PD-1 Imposes Qualitative Control of Cellular Transcriptomes in Response to T Cell Activation.

Targeted blockade of programmed cell death 1 (PD-1), an immune-checkpoint receptor that inhibits T cell activation, provides clinical benefits in various cancers. However, how PD-1 modulates gene expression in T cells remains enigmatic. Here we investigated how PD-1 affects transcriptome changes induced by T cell receptor (TCR) activation. Intriguingly, we identified a huge variance in PD-1 sensitivity among TCR-inducible genes. When we quantified the half maximal effective concentration (EC50) as the relationship between change in gene expression and TCR signal strength, we found that genes associated with survival and proliferation were efficiently expressed upon TCR activation and resistant to PD-1-mediated inhibition. Conversely, genes encoding cytokines and effector molecules were expressed less efficiently and sensitive to PD-1-mediated inhibition. We further demonstrated that transcription factor binding motifs and CpG frequency in the promoter region affect EC50 and thus the PD-1 sensitivity of genes. Our findings explain how PD-1, dependent on the TCR signal strength, calibrates cellular transcriptomes to shape functional properties of T cell populations.

Functional screening of salt tolerance genes from a halophyte Sporobolus virginicus and transcriptomic and metabolomic analysis of salt tolerant plants expressing glycine-rich RNA-binding protein.

Sporobolus virginicus is a halophytic C4 grass found worldwide, from tropical to warm temperate regions. One Japanese genotype showed a salinity tolerance up to 1.5 M NaCl, a three-fold higher concentration than the salinity of sea water. To identify the key genes involved in the regulation of salt tolerance in S. virginicus, we produced 3500 independent transgenic Arabidopsis lines expressing random cDNA from S. virginicus and screened 10 lines which showed enhanced salt tolerance compared with the wild type in a medium containing 150 mM NaCl. Among the selected lines, two contained cDNA coding glycine-rich RNA-binding proteins (SvGRP1 and SvGRP2). This is the first reports on the function of GRPs from halophytes in salt tolerance though reports have shown GRPs are involved in diverse biological and biochemical processes including salt tolerance in Arabidopsis and some other glycophytes. Transcriptomic analysis and GO enrichment analysis of SvGRP1-expressing Arabidopsis under salt stress revealed upregulation of polyol and downregulation of glucosinolate and indole acetic acid biosynthesis/metabolic pathways. Metabolomic analysis of the SvGRP1-transformant suggested that the increase in 3-aminoppropanoic acid, citramalic acid, and isocitric acid content was associated with enhanced salt tolerance. These findings could provide novel insight into the roles of GRPs in plant salt tolerance.

TOMATOMICS: A Web Database for Integrated Omics Information in Tomato.

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.

Identification of reference genes for quantitative expression analysis using large-scale RNA-seq data of Arabidopsis thaliana and model crop plants.

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.

Plant Omics Data Center: an integrated web repository for interspecies gene expression networks with NLP-based curation.

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.

Coexpression analysis of tomato genes and experimental verification of coordinated expression of genes found in a functionally enriched coexpression module.

Gene-to-gene coexpression analysis is a powerful approach to infer the function of uncharacterized genes. Here, we report comprehensive identification of coexpression gene modules of tomato (Solanum lycopersicum) and experimental verification of coordinated expression of module member genes. On the basis of the gene-to-gene correlation coefficient calculated from 67 microarray hybridization data points, we performed a network-based analysis. This facilitated the identification of 199 coexpression modules. A gene ontology annotation search revealed that 75 out of the 199 modules are enriched with genes associated with common functional categories. To verify the coexpression relationships between module member genes, we focused on one module enriched with genes associated with the flavonoid biosynthetic pathway. A non-enzyme, non-transcription factor gene encoding a zinc finger protein in this module was overexpressed in S. lycopersicum cultivar Micro-Tom, and expression levels of flavonoid pathway genes were investigated. Flavonoid pathway genes included in the module were up-regulated in the plant overexpressing the zinc finger gene. This result demonstrates that coexpression modules, at least the ones identified in this study, represent actual transcriptional coordination between genes, and can facilitate the inference of tomato gene function.