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An informational transition in conditioned Markov chains: Applied to genetics and evolution
Fudan Univ, Ctr Computat Syst Biol, 220 Handan Rd, Shanghai 200433, Peoples R China..
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Plant Ecology and Evolution. Fudan Univ, Ctr Computat Syst Biol, 220 Handan Rd, Shanghai 200433, Peoples R China..
Fudan Univ, Ctr Computat Syst Biol, 220 Handan Rd, Shanghai 200433, Peoples R China..
2016 (English)In: Journal of Theoretical Biology, ISSN 0022-5193, E-ISSN 1095-8541, Vol. 402, 158-170 p.Article in journal (Refereed) PublishedText
Abstract [en]

In this work we assume that we have some knowledge about the state of a population at two known times, when the dynamics is governed by a Markov chain such as a Wright-Fisher model. Such knowledge could be obtained, for example, from observations made on ancient and contemporary DNA, or during laboratory experiments involving long term evolution. A natural assumption is that the behaviour of the population, between observations, is related to (or constrained by) what was actually observed. The present work shows that this assumption has limited validity. When the time interval between observations is larger than a characteristic value, which is a property of the population under consideration, there is a range of intermediate times where the behaviour of the population has reduced or no dependence on what was observed and an equilibrium-like distribution applies. Thus, for example, if the frequency of an allele is observed at two different times, then for a large enough time interval between observations, the population has reduced or no dependence on the two observed frequencies for a range of intermediate times. Given observations of a population at two times, we provide a general theoretical analysis of the behaviour of the population at all intermediate times, and determine an expression for the characteristic time interval, beyond which the observations do not constrain the population's behaviour over a range of intermediate times. The findings of this work relate to what can be meaningfully inferred about a population at intermediate times, given knowledge of terminal states.

Place, publisher, year, edition, pages
2016. Vol. 402, 158-170 p.
Keyword [en]
Random genetic drift, Population genetics theory, Frequency trajectories, Conditional distribution, Ancient DNA
National Category
Evolutionary Biology
Identifiers
URN: urn:nbn:se:uu:diva-299544DOI: 10.1016/j.jtbi.2016.04.021ISI: 000377623700016PubMedID: 27105672OAI: oai:DiVA.org:uu-299544DiVA: diva2:949815
Available from: 2016-07-25 Created: 2016-07-22 Last updated: 2016-07-25Bibliographically approved

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