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evogytis committed Jul 31, 2019
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%% This BibTeX bibliography file was created using BibDesk.
%% http://bibdesk.sourceforge.net/

%% Created for Gytis Dudas at 2019-03-18 13:23:26 -0700
%% Created for Gytis Dudas at 2019-07-31 15:42:40 +0200


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@article{duchene_genome-scale_2016,
Abstract = {Estimating the rates at which bacterial genomes evolve is critical to understanding major evolutionary and ecological processes such as disease emergence, long-term host--pathogen associations and short-term transmission patterns. The surge in bacterial genomic data sets provides a new opportunity to estimate these rates and reveal the factors that shape bacterial evolutionary dynamics. For many organisms estimates of evolutionary rate display an inverse association with the time-scale over which the data are sampled. However, this relationship remains unexplored in bacteria due to the difficulty in estimating genome-wide evolutionary rates, which are impacted by the extent of temporal structure in the data and the prevalence of recombination. We collected 36 whole genome sequence data sets from 16 species of bacterial pathogens to systematically estimate and compare their evolutionary rates and assess the extent of temporal structure in the absence of recombination. The majority (28/36) of data sets possessed sufficient clock-like structure to robustly estimate evolutionary rates. However, in some species reliable estimates were not possible even with `ancient DNA' data sampled over many centuries, suggesting that they evolve very slowly or that they display extensive rate variation among lineages. The robustly estimated evolutionary rates spanned several orders of magnitude, from approximately 10−5 to 10−8 nucleotide substitutions per site year−1. This variation was negatively associated with sampling time, with this relationship best described by an exponential decay curve. To avoid potential estimation biases, such time-dependency should be considered when inferring evolutionary time-scales in bacteria.},
Author = {Duch{\^e}ne, Sebastian and Holt, Kathryn E. and Weill, Fran{\c c}ois-Xavier and Le Hello, Simon and Hawkey, Jane and Edwards, David J. and Fourment, Mathieu and Holmes, Edward C.},
Date-Added = {2019-07-31 15:42:39 +0200},
Date-Modified = {2019-07-31 15:42:39 +0200},
Doi = {10.1099/mgen.0.000094},
File = {Full Text:/Users/evogytis/Zotero/storage/6MCS9UUY/Duch{\^e}ne et al. - 2016 - Genome-scale rates of evolutionary change in bacte.pdf:application/pdf;Snapshot:/Users/evogytis/Zotero/storage/3XVW22JA/mgen.0.html:text/html},
Journal = {Microbial Genomics},
Number = {11},
Title = {Genome-scale rates of evolutionary change in bacteria},
Url = {https://mgen.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000094},
Urldate = {2019-07-31},
Volume = {2},
Year = {2016},
Bdsk-Url-1 = {https://mgen.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000094},
Bdsk-Url-2 = {https://doi.org/10.1099/mgen.0.000094}}

@article{magiorkinis_global_2009,
Abstract = {Using phylodynamic and phylogeographic methods, Angelos Hatzakis and colleagues find that the global spread of Hepatitis C virus coincided with widespread use of transfused blood and with the expansion of intravenous drug use.},
Author = {Magiorkinis, Gkikas and Magiorkinis, Emmanouil and Paraskevis, Dimitrios and Ho, Simon Y. W. and Shapiro, Beth and Pybus, Oliver G. and Allain, Jean-Pierre and Hatzakis, Angelos},
Date-Added = {2019-07-30 16:07:44 +0200},
Date-Modified = {2019-07-30 16:07:44 +0200},
Doi = {10.1371/journal.pmed.1000198},
File = {Full Text PDF:/Users/evogytis/Zotero/storage/Q7Q889KF/Magiorkinis et al. - 2009 - The Global Spread of Hepatitis C Virus 1a and 1b .pdf:application/pdf},
Issn = {1549-1676},
Journal = {PLOS Medicine},
Keywords = {Blood transfusion, Genomic medicine, Hepatitis C virus, HIV epidemiology, Phylogenetic analysis, Phylogeography, Sequence analysis, Sequence databases},
Language = {en},
Month = dec,
Number = {12},
Pages = {e1000198},
Shorttitle = {The {Global} {Spread} of {Hepatitis} {C} {Virus} 1a and 1b},
Title = {The {Global} {Spread} of {Hepatitis} {C} {Virus} 1a and 1b: {A} {Phylodynamic} and {Phylogeographic} {Analysis}},
Url = {https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000198},
Urldate = {2019-07-30},
Volume = {6},
Year = {2009},
Bdsk-Url-1 = {https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000198},
Bdsk-Url-2 = {https://doi.org/10.1371/journal.pmed.1000198}}

@article{patino-galindo_substitution_2017,
Abstract = {Abstract. HIV-1M causes most infections in the AIDS pandemic. Its genetic diversity is defined by nine pure subtypes and more than sixty recombinant forms. We},
Author = {Pati{\~n}o-Galindo, Juan {\'A}ngel and Gonz{\'a}lez-Candelas, Fernando},
Date-Added = {2019-07-30 16:07:25 +0200},
Date-Modified = {2019-07-30 16:07:25 +0200},
Doi = {10.1093/ve/vex029},
File = {Full Text PDF:/Users/evogytis/Zotero/storage/9THKCDUI/Pati{\~n}o-Galindo and Gonz{\'a}lez-Candelas - 2017 - The substitution rate of HIV-1 subtypes a genomic.pdf:application/pdf;Snapshot:/Users/evogytis/Zotero/storage/76J84DTQ/4561620.html:text/html},
Journal = {Virus Evolution},
Language = {en},
Month = jul,
Number = {2},
Shorttitle = {The substitution rate of {HIV}-1 subtypes},
Title = {The substitution rate of {HIV}-1 subtypes: a genomic approach},
Url = {https://academic.oup.com/ve/article/3/2/vex029/4561620},
Urldate = {2019-07-30},
Volume = {3},
Year = {2017},
Bdsk-Url-1 = {https://academic.oup.com/ve/article/3/2/vex029/4561620},
Bdsk-Url-2 = {https://doi.org/10.1093/ve/vex029}}

@article{vaughan_inferring_2017,
Abstract = {Homologous recombination is a central feature of bacterial evolution, yet it confounds traditional phylogenetic methods. While a number of methods specific to bacterial evolution have been developed, none of these permit joint inference of a bacterial recombination graph and associated parameters. In this article, we present a new method which addresses this shortcoming. Our method uses a novel Markov chain Monte Carlo algorithm to perform phylogenetic inference under the ClonalOrigin model. We demonstrate the utility of our method by applying it to ribosomal multilocus sequence typing data sequenced from pathogenic and nonpathogenic Escherichia coli serotype O157 and O26 isolates collected in rural New Zealand. The method is implemented as an open source BEAST 2 package, Bacter, which is available via the project web page at http://tgvaughan.github.io/bacter.},
Author = {Vaughan, Timothy G. and Welch, David and Drummond, Alexei J. and Biggs, Patrick J. and George, Tessy and French, Nigel P.},

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