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Contamination detection in sequencing studies using the mitochondrial phylogeny.

ABSTRACT: Within-species contamination is a major issue in sequencing studies, especially for mitochondrial studies. Contamination can be detected by analyzing the nuclear genome or by inspecting polymorphic sites in the mitochondrial genome (mtDNA). Existing methods using the nuclear genome are computationally expensive, and no appropriate tool for detecting sample contamination in large-scale mtDNA data sets is available. Here we present haplocheck, a tool that requires only the mtDNA to detect contamination in both targeted mitochondrial and whole-genome sequencing studies. Our in silico simulations and amplicon mixture experiments indicate that haplocheck detects mtDNA contamination accurately and is independent of the phylogenetic distance within a sample mixture. By applying haplocheck to The 1000 Genomes Project Consortium data, we further evaluate the application of haplocheck as a fast proxy tool for nDNA-based contamination detection using the mtDNA and identify the mitochondrial copy number within a mixture as a critical component for the overall accuracy. The haplocheck tool is available both as a command-line tool and as a cloud web service producing interactive reports that facilitates the navigation through the phylogeny of contaminated samples.

SUBMITTER: Weissensteiner H

PROVIDER: S-EPMC7849411 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundContamination of reagents and cross contamination across samples is a long-recognized issue in molecular biology laboratories. While often innocuous, contamination can lead to inaccurate results. Cantalupo et al., for example, found HeLa-derived human papillomavirus 18 (H-HPV18) in several of The Cancer Genome Atlas (TCGA) RNA-sequencing samples. This work motivated us to assess a greater number of samples and determine the origin of possible contaminations using viral sequences. To detect viruses with high specificity, we developed the publicly available workflow, VirDetect, that detects virus and laboratory vector sequences in RNA-seq samples. We applied VirDetect to 9143 RNA-seq samples sequenced at one TCGA sequencing center (28/33 cancer types) over 5 years.ResultsWe confirmed that H-HPV18 was present in many samples and determined that viral transcripts from H-HPV18 significantly co-occurred with those from xenotropic mouse leukemia virus-related virus (XMRV). Using laboratory metadata and viral transcription, we determined that the likely contaminant was a pool of cell lines known as the "common reference", which was sequenced alongside TCGA RNA-seq samples as a control to monitor quality across technology transitions (i.e. microarray to GAII to HiSeq), and to link RNA-seq to previous generation microarrays that standardly used the "common reference". One of the cell lines in the pool was a laboratory isolate of MCF-7, which we discovered was infected with XMRV; another constituent of the pool was likely HeLa cells.ConclusionsAltogether, this indicates a multi-step contamination process. First, MCF-7 was infected with an XMRV. Second, this infected cell line was added to a pool of cell lines, which contained HeLa. Finally, RNA from this pool of cell lines contaminated several TCGA tumor samples most-likely during library construction. Thus, these human tumors with H-HPV or XMRV reads were likely not infected with H-HPV 18 or XMRV.

Project description:Malaria is a vector-borne disease that is a great burden on the poorest and most marginalized communities of the tropical and subtropical world. Approximately 41 species of Anopheline mosquitoes can effectively spread species of Plasmodium parasites that cause human malaria. Proposing a natural classification for the subfamily Anophelinae has been a continuous effort, addressed using both morphology and DNA sequence data. The monophyly of the genus Anopheles, and phylogenetic placement of the genus Bironella, subgenera Kerteszia, Lophopodomyia and Stethomyia within the subfamily Anophelinae, remain in question. To understand the classification of Anophelinae, we inferred the phylogeny of all three genera (Anopheles, Bironella, Chagasia) and major subgenera by analysing the amino acid sequences of the 13 protein coding genes of 150 newly sequenced mitochondrial genomes of Anophelinae and 18 newly sequenced Culex species as outgroup taxa, supplemented with 23 mitogenomes from GenBank. Our analyses generally place genus Bironella within the genus Anopheles, which implies that the latter as it is currently defined is not monophyletic. With some inconsistencies, Bironella was placed within the major clade that includes Anopheles, Cellia, Kerteszia, Lophopodomyia, Nyssorhynchus and Stethomyia, which were found to be monophyletic groups within Anophelinae. Our findings provided robust evidence for elevating the monophyletic groupings Kerteszia, Lophopodomyia, Nyssorhynchus and Stethomyia to genus level; genus Anopheles to include subgenera Anopheles, Baimaia, Cellia and Christya; Anopheles parvus to be placed into a new genus; Nyssorhynchus to be elevated to genus level; the genus Nyssorhynchus to include subgenera Myzorhynchella and Nyssorhynchus; Anopheles atacamensis and Anopheles pictipennis to be transferred from subgenus Nyssorhynchus to subgenus Myzorhynchella; and subgenus Nyssorhynchus to encompass the remaining species of Argyritarsis and Albimanus Sections.

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Contamination detection in sequencing studies using the mitochondrial phylogeny.

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