Yoshihiro Kawahara

Improvement of the Oryza sativa Nipponbare reference genome using next generation sequence and optical map data

BackgroundRice research has been enabled by access to the high quality reference genome sequence generated in 2005 by the International Rice Genome Sequencing Project (IRGSP). To further facilitate genomic-enabled research, we have updated and validated the genome assembly and sequence for the Nipponbare cultivar of Oryza sativa (japonica group).ResultsThe Nipponbare genome assembly was updated by revising and validating the minimal tiling path of clones with the optical map for rice. Sequencing errors in the revised genome assembly were identified by re-sequencing the genome of two different Nipponbare individuals using the Illumina Genome Analyzer II/IIx platform. A total of 4,886 sequencing errors were identified in 321 Mb of the assembled genome indicating an error rate in the original IRGSP assembly of only 0.15 per 10,000 nucleotides. A small number (five) of insertions/deletions were identified using longer reads generated using the Roche 454 pyrosequencing platform. As the re-sequencing data were generated from two different individuals, we were able to identify a number of allelic differences between the original individual used in the IRGSP effort and the two individuals used in the re-sequencing effort. The revised assembly, termed Os-Nipponbare-Reference-IRGSP-1.0, is now being used in updated releases of the Rice Annotation Project and the Michigan State University Rice Genome Annotation Project, thereby providing a unified set of pseudomolecules for the rice community.ConclusionsA revised, error-corrected, and validated assembly of the Nipponbare cultivar of rice was generated using optical map data, re-sequencing data, and manual curation that will facilitate on-going and future research in rice. Detection of polymorphisms between three different Nipponbare individuals highlights that allelic differences between individuals should be considered in diversity studies.

Rice Annotation Project Database (RAP-DB): an integrative and interactive database for rice genomics.

The Rice Annotation Project Database (RAP-DB, http://rapdb.dna.affrc.go.jp/) has been providing a comprehensive set of gene annotations for the genome sequence of rice, Oryza sativa (japonica group) cv. Nipponbare. Since the first release in 2005, RAP-DB has been updated several times along with the genome assembly updates. Here, we present our newest RAP-DB based on the latest genome assembly, Os-Nipponbare-Reference-IRGSP-1.0 (IRGSP-1.0), which was released in 2011. We detected 37,869 loci by mapping transcript and protein sequences of 150 monocot species. To provide plant researchers with highly reliable and up to date rice gene annotations, we have been incorporating literature-based manually curated data, and 1,626 loci currently incorporate literature-based annotation data, including commonly used gene names or gene symbols. Transcriptional activities are shown at the nucleotide level by mapping RNA-Seq reads derived from 27 samples. We also mapped the Illumina reads of a Japanese leading japonica cultivar, Koshihikari, and a Chinese indica cultivar, Guangluai-4, to the genome and show alignments together with the single nucleotide polymorphisms (SNPs) and gene functional annotations through a newly developed browser, Short-Read Assembly Browser (S-RAB). We have developed two satellite databases, Plant Gene Family Database (PGFD) and Integrative Database of Cereal Gene Phylogeny (IDCGP), which display gene family and homologous gene relationships among diverse plant species. RAP-DB and the satellite databases offer simple and user-friendly web interfaces, enabling plant and genome researchers to access the data easily and facilitating a broad range of plant research topics.

Massive parallel sequencing of mRNA in identification of unannotated salinity stress-inducible transcripts in rice (Oryza sativa L.)

BackgroundMicroarray technology is limited to monitoring the expression of previously annotated genes that have corresponding probes on the array. Computationally annotated genes have not fully been validated, because ESTs and full-length cDNAs cannot cover entire transcribed regions. Here, mRNA-Seq (an Illumina cDNA sequencing application) was used to monitor whole mRNAs of salinity stress-treated rice tissues.ResultsThirty-six-base-pair reads from whole mRNAs were mapped to the rice genomic sequence: 72.0% to 75.2% were mapped uniquely to the genome, and 5.0% to 5.7% bridged exons. From the piling up of short reads mapped on the genome, a series of programs (Bowtie, TopHat, and Cufflinks) comprehensively predicted 51,301 (shoot) and 54,491 (root) transcripts, including 2,795 (shoot) and 3,082 (root) currently unannotated in the Rice Annotation Project database. Of these unannotated transcripts, 995 (shoot) and 1,052 (root) had ORFs similar to those encoding the amino acid sequences of functional proteins in a BLASTX search against UniProt and RefSeq databases. Among the unannotated genes, 213 (shoot) and 436 (root) were differentially expressed in response to salinity stress. Sequence-based and array-based measurements of the expression ratios of previously annotated genes were highly correlated.ConclusionUnannotated transcripts were identified on the basis of the piling up of mapped reads derived from mRNAs in rice. Some of these unannotated transcripts encoding putative functional proteins were expressed differentially in response to salinity stress.

Genome-wide transcriptome analysis reveals that cadmium stress signaling controls the expression of genes in drought stress signal pathways in rice.

Plant growth is severely affected by toxic concentrations of the non-essential heavy metal cadmium (Cd). Comprehensive transcriptome analysis by RNA-Seq following cadmium exposure is required to further understand plant responses to Cd and facilitate future systems-based analyses of the underlying regulatory networks. In this study, rice plants were hydroponically treated with 50 µM Cd for 24 hours and ∼60,000 expressed transcripts, including transcripts that could not be characterized by microarray-based approaches, were evaluated. Upregulation of various ROS-scavenging enzymes, chelators and metal transporters demonstrated the appropriate expression profiles to Cd exposure. Gene Ontology enrichment analysis of the responsive transcripts indicated the upregulation of many drought stress-related genes under Cd exposure. Further investigation into the expression of drought stress marker genes such as DREB suggested that expression of genes in several drought stress signal pathways was activated under Cd exposure. Furthermore, qRT-PCR analyses of randomly selected Cd-responsive metal transporter transcripts under various metal ion stresses suggested that the expression of Cd-responsive transcripts might be easily affected by other ions. Our transcriptome analysis demonstrated a new transcriptional network linking Cd and drought stresses in rice. Considering our data and that Cd is a non-essential metal, the network underlying Cd stress responses and tolerance, which plants have developed to adapt to other stresses, could help to acclimate to Cd exposure. Our examination of this transcriptional network provides useful information for further studies of the molecular mechanisms of plant adaptation to Cd exposure and the improvement of tolerance in crop species.

mRNA-Seq Reveals a Comprehensive Transcriptome Profile of Rice under Phosphate Stress

Plants have developed several morphological and physiological strategies to adapt to phosphate stress. We analyzed the inducible transcripts associated with phosphate starvation and over-abundant phosphate supply to characterize the transcriptome in rice seedlings using the mRNA-Seq strategy. Fifty-three million reads obtained from 16 libraries under various phosphate stress and recovery treatments were uniquely mapped to the rice genome. Transcripts identified specifically tagged to 40,574 (root) and 39,748 (shoot) Rice Annotation Project (RAP) transcripts. Additionally, we detected uniquely 10,388 transcripts with no match to any RAP transcript. These transcripts that showed specific response to Pi stress include those without ORFs that may act as non-protein coding transcripts. With an accompanying browser of the transcriptome under Pi stress, a deeper understanding of the structural and functional features of both annotated and unannotated Pi stress-responsive transcripts can provide useful information in improving Pi acquisition and utilization in rice and other cereal crops.

Evola : Ortholog database of all human genes in H-InvDB with manual curation of phylogenetic trees

Orthologs are genes in different species that evolved from a common ancestral gene by speciation. Currently, with the rapid growth of transcriptome data of various species, more reliable orthology information is prerequisite for further studies. However, detection of orthologs could be erroneous if pairwise distance-based methods, such as reciprocal BLAST searches, are utilized. Thus, as a sub-database of H-InvDB, an integrated database of annotated human genes (http://h-invitational.jp/), we constructed a fully curated database of evolutionary features of human genes, called ‘Evola’. In the process of the ortholog detection, computational analysis based on conserved genome synteny and transcript sequence similarity was followed by manual curation by researchers examining phylogenetic trees. In total, 18 968 human genes have orthologs among 11 vertebrates (chimpanzee, mouse, cow, chicken, zebrafish, etc.), either computationally detected or manually curated orthologs. Evola provides amino acid sequence alignments and phylogenetic trees of orthologs and homologs. In ‘dN/dS view’, natural selection on genes can be analyzed between human and other species. In ‘Locus maps’, all transcript variants and their exon/intron structures can be compared among orthologous gene loci. We expect the Evola to serve as a comprehensive and reliable database to be utilized in comparative analyses for obtaining new knowledge about human genes. Evola is available at http://www.h-invitational.jp/evola/.

Retrogenes in Rice (Oryza sativa L. ssp. japonica) Exhibit Correlated Expression with Their Source Genes

Gene duplication occurs by either DNA- or RNA-based processes; the latter duplicates single genes via retroposition of messenger RNA. The expression of a retroposed gene copy (retrocopy) is expected to be uncorrelated with its source gene because upstream promoter regions are usually not part of the retroposition process. In contrast, DNA-based duplication often encompasses both the coding and the intergenic (promoter) regions; hence, expression is often correlated, at least initially, between DNA-based duplicates. In this study, we identified 150 retrocopies in rice (Oryza sativa L. ssp japonica), most of which represent ancient retroposition events. We measured their expression from high-throughput RNA sequencing (RNAseq) data generated from seven tissues. At least 66% of the retrocopies were expressed but at lower levels than their source genes. However, the tissue specificity of retrogenes was similar to their source genes, and expression between retrocopies and source genes was correlated across tissues. The level of correlation was similar between RNA- and DNA-based duplicates, and they decreased over time at statistically indistinguishable rates. We extended these observations to previously identified retrocopies in Arabidopsis thaliana, suggesting they may be general features of the process of retention of plant retrogenes.

A genome-wide survey of changes in protein evolutionary rates across four closely related species of Saccharomyces sensu stricto group.

BackgroundChanges in protein evolutionary rates among lineages have been frequently observed during periods of notable phenotypic evolution. It is also known that, following gene duplication and loss, the protein evolutionary rates of genes involved in such events changed because of changes in functional constraints acting on the genes. However, in the evolution of closely related species, excluding the aforementioned situations, the frequency of changes in protein evolutionary rates is still not clear at the genome-wide level. Here we examine the constancy of protein evolutionary rates in the evolution of four closely related species of the Saccharomyces sensu stricto group (S. cerevisiae, S. paradoxus, S. mikatae and S. bayanus).ResultsFor 2,610 unambiguously defined orthologous genes among the four species, we carried out likelihood ratio tests between constant-rate and variable-rate models and found 344 (13.2%) genes showing significant changes in the protein evolutionary rates in at least one lineage. Of all those genes which experienced rate changes, 139 and 49 genes showed accelerated and decelerated evolution, respectively. Most of the evolutionary rate changes could be attributed to changes in selective constraints acting on nonsynonymous sites, independently of species-specific gene duplication and loss. We estimated that the changes in protein evolutionary rates have appeared with a probability of 2.0 × 10-3 per gene per million years in the evolution of the Saccharomyces species. Furthermore, we found that the genes which experienced rate acceleration have lower expression levels and weaker codon usage bias than those which experienced rate deceleration.ConclusionChanges in protein evolutionary rates possibly occur frequently in the evolution of closely related Saccharomyces species. Selection for translational accuracy and efficiency may dominantly affect the variability of protein evolutionary rates.

Global transcriptome analysis reveals distinct expression among duplicated genes during sorghum-Bipolaris sorghicola interaction

BackgroundSorghum (Sorghum bicolor L. Moench) is a rich source of natural phytochemicals. We performed massive parallel sequencing of mRNA to identify differentially expressed genes after sorghum BTx623 had been infected with Bipolaris sorghicola, a necrotrophic fungus causing a sorghum disease called target leaf spot.ResultSeventy-six-base-pair reads from mRNAs of mock- or pathogen-infected leaves were sequenced. Unannotated transcripts were predicted on the basis of the piling-up of mapped short reads. Differentially expressed genes were identified statistically; particular genes in tandemly duplicated putative paralogs were highly upregulated. Pathogen infection activated the glyoxylate shunt in the TCA cycle; this changes the role of the TCA cycle from energy production to synthesis of cell components. The secondary metabolic pathways of phytoalexin synthesis and of sulfur-dependent detoxification were activated by upregulation of the genes encoding amino acid metabolizing enzymes located at the branch point between primary and secondary metabolism. Coordinated gene expression could guide the metabolic pathway for accumulation of the sorghum-specific phytochemicals 3-deoxyanthocyanidin and dhurrin. Key enzymes for synthesizing these sorghum-specific phytochemicals were not found in the corresponding region of the rice genome.ConclusionPathogen infection dramatically changed the expression of particular paralogs that putatively encode enzymes involved in the sorghum-specific metabolic network.

TENOR: Database for Comprehensive mRNA-Seq Experiments in Rice

Here we present TENOR (Transcriptome ENcyclopedia Of Rice, http://tenor.dna.affrc.go.jp), a database that encompasses large-scale mRNA sequencing (mRNA-Seq) data obtained from rice under a wide variety of conditions. Since the elucidation of the ability of plants to adapt to various growing conditions is a key issue in plant sciences, it is of great interest to understand the regulatory networks of genes responsible for environmental changes. We used mRNA-Seq and performed a time-course transcriptome analysis of rice, Oryza sativa L. (cv. Nipponbare), under 10 abiotic stress conditions (high salinity; high and low phosphate; high, low and extremely low cadmium; drought; osmotic; cold; and flood) and two plant hormone treatment conditions (ABA and jasmonic acid). A large number of genes that were responsive to abiotic stresses and plant hormones were detected by differential expression analysis. Furthermore, several responsive genes were found to encode transcription factors that could control the transcriptional network of stress responses, but the timing of the induction of these genes was not uniform across conditions. A significant number of cis-regulatory elements were enriched in the promoter regions of the responsive genes and were shared among conditions. These data suggest that some key components of gene regulation networks are shared between different stress signaling pathways. All the resources (novel genes identified from mRNA-Seq data, expression profiles, co-expressed genes and cis-regulatory elements) can be searched for and are available in TENOR.