Inferring the distribution of fitness effects in patient-sampled and experimental virus populations: two case studies

Ana Y. Morales-Arce, Parul Johri, Jeffrey D. Jensen

Research output: Contribution to journalArticlepeer-review

Abstract

We here propose an analysis pipeline for inferring the distribution of fitness effects (DFE) from either patient-sampled or experimentally-evolved viral populations, that explicitly accounts for non-Wright-Fisher and non-equilibrium population dynamics inherent to pathogens. We examine the performance of this approach via extensive power and performance analyses, and highlight two illustrative applications - one from an experimentally-passaged RNA virus, and the other from a clinically-sampled DNA virus. Finally, we discuss how such DFE inference may shed light on major research questions in virus evolution, ranging from a quantification of the population genetic processes governing genome size, to the role of Hill-Robertson interference in dictating adaptive outcomes, to the potential design of novel therapeutic approaches to eradicate within-patient viral populations via induced mutational meltdown.

Original languageEnglish (US)
Pages (from-to)79-87
Number of pages9
JournalHeredity
Volume128
Issue number2
DOIs
StatePublished - Feb 2022
Externally publishedYes

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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