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Recombination rates in admixed individuals identified by ancestry-based inference

Abstract

Studies of recombination and how it varies depend crucially on accurate recombination maps. We propose a new approach for constructing high-resolution maps of relative recombination rates based on the observation of ancestry switch points among admixed individuals. We show the utility of this approach using simulations and by applying it to SNP genotype data from a sample of 2,565 African Americans and 299 African Caribbeans and detecting several hundred thousand recombination events. Comparison of the inferred map with high-resolution maps from non-admixed populations provides evidence of fine-scale differentiation in recombination rates between populations. Overall, the admixed map is well predicted by the average proportion of admixture and the recombination rate estimates from the source populations. The exceptions to this are in areas surrounding known large chromosomal structural variants, specifically inversions. These results suggest that outside of structurally variable regions, admixture does not substantially disrupt the factors controlling recombination rates in humans.

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Figure 1: Sketch of the haplotype-copying Hidden Markov model used to detect ancestry switch points.
Figure 2: Sensitivity and specificity of inference.
Figure 3: Comparison of the African admixture-based map to existing maps.
Figure 4: Population differences in recombination patterns.
Figure 5: Recombination rates in notable genomic locations.

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Acknowledgements

J.N., D.W. and K.R.V. were funded by a Searle Scholar Program award to J.N. N.B.F. was supported by US National Institutes of Health (NIH) grants R01HL087679 and RL1MH083268. The sample assembled is compiled from the larger efforts and the generous sharing of data from four major consortiums. For the GeneSTAR consortium (L.C.B., D.R.B., L.R.Y. and R.A.M.), support came from NIH grants HL072518 and M01-RR00052. For the CAG-CSGA consortium (D.A.M., D.G.T. and D.L.N.), support came from NIH grants U01 HL49596, R01 HL072414, R01 HL087665 and RC2 HL101651, and special thanks is given to C. Ober. For the GENOA samples (Y.V.S. and S.L.R.K.), support came from NIH grants HL087660 and HL100245, and special thanks is given to E. Boerwinkle. For the GRAAD consortium (K.C.B., N.R., I.R., T.H.B. and R.A.M.), support came from NIH grants HL087699, HL49612, AI50024, AI44840, HL075417, HL072433, AI41040, ES09606, HL072433 and RR03048, US Environmental Protection Agency grant 83213901, and National Institute of General Medical Sciences (NIGMS) grant S06GM08015, and special thanks are given to A.V. Grant, L. Gao, C. Vergara, Y.J. Tsai, P. Gao, M.C. Liu, P. Breysse, M.B. Bracken, J. Hoh, E.W. Pugh, A.F. Scott, G. Abecasis, T. Murray, T. Hand, M. Yang, M. Campbell, C. Foster, J.B. Hetmanski, R. Ashworth, C.M. Ongaco, K.N. Hetrick and K.F. Doheny. K.C.B. was supported in part by the Mary Beryl Patch Turnbull Scholar Program. R.A.M. was supported in part by the Mosaic Initiative Award from Johns Hopkins University. We thank C. Jaquish and the NHLBI STAMPEED program for their support of this collaboration. We also acknowledge G. Coop, A. di Rienzo, K. Lohmueller, and M. Przeworski for helpful discussions and comments on a draft of the manuscript.

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J.N. and N.B.F. conceived of the project, and D.W., J.N., N.B.F. and D.L.N. designed the analyses. D.G.T. and D.L.N. worked as part of the Chicago Asthma Genetics (CAG) and Collaborative Study on the Genetics of Asthma (CGSA) consortium to gather and prepare primary data for subsequent analysis. R.A.M., L.R.Y., L.C.B. and D.M.B. worked as part of the Genetic Study of Atherosclerosis Risk (GeneSTAR) Consortium to gather and prepare primary data for subsequent analysis. I.R., N.R., R.A.M., T.H.B. and K.C.B. worked as part of the Genetic Research on Asthma in the African Diaspora (GRAAD) consortium to gather and prepare primary data for subsequent analysis. Y.V.S., T.M. and S.L.R.K. worked as part of the Genetic Epidemiology Network of Arteriopathy (GENOA) consortium to gather and prepare primary data for subsequent analysis. D.G.T. and D.A.M. worked as part of the Severe Asthma Research Program (SARP) to gather and prepare primary data for subsequent analysis. D.W., D.E.K., K.R.V. and J.N. developed tools for the analysis and performed the analysis. D.W., N.B.F. and J.N. drafted the manuscript and revised it with D.E.K., K.R.V., R.A.M., D.L.N., L.R.Y., Y.V.S., L.C.B., N.R., I.R., T.H.B., S.L.R.K., D.A.M., K.C.B. and D.M.B.

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Correspondence to John Novembre.

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Wegmann, D., Kessner, D., Veeramah, K. et al. Recombination rates in admixed individuals identified by ancestry-based inference. Nat Genet 43, 847–853 (2011). https://doi.org/10.1038/ng.894

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