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Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
Population-genetic properties of differentiated human copy-number polymorphisms
Catarina D Campbell1, Nick Sampas, Anya Tsalenko
1Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA.
American Journal of Human Genetics
|March 15, 2011
Summary
This study introduces a new method for discovering copy-number polymorphisms (CNPs), revealing population-specific genetic variants. These findings enhance our understanding of human diversity and disease associations.
Area of Science:
- Human Genetics
- Genomics
- Population Genetics
Background:
- Copy-number variants (CNVs) and copy-number polymorphisms (CNPs) are increasingly linked to human diseases.
- Existing methods for CNP discovery and genotyping face significant biases.
Purpose of the Study:
- To develop and validate a novel microarray-based method for CNP genotyping using single-channel intensity data.
- To identify and characterize population-differentiated CNPs, particularly in complex genomic regions.
Main Methods:
- Developed a microarray method utilizing single-channel intensity data for CNP genotyping.
- Benchmarked the method against sequencing read depth for accuracy.
- Analyzed 1495 CNPs across 487 diverse human DNA samples.
- Further characterized a subset of CNPs in 1876 samples from 62 populations.
Main Results:
- Successfully genotyped 1495 CNPs, including those in segmental duplications and non-reference sequences.
- Observed significant population differentiation for CNPs in segmental duplications and biallelic CNPs compared to SNPs.
- Identified population-differentiated structural variants in clinically relevant genes like OCLN.
Conclusions:
- The developed microarray method enables efficient CNP discovery and genotyping.
- CNPs, especially those not imputable from SNP data, show substantial population stratification and may have influenced human diversity and selection.
- These findings facilitate rapid testing of CNPs for disease association.
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