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Getting the most out of parasitic helminth transcriptomes using HelmDB: Implications for biology and biotechnology

Mangiola, Stefano and Young, Neil D. and Korhonen, Pasi and Mondal, Alinda and Scheerlinck, Jean-Pierre and Sternberg, Paul W. and Cantacessi, Cinzia and Hall, Ross S. and Jex, Aaron R. and Gasser, Robin B. (2013) Getting the most out of parasitic helminth transcriptomes using HelmDB: Implications for biology and biotechnology. Biotechnology Advances, 31 (8). pp. 1109-1119. ISSN 0734-9750. doi:10.1016/j.biotechadv.2012.12.004.

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Compounded by a massive global food shortage, many parasitic diseases have a devastating, long-term impact on animal and human health and welfare worldwide. Parasitic helminths (worms) affect the health of billions of animals. Unlocking the systems biology of these neglected pathogens will underpin the design of new and improved interventions against them. Currently, the functional annotation of genomic and transcriptomic sequence data for socio-economically important parasitic worms relies almost exclusively on comparative bioinformatic analyses using model organism- and other databases. However, many genes and gene products of parasitic helminths (often > 50%) cannot be annotated using this approach, because they are specific to parasites and/or do not have identifiable homologs in other organisms for which sequence data are available. This inability to fully annotate transcriptomes and predicted proteomes is a major challenge and constrains our understanding of the biology of parasites, interactions with their hosts and of parasitism and the pathogenesis of disease on a molecular level. In the present article, we compiled transcriptomic data sets of key, socioeconomically important parasitic helminths, and constructed and validated a curated database, called HelmDB ( We demonstrate how this database can be used effectively for the improvement of functional annotation by employing data integration and clustering. Importantly, HelmDB provides a practical and user-friendly toolkit for sequence browsing and comparative analyses among divergent helminth groups (including nematodes and trematodes), and should be readily adaptable and applicable to a wide range of other organisms. This web-based, integrative database should assist ‘systems biology’ studies of parasitic helminths, and the discovery and prioritization of novel drug and vaccine targets. This focus provides a pathway toward developing new and improved approaches for the treatment and control of parasitic diseases, with the potential for important biotechnological outcomes.

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Sternberg, Paul W.0000-0002-7699-0173
Additional Information:© 2012 Elsevier Inc. Received 11 October 2012. Received in revised form 8 December 2012. Accepted 13 December 2012. Available online 21 December 2012. This research was supported largely through grants from the Australian Research Council (ARC) and the National Health and Medical Research Council (NHMRC) (RBG). Other support from the Australian Academy of Science, the Australian–American Fulbright Commission, Melbourne Water Corporation and the Victorian Life Sciences Computation Initiative (VLSCI) is gratefully acknowledged. SM is the grateful recipient of scholarships from the University of Melbourne and a special scholarship from VLSCI. NDY holds an Early Career Research Fellowship (ECRF) from (NHMRC). PWS is an investigator with the Howard Hughes Medical Institute (HHMI).
Funding AgencyGrant Number
Australian Research Council (ARC)UNSPECIFIED
National Health and Medical Research Council (NHMRC)UNSPECIFIED
Australian Academy of ScienceUNSPECIFIED
Australian–American Fulbright CommissionUNSPECIFIED
Melbourne Water CorporationUNSPECIFIED
Victorian Life Sciences Computation Initiative (VLSCI)UNSPECIFIED
Howard Hughes Medical Institute (HHMI)UNSPECIFIED
University of MelbourneUNSPECIFIED
Subject Keywords:Parasitic helminths (nematode and trematode); Systems biology; Transcriptomics; Annotation-improvement; Genomics; Bioinformatics
Issue or Number:8
Record Number:CaltechAUTHORS:20140214-073210680
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Official Citation:Stefano Mangiola, Neil D. Young, Pasi Korhonen, Alinda Mondal, Jean-Pierre Scheerlinck, Paul W. Sternberg, Cinzia Cantacessi, Ross S. Hall, Aaron R. Jex, Robin B. Gasser, Getting the most out of parasitic helminth transcriptomes using HelmDB: Implications for biology and biotechnology, Biotechnology Advances, Volume 31, Issue 8, December 2013, Pages 1109-1119, ISSN 0734-9750, (
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:43825
Deposited By: Ruth Sustaita
Deposited On:18 Feb 2014 17:36
Last Modified:10 Nov 2021 16:43

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