Differentiation of the two rice subspecies indica and japonica: a Gene Ontology perspective

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.

Balance between a higher degree of heterosis and increased reproductive isolation: a strategic design for breeding inter-subspecific hybrid rice

The application of heterosis (hybrid vigor) has brought great success to plant breeding, particularly of hybrid rice, achieving significant yield increases. Attempts to explore the heterosis of inter-subspecific hybrids between indica and japonica rice, which result in even greater yield increases, have greatly increased in the past decades. However, because of the reduced seed setting rate in F1 hybrids as a result of increased reproductive isolation, the application of inter-subspecific hybrids in rice has slowed. Understanding the balance between heterosis and the reproductive isolation of inter-subspecific hybrids will facilitate the strategic design of inter-subspecific hybrid breeding. In this study, five indica and seven japonica rice varieties were chosen as the parental lines of a complete diallel mating design. Data from six group traits from all of the hybrids and inbred lines were collected. We found that the grain weight per plant, grain number per panicle, tiller per plant, thousand grain weight and plant height, which reflected increased heterosis, were associated with the genetic divergence index (GDI) of the parents. Meanwhile, owing to the reduced seed setting rate, which was also associated with the parents' GDI, the grain production of the hybrids was negatively affected. After analyzing the relationships between the GDI of indica-japonica parents and the grain weight per plant of the F1 hybrids, an ideal GDI value (0.37) for the two indica-japonica parents that could provide an optimal balance between the inter-subspecific heterosis and reproductive isolation was proposed. Our findings will help in the strategic design of an inter-subspecific hybrid rice breeding program by identifying the ideal indica and japonica parents for a hybrid combination to achieve hybrid rice with an optimal yield. This strategic design of an inter-subspecific hybrid rice breeding program will be time saving and cost effective.

Genome-wide identification and analysis of Japonica and Indica cultivar-preferred transcripts in rice using 983 Affymetrix array data

BACKGROUND

Accumulation of genome-wide transcriptome data provides new insight on a genomic scale which cannot be gained by analyses of individual data. The majority of rice (O. sativa) species are japonica and indica cultivars. Genome-wide identification of genes differentially expressed between japonica and indica cultivars will be very useful in understanding the domestication and evolution of rice species.

RESULTS

In this study, we analyzed 983 of the 1866 entries in the Affymetrix array data in the public database: 595 generated from indica and 388 from japonica rice cultivars. To discover differentially expressed genes in each cultivar, we performed significance analysis of microarrays for normalized data, and identified 490 genes preferentially expressed in japonica and 104 genes in indica. Gene Ontology analyses revealed that defense response-related genes are significantly enriched in both cultivars, indicating that japonica and indica might be under strong selection pressure for these traits during domestication. In addition, 36 (34.6%) of 104 genes preferentially expressed in indica and 256 (52.2%) of 490 genes preferentially expressed in japonica were annotated as genes of unknown function. Biotic stress overview in the MapMan toolkit revealed key elements of the signaling pathway for defense response in japonica or indica eQTLs.

CONCLUSIONS

The percentage of screened genes preferentially expressed in indica was 4-fold higher (34.6%) and that in japonica was 5-fold (52.2%) higher than expected (11.1%), suggesting that genes of unknown function are responsible for the novel traits that distinguish japonica and indica cultivars. The identification of 10 functionally characterized genes expressed preferentially in either japonica or indica highlights the significance of our candidate genes during the domestication of rice species. Functional analysis of the roles of individual components of stress-mediated signaling pathways will shed light on potential molecular mechanisms to improve disease resistance in rice.

Gene expression profiles deciphering rice phenotypic variation between Nipponbare (Japonica) and 93-11 (Indica) during oxidative stress

Rice is a very important food staple that feeds more than half the world's population. Two major Asian cultivated rice (Oryza sativa L.) subspecies, japonica and indica, show significant phenotypic variation in their stress responses. However, the molecular mechanisms underlying this phenotypic variation are still largely unknown. A common link among different stresses is that they produce an oxidative burst and result in an increase of reactive oxygen species (ROS). In this study, methyl viologen (MV) as a ROS agent was applied to investigate the rice oxidative stress response. We observed that 93-11 (indica) seedlings exhibited leaf senescence with severe lesions under MV treatment compared to Nipponbare (japonica). Whole-genome microarray experiments were conducted, and 1,062 probe sets were identified with gene expression level polymorphisms between the two rice cultivars in addition to differential expression under MV treatment, which were assigned as Core Intersectional Probesets (CIPs). These CIPs were analyzed by gene ontology (GO) and highlighted with enrichment GO terms related to toxin and oxidative stress responses as well as other responses. These GO term-enriched genes of the CIPs include glutathine S-transferases (GSTs), P450, plant defense genes, and secondary metabolism related genes such as chalcone synthase (CHS). Further insertion/deletion (InDel) and regulatory element analyses for these identified CIPs suggested that there may be some eQTL hotspots related to oxidative stress in the rice genome, such as GST genes encoded on chromosome 10. In addition, we identified a group of marker genes individuating the japonica and indica subspecies. In summary, we developed a new strategy combining biological experiments and data mining to study the possible molecular mechanism of phenotypic variation during oxidative stress between Nipponbare and 93-11. This study will aid in the analysis of the molecular basis of quantitative traits.

Refinement of light-responsive transcript lists using rice oligonucleotide arrays: evaluation of gene-redundancy

Studies of gene function are often hampered by gene-redundancy, especially in organisms with large genomes such as rice (Oryza sativa). We present an approach for using transcriptomics data to focus functional studies and address redundancy. To this end, we have constructed and validated an inexpensive and publicly available rice oligonucleotide near-whole genome array, called the rice NSF45K array. We generated expression profiles for light- vs. dark-grown rice leaf tissue and validated the biological significance of the data by analyzing sources of variation and confirming expression trends with reverse transcription polymerase chain reaction. We examined trends in the data by evaluating enrichment of gene ontology terms at multiple false discovery rate thresholds. To compare data generated with the NSF45K array with published results, we developed publicly available, web-based tools (www.ricearray.org). The Oligo and EST Anatomy Viewer enables visualization of EST-based expression profiling data for all genes on the array. The Rice Multi-platform Microarray Search Tool facilitates comparison of gene expression profiles across multiple rice microarray platforms. Finally, we incorporated gene expression and biochemical pathway data to reduce the number of candidate gene products putatively participating in the eight steps of the photorespiration pathway from 52 to 10, based on expression levels of putatively functionally redundant genes. We confirmed the efficacy of this method to cope with redundancy by correctly predicting participation in photorespiration of a gene with five paralogs. Applying these methods will accelerate rice functional genomics.