title: An ancestral recombination graph for diploid populations with skewed offspring distribution.
abstract: A large offspring-number diploid biparental multilocus population model of Moran type is our object of study. At each time step, a pair of diploid individuals drawn uniformly at random contributes offspring to the population. The number of offspring can be large relative to the total population size. Similar "heavily skewed" reproduction mechanisms have been recently considered by various authors (cf. e.g., Eldon and Wakeley 2006, 2008) and reviewed by Hedgecock and Pudovkin (2011). Each diploid parental individual contributes exactly one chromosome to each diploid offspring, and hence ancestral lineages can coalesce only when in distinct individuals. A separation-of-timescales phenomenon is thus observed. A result of Möhle (1998) is extended to obtain convergence of the ancestral process to an ancestral recombination graph necessarily admitting simultaneous multiple mergers of ancestral lineages. The usual ancestral recombination graph is obtained as a special case of our model when the parents contribute only one offspring to the population each time. Due to diploidy and large offspring numbers, novel effects appear. For example, the marginal genealogy at each locus admits simultaneous multiple mergers in up to four groups, and different loci remain substantially correlated even as the recombination rate grows large. Thus, genealogies for loci far apart on the same chromosome remain correlated. Correlation in coalescence times for two loci is derived and shown to be a function of the coalescence parameters of our model. Extending the observations by Eldon and Wakeley (2008), predictions of linkage disequilibrium are shown to be functions of the reproduction parameters of our model, in addition to the recombination rate. Correlations in ratios of coalescence times between loci can be high, even when the recombination rate is high and sample size is large, in large offspring-number populations, as suggested by simulations, hinting at how to distinguish between different population models.
authors.affiliation: Institut für Mathematik, Johannes-Gutenberg-Universität Mainz, 55099 Mainz, Germany.
authors.forename: Matthias
authors.initials: M
authors.lastname: Birkner
authors.forename: Jochen
authors.initials: J
authors.lastname: Blath
authors.forename: Bjarki
authors.initials: B
authors.lastname: Eldon
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D004171:Diploidy; D019143:Evolution, Molecular; D005260:Female; D056426:Genetic Loci; D005828:Genetics, Population; D006801:Humans; D008297:Male; D008957:Models, Genetic; D011995:Recombination, Genetic