Conditions for the evolution of gene clusters in bacterial genomes.

Genes encoding proteins in a common pathway are often found near each other along bacterial chromosomes. Several explanations have been proposed to account for the evolution of these structures. For instance, natural selection may directly favour gene clusters through a variety of mechanisms, such a...

Full description

Bibliographic Details
Main Authors: Sara Ballouz, Andrew R Francis, Ruiting Lan, Mark M Tanaka
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2010-02-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC2820515?pdf=render
_version_ 1818363126581559296
author Sara Ballouz
Andrew R Francis
Ruiting Lan
Mark M Tanaka
author_facet Sara Ballouz
Andrew R Francis
Ruiting Lan
Mark M Tanaka
author_sort Sara Ballouz
collection DOAJ
description Genes encoding proteins in a common pathway are often found near each other along bacterial chromosomes. Several explanations have been proposed to account for the evolution of these structures. For instance, natural selection may directly favour gene clusters through a variety of mechanisms, such as increased efficiency of coregulation. An alternative and controversial hypothesis is the selfish operon model, which asserts that clustered arrangements of genes are more easily transferred to other species, thus improving the prospects for survival of the cluster. According to another hypothesis (the persistence model), genes that are in close proximity are less likely to be disrupted by deletions. Here we develop computational models to study the conditions under which gene clusters can evolve and persist. First, we examine the selfish operon model by re-implementing the simulation and running it under a wide range of conditions. Second, we introduce and study a Moran process in which there is natural selection for gene clustering and rearrangement occurs by genome inversion events. Finally, we develop and study a model that includes selection and inversion, which tracks the occurrence and fixation of rearrangements. Surprisingly, gene clusters fail to evolve under a wide range of conditions. Factors that promote the evolution of gene clusters include a low number of genes in the pathway, a high population size, and in the case of the selfish operon model, a high horizontal transfer rate. The computational analysis here has shown that the evolution of gene clusters can occur under both direct and indirect selection as long as certain conditions hold. Under these conditions the selfish operon model is still viable as an explanation for the evolution of gene clusters.
first_indexed 2024-12-13T21:43:31Z
format Article
id doaj.art-bcc3e0a6a5984372a7f37b0be153df31
institution Directory Open Access Journal
issn 1553-734X
1553-7358
language English
last_indexed 2024-12-13T21:43:31Z
publishDate 2010-02-01
publisher Public Library of Science (PLoS)
record_format Article
series PLoS Computational Biology
spelling doaj.art-bcc3e0a6a5984372a7f37b0be153df312022-12-21T23:30:29ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582010-02-0162e100067210.1371/journal.pcbi.1000672Conditions for the evolution of gene clusters in bacterial genomes.Sara BallouzAndrew R FrancisRuiting LanMark M TanakaGenes encoding proteins in a common pathway are often found near each other along bacterial chromosomes. Several explanations have been proposed to account for the evolution of these structures. For instance, natural selection may directly favour gene clusters through a variety of mechanisms, such as increased efficiency of coregulation. An alternative and controversial hypothesis is the selfish operon model, which asserts that clustered arrangements of genes are more easily transferred to other species, thus improving the prospects for survival of the cluster. According to another hypothesis (the persistence model), genes that are in close proximity are less likely to be disrupted by deletions. Here we develop computational models to study the conditions under which gene clusters can evolve and persist. First, we examine the selfish operon model by re-implementing the simulation and running it under a wide range of conditions. Second, we introduce and study a Moran process in which there is natural selection for gene clustering and rearrangement occurs by genome inversion events. Finally, we develop and study a model that includes selection and inversion, which tracks the occurrence and fixation of rearrangements. Surprisingly, gene clusters fail to evolve under a wide range of conditions. Factors that promote the evolution of gene clusters include a low number of genes in the pathway, a high population size, and in the case of the selfish operon model, a high horizontal transfer rate. The computational analysis here has shown that the evolution of gene clusters can occur under both direct and indirect selection as long as certain conditions hold. Under these conditions the selfish operon model is still viable as an explanation for the evolution of gene clusters.http://europepmc.org/articles/PMC2820515?pdf=render
spellingShingle Sara Ballouz
Andrew R Francis
Ruiting Lan
Mark M Tanaka
Conditions for the evolution of gene clusters in bacterial genomes.
PLoS Computational Biology
title Conditions for the evolution of gene clusters in bacterial genomes.
title_full Conditions for the evolution of gene clusters in bacterial genomes.
title_fullStr Conditions for the evolution of gene clusters in bacterial genomes.
title_full_unstemmed Conditions for the evolution of gene clusters in bacterial genomes.
title_short Conditions for the evolution of gene clusters in bacterial genomes.
title_sort conditions for the evolution of gene clusters in bacterial genomes
url http://europepmc.org/articles/PMC2820515?pdf=render
work_keys_str_mv AT saraballouz conditionsfortheevolutionofgeneclustersinbacterialgenomes
AT andrewrfrancis conditionsfortheevolutionofgeneclustersinbacterialgenomes
AT ruitinglan conditionsfortheevolutionofgeneclustersinbacterialgenomes
AT markmtanaka conditionsfortheevolutionofgeneclustersinbacterialgenomes