trEST, trGEN and Hits: access to databases of predicted protein sequences.

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).

MyHits: improvements to an interactive resource for analyzing protein sequences.

The MyHits web site (http://myhits.isb-sib.ch) is an integrated service dedicated to the analysis of protein sequences. Since its first description in 2004, both the user interface and the back end of the server were improved. A number of tools (e.g. MAFFT, Jacop, Dotlet, Jalview, ESTScan) were added or updated to improve the usability of the service. The MySQL schema and its associated API were revamped and the database engine (HitKeeper) was separated from the web interface. This paper summarizes the current status of the server, with an emphasis on the new services.

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.

From protein sequences to 3D-structures and beyond: the example of the UniProt knowledgebase.

With the dramatic increase in the volume of experimental results in every domain of life sciences, assembling pertinent data and combining information from different fields has become a challenge. Information is dispersed over numerous specialized databases and is presented in many different formats. Rapid access to experiment-based information about well-characterized proteins helps predict the function of uncharacterized proteins identified by large-scale sequencing. In this context, universal knowledgebases play essential roles in providing access to data from complementary types of experiments and serving as hubs with cross-references to many specialized databases. This review outlines how the value of experimental data is optimized by combining high-quality protein sequences with complementary experimental results, including information derived from protein 3D-structures, using as an example the UniProt knowledgebase (UniProtKB) and the tools and links provided on its website ( http://www.uniprot.org/ ). It also evokes precautions that are necessary for successful predictions and extrapolations.

MyHits: a new interactive resource for protein annotation and domain identification.

The MyHits web server (http://myhits.isb-sib.ch) is a new integrated service dedicated to the annotation of protein sequences and to the analysis of their domains and signatures. Guest users can use the system anonymously, with full access to (i) standard bioinformatics programs (e.g. PSI-BLAST, ClustalW, T-Coffee, Jalview); (ii) a large number of protein sequence databases, including standard (Swiss-Prot, TrEMBL) and locally developed databases (splice variants); (iii) databases of protein motifs (Prosite, Interpro); (iv) a precomputed list of matches ('hits') between the sequence and motif databases. All databases are updated on a weekly basis and the hit list is kept up to date incrementally. The MyHits server also includes a new collection of tools to generate graphical representations of pairwise and multiple sequence alignments including their annotated features. Free registration enables users to upload their own sequences and motifs to private databases. These are then made available through the same web interface and the same set of analytical tools. Registered users can manage their own sequences and annotations using only web tools and freeze their data in their private database for publication purposes.

The UniProtKB/Swiss-Prot Tox-Prot program: A central hub of integrated venom protein data.

Animal toxins are of interest to a wide range of scientists, due to their numerous applications in pharmacology, neurology, hematology, medicine, and drug research. This, and to a lesser extent the development of new performing tools in transcriptomics and proteomics, has led to an increase in toxin discovery. In this context, providing publicly available data on animal toxins has become essential. The UniProtKB/Swiss-Prot Tox-Prot program (http://www.uniprot.org/program/Toxins) plays a crucial role by providing such an access to venom protein sequences and functions from all venomous species. This program has up to now curated more than 5000 venom proteins to the high-quality standards of UniProtKB/Swiss-Prot (release 2012_02). Proteins targeted by these toxins are also available in the knowledgebase. This paper describes in details the type of information provided by UniProtKB/Swiss-Prot for toxins, as well as the structured format of the knowledgebase.

Evolution of the correlation between expression divergence and protein divergence in mammals.

Divergence of protein sequences and gene expression patterns are two fundamental mechanisms that generate organismal diversity. Here, we have used genome and transcriptome data from eight mammals and one bird to study the positive correlation of these two processes throughout mammalian evolution. We demonstrate that the correlation is stable over time and most pronounced in neural tissues, which indicates that it is the result of strong negative selection. The correlation is not driven by genes with specific functions and may instead best be viewed as an evolutionary default state, which can nevertheless be evaded by certain gene types. In particular, genes with developmental and neural functions are skewed toward changes in gene expression, consistent with selection against pleiotropic effects associated with changes in protein sequences. Surprisingly, we find that the correlation between expression divergence and protein divergence is not explained by between-gene variation in expression level, tissue specificity, protein connectivity, or other investigated gene characteristics, suggesting that it arises independently of these gene traits. The selective constraints on protein sequences and gene expression patterns also fluctuate in a coordinate manner across phylogenetic branches: We find that gene-specific changes in the rate of protein evolution in a specific mammalian lineage tend to be accompanied by similar changes in the rate of expression evolution. Taken together, our findings highlight many new aspects of the correlation between protein divergence and expression divergence, and attest to its role as a fundamental property of mammalian genome evolution.

HAMAP in 2015: updates to the protein family classification and annotation system.

HAMAP (High-quality Automated and Manual Annotation of Proteins-available at http://hamap.expasy.org/) is a system for the automatic classification and annotation of protein sequences. HAMAP provides annotation of the same quality and detail as UniProtKB/Swiss-Prot, using manually curated profiles for protein sequence family classification and expert curated rules for functional annotation of family members. HAMAP data and tools are made available through our website and as part of the UniRule pipeline of UniProt, providing annotation for millions of unreviewed sequences of UniProtKB/TrEMBL. Here we report on the growth of HAMAP and updates to the HAMAP system since our last report in the NAR Database Issue of 2013. We continue to augment HAMAP with new family profiles and annotation rules as new protein families are characterized and annotated in UniProtKB/Swiss-Prot; the latest version of HAMAP (as of 3 September 2014) contains 1983 family classification profiles and 1998 annotation rules (up from 1780 and 1720). We demonstrate how the complex logic of HAMAP rules allows for precise annotation of individual functional variants within large homologous protein families. We also describe improvements to our web-based tool HAMAP-Scan which simplify the classification and annotation of sequences, and the incorporation of an improved sequence-profile search algorithm.

MAMOT: hidden Markov modeling tool.

Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot

OpenFluDB, a database for human and animal influenza virus.

Although research on influenza lasted for more than 100 years, it is still one of the most prominent diseases causing half a million human deaths every year. With the recent observation of new highly pathogenic H5N1 and H7N7 strains, and the appearance of the influenza pandemic caused by the H1N1 swine-like lineage, a collaborative effort to share observations on the evolution of this virus in both animals and humans has been established. The OpenFlu database (OpenFluDB) is a part of this collaborative effort. It contains genomic and protein sequences, as well as epidemiological data from more than 27,000 isolates. The isolate annotations include virus type, host, geographical location and experimentally tested antiviral resistance. Putative enhanced pathogenicity as well as human adaptation propensity are computed from protein sequences. Each virus isolate can be associated with the laboratories that collected, sequenced and submitted it. Several analysis tools including multiple sequence alignment, phylogenetic analysis and sequence similarity maps enable rapid and efficient mining. The contents of OpenFluDB are supplied by direct user submission, as well as by a daily automatic procedure importing data from public repositories. Additionally, a simple mechanism facilitates the export of OpenFluDB records to GenBank. This resource has been successfully used to rapidly and widely distribute the sequences collected during the recent human swine flu outbreak and also as an exchange platform during the vaccine selection procedure. Database URL: http://openflu.vital-it.ch.

EGASP: the human ENCODE Genome Annotation Assessment Project.

BACKGROUND: We present the results of EGASP, a community experiment to assess the state-of-the-art in genome annotation within the ENCODE regions, which span 1% of the human genome sequence. The experiment had two major goals: the assessment of the accuracy of computational methods to predict protein coding genes; and the overall assessment of the completeness of the current human genome annotations as represented in the ENCODE regions. For the computational prediction assessment, eighteen groups contributed gene predictions. We evaluated these submissions against each other based on a 'reference set' of annotations generated as part of the GENCODE project. These annotations were not available to the prediction groups prior to the submission deadline, so that their predictions were blind and an external advisory committee could perform a fair assessment. RESULTS: The best methods had at least one gene transcript correctly predicted for close to 70% of the annotated genes. Nevertheless, the multiple transcript accuracy, taking into account alternative splicing, reached only approximately 40% to 50% accuracy. At the coding nucleotide level, the best programs reached an accuracy of 90% in both sensitivity and specificity. Programs relying on mRNA and protein sequences were the most accurate in reproducing the manually curated annotations. Experimental validation shows that only a very small percentage (3.2%) of the selected 221 computationally predicted exons outside of the existing annotation could be verified. CONCLUSION: This is the first such experiment in human DNA, and we have followed the standards established in a similar experiment, GASP1, in Drosophila melanogaster. We believe the results presented here contribute to the value of ongoing large-scale annotation projects and should guide further experimental methods when being scaled up to the entire human genome sequence.

Multiplication of an ancestral gene encoding secreted fungalysin preceded species differentiation in the dermatophytes Trichophyton and Microsporum.

Dermatophytes are human and animal pathogenic fungi which cause cutaneous infections and grow exclusively in the stratum corneum, nails and hair. In a culture medium containing soy proteins as sole nitrogen source a substantial proteolytic activity was secreted by Trichophyton rubrum, Trichophyton mentagrophytes and Microsporum canis. This proteolytic activity was 55-75 % inhibited by o-phenanthroline, attesting that metalloproteases were secreted by all three species. Using a consensus probe constructed on previously characterized genes encoding metalloproteases (MEP) of the M36 fungalysin family in Aspergillus fumigatus, Aspergillus oryzae and M. canis, a five-member MEP family was isolated from genomic libraries of T. rubrum, T. mentagrophytes and M. canis. A phylogenetic analysis of genomic and protein sequences revealed a robust tree consisting of five main clades, each of them including a MEP sequence type from each dermatophyte species. Each MEP type was remarkably conserved across species (72-97 % amino acid sequence identity). The tree topology clearly indicated that the multiplication of MEP genes in dermatophytes occurred prior to species divergence. In culture medium containing soy proteins as a sole nitrogen source secreted Meps accounted for 19-36 % of total secreted protein extracts; characterization of protein bands by proteolysis and mass spectrometry revealed that the three dermatophyte species secreted two Meps (Mep3 and Mep4) encoded by orthologous genes.

Taxogenomics of the order Chlamydiales.

Bacterial classification is a long-standing problem for taxonomists and species definition itself is constantly debated among specialists. The classification of strict intracellular bacteria such as members of the order Chlamydiales mainly relies on DNA- or protein-based phylogenetic reconstructions because these organisms exhibit few phenotypic differences and are difficult to culture. The availability of full genome sequences allows the comparison of the performance of conserved protein sequences to reconstruct Chlamydiales phylogeny. This approach permits the identification of markers that maximize the phylogenetic signal and the robustness of the inferred tree. In this study, a set of 424 core proteins was identified and concatenated to reconstruct a reference species tree. Although individual protein trees present variable topologies, we detected only few cases of incongruence with the reference species tree, which were due to horizontal gene transfers. Detailed analysis of the phylogenetic information of individual protein sequences (i) showed that phylogenies based on single randomly chosen core proteins are not reliable and (ii) led to the identification of twenty taxonomically highly reliable proteins, allowing the reconstruction of a robust tree close to the reference species tree. We recommend using these protein sequences to precisely classify newly discovered isolates at the family, genus and species levels.

Importance of sequences adjacent to the terminal tripeptide in the import of a peroxisomal Candida tropicalis protein in plant peroxisomes.

The peroxisome targeting signal (PTS) required for import of the rat acyl-CoA oxidase (AOX; EC 1.3.3.6) and the Candida tropicalis multifunctional protein (MFP) in plant peroxisomes was assessed in transgenic Arabidopsis thaliana (L.) Heynh. The native rat AOX accumulated in peroxisomes in A. thaliana cotyledons and targeting was dependent on the presence of the C-terminal tripeptide S-K-L. In contrast, the native C. tropicalis MFP, containing the consensus PTS sequence A-K-I was not targeted to plant peroxisomes. Modification of the carboxy terminus to the S-K-L tripeptide also failed to deliver the MFP to peroxisomes while addition of the last 34 amino acids of the Brassica napus isocitrate lyase, containing the terminal tripeptide S-R-M, enabled import of the fusion protein into peroxisomes. These results underline the influence of the amino acids adjacent to the terminal tripeptide of the C. tropicalis MFP on peroxisomal targeting, even in the context of a protein having a consensus PTS sequence S-K-L.

Identifying protein-coding genes in genomic sequences.

The vast majority of the biology of a newly sequenced genome is inferred from the set of encoded proteins. Predicting this set is therefore invariably the first step after the completion of the genome DNA sequence. Here we review the main computational pipelines used to generate the human reference protein-coding gene sets.