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

TL;DR

This paper introduces a novel efficient forward simulation model for biological populations that focuses on mutations relative to a reference, demonstrated through HIV drug resistance evolution.

Contribution

A new simple and efficient forward simulation model based on mutation differences from a reference genome is proposed, overcoming limitations of traditional methods.

Findings

The model efficiently simulates HIV resistance evolution.

It accurately tracks emergence of resistance mutants.

Demonstrates advantages over classical forward simulation methods.

Abstract

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