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Rare Variation Facilitates Inferences of Fine-Scale Population Structure in Humans

Understanding the genetic structure of human populations has important implications for the design and interpretation of disease mapping studies and reconstructing human evolutionary history. To date, inferences of human population structure have primarily been made with common variants. However, re...

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Autores principales: O’Connor, Timothy D., Fu, Wenqing, Mychaleckyj, Josyf C., Logsdon, Benjamin, Auer, Paul, Carlson, Christopher S., Leal, Suzanne M., Smith, Joshua D., Rieder, Mark J., Bamshad, Michael J., Nickerson, Deborah A., Akey, Joshua M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4327153/
https://www.ncbi.nlm.nih.gov/pubmed/25415970
http://dx.doi.org/10.1093/molbev/msu326
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author O’Connor, Timothy D.
Fu, Wenqing
Mychaleckyj, Josyf C.
Logsdon, Benjamin
Auer, Paul
Carlson, Christopher S.
Leal, Suzanne M.
Smith, Joshua D.
Rieder, Mark J.
Bamshad, Michael J.
Nickerson, Deborah A.
Akey, Joshua M.
author_facet O’Connor, Timothy D.
Fu, Wenqing
Mychaleckyj, Josyf C.
Logsdon, Benjamin
Auer, Paul
Carlson, Christopher S.
Leal, Suzanne M.
Smith, Joshua D.
Rieder, Mark J.
Bamshad, Michael J.
Nickerson, Deborah A.
Akey, Joshua M.
author_sort O’Connor, Timothy D.
collection PubMed
description Understanding the genetic structure of human populations has important implications for the design and interpretation of disease mapping studies and reconstructing human evolutionary history. To date, inferences of human population structure have primarily been made with common variants. However, recent large-scale resequencing studies have shown an abundance of rare variation in humans, which may be particularly useful for making inferences of fine-scale population structure. To this end, we used an information theory framework and extensive coalescent simulations to rigorously quantify the informativeness of rare and common variation to detect signatures of fine-scale population structure. We show that rare variation affords unique insights into patterns of recent population structure. Furthermore, to empirically assess our theoretical findings, we analyzed high-coverage exome sequences in 6,515 European and African American individuals. As predicted, rare variants are more informative than common polymorphisms in revealing a distinct cluster of European–American individuals, and subsequent analyses demonstrate that these individuals are likely of Ashkenazi Jewish ancestry. Our results provide new insights into the population structure using rare variation, which will be an important factor to account for in rare variant association studies.
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spelling pubmed-43271532015-02-26 Rare Variation Facilitates Inferences of Fine-Scale Population Structure in Humans O’Connor, Timothy D. Fu, Wenqing Mychaleckyj, Josyf C. Logsdon, Benjamin Auer, Paul Carlson, Christopher S. Leal, Suzanne M. Smith, Joshua D. Rieder, Mark J. Bamshad, Michael J. Nickerson, Deborah A. Akey, Joshua M. Mol Biol Evol Discoveries Understanding the genetic structure of human populations has important implications for the design and interpretation of disease mapping studies and reconstructing human evolutionary history. To date, inferences of human population structure have primarily been made with common variants. However, recent large-scale resequencing studies have shown an abundance of rare variation in humans, which may be particularly useful for making inferences of fine-scale population structure. To this end, we used an information theory framework and extensive coalescent simulations to rigorously quantify the informativeness of rare and common variation to detect signatures of fine-scale population structure. We show that rare variation affords unique insights into patterns of recent population structure. Furthermore, to empirically assess our theoretical findings, we analyzed high-coverage exome sequences in 6,515 European and African American individuals. As predicted, rare variants are more informative than common polymorphisms in revealing a distinct cluster of European–American individuals, and subsequent analyses demonstrate that these individuals are likely of Ashkenazi Jewish ancestry. Our results provide new insights into the population structure using rare variation, which will be an important factor to account for in rare variant association studies. Oxford University Press 2015-03 2014-11-21 /pmc/articles/PMC4327153/ /pubmed/25415970 http://dx.doi.org/10.1093/molbev/msu326 Text en © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Discoveries
O’Connor, Timothy D.
Fu, Wenqing
Mychaleckyj, Josyf C.
Logsdon, Benjamin
Auer, Paul
Carlson, Christopher S.
Leal, Suzanne M.
Smith, Joshua D.
Rieder, Mark J.
Bamshad, Michael J.
Nickerson, Deborah A.
Akey, Joshua M.
Rare Variation Facilitates Inferences of Fine-Scale Population Structure in Humans
title Rare Variation Facilitates Inferences of Fine-Scale Population Structure in Humans
title_full Rare Variation Facilitates Inferences of Fine-Scale Population Structure in Humans
title_fullStr Rare Variation Facilitates Inferences of Fine-Scale Population Structure in Humans
title_full_unstemmed Rare Variation Facilitates Inferences of Fine-Scale Population Structure in Humans
title_short Rare Variation Facilitates Inferences of Fine-Scale Population Structure in Humans
title_sort rare variation facilitates inferences of fine-scale population structure in humans
topic Discoveries
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4327153/
https://www.ncbi.nlm.nih.gov/pubmed/25415970
http://dx.doi.org/10.1093/molbev/msu326
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