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Efficient identification of rare variants in large populations: deep re-sequencing the CRP locus in the CARDIA study
Effect sizes of many common single nucleotide polymorphisms identified in genome-wide association studies generally explain only a modest fraction of the total estimated heritability in a variety of traits. One hypothesis is that rare variants with larger effects might account for the missing herita...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3627584/ https://www.ncbi.nlm.nih.gov/pubmed/23408856 http://dx.doi.org/10.1093/nar/gkt092 |
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author | Chen, Christina T. L. McDavid, Andrew N. Kahsai, Orsalem J. Zebari, Ahmad S. Carlson, Christopher S. |
author_facet | Chen, Christina T. L. McDavid, Andrew N. Kahsai, Orsalem J. Zebari, Ahmad S. Carlson, Christopher S. |
author_sort | Chen, Christina T. L. |
collection | PubMed |
description | Effect sizes of many common single nucleotide polymorphisms identified in genome-wide association studies generally explain only a modest fraction of the total estimated heritability in a variety of traits. One hypothesis is that rare variants with larger effects might account for the missing heritability. Despite advances in sequencing technology, discovering rare variants in a large population is still economically challenging. Sequencing pooled samples can reduce the cost, but detecting rare variants and identifying individual carriers is difficult and requires additional experiments. To address these issues, we have developed a rare variant-detection algorithm V-Sieve to screen for rare alleles in pooled DNA samples which, in combination with a unique pooling strategy, is able to efficiently screen a candidate gene for idiosyncratic variants in thousands of samples. We applied this method to 2283 individuals, and identified >100 polymorphisms in the C-reactive protein locus at an allele frequency as low as 0.02%, with a positive predictive rate of 93%. We believe this algorithm will be useful in both screening for rare variants in genomic regions known to associate with particular phenotypes and in replicating rare variant associations identified in large-scale studies, such as exome re-sequencing projects. |
format | Online Article Text |
id | pubmed-3627584 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-36275842013-04-17 Efficient identification of rare variants in large populations: deep re-sequencing the CRP locus in the CARDIA study Chen, Christina T. L. McDavid, Andrew N. Kahsai, Orsalem J. Zebari, Ahmad S. Carlson, Christopher S. Nucleic Acids Res Methods Online Effect sizes of many common single nucleotide polymorphisms identified in genome-wide association studies generally explain only a modest fraction of the total estimated heritability in a variety of traits. One hypothesis is that rare variants with larger effects might account for the missing heritability. Despite advances in sequencing technology, discovering rare variants in a large population is still economically challenging. Sequencing pooled samples can reduce the cost, but detecting rare variants and identifying individual carriers is difficult and requires additional experiments. To address these issues, we have developed a rare variant-detection algorithm V-Sieve to screen for rare alleles in pooled DNA samples which, in combination with a unique pooling strategy, is able to efficiently screen a candidate gene for idiosyncratic variants in thousands of samples. We applied this method to 2283 individuals, and identified >100 polymorphisms in the C-reactive protein locus at an allele frequency as low as 0.02%, with a positive predictive rate of 93%. We believe this algorithm will be useful in both screening for rare variants in genomic regions known to associate with particular phenotypes and in replicating rare variant associations identified in large-scale studies, such as exome re-sequencing projects. Oxford University Press 2013-04 2013-02-12 /pmc/articles/PMC3627584/ /pubmed/23408856 http://dx.doi.org/10.1093/nar/gkt092 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Online Chen, Christina T. L. McDavid, Andrew N. Kahsai, Orsalem J. Zebari, Ahmad S. Carlson, Christopher S. Efficient identification of rare variants in large populations: deep re-sequencing the CRP locus in the CARDIA study |
title | Efficient identification of rare variants in large populations: deep re-sequencing the CRP locus in the CARDIA study |
title_full | Efficient identification of rare variants in large populations: deep re-sequencing the CRP locus in the CARDIA study |
title_fullStr | Efficient identification of rare variants in large populations: deep re-sequencing the CRP locus in the CARDIA study |
title_full_unstemmed | Efficient identification of rare variants in large populations: deep re-sequencing the CRP locus in the CARDIA study |
title_short | Efficient identification of rare variants in large populations: deep re-sequencing the CRP locus in the CARDIA study |
title_sort | efficient identification of rare variants in large populations: deep re-sequencing the crp locus in the cardia study |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3627584/ https://www.ncbi.nlm.nih.gov/pubmed/23408856 http://dx.doi.org/10.1093/nar/gkt092 |
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