Simulating Genomes and Populations in the Mutation Space: An example with the evolution of HIV drug resistance

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When simulating biological populations under different evolutionary genetic models, backward or forward strategies can be followed. Backward simulations, also called coalescent-based simulations, are computationally very efficient. However, this framework imposes several limitations that forward simulation does not. In this work, a new simple and efficient model to perform forward simulation of populations and/or genomes is proposed. The basic idea considers an individual as the differences (mutations) between this individual and a reference or consensus genotype. Thus, this individual is no longer represented by its complete sequence or genotype. An example of the efficiency of the new model with respect to a more classical forward one is demonstrated. This example models the evolution of HIV resistance using the B_FR.HXB2 reference sequence to study the emergence of known resistance mutants to Zidovudine and Didanosine drugs
17 pages, 3 figures

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