ABSTRACT Genomic data encode past evolutionary events and have the potential to reveal the strength, rate and biological drivers of adaptation. However, joint estimation of adaptation rate

(_α_) and adaptation strength remains challenging because evolutionary processes such as demography, linkage and non-neutral polymorphism can confound inference. Here, we exploit the

influence of background selection to reduce the fixation rate of weakly beneficial alleles to jointly infer the strength and rate of adaptation. We develop a McDonald–Kreitman-based method

to infer adaptation rate and strength, and estimate _α_ = 0.135 in human protein-coding sequences, 72% of which is contributed by weakly adaptive variants. We show that, in this adaptation

beneficial. Our method provides a robust framework for estimation of adaptation rate and strength across species. Access through your institution Buy or subscribe This is a preview of

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ADAPTING POPULATIONS Article 11 September 2024 EXTREME PURIFYING SELECTION AGAINST POINT MUTATIONS IN THE HUMAN GENOME Article Open access 25 July 2022 THE POPULATION GENOMICS OF ADAPTIVE

LOSS OF FUNCTION Article Open access 11 February 2021 DATA AVAILABILITY Supplemental Data Table 1 is provided on the publisher’s website. The data that we used to parameterize our model are

also available online at https://github.com/uricchio/mktest. Columns in Supplementary Data Table 1 are as follows: 1, Ensembl coding gene identification; 2, number of non-synonymous

polymorphic sites; 3, respective derived allele frequencies of these sites separated by commas; 4, number of synonymous polymorphic sites; 5, respective frequency-derived allele frequencies

of these sites; 6, number of fixed non-synonymous substitutions on the human branch; and 7, number of fixed synonymous substitutions on the human branch. CODE AVAILABILITY The code that we

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(2012). Article  CAS  Google Scholar  Download references ACKNOWLEDGEMENTS We thank A. Aw, N. Rosenberg and members of the Rosenberg and Petrov laboratories for helpful discussions. L.H.U.

was partially supported by an IRACDA fellowship through NIGMS grant No. K12GM088033. L.H.U was supported by National Institutes of Health grant R01 HG005855 and National Science Foundation

grant DBI-1458059 (to N. Rosenberg). We also thank the Stanford/SJSU IRACDA Program for support. AUTHOR INFORMATION Author notes * Lawrence H. Uricchio Present address: Department of

Integrative Biology, University of California, Berkeley, CA, USA AUTHORS AND AFFILIATIONS * Department of Biology, Stanford University, Stanford, CA, USA Lawrence H. Uricchio & Dmitri A.

Petrov * Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA David Enard Authors * Lawrence H. Uricchio View author publications You can also search for

this author inPubMed Google Scholar * Dmitri A. Petrov View author publications You can also search for this author inPubMed Google Scholar * David Enard View author publications You can

also search for this author inPubMed Google Scholar CONTRIBUTIONS Designed the research: L.H.U., D.A.P., D.E. Performed the modeling and simulations: L.H.U. Analyzed the data: L.H.U.,

D.A.P.. Designed inference procedure: L.H.U. Wrote the paper: L.H.U. Edited and approved paper: L.H.U., D.A.P., D.E. CORRESPONDING AUTHORS Correspondence to Lawrence H. Uricchio or David

Enard. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. ADDITIONAL INFORMATION PUBLISHER’S NOTE: Springer Nature remains neutral with regard to

jurisdictional claims in published maps and institutional affiliations. SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION Supplementary Methods, Supplementary Figs. 1–20 REPORTING SUMMARY

SUPPLEMENTARY DATA 1 Data we used to parameterize the model. RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Uricchio, L.H., Petrov, D.A. & Enard, D.

Exploiting selection at linked sites to infer the rate and strength of adaptation. _Nat Ecol Evol_ 3, 977–984 (2019). https://doi.org/10.1038/s41559-019-0890-6 Download citation * Received:

25 September 2018 * Accepted: 28 March 2019 * Published: 06 May 2019 * Issue Date: June 2019 * DOI: https://doi.org/10.1038/s41559-019-0890-6 SHARE THIS ARTICLE Anyone you share the

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