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Identification of foreign gene sequences by transcript filtering against the human genome

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Abstract

We have developed a computational subtraction approach to detect microbial causes for putative infectious diseases by filtering a set of human tissue–derived sequences against the human genome. We demonstrate the potential of this method by identifying sequences from known pathogens in established expressed–sequence tag libraries.

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Figure 1: Computational subtraction of the human transcriptome.

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Acknowledgements

We thank P. Vaglio, M. Vidal and W. Wong for assistance with computational platforms; R. DePinho, W. Kaelin, K. Polyak and M. Vidal for discussion and the National Cancer Institute (D.T.) and the Pew Scholars in the Biomedical Sciences (M.M.) for support. M.M. is a Claudia Adams Barr investigator.

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Author notes

  1. Griffin Weber and Jay Shendure: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Adult Oncology, Dana-Farber Cancer Institute, 44 Binney Street, Boston, 02115, Massachusetts, USA

    Griffin Weber, David M. Tanenbaum & Matthew Meyerson

  2. Department of Pathology, Harvard Medical School, Boston, 02115, Massachusetts, USA

    Griffin Weber, David M. Tanenbaum & Matthew Meyerson

  3. Decision Systems Group, Brigham and Women's Hospital, 75 Francis Street, Boston, 02115, Massachusetts, USA

    Griffin Weber

  4. Department of Genetics, Harvard Medical School, Boston, 02115, Massachusetts, USA

    Jay Shendure & George M. Church

Authors
  1. Griffin Weber
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  2. Jay Shendure
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  3. David M. Tanenbaum
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  4. George M. Church
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  5. Matthew Meyerson
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Correspondence to Matthew Meyerson.

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Weber, G., Shendure, J., Tanenbaum, D. et al. Identification of foreign gene sequences by transcript filtering against the human genome. Nat Genet 30, 141–142 (2002). https://doi.org/10.1038/ng818

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