Evading the annotation bottleneck: using sequence similarity to search non-sequence gene data

Comparative Genomics Analysis Provides New Insight Into Molecular Basis of Stomatal Movement in Kalanchoë fedtschenkoi

CO₂ uptake and water loss in plants are regulated by microscopic pores on the surface of leaves, called stomata. This enablement of gas exchange by the opening and closing of stomata is one of the most essential processes in plant photosynthesis and transpiration, affecting water-use efficiency (WUE) and thus drought susceptibility. In plant species with crassulacean acid metabolism (CAM) photosynthesis, diel stomatal movement pattern is inverted relative to C₃ and C₄ photosynthesis species, resulting in much higher WUE and drought tolerance. However, little is known about the molecular basis of stomatal movement in CAM species. The goal of this study is to identify candidate genes that could play a role in stomatal movement in an obligate CAM species, Kalanchoë fedtschenkoi. By way of a text-mining approach, proteins were identified in various plant species, spanning C₃, C₄, and CAM photosynthetic types, which are orthologous to proteins known to be involved in stomatal movement. A comparative analysis of diel time-course gene expression data was performed between K. fedtschenkoi and two C₃ species (i.e., Arabidopsis thaliana and Solanum lycopersicum) to identify differential gene expression between the dusk and dawn phases of the 24-h cycle. A rescheduled catalase gene known to be involved in stomatal movement was identified, suggesting a role for H₂O₂ in CAM-like stomatal movement. Overall, these results provide new insights into the molecular regulation of stomatal movement in CAM plants, facilitating genetic improvement of drought resistance in agricultural crops through manipulation of stomata-related genes.

PaperBLAST: Text Mining Papers for Information about Homologs

With the recent explosion of genome sequencing data, there are now millions of uncharacterized proteins. If a scientist becomes interested in one of these proteins, it can be very difficult to find information as to its likely function. Often a protein whose sequence is similar, and which is likely to have a similar function, has been studied already, but this information is not available in any database. To help find articles about similar proteins, PaperBLAST searches the full text of scientific articles for protein identifiers or gene identifiers, and it links these articles to protein sequences. Then, given a protein of interest, it can quickly find similar proteins in its database by using standard software (BLAST), and it can show snippets of text from relevant papers. We hope that PaperBLAST will make it easier for biologists to predict proteins’ functions.

Large-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources (Swiss-Prot, GeneRIF, and EcoCyc) that link protein sequences to scientific articles. PaperBLAST’s database includes over 700,000 scientific articles that mention over 400,000 different proteins. Given a protein of interest, PaperBLAST quickly finds similar proteins that are discussed in the literature and presents snippets of text from relevant articles or from the curators. PaperBLAST is available at http://papers.genomics.lbl.gov/.

IMPORTANCE With the recent explosion of genome sequencing data, there are now millions of uncharacterized proteins. If a scientist becomes interested in one of these proteins, it can be very difficult to find information as to its likely function. Often a protein whose sequence is similar, and which is likely to have a similar function, has been studied already, but this information is not available in any database. To help find articles about similar proteins, PaperBLAST searches the full text of scientific articles for protein identifiers or gene identifiers, and it links these articles to protein sequences. Then, given a protein of interest, it can quickly find similar proteins in its database by using standard software (BLAST), and it can show snippets of text from relevant papers. We hope that PaperBLAST will make it easier for biologists to predict proteins’ functions.

PubServer: literature searches by homology

PubServer, available at http://pubserver.burnham.org/, is a tool to automatically collect, filter and analyze publications associated with groups of homologous proteins. Protein entries in databases such as Entrez Protein database at NCBI contain information about publications associated with a given protein. The scope of these publications varies a lot: they include studies focused on biochemical functions of individual proteins, but also reports from genome sequencing projects that introduce tens of thousands of proteins. Collecting and analyzing publications related to sets of homologous proteins help in functional annotation of novel protein families and in improving annotations of well-studied protein families or individual genes. However, performing such collection and analysis manually is a tedious and time-consuming process. PubServer automatically collects identifiers of homologous proteins using PSI-Blast, retrieves literature references from corresponding database entries and filters out publications unlikely to contain useful information about individual proteins. It also prepares simple vocabulary statistics from titles, abstracts and MeSH terms to identify the most frequently occurring keywords, which may help to quickly identify common themes in these publications. The filtering criteria applied to collected publications are user-adjustable. The results of the server are presented as an interactive page that allows re-filtering and different presentations of the output.

Xenbase: expansion and updates of the Xenopus model organism database

Xenbase (http://www.xenbase.org) is a model organism database that provides genomic, molecular, cellular and developmental biology content to biomedical researchers working with the frog, Xenopus and Xenopus data to workers using other model organisms. As an amphibian Xenopus serves as a useful evolutionary bridge between invertebrates and more complex vertebrates such as birds and mammals. Xenbase content is collated from a variety of external sources using automated and semi-automated pipelines then processed via a combination of automated and manual annotation. A link-matching system allows for the wide variety of synonyms used to describe biological data on unique features, such as a gene or an anatomical entity, to be used by the database in an equivalent manner. Recent updates to the database include the Xenopus laevis genome, a new Xenopus tropicalis genome build, epigenomic data, collections of RNA and protein sequences associated with genes, more powerful gene expression searches, a community and curated wiki, an extensive set of manually annotated gene expression patterns and a new database module that contains data on over 700 antibodies that are useful for exploring Xenopus cell and developmental biology.

Databases of gene expression in Xenopus development

Gene expression data for Xenopus are collected and curated in diverse forms and locations. The intention of this chapter is to give the reader a guide to the publicly accessible databases where these data can be found and an idea of the current scope and limitations of the data in these resources. Instructions are given on how to access and interpret the data provided by the NCBI Gene database, Xenbase, and the Xenopus full-length EST, quickImage, and Xenmark databases.

GeneReporter--sequence-based document retrieval and annotation

Summary: GeneReporter is a web tool that reports functional information and relevant literature on a protein-coding sequence of interest. Its purpose is to support both manual genome annotation and document retrieval. PubMed references corresponding to a sequence are detected by the extraction of query words from UniProt entries of homologous sequences. Data on protein families, domains, potential cofactors, structure, function, cellular localization, metabolic contribution and corresponding DNA binding sites complement the information on a given gene product of interest.

Availability and implementation: GeneReporter is available at http://www.genereporter.tu-bs.de. The web site integrates databases and analysis tools as SOAP-based web services from the EBI (European Bioinformatics Institute) and NCBI (National Center for Biotechnology Information).

Contact:i.retter@tu-bs.de; ida.retter@helmholtz-hzi.de

Supplementary information:Supplementary data are available at Bioinformatics online.

Xenbase: gene expression and improved integration

Xenbase (www.xenbase.org), the model organism database for Xenopus laevis and X. (Silurana) tropicalis, is the principal centralized resource of genomic, development data and community information for Xenopus research. Recent improvements include the addition of the literature and interaction tabs to gene catalog pages. New content has been added including a section on gene expression patterns that incorporates image data from the literature, large scale screens and community submissions. Gene expression data are integrated into the gene catalog via an expression tab and is also searchable by multiple criteria using an expression search interface. The gene catalog has grown to contain over 15 000 genes. Collaboration with the European Xenopus Research Center (EXRC) has resulted in a stock center section with data on frog lines supplied by the EXRC. Numerous improvements have also been made to search and navigation. Xenbase is also the source of the Xenopus Anatomical Ontology and the clearinghouse for Xenopus gene nomenclature.

Database of queryable gene expression patterns for Xenopus

The precise localization of gene expression within the developing embryo, and how it changes over time, is one of the most important sources of information for elucidating gene function. As a searchable resource, this information has up until now been largely inaccessible to the Xenopus community. Here, we present a new database of Xenopus gene expression patterns, queryable by specific location or region in the embryo. Pattern matching can be driven either from an existing in situ image, or from a user-defined pattern based on development stage schematic diagrams. The data are derived from the work of a group of 21 Xenopus researchers over a period of 4 days. We used a novel, rapid manual annotation tool, XenMARK, which exploits the ability of the human brain to make the necessary distortions in transferring data from the in situ images to the standard schematic geometry. Developmental Dynamics 238:1379-1388, 2009. (c) 2009 Wiley-Liss, Inc.