A practical, bioinformatic workflow system for large data sets generated by next-generation sequencing

Department of Veterinary Science, The University of Melbourne, 250 Princes Highway, Werribee, Victoria 3030, Australia.
Nucleic Acids Research (Impact Factor: 9.11). 09/2010; 38(17):e171. DOI: 10.1093/nar/gkq667
Source: PubMed


Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic workflow system, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This workflow system provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This system is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism.

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    • "These results showed a slight imbalance in favor of the male sequences. This tendency has been previously reported in the sequences of other organisms such as Acipenser fulvescens (Hale et al., 2010), where 3332 transcripts were expressed in females and 4008 were expressed in males; Oesophagostomum dentatum (Cantacessi et al., 2010), where 3451 transcripts were found in females and 10,344 in males; and Haliotis rufescens (Valenzuela-Muñoz et al., 2012) where 1296 and 2254 transcripts were found to be significantly expressed in female and male tissues, respectively. Gene ontology annotations for the contigs revealed an important difference in the number of expressed transcripts between male and female individuals, where there was an overall predominance of female over male transcripts. "
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    • "We re-visited previously published Roche/454 data from C. oncophora[27], O. flexuosa[28], O. ostertagi[27], T. circumcincta[29], and T. colubriformis[25], re-screening and re-assembling with up-to-date, cDNA specific assembly software and our optimized parameters. Additional life cycle stages were sequenced and added to available datasets from A. caninum[30], D. viviparus[23], N. americanus[26], and O. dentatum[24] prior to assembly (see Additional file 1: Table S1). Together, these nine species represent a diverse array of parasitic nematodes, in terms of biology as well as phylogeny. "
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    • " [32-34,39,40,42-45] and analysed herein included known TIMP amino acid sequences from Homo sapiens (GenBank accession numbers XP_010392.1, NP_003246.1, "
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