Chikatoshi Kai

Genome-wide analysis of mammalian promoter architecture and evolution

Mammalian promoters can be separated into two classes, conserved TATA box–enriched promoters, which initiate at a well-defined site, and more plastic, broad and evolvable CpG-rich promoters. We have sequenced tags corresponding to several hundred thousand transcription start sites (TSSs) in the mouse and human genomes, allowing precise analysis of the sequence architecture and evolution of distinct promoter classes. Different tissues and families of genes differentially use distinct types of promoters. Our tagging methods allow quantitative analysis of promoter usage in different tissues and show that differentially regulated alternative TSSs are a common feature in protein-coding genes and commonly generate alternative N termini. Among the TSSs, we identified new start sites associated with the majority of exons and with 3′ UTRs. These data permit genome-scale identification of tissue-specific promoters and analysis of the cis-acting elements associated with them.

CAGE: cap analysis of gene expression.

1Laboratory for Genome Exploration Research Group, RIKEN Genomic Sciences Center (GSC), Yokohama Institute 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan. 2 Genome Science Laboratory, RIKEN, Wako main campus, 2-1 Hirosawa Wako, Saitama, 351-0198, Japan. 3 K.K. Dnaform, Tsukuba Branch, 3-1 Chuo 8-chome, Ami Machi, Inashiki Gun, Ibaraki, 300-0332, Japan. 4Present address: Vaxine Pty Ltd., Department of Diabetes and Endocrinology, Flinders Medical Centre, Bedford Park, Southern Australia 5042, Australia. Correspondence should be addressed to Y.H. (rgscerg@gsc.riken.jp), P.C. (rgscerg@gsc.riken.jp) or M.H. (matthias. harbers@dnaforminc.com).

Hidden layers of human small RNAs

BackgroundSmall RNA attracts increasing interest based on the discovery of RNA silencing and the rapid progress of our understanding of these phenomena. Although recent studies suggest the possible existence of yet undiscovered types of small RNAs in higher organisms, many studies to profile small RNA have focused on miRNA and/or siRNA rather than on the exploration of additional classes of RNAs.ResultsHere, we explored human small RNAs by unbiased sequencing of RNAs with sizes of 19–40 nt. We provide substantial evidences for the existence of independent classes of small RNAs. Our data shows that well-characterized non-coding RNA, such as tRNA, snoRNA, and snRNA are cleaved at sites specific to the class of ncRNA. In particular, tRNA cleavage is regulated depending on tRNA type and tissue expression. We also found small RNAs mapped to genomic regions that are transcribed in both directions by bidirectional promoters, indicating that the small RNAs are a product of dsRNA formation and their subsequent cleavage. Their partial similarity with ribosomal RNAs (rRNAs) suggests unrevealed functions of ribosomal DNA or interstitial rRNA. Further examination revealed six novel miRNAs.ConclusionOur results underscore the complexity of the small RNA world and the biogenesis of small RNAs.

Transcript annotation in FANTOM3: mouse gene catalog based on physical cDNAs.

The international FANTOM consortium aims to produce a comprehensive picture of the mammalian transcriptome, based upon an extensive cDNA collection and functional annotation of full-length enriched cDNAs. The previous dataset, FANTOM2, comprised 60,770 full-length enriched cDNAs. Functional annotation revealed that this cDNA dataset contained only about half of the estimated number of mouse protein-coding genes, indicating that a number of cDNAs still remained to be collected and identified. To pursue the complete gene catalog that covers all predicted mouse genes, cloning and sequencing of full-length enriched cDNAs has been continued since FANTOM2. In FANTOM3, 42,031 newly isolated cDNAs were subjected to functional annotation, and the annotation of 4,347 FANTOM2 cDNAs was updated. To accomplish accurate functional annotation, we improved our automated annotation pipeline by introducing new coding sequence prediction programs and developed a Web-based annotation interface for simplifying the annotation procedures to reduce manual annotation errors. Automated coding sequence and function prediction was followed with manual curation and review by expert curators. A total of 102,801 full-length enriched mouse cDNAs were annotated. Out of 102,801 transcripts, 56,722 were functionally annotated as protein coding (including partial or truncated transcripts), providing to our knowledge the greatest current coverage of the mouse proteome by full-length cDNAs. The total number of distinct non-protein-coding transcripts increased to 34,030. The FANTOM3 annotation system, consisting of automated computational prediction, manual curation, and final expert curation, facilitated the comprehensive characterization of the mouse transcriptome, and could be applied to the transcriptomes of other species.

The Abundance of Short Proteins in the Mammalian Proteome

Short proteins play key roles in cell signalling and other processes, but their abundance in the mammalian proteome is unknown. Current catalogues of mammalian proteins exhibit an artefactual discontinuity at a length of 100 aa, so that protein abundance peaks just above this length and falls off sharply below it. To clarify the abundance of short proteins, we identify proteins in the FANTOM collection of mouse cDNAs by analysing synonymous and non-synonymous substitutions with the computer program CRITICA. This analysis confirms that there is no real discontinuity at length 100. Roughly 10% of mouse proteins are shorter than 100 aa, although the majority of these are variants of proteins longer than 100 aa. We identify many novel short proteins, including a “dark matter” subset containing ones that lack detectable homology to other known proteins. Translation assays confirm that some of these novel proteins can be translated and localised to the secretory pathway.

Clusters of internally primed transcripts reveal novel long noncoding RNAs.

Non-protein-coding RNAs (ncRNAs) are increasingly being recognized as having important regulatory roles. Although much recent attention has focused on tiny 22- to 25-nucleotide microRNAs, several functional ncRNAs are orders of magnitude larger in size. Examples of such macro ncRNAs include Xist and Air, which in mouse are 18 and 108 kilobases (Kb), respectively. We surveyed the 102,801 FANTOM3 mouse cDNA clones and found that Air and Xist were present not as single, full-length transcripts but as a cluster of multiple, shorter cDNAs, which were unspliced, had little coding potential, and were most likely primed from internal adenine-rich regions within longer parental transcripts. We therefore conducted a genome-wide search for regional clusters of such cDNAs to find novel macro ncRNA candidates. Sixty-six regions were identified, each of which mapped outside known protein-coding loci and which had a mean length of 92 Kb. We detected several known long ncRNAs within these regions, supporting the basic rationale of our approach. In silico analysis showed that many regions had evidence of imprinting and/or antisense transcription. These regions were significantly associated with microRNAs and transcripts from the central nervous system. We selected eight novel regions for experimental validation by northern blot and RT-PCR and found that the majority represent previously unrecognized noncoding transcripts that are at least 10 Kb in size and predominantly localized in the nucleus. Taken together, the data not only identify multiple new ncRNAs but also suggest the existence of many more macro ncRNAs like Xist and Air.

LOCATE: a mouse protein subcellular localization database

We present here LOCATE, a curated, web-accessible database that houses data describing the membrane organization and subcellular localization of proteins from the FANTOM3 Isoform Protein Sequence set. Membrane organization is predicted by the high-throughput, computational pipeline MemO. The subcellular locations of selected proteins from this set were determined by a high-throughput, immunofluorescence-based assay and by manually reviewing >1700 peer-reviewed publications. LOCATE represents the first effort to catalogue the experimentally verified subcellular location and membrane organization of mammalian proteins using a high-throughput approach and provides localization data for ∼40% of the mouse proteome. It is available at .

CAGE Basic/Analysis Databases: the CAGE resource for comprehensive promoter analysis

Cap-analysis gene expression (CAGE) Basic and Analysis Databases store an original resource produced by CAGE, which measures expression levels of transcription starting sites by sequencing large amounts of transcript 5′ ends, termed CAGE tags. Millions of human and mouse high-quality CAGE tags derived from different conditions in >20 tissues consisting of >250 RNA samples are essential for identification of novel promoters and promoter characterization in the aspect of expression profile. CAGE Basic Database is a primary database of the CAGE resource, RNA samples, CAGE libraries, CAGE clone and tag sequences and so on. CAGE Analysis Database stores promoter related information, such as counts of related transcripts, CpG islands and conserved genome region. It also provides expression profiles at base pair and promoter levels. Both databases are based on the same framework, CAGE tag starting sites, tag clusters for defining promoters and transcriptional units (TUs). Their associations and TU attributes are available to find promoters of interest. These databases were provided for Functional Annotation Of Mouse 3 (FANTOM3), an international collaboration research project focusing on expanding the transcriptome and subsequent analyses. Now access is free for all users through the World Wide Web at .

The PDZ Protein Tax-interacting Protein-1 Inhibits β-Catenin Transcriptional Activity and Growth of Colorectal Cancer Cells

Wnt signaling is essential during development while deregulation of this pathway frequently leads to the formation of various tumors including colorectal carcinomas. A key component of the pathway is β-catenin that, in association with TCF-4, directly regulates the expression of Wnt-responsive genes. To identify novel binding partners of β-catenin that may control its transcriptional activity, we performed a mammalian two-hybrid screen and isolated the Tax-interacting protein (TIP-1). The in vivo complex formation between β-catenin and TIP-1 was verified by coimmunoprecipitation, and a direct physical association was revealed by glutathione S-transferase pull-down experiments in vitro. By using a panel of deletion mutants of both proteins, we demonstrate that the interaction is mediated by the PDZ (PSD-95/DLG/ZO-1 homology) domain of TIP-1 and requires primarily the last four amino acids of β-catenin. TIP-1 overexpression resulted in a dose-dependent decrease in the transcriptional activity of β-catenin when tested on the TOP/FOPFLASH reporter system. Conversely, siRNA-mediated knock-down of endogenous TIP-1 slightly increased endogenous β-catenin transactivation function. Moreover, we show that overexpression of TIP-1 reduced the proliferation and anchorage-independent growth of colorectal cancer cells. These data suggest that TIP-1 may represent a novel regulatory element in the Wnt/β-catenin signaling pathway.

Discrimination of Non-Protein-Coding Transcripts from Protein-Coding mRNA.

Several recent studies indicate that mammals and other organisms produce large numbers of RNA transcripts that do not correspond to known genes. It has been suggested that these transcripts do not encode proteins, but may instead function as RNAs. However, discrimination of coding and noncoding transcripts is not straightforward, and different laboratories have used different methods, whose ability to perform this discrimination is unclear. In this study, we examine ten bioinformatic methods that assess protein-coding potential and compare their ability and congruency in the discrimination of noncoding from coding sequences, based on four underlying principles: open reading frame size, sequence similarity to known proteins or protein domains, statistical models of protein-coding sequence, and synonymous versus nonsynonymous substitution rates. Despite these different approaches, the methods show broad concordance, suggesting that coding and noncoding transcripts can, in general, be reliably discriminated, and that many of the recently discovered extra-genic transcripts are indeed noncoding. Comparison of the methods indicates reasons for unreliable predictions, and approaches to increase confidence further. Conversely and surprisingly, our analyses also provide evidence that as much as ~10% of entries in the manually curated protein database Swiss-Prot are erroneous translations of actually noncoding transcripts.