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DBTSS (http://dbtss.hgc.jp/) was originally constructed as a collection of uniquely determined transcriptional start sites (TSSs) in humans and some other species in 2002. Since then, it has been regularly updated and in recent updates epigenetic information has also been incorporated because such information is useful for characterizing the biological relevance of these TSSs/downstream genes. In the newest release, Release 9, we further integrated public and original single nucleotide variation (SNV) data into our database. For our original data, we generated SNV data from genomic analyses of various cancer types, including 97 lung adenocarcinomas and 57 lung small cell carcinomas from Japanese patients as well as 26 cell lines of lung cancer origin. In addition, we obtained publically available SNV data from other cancer types and germline variations in total of 11,322 individuals. With these updates, users can examine the association between sequence variation pattern in clinical lung cancers with its corresponding TSS-seq, RNA-seq, ChIP-seq and BS-seq data. Consequently, DBTSS is no longer a mere storage site for TSS information but has evolved into an integrative platform of a variety of genome activity data., (© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.)

To identify and characterize transcript structures ranging from transcriptional start sites (TSSs) to poly(A)-addition sites (PASs), we constructed and analyzed human TSS/PAS mate pair full-length cDNA libraries from 14 tissue types and four cell lines. The collected information enabled us to define TSS cluster (TSC) and PAS cluster (PAC) relationships for a total of 8530/9400 RefSeq genes, as well as 4251/5618 of their putative alternative promoters/terminators and 4619/4605 intervening transcripts, respectively. Analyses of the putative alternative TSCs and alternative PACs revealed that their selection appeared to be mostly independent, with rare exceptions. In those exceptional cases, pairs of transcript units rarely overlapped one another and were occasionally separated by Rad21/CTCF. We also identified a total of 172 similar cases in which TSCs and PACs spanned adjacent but distinct genes. In these cases, different transcripts may utilize different functional units of a particular gene or of adjacent genes. This approach was also useful for identifying fusion gene transcripts in cancerous cells. Furthermore, we could construct cDNA libraries in which 3'-end mate pairs were distributed randomly over the transcripts. These libraries were useful for assembling the internal structure of previously uncharacterized alternative promoter products, as well as intervening transcripts., (© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.)

For the last couple of years, a method that permits the collection of precise positional information of transcriptional start sites (TSSs) together with digital information of the gene-expression levels in a high-throughput manner was established. We applied this novel method, 'tss-seq', to elucidate the transcriptome of tachyzoites of the Toxoplasma gondii, which resulted in the identification of 124,000 TSSs, and they were clustered into 10,000 transcription regions (TRs) with a statistics-based analysis. The TRs and annotated ORFs were paired, resulting in the identification of 30% of the TRs and 40% of the ORFs without their counterparts, which predicted undiscovered genes and stage-specific transcriptions, respectively. The massive data for TSSs make it possible to execute the first systematic analysis of the T. gondii core promoter structure, and the information showed that T. gondii utilized an initiator-like motif for their transcription in the major and novel motif, the downstream thymidine cluster, which was similar to the Y patch observed in plants. This encyclopaedic analysis also suggested that the TATA box, and the other well-known core promoter elements were hardly utilized.

DataBase of Transcription Start Sites (DBTSS) is a database which contains precise positional information for transcription start sites (TSSs) of eukaryotic mRNAs. In this update, we included 330 million new tags generated by massively sequencing the 5'-end of oligo-cap selected cDNAs in humans and mice. The tags were collected from normal fetal or adult human tissues, including brain, thymus, liver, kidney and heart, from 6 human cell lines in 21 diverse growth conditions as well as from mouse NIH3T3 cell line: altogether 31 different cell types or culture conditions are represented. This unprecedented increase in depth of data now allows DBTSS to faithfully represent the dynamically changing landscape of TSSs in different cell types and conditions, during development and in the course of evolution. Differential usage of alternative 5'-ends across cell types and conditions can be viewed in a series of new interfaces. Promoter sequence information is now displayed in a comparative genomics viewer where evolutionary turnover of the TSSs can be evaluated. DBTSS can be accessed at http://dbtss.hgc.jp/.

Combining our full-length cDNA method and the massively parallel sequencing technology, we developed a simple method to collect precise positional information of transcriptional start sites (TSSs) together with digital information of the gene-expression levels in a high throughput manner. We applied this method to observe gene-expression changes in a colon cancer cell line cultured in normoxic and hypoxic conditions. We generated more than 100 million 36-base TSS-tag sequences and revealed comprehensive features of hypoxia responsive alterations in the transcriptional landscape of the human genome. The features include presence of inducible 'hot regions' in 54 genomic regions, 220 novel hypoxia inducible promoters that may drive non-protein-coding transcripts, 191 hypoxia responsive alternative promoters and detailed views of 120 novel as well as known hypoxia responsive genes. We further analyzed hypoxic response of different cells using additional 60 million TSS-tags and found that the degree of the gene-expression changes were different among cell lines, possibly reflecting cellular robustness against hypoxia. The novel dynamic figure of the human gene transcriptome will deepen our understanding of the transcriptional program of the human genome as well as bringing new insights into the biology of cancer cells in hypoxia.

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 was first constructed in 2002 based on precise, experimentally determined 5' end clones. Several major updates and additions have been made since the last report. First, the number of human clones has drastically increased, going from 190,964 to 1,359,000. Second, information about potential alternative promoters is presented because the number of 5' end clones is now sufficient to determine several promoters for one gene. Namely, we defined putative promoter groups by clustering transcription start sites (TSSs) separated by <500 bases. A total of 8308 human genes and 4276 mouse genes were found to have putative multiple promoters. Third, DBTSS provides detailed sequence comparisons of user-specified TSSs. Finally, we have added TSS information for zebrafish, malaria and schyzon (a red algae model organism). DBTSS is accessible at http://dbtss.hgc.jp.