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Biomedical subjects

Philipp Bucher

Publications and source records attributed to Philipp Bucher.

17 recordsLinked to original sources

An expanded codebook of human transcription factor DNA-binding specificity.

Gene expression is regulated by transcription factors (TFs), which recognize specific DNA sequence motifs. Several hundred putative human TFs, identified mainly by an apparent DNA-binding domain, lack known binding motifs1. Furthermore, even for well-characterized TFs, it remains controversial the degree to which motifs accurately reflect binding sites in living cells2. Here we describe a systematic effort ('Codebook') to determine the sequence specificity of 332 putative and poorly characterized human TFs. More than 4,000 independent experiments, encompassing multiple in vitro and in vivo assays, produced motifs for just over half (177; 53%) of the TFs, of which most are associated with only a single protein. These results extend the vocabulary of sequence recognition encoded by human TFs by around 130 distinct motifs. Moreover, binding motifs identified in vitro are strongly enriched in cellular binding sites. Collectively, the data reveal tens of thousands of previously unknown, conserved and direct TF-binding sites across the human genome. These sites are concentrated in promoter regions and are predictive of gene expression. In summary, this new codebook provides an important step forward in decoding the human genome.

Humans↗

Recent improvements to the PROSITE database.

The PROSITE database consists of a large collection of biologically meaningful signatures that are described as patterns or profiles. Each signature is linked to documentation that provides useful biological information on the protein family, domain or functional site identified by the signature. The PROSITE web page has been redesigned and several tools have been implemented to help the user discover new conserved regions in their own proteins and to visualize domain arrangements. We also introduced the facility to search PDB with a PROSITE entry or a user's pattern and visualize matched positions on 3D structures. The latest version of PROSITE (release 18.17 of November 30, 2003) contains 1676 entries. The database is accessible at http://www.expasy.org/prosite/.

Amino Acid Motifs↗

trome, trEST and trGEN: databases of predicted protein sequences.

We previously introduced two new protein databases (trEST and trGEN) of hypothetical protein sequences predicted from EST and HTG sequences, respectively. Here, we present the updates made on these two databases plus a new database (trome), which uses alignments of EST data to HTG or full genomes to generate virtual transcripts and coding sequences. This new database is of higher quality and since it contains the information in a much denser format it is of much smaller size. These new databases are in a Swiss-Prot-like format and are updated on a weekly basis (trEST and trGEN) or every 3 months (trome). They can be downloaded by anonymous ftp from ftp://ftp.isrec.isb-sib.ch/pub/databases.

Animals↗

CleanEx: a database of heterogeneous gene expression data based on a consistent gene nomenclature.

The main goal of CleanEx is to provide access to public gene expression data via unique gene names. A second objective is to represent heterogeneous expression data produced by different technologies in a way that facilitates joint analysis and cross-data set comparisons. A consistent and up-to-date gene nomenclature is achieved by associating each single experiment with a permanent target identifier consisting of a physical description of the targeted RNA population or the hybridization reagent used. These targets are then mapped at regular intervals to the growing and evolving catalogues of human genes and genes from model organisms. The completely automatic mapping procedure relies partly on external genome information resources such as UniGene and RefSeq. The central part of CleanEx is a weekly built gene index containing cross-references to all public expression data already incorporated into the system. In addition, the expression target database of CleanEx provides gene mapping and quality control information for various types of experimental resource, such as cDNA clones or Affymetrix probe sets. The web-based query interfaces offer access to individual entries via text string searches or quantitative expression criteria. CleanEx is accessible at: http://www.cleanex.isb-sib.ch/.

Animals↗

The Eukaryotic Promoter Database EPD: the impact of in silico primer extension.

The Eukaryotic Promoter Database (EPD) is an annotated non-redundant collection of eukaryotic POL II promoters, experimentally defined by a transcription start site (TSS). There may be multiple promoter entries for a single gene. The underlying experimental evidence comes from journal articles and, starting from release 73, from 5' ESTs of full-length cDNA clones used for so-called in silico primer extension. Access to promoter sequences is provided by pointers to TSS positions in nucleotide sequence entries. The annotation part of an EPD entry includes a description of the type and source of the initiation site mapping data, links to other biological databases and bibliographic references. EPD is structured in a way that facilitates dynamic extraction of biologically meaningful promoter subsets for comparative sequence analysis. Web-based interfaces have been developed that enable the user to view EPD entries in different formats, to select and extract promoter sequences according to a variety of criteria and to navigate to related databases exploiting different cross-references. Tools for analysing sequence motifs around TSSs defined in EPD are provided by the signal search analysis server. EPD can be accessed at http://www.epd. isb-sib.ch.

Animals↗

Classification of human astrocytic gliomas on the basis of gene expression: a correlated group of genes with angiogenic activity emerges as a strong predictor of subtypes.

The development of targeted treatment strategies adapted to individual patients requires identification of the different tumor classes according to their biology and prognosis. We focus here on the molecular aspects underlying these differences, in terms of sets of genes that control pathogenesis of the different subtypes of astrocytic glioma. By performing cDNA-array analysis of 53 patient biopsies, comprising low-grade astrocytoma, secondary glioblastoma (respective recurrent high-grade tumors), and newly diagnosed primary glioblastoma, we demonstrate that human gliomas can be differentiated according to their gene expression. We found that low-grade astrocytoma have the most specific and similar expression profiles, whereas primary glioblastoma exhibit much larger variation between tumors. Secondary glioblastoma display features of both other groups. We identified several sets of genes with relatively highly correlated expression within groups that: (a). can be associated with specific biological functions; and (b). effectively differentiate tumor class. One prominent gene cluster discriminating primary versus nonprimary glioblastoma comprises mostly genes involved in angiogenesis, including VEGF fms-related tyrosine kinase 1 but also IGFBP2, that has not yet been directly linked to angiogenesis. In situ hybridization demonstrating coexpression of IGFBP2 and VEGF in pseudopalisading cells surrounding tumor necrosis provided further evidence for a possible involvement of IGFBP2 in angiogenesis. The separating groups of genes were found by the unsupervised coupled two-way clustering method, and their classification power was validated by a supervised construction of a nearly perfect glioma classifier.

Adolescent↗

Signal search analysis server.

Signal search analysis is a general method to discover and characterize sequence motifs that are positionally correlated with a functional site (e.g. a transcription or translation start site). The method has played an instrumental role in the analysis of eukaryotic promoter elements. The signal search analysis server provides access to four different computer programs as well as to a large number of precompiled functional site collections. The programs offered allow: (i) the identification of non-random sequence regions under evolutionary constraint; (ii) the detection of consensus sequence-based motifs that are over- or under-represented at a particular distance from a functional site; (iii) the analysis of the positional distribution of a consensus sequence- or weight matrix-based sequence motif around a functional site; and (iv) the optimization of a weight matrix description of a locally over-represented sequence motif. These programs can be accessed at: http://www.isrec.isb-sib.ch/ssa/.

Consensus Sequence↗

Telomere maintenance in fission yeast requires an Est1 ortholog.

Telomerase regulation is critical to genome maintenance yet remains poorly understood. Without telomerase's ability to synthesize telomere repeats, chromosome ends shorten progressively, as conventional DNA polymerases cannot fully replicate the ends of linear molecules. In Saccharomyces cerevisiae, telomerase activity in vivo absolutely depends on a set of telomerase accessory proteins that includes Est1p, which appears to recruit or activate telomerase at the site of polymerization. Thus, est1Delta cells have the same cellular senescence phenotype as cells lacking either the catalytic protein subunit of telomerase or its template-containing RNA subunit. While the telomerase protein is highly conserved among eukaryotes, the apparent lack of Est1p homologs has frustrated efforts to describe a common mechanism of telomerase recruitment and activation. Here, we describe SpEst1p, a homolog of Est1p from the evolutionarily distant Schizosaccharomyces pombe. Like ScEst1p, SpEst1p is required for telomerase activity in vivo. Coupled with the identification of an orthologous Est1 protein in humans [10], this suggests a much wider conservation of telomerase regulation than was previously known. Strikingly, in cells with compromised telomere function (taz1Delta), SpEst1p loss confers a lethal germination phenotype, while telomerase loss does not, indicating that SpEst1p plays an unexpected additional role in chromosome end protection.

Animals↗

A human homolog of yeast Est1 associates with telomerase and uncaps chromosome ends when overexpressed.

Telomeres protect the eukaryotic chromosome ends from degradation and fusion. They are maintained by the ribonucleoprotein telomerase, the core of which is composed of a reverse transcriptase (TERT) and a RNA subunit. In the yeast Saccharomyces cerevisiae, a third critical telomerase subunit, the Ever Shorter Telomeres 1 (EST1) gene product, recruits or activates telomerase at the 3' end of telomeres. Est1p has so far only been known in budding yeast, and mechanisms that mediate telomerase access and activation in other eukaryotes have remained elusive. Here, we use iterative profile searches to identify homologs of yeast Est1p in a large variety of eukaryotes, including human. One of three human homologs, designated human EST1A (hEST1A), is shown to be associated with most or all active telomerase in HeLa cell extracts. Overexpression of hEST1A induces anaphase bridges due to chromosome-end fusions, and telomeric DNA persists at the fusion points. Thus, overexpression of hEST1A affects telomere capping. The identification of EST1 homologs in a large variety of eukaryotes may indicate that the mechanisms of telomere extension are more conserved than anticipated previously.

Amino Acid Sequence↗

APDB: a novel measure for benchmarking sequence alignment methods without reference alignments.

MOTIVATION: We describe APDB, a novel measure for evaluating the quality of a protein sequence alignment, given two or more PDB structures. This evaluation does not require a reference alignment or a structure superposition. APDB is designed to efficiently and objectively benchmark multiple sequence alignment methods. RESULTS: Using existing collections of reference multiple sequence alignments and existing alignment methods, we show that APDB gives results that are consistent with those obtained using conventional evaluations. We also show that APDB is suitable for evaluating sequence alignments that are structurally equivalent. We conclude that APDB provides an alternative to more conventional methods used for benchmarking sequence alignment packages.

Algorithms↗

Numerous potentially functional but non-genic conserved sequences on human chromosome 21.

The use of comparative genomics to infer genome function relies on the understanding of how different components of the genome change over evolutionary time. The aim of such comparative analysis is to identify conserved, functionally transcribed sequences such as protein-coding genes and non-coding RNA genes, and other functional sequences such as regulatory regions, as well as other genomic features. Here, we have compared the entire human chromosome 21 with syntenic regions of the mouse genome, and have identified a large number of conserved blocks of unknown function. Although previous studies have made similar observations, it is unknown whether these conserved sequences are genes or not. Here we present an extensive experimental and computational analysis of human chromosome 21 in an effort to assign function to sequences conserved between human chromosome 21 (ref. 8) and the syntenic mouse regions. Our data support the presence of a large number of potentially functional non-genic sequences, probably regulatory and structural. The integration of the properties of the conserved components of human chromosome 21 to the rapidly accumulating functional data for this chromosome will improve considerably our understanding of the role of sequence conservation in mammalian genomes.

Animals↗

High-throughput SELEX SAGE method for quantitative modeling of transcription-factor binding sites.

The ability to determine the location and relative strength of all transcription-factor binding sites in a genome is important both for a comprehensive understanding of gene regulation and for effective promoter engineering in biotechnological applications. Here we present a bioinformatically driven experimental method to accurately define the DNA-binding sequence specificity of transcription factors. A generalized profile was used as a predictive quantitative model for binding sites, and its parameters were estimated from in vitro-selected ligands using standard hidden Markov model training algorithms. Computer simulations showed that several thousand low- to medium-affinity sequences are required to generate a profile of desired accuracy. To produce data on this scale, we applied high-throughput genomics methods to the biochemical problem addressed here. A method combining systematic evolution of ligands by exponential enrichment (SELEX) and serial analysis of gene expression (SAGE) protocols was coupled to an automated quality-controlled sequence extraction procedure based on Phred quality scores. This allowed the sequencing of a database of more than 10,000 potential DNA ligands for the CTF/NFI transcription factor. The resulting binding-site model defines the sequence specificity of this protein with a high degree of accuracy not achieved earlier and thereby makes it possible to identify previously unknown regulatory sequences in genomic DNA. A covariance analysis of the selected sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism.

Base Sequence↗

The PROSITE database, its status in 2002.

PROSITE [Bairoch and Bucher (1994) Nucleic Acids Res., 22, 3583-3589; Hofmann et al. (1999) Nucleic Acids Res., 27, 215-219] is a method of identifying the functions of uncharacterized proteins translated from genomic or cDNA sequences. The PROSITE database (http://www.expasy.org/prosite/) consists of biologically significant patterns and profiles designed in such a way that with appropriate computational tools it can rapidly and reliably help to determine to which known family of proteins (if any) a new sequence belongs, or which known domain(s) it contains.

Amino Acid Motifs↗

The Eukaryotic Promoter Database, EPD: new entry types and links to gene expression data.

The Eukaryotic Promoter Database (EPD) is an annotated, non-redundant collection of eukaryotic Pol II promoters, for which the transcription start site has been determined experimentally. Access to promoter sequences is provided by pointers to positions in nucleotide sequence entries. The annotation part of an entry includes a description of the initiation site mapping data, exhaustive cross-references to the EMBL nucleotide sequence database, SWISS-PROT, TRANSFAC and other databases, as well as bibliographic references. EPD is structured in a way that facilitates dynamic extraction of biologically meaningful promoter subsets for comparative sequence analysis. World Wide Web-based interfaces have been developed which enable the user to view EPD entries in different formats, to select and extract promoter sequences according to a variety of criteria, and to navigate to related databases exploiting different cross-references. The EPD web site also features yearly updated base frequency matrices for major eukaryotic promoter elements. EPD can be accessed at http://www.epd.isb-sib.ch.

Animals↗

Nineteen additional unpredicted transcripts from human chromosome 21.

The identification of all human chromosome 21 (HC21) genes is a necessary step in understanding the molecular pathogenesis of trisomy 21 (Down syndrome). The first analysis of the sequence of 21q included 127 previously characterized genes and predicted an additional 98 novel anonymous genes. Recently we evaluated the quality of this annotation by characterizing a set of HC21 open reading frames (C21orfs) identified by mapping spliced expressed sequence tags (ESTs) and predicted genes (PREDs), identified only in silico. This study underscored the limitations of in silico-only gene prediction, as many PREDs were incorrectly predicted. To refine the HC21 annotation, we have developed a reliable algorithm to extract and stringently map sequences that contain bona fide 3' transcript ends to the genome. We then created a specific 21q graphical display allowing an integrated view of the data that incorporates new ESTs as well as features such as CpG islands, repeats, and gene predictions. Using these tools we identified 27 new putative genes. To validate these, we sequenced previously cloned cDNAs and carried out RT-PCR, 5'- and 3'-RACE procedures, and comparative mapping. These approaches substantiated 19 new transcripts, thus increasing the HC21 gene count by 9.5%. These transcripts were likely not previously identified because they are small and encode small proteins. We also identified four transcriptional units that are spliced but contain no obvious open reading frame. The HC21 data presented here further emphasize that current gene prediction algorithms miss a substantial number of transcripts that nevertheless can be identified using a combination of experimental approaches and multiple refined algorithms.

Chromosomes, Human, Pair 21↗

PROSITE: a documented database using patterns and profiles as motif descriptors.

Among the various databases dedicated to the identification of protein families and domains, PROSITE is the first one created and has continuously evolved since. PROSITE currently consists of a large collection of biologically meaningful motifs that are described as patterns or profiles, and linked to documentation briefly describing the protein family or domain they are designed to detect. The close relationship of PROSITE with the SWISS-PROT protein database allows the evaluation of the sensitivity and specificity of the PROSITE motifs and their periodic reviewing. In return, PROSITE is used to help annotate SWISS-PROT entries. The main characteristics and the techniques of family and domain identification used by PROSITE are reviewed in this paper.

Amino Acid Motifs↗

Long-range heterogeneity at the 3' ends of human mRNAs.

The publication of a draft of the human genome and of large collections of transcribed sequences has made it possible to study the complex relationship between the transcriptome and the genome. In the work presented here, we have focused on mapping mRNA 3' ends onto the genome by use of the raw data generated by the expressed sequence tag (EST) sequencing projects. We find that at least half of the human genes encode multiple transcripts whose polyadenylation is driven by multiple signals. The corresponding transcript 3' ends are spread over distances in the kilobase range. This finding has profound implications for our understanding of gene expression regulation and of the diversity of human transcripts, for the design of cDNA microarray probes, and for the interpretation of gene expression profiling experiments.

3' Flanking Region↗