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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

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GENOMEPOP: a program to simulate genomes in populations.

Antonio Carvajal-Rodríguez¹

¹Departamento de Bioquímica, Genética e Inmunología, Universidad de Vigo, 36310 Vigo, Spain. acraaj@uvigo.es.

BMC Bioinformatics

|May 2, 2008

Summary

GenomePop is a new forward simulation program for DNA sequences. It efficiently simulates complex evolutionary and demographic models, aiding in understanding DNA evolutionary forces.

Area of Science:

Population genetics
Computational biology
Evolutionary genetics

Background:

Simulating DNA sequences is crucial in population biology for understanding evolutionary genetic models.
Backward (coalescent) simulations are efficient but limited, driving interest in forward simulations.
Existing tools struggle with large DNA fragments and complex evolutionary scenarios.

Purpose of the Study:

Introduce GenomePop, a novel forward simulation program.
Address the need for efficient simulation of large DNA fragments under complex models.
Demonstrate GenomePop's utility in studying intracodon recombination's impact on dN/dS.

Main Methods:

Developed algorithms for efficient forward-in-time DNA sequence simulation.
Implemented Markovian nucleotide and codon models of DNA mutation.

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Integrated recombination (inter- and intra-codon), fitness-based selection, and demographic scenarios.

Main Results:

GenomePop enables efficient forward simulation of DNA sequences.
The software supports complex evolutionary models, including GTR and GTRxMG94 codon models.
It accommodates intra-codon recombination, custom migration, and various ploidy/population size models.

Conclusions:

GenomePop offers unique features for simulating DNA under complex evolutionary and demographic models.
Its capabilities include fitness-based selection, recombination hot-spots, and handling large DNA fragments.
A scaling option optimizes computation for large-scale simulations, making it a versatile tool.