Asian rice, Oryza sativa is a cultivated, inbreeding species that feeds over half of the world's population. Understanding the genetic basis of diverse physiological, developmental, and morphological traits provides the basis for improving yield, quality and sustainability of rice. Here we show the results of a genome-wide association study based on genotyping 44,100 SNP variants across 413 diverse accessions of O. sativa collected from 82 countries that were systematically phenotyped for 34 traits. Using cross-population-based mapping strategies, we identified dozens of common variants influencing numerous complex traits. Significant heterogeneity was observed in the genetic architecture associated with subpopulation structure and response to environment. This work establishes an open-source translational research platform for genome-wide association studies in rice that directly links molecular variation in genes and metabolic pathways with the germplasm resources needed to accelerate varietal development and crop improvement.

BackgroundThe domestication of Asian rice (Oryza sativa) was a complex process punctuated by episodes of introgressive hybridization among and between subpopulations. Deep genetic divergence between the two main varietal groups (Indica and Japonica) suggests domestication from at least two distinct wild populations. However, genetic uniformity surrounding key domestication genes across divergent subpopulations suggests cultural exchange of genetic material among ancient farmers.Methodology/Principal FindingsIn this study, we utilize a novel 1,536 SNP panel genotyped across 395 diverse accessions of O. sativa to study genome-wide patterns of polymorphism, to characterize population structure, and to infer the introgression history of domesticated Asian rice. Our population structure analyses support the existence of five major subpopulations (indica, aus, tropical japonica, temperate japonica and GroupV) consistent with previous analyses. Our introgression analysis shows that most accessions exhibit some degree of admixture, with many individuals within a population sharing the same introgressed segment due to artificial selection. Admixture mapping and association analysis of amylose content and grain length illustrate the potential for dissecting the genetic basis of complex traits in domesticated plant populations.Conclusions/SignificanceGenes in these regions control a myriad of traits including plant stature, blast resistance, and amylose content. These analyses highlight the power of population genomics in agricultural systems to identify functionally important regions of the genome and to decipher the role of human-directed breeding in refashioning the genomes of a domesticated species.

Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variation in eukaryotic genomes. SNPs may be functionally responsible for specific traits or phenotypes, or they may be informative for tracing the evolutionary history of a species or the pedigree of a variety. As genetic markers, SNPs are rapidly replacing simple sequence repeats (SSRs) because they are more abundant, stable, amenable to automation, efficient, and increasingly cost-effective. The integration of high throughput SNP genotyping capability promises to accelerate genetic gain in a breeding program, but also imposes a series of economic, organizational and technical hurdles. To begin to address these challenges, SNP-based resources are being developed and made publicly available for broad application in rice research. These resources include large SNP datasets, tools for identifying informative SNPs for targeted applications, and a suite of custom-designed SNP assays for use in marker-assisted and genomic selection, association and QTL mapping, positional cloning, pedigree analysis, variety identification and seed purity testing. SNP resources also make it possible for breeders to more efficiently evaluate and utilize the wealth of natural variation that exists in both wild and cultivated germplasm with the aim of improving the productivity and sustainability of agriculture.

The Rice Diversity Panel 1 (Reg. No. MP‐6, NSL 500357 MAP) (RDP1) is a collection of 421 purified, homozygous rice (Oryza sativa L.) accessions (GSOR 301001 through GSOR 301421; GSOR 312001 through 312020) representing the broad range of genetic variation within O. sativa. The accessions include both landraces and elite rice cultivars, which were classified into five subpopulation groups, including indica (95 accessions) and aus (60), which belong to the Indica varietal group, and tropical japonica (106), temperate japonica (111), and aromatic (Group V) (16) which comprise the Japonica varietal group. Thirty‐three accessions are classified as admixtures because they shared <60% ancestry with a single group. The seed, with and without the hull, and panicle morphology of each accession were documented with digital images, and the RDP1 was phenotyped for morphological, developmental, and physiological traits. Genotypes for 36,901 SNP loci are publicly available for additional genomewide association mapping studies. In this report, we evaluate three grain quality traits on the RDP1: apparent amylose content (AC), gelatinization temperature as measured by alkali spreading value (ASV), and protein content. Canonical discriminant analysis revealed AC was the quality trait most closely correlated with subpopulation structure, followed by ASV. These traits indicate that temperate japonica was the most distinct group, whereas aus and indica could not be differentiated, and the aromatic accessions were closest to tropical japonica.

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Wild species of rice (genus Oryza) contain many useful genes but a vast majority of these genes remain untapped to date because it is often difficult to transfer these genes into cultivated rice (Oryza sativa L.). Chromosome segment substitution lines (CSSLs) and backcross inbred lines (BILs) are powerful tools for identifying these naturally occurring, favorable alleles in unadapted germplasm. In this paper, we present an overview of the research involving CSSLs and BILs in the introgression of quantitative trait loci (QTLs) associated with the improved performance of rice including resistance to various biotic and abiotic stresses, and even high yield from wild relatives of rice and other unadapted germplasm into the genetic background of adapted rice cultivars. The CSSLs can be used to dissect quantitative traits into the component genetic factors and evaluate gene action as single factors (monogenic loci). CSSLs have the potential to uncover new alleles from the unadapted, non-productive wild rice accessions, develop genome-wide genetic stocks, and clone genes identified in QTL studies for functional genomics research. Recent development of high-density singlenucleotide polymorphism (SNP) arrays in rice and availability of custom-designed medium-and low-density SNP arrays will enhance the CSSL development process with smaller marker-defined segment introgressions from unadapted germplasm.

In the rainfed lowlands, rice ( Oryza sativa L.) develops roots under anaerobic soil conditions with ponded water, prior to exposure to water stress and aerobic soil conditions that arise later in the season. Constitutive root system development in anaerobic soil conditions has been reported to have a positive effect on subsequent expression of adaptive root traits and water extraction during progressive water stress in aerobic soil conditions. We examined quantitative trait loci (QTLs) for constitutive root morphology traits using a mapping population derived from a cross between two rice lines which were well-adapted to rainfed lowland conditions. The effects of phenotyping environment and genetic background on QTLs identification were examined by comparing the experimental data with published results from four other populations. One hundred and eighty-four recombinant inbred lines (RILs) from a lowland indica cross (IR58821/IR52561) were grown under anaerobic conditions in two experiments. Seven traits, categorized into three groups (shoot biomass, deep root morphology, root thickness) were measured during the tillering stage. Though parental lines showed consistent differences in shoot biomass and root morphology traits across the two seasons, genotype-by-environment interaction (GxE) and QTL-by-environment interaction were significant among the progeny. Two, twelve, and eight QTLs for shoot biomass, deep root morphology, and root thickness, respectively, were identified, with LOD scores ranging from 2.0 to 12.8. Phenotypic variation explained by a single QTL ranged from 6% to 30%. Only two QTLs for deep root morphology, in RG256-RG151 in chromosome 2 and in PC75M3-PC11M4 in chromosome 4, were identified in both experiments. Comparison of positions of QTLs across five mapping populations (the current population plus populations from four other studies) revealed that these two QTLs for deep root morphology were only identified in populations that were phenotyped under anaerobic conditions. Fourteen and nine chromosome regions overlapped across different populations as putative QTLs for deep root morphology and root thickness, respectively. PC41M2-PC173M5 in chromosome 2 was identified as an interval that had QTLs for deep root morphology in four mapping populations. The PC75M3-PC11M4 interval in chromosome 4 was identified as a QTL for root thickness in three mapping populations with phenotypic variation explained by a single QTL consistently as large as 20-30%. Three QTLs for deep root morphology were found only in japonica/indica populations but not in IR58821/IR52561. The results identifying chromosome regions that had putative QTLs for deep root morphology and root thickness over different mapping populations indicate potential for marker-assisted selection for these traits.

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