InParanoid 6: eukaryotic ortholog clusters with inparalogs

The InParanoid eukaryotic ortholog database (http://InParanoid.sbc.su.se/) has been updated to version 6 and is now based on 35 species. We collected all available ‘complete’ eukaryotic proteomes and Escherichia coli, and calculated ortholog groups for all 595 species pairs using the InParanoid program. This resulted in 2 642 187 pairwise ortholog groups in total. The orthology-based species relations are presented in an orthophylogram. InParanoid clusters contain one or more orthologs from each of the two species. Multiple orthologs in the same species, i.e. inparalogs, result from gene duplications after the species divergence. A new InParanoid website has been developed which is optimized for speed both for users and for updating the system. The XML output format has been improved for efficient processing of the InParanoid ortholog clusters

Domainoid: domain-oriented orthology inference

BACKGROUND: Orthology inference is normally based on full-length protein sequences. However, most proteins contain independently folding and recurring regions, domains. The domain architecture of a protein is vital for its function, and recombination events mean individual domains can have different evolutionary histories. It has previously been shown that orthologous proteins may differ in domain architecture, creating challenges for orthology inference methods operating on full-length sequences. We have developed Domainoid, a new tool aiming to overcome these challenges faced by full-length orthology methods by inferring orthology on the domain level. It employs the InParanoid algorithm on single domains separately, to infer groups of orthologous domains. RESULTS: This domain-oriented approach allows detection of discordant domain orthologs, cases where different domains on the same protein have different evolutionary histories. In addition to domain level analysis, protein level orthology based on the fraction of domains that are orthologous can be inferred. Domainoid orthology assignments were compared to those yielded by the conventional full-length approach InParanoid, and were validated in a standard benchmark. CONCLUSIONS: Our results show that domain-based orthology inference can reveal many orthologous relationships that are not found by full-length sequence approaches. AVAILABILITY: https://bitbucket.org/sonnhammergroup/domainoid/

InParanoid 7: new algorithms and tools for eukaryotic orthology analysis

The InParanoid project gathers proteomes of completely sequenced eukaryotic species plus Escherichia coli and calculates pairwise ortholog relationships among them. The new release 7.0 of the database has grown by an order of magnitude over the previous version and now includes 100 species and their collective 1.3 million proteins organized into 42.7 million pairwise ortholog groups. The InParanoid algorithm itself has been revised and is now both more specific and sensitive. Based on results from our recent benchmarking of low-complexity filters in homology assignment, a two-pass BLAST approach was developed that makes use of high-precision compositional score matrix adjustment, but avoids the alignment truncation that sometimes follows. We have also updated the InParanoid web site (http://InParanoid.sbc.su.se). Several features have been added, the response times have been improved and the site now sports a new, clearer look. As the number of ortholog databases has grown, it has become difficult to compare among these resources due to a lack of standardized source data and incompatible representations of ortholog relationships. To facilitate data exchange and comparisons among ortholog databases, we have developed and are making available two XML schemas: SeqXML for the input sequences and OrthoXML for the output ortholog clusters

siRNAdb: a database of siRNA sequences

Short interfering RNAs (siRNAs) are a popular method for gene-knockdown, acting by degrading the target mRNA. Before performing experiments it is invaluable to locate and evaluate previous knockdown experiments for the gene of interest. The siRNA database provides a gene-centric view of siRNA experimental data, including siRNAs of known efficacy and siRNAs predicted to be of high efficacy by a combination of methods. Linked to these sequences is information such as siRNA thermodynamic properties and the potential for sequence-specific off-target effects. The database enables the user to evaluate an siRNA's potential for inhibition and non-specific effects. The database is available at http://siRNA.cgb.ki.se

Comparative interactomics with Funcoup 2.0

FunCoup (http://FunCoup.sbc.su.se) is a database that maintains and visualizes global gene/protein networks of functional coupling that have been constructed by Bayesian integration of diverse high-throughput data. FunCoup achieves high coverage by orthology-based integration of data sources from different model organisms and from different platforms. We here present release 2.0 in which the data sources have been updated and the methodology has been refined. It contains a new data type Genetic Interaction, and three new species: chicken, dog and zebra fish. As FunCoup extensively transfers functional coupling information between species, the new input datasets have considerably improved both coverage and quality of the networks. The number of high-confidence network links has increased dramatically. For instance, the human network has more than eight times as many links above confidence 0.5 as the previous release. FunCoup provides facilities for analysing the conservation of subnetworks in multiple species. We here explain how to do comparative interactomics on the FunCoup website

The Pfam protein families database

Pfam is a comprehensive collection of protein domains and families, represented as multiple sequence alignments and as profile hidden Markov models. The current release of Pfam (22.0) contains 9318 protein families. Pfam is now based not only on the UniProtKB sequence database, but also on NCBI GenPept and on sequences from selected metagenomics projects. Pfam is available on the web from the consortium members using a new, consistent and improved website design in the UK (http://pfam.sanger.ac.uk/), the USA (http://pfam.janelia.org/) and Sweden (http://pfam.sbc.su.se/), as well as from mirror sites in France (http://pfam.jouy.inra.fr/) and South Korea (http://pfam.ccbb.re.kr/)

OrthoDB: the hierarchical catalog of eukaryotic orthologs

The concept of orthology is widely used to relate genes across different species using comparative genomics, and it provides the basis for inferring gene function. Here we present the web accessible OrthoDB database that catalogs groups of orthologous genes in a hierarchical manner, at each radiation of the species phylogeny, from more general groups to more fine-grained delineations between closely related species. We used a COG-like and Inparanoid-like ortholog delineation procedure on the basis of all-against-all Smith-Waterman sequence comparisons to analyze 58 eukaryotic genomes, focusing on vertebrates, insects and fungi to facilitate further comparative studies. The database is freely available at http://cegg.unige.ch/orthod

The Molecule Pages database

The UCSD-Nature Signaling Gateway Molecule Pages (http://www.signaling-gateway.org/molecule) provides essential information on more than 3800 mammalian proteins involved in cellular signaling. The Molecule Pages contain expert-authored and peer-reviewed information based on the published literature, complemented by regularly updated information derived from public data source references and sequence analysis. The expert-authored data includes both a full-text review about the molecule, with citations, and highly structured data for bioinformatics interrogation, including information on protein interactions and states, transitions between states and protein function. The expert-authored pages are anonymously peer reviewed by the Nature Publishing Group. The Molecule Pages data is present in an object-relational database format and is freely accessible to the authors, the reviewers and the public from a web browser that serves as a presentation layer. The Molecule Pages are supported by several applications that along with the database and the interfaces form a multi-tier architecture. The Molecule Pages and the Signaling Gateway are routinely accessed by a very large research community