Biology subjects

Nene, N. R.

Publications and source records attributed to Nene, N. R..

2 recordsLinked to original sources

bioRxiv2018

A novel framework for inferring parameters of transmission from viral sequence data

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. Our model describes transmission as an event involving whole viruses, rather than independent alleles. We demonstrate how selection and noisy sequence data may each affect inferences of the population bottleneck, and identify circumstances in which selection for increased viral transmission may or may not be identified. Applying our model to data from a previous experimental transmission study, we show that our approach grants a more quantitative insight into viral transmission, inferring that between 2 to 6 viruses initiated infection, and allowing for a more informed interpretation of transmission events. While our model is here applied to influenza transmission, the framework we present is highly generalisable to other systems. Our work provides new opportunities for studying viral transmission.

evolutionary biology↗

bioRxiv2017

A delay-deterministic model for inferring fitnesseffects from time-resolved genome sequence data

A common challenge arising from the observation of an evolutionary system over time is to infer the magnitude of selection acting upon a specific genetic variant, or variants, within the population. The inference of selection may be confounded by the effects of genetic drift in a system, leading to the development of inference procedures to account for these effects. However, recent work has suggested that deterministic models of evolution may be effective in capturing the effects of selection even under complex models of demography, suggesting the more general application of deterministic approaches to inference. Responding to this literature, we here note a case in which a deterministic model of evolution may give highly misleading inferences, resulting from the non-deterministic properties of mutation in a finite population. We propose an alternative approach which corrects for this error, which we denote the delay-deterministic model. Applying our model to a simple evolutionary system we demonstrate its performance in quantifying the extent of selection acting within that system. We further consider the application of our model to sequence data from an evolutionary experiment. We outline scenarios in which our model may produce improved results for the inference of selection, noting that such situations can be easily identified via the use of a regular deterministic model.

evolutionary biology↗