title: On the importance of skewed offspring distributions and background selection in virus population genetics.
abstract: Many features of virus populations make them excellent candidates for population genetic study, including a very high rate of mutation, high levels of nucleotide diversity, exceptionally large census population sizes, and frequent positive selection. However, these attributes also mean that special care must be taken in population genetic inference. For example, highly skewed offspring distributions, frequent and severe population bottleneck events associated with infection and compartmentalization, and strong purifying selection all affect the distribution of genetic variation but are often not taken into account. Here, we draw particular attention to multiple-merger coalescent events and background selection, discuss potential misinference associated with these processes, and highlight potential avenues for better incorporating them into future population genetic analyses.
authors.affiliation: École Polytechnique Fédérale de Lausanne (EPFL), School of Life Sciences, Lausanne, Switzerland.|Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
authors.forename: K K
authors.initials: KK
authors.lastname: Irwin
authors.affiliation: École Polytechnique Fédérale de Lausanne (EPFL), School of Life Sciences, Lausanne, Switzerland.|Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
authors.forename: S
authors.initials: S
authors.lastname: Laurent
authors.affiliation: École Polytechnique Fédérale de Lausanne (EPFL), School of Life Sciences, Lausanne, Switzerland.|Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
authors.forename: S
authors.initials: S
authors.lastname: Matuszewski
authors.affiliation: École Polytechnique Fédérale de Lausanne (EPFL), School of Life Sciences, Lausanne, Switzerland.|Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
authors.forename: S
authors.initials: S
authors.lastname: Vuilleumier
authors.affiliation: École Polytechnique Fédérale de Lausanne (EPFL), School of Life Sciences, Lausanne, Switzerland.|Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
authors.forename: L
authors.initials: L
authors.lastname: Ormond
authors.affiliation: École Polytechnique Fédérale de Lausanne (EPFL), School of Life Sciences, Lausanne, Switzerland.|Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
authors.forename: H
authors.initials: H
authors.lastname: Shim
authors.affiliation: École Polytechnique Fédérale de Lausanne (EPFL), School of Life Sciences, Lausanne, Switzerland.|Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.|Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal.
authors.forename: C
authors.initials: C
authors.lastname: Bank
authors.affiliation: École Polytechnique Fédérale de Lausanne (EPFL), School of Life Sciences, Lausanne, Switzerland.|Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.|Arizona State University (ASU), School of Life Sciences, Center for Evolution & Medicine, Tempe, AZ, USA.
authors.forename: J D
authors.initials: JD
authors.lastname: Jensen
mesh_terms: D005075:Biological Evolution; D008040:Genetic Linkage; D005828:Genetics, Population; D008957:Models, Genetic; D059645:Mutation Rate; D012641:Selection, Genetic; D014780:Viruses / Q000235:genetics*