The turf grass Sporobolus virginicus is halophyte and has high salinity tolerance. To investigate the molecular basis of its remarkable tolerance, we performed Illumina high-throughput RNA sequencing on roots and shoots of a S. virginicus genotype under normal and saline conditions. The 130 million short reads were assembled into 444,242 unigenes. A comparative analysis of the transcriptome with rice and Arabidopsis transcriptome revealed six turf grass-specific unigenes encoding transcription factors. Interestingly, all of them showed root specific expression and five of them encode bZIP type transcription factors. Another remarkable transcriptional feature of S. virginicus was activation of specific pathways under salinity stress. Pathway enrichment analysis suggested transcriptional activation of amino acid, pyruvate, and phospholipid metabolism. Up-regulation of several unigenes, previously shown to respond to salt stress in other halophytes was also observed. Gene Ontology enrichment analysis revealed that unigenes assigned as proteins in response to water stress, such as dehydrin and aquaporin, and transporters such as cation, amino acid, and citrate transporters, and H+-ATPase, were up-regulated in both shoots and roots under salinity. A correspondence analysis of the enriched pathways in turf grass cells, but not in rice cells, revealed two groups of unigenes similarly up-regulated in the turf grass in response to salt stress; one of the groups, showing excessive up-regulation under salinity, included unigenes homologos to salinity responsive genes in other halophytes. Thus, the present study identified candidate genes involved in salt tolerance of S. virginicus. This genetic resource should be valuable for understanding the mechanisms underlying high salt tolerance in S. virginicus. This information can also provide insight into salt tolerance in other halophytes.

The Oryza officinalis complex is the largest species group in Oryza, with more than nine species from four continents, and is a tertiary gene pool that can be exploited in breeding programs for the improvement of cultivated rice. Most diploid and tetraploid members of this group have a C genome. Using a new reference C genome for the diploid species Oryza officinalis, and draft genomes for two other C genome diploid species O. eichingeri and O. rhizomatis, we examine the influence of transposable elements on genome structure and provide a detailed phylogeny and evolutionary history of the Oryza C genomes. The O. officinalis genome is 1.6 times larger than the A genome of cultivated O. sativa, mostly due to proliferation of Gypsy type long-terminal repeat (LTR) transposable elements, but overall syntenic relationships are maintained with other Oryza genomes (A, B and F). Draft genome assemblies of the two other C genome diploid species, O. eichingeri and O. rhizomatis, and short-read resequencing of a series of other C genome species and accessions reveal that after the divergence of the C genome progenitor, there was still a substantial degree of variation within the C genome species through proliferation and loss of both DNA and LTR transposable elements. We provide a detailed phylogeny and evolutionary history of the Oryza C genomes, and a genomic resource for the exploitation of the Oryza tertiary gene pool.

Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources.

Solanum lycopersicum (tomato) is an important agronomic crop and a major model fruit-producing plant. To facilitate basic and applied research, comprehensive experimental resources and omics information on tomato are available following their development. Mutant lines and cDNA clones from a dwarf cultivar, Micro-Tom, are two of these genetic resources. Large-scale sequencing data for ESTs and full-length cDNAs from Micro-Tom continue to be gathered. In conjunction with information on the reference genome sequence of another cultivar, Heinz 1706, the Micro-Tom experimental resources have facilitated comprehensive functional analyses. To enhance the efficiency of acquiring omics information for tomato biology, we have integrated the information on the Micro-Tom experimental resources and the Heinz 1706 genome sequence. We have also inferred gene structure by comparison of sequences between the genome of Heinz 1706 and the transcriptome, which are comprised of Micro-Tom full-length cDNAs and Heinz 1706 RNA-seq data stored in the KaFTom and Sequence Read Archive databases. In order to provide large-scale omics information with streamlined connectivity we have developed and maintain a web database TOMATOMICS (http://bioinf.mind.meiji.ac.jp/tomatomics/). In TOMATOMICS, access to the information on the cDNA clone resources, full-length mRNA sequences, gene structures, expression profiles and functional annotations of genes is available through search functions and the genome browser, which has an intuitive graphical interface.

In quantitative gene expression analysis, normalization using a reference gene as an internal control is frequently performed for appropriate interpretation of the results. Efforts have been devoted to exploring superior novel reference genes using microarray transcriptomic data and to evaluating commonly used reference genes by targeting analysis. However, because the number of specifically detectable genes is totally dependent on probe design in the microarray analysis, exploration using microarray data may miss some of the best choices for the reference genes. Recently emerging RNA sequencing (RNA-seq) provides an ideal resource for comprehensive exploration of reference genes since this method is capable of detecting all expressed genes, in principle including even unknown genes. We report the results of a comprehensive exploration of reference genes using public RNA-seq data from plants such as Arabidopsis thaliana (Arabidopsis), Glycine max (soybean), Solanum lycopersicum (tomato) and Oryza sativa (rice). To select reference genes suitable for the broadest experimental conditions possible, candidates were surveyed by the following four steps: (1) evaluation of the basal expression level of each gene in each experiment; (2) evaluation of the expression stability of each gene in each experiment; (3) evaluation of the expression stability of each gene across the experiments; and (4) selection of top-ranked genes, after ranking according to the number of experiments in which the gene was expressed stably. Employing this procedure, 13, 10, 12 and 21 top candidates for reference genes were proposed in Arabidopsis, soybean, tomato and rice, respectively. Microarray expression data confirmed that the expression of the proposed reference genes under broad experimental conditions was more stable than that of commonly used reference genes. These novel reference genes will be useful for analyzing gene expression profiles across experiments carried out under various experimental conditions.