Gongwei Wang

Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism

Plant metabolites are important to world food security in terms of maintaining sustainable yield and providing food with enriched phytonutrients. Here we report comprehensive profiling of 840 metabolites and a further metabolic genome-wide association study based on ∼6.4 million SNPs obtained from 529 diverse accessions of Oryza sativa. We identified hundreds of common variants influencing numerous secondary metabolites with large effects at high resolution. We observed substantial heterogeneity in the natural variation of metabolites and their underlying genetic architectures among different subspecies of rice. Data mining identified 36 candidate genes modulating levels of metabolites that are of potential physiological and nutritional importance. As a proof of concept, we functionally identified or annotated five candidate genes influencing metabolic traits. Our study provides insights into the genetic and biochemical bases of rice metabolome variation and can be used as a powerful complementary tool to classical phenotypic trait mapping for rice improvement.

Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice

Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1. Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits.

Chalk5 encodes a vacuolar H+-translocating pyrophosphatase influencing grain chalkiness in rice

Grain chalkiness is a highly undesirable quality trait in the marketing and consumption of rice grain. However, the molecular basis of this trait is poorly understood. Here we show that a major quantitative trait locus (QTL), Chalk5, influences grain chalkiness, which also affects head rice yield and many other quality traits. Chalk5 encodes a vacuolar H+-translocating pyrophosphatase (V-PPase) with inorganic pyrophosphate (PPi) hydrolysis and H+-translocation activity. Elevated expression of Chalk5 increases the chalkiness of the endosperm, putatively by disturbing the pH homeostasis of the endomembrane trafficking system in developing seeds, which affects the biogenesis of protein bodies and is coupled with a great increase in small vesicle-like structures, thus forming air spaces among endosperm storage substances and resulting in chalky grain. Our results indicate that two consensus nucleotide polymorphisms in the Chalk5 promoter in rice varieties might partly account for the differences in Chalk5 mRNA levels that contribute to natural variation in grain chalkiness.

RiceVarMap: a comprehensive database of rice genomic variations

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.

Extensive sequence divergence between the reference genomes of two elite indica rice varieties Zhenshan 97 and Minghui 63

Significance Indica rice accounts for >70% of total rice production worldwide, is genetically highly diverse, and can be divided into two major varietal groups independently bred and widely cultivated in China and Southeast Asia. Here, we generated high-quality genome sequences for two elite rice varieties, Zhenshan 97 and Minghui 63, representing the two groups of indica rice and the parents of a leading rice hybrid. Comparative analyses uncovered extensive structural differences between the two genomes and complementarity in their hybrid transcriptome. These findings have general implications for understanding intraspecific variations of organisms with complex genomes. The availability of the two genomes will serve as a foundation for future genome-based explorations in rice toward both basic and applied goals. Asian cultivated rice consists of two subspecies: Oryza sativa subsp. indica and O. sativa subsp. japonica. Despite the fact that indica rice accounts for over 70% of total rice production worldwide and is genetically much more diverse, a high-quality reference genome for indica rice has yet to be published. We conducted map-based sequencing of two indica rice lines, Zhenshan 97 (ZS97) and Minghui 63 (MH63), which represent the two major varietal groups of the indica subspecies and are the parents of an elite Chinese hybrid. The genome sequences were assembled into 237 (ZS97) and 181 (MH63) contigs, with an accuracy >99.99%, and covered 90.6% and 93.2% of their estimated genome sizes. Comparative analyses of these two indica genomes uncovered surprising structural differences, especially with respect to inversions, translocations, presence/absence variations, and segmental duplications. Approximately 42% of nontransposable element related genes were identical between the two genomes. Transcriptome analysis of three tissues showed that 1,059–2,217 more genes were expressed in the hybrid than in the parents and that the expressed genes in the hybrid were much more diverse due to their divergence between the parental genomes. The public availability of two high-quality reference genomes for the indica subspecies of rice will have large-ranging implications for plant biology and crop genetic improvement.

Breeding signatures of rice improvement revealed by a genomic variation map from a large germplasm collection

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. 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.

OsAAP6 functions as an important regulator of grain protein content and nutritional quality in rice

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) qPC1 in rice controls GPC by regulating the synthesis and accumulation of glutelins, prolamins, globulins, albumins and starch. qPC1 encodes a putative amino acid transporter OsAAP6, which functions as a positive regulator of GPC in rice, such that higher expression of OsAAP6 is correlated with higher GPC. OsAAP6 greatly enhances root absorption of a range of amino acids and has effects on the distribution of various amino acids. Two common variations in the potential cis-regulatory elements of the OsAAP6 5′-untranslated region seem to be associated with GPC diversity mainly in indica cultivars. Our results represent the first step toward unravelling the mechanism of regulation underlying natural variation of GPC in rice.

Combinations of the Ghd7, Ghd8 and Hd1 genes largely define the ecogeographical adaptation and yield potential of cultivated rice

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.

Building two indica rice reference genomes with PacBio long-read and Illumina paired-end sequencing data

Over the past 30 years, we have performed many fundamental studies on two Oryza sativa subsp. indica varieties, Zhenshan 97 (ZS97) and Minghui 63 (MH63). To improve the resolution of many of these investigations, we generated two reference-quality reference genome assemblies using the most advanced sequencing technologies. Using PacBio SMRT technology, we produced over 108 (ZS97) and 174 (MH63) Gb of raw sequence data from 166 (ZS97) and 209 (MH63) pools of BAC clones, and generated ~97 (ZS97) and ~74 (MH63) Gb of paired-end whole-genome shotgun (WGS) sequence data with Illumina sequencing technology. With these data, we successfully assembled two platinum standard reference genomes that have been publicly released. Here we provide the full sets of raw data used to generate these two reference genome assemblies. These data sets can be used to test new programs for better genome assembly and annotation, aid in the discovery of new insights into genome structure, function, and evolution, and help to provide essential support to biological research in general.

Genome-wide association studies reveal that members of bHLH subfamily 16 share a conserved function in regulating flag leaf angle in rice (Oryza sativa)

As a major component of ideal plant architecture, leaf angle especially flag leaf angle (FLA) makes a large contribution to grain yield in rice. We utilized a worldwide germplasm collection to elucidate the genetic basis of FLA that would be helpful for molecular design breeding in rice. Genome-wide association studies (GWAS) identified a total of 40 and 32 QTLs for FLA in Wuhan and Hainan, respectively. Eight QTLs were commonly detected in both conditions. Of these, 2 and 3 QTLs were identified in the indica and japonica subpopulations, respectively. In addition, the candidates of 5 FLA QTLs were verified by haplotype-level association analysis. These results indicate diverse genetic bases for FLA between the indica and japonica subpopulations. Three candidates, OsbHLH153, OsbHLH173 and OsbHLH174, quickly responded to BR and IAA involved in plant architecture except for OsbHLH173, whose expression level was too low to be detected; their overexpression in plants increased rice leaf angle. Together with previous studies, it was concluded that all 6 members in bHLH subfamily 16 had the conserved function in regulating FLA in rice. A comparison with our previous GWAS for tiller angle (TA) showed only one QTL had pleiotropic effects on FLA and TA, which explained low similarity of the genetic basis between FLA and TA. An ideal plant architecture is expected to be efficiently developed by combining favorable alleles for FLA from indica with favorable alleles for TA from japonica by inter-subspecies hybridization.