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Biotechnol Adv. 2016 Sep-Oct;34(5):663-686. doi: 10.1016/j.biotechadv.2016.03.001. Epub 2016 Mar 5.

Making sense of genomes of parasitic worms: Tackling bioinformatic challenges.

Author information

1
Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, Victoria 3010, Australia. Electronic address: pasi.korhonen@unimelb.edu.au.
2
Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, Victoria 3010, Australia.
3
Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, Victoria 3010, Australia. Electronic address: robinbg@unimelb.edu.au.

Abstract

Billions of people and animals are infected with parasitic worms (helminths). Many of these worms cause diseases that have a major socioeconomic impact worldwide, and are challenging to control because existing treatment methods are often inadequate. There is, therefore, a need to work toward developing new intervention methods, built on a sound understanding of parasitic worms at molecular level, the relationships that they have with their animal hosts and/or the diseases that they cause. Decoding the genomes and transcriptomes of these parasites brings us a step closer to this goal. The key focus of this article is to critically review and discuss bioinformatic tools used for the assembly and annotation of these genomes and transcriptomes, as well as various post-genomic analyses of transcription profiles, biological pathways, synteny, phylogeny, biogeography and the prediction and prioritisation of drug target candidates. Bioinformatic pipelines implemented and established recently provide practical and efficient tools for the assembly and annotation of genomes of parasitic worms, and will be applicable to a wide range of other parasites and eukaryotic organisms. Future research will need to assess the utility of long-read sequence data sets for enhanced genomic assemblies, and develop improved algorithms for gene prediction and post-genomic analyses, to enable comprehensive systems biology explorations of parasitic organisms.

KEYWORDS:

Annotation; Assembly; Bioinformatics; Genome; Parasitic worms

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