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

Abstract

BackgroundContamination 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.ResultsUsing 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.ConclusionsWe 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 FIT, 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 materialThe online version of this article (doi:10.1186/s12915-017-0366-6) contains supplementary material, which is available to authorized users.

Contaminations in (meta)genome data: An open issue for the scientific community

“…Currently, the rapid advances of the next‐generation sequencing (NGS) technologies have increased the sequencing throughput and lowered sequencing costs, allowing a wide range of large‐scale genomic studies. However, although the quality of sequence data has been improved, the methods and protocols are still not perfect and errors inevitably occur . Indeed, it is known that data from massive sequencing projects based on NGS technologies (e.g., Illumina, 454 and Ion Torrent) contain contaminant sequence reads, difficult to detect and remove, that are lost in the myriad of reads from the target sample .…”

“…NGS library construction protocols involve one or multiple polymerase chain reaction (PCR) steps that are particularly sensitive to contamination. In fact, initially small amounts of foreign DNA can accidentally be amplified by PCR contaminating the downstream data sets . This issue becomes particularly serious when the target sample is derived from a non‐model species lacking a reference genome, so that genuine sequence reads cannot be easily identified by similarity .…”

“…In fact, initially small amounts of foreign DNA can accidentally be amplified by PCR contaminating the downstream data sets . This issue becomes particularly serious when the target sample is derived from a non‐model species lacking a reference genome, so that genuine sequence reads cannot be easily identified by similarity . Also, data obtained by Sanger sequencing, a complementary method generally used to narrow down and confirm the NGS results in clinical settings, can be affected by laboratory contaminants …”

“…To limit these problems, several integrated software tools have recently been developed to discriminate between the sequences of the organism of interest and contaminating sequences introduced during the manipulation of the sample and the preparation of the genomic libraries . These algorithms usually identify the contaminant sequences by specific criteria and infer the taxonomic source of the contaminant using a reference database …”

“…In order to prevent researchers from drawing wrong information from reference genome databases, an overview of tools able to detect bacterial contaminations, contaminations of human origin, mitochondrial contaminations of ancient DNA, and cross contaminations have been examined.…”