title: Unexpected cross-species contamination in genome sequencing projects.
abstract: The raw data from a genome sequencing project sometimes contains DNA from contaminating organisms, which may be introduced during sample collection or sequence preparation. In some instances, these contaminants remain in the sequence even after assembly and deposition of the genome into public databases. As a result, searches of these databases may yield erroneous and confusing results. We used efficient microbiome analysis software to scan the draft assembly of domestic cow, Bos taurus, and identify 173 small contigs that appeared to derive from microbial contaminants. In the course of verifying these findings, we discovered that one genome, Neisseria gonorrhoeae TCDC-NG08107, although putatively a complete genome, contained multiple sequences that actually derived from the cow and sheep genomes. Our findings illustrate the need to carefully validate findings of anomalous DNA that rely on comparisons to either draft or finished genomes.
authors.affiliation: Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University , Baltimore, MD , USA ; Department of Computer Science, Brown University , Providence, RI , USA.
authors.forename: Samier
authors.initials: S
authors.lastname: Merchant
authors.affiliation: Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University , Baltimore, MD , USA ; Department of Computer Science, Johns Hopkins University , USA.
authors.forename: Derrick E
authors.initials: DE
authors.lastname: Wood
authors.affiliation: Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University , Baltimore, MD , USA ; Department of Computer Science, Johns Hopkins University , USA ; Department of Biomedical Engineering, Johns Hopkins University , USA.
authors.forename: Steven L
authors.initials: SL
authors.lastname: Salzberg
keywords: Bioinformatics; DNA sequencing; Genome assembly; Genomics; Microbiome; Sequence analysis