{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T14:52:22Z","timestamp":1791298342185,"version":"4.1.0"},"reference-count":97,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T00:00:00Z","timestamp":1790553600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R35GM161641"],"award-info":[{"award-number":["R35GM161641"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Epistasis, the nonadditive effects of mutations, shapes fitness landscapes and evolutionary trajectories. Temporal genetic data reveal evolutionary dynamics and could be used to infer epistatic interactions, especially through linkage disequilibrium (LD) between interacting mutations. However, other evolutionary forces can also generate LD, challenging inference. Here, we systematically evaluated the accuracy of a variety of epistasis inference approaches across a range of selective pressures, recombination rates, and population sizes. In general, we found that inference accuracy depends on the evolutionary regime: methods based on marginal path likelihood performed best under strong selection and low recombination, whereas quasilinkage equilibrium approaches were more accurate when recombination is frequent. We further showed that the strength of genetic drift can influence inference accuracy for approaches that learn from changes in allele frequencies over time. Collectively, our results show that the detectability of epistasis from temporal genetic data depends on the interplay between selection, recombination, and genetic drift, providing guidance for method selection across evolutionary contexts.<\/jats:p>","DOI":"10.1093\/genetics\/iyag258","type":"journal-article","created":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T10:49:03Z","timestamp":1790592543000},"source":"Crossref","is-referenced-by-count":0,"title":["Evolutionary regimes determine the accuracy of epistasis inference from temporal genetic data"],"prefix":"10.1093","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7580-4781","authenticated-orcid":false,"given":"Kai S","family":"Shimagaki","sequence":"first","affiliation":[{"name":"Department of Computational and Systems Biology, University of Pittsburgh School of Medicine , Pittsburgh, PA 15213 ,","place":["United States"]},{"name":"Department of Physics and Astronomy, University of Pittsburgh , Pittsburgh, PA 15213 ,","place":["United States"]},{"name":"Michigan Center for Applied and Interdisciplinary Mathematics, College of Literature, Science, and the Arts, University of Michigan , Ann Arbor, MI 48109 ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1467-421X","authenticated-orcid":false,"given":"John P","family":"Barton","sequence":"additional","affiliation":[{"name":"Department of Computational and Systems Biology, University of Pittsburgh School of Medicine , Pittsburgh, PA 15213 ,","place":["United States"]},{"name":"Department of Physics and Astronomy, University of Pittsburgh , Pittsburgh, PA 15213 ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,9,28]]},"reference":[{"key":"2026100610013996400_iyag258-B1","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1093\/molbev\/msz225","article-title":"Fine-scale haplotype 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