title: Using rare mutations to estimate population divergence times: a maximum likelihood approach.
abstract: In this paper we propose a method to estimate by maximum likelihood the divergence time between two populations, specifically designed for the analysis of nonrecurrent rare mutations. Given the rapidly growing amount of data, rare disease mutations affecting humans seem the most suitable candidates for this method. The estimator RD, and its conditional version RDc, were derived, assuming that the population dynamics of rare alleles can be described by using a birth-death process approximation and that each mutation arose before the split of a common ancestral population into the two diverging populations. The RD estimator seems more suitable for large sample sizes and few alleles, whose age can be approximated, whereas the RDc estimator appears preferable when this is not the case. When applied to three cystic fibrosis mutations, the estimator RD could not exclude a very recent time of divergence among three Mediterranean populations. On the other hand, the divergence time between these populations and the Danish population was estimated to be, on the average, 4,500 or 15,000 years, assuming or not a selective advantage for cystic fibrosis carriers, respectively. Confidence intervals are large, however, and can probably be reduced only by analyzing more alleles or loci.
authors.affiliation: Department of Integrative Biology, University of California, Berkeley, CA 94720-3140, USA. giorgio@mws4.biol.berkeley.edu
authors.forename: G
authors.initials: G
authors.lastname: Bertorelle
authors.forename: a B
authors.initials: aB
authors.lastname: Rannala
mesh_terms: D003550:Cystic Fibrosis / Q000235:genetics*; D003718:Denmark; D019143:Evolution, Molecular; D006580:Genetic Carrier Screening; D014644:Genetic Variation; D006801:Humans; D007558:Italy; D016013:Likelihood Functions; D019083:Mediterranean Region; D008957:Models, Genetic; D015233:Models, Statistical; D009154:Mutation; D011158:Population Growth; D013995:Time; D014421:Turkey