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ALF--a simulation framework for genome evolution.

ABSTRACT: In computational evolutionary biology, verification and benchmarking is a challenging task because the evolutionary history of studied biological entities is usually not known. Computer programs for simulating sequence evolution in silico have shown to be viable test beds for the verification of newly developed methods and to compare different algorithms. However, current simulation packages tend to focus either on gene-level aspects of genome evolution such as character substitutions and insertions and deletions (indels) or on genome-level aspects such as genome rearrangement and speciation events. Here, we introduce Artificial Life Framework (ALF), which aims at simulating the entire range of evolutionary forces that act on genomes: nucleotide, codon, or amino acid substitution (under simple or mixture models), indels, GC-content amelioration, gene duplication, gene loss, gene fusion, gene fission, genome rearrangement, lateral gene transfer (LGT), or speciation. The other distinctive feature of ALF is its user-friendly yet powerful web interface. We illustrate the utility of ALF with two possible applications: 1) we reanalyze data from a study of selection after globin gene duplication and test the statistical significance of the original conclusions and 2) we demonstrate that LGT can dramatically decrease the accuracy of two well-established orthology inference methods. ALF is available as a stand-alone application or via a web interface at http://www.cbrg.ethz.ch/alf.

SUBMITTER: Dalquen DA

PROVIDER: S-EPMC3341827 | biostudies-other | 2012 Apr

REPOSITORIES: biostudies-other

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ALF--a simulation framework for genome evolution.

Dalquen Daniel A DA Anisimova Maria M Gonnet Gaston H GH Dessimoz Christophe C

Molecular biology and evolution 20111208 4

In computational evolutionary biology, verification and benchmarking is a challenging task because the evolutionary history of studied biological entities is usually not known. Computer programs for simulating sequence evolution in silico have shown to be viable test beds for the verification of newly developed methods and to compare different algorithms. However, current simulation packages tend to focus either on gene-level aspects of genome evolution such as character substitutions and insert ...[more]

PMID: 22160766

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Project description:BackgroundThere is increasing demand to test hypotheses that contrast the evolution of genes and gene families among genomes, using simulations that work across these levels of organization. The EvolSimulator program was developed recently to provide a highly flexible platform for forward simulations of amino acid evolution in multiple related lineages of haploid genomes, permitting copy number variation and lateral gene transfer. Synonymous nucleotide evolution is not currently supported, however, and would be highly advantageous for comparisons to full genome, transcriptome, and single nucleotide polymorphism (SNP) datasets. In addition, EvolSimulator creates new genomes for each simulation, and does not allow the input of user-specified sequences and gene family information, limiting the incorporation of further biological realism and/or user manipulations of the data.FindingsWe present modified C++ source code for the EvolSimulator platform, which we provide as the extension module NU-IN. With NU-IN, synonymous and non-synonymous nucleotide evolution is fully implemented, and the user has the ability to use real or previously-simulated sequence data to initiate a simulation of one or more lineages. Gene family membership can be optionally specified, as well as gene retention probabilities that model biased gene retention. We provide PERL scripts to assist the user in deriving this information from previous simulations. We demonstrate the features of NU-IN by simulating genome duplication (polyploidy) in the presence of ongoing copy number variation in an evolving lineage. This example is initiated with real genomic data, and produces output that we analyse directly with existing bioinformatic pipelines.ConclusionsThe NU-IN extension module is a publicly available open source software (GNU GPLv3 license) extension to EvolSimulator. With the NU-IN module, users are now able to simulate both drift and selection at the nucleotide, amino acid, copy number, and gene family levels across sets of related genomes, for user-specified starting sequences and associated parameters. These features can be used to generate simulated genomic datasets under an extremely broad array of conditions, and with a high degree of biological realism.

Dataset Information

ALF--a simulation framework for genome evolution.

Publications

ALF--a simulation framework for genome evolution.

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