RESUMO
One of the most reliable methods for protein function annotation is to transfer experimentally known functions from orthologous proteins in other organisms. Most methods for identifying orthologs operate on a subset of organisms with a completely sequenced genome, and treat proteins as single-domain units. However, it is well known that proteins are often made up of several independent domains, and there is a wealth of protein sequences from genomes that are not completely sequenced. A comprehensive set of protein domain families is found in the Pfam database. We wanted to apply orthology detection to Pfam families, but first some issues needed to be addressed. First, orthology detection becomes impractical and unreliable when too many species are included. Second, shorter domains contain less information. It is therefore important to assess the quality of the orthology assignment and avoid very short domains altogether. We present a database of orthologous protein domains in Pfam called HOPS: Hierarchical grouping of Orthologous and Paralogous Sequences. Orthology is inferred in a hierarchic system of phylogenetic subgroups using ortholog bootstrapping. To avoid the frequent errors stemming from horizontally transferred genes in bacteria, the analysis is presently limited to eukaryotic genes. The results are accessible in the graphical browser NIFAS, a Java tool originally developed for analyzing phylogenetic relations within Pfam families. The method was tested on a set of curated orthologs with experimentally verified function. In comparison to tree reconciliation with a complete species tree, our approach finds significantly more orthologs in the test set. Examples for investigating gene fusions and domain recombination using HOPS are given.
Assuntos
Bases de Dados de Proteínas , Animais , Proteínas de Arabidopsis/genética , Proteínas de Caenorhabditis elegans/genética , Proteínas de Drosophila/genética , Evolução Molecular , Humanos , Filogenia , Estrutura Terciária de Proteína/genética , Recombinação Genética/genética , Proteínas de Saccharomyces cerevisiae/genética , Homologia de Sequência de AminoácidosRESUMO
SUMMARY: Orthostrapper is a program that calculates orthology support values for pairs of sequences in a multiple alignment (Storm and Sonnhammer, Bioinformatics, 18, 92-99, 2002). Here we present OrthoGUI, a web interface and display tool for Orthostrapper analysis. OrthoGUI visualizes the Orthostrapper output in both tabular and tree representations, and can also apply a clustering algorithm to identify groups of multiple orthologs, which are indicated by colour coding. AVAILABILITY: http://www.cgb.ki.se/OrthoGUI CONTACT: erik.sonnhammer@cgb.ki.se
Assuntos
Gráficos por Computador , Bases de Dados de Proteínas , Armazenamento e Recuperação da Informação/métodos , Alinhamento de Sequência/métodos , Análise de Sequência de Proteína/métodos , Homologia de Sequência , Transportadores de Cassetes de Ligação de ATP/genética , Transportadores de Cassetes de Ligação de ATP/metabolismo , Trifosfato de Adenosina/metabolismo , Algoritmos , Apresentação de Dados , Humanos , Internet , Ligação Proteica/genética , Sensibilidade e Especificidade , Especificidade da Espécie , Interface Usuário-ComputadorRESUMO
MOTIVATION: Orthologous proteins in different species are likely to have similar biochemical function and biological role. When annotating a newly sequenced genome by sequence homology, the most precise and reliable functional information can thus be derived from orthologs in other species. A standard method of finding orthologs is to compare the sequence tree with the species tree. However, since the topology of phylogenetic tree is not always reliable one might get incorrect assignments. RESULTS: Here we present a novel method that resolves this problem by analyzing a set of bootstrap trees instead of the optimal tree. The frequency of orthology assignments in the bootstrap trees can be interpreted as a support value for the possible orthology of the sequences. Our method is efficient enough to analyze data in the scale of whole genomes. It is implemented in Java and calculates orthology support levels for all pairwise combinations of homologous sequences of two species. The method was tested on simulated datasets and on real data of homologous proteins.
