ArticleBMC genomics2014
Estimation of prokaryotic supergenome size and composition from gene frequency distributions.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution.Trends in microbiology · 2016Review
- Evolvability of an Optimal Recombination Rate.Genome biology and evolution · 2015Article
- Horizontal gene transfer: building the web of life.Nature reviews. Genetics · 2015Review
- The Turbulent Network Dynamics of Microbial Evolution and the Statistical Tree of Life.Journal of molecular evolution · 2015Review
- micropan: an R-package for microbial pan-genomics.BMC bioinformatics · 2015Article
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3 authors.
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Abstract
backgroundBecause prokaryotic genomes experience a rapid flux of genes, selection may act at a higher level than an individual genome. We explore a quantitative model of the distributed genome whereby groups of genomes evolve by acquiring genes from a fixed reservoir which we denote as supergenome. Previous attempts to understand the nature of the supergenome treated genomes as random, independent collections of genes and assumed that the supergenome consists of a small number of homogeneous sub-reservoirs. Here we explore the consequences of relaxing both assumptions.
resultsWe surveyed several methods for estimating the size and composition of the supergenome. The methods assumed that genomes were either random, independent samples of the supergenome or that they evolved from a common ancestor along a known tree via stochastic sampling from the reservoir. The reservoir was assumed to be either a collection of homogeneous sub-reservoirs or alternatively composed of genes with Gamma distributed gain probabilities. Empirical gene frequencies were used to either compute the likelihood of the data directly or first to reconstruct the history of gene gains and then compute the likelihood of the reconstructed numbers of gains.
conclusionsSupergenome size estimates using the empirical gene frequencies directly are not robust with respect to the choice of the model. By contrast, using the gene frequencies and the phylogenetic tree to reconstruct multiple gene gains produces reliable estimates of the supergenome size and indicates that a homogeneous supergenome is more consistent with the data than a supergenome with Gamma distributed gain probabilities.
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