Kenta Nakai

T Cell Receptor Stimulation-Induced Epigenetic Changes and Foxp3 Expression Are Independent and Complementary Events Required for Treg Cell Development

The transcription factor Foxp3 is essential for the development of regulatory T (Treg) cells, yet its expression is insufficient for establishing the Treg cell lineage. Here we showed that Treg cell development was achieved by the combination of two independent processes, i.e., the expression of Foxp3 and the establishment of Treg cell-specific CpG hypomethylation pattern. Both events were induced by T cell receptor stimulation. The Treg cell-type CpG hypomethylation began in the thymus and continued to proceed in the periphery and could be fully established without Foxp3. The hypomethylation was required for Foxp3(+) T cells to acquire Treg cell-type gene expression, lineage stability, and full suppressive activity. Thus, those T cells in which the two events have concurrently occurred are developmentally set into the Treg cell lineage. This model explains how Treg cell fate and plasticity is controlled and can be exploited to generate functionally stable Treg cells.

ATTED-II: a database of co-expressed genes and cis elements for identifying co-regulated gene groups in Arabidopsis

Publicly available database of co-expressed gene sets would be a valuable tool for a wide variety of experimental designs, including targeting of genes for functional identification or for regulatory investigation. Here, we report the construction of an Arabidopsis thaliana trans-factor and cis-element prediction database (ATTED-II) that provides co-regulated gene relationships based on co-expressed genes deduced from microarray data and the predicted cis elements. ATTED-II () includes the following features: (i) lists and networks of co-expressed genes calculated from 58 publicly available experimental series, which are composed of 1388 GeneChip data in A.thaliana; (ii) prediction of cis-regulatory elements in the 200 bp region upstream of the transcription start site to predict co-regulated genes amongst the co-expressed genes; and (iii) visual representation of expression patterns for individual genes. ATTED-II can thus help researchers to clarify the function and regulation of particular genes and gene networks.

Assessment of prediction accuracy of protein function from protein--protein interaction data.

Functional prediction of open reading frames coded in the genome is one of the most important tasks in yeast genomics. Among a number of large‐scale experiments for assigning certain functional classes to proteins, experiments determining protein–protein interaction are especially important because interacting proteins usually have the same function. Thus, it seems possible to predict the function of a protein when the function of its interacting partner is known. However, in vitro experiments often suffer from artifacts and a protein can often have multiple binding partners with different functions. We developed an objective prediction method that can systematically include the information of indirect interaction. Our method can predict the subcellular localization, the cellular role and the biochemical function of yeast proteins with accuracies of 72.7%, 63.6% and 52.7%, respectively. The prediction accuracy rises for proteins with more than three binding partners and thus we present the open prediction results for 16 such proteins. Copyright

DBTBS: a database of transcriptional regulation in Bacillus subtilis containing upstream intergenic conservation information

DBTBS, first released in 1999, is a reference database on transcriptional regulation in Bacillus subtilis, summarizing the experimentally characterized transcription factors, their recognition sequences and the genes they regulate. Since the previous release, the original content was extended by the addition of the data contained in 569 new publications, the total of which now reaches 947. The number of B. subtilis promoters annotated in the database was more than doubled to 1475. In addition, 463 experimentally validated B. subtilis operons and their terminators have been included. Given the increase in the number of fully sequenced bacterial genomes, we decided to extend the usability of DBTBS in comparative regulatory genomics. We therefore created a new section on the conservation of the upstream regulatory sequences between homologous genes in 40 Gram-positive bacterial species, as well as on the presence of overrepresented hexameric motifs that may have regulatory functions. DBTBS can be accessed at: http://dbtbs.hgc.jp.

DBTSS: DataBase of Human Transcription Start Sites, progress report 2006

DBTSS is a database of transcriptional start sites, based on our unique collection of precise, experimentally determined 5′-end sequences of full-length cDNAs. Since its first release in 2002, several major updates have been made. In this update, we expanded the human transcriptional start site dataset by 19 million uniquely mapped, and RefSeq-associated, 5′-end sequences, which were generated by a newly introduced Solexa sequencer. Moreover, in order to provide means for interpreting those massive TSS data, we implemented two new analytical tools: one for connecting expression information with predicted transcription factor binding sites; the other for examining evolutionary conservation or species-specificity of promoters and transcripts, which can be browsed by our own comparative genome viewer. With the expanded dataset and the enhanced functionalities, DBTSS provides a unique platform that enables in-depth transcriptome analyses. DBTSS is accessible at http://dbtss.hgc.jp/.

DBTSS: DataBase of Transcriptional Start Sites progress report in 2012

To support transcriptional regulation studies, we have constructed DBTSS (DataBase of Transcriptional Start Sites), which contains exact positions of transcriptional start sites (TSSs), determined with our own technique named TSS-seq, in the genomes of various species. In its latest version, DBTSS covers the data of the majority of human adult and embryonic tissues: it now contains 418 million TSS tag sequences from 28 tissues/cell cultures. Moreover, we integrated a series of our own transcriptomic data, such as the RNA-seq data of subcellular-fractionated RNAs as well as the ChIP-seq data of histone modifications and the binding of RNA polymerase II/several transcription factors in cultured cell lines into our original TSS information. We also included several external epigenomic data, such as the chromatin map of the ENCODE project. We further associated our TSS information with public or original single-nucleotide variation (SNV) data, in order to identify SNVs in the regulatory regions. These data can be browsed in our new viewer, which supports versatile search conditions of users. We believe that our new DBTSS will be an invaluable resource for interpreting the differential uses of TSSs and for identifying human genetic variations that are associated with disordered transcriptional regulation. DBTSS can be accessed at http://dbtss.hgc.jp.

DBTBS: database of transcriptional regulation in Bacillus subtilis and its contribution to comparative genomics

DBTBS (http://dbtbs.hgc.jp) was originally released in 1999 as a reference database of published transcriptional regulation events in Bacillus subtilis, one of the best studied bacteria. It is essentially a compilation of transcription factors with their regulated genes as well as their recognition sequences, which were experimentally characterized and reported in the literature. Here we report its major update, which contains information on 114 transcription factors, including sigma factors, and 633 promoters of 525 genes. The number of references cited in the database has increased from 291 to 378. It also supports a function to find putative transcription factor binding sites within input sequences by using our collection of weight matrices and consensus patterns. Furthermore, though preliminarily, DBTBS now aims to contribute to comparative genomics by showing the presence or absence of potentially orthologous transcription factors and their corresponding cis-elements on the promoters of their potentially orthologously regulated genes in 50 eubacterial genomes.

Prediction of Transcriptional Terminators in Bacillus subtilis and Related Species

In prokaryotes, genes belonging to the same operon are transcribed in a single mRNA molecule. Transcription starts as the RNA polymerase binds to the promoter and continues until it reaches a transcriptional terminator. Some terminators rely on the presence of the Rho protein, whereas others function independently of Rho. Such Rho-independent terminators consist of an inverted repeat followed by a stretch of thymine residues, allowing us to predict their presence directly from the DNA sequence. Unlike in Escherichia coli, the Rho protein is dispensable in Bacillus subtilis, suggesting a limited role for Rho-dependent termination in this organism and possibly in other Firmicutes. We analyzed 463 experimentally known terminating sequences in B. subtilis and found a decision rule to distinguish Rho-independent transcriptional terminators from non-terminating sequences. The decision rule allowed us to find the boundaries of operons in B. subtilis with a sensitivity and specificity of about 94%. Using the same decision rule, we found an average sensitivity of 94% for 57 bacteria belonging to the Firmicutes phylum, and a considerably lower sensitivity for other bacteria. Our analysis shows that Rho-independent termination is dominant for Firmicutes in general, and that the properties of the transcriptional terminators are conserved. Terminator prediction can be used to reliably predict the operon structure in these organisms, even in the absence of experimentally known operons. Genome-wide predictions of Rho-independent terminators for the 57 Firmicutes are available in the Supporting Information section.

Modeling and predicting transcriptional units of Escherichia coli genes using hidden Markov models

Motivation: The hidden Markov model (HMM) is a valuable technique for gene-finding, especially because its flexibility enables the inclusion of various sequence features. Recent programs for bacterial gene-finding include the information of ribosomal binding site (RBS) to improve the recognition accuracy of the start codon, using this feature. We report here our attempt to extend the model into the total transcriptional unit, enabling the prediction of operon structures. Results: First, we improved the prediction accuracy of coding sequences (CDSs) by employing the models of ‘typical’, ‘atypical’ and ‘negative (false-positive)’ classes as well as the models of RBS and its downstream spacer. The sensitivity of exactly predicting the 204 experimentally confirmed CDSs reached 90.2% in an objective test. Based on the prediction result of CDSs, the positions of the promoters and terminators were predicted. Our model could exactly recognize 60% of 390 known transcriptional units. Thus, the accuracy and significance of this prediction problem is far from trivial. We would like to propose this problem as an open theme in bioinformatics because the ongoing or planned postsequencing projects will produce much data for future improvements. Availability: The table of predicted transcriptional units of Escherichia coli will be distributed upon request.

DBTBS: a database of Bacillus subtilis promoters and transcription factors

With the completion of the determination of its entire genome sequence, one of the next major targets of Bacillus subtilis genomics is to clarify the whole gene regulatory network. To this end, the results of systematic experiments should be compared with the rich source of individual experimental results accumulated so far. Thus, we constructed a database of the upstream regulatory information of B.subtilis (DBTBS). The current version was constructed by surveying 291 references and contains information on 90 binding factors and 403 promoters. For each promoter, all of its known cis-elements are listed according to their positions, while these cis-elements are aligned to illustrate their consensus sequence for each transcription factor. All probable transcription factors coded in the genome were classified with the Pfam motifs. Using this database, we compared the character of B.subtilis promoters with that of Escherichia coli promoters. Our database is accessible at http://elmo.ims.u-tokyo.ac.jp/dbtbs/.