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Closed-Form Asymptotic Sampling Distributions under the Coalescent with Recombination for an Arbitrary Number of Loci

Published online by Cambridge University Press:  04 January 2016

Anand Bhaskar*
Affiliation:
University of California, Berkeley
Yun S. Song*
Affiliation:
University of California, Berkeley
*
Postal address: Computer Science Division, University of California, Berkeley, CA 94720, USA.
∗∗ Postal address: Computer Science Division and Department of Statistics, University of California, Berkeley, CA 94720, USA. Email address: yss@stat.berkeley.edu
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Abstract

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Obtaining a closed-form sampling distribution for the coalescent with recombination is a challenging problem. In the case of two loci, a new framework based on an asymptotic series has recently been developed to derive closed-form results when the recombination rate is moderate to large. In this paper, an arbitrary number of loci is considered and combinatorial approaches are employed to find closed-form expressions for the first couple of terms in an asymptotic expansion of the multi-locus sampling distribution. These expressions are universal in the sense that their functional form in terms of the marginal one-locus distributions applies to all finite- and infinite-alleles models of mutation.

Type
General Applied Probability
Copyright
© Applied Probability Trust 

References

Ethier, S. N. (1979). A limit theorem for two-locus diffusion models in population genetics. J. Appl. Prob. 16, 402408.Google Scholar
Ethier, S. N. and Griffiths, R. C. (1990). On the two-locus sampling distribution. J. Math. Biol. 29, 131159.Google Scholar
Ewens, W. J. (1972). The sampling theory of selectively neutral alleles. Theoret. Pop. Biol. 3, 87112.Google Scholar
Fearnhead, P. and Donnelly, P. (2001). Estimating recombination rates from population genetic data. Genetics 159, 12991318.Google Scholar
Golding, G. B. (1984). The sampling distribution of linkage disequilibrium. Genetics 108, 257274.Google Scholar
Griffiths, R. C. (1981). Neutral two-locus multiple allele models with recombination. Theoret. Pop. Biol. 19, 169186.CrossRefGoogle Scholar
Griffiths, R. C. and Marjoram, P. (1996). Ancestral inference from samples of DNA sequences with recombination. J. Comput. Biol. 3, 479502.Google Scholar
Griffiths, R. C., Jenkins, P. A. and Song, Y. S. (2008). Importance sampling and the two-locus model with subdivided population structure. Adv. Appl. Prob. 40, 473500.CrossRefGoogle ScholarPubMed
Hudson, R. R. (1985). The sampling distribution of linkage disequilibrium under an infinite allele model without selection. Genetics 109, 611631.Google Scholar
Hudson, R. R. (2001). Two-locus sampling distributions and their application. Genetics 159, 18051817.Google Scholar
Jenkins, P. A. and Song, Y. S. (2009). Closed-form two-locus sampling distributions: accuracy and universality. Genetics 183, 10871103.Google Scholar
Jenkins, P. A. and Song, Y. S. (2010). An asymptotic sampling formula for the coalescent with recombination. Ann. Appl. Prob. 20, 10051028.Google Scholar
Jenkins, P. A. and Song, Y. S. (2012). Padé approximants and exact two-locus sampling distributions. Ann. Appl. Prob. 22, 576607.Google Scholar
Kingman, J. F. C. (1982). The coalescent. Stoch. Process. Appl. 13, 235248.Google Scholar
Kingman, J. F. C. (1982). On the genealogy of large populations. In Essays in Statistical Science (J. Appl. Prob. Spec. Vol. 19A), eds Gani, J. and Hannan, E. J., Applied Probability Trust, Sheffield, pp. 2743.Google Scholar
Kuhner, M. K., Yamato, J. and Felsenstein, J. (2000). Maximum likelihood estimation of recombination rates from population data. Genetics 156, 13931401.Google Scholar
McVean, G., Awadalla, P. and Fearnhead, P. (2002). A coalescent-based method for detecting and estimating recombination from gene sequences. Genetics 160, 12311241.CrossRefGoogle ScholarPubMed
McVean, G. A. T. et al. (2004). The fine-scale structure of recombination rate variation in the human genome. Science 304, 581584.Google Scholar
Nielsen, R. (2000). Estimation of population parameters and recombination rates from single nucleotide polymorphisms. Genetics 154, 931942.Google Scholar
Stephens, M. and Donnelly, P. (2000). Inference in molecular population genetics. J. Roy. Statist. Soc. B 62, 605655.Google Scholar
Wang, Y. and Rannala, B. (2008). Bayesian inference of fine-scale recombination rates using population genomic data. Phil. Trans. R. Soc. B 363, 39213930.Google Scholar
Wright, S. (1949). Adaptation and selection. In Genetics, Paleontology and Evolution, eds Jepson, G. L., Simpson, G. G. and Mayr, E., Princeton University Press, pp. 365389.Google Scholar