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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
Published on: June 23, 2012
Efficient and cost effective population resequencing by pooling and in-solution hybridization
Vikas Bansal1, Ryan Tewhey, Emily M Leproust
1Scripps Genomic Medicine, Scripps Translational Science Institute, La Jolla, California, United States of America. vbansal@scripps.edu
Plos One
|April 12, 2011
Summary
This study demonstrates that pooled DNA sequencing with targeted capture is a cost-effective method for identifying rare genetic variants in large populations. The approach accurately detects single nucleotide variants and short insertions/deletions, crucial for disease risk assessment.
Area of Science:
- Genomics
- Population Genetics
- Molecular Biology
Background:
- High-throughput sequencing of targeted genomic loci is vital for assessing rare variant contributions to disease risk.
- Population sequencing studies require cost-efficient methodologies to analyze large datasets.
Purpose of the Study:
- To evaluate the feasibility of in-solution hybridization-based target capture on pooled DNA samples.
- To enable cost-efficient population sequencing for disease risk variant identification.
Main Methods:
- Pooled sequencing of 100 HapMap samples across ~600 kb using Illumina GAIIx.
- Development and application of an accurate variant calling method for pooled sequence data.
- In-solution hybridization-based target capture on pooled DNA samples.
Main Results:
- Accurate identification of single nucleotide variants (SNVs) with a false discovery rate <1%.
- Accurate detection of short insertion/deletion variants.
- Detection of 97.2% of total variants and 93.6% of variants with <5% frequency at 30-fold coverage per individual.
- High correlation (r > 0.995) between pooled data and HapMap genotype data for SNV allele frequencies.
Conclusions:
- In-solution target capture on pooled DNA is a feasible and cost-efficient approach for population sequencing.
- The developed variant calling method accurately identifies common and rare variants in pooled sequencing data.
- This methodology supports large-scale genetic studies for disease risk evaluation.
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