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Inference of population genetic parameters from an irregular time series of seasonal influenza virus sequences

Title
Inference of population genetic parameters from an irregular time series of seasonal influenza virus sequences
Authors
Croze, MyriamKim, Yuseob
Ewha Authors
김유섭
SCOPUS Author ID
김유섭scopus
Issue Date
2021
Journal Title
GENETICS
ISSN
0016-6731JCR Link

1943-2631JCR Link
Citation
GENETICS vol. 217, no. 2
Keywords
serial sampleinfluenza virussummary statisticsmismatch distribution
Publisher
OXFORD UNIV PRESS INC
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Article
Abstract
Basic summary statistics that quantify the population genetic structure of influenza virus are important for understanding and inferring the evolutionary and epidemiological processes. However, the sampling dates of global virus sequences in the last several decades are scattered nonuniformly throughout the calendar. Such temporal structure of samples and the small effective size of viral population hampers the use of conventional methods to calculate summary statistics. Here, we define statistics that overcome this problem by correcting for the sampling-time difference in quantifying a pairwise sequence difference. A simple linear regression method jointly estimates the mutation rate and the level of sequence polymorphism, thus providing an estimate of the effective population size. It also leads to the definition of Wright's FST for arbitrary time-series data. Furthermore, as an alternative to Tajima's D statistic or the site-frequency spectrum, a mismatch distribution corrected for sampling-time differences can be obtained and compared between actual and simulated data. Application of these methods to seasonal influenza A/H3N2 viruses sampled between 1980 and 2017 and sequences simulated under the model of recurrent positive selection with metapopulation dynamics allowed us to estimate the synonymous mutation rate and find parameter values for selection and demographic structure that fit the observation. We found that the mutation rates of HA and PB1 segments before 2007 were particularly high and that including recurrent positive selection in our model was essential for the genealogical structure of the HA segment. Methods developed here can be generally applied to population genetic inferences using serially sampled genetic data.
DOI
10.1093/genetics/iyaa039
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자연과학대학 > 생명과학전공 > Journal papers
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