Abel Ureta-Vidal

The Ensembl genome database project

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of the human genome sequence, with confirmed gene predictions that have been integrated with external data sources, and is available as either an interactive web site or as flat files. It is also an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements from sequence analysis to data storage and visualisation. The Ensembl site is one of the leading sources of human genome sequence annotation and provided much of the analysis for publication by the international human genome project of the draft genome. The Ensembl system is being installed around the world in both companies and academic sites on machines ranging from supercomputers to laptops.

EnsemblCompara GeneTrees: Complete, duplication-aware phylogenetic trees in vertebrates

We have developed a comprehensive gene orientated phylogenetic resource, EnsemblCompara GeneTrees, based on a computational pipeline to handle clustering, multiple alignment, and tree generation, including the handling of large gene families. We developed two novel non-sequence-based metrics of gene tree correctness and benchmarked a number of tree methods. The TreeBeST method from TreeFam shows the best performance in our hands. We also compared this phylogenetic approach to clustering approaches for ortholog prediction, showing a large increase in coverage using the phylogenetic approach. All data are made available in a number of formats and will be kept up to date with the Ensembl project.

Ensembl 2002: accommodating comparative genomics

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of human, mouse and other genome sequences, available as either an interactive web site or as flat files. Ensembl also integrates manually annotated gene structures from external sources where available. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. These range from sequence analysis to data storage and visualisation and installations exist around the world in both companies and at academic sites. With both human and mouse genome sequences available and more vertebrate sequences to follow, many of the recent developments in Ensembl have focusing on developing automatic comparative genome analysis and visualisation.

Comparative genomics: genome-wide analysis in metazoan eukaryotes.

The increasing number of complete and nearly complete metazoan genome sequences provides a significant amount of material for large-scale comparative genomic analysis. Finding new effective methods to analyse such enormous datasets has been the object of intense research. Three main areas in comparative genomics have recently shown important developments: whole-genome alignment, gene prediction and regulatory-region prediction. Each of these areas improves the methods of deciphering long genomic sequences and uncovering what lies hidden in them.

TreeFam: 2008 Update

TreeFam (http://www.treefam.org) was developed to provide curated phylogenetic trees for all animal gene families, as well as orthologue and paralogue assignments. Release 4.0 of TreeFam contains curated trees for 1314 families and automatically generated trees for another 14 351 families. We have expanded TreeFam to include 25 fully sequenced animal genomes, as well as four genomes from plant and fungal outgroup species. We have also introduced more accurate approaches for automatically grouping genes into families, for building phylogenetic trees, and for inferring orthologues and paralogues. The user interface for viewing phylogenetic trees and family information has been improved. Furthermore, a new perl API lets users easily extract data from the TreeFam mysql database.

EMMA—mouse mutant resources for the international scientific community

The laboratory mouse is the premier animal model for studying human disease and thousands of mutants have been identified or produced, most recently through gene-specific mutagenesis approaches. High throughput strategies by the International Knockout Mouse Consortium (IKMC) are producing mutants for all protein coding genes. Generating a knock-out line involves huge monetary and time costs so capture of both the data describing each mutant alongside archiving of the line for distribution to future researchers is critical. The European Mouse Mutant Archive (EMMA) is a leading international network infrastructure for archiving and worldwide provision of mouse mutant strains. It operates in collaboration with the other members of the Federation of International Mouse Resources (FIMRe), EMMA being the European component. Additionally EMMA is one of four repositories involved in the IKMC, and therefore the current figure of 1700 archived lines will rise markedly. The EMMA database gathers and curates extensive data on each line and presents it through a user-friendly website. A BioMart interface allows advanced searching including integrated querying with other resources e.g. Ensembl. Other resources are able to display EMMA data by accessing our Distributed Annotation System server. EMMA database access is publicly available at http://www.emmanet.org.

eHive: An Artificial Intelligence workflow system for genomic analysis

BackgroundThe Ensembl project produces updates to its comparative genomics resources with each of its several releases per year. During each release cycle approximately two weeks are allocated to generate all the genomic alignments and the protein homology predictions. The number of calculations required for this task grows approximately quadratically with the number of species. We currently support 50 species in Ensembl and we expect the number to continue to grow in the future.ResultsWe present eHive, a new fault tolerant distributed processing system initially designed to support comparative genomic analysis, based on blackboard systems, network distributed autonomous agents, dataflow graphs and block-branch diagrams. In the eHive system a MySQL database serves as the central blackboard and the autonomous agent, a Perl script, queries the system and runs jobs as required. The system allows us to define dataflow and branching rules to suit all our production pipelines. We describe the implementation of three pipelines: (1) pairwise whole genome alignments, (2) multiple whole genome alignments and (3) gene trees with protein homology inference. Finally, we show the efficiency of the system in real case scenarios.ConclusionseHive allows us to produce computationally demanding results in a reliable and efficient way with minimal supervision and high throughput. Further documentation is available at: http://www.ensembl.org/info/docs/eHive/.