Abstract
Cell lines are the foundation for much of the fundamental research into the mechanisms underlying normal biologic processes and disease mechanisms. It is estimated that 15%–35% of human cell lines are misidentified or contaminated, resulting in a huge waste of resources and publication of false or misleading data. Here we evaluate a panel of 96 single-nucleotide polymorphism (SNP) assays utilizing Fluidigm microfluidics technology for authentication and sex determination of human cell lines. The SNPtrace Panel was tested on 907 human cell lines. Pairwise comparison of these data show the SNPtrace Panel discriminated among identical, related and unrelated pairs of samples with a high degree of confidence, equivalent to short tandem repeat (STR) profiling. We also compared annotated sex calls with those determined by the SNPtrace Panel, STR and Illumina SNP arrays, revealing a high number of male samples are identified as female due to loss of the Y chromosome. Finally we assessed the sensitivity of the SNPtrace Panel to detect intra-human cross-contamination, resulting in detection of as little as 2% contaminating cell population. In conclusion, this study has generated a database of SNP fingerprints for 907 cell lines used in biomedical research and provides a reliable, fast, and economic alternative to STR profiling which can be applied to any human cell line or tissue sample.
Highlights
Human cell lines and patient-derived tissue are an essential resource for biomedical research
We report the performance of the assay in comparison to short tandem repeat (STR) profiling based on ability to discriminate related and unrelated samples, sex calls and intra-human cross-contamination and we provide a database of single-nucleotide polymorphism (SNP) calls for 907 individual cell lines
With one exception, synonymous/derivative pairs of cell lines were highly similar and could be identified by the SNPtrace Panel (Fig. 1A)
Summary
Human cell lines and patient-derived tissue are an essential resource for biomedical research. As the need for these resources grows in industry and academia, so have examples of biosample mix-ups [1,2,3,4,5]. The simple fact is that human error leads to mistakes which, unless stringent quality controls are in place, can result in costly mistakes, false and invalid data and retractions of publications [6,7,8,9,10]. Serial biopsies, matched normal and diseased tissue or PLOS ONE | DOI:10.1371/journal.pone.0116218. All data included in this manuscript is shared freely. Cell lines used in this manuscript all have associated MTAs or licenses which may restrict Genentech's ability to distribute cell lines. If the MTA/license prevents sharing the line can be obtained from the original supplier
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