Bayesian analysis of congruence of core genes in Prochlorococcus and Synechococcus and implications on horizontal gene transfer
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Matzke, Nicholas; Shih, Patrick M.; Kerfeld, Cheryl
Description
It is often suggested that horizontal gene transfer is so ubiquitous in microbes that the concept of a phylogenetic tree representing the pattern of vertical inheritance is oversimplified or even positively misleading. “Universal proteins” have been used to infer the organismal phylogeny, but have been criticized as being only the “tree of one percent.” Currently, few options exist for those wishing to rigorously assess how well a universal protein phylogeny, based on a relative handful of...[Show more]
dc.contributor.author | Matzke, Nicholas | |
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dc.contributor.author | Shih, Patrick M. | |
dc.contributor.author | Kerfeld, Cheryl | |
dc.date.accessioned | 2018-11-29T22:56:12Z | |
dc.date.available | 2018-11-29T22:56:12Z | |
dc.identifier.issn | 1932-6203 | |
dc.identifier.uri | http://hdl.handle.net/1885/153436 | |
dc.description.abstract | It is often suggested that horizontal gene transfer is so ubiquitous in microbes that the concept of a phylogenetic tree representing the pattern of vertical inheritance is oversimplified or even positively misleading. “Universal proteins” have been used to infer the organismal phylogeny, but have been criticized as being only the “tree of one percent.” Currently, few options exist for those wishing to rigorously assess how well a universal protein phylogeny, based on a relative handful of well-conserved genes, represents the phylogenetic histories of hundreds of genes. Here, we address this problem by proposing a visualization method and a statistical test within a Bayesian framework. We use the genomes of marine cyanobacteria, a group thought to exhibit substantial amounts of HGT, as a test case. We take 379 orthologous gene families from 28 cyanobacteria genomes and estimate the Bayesian posterior distributions of trees – a “treecloud” – for each, as well as for a concatenated dataset based on putative “universal proteins.” We then calculate the average distance between trees within and between all treeclouds on various metrics and visualize this high-dimensional space with non-metric multidimensional scaling (NMMDS). We show that the tree space is strongly clustered and that the universal protein treecloud is statistically significantly closer to the center of this tree space than any individual gene treecloud. We apply several commonly-used tests for incongruence/HGT and show that they agree HGT is rare in this dataset, but make different choices about which genes were subject to HGT. Our results show that the question of the representativeness of the “tree of one percent” is a quantitative empirical question, and that the phylogenetic central tendency is a meaningful observation even if many individual genes disagree due to the various sources of incongruence. | |
dc.format.mimetype | application/pdf | |
dc.publisher | Public Library of Science | |
dc.source | PLOS ONE (Public Library of Science) | |
dc.subject | Keywords: article; bacterial gene; Bayes theorem; genetic variability; horizontal gene transfer; multidimensional scaling; nonhuman; phylogenetic tree; phylogeny; Prochlorococcus; protein database; sequence alignment; Synechococcus; Aquatic Organisms; Bayes Theorem | |
dc.title | Bayesian analysis of congruence of core genes in Prochlorococcus and Synechococcus and implications on horizontal gene transfer | |
dc.type | Journal article | |
local.description.notes | Imported from ARIES | |
local.identifier.citationvolume | 9 | |
dc.date.issued | 2014 | |
local.identifier.absfor | 060309 - Phylogeny and Comparative Analysis | |
local.identifier.absfor | 060409 - Molecular Evolution | |
local.identifier.absfor | 060408 - Genomics | |
local.identifier.ariespublication | U3488905xPUB16725 | |
local.type.status | Published Version | |
local.contributor.affiliation | Matzke, Nicholas, College of Science, ANU | |
local.contributor.affiliation | Shih, Patrick M., University of California | |
local.contributor.affiliation | Kerfeld, Cheryl, DOE Joint Genome Institute | |
local.bibliographicCitation.issue | 1 | |
local.bibliographicCitation.startpage | e85103 | |
local.bibliographicCitation.lastpage | e85103 | |
local.identifier.doi | 10.1371/journal.pone.0085103 | |
local.identifier.absseo | 970106 - Expanding Knowledge in the Biological Sciences | |
dc.date.updated | 2018-11-29T08:10:41Z | |
local.identifier.scopusID | 2-s2.0-84908084037 | |
local.identifier.thomsonID | 000330244500036 | |
dcterms.accessRights | Open Access | |
Collections | ANU Research Publications |
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01_Matzke_Bayesian_analysis_of_2014.pdf | 1.14 MB | Adobe PDF |
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