RepSeq – A database of amino acid repeats present in lower eukaryotic pathogens

By Daniel P. Depledge, Ryan P. J. Lower, Deborah F. Smith. BMC Bioinformatics, 2007

787 citations recorded by the source corpus.

BackgroundAmino acid repeat-containing proteins have a broad range of functions and their identification is of relevance to many experimental biologists. In human-infective protozoan parasites (such as the Kinetoplastid and Plasmodium species), they are implicated in immune evasion and have been shown to influence virulence and pathogenicity. RepSeq http://repseq.gugbe.com is a new database of amino acid repeat-containing proteins found in lower eukaryotic pathogens. The RepSeq database is accessed via a web-based application which also provides links to related online tools and databases for further analyses.ResultsThe RepSeq algorithm typically identifies more than 98% of repeat-containing proteins and is capable of identifying both perfect and mismatch repeats. The proportion of proteins that contain repeat elements varies greatly between different families and even species (3–35% of the total protein content). The most common motif type is the Sequence Repeat Region (SRR) – a repeated motif containing multiple different amino acid types. Proteins containing Single Amino Acid Repeats (SAARs) and Di-Peptide Repeats (DPRs) typically account for 0.5–1.0% of the total protein number. Notable exceptions are P. falciparum and D. discoideum, in which 33.67% and 34.28% respectively of the predicted proteomes consist of repeat-containing proteins. These numbers are due to large insertions of low complexity single and multi-codon repeat regions.ConclusionThe RepSeq database provides a repository for repeat-containing proteins found in parasitic protozoa. The database allows for both individual and cross-species proteome analyses and also allows users to upload sequences of interest for analysis by the RepSeq algorithm. Identification of repeat-containing proteins provides researchers with a defined subset of proteins which can be analysed by expression profiling and functional characterisation, thereby facilitating study of pathogenicity and virulence factors in the parasitic protozoa. While primarily designed for kinetoplastid work, the RepSeq algorithm and database retain full functionality when used to analyse other species.

Subfields: Epidemiology, Molecular Biology, Parasitology

View Paper: https://www.semanticscholar.org/paper/97078e8522451e4f839d93f822e913cf257c08a5

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In Epidemiology

1. Feng Zhang
2. Rodolphe Barrangou
3. Sylvain Moineau
4. Josiane E. Garneau
5. J. van der Oost
6. H. Deveau
7. Jennifer A. Doudna

In Molecular Biology

1. Rodolphe Barrangou
2. Feng Zhang
3. Jennifer A. Doudna
4. L. Marraffini
5. J. van der Oost
6. Philippe Horvath
7. Sylvain Moineau
8. E. Charpentier

In Parasitology

1. Rodolphe Barrangou
2. Sylvain Moineau
3. Josiane E. Garneau
4. J. van der Oost
5. H. Deveau

Citations in the corpus

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