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Human biosample authentication using the high-throughput, cost-effective SNPtrace(TM) system.

Liang-Chu MM, Yu M, Haverty PM, Koeman J, Ziegle J, Lee M, Bourgon R, Neve RM - PLoS ONE (2015)

Bottom Line: Cell lines are the foundation for much of the fundamental research into the mechanisms underlying normal biologic processes and disease mechanisms.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Discovery Oncology, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, United States of America.

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.

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Related in: MedlinePlus

Detection of cell line cross-contamination by the SNPtrace Panel.DNA from two different normal human samples (A) and tumor cell lines (B) were mixed as indicated at the specified ratios, and analyzed by the SNPtrace Panel. Tables A and B include the calculated percent identity for each sample pair, and percent identities highlighted in grey indicate a non-identical call (<90%). Plots to the right of each table show the overlay of percent identities for reciprocal mixes.
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pone.0116218.g002: Detection of cell line cross-contamination by the SNPtrace Panel.DNA from two different normal human samples (A) and tumor cell lines (B) were mixed as indicated at the specified ratios, and analyzed by the SNPtrace Panel. Tables A and B include the calculated percent identity for each sample pair, and percent identities highlighted in grey indicate a non-identical call (<90%). Plots to the right of each table show the overlay of percent identities for reciprocal mixes.

Mentions: Cell line cross-contamination is an acknowledged and major problem in biomedical sciences [10], and STRs have been reported to reliably detect a contaminant at 5–10% [41]. To test the sensitivity of the SNPtrace Panel to detect cell contaminants, we performed cell mixing experiments (see Materials and Methods). Initially, these were performed on normal (diploid) human DNA, and the percent identity for SNP calls was calculated between the mixes and both the parental samples. Using an identity score cutoff of 90% to call samples as identical, the SNPtrace Panel could reliably detect 5% contamination in three independent mixes. For diploid cells, identity was not affected by the sample chosen, as reciprocal mixes resulted in similar identity scores with each individual sample (Fig. 2A). We performed the same test on three pairs of tumor cell lines and found that sensitivity ranged from 2%-10% depending on the ratio of the samples, and equivalent reciprocal mixes were often not detected with the same degree of sensitivity. For example, MCF-7 was only detected at 50% contamination (a 50:50 mix ratio in the MCF-7:LOX-IMVI mixture), whereas just 2% contamination of LOX-IMVI was detected (a 98:2 mix ratio in the MCF-7:LOX-IMVI mixture) (Fig. 2B). Similar results were observed using STR analysis of these samples (data not shown). Our best interpretation of this data is that the degree of aneuploidy and copy number at any given locus may influence the sensitivity of the assay and thus make contamination by a high copy number cell line easier to detect than contamination by a line with fewer copies.


Human biosample authentication using the high-throughput, cost-effective SNPtrace(TM) system.

Liang-Chu MM, Yu M, Haverty PM, Koeman J, Ziegle J, Lee M, Bourgon R, Neve RM - PLoS ONE (2015)

Detection of cell line cross-contamination by the SNPtrace Panel.DNA from two different normal human samples (A) and tumor cell lines (B) were mixed as indicated at the specified ratios, and analyzed by the SNPtrace Panel. Tables A and B include the calculated percent identity for each sample pair, and percent identities highlighted in grey indicate a non-identical call (<90%). Plots to the right of each table show the overlay of percent identities for reciprocal mixes.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4340925&req=5

pone.0116218.g002: Detection of cell line cross-contamination by the SNPtrace Panel.DNA from two different normal human samples (A) and tumor cell lines (B) were mixed as indicated at the specified ratios, and analyzed by the SNPtrace Panel. Tables A and B include the calculated percent identity for each sample pair, and percent identities highlighted in grey indicate a non-identical call (<90%). Plots to the right of each table show the overlay of percent identities for reciprocal mixes.
Mentions: Cell line cross-contamination is an acknowledged and major problem in biomedical sciences [10], and STRs have been reported to reliably detect a contaminant at 5–10% [41]. To test the sensitivity of the SNPtrace Panel to detect cell contaminants, we performed cell mixing experiments (see Materials and Methods). Initially, these were performed on normal (diploid) human DNA, and the percent identity for SNP calls was calculated between the mixes and both the parental samples. Using an identity score cutoff of 90% to call samples as identical, the SNPtrace Panel could reliably detect 5% contamination in three independent mixes. For diploid cells, identity was not affected by the sample chosen, as reciprocal mixes resulted in similar identity scores with each individual sample (Fig. 2A). We performed the same test on three pairs of tumor cell lines and found that sensitivity ranged from 2%-10% depending on the ratio of the samples, and equivalent reciprocal mixes were often not detected with the same degree of sensitivity. For example, MCF-7 was only detected at 50% contamination (a 50:50 mix ratio in the MCF-7:LOX-IMVI mixture), whereas just 2% contamination of LOX-IMVI was detected (a 98:2 mix ratio in the MCF-7:LOX-IMVI mixture) (Fig. 2B). Similar results were observed using STR analysis of these samples (data not shown). Our best interpretation of this data is that the degree of aneuploidy and copy number at any given locus may influence the sensitivity of the assay and thus make contamination by a high copy number cell line easier to detect than contamination by a line with fewer copies.

Bottom Line: Cell lines are the foundation for much of the fundamental research into the mechanisms underlying normal biologic processes and disease mechanisms.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Discovery Oncology, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, United States of America.

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.

Show MeSH
Related in: MedlinePlus