2018
DOI: 10.1371/journal.pgen.1007718
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A novel framework for inferring parameters of transmission from viral sequence data

Abstract: Transmission between hosts is a critical part of the viral lifecycle. Recent studies of viral transmission have used genome sequence data to evaluate the number of particles transmitted between hosts, and the role of selection as it operates during the transmission process. However, the interpretation of sequence data describing transmission events is a challenging task. We here present a novel and comprehensive framework for using short-read sequence data to understand viral transmission events, designed for … Show more

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Cited by 19 publications
(7 citation statements)
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“…There is some suggestive evidence of differential survival of particular (not necessarily antigenic) influenza genetic variants at the point of transmission from experiments in ferrets ( Wilker et al, 2013 ; Moncla et al, 2016 ). But as Lumby and colleagues ( Lumby et al, 2018 ) point out in a reanalysis of those experiments, it is difficult empirically to distinguish selection that occurs at the point of transmission from selection that occurs during early replication in the recipient host because of the challenges associated with sampling the small virus populations present at the earliest stages of infection. Here we define inoculation selection as selection on the bottlenecked virus population that establishes infection in the recipient host before any virus replication has taken place in that host.…”
Section: Resultsmentioning
confidence: 99%
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“…There is some suggestive evidence of differential survival of particular (not necessarily antigenic) influenza genetic variants at the point of transmission from experiments in ferrets ( Wilker et al, 2013 ; Moncla et al, 2016 ). But as Lumby and colleagues ( Lumby et al, 2018 ) point out in a reanalysis of those experiments, it is difficult empirically to distinguish selection that occurs at the point of transmission from selection that occurs during early replication in the recipient host because of the challenges associated with sampling the small virus populations present at the earliest stages of infection. Here we define inoculation selection as selection on the bottlenecked virus population that establishes infection in the recipient host before any virus replication has taken place in that host.…”
Section: Resultsmentioning
confidence: 99%
“…Rather, a ‘selective bottleneck’ typically refers either to a tight neutral bottleneck that leads to stochastic loss of diversity or to non-antigenic factors that lead to preferential transmission of certain variants ( Moncla et al, 2016 ). An important exception is ( Lumby et al, 2018 ). Those authors studied ferret transmission experiments and partitioned selection for adaptive mutants (not necessarily antigenic) into selection for transmissibility (acting at a potentially tight bottleneck) and selection during exponential growth.…”
Section: Discussionmentioning
confidence: 99%
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“…An experimental evolution study of avian influenza virus adaptation in ferrets found that transmission bottlenecks in naive hosts became tighter that as the virus adapted (Moncla et al, 2016). A reanalysis of that data found that bottlenecks were tight throughout (Lumby et al, 2018). The fact that bottlenecks do not appear to loosen (and may tighten) with adaptation for better transmission and replication is further evidence, albeit circumstantial, that when an influenza virus is well-adapted to its host and replicates rapidly, the first virion or first few virions to infect a cell will be the ancestor of the vast majority of progeny viruses.…”
Section: A53 Bottleneck Sizesmentioning
confidence: 99%
“…Sobel Leonard et al [25] devised a model that estimates the bottleneck size without estimating selective pressures during the early stage of establishing the disease. Lumby et al [26] proposed a fully probabilistic model that infers selection and the transmission bottleneck. More recent models have combined intra-and inter-host selection into an overall model for global influenza evolution [27].…”
Section: Introductionmentioning
confidence: 99%