Recovering Population Parameters from a Single Gene Genealogy: An Unbiased Estimator of the Growth Rate


Cite as:

Y.E. Maruvka, N.M. Shnerb, Y. Bar-Yam, J. Wakeley, Recovering Population Parameters from a Single Gene Genealogy: An Unbiased Estimator of the Growth Rate, Molecular Biology and Evolution 2010, doi: 10.1093/molbev/msq331.


Abstract

We show that the number of lineages ancestral to a sample, as a function of time back into the past, which we call the number of lineages as a function of time (NLFT), is a nearly deterministic property of large-sample gene genealogies. We obtain analytic expressions for the NLFT for both constant-sized and exponentially growing populations. The low level of stochastic variation associated with the NLFT of a large sample suggests using the NLFT to make estimates of population parameters. Based on this, we develop a new computational method of inferring the size and growth rate of a population from a large sample of DNA sequences at a single locus. We apply our method first to a sample of 1,212 mitochondrial DNA (mtDNA) sequences from China, confirming a pattern of recent population growth previously identified using other techniques, but with much smaller confidence intervals for past population sizes due to the low variation of the NLFT. We further analyze a set of 63 mtDNA sequences from blue whales (BWs), concluding that the population grew in the past. This calls for reevaluation of previous studies that were based on the assumption that the BW population was fixed.

 

 

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