%0 Journal Article
%T Inferring the distribution of fitness effects in patient-sampled and experimental virus populations: two case studies.
%A Morales-Arce AY
%A Johri P
%A Jensen JD
%J Heredity (Edinb)
%V 128
%N 2
%D 02 2022
%M 34987185
%F 3.832
%R 10.1038/s41437-021-00493-y
%X 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.