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. 2022 Feb;128(2):79-87.
doi: 10.1038/s41437-021-00493-y. Epub 2022 Jan 5.

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

Ana Y Morales-Arce #  1 , Parul Johri #  1 , Jeffrey D Jensen  2
Affiliations

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

Ana Y Morales-Arce et al. Heredity (Edinb). 2022 Feb.

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.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Effects of progeny-skew and background selection on the inference of demography and the DFE, using the DFE-alpha approach (Keightley and Eyre-Walker 2007).
The left panels show the inference of the DFE while the right panels show the inference of fold-change in population size. Inference is shown when 30% of new mutations are neutral, and the remainder are: (A) weakly deleterious, (B) moderately deleterious, and (C) strongly deleterious. Estimates are shown only for the selected classes. Black bars depict true values, gray bars show inference in the absence of progeny skew (thus no violation of the assumption), and the blue bars correspond to populations with levels of progeny skew characterized by ψ = 0.075 (light blue) and ψ = 0.15 (dark blue).
Fig. 2
Fig. 2. Graphical representation of the demographic models of IAV and HCMV.
A IAV: in which the population size changes correspond to the experimental passaging. B HCMV: in which the size changes correspond to the initial infection and subsequent compartmentalization.
Fig. 3
Fig. 3. Inference of the DFE in the IAV population.
A Power and performance analyses concerning the inference of the DFE in an oscillating population size model mirroring that of the experimental IAV populations in question. The black diagonal lines represent the points at which estimated parameters match their true values, where f0 is the proportion of new mutations in the neutral class, f1 is the proportion of the weakly deleterious class, f2 is the proportion of the moderately deleterious class, and f3 is proportion of the strongly deleterious/lethal class. B Posterior estimates of the parameters of the DFE in an experimental population of IAV. Dashed lines indicate the distribution of sampled priors, the histograms present the posterior distribution, and the red vertical lines show the point estimates calculated as the weighted median.
Fig. 4
Fig. 4. Inference of the DFE in the HCMV population.
A Power and performance analyses concerning the inference of the DFE under an infection scenario mirroring that previously inferred for the HCMV population in question. The black diagonal lines represent the points at which estimated parameters match their true values, in which f0 is the proportion of new mutations in the neutral class, f1 is the proportion of the weakly deleterious class, f2 is the proportion of the moderately deleterious class, and f3 is the proportion of the strongly deleterious/lethal class. B Posterior estimates of the parameters of the DFE in a patient population of HCMV. Dashed lines indicate the distribution of sampled priors, the histograms present the posterior distributions, and the red vertical lines show the point estimates defined as the weighted median.
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