Statistical guidelines for detecting past population shifts using ancient DNA

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Statistical guidelines for detecting past population shifts using ancient DNA. / Mourier, Tobias; Ho, Simon Y. W.; Gilbert, Tom; Willerslev, Eske; Orlando, Ludovic Antoine Alexandre.

I: Molecular Biology and Evolution, Bind 29, Nr. 9, 16.03.2012, s. 2241-2251.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Mourier, T, Ho, SYW, Gilbert, T, Willerslev, E & Orlando, LAA 2012, 'Statistical guidelines for detecting past population shifts using ancient DNA', Molecular Biology and Evolution, bind 29, nr. 9, s. 2241-2251. https://doi.org/10.1093/molbev/mss094

APA

Mourier, T., Ho, S. Y. W., Gilbert, T., Willerslev, E., & Orlando, L. A. A. (2012). Statistical guidelines for detecting past population shifts using ancient DNA. Molecular Biology and Evolution, 29(9), 2241-2251. https://doi.org/10.1093/molbev/mss094

Vancouver

Mourier T, Ho SYW, Gilbert T, Willerslev E, Orlando LAA. Statistical guidelines for detecting past population shifts using ancient DNA. Molecular Biology and Evolution. 2012 mar. 16;29(9):2241-2251. https://doi.org/10.1093/molbev/mss094

Author

Mourier, Tobias ; Ho, Simon Y. W. ; Gilbert, Tom ; Willerslev, Eske ; Orlando, Ludovic Antoine Alexandre. / Statistical guidelines for detecting past population shifts using ancient DNA. I: Molecular Biology and Evolution. 2012 ; Bind 29, Nr. 9. s. 2241-2251.

Bibtex

@article{f03ffd1cd53e4a75980d172b70300593,
title = "Statistical guidelines for detecting past population shifts using ancient DNA",
abstract = "Populations carry a genetic signal of their demographic past, providing an opportunity for investigating the processes that shaped their evolution. Our ability to infer population histories can be enhanced by including ancient DNA data. Using serial-coalescent simulations and a range of both quantitative and temporal sampling schemes, we test the power of ancient mitochondrial sequences and nuclear single-nucleotide polymorphisms (SNPs) to detect past population bottlenecks. Within our simulated framework, mitochondrial sequences have only limited power to detect subtle bottlenecks and/or fast post-bottleneck recoveries. In contrast, nuclear SNPs can detect bottlenecks followed by rapid recovery, although bottlenecks involving reduction of less than half the population are generally detected with low power unless extensive genetic information from ancient individuals is available. Our results provide useful guidelines for scaling sampling schemes and for optimizing our ability to infer past population dynamics. In addition, our results suggest that many ancient DNA studies may face power issues in detecting moderate demographic collapses and/or highly dynamic demographic shifts when based solely on mitochondrial information.",
author = "Tobias Mourier and Ho, {Simon Y. W.} and Tom Gilbert and Eske Willerslev and Orlando, {Ludovic Antoine Alexandre}",
year = "2012",
month = mar,
day = "16",
doi = "10.1093/molbev/mss094",
language = "English",
volume = "29",
pages = "2241--2251",
journal = "Molecular Biology and Evolution",
issn = "0737-4038",
publisher = "Oxford University Press",
number = "9",

}

RIS

TY - JOUR

T1 - Statistical guidelines for detecting past population shifts using ancient DNA

AU - Mourier, Tobias

AU - Ho, Simon Y. W.

AU - Gilbert, Tom

AU - Willerslev, Eske

AU - Orlando, Ludovic Antoine Alexandre

PY - 2012/3/16

Y1 - 2012/3/16

N2 - Populations carry a genetic signal of their demographic past, providing an opportunity for investigating the processes that shaped their evolution. Our ability to infer population histories can be enhanced by including ancient DNA data. Using serial-coalescent simulations and a range of both quantitative and temporal sampling schemes, we test the power of ancient mitochondrial sequences and nuclear single-nucleotide polymorphisms (SNPs) to detect past population bottlenecks. Within our simulated framework, mitochondrial sequences have only limited power to detect subtle bottlenecks and/or fast post-bottleneck recoveries. In contrast, nuclear SNPs can detect bottlenecks followed by rapid recovery, although bottlenecks involving reduction of less than half the population are generally detected with low power unless extensive genetic information from ancient individuals is available. Our results provide useful guidelines for scaling sampling schemes and for optimizing our ability to infer past population dynamics. In addition, our results suggest that many ancient DNA studies may face power issues in detecting moderate demographic collapses and/or highly dynamic demographic shifts when based solely on mitochondrial information.

AB - Populations carry a genetic signal of their demographic past, providing an opportunity for investigating the processes that shaped their evolution. Our ability to infer population histories can be enhanced by including ancient DNA data. Using serial-coalescent simulations and a range of both quantitative and temporal sampling schemes, we test the power of ancient mitochondrial sequences and nuclear single-nucleotide polymorphisms (SNPs) to detect past population bottlenecks. Within our simulated framework, mitochondrial sequences have only limited power to detect subtle bottlenecks and/or fast post-bottleneck recoveries. In contrast, nuclear SNPs can detect bottlenecks followed by rapid recovery, although bottlenecks involving reduction of less than half the population are generally detected with low power unless extensive genetic information from ancient individuals is available. Our results provide useful guidelines for scaling sampling schemes and for optimizing our ability to infer past population dynamics. In addition, our results suggest that many ancient DNA studies may face power issues in detecting moderate demographic collapses and/or highly dynamic demographic shifts when based solely on mitochondrial information.

U2 - 10.1093/molbev/mss094

DO - 10.1093/molbev/mss094

M3 - Journal article

C2 - 22427706

VL - 29

SP - 2241

EP - 2251

JO - Molecular Biology and Evolution

JF - Molecular Biology and Evolution

SN - 0737-4038

IS - 9

ER -

ID: 37800815