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Optimized PCR-based Detection of Mycoplasma
Published on: June 20, 2011
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Mycoplasma contamination in the 1000 Genomes Project
1Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK.
Biodata Mining
|May 30, 2014
Summary
Database corruption is a significant issue in bioinformatics, potentially impacting public data integrity. Our study found at least 7% of The Thousand Genomes Project samples show evidence of Mycoplasma contamination.
Area of Science:
- Bioinformatics and Genomics
- Microbial Contamination Analysis
Background:
- In silico biology relies heavily on public data, making data integrity crucial.
- While laboratory contamination is recognized, database corruption is less understood.
- Publicly available genomic datasets may harbor undetected contaminants.
Purpose of the Study:
- To investigate the prevalence of database corruption in large-scale genomic projects.
- To assess the impact of potential contaminants on human genome reference data.
Main Methods:
- Analysis of 50 billion next-generation DNA sequences from The Thousand Genomes Project.
- Comparison of sequences against published reference genomes, including human (GRCh37.p5).
- Utilized NCBI BLAST for sequence identification and quality assessment.
Main Results:
- Numerous sequences from The Thousand Genomes Project matched Mycoplasma genomes.
- These Mycoplasma sequences were absent from the human reference genome.
- High-quality, high-entropy sequences confirmed Mycoplasma presence, distinct from human DNA.
Conclusions:
- A significant portion of The Thousand Genomes Project samples are contaminated with Mycoplasma.
- At least 7% of analyzed samples exhibit detectable contamination.
- Highlights the need for rigorous quality control in public genomic databases.
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