MimicrEE2: Genome-wide forward simulations of Evolve and Resequencing studies

Abstract

Evolve and Resequencing (E&R) studies allow us to monitor adaptation at the genomic level. By sequencing evolving populations at regular time intervals, E&R studies promise to shed light on some of the major open questions in evolutionary biology such as the repeatability of evolution and the molecular basis of adaptation. However, data interpretation, statistical analysis and the experimental design of E&R studies increasingly require simulations of evolving populations, a task that is difficult to accomplish with existing tools, which may i) be too slow, ii) require substantial reformatting of data, iii) not support an adaptive scenario of interest or iv) not sufficiently capture the biology of the used model organism. Therefore we developed MimicrEE2, a multi-threaded Java program for genome-wide forward simulations of evolving populations. MimicrEE2 enables the convenient usage of available genomic resources, supports biological particulars of model organism frequently used in E&R studies and offers a wide range of different adaptive models (selective sweeps, polygenic adaptation, epistasis). Due to its user-friendly and efficient design MimicrEE2 will facilitate simulations of E&R studies even for small labs with limited bioinformatics expertise or computational resources. Additionally, the scripts provided for executing MimicrEE2 on a computer cluster permit the coverage even of a large parameter space. MimicrEE2 runs on any computer with Java installed. It is distributed under the GPLv3 license at https://sourceforge.net/projects/mimicree2/.

Optimizing the power to identify the genetic basis of complex traits with Evolve and Resequence studies

“…To test if the selection regime has an influence on the performance of E&R studies we performed genomewide forward simulations with MimicrEE2 (Vlachos and Kofler, 2018). MimicrEE2 is a versatile tool that allows to simulate temporally variable truncating selection with a quantitative trait.…”

“…We used the CMH test (Landis et al, 1978) implemented in PoPoolation2 (Kofler et al, 2011) to identify selected loci. Previous works showed that the cmh-test has a high power to identify selected loci in E&R studies (Vlachos and Kofler, 2018;. The CMH test is based on a meta-analysis of a 2 * 2 * k contingency table.…”

“…All simulations were performed with the software MimicrEE2 (Vlachos and Kofler, 2018). Briefly, Mimi-crEE2 allows to perform genome-wide forward simulations of evolving populations.…”

“…It uses non-overlapping generations and supports simulation of temporally varying truncating selection, i.e. different numbers of individuals may be selected at each generation (Vlachos and Kofler, 2018). As not-evolved base population we obtained haplotypes that capture the pattern of natural variation of a D. melanogaster population from Vienna (2010) (Bastide et al, 2013).…”

Benchmarking software tools for detecting and quantifying selection in Evolve and Resequencing studies

“…To detect selected loci, CLEAR uses a Hidden Markov Model consisting of an underlying Wright-Fisher process and observed allele frequency counts from pool-sequenced organisms (Iranmehr et al, 2017). Besides estimating selection coefficients, CLEAR also provides estimates for N e and h. We evaluated the performance of the software tools with individual-based forward simulations with MimicrEE2 (Vlachos and Kofler, 2018). The simulation parameters were chosen to match D. melanogaster , the most frequently used organism in E&R studies of an obligatory sexual organism.…”