Philipp Bucher

Weight matrix descriptions of four eukaryotic RNA polymerase II promoter elements derived from 502 unrelated promoter sequences

Optimized weight matrices defining four major eukaryotic promoter elements, the TATA-box, cap signal, CCAAT-, and GC-box, are presented; they were derived by comparative sequence analysis of 502 unrelated RNA polymerase II promoter regions. The new TATA-box and cap signal descriptions differ in several respects from the only hitherto available base frequency Tables. The CCAAT-box matrix, obtained with no prior assumption but CCAAT being the core of the motif, reflects precisely the sequence specificity of the recently discovered nuclear factor NY-I/CP1 but does not include typical recognition sequences of two other purported CCAAT-binding proteins, CTF and CBP. The GC-box description is longer than the previously proposed consensus sequences but is consistent with Sp1 protein-DNA binding data. The notion of a CACCC element distinct from the GC-box seems not to be justified any longer in view of the new weight matrix. Unlike the two fixed-distance elements, neither the CCAAT- nor the GC-box occurs at significantly high frequency in the upstream regions of non-vertebrate genes. Preliminary attempts to predict promoters with the aid of the new signal descriptions were unexpectedly successful. The new TATA-box matrix locates eukaryotic transcription initiation sites as reliably as do the best currently available methods to map Escherichia coli promoters. This analysis was made possible by the recently established Eukaryotic Promoter Database (EPD) of the EMBL Nucleotide Sequence Data Library. In order to derive the weight matrices, a novel algorithm has been devised that is generally applicable to sequence motifs positionally correlated with a biologically defined position in the sequences. The signal must be sufficiently over-represented in a particular region relative to the given site, but need not be present in all members of the input sequence collection. The algorithm iteratively redefines the set of putative motif representatives from which a weight matrix is derived, so as to maximize a quantitative measure of local over-representation, an optimization criterion that naturally combines structural and positional constancy. A comprehensive description of the technique is presented in Methods and Data.

A superfamily of conserved domains in DNA damage-responsive cell cycle checkpoint proteins.

Computer analysis of a conserved domain, BRCT, first described at the carboxyl ter‐minus of the breast cancer protein BRCA1, a p53 binding protein (53BP1), and the yeast cell cycle checkpoint protein RAD9 revealed a large super‐ family of domains that occur predominantly in proteins involved in cell cycle checkpoint functions responsive to DNA damage. The BRCT domain consists of ~95 amino acid residues and occurs as a tandem repeat at the carboxyl terminus of numerous proteins, but has been observed also as a tandem repeat at the amino terminus or as a single copy. The BRCT superfamily presently includes ~40 nonorthologous proteins, namely, BRCA1, 53BP1, and RAD9; a protein family that consists of the fission yeast replication checkpoint protein Rad4, the oncoprotein ECT2, the DNA repair protein XRCC1, and yeast DNA polymerase subunit DPB11; DNA binding enzymes such as terminal deoxynucleotidyltransferases, deoxycy‐ tidyl transferase involved in DNA repair, and DNA‐ligases III and IV; yeast multifunctional transcription factor RAP1; and several uncharacterized gene products. Another previously described domain that is shared by bacterial NAD‐dependent DNA‐ligases, the large subunits of eukaryotic replication factor C, and poly(ADP‐ri‐ bose) polymerases appears to be a distinct version of the BRCT domain. The retinoblastoma protein (a universal tumor suppressor) and related proteins may contain a distant relative of the BRCT domain. Despite the functional diversity of all these proteins, participation in DNA damage‐re‐ sponsive checkpoints appears to be a unifying theme. Thus, the BRCT domain is likely to perform critical, yet uncharacterized, functions in the cell cycle control of organisms from bacteria to humans. The car boxyterminal BRCT domain of BRCA1 corresponds precisely to the recently identified minimal transcription activation domain of this protein, indicating one such function.— Bork, P., Hofmann, K., Bucher, P., Neuwald, A. F., Altschul, S. F., Koonin, E. V. A superfamily of conserved domains in DNA damage‐responsive cell cycle checkpoint proteins. FASEB J. 11, 68‐ 76 (1997)

The CARD domain: a new apoptotic signalling motif

Note: Swiss Institute for Experimental Cancer Research, University of Lausanne, Switzerland. Reference GR-BUCHER-ARTICLE-1997-004doi:10.1016/S0968-0004(97)01043-8 Record created on 2007-12-17, modified on 2017-05-12

The UBA domain: a sequence motif present in multiple enzyme classes of the ubiquitination pathway.

Note: Swiss Institute for Experimental Cancer Research, Epalinges s/Lausanne, Switzerland. Reference GR-BUCHER-ARTICLE-1996-005 Record created on 2007-12-17, modified on 2017-05-12

A flexible motif search technique based on generalized profiles

A flexible motif search technique is presented which has two major components: (1) a generalized profile syntax serving as a motif definition language; and (2) a motif search method specifically adapted to the problem of finding multiple instances of a motif in the same sequence. The new profile structure, which is the core of the generalized profile syntax, combines the functions of a variety of motif descriptors implemented in other methods, including regular expression-like patterns, weight matrices, previously used profiles, and certain types of hidden Markov models (HMMs). The relationship between generalized profiles and other biomolecular motif descriptors is analyzed in detail, with special attention to HMMs. Generalized profiles are shown to be equivalent to a particular class of HMMs, and conversion procedures in both directions are given. The conversion procedures provide an interpretation for local alignment in the framework of stochastic models, allowing for clear, simple significance tests. A mathematical statement of the motif search problem defines the new method exactly without linking it to a specific algorithmic solution. Part of the definition includes a new definition of disjointness of alignments.

The PCI domain: a common theme in three multiprotein complexes

Note: Swiss Institute for Experimental Cancer Research, Lausanne, Switzerland. khofmann@isrec.unil.ch/domains. Reference GR-BUCHER-ARTICLE-1998-003doi:10.1016/S0968-0004(98)01217-1 Record created on 2007-12-17, modified on 2017-05-12

Searching for regulatory elements in human noncoding sequences

Important progress has been made in the past two years in the identification of Pol II promoters. For most other regulatory elements, however, current biological knowledge is still insufficient to allow the development of prediction tools. The phylogenetic-footprinting strategy, which is based on the comparative analysis of homologous sequences, is a very efficient approach to identify new unknown regulatory elements. The recent organization of large-scale sequencing projects for some model vertebrate organisms will be extremely valuable for the prediction of regulatory elements in the human genome.

The Eukaryotic Promoter Database EPD

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. WWW-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. 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

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.

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.