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Related Experiment Video

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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

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Published on: June 23, 2012

Multi-sample pooling and illumina genome analyzer sequencing methods to determine gene sequence variation for

Rebecca L Margraf1, Jacob D Durtschi, Shale Dames

  • 1ARUP Institute for Clinical and Experimental Pathology, Salt Lake City, Utah 84108, USA. rebecca.margraf@aruplab.com

Journal of Biomolecular Techniques : JBT
|September 3, 2010
PubMed
Summary

Multisample pooling for Illumina Genome Analyzer (GA) sequencing enables reliable detection of genetic variants. Up to 30 samples can be pooled to accurately identify singleton variants, crucial for molecular assay design.

Keywords:
IlluminaRETmassively parallel sequencingnext generation sequencing

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Accurate determination of sequence variation is crucial for molecular assay design and clinical interpretation.
  • Multisample pooling strategies are being explored to enhance the efficiency of next-generation sequencing.
  • The RET proto-oncogene serves as a model for investigating genetic variations.

Purpose of the Study:

  • To investigate the feasibility and reliability of multisample pooling for Illumina Genome Analyzer (GA) sequencing.
  • To determine the optimal number of samples that can be pooled for accurate variant detection.
  • To establish a method for detecting singleton variants in pooled sequencing data.

Main Methods:

  • Ten samples with known RET proto-oncogene variants were equimolarly pooled and sequenced using Illumina GA.
  • Sanger sequencing was used for initial variant identification and comparison.
  • Sequencing data underwent quality screening, read trimming, and analysis using established variant detection methods and a novel subtractive correction method.

Main Results:

  • All Sanger-identified variants, including 23 singleton variants, were detected in the pooled sequencing data.
  • Singleton variants were identified at an average allele frequency of 5.17%, significantly above background error rates (1.25%).
  • Computational modeling indicated that pooling up to 30 samples could reliably detect singleton variants with a minimum of 1% variant reads.

Conclusions:

  • Multisample pooling is a viable strategy for Illumina GA sequencing, enhancing the cost-effectiveness of genetic variation analysis.
  • Pooling up to 30 samples allows for reliable detection of singleton variants, supporting clinical applications.
  • The developed methods and findings contribute to improved molecular assay design and clinical test interpretation.