article
Inference in two dimensions: Allele frequencies versus lengths of shared sequence blocks
published
yes
Nicholas H
Barton
author 4880FE40-F248-11E8-B48F-1D18A9856A870000-0002-8548-5240
Alison
Etheridge
author
Jerome
Kelleher
author
Amandine
Véber
author
NiBa
department
Limits to selection in biology and in evolutionary computation
project
We outline two approaches to inference of neighbourhood size, N, and dispersal rate, σ2, based on either allele frequencies or on the lengths of sequence blocks that are shared between genomes. Over intermediate timescales (10-100 generations, say), populations that live in two dimensions approach a quasi-equilibrium that is independent of both their local structure and their deeper history. Over such scales, the standardised covariance of allele frequencies (i.e. pairwise FS T) falls with the logarithm of distance, and depends only on neighbourhood size, N, and a 'local scale', κ; the rate of gene flow, σ2, cannot be inferred. We show how spatial correlations can be accounted for, assuming a Gaussian distribution of allele frequencies, giving maximum likelihood estimates of N and κ. Alternatively, inferences can be based on the distribution of the lengths of sequence that are identical between blocks of genomes: long blocks (>0.1 cM, say) tell us about intermediate timescales, over which we assume a quasi-equilibrium. For large neighbourhood size, the distribution of long blocks is given directly by the classical Wright-Malécot formula; this relationship can be used to infer both N and σ2. With small neighbourhood size, there is an appreciable chance that recombinant lineages will coalesce back before escaping into the distant past. For this case, we show that if genomes are sampled from some distance apart, then the distribution of lengths of blocks that are identical in state is geometric, with a mean that depends on N and σ2.
https://research-explorer.app.ist.ac.at/download/2842/5288/IST-2016-558-v1+1_inference_revised3101NB.pdf
application/pdfno
https://research-explorer.app.ist.ac.at/download/2842/5289/IST-2016-558-v1+2_inference_revised3101NBApp.pdf
application/pdfno
Elsevier2013
eng
Theoretical Population Biology10.1016/j.tpb.2013.03.001
871105 - 119
Barton, Nicholas H., et al. “Inference in Two Dimensions: Allele Frequencies versus Lengths of Shared Sequence Blocks.” <i>Theoretical Population Biology</i>, vol. 87, no. 1, Elsevier, 2013, pp. 105–19, doi:<a href="https://doi.org/10.1016/j.tpb.2013.03.001">10.1016/j.tpb.2013.03.001</a>.
N. H. Barton, A. Etheridge, J. Kelleher, and A. Véber, “Inference in two dimensions: Allele frequencies versus lengths of shared sequence blocks,” <i>Theoretical Population Biology</i>, vol. 87, no. 1, pp. 105–119, 2013.
Barton NH, Etheridge A, Kelleher J, Véber A. Inference in two dimensions: Allele frequencies versus lengths of shared sequence blocks. <i>Theoretical Population Biology</i>. 2013;87(1):105-119. doi:<a href="https://doi.org/10.1016/j.tpb.2013.03.001">10.1016/j.tpb.2013.03.001</a>
Barton NH, Etheridge A, Kelleher J, Véber A. 2013. Inference in two dimensions: Allele frequencies versus lengths of shared sequence blocks. Theoretical Population Biology. 87(1), 105–119.
N.H. Barton, A. Etheridge, J. Kelleher, A. Véber, Theoretical Population Biology 87 (2013) 105–119.
Barton, Nicholas H, Alison Etheridge, Jerome Kelleher, and Amandine Véber. “Inference in Two Dimensions: Allele Frequencies versus Lengths of Shared Sequence Blocks.” <i>Theoretical Population Biology</i> 87, no. 1 (2013): 105–19. <a href="https://doi.org/10.1016/j.tpb.2013.03.001">https://doi.org/10.1016/j.tpb.2013.03.001</a>.
Barton, N. H., Etheridge, A., Kelleher, J., & Véber, A. (2013). Inference in two dimensions: Allele frequencies versus lengths of shared sequence blocks. <i>Theoretical Population Biology</i>, <i>87</i>(1), 105–119. <a href="https://doi.org/10.1016/j.tpb.2013.03.001">https://doi.org/10.1016/j.tpb.2013.03.001</a>
28422018-12-11T11:59:53Z2020-01-16T12:36:42Z