The Eimeria transcript DB: an integrated resource for annotated transcripts of protozoan parasites of the genus Eimeria

Abstract

Parasites of the genus Eimeria infect a wide range of vertebrate hosts, including chickens. We have recently reported a comparative analysis of the transcriptomes of Eimeria acervulina, Eimeria maxima and Eimeria tenella, integrating ORESTES data produced by our group and publicly available Expressed Sequence Tags (ESTs). All cDNA reads have been assembled, and the reconstructed transcripts have been submitted to a comprehensive functional annotation pipeline. Additional studies included orthology assignment across apicomplexan parasites and clustering analyses of gene expression profiles among different developmental stages of the parasites. To make all this body of information publicly available, we constructed the Eimeria Transcript Database (EimeriaTDB), a web repository that provides access to sequence data, annotation and comparative analyses. Here, we describe the web interface, available sequence data sets and query tools implemented on the site. The main goal of this work is to offer a public repository of sequence and functional annotation data of reconstructed transcripts of parasites of the genus Eimeria. We believe that EimeriaTDB will represent a valuable and complementary resource for the Eimeria scientific community and for those researchers interested in comparative genomics of apicomplexan parasites. Database URL: http://www.coccidia.icb.usp.br/eimeriatdb/

Figure 1

Screenshots of some resources available at EimeriaTDB. The home page (A) contains tabs redirecting to specific service pages. The search page (B) allows querying the database using sequence IDs or keywords. Queries can be restricted to specific Eimeria species or according to different types of evidence. The annotation page (C) provides access to sequence and annotation data, orthology analysis within apicomplexan organisms and a link to the respective GBrowse (D) screen. When available, expression data are displayed in a graphic (E).

Figure 2

Evidence-based annotation. Each annotation page provides specific links to different bioinformatics analyses (A), including sequence mapping onto KEGG pathways (B), BLAST similarity (C) and InterPro motif searching (D). Global analyses include functional classification into KEGG Metabolic Pathway (E) and KOG orthology (F) classes.