InParanoid 6: eukaryotic ortholog clusters with inparalogs

Comparative functional analysis of the Caenorhabditis elegans and Drosophila melanogaster proteomes

The nematode Caenorhabditis elegans is a popular model system in genetics, not least because a majority of human disease genes are conserved in C. elegans. To generate a comprehensive inventory of its expressed proteome, we performed extensive shotgun proteomics and identified more than half of all predicted C. elegans proteins. This allowed us to confirm and extend genome annotations, characterize the role of operons in C. elegans, and semiquantitatively infer abundance levels for thousands of proteins. Furthermore, for the first time to our knowledge, we were able to compare two animal proteomes (C. elegans and Drosophila melanogaster). We found that the abundances of orthologous proteins in metazoans correlate remarkably well, better than protein abundance versus transcript abundance within each organism or transcript abundances across organisms; this suggests that changes in transcript abundance may have been partially offset during evolution by opposing changes in protein abundance.

Proteins are the active players that execute the genetic program of a cell, and their levels and interactions are precisely controlled. Routinely monitoring thousands of proteins is difficult, as they can be present at vastly different abundances, come with various sizes, shapes, and charge, and have a more complex alphabet of twenty “letters,” in contrast to the four letters of the genome itself. Here, we used mass spectrometry to extensively characterize the proteins of a popular model organism, the nematode Caenorhabditis elegans. Together with previous data from the fruit fly Drosophila melanogaster, this allows us to compare the protein levels of two animals on a global scale. Surprisingly, we find that individual protein abundance is highly conserved between the two species. So, although worms and flies look very different, they need similar amounts of each conserved, orthologous protein. Because many C. elegans and D. melanogaster proteins also have counterparts in humans, our results suggest that similar rules may apply to our own proteins.

A quantitative comparison of two animal proteomes shows a striking correlation of protein abundance levels, a better correlation than transcript levels. Are the latter more variable during evolution?

GoGene: gene annotation in the fast lane

High-throughput screens such as microarrays and RNAi screens produce huge amounts of data. They typically result in hundreds of genes, which are often further explored and clustered via enriched GeneOntology terms. The strength of such analyses is that they build on high-quality manual annotations provided with the GeneOntology. However, the weakness is that annotations are restricted to process, function and location and that they do not cover all known genes in model organisms. GoGene addresses this weakness by complementing high-quality manual annotation with high-throughput text mining extracting co-occurrences of genes and ontology terms from literature. GoGene contains over 4 000 000 associations between genes and gene-related terms for 10 model organisms extracted from more than 18 000 000 PubMed entries. It does not cover only process, function and location of genes, but also biomedical categories such as diseases, compounds, techniques and mutations. By bringing it all together, GoGene provides the most recent and most complete facts about genes and can rank them according to novelty and importance. GoGene accepts keywords, gene lists, gene sequences and protein sequences as input and supports search for genes in PubMed, EntrezGene and via BLAST. Since all associations of genes to terms are supported by evidence in the literature, the results are transparent and can be verified by the user. GoGene is available at http://gopubmed.org/gogene.

COFECO: composite function annotation enriched by protein complex data

COFECO is a web-based tool for a composite annotation of protein complexes, KEGG pathways and Gene Ontology (GO) terms within a class of genes and their orthologs under study. Widely used functional enrichment tools using GO and KEGG pathways create large list of annotations that make it difficult to derive consolidated information and often include over-generalized terms. The interrelationship of annotation terms can be more clearly delineated by integrating the information of physically interacting proteins with biological pathways and GO terms. COFECO has the following advanced characteristics: (i) The composite annotation sets of correlated functions and cellular processes for a given gene set can be identified in a more comprehensive and specified way by the employment of protein complex data together with GO and KEGG pathways as annotation resources. (ii) Orthology based integrative annotations among different species complement the defective annotations in an individual genome and provide the information of evolutionary conserved correlations. (iii) A term filtering feature enables users to collect the specified annotations enriched with selected function terms. (iv) A cross-comparison of annotation results between two different datasets is possible. In addition, COFECO provides a web-based GO hierarchical viewer and KEGG pathway viewer where the enrichment results can be summarized and further explored. COFECO is freely accessible at http://piech.kaist.ac.kr/cofeco.

How confident can we be that orthologs are similar, but paralogs differ?

Homologous genes are classified into orthologs and paralogs, depending on whether they arose by speciation or duplication. It is widely assumed that orthologs share similar functions, whereas paralogs are expected to diverge more from each other. But does this assumption hold up on further examination? We present evidence that orthologs and paralogs are not so different in either their evolutionary rates or their mechanisms of divergence. We emphasize the importance of appropriately designed studies to test models of gene evolution between orthologs and between paralogs. Thus, functional change between orthologs might be as common as between paralogs, and future studies should be designed to test the impact of duplication against this alternative model.

Systematic definition of protein constituents along the major polarization axis reveals an adaptive reuse of the polarization machinery in pheromone-treated budding yeast

Polarizing cells extensively restructure cellular components in a spatially and temporally coupled manner along the major axis of cellular extension. Budding yeast are a useful model of polarized growth, helping to define many molecular components of this conserved process. Besides budding, yeast cells also differentiate upon treatment with pheromone from the opposite mating type, forming a mating projection (the ‘shmoo’) by directional restructuring of the cytoskeleton, localized vesicular transport and overall reorganization of the cytosol. To characterize the proteomic localization changes accompanying polarized growth, we developed and implemented a novel cell microarray-based imaging assay for measuring the spatial redistribution of a large fraction of the yeast proteome, and applied this assay to identify proteins localized along the mating projection following pheromone treatment. We further trained a machine learning algorithm to refine the cell imaging screen, identifying additional shmoo-localized proteins. In all, we identified 74 proteins that specifically localize to the mating projection, including previously uncharacterized proteins (Ycr043c, Ydr348c, Yer071c, Ymr295c, and Yor304c-a) and known polarization complexes such as the exocyst. Functional analysis of these proteins, coupled with quantitative analysis of individual organelle movements during shmoo formation, suggests a model in which the basic machinery for cell polarization is generally conserved between processes forming the bud and the shmoo, with a distinct subset of proteins used only for shmoo formation. The net effect is a defined ordering of major organelles along the polarization axis, with specific proteins implicated at the proximal growth tip.

Upon sensing mating pheromone, budding yeast cells form a mating projection (the ‘shmoo’) that serves as a model for polarized cell growth, involving cytoskeletal/cytosolic restructuring and directed vesicular transport. We developed a cell microarray-based imaging assay for measuring localization of the yeast proteome during polarized growth. We find major organelles ordered along the polarization axis, localize 74 proteins to the growth tip, and observe adaptive reuse of general polarization machinery.

Revisiting the missing protein-coding gene catalog of the domestic dog

Background

Among mammals for which there is a high sequence coverage, the whole genome assembly of the dog is unique in that it predicts a low number of protein-coding genes, ~19,000, compared to the over 20,000 reported for other mammalian species. Of particular interest are the more than 400 of genes annotated in primates and rodent genomes, but missing in dog.

Results

Using over 14,000 orthologous genes between human, chimpanzee, mouse rat and dog, we built multiple pairwise synteny maps to infer short orthologous intervals that were targeted for characterizing the canine missing genes. Based on gene prediction and a functionality test using the ratio of replacement to silent nucleotide substitution rates (d_N/d_S), we provide compelling structural and functional evidence for the identification of 232 new protein-coding genes in the canine genome and 69 gene losses, characterized as undetected gene or pseudogenes. Gene loss phyletic pattern analysis using ten species from chicken to human allowed us to characterize 28 canine-specific gene losses that have functional orthologs continuously from chicken or marsupials through human, and 10 genes that arose specifically in the evolutionary lineage leading to rodent and primates.

Conclusion

This study demonstrates the central role of comparative genomics for refining gene catalogs and exploring the evolutionary history of gene repertoires, particularly as applied for the characterization of species-specific gene gains and losses.

PIPs: human protein-protein interaction prediction database

The PIPs database (http://www.compbio.dundee.ac.uk/www-pips) is a resource for studying protein-protein interactions in human. It contains predictions of >37,000 high probability interactions of which >34,000 are not reported in the interaction databases HPRD, BIND, DIP or OPHID. The interactions in PIPs were calculated by a Bayesian method that combines information from expression, orthology, domain co-occurrence, post-translational modifications and sub-cellular location. The predictions also take account of the topology of the predicted interaction network. The web interface to PIPs ranks predictions according to their likelihood of interaction broken down by the contribution from each information source and with easy access to the evidence that supports each prediction. Where data exists in OPHID, HPRD, DIP or BIND for a protein pair this is also reported in the output tables returned by a search. A network browser is included to allow convenient browsing of the interaction network for any protein in the database. The PIPs database provides a new resource on protein-protein interactions in human that is straightforward to browse, or can be exploited completely, for interaction network modelling.

KAGIANA: an excel-based tool for retrieving summary information on Arabidopsis genes

Various public databases provide Arabidopsis gene information via the internet. It is useful to abstract information obtained from such databases. We have developed the KAGIANA tool, which allows a user to retrieve summary information obtained from selective databases and to access pages for a gene of interest in those databases. The tool is based on Microsoft Excel and provides several macro programs for gene expression analyses. It can assist plant biologists in accessing omics information for plant biology. The KAGIANA tool is freely available at http://pmnedo.kazusa.or.jp/kagiana/.

Phylogenetic and functional assessment of orthologs inference projects and methods

Accurate genome-wide identification of orthologs is a central problem in comparative genomics, a fact reflected by the numerous orthology identification projects developed in recent years. However, only a few reports have compared their accuracy, and indeed, several recent efforts have not yet been systematically evaluated. Furthermore, orthology is typically only assessed in terms of function conservation, despite the phylogeny-based original definition of Fitch. We collected and mapped the results of nine leading orthology projects and methods (COG, KOG, Inparanoid, OrthoMCL, Ensembl Compara, Homologene, RoundUp, EggNOG, and OMA) and two standard methods (bidirectional best-hit and reciprocal smallest distance). We systematically compared their predictions with respect to both phylogeny and function, using six different tests. This required the mapping of millions of sequences, the handling of hundreds of millions of predicted pairs of orthologs, and the computation of tens of thousands of trees. In phylogenetic analysis or in functional analysis where high specificity is required, we find that OMA and Homologene perform best. At lower functional specificity but higher coverage level, OrthoMCL outperforms Ensembl Compara, and to a lesser extent Inparanoid. Lastly, the large coverage of the recent EggNOG can be of interest to build broad functional grouping, but the method is not specific enough for phylogenetic or detailed function analyses. In terms of general methodology, we observe that the more sophisticated tree reconstruction/reconciliation approach of Ensembl Compara was at times outperformed by pairwise comparison approaches, even in phylogenetic tests. Furthermore, we show that standard bidirectional best-hit often outperforms projects with more complex algorithms. First, the present study provides guidance for the broad community of orthology data users as to which database best suits their needs. Second, it introduces new methodology to verify orthology. And third, it sets performance standards for current and future approaches.

ERGR: An ethanol-related gene resource

Over the last decade rapid progress has been made in the study of ethanol-related traits including alcohol abuse and dependence, and behavioral responses to ethanol in both humans and animal models. To collect, curate, integrate these results so as to make them easily accessible and interpretable for researchers, we developed ERGR, a comprehensive ethanol-related gene resource. We collected and curated more than 30 large-scale data sets including linkage, association and microarray gene expression from the literature and 21 mouse QTLs from public databases. At present, the ERGR deposits ethanol-related information of ∼7000 genes from five organisms: human (3311), mouse (2129), rat (679), fly (614) and worm (228). ERGR provides gene annotations and orthologs, detailed gene study information (e.g. fold changes of gene expression, P-values), and both the text and BLAST searches. Moreover, ERGR has data integration tools such as for data union and intersection, and candidate gene selection based on evidence in multiple datasets or organisms. The ERGR database is evolving with new data releases. More functions will also be added. ERGR has a user-friendly web interface with browse and search functions at multiple levels. It is freely available at http://bioinfo.vipbg.vcu.edu/ERGR/.

SynBlast: assisting the analysis of conserved synteny information

Motivation

In the last years more than 20 vertebrate genomes have been sequenced, and the rate at which genomic DNA information becomes available is rapidly accelerating. Gene duplication and gene loss events inherently limit the accuracy of orthology detection based on sequence similarity alone. Fully automated methods for orthology annotation do exist but often fail to identify individual members in cases of large gene families, or to distinguish missing data from traceable gene losses. This situation can be improved in many cases by including conserved synteny information.

Results

Here we present the SynBlast pipeline that is designed to construct and evaluate local synteny information. SynBlast uses the genomic region around a focal reference gene to retrieve candidates for homologous regions from a collection of target genomes and ranks them in accord with the available evidence for homology. The pipeline is intended as a tool to aid high quality manual annotation in particular in those cases where automatic procedures fail. We demonstrate how SynBlast is applied to retrieving orthologous and paralogous clusters using the vertebrate Hox and ParaHox clusters as examples.

Software

The SynBlast package written in Perl is available under the GNU General Public License at .

Wormnet: a crystal ball for Caenorhabditis elegans

An integrated gene network for Caenorhabditis elegans encompasses most protein-coding genes.

An integrated gene network for Caenorhabditis elegans using data from multiple genome-wide screens encompasses most protein-coding genes and can accurately predict their phenotypes.