Search

Mammalian Cdc25 phosphatase is responsible for the dephosphorylation of Cdc2 and other cyclin-dependent kinases at Thr14 and Tyr15, thus activating the kinase and allowing cell cycle progression. The catalytic domain of this dual-specificity phosphatase has recently been mapped to the 180 most C-terminal amino acids. Apart from a CX3R motif, which is present at the active site of all known tyrosine phosphatases, Cdc25 does not share any obvious sequence similarity with any of those enzymes. Until very recently, the Cdc25 family was the only subfamily of tyrosine phosphates for which no three-dimensional structural data were available. Using the generalized profile technique, a sensitive method for sequence database searches, we found an extended and highly significant sequence similarity between the Cdc25 catalytic domain and similarly sized regions in other proteins: the non-catalytic domain of two distinct families of MAP-kinase phosphates, the non-catalytic domain of several ubiquitin protein hydrolases, the N and C-terminal domain of rhodanese, and a large and heterogeneous groups of stress-response proteins from all phyla. The relationship of Cdc25 to the structurally well-characterized rhodanese spans the entire catalytic domain and served as template for a structural model for human Cdc25a, which is fundamentally different from previously suggested models for Cdc25 catalytic domain organization. The surface positioning of subfamily-specific conserved residues allows us to predict the sites of interaction with Cdk2, a physiological target of Cdc25a. Based on the results of this analysis, we also predict that the budding yeast arsenate resistance protein Acr2 and the ORF Ygr203w encode protein phosphatases with catalytic properties similar to that of the Cdc25 family. Recent determination of the crystal structure of the Cdc25a catalytic domain supports the validity of the model and demonstrates the power of the generalized sequence profile technique in homology-based modeling of the three-dimensional structure of a protein having a weak but significant sequence similarity with a structurally characterized protein.

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

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 interleukin 2 receptor alpha-chain (IL-2R alpha) gene is a key regulator of lymphocyte proliferation. IL-2R alpha is rapidly and potently induced in T cells in response to mitogenic stimuli. Interleukin 2 (IL-2) stimulates IL-2R alpha. transcription, thereby amplifying expression of its own high-affinity receptor. IL-2R alpha transcription is at least in part controlled by two positive regulatory regions, PRRI and PRRII. PRRI is an inducible proximal enhancer, located between nucleotides -276 and -244, which contains NF-kappaB and SRE/CArG motifs. PRRII is a T-cell-specific enhancer, located between nucleotides -137 and -64, which binds the T-cell-specific Ets protein Elf-1 and HMG-I(Y) proteins. However, none of these proximal regions account for the induction of IL-2R alpha transcription by IL-2. To find new regulatory regions of the IL-2R alpha gene, 8.5 kb of the 5' end noncoding sequence of the IL-2R alpha gene have been sequenced. We identified an 86-nucleotide fragment that is 90% identical to the recently characterized murine IL-2-responsive element (mIL-2rE). This putative human IL-2rE, designated PRRIII, confers IL-2 responsiveness on a heterologous promoter. PRRIII contains a Stat protein binding site that overlaps with an EBS motif (GASd/EBSd). These are essential for IL-2 inducibility of PRRIII/CAT reporter constructs. IL-2 induced the binding of Stat5a and b proteins to the human GASd element. To confirm the physiological relevance of these findings, we carried out in vivo footprinting experiments which showed that stimulation of IL-2R alpha expression correlated with occupancy of the GASd element. Our data demonstrate a major role of the GASd/EBSd element in IL-2R alpha regulation and suggest that the T-cell-specific Elf-1 factor can serve as a transcriptional repressor.

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

The RFX DNA binding domain is a novel motif that has been conserved in a growing number of dimeric DNA-binding proteins, having diverse regulatory functions, in eukaryotic organisms ranging from yeasts to humans. To characterize this novel motif, we have performed a detailed dissection of the site-specific DNA binding activity of RFX1, a prototypical member of the RFX family. First, we have performed a site selection procedure to define the consensus binding site of RFX1. Second, we have developed a new mutagenesis-selection procedure to derive a precise consensus motif, and to test the accuracy of a secondary structure prediction, for the RFX domain. Third, a modification of this procedure has allowed us to isolate altered-specificity RFX1 mutants. These results should facilitate the identification both of additional candidate genes controlled by RFX1 and of new members of the RFX family. Moreover, the altered-specificity RFX1 mutants represent valuable tools that will permit the function of RFX1 to be analyzed in vivo without interference from the ubiquitously expressed endogenous protein. Finally, the simplicity, efficiency, and versatility of the selection procedure we have developed make it of general value for the determination of consensus motifs, and for the isolation of mutants exhibiting altered functional properties, for large protein domains involved in protein-DNA as well as protein-protein interactions.

Taking advantage of a potent MHC class I–restricted response that allows the identification of antigen- selected CD8 T cells directly ex vivo, we characterized the antigen-specific T cell repertoires that develop in individual mice by single-cell PCR analysis. Each of the immune mice displayed distinct yet structurally similar TCR repertoires. The overall repertoire size was estimated to be in the range of 15–20 for most mice. No major differences were observed between primary and secondary responses. Moreover, for a hyperimmunized mouse the antigen-specific TCR repertoire expressed 8 months after the initial immunization was very similar to that found at the peak of the primary response. Our results demonstrate that a high magnitude immune response may be composed of very few clones, and that at least in the system analyzed, the memory response largely reflects the repertoire selected by the peak of the primary response.

Note: Swiss Institute of Experimental Cancer Research (ISREC), Epalinges, Switzerland. Reference GR-BUCHER-ARTICLE-1995-003 Record created on 2007-12-17, modified on 2017-05-12

Commonly used RNA folding programs compute the minimum free energy structure of a sequence under the pseudoknot exclusion constraint. They are based on Zuker's algorithm which runs in time O(n3). Recently, it has been claimed that RNA folding can be achieved in average time O(n2) using a sparsification technique. A proof of quadratic time complexity was based on the assumption that computational RNA folding obeys the "polymer-zeta property". Several variants of sparse RNA folding algorithms were later developed. Here, we present our own version, which is readily applicable to existing RNA folding programs, as it is extremely simple and does not require any new data structure. We applied it to the widely used Vienna RNAfold program, to create sibRNAfold, the first public sparsified version of a standard RNA folding program. To gain a better understanding of the time complexity of sparsified RNA folding in general, we carried out a thorough run time analysis with synthetic random sequences, both in the context of energy minimization and base pairing maximization. Contrary to previous claims, the asymptotic time complexity of a sparsified RNA folding algorithm using standard energy parameters remains O(n3) under a wide variety of conditions. Consistent with our run-time analysis, we found that RNA folding does not obey the "polymer-zeta property" as claimed previously. Yet, a basic version of a sparsified RNA folding algorithm provides 15- to 50-fold speed gain. Surprisingly, the same sparsification technique has a different effect when applied to base pairing optimization. There, its asymptotic running time complexity appears to be either quadratic or cubic depending on the base composition. The code used in this work is available at: http://sibRNAfold.sourceforge.net/ .

The advent of high-throughput technologies such as ChIP-seq has made possible the study of histone modifications. A problem of particular interest is the identification of regions of the genome where different cell types from the same organism exhibit different patterns of histone enrichment. This problem turns out to be surprisingly difficult, even in simple pairwise comparisons, because of the significant level of noise in ChIP-seq data. In this paper we propose a two-stage statistical method, called ChIPnorm, to normalize ChIP-seq data, and to find differential regions in the genome, given two libraries of histone modifications of different cell types. We show that the ChIPnorm method removes most of the noise and bias in the data and outperforms other normalization methods. We correlate the histone marks with gene expression data and confirm that histone modifications H3K27me3 and H3K4me3 act as respectively a repressor and an activator of genes. Compared to what was previously reported in the literature, we find that a substantially higher fraction of bivalent marks in ES cells for H3K27me3 and H3K4me3 move into a K27-only state. We find that most of the promoter regions in protein-coding genes have differential histone-modification sites. The software for this work can be downloaded from http://lcbb.epfl.ch/software.html.

Common practice emphasizes significant sequence similarities between different members of protein families. These similarities presumably reflect on evolutionary conservation of structurally and functionally essential residues. The nonconserved regions, on the other hand, may be either selectively neutral or differentiated. We propose several distributional sequence statistics (e.g., clustering of charged residues, compositional biases, and repetitive patterns) as indicators of differentiation events. These ideas are illustrated with various examples, including comparisons among G protein-coupled receptors, herpesvirus proteins, and GTPase-activating proteins.

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

The genomes of human viruses herpes simplex 1 (HSV1) and varicella zoster (VZV), although similar in biology, largely concordant in gene order, and identical in many amino acid segments, differ widely in their genomic G + C (abbreviated S) content, which is high in HSV1 (68%) and low in VZV (46%). This paper analyzes several striking codon usage contrasts. The S difference in coding regions is dramatically large in codon site 3, S3, about 42%. The large difference in S3 is maintained at the same level in a subset of closely similar genes and even in corresponding identical amino acid blocks. A similar difference in S levels in silent site 1 (S1) is found in leucine and arginine. The difference in S3 levels occurs in every gene and in every multicodon amino acid form. The S difference also exists in amino acid usage, with HSV1 using significantly more codon types SSN, while VZV uses more codon types WWN (where W stands for A or T). The nonoverlapping and narrow histograms of S3 gene frequencies in both viruses suggest that the difference has arisen and been maintained by a process of selective rather than nonselective effects. This is in sharp contrast to the relatively large variance seen for highly similar genes in the human versus yeast analysis. Interpretations and hypotheses to explain the HSV1 vs VZV codon usage disparity relate to virus-host interactions, to the role of viral genes in DNA metabolism, to availability of molecular resources (molecular Gause exclusion principle), and to differences in genomic structure.

Note: Department of Mathematics, Stanford University, California 94305. Reference GR-BUCHER-ARTICLE-1991-002 Record created on 2007-12-17, modified on 2017-05-12

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.

There are a variety of bacterial defense strategies to survive in a hostile environment. Generation of extracellular polysaccharides has proved to be a simple but effective strategy against the host's innate immune system. A comparative genomics approach led us to identify a new protein family termed Stealth, most likely involved in the synthesis of extracellular polysaccharides. This protein family is characterized by a series of domains conserved across phylogeny from bacteria to eukaryotes. In bacteria, Stealth (previously characterized as SacB, XcbA, or WefC) is encoded by subsets of strains mainly colonizing multicellular organisms, with evidence for a protective effect against the host innate immune defense. More specifically, integrating all the available information about Stealth proteins in bacteria, we propose that Stealth is a D-hexose-1-phosphoryl transferase involved in the synthesis of polysaccharides. In the animal kingdom, Stealth is strongly conserved across evolution from social amoebas to simple and complex multicellular organisms, such as Dictyostelium discoideum, hydra, and human. Based on the occurrence of Stealth in most Eukaryotes and a subset of Prokaryotes together with its potential role in extracellular polysaccharide synthesis, we propose that metazoan Stealth functions to regulate the innate immune system. Moreover, there is good reason to speculate that the acquisition and spread of Stealth could be responsible for future epidemic outbreaks of infectious diseases caused by a large variety of eubacterial pathogens. Our in silico identification of a homologous protein in the human host will help to elucidate the causes of Stealth-dependent virulence. At a more basic level, the characterization of the molecular and cellular function of Stealth proteins may shed light on fundamental mechanisms of innate immune defense against microbial invasion., Synopsis The immune system is a complex and highly developed system of specialized cells and organs that protects an organism against bacterial, parasitic, fungal, and viral infections. Broadly speaking, the different types of immune responses subdivide the immune system into two categories: innate (or nonadaptive) and adaptive immune system. The innate immune system serves as a first line of defense but lacks the ability to recognize certain pathogens and to provide the specific protective immunity that prevents reinfection. Just as metazoans have developed many different defenses against pathogens, so have pathogens evolved elaborate strategies to evade these defenses. Based on a comparative genomics approach and data mining, the authors have discovered a new family of proteins with a striking phylogenetic distribution, occurring in most eukaryotes and in subsets of mostly pathogenic or commensal prokaryotes. While the precise functions of these proteins remain unknown, prokaryotic versions have been implicated in the synthesis of extracellular polysaccharides known to be potent regulators of the innate immune system. This previously unrecognized link hints towards a potentially novel regulatory mechanism of the innate immune system. It remains to be shown if drugs selectively inhibiting Stealth in pathogens will help fight Stealth-mediated infections.

Sequence analytic methods have played a role in the understanding of transcriptional regulation for many years (for example, an alignment of E. coli promoter regions showing conserved upstream regions was reported by Pribnow et al. in 1975). In recent years there has been a tremendous increase in experimental work aimed at understanding the fundamental biochemistry of transcription initiation as well as the mechanisms that regulate gene expression at the level of transcription. There is currently great interest in developing new computational methods as well. This interest is driven partly by the new biological understanding (and will hopefully contribute to it, by the use of quantitative models), and partly by the need to efficiently analyse newly determined genomic sequences. Computational biologists interested in transcription have made good progress in the last few years. For example, an improved ability to describe the DNA binding specificity of proteins involved in transcription lies at the foundation of much of the mathematical modeling in the field. It has been generally recognized that consensus sequences are usually inadequate to describe DNA-binding specificity, and it is now most common to describe the binding sites of a particular protein as the set of sequences scoring above a particular threshold with a Positional Weight Matrix (PWM). Considerable theoretical work, and some experimental effort, have gone into the development of algorithms to find a PWM from known binding sites, understand to what extent the description of specificity by means of a PWM is valid, and record PWMs for particular proteins. Other important areas of progress include computer programs for the recognition of eukaryotic promoters that for the first time have error rates low enough so that the program is of practical interest, and a number of recently developed data collections that are either more complete or more consistent than what is available in the primary sequence databases. It may also be counted as progress that some early errors of the field have now been corrected, so that (1) it is now widely recognized that transcriptional regulation is exceedingly complex, and that algorithms must take into account alternative pathways and the synergism of multiple transcription factors, and (2) cross-validation techniques are now commonly employed in the benchmarking of new algorithms for functional prediction. We feel that one of the main needs in the field is simply for better communication. Experimentalists often do not take advantage of the best computational techniques; algorithm developers often base their methods on an overly simplified view of the biology; computer scientists do not use the best data collections; and mathematicians sometimes show an aversion to learning about powerful machine learning techniques. In order to promote communication and collaboration, and to assess the state of the art, we organized the first International Workshop on Computational Analysis of Eukaryotic Transcriptional Regulatory Elements, at the Deutsches Krebsforschungszentrum in Heidelberg, in January of 1996. We were very pleased to have a highly interdisciplinary meeting of about 70 people, with participation from sequence analysts, pure experimentalists, computer scientists, researchers working on the nucleosome positioning problem, microscopists using computers for image processing, structural biologists interested in the 3D structure of promoters and gene regulatory proteins, and experts from the neighbouring field of prokaryotic gene transcription. It was particularly encouraging that there were several presentations at the meeting by groups comprising both experimental and computational biologists, and that communication between the experimental and the computational side seemed to be excellent. The interdisciplinary nature of the meeting also helped to focus attention on the primary scientific goal that all participants share: to understand, by modelling and model-testing, the transcription initiation event and its use in the regulation of gene expression. It remains a controversial issue whether function can be determined from the DNA sequence, at the level of symbol manipulation, without reference to 3D structure or other more biological representations of the data. (Most sequence analysis developers tacitly assume that such is possible, although it may be unwise to do so.) What is clear is that the work of a person in any one discipline will be much more effective if he or she is willing to understand and make use of the results of related disciplines. Experience to date suggests that in the analysis of transcriptional regulatory elements, more than in other domains of

Keywords: DNA ; Nucleic Acid Conformation ; Nucleic Acid Renaturation Reference EPFL-ARTICLE-176179doi:10.1101/SQB.1983.047.01.015 Record created on 2012-04-13, modified on 2017-05-12

The generation of "signal search data" represents a general method of describing the common properties of a set of DNA sequences presumed to be functionally analogous. Besides the detailed description of this method we present two computer programs which use signal search data as input data: One that processes them to a "constraint profile" and another one which lists over-represented "signals" of potential functional relevance. To illustrate the possibilities of our method we have analysed a set of transcription initiation sites of sea urchin histone genes.

A cloned Xenopus laevis H4 histone gene has been expressed in the X.laevis oocyte nucleus. The homologous histone H4 gene can be correctly and efficiently expressed in the frog oocyte even in presence of bacterial vector DNA. As revealed by both analytical gel electrophoresis and S1 mapping, two H4 mRNAs are specified with different transcriptional efficiencies from the tandemly repeated promoter. Results from deletion mapping of the sequences essential for promoting H4 transcription show that drastic reduction of transcription is obtained when the sequences lying between -64 and -35 bp from the mRNA cap site are removed. We demonstrate by DNA sequence comparison using a novel computer program that this important area of the H4 promoter contains two highly conserved DNA motifs near positions -51 to -46 upstream from the cap site in all H4 gene promoters analysed.

S1 nuclease mapping of the Psammechinus miliaris embryonic histone mRNAs locates the 5' termini in or adjacent to a short sequence homology (5'pyCATTCpu3') downstream from the putative RNA polymerase II regulatory sequence (5'TATAAATA3') or related sequences. The 3' termini map just after a sequence containing GC-rich hyphenated dyad symmetry, a feature of most known terminator sequences.

The so-called CCAAT box is believed to be a major promoter element of higher eukaryotes though it is ill-defined being deduced from very limited sequence data. The comprehensive computer analysis of an unbiased set of 168 promoters presented here removes several of the persisting uncertainties. In particular, it delineates the region of preferential occurrence of the CCAAT element to -110 to -50 relative to the initiation site, suggests that integrity of this pentamer is essential, and confirms bidirectionality as a general property of this element. Within the above region the signal is found to occur in a specific sequence context which is an important supplement to its description.

A representative set of 168 eukaryotic POL II promoters has been compiled from the EMBL library and subjected to computer signal search analysis. Application of this technique to E. coli promoters as a control ensemble revealed the well known consensus sequences at -35 and -10 which indicates that the methods are adequate to approach problems of this kind. The results obtained from the eukaryotic promoter set can be summarized as follows: Common sequence features are confined to a region between -50 and +10 relative to the transcriptional initiation site. The only well conserved consensus sequence is TATAAA, centered at -28. A weak motif, CA followed preferentially by pyrimidines, surrounds the cap-site. Two pentanucleotides which have been shown by experiments to stimulate transcription of certain genes, GGGCG and CCAAT, are moderately over-represented in the upstream region (between -129 and -50). However, they occur at highly variable distances from the initiation site.

The low frequency of precursor cells specific for any particular antigen (Ag) makes it difficult to characterize preimmune T cell receptor (TCR) repertoires and to understand repertoire selection during an immune response. We have undertaken a combined adoptive transfer single-cell PCR approach to probe the Ag-specific preimmune repertoires of individual mice. Our strategy was to inject paired irradiated recipient mice with normal spleen cells prepared from individual donors and to compare the TCR repertoires subsequently selected during a CD8 response to a defined model Ag. We found that although some TCRs were shared, the TCR repertoires selected by mice receiving splenocytes from the same donor were not identical in terms of the TCRs selected and their relative frequencies. Our results together with computer simulations imply that individual mice express distinct Ag-specific preimmune TCR repertoires composed of expanded clones and that selection by Ag is a random process.

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.

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 description of the initiation site mapping data, cross-references to other databases, and bibliographic references. EPD is structured in a way that facilitates dynamic extraction of biologically meaningful promoter subsets for comparative sequence analysis. Recent efforts have focused on exhaustive crossreferencing to the EMBL nucleotide sequence database, and on the improvement of the WWW-based user interfaces and data retrieval mechanisms. EPD can be accessed at http://www.epd.isb-sib.ch DATABASE DESCRIPTION EPD is a database of gene function which keeps track of experimental evidence defining the initiation sites of eukaryotic RNA POL II genes. This information is linked to promoter sequence data via machine readable pointers to corresponding positions in entries of the EMBL nucleotide sequence database (1). Note that EPD does not provide information on promoters in the sense of genetically defined transcription regulatory elements. Such information can be found in TRANSFAC and COMPEL (2) and other databases described in this issue. EPD was originally designed as a resource for comparative sequence analysis and as such has played an instrumental role in the development of eukaryotic promoter prediction algorithms (3). Recently, its scope has been expanded to meet the requirements of the TRADAT project (see http://www.itba.mi.cnr.it/ tradat/ ), a European consortium effort to develop integrated tools for the interpretation of genomic DNA sequences with emphasis on regulatory regions. The extensions comprise many cross-references to data collections covering other aspects of genes and promoters. EPD is a rigorously selected, curated, and quality-controlled database. In order to be included, a promoter must fulfill a number of conditions laid down in the user manual. For instance, its transcription start site must be mapped with a certain accuracy and certainty, the corresponding gene must be functional, and corresponding sequence data must be available in the public databases. EPD is further confined to promoters recognized by the RNA POL II systems of higher eukaryotes, excluding fungi, algae and protists. However, since promoters are viewed as physiological elements dependent on the correct interpretation by a trans-acting environment, many viral promoters are included and classified with their host species. A strict non-redundancy policy is applied based on the principle that one entry should correspond to one biological entity. Data from different literature sources pertaining to the same transcription initiation sites are thus always combined in a single entry. Orthologous promoters from different species are linked by internal cross-references, as are alternative promoters of the same gene. All information in EPD originates from a critical examination and independent interpretation of the experimental data presented in the cited research publications. Published conclusions and feature table annotations in EMBL sequence entries are never blindly relied upon. A more detailed description of the contents and format of EPD has been published in last year’s database issue ( 4).

Background: In cell differentiation, a less specialized cell differentiates into a more specialized one, even though all cells in one organism have (almost) the same genome. Epigenetic factors such as histone modifications are known to play a significant role in cell differentiation. We previously introduce cell-type trees to represent the differentiation of cells into more specialized types, a representation that partakes of both ontogeny and phylogeny. Results: We propose a maximum-likelihood (ML) approach to build cell-type trees and show that this ML approach outperforms our earlier distance-based and parsimony-based approaches. We then study the reconstruction of ancestral cell types; since both ancestral and derived cell types can coexist in adult organisms, we propose a lifting algorithm to infer internal nodes. We present results on our lifting algorithm obtained both through simulations and on real datasets. Conclusions: We show that our ML-based approach outperforms previously proposed techniques such as distance-based and parsimony-based methods. We show our lifting-based approach works well on both simulated and real data.

Metazoan core promoters, which direct the initiation of transcription by RNA polymerase II (Pol II), may contain short sequence motifs termed core promoter elements/motifs (e.g. the TATA box, initiator (Inr) and downstream core promoter element (DPE)), which recruit Pol II via the general transcription machinery. The DPE was discovered and extensively characterized in Drosophila, where it is strictly dependent on both the presence of an Inr and the precise spacing from it. Since the Drosophila DPE is recognized by the human transcription machinery, it is most likely that some human promoters contain a downstream element that is similar, though not necessarily identical, to the Drosophila DPE. However, only a couple of human promoters were shown to contain a functional DPE, and attempts to computationally detect human DPE-containing promoters have mostly been unsuccessful. Using a newly-designed motif discovery strategy based on Expectation-Maximization probabilistic partitioning algorithms, we discovered preferred downstream positions (PDP) in human promoters that resemble the Drosophila DPE. Available chromatin accessibility footprints revealed that Drosophila and human Inr+DPE promoter classes are not only highly structured, but also similar to each other, particularly in the proximal downstream region. Clustering of the corresponding sequence motifs using a neighbor-joining algorithm strongly suggests that canonical Inr+DPE promoters could be common to metazoan species. Using reporter assays we demonstrate the contribution of the identified downstream positions to the function of multiple human promoters. Furthermore, we show that alteration of the spacing between the Inr and PDP by two nucleotides results in reduced promoter activity, suggesting a spacing dependency of the newly discovered human PDP on the Inr. Taken together, our strategy identified novel functional downstream positions within human core promoters, supporting the existence of DPE-like motifs in human promoters., Author summary Transcription of genes by the RNA polymerase II enzyme initiates at a genomic region termed the core promoter. The core promoter is a regulatory region that may contain diverse short DNA sequence motifs/elements that confer specific properties to it. Interestingly, core promoter motifs can be located both upstream and downstream of the transcription start site. Variable compositions of core promoter elements were identified. The initiator (Inr) motif and the downstream core promoter element (DPE) is a combination of elements that has been identified and extensively characterized in fruit flies. Although a few Inr+DPE -containing human promoters were identified, the presence of transcriptionally important downstream core promoter positions within human promoters has been a matter of controversy in the literature. Here, using a newly-designed motif discovery strategy, we discovered preferred downstream positions in human promoters that resemble fruit fly DPE. Clustering of the corresponding sequence motifs in eight additional species indicated that such promoters could be common to multicellular non-plant organisms. Importantly, functional characterization of the newly discovered preferred downstream positions supports the existence of Inr+DPE-containing promoters in human genes.

Theoretical considerations predict that amplification of expressed gene transcripts by reverse transcription-PCR using arbitrarily chosen primers will result in the preferential amplification of the central portion of the transcript. systematic, high-throughput sequencing of such products would result in an expressed sequence tag (EST) database consisting of central, generally coding regions of expressed genes. Such a database would add significant value to existing public EST databases, which consist mostly of sequences derived from the extremities of cDNAs, and facilitate the construction of contigs of transcript sequences. We tested our predictions, creating a database of 10,000 sequences from human breast tumors. The data confirmed the central distribution of the sequences, the significant normalization of the sequence population, the frequent extension of contigs composed of existing human ESTs, and the identification of a series of potentially important homologues of known genes. This approach should make a significant contribution to the early identification of important human genes, the deciphering of the draft human genome sequence currently being compiled, and the shotgun sequencing of the human transcriptome. Ludwig Inst Canc Res, BR-01509010 Sao Paulo, Brazil Univ Sao Paulo, Inst Quim, Dept Bioquim, BR-05599970 Sao Paulo, Brazil Univ Fed Sao Paulo, Escola Paulista Med, BR-04023062 Sao Paulo, Brazil Univ Sao Paulo, Fac Med, Dept Radiol, BR-01296903 Sao Paulo, Brazil Fac Med Ribeirao Preto, Dept Clin Med, BR-14049900 Sao Paulo, Brazil Univ Estadual Campinas, Hemoctr, BR-13089970 Sao Paulo, Brazil Fac Ciencias Farmaceut Ribeirao Preto, Dept Ciencias Farmaceut, BR-14049900 Sao Paulo, Brazil Swiss Inst Bioinformat, CH-1066 Epalinges, Switzerland Swiss Inst Expt Canc Res, CH-1066 Epalinges, Switzerland Ludwig Inst Canc Res, Off Informat Technol, CH-1066 Epalinges, Switzerland UCL, Ludwig Inst Canc Res, London W1P 7LD, England Hosp AC Camargo Fund Antonio Prudente, BR-01509010 Sao Paulo, Brazil Univ Fed Sao Paulo, Escola Paulista Med, BR-04023062 Sao Paulo, Brazil Web of Science

The CleanEx expression database (http://www.cleanex.isb-sib.ch) provides access to public gene expression data via unique gene names as well as via experiments biomedical characteristics. To reach this, a dual annotation of both sequences and experiments has been generated. First, the system links official gene symbols to any kind of sequences used for gene expression measurements (cDNA, Affymetrix, oligonucleotide arrays, SAGE or MPSS tags, Expressed Sequence Tags or other mRNA sequences, etc.). For the biomedical annotation, we re-annotate each experiment from the CleanEx database with the MeSH (Medical Subject Headings) terms, primarily used by NLM (National Library of Medicine) for indexing articles for the MEDLINE/PubMED database. This annotation allows a fast and easy retrieval of expression data with common biological or medical features. The numerical data can then be exported as matrix-like tab-delimited text files. Data can be extracted from either one dataset or from heterogeneous datasets.

We have biochemically and functionally characterized a new transcription factor, NP-TCII, which is present in nuclei from unstimulated T and B lymphocytes but is not found in nonhematopoietic cells. This factor has a DNA-binding specificity similar to that of NF-kappa B but is unrelated to this or other Rel proteins by functional and biochemical criteria. It can also be distinguished from other previously described lymphocyte-specific DNA-binding proteins.

The function of DNA-binding proteins is controlled not just by their abundance, but mainly at the level of their activity in terms of their interactions with DNA and protein targets. Moreover, the affinity of such transcription factors to their target sequences is often controlled by co-factors and/or modifications that are not easily assessed from biological samples. Here, we describe a scalable method for monitoring protein-DNA interactions on a microarray surface. This approach was designed to determine the DNA-binding activity of proteins in crude cell extracts, complementing conventional expression profiling arrays. Enzymatic labeling of DNA enables direct normalization of the protein binding to the microarray, allowing the estimation of relative binding affinities. Using DNA sequences covering a range of affinities, we show that the new microarray-based method yields binding strength estimates similar to low-throughput gel mobility-shift assays. The microarray is also of high sensitivity, as it allows the detection of a rare DNA-binding protein from breast cancer cells, the human tumor suppressor AP-2. This approach thus mediates precise and robust assessment of the activity of DNA-binding proteins and takes present DNA-binding assays to a high throughput level.

We present a comparative study of residue usage correlations of various organism protein sets of diverse phylogenetic species and of open reading frames of several large human viral genomes. Our correlation analysis reveals three major tendencies: (i) charge compensation reflected by the high correlation of basic with acidic residues; (ii) the positive correlations of functionally and structurally similar amino acids including many pairs of hydrophobic amino acids, all pairs of aromatic amino acids, the anionic pair (glutamate and aspartate), but not the cationic pair (lysine and arginine), moderately the hydroxyl pair (serine and threonine), the small amino acids (glycine and alanine), and many (but not all) of those having high values in the Dayhoff substitutability matrix (characteristics such as amino acid polarity or codon usage agreement, except for the wobble position, do not necessarily imply significant positive correlations); (iii) a widespread negative correlation of the aggregate strong codon group amino acids (Ala, Gly, Pro) versus the weak codon group amino acids (Lys, Ile, Tyr, Asn, Phe). Discussion and speculations relate amino acid usage correlations to protein function/structure, cellular localization, proximity in amino acid biosynthetic pathways, amino acid relative abundances, tRNA and aminoacyl synthetase availabilities, and evolutionary processes.

Motivation: Genomic context analysis, also known as phylogenetic profiling, is widely used to infer functional interactions between proteins but rarely applied to non-coding cis-regulatory DNA elements. We were wondering whether this approach could provide insights about utlraconserved non-coding elements (UCNEs). These elements are organized as large clusters, so-called gene regulatory blocks (GRBs) around key developmental genes. Their molecular functions and the reasons for their high degree of conservation remain enigmatic. Results: In a special setting of genomic context analysis, we analyzed the fate of GRBs after a whole-genome duplication event in five fish genomes. We found that in most cases all UCNEs were retained together as a single block, whereas the corresponding target genes were often retained in two copies, one completely devoid of UCNEs. This ‘winner-takes-all’ pattern suggests that UCNEs of a GRB function in a highly cooperative manner. We propose that the multitude of interactions between UCNEs is the reason for their extreme sequence conservation. Supplementary information: Supplementary data are available at Bioinformatics online and at http://ccg.vital-it.ch/ucne/

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.

Background Cleavage of messenger RNA (mRNA) precursors is an essential step in mRNA maturation. The signal recognized by the cleavage enzyme complex has been characterized as an A rich region upstream of the cleavage site containing a motif with consensus AAUAAA, followed by a U or UG rich region downstream of the cleavage site. Results We studied these signals using exhaustive databases of cleavage sites obtained from aligning raw expressed sequence tags (EST) sequences to genomic sequences in Homo sapiens and Drosophila melanogaster. These data show that the polyadenylation signal is highly conserved in human and fly. In addition, de novo motif searches generated a refined description of the U-rich downstream sequence (DSE) element, which shows more divergence between the two species. These refined motifs are applied, within a Hidden Markov Model (HMM) framework, to predict mRNA cleavage sites. Conclusion We demonstrate that the DSE is a specific motif in both human and Drosophila. These findings shed light on the sequence correlates of a highly conserved biological process, and improve in silico prediction of 3' mRNA cleavage and polyadenylation sites.

High throughput genome (HTG) and expressed sequence tag (EST) sequences are currently the most abundant nucleotide sequence classes in the public database. The large volume, high degree of fragmentation and lack of gene structure annotations prevent efficient and effective searches of HTG and EST data for protein sequence homologies by standard search methods. Here, we briefly describe three newly developed resources that should make discovery of interesting genes in these sequence classes easier in the future, especially to biologists not having access to a powerful local bioinformatics environment. trEST and trGEN are regularly regenerated databases of hypothetical protein sequences predicted from EST and HTG sequences, respectively. Hits is a web-based data retrieval and analysis system providing access to precomputed matches between protein sequences (including sequences from trEST and trGEN) and patterns and profiles from Prosite and Pfam. The three resources can be accessed via the Hits home page (http://hits.isb-sib.ch).

Background Understanding the mechanisms by which transcription factors (TF) are recruited to their physiological target sites is crucial for understanding gene regulation. DNA sequence intrinsic features such as predicted binding affinity are often not very effective in predicting in vivo site occupancy and in any case could not explain cell-type specific binding events. Recent reports show that chromatin accessibility, nucleosome occupancy and specific histone post-translational modifications greatly influence TF site occupancy in vivo. In this work, we use machine-learning methods to build predictive models and assess the relative importance of different sequence-intrinsic and chromatin features in the TF-to-target-site recruitment process. Methods Our study primarily relies on recent data published by the ENCODE consortium. Five dissimilar TFs assayed in multiple cell-types were selected as examples: CTCF, JunD, REST, GABP and USF2. We used two types of candidate target sites: (a) predicted sites obtained by scanning the whole genome with a position weight matrix, and (b) cell-type specific peak lists provided by ENCODE. Quantitative in vivo occupancy levels in different cell-types were based on ChIP-seq data for the corresponding TFs. In parallel, we computed a number of associated sequence-intrinsic and experimental features (histone modification, DNase I hypersensitivity, etc.) for each site. Machine learning algorithms were then used in a binary classification and regression framework to predict site occupancy and binding strength, for the purpose of assessing the relative importance of different contextual features. Results We observed striking differences in the feature importance rankings between the five factors tested. PWM-scores were amongst the most important features only for CTCF and REST but of little value for JunD and USF2. Chromatin accessibility and active histone marks are potent predictors for all factors except REST. Structural DNA parameters, repressive and gene body associated histone marks are generally of little or no predictive value. Conclusions We define a general and extensible computational framework for analyzing the importance of various DNA-intrinsic and chromatin-associated features in determining cell-type specific TF binding to target sites. The application of our methodology to ENCODE data has led to new insights on transcription regulatory processes and may serve as example for future studies encompassing even larger datasets. Electronic supplementary material The online version of this article (doi:10.1186/s12859-015-0846-z) contains supplementary material, which is available to authorized users.

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/.

MHC class II (MHC-II) genes are regulated by an enhanceosome complex containing two gene-specific transcription factors, regulatory factor X complex (RFX) and CIITA. These factors assemble on a strictly conserved regulatory module (S-X-X2-Y) found immediately upstream of the promoters of all classical and nonclassical MHC-II genes as well as the invariant chain (Ii) gene. To identify new targets of RFX and CIITA, we developed a computational approach based on the unique and highly constrained architecture of the composite S-Y motif. We identified six novel S′-Y′ modules situated far away from the promoters of known human RFX- and CIITA-controlled genes. Four are situated at strategic positions within the MHC-II locus, and two are found within the Ii gene. These S′-Y′ modules function as transcriptional enhancers, are bona fide targets of RFX and CIITA in B cells and IFN-γ-induced cells, and induce broad domains of histone hyperacetylation. These results reveal a hitherto unexpected level of complexity involving long distance control of MHC-II expression by multiple distal regulatory elements.

Discoidin (DS) domains occur in a large variety of proteins. We have recently reported the D1 domain of galactose oxidase (GOase), a copper-containing enzyme whose structure has been determined at 1.7 A resolution, as distant member of the DS domain family. The D1 domain of GOase consists of a five-stranded antiparallel β-sheet packing against a three-stranded antiparallel β-sheet. We here show that it is possible to build 3D models for DS domains using GOase as initial template and propose a 3D structure for the C1 and C2 domains of factor V (residues 1879-2037 and 2038-2196). Factors V (FV) and VIII (FVIII) are essential and homologous non-enzymatic cofactors in the coagulation cascade. They share the domain organization A1-A2-B-A3-C1 and C2 and their C domains are members of the DS family. The C1 and C2 domains of FV are rich in positively charged residues. Several clusters of amino acids, most likely involved in inter-domain interactions, protein-protein interactions and/or phospholipid binding, are identified. Our report opens new avenues to study the structure-function relationships of DS domains.

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.

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

Background KRAB-ZFPs (Krüppel-associated box domain-zinc finger proteins) are vertebrate-restricted transcriptional repressors encoded in the hundreds by the mouse and human genomes. They act via an essential cofactor, KAP1, which recruits effectors responsible for the formation of facultative heterochromatin. We have recently shown that KRAB/KAP1 can mediate long-range transcriptional repression through heterochromatin spreading, but also demonstrated that this process is at times countered by endogenous influences. Method To investigate this issue further we used an ectopic KRAB-based repressor. This system allowed us to tether KRAB/KAP1 to hundreds of euchromatic sites within genes, and to record its impact on gene expression. We then correlated this KRAB/KAP1-mediated transcriptional effect to pre-existing genomic and chromatin structures to identify specific characteristics making a gene susceptible to repression. Results We found that genes that were susceptible to KRAB/KAP1-mediated silencing carried higher levels of repressive histone marks both at the promoter and over the transcribed region than genes that were insensitive. In parallel, we found a high enrichment in euchromatic marks within both the close and more distant environment of these genes. Conclusion Together, these data indicate that high levels of gene activity in the genomic environment and the pre-deposition of repressive histone marks within a gene increase its susceptibility to KRAB/KAP1-mediated repression.

One major methodological problem in analysis of sequence data is the determination of costs from which distances between sequences are derived. Although this problem is currently not optimally dealt with in the social sciences, it has some similarity with problems that have been solved in bioinformatics for three decades. In this article, the authors propose an optimization of substitution and deletion/insertion costs based on computational methods. The authors provide an empirical way of determining costs for cases, frequent in the social sciences, in which theory does not clearly promote one cost scheme over another. Using three distinct data sets, the authors tested the distances and cluster solutions produced by the new cost scheme in comparison with solutions based on cost schemes associated with other research strategies. The proposed method performs well compared with other cost-setting strategies, while it alleviates the justification problem of cost schemes.

Background ChIP-seq and related high-throughput chromatin profilig assays generate ever increasing volumes of highly valuable biological data. To make sense out of it, biologists need versatile, efficient and user-friendly tools for access, visualization and itegrative analysis of such data. Results Here we present the ChIP-Seq command line tools and web server, implementing basic algorithms for ChIP-seq data analysis starting with a read alignment file. The tools are optimized for memory-efficiency and speed thus allowing for processing of large data volumes on inexpensive hardware. The web interface provides access to a large database of public data. The ChIP-Seq tools have a modular and interoperable design in that the output from one application can serve as input to another one. Complex and innovative tasks can thus be achieved by running several tools in a cascade. Conclusions The various ChIP-Seq command line tools and web services either complement or compare favorably to related bioinformatics resources in terms of computational efficiency, ease of access to public data and interoperability with other web-based tools. The ChIP-Seq server is accessible at http://ccg.vital-it.ch/chipseq/. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3288-8) contains supplementary material, which is available to authorized users.