- THIS ARTICLE
- Full Text
- Full Text (PDF)
- Supporting Information
-
All Versions of this Article:
genetics.109.103010v1
183/1/259 most recent - Alert me when this article is cited
- Alert me if a correction is posted
- SERVICES
- Email this article to a friend
- Related articles in Genetics
- Similar articles in this journal
- Similar articles in PubMed
- Alert me to new issues of the journal
- Download to citation manager
- Reprints & Permissions
- GOOGLE SCHOLAR
- Articles by Dutheil, J. Y.
- Articles by Schierup, M. H.
- PUBMED
- PubMed Citation
- Articles by Dutheil, J. Y.
- Articles by Schierup, M. H.
Originally published as Genetics Published Articles Ahead of Print on July 6, 2009.
Genetics, Vol. 183, 259-274, September 2009, Copyright © 2009
doi:10.1534/genetics.109.103010
Ancestral Population Genomics: The Coalescent Hidden Markov Model Approach
Julien Y. Dutheil*,1,
Ganesh Ganapathy
,
Asger Hobolth*,
Thomas Mailund*,
Marcy K. Uyenoyama
and
Mikkel H. Schierup*,
* Bioinformatics Research Center and Department of Biological Sciences, Aarhus University, DK-8000 Aarhus C, Denmark, National Evolutionary Synthesis Center, Durham, North Carolina 27705-4667 and Department of Biology, Duke University, Durham, North Carolina 27708-0338
1 Corresponding author: Bioinformatics Research Center, Aarhus University, C. F. Møllers Alle 8, Bldg. 1110, DK-8000 Aarhus C, Denmark.
E-mail: jdutheil{at}birc.au.dk
With incomplete lineage sorting (ILS), the genealogy of closely related species differs along their genomes. The amount of ILS depends on population parameters such as the ancestral effective population sizes and the recombination rate, but also on the number of generations between speciation events. We use a hidden Markov model parameterized according to coalescent theory to infer the genealogy along a four-species genome alignment of closely related species and estimate population parameters. We analyze a basic, panmictic demographic model and study its properties using an extensive set of coalescent simulations. We assess the effect of the model assumptions and demonstrate that the Markov property provides a good approximation to the ancestral recombination graph. Using a too restricted set of possible genealogies, necessary to reduce the computational load, can bias parameter estimates. We propose a simple correction for this bias and suggest directions for future extensions of the model. We show that the patterns of ILS along a sequence alignment can be recovered efficiently together with the ancestral recombination rate. Finally, we introduce an extension of the basic model that allows for mutation rate heterogeneity and reanalyze human–chimpanzee–gorilla–orangutan alignments, using the new models. We expect that this framework will prove useful for population genomics and provide exciting insights into genome evolution.
Related articles in Genetics:
ISSUE HIGHLIGHTS
Genetics 2009 183: NP.
 |