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Patterns of cross-contamination in a multispecies population genomic project: detection, quantification, impact, and solutions

BACKGROUND: Contamination is a well-known but often neglected problem in molecular biology. Here, we investigated the prevalence of cross-contamination among 446 samples from 116 distinct species of animals, which were processed in the same laboratory and subjected to subcontracted transcriptome seq...

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Autores principales: Ballenghien, Marion, Faivre, Nicolas, Galtier, Nicolas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5370491/
https://www.ncbi.nlm.nih.gov/pubmed/28356154
http://dx.doi.org/10.1186/s12915-017-0366-6
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author Ballenghien, Marion
Faivre, Nicolas
Galtier, Nicolas
author_facet Ballenghien, Marion
Faivre, Nicolas
Galtier, Nicolas
author_sort Ballenghien, Marion
collection PubMed
description BACKGROUND: Contamination is a well-known but often neglected problem in molecular biology. Here, we investigated the prevalence of cross-contamination among 446 samples from 116 distinct species of animals, which were processed in the same laboratory and subjected to subcontracted transcriptome sequencing. RESULTS: Using cytochrome oxidase 1 as a barcode, we identified a minimum of 782 events of between-species contamination, with approximately 80% of our samples being affected. An analysis of laboratory metadata revealed a strong effect of the sequencing center: nearly all the detected events of between-species contamination involved species that were sent the same day to the same company. We introduce new methods to address the amount of within-species, between-individual contamination, and to correct for this problem when calling genotypes from base read counts. CONCLUSIONS: We report evidence for pervasive within-species contamination in this data set, and show that classical population genomic statistics, such as synonymous diversity, the ratio of non-synonymous to synonymous diversity, inbreeding coefficient F(IT), and Tajima’s D, are sensitive to this problem to various extents. Control analyses suggest that our published results are probably robust to the problem of contamination. Recommendations on how to prevent or avoid contamination in large-scale population genomics/molecular ecology are provided based on this analysis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12915-017-0366-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-53704912017-03-30 Patterns of cross-contamination in a multispecies population genomic project: detection, quantification, impact, and solutions Ballenghien, Marion Faivre, Nicolas Galtier, Nicolas BMC Biol Methodology Article BACKGROUND: Contamination is a well-known but often neglected problem in molecular biology. Here, we investigated the prevalence of cross-contamination among 446 samples from 116 distinct species of animals, which were processed in the same laboratory and subjected to subcontracted transcriptome sequencing. RESULTS: Using cytochrome oxidase 1 as a barcode, we identified a minimum of 782 events of between-species contamination, with approximately 80% of our samples being affected. An analysis of laboratory metadata revealed a strong effect of the sequencing center: nearly all the detected events of between-species contamination involved species that were sent the same day to the same company. We introduce new methods to address the amount of within-species, between-individual contamination, and to correct for this problem when calling genotypes from base read counts. CONCLUSIONS: We report evidence for pervasive within-species contamination in this data set, and show that classical population genomic statistics, such as synonymous diversity, the ratio of non-synonymous to synonymous diversity, inbreeding coefficient F(IT), and Tajima’s D, are sensitive to this problem to various extents. Control analyses suggest that our published results are probably robust to the problem of contamination. Recommendations on how to prevent or avoid contamination in large-scale population genomics/molecular ecology are provided based on this analysis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12915-017-0366-6) contains supplementary material, which is available to authorized users. BioMed Central 2017-03-29 /pmc/articles/PMC5370491/ /pubmed/28356154 http://dx.doi.org/10.1186/s12915-017-0366-6 Text en © Galtier et al. 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology Article
Ballenghien, Marion
Faivre, Nicolas
Galtier, Nicolas
Patterns of cross-contamination in a multispecies population genomic project: detection, quantification, impact, and solutions
title Patterns of cross-contamination in a multispecies population genomic project: detection, quantification, impact, and solutions
title_full Patterns of cross-contamination in a multispecies population genomic project: detection, quantification, impact, and solutions
title_fullStr Patterns of cross-contamination in a multispecies population genomic project: detection, quantification, impact, and solutions
title_full_unstemmed Patterns of cross-contamination in a multispecies population genomic project: detection, quantification, impact, and solutions
title_short Patterns of cross-contamination in a multispecies population genomic project: detection, quantification, impact, and solutions
title_sort patterns of cross-contamination in a multispecies population genomic project: detection, quantification, impact, and solutions
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5370491/
https://www.ncbi.nlm.nih.gov/pubmed/28356154
http://dx.doi.org/10.1186/s12915-017-0366-6
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