed pronounced differential expression either qualitatively or quantitatively in response to drought. These QTLs could be grouped into three major types based on their behaviors under control and stress conditions. Type I included 12 QTLs that expressed under both the stress and non-stress conditions. Type II comprised 17 QTLs that expressed under irrigation but not under stress. Type III included seven QTLs that were apparently induced by stress. The observation that the Lemont (japonica) alleles at all HD QTLs except QHd5 resulted in early heading under stress appeared to be responsible for the putative adaptation of Lemont to drought by escaping, whereas the Teqing (indica) alleles at most PH/GY QTLs were consistently associated with increased yield potential and trait stability and thus contributed to DT. Our result that most DT QTLs were non-allelic with QTLs for drought escaping suggests that the two adaptive strategies in the parental lines are under possible negative regulation of two largely non-overlapping genetic systems.