Assessing the reliability of eBURST using simulated populations with known ancestry

<p>Abstract</p> <p>Background</p> <p>The program eBURST uses multilocus sequence typing data to divide bacterial populations into groups of closely related strains (clonal complexes), predicts the founding genotype of each group, and displays the patterns of recent evol...

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Main Authors: Connor Thomas R, Fraser Christophe, Hanage William P, Turner Katherine ME, Spratt Brian G
Format: Article
Language:English
Published: BMC 2007-04-01
Series:BMC Microbiology
Online Access:http://www.biomedcentral.com/1471-2180/7/30
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spelling doaj-928aeb9c406741419c147228e05abe0e2020-11-25T00:09:33ZengBMCBMC Microbiology1471-21802007-04-01713010.1186/1471-2180-7-30Assessing the reliability of eBURST using simulated populations with known ancestryConnor Thomas RFraser ChristopheHanage William PTurner Katherine MESpratt Brian G<p>Abstract</p> <p>Background</p> <p>The program eBURST uses multilocus sequence typing data to divide bacterial populations into groups of closely related strains (clonal complexes), predicts the founding genotype of each group, and displays the patterns of recent evolutionary descent of all other strains in the group from the founder. The reliability of eBURST was evaluated using populations simulated with different levels of recombination in which the ancestry of all strains was known.</p> <p>Results</p> <p>For strictly clonal simulations, where all allelic change is due to point mutation, the groups of related strains identified by eBURST were very similar to those expected from the true ancestry and most of the true ancestor-descendant relationships (90–98%) were identified by eBURST. Populations simulated with low or moderate levels of recombination showed similarly high performance but the reliability of eBURST declined with increasing recombination to mutation ratio. Populations simulated under a high recombination to mutation ratio were dominated by a single large straggly eBURST group, which resulted from the incorrect linking of unrelated groups of strains into the same eBURST group. The reliability of the ancestor-descendant links in eBURST diagrams was related to the proportion of strains in the largest eBURST group, which provides a useful guide to when eBURST is likely to be unreliable.</p> <p>Conclusion</p> <p>Examination of eBURST groups within populations of a range of bacterial species showed that most were within the range in which eBURST is reliable, and only a small number (e.g. <it>Burkholderia pseudomallei </it>and <it>Enterococcus faecium</it>) appeared to have such high rates of recombination that eBURST is likely to be unreliable. The study also demonstrates how three simple tests in eBURST v3 can be used to detect unreliable eBURST performance and recognise populations in which there appears to be a high rate of recombination relative to mutation.</p> http://www.biomedcentral.com/1471-2180/7/30
collection DOAJ
language English
format Article
sources DOAJ
author Connor Thomas R
Fraser Christophe
Hanage William P
Turner Katherine ME
Spratt Brian G
spellingShingle Connor Thomas R
Fraser Christophe
Hanage William P
Turner Katherine ME
Spratt Brian G
Assessing the reliability of eBURST using simulated populations with known ancestry
BMC Microbiology
author_facet Connor Thomas R
Fraser Christophe
Hanage William P
Turner Katherine ME
Spratt Brian G
author_sort Connor Thomas R
title Assessing the reliability of eBURST using simulated populations with known ancestry
title_short Assessing the reliability of eBURST using simulated populations with known ancestry
title_full Assessing the reliability of eBURST using simulated populations with known ancestry
title_fullStr Assessing the reliability of eBURST using simulated populations with known ancestry
title_full_unstemmed Assessing the reliability of eBURST using simulated populations with known ancestry
title_sort assessing the reliability of eburst using simulated populations with known ancestry
publisher BMC
series BMC Microbiology
issn 1471-2180
publishDate 2007-04-01
description <p>Abstract</p> <p>Background</p> <p>The program eBURST uses multilocus sequence typing data to divide bacterial populations into groups of closely related strains (clonal complexes), predicts the founding genotype of each group, and displays the patterns of recent evolutionary descent of all other strains in the group from the founder. The reliability of eBURST was evaluated using populations simulated with different levels of recombination in which the ancestry of all strains was known.</p> <p>Results</p> <p>For strictly clonal simulations, where all allelic change is due to point mutation, the groups of related strains identified by eBURST were very similar to those expected from the true ancestry and most of the true ancestor-descendant relationships (90–98%) were identified by eBURST. Populations simulated with low or moderate levels of recombination showed similarly high performance but the reliability of eBURST declined with increasing recombination to mutation ratio. Populations simulated under a high recombination to mutation ratio were dominated by a single large straggly eBURST group, which resulted from the incorrect linking of unrelated groups of strains into the same eBURST group. The reliability of the ancestor-descendant links in eBURST diagrams was related to the proportion of strains in the largest eBURST group, which provides a useful guide to when eBURST is likely to be unreliable.</p> <p>Conclusion</p> <p>Examination of eBURST groups within populations of a range of bacterial species showed that most were within the range in which eBURST is reliable, and only a small number (e.g. <it>Burkholderia pseudomallei </it>and <it>Enterococcus faecium</it>) appeared to have such high rates of recombination that eBURST is likely to be unreliable. The study also demonstrates how three simple tests in eBURST v3 can be used to detect unreliable eBURST performance and recognise populations in which there appears to be a high rate of recombination relative to mutation.</p>
url http://www.biomedcentral.com/1471-2180/7/30
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