STUN: forward-time simulation on TUnable fitNess landscapes in recombining populations

被引:1
作者
Amado, Andre [1 ,2 ,3 ]
Li, Juan [1 ,2 ,3 ]
Bank, Claudia [1 ,2 ]
机构
[1] Univ Bern, Inst Ecol & Evolut, CH-3012 Bern, Switzerland
[2] Swiss Inst Bioinformat, Quartier Sorge Batiment Amphipole, CH-1015 Lausanne, Switzerland
[3] Univ Bern, Inst Ecol & Evolut, Baltzerstr 6, CH-3012 Bern, Switzerland
来源
BIOINFORMATICS ADVANCES | 2023年 / 3卷 / 01期
基金
欧洲研究理事会; 瑞士国家科学基金会;
关键词
EPISTASIS; EVOLUTION;
D O I
10.1093/bioadv/vbad164
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Motivation Understanding the population genetics of complex polygenic traits during adaptation is challenging.Results Here, we implement a forward-in-time population-genetic simulator (STUN) based on Wright-Fisher dynamics. STUN is a flexible and user-friendly software package for simulating the polygenic adaptation of recombining haploid populations using either new mutations or standing genetic variation. STUN assumes that populations adapt to sudden environmental changes by undergoing selection on a new fitness landscape. With pre-implemented fitness landscape models like Rough Mount Fuji, NK, Block, additive, and House-of-Cards, users can explore the effect of different levels of epistasis (ruggedness of the fitness landscape). Custom fitness landscapes and recombination maps can also be defined. STUN empowers both experimentalists and advanced programmers to study the evolution of complex polygenic traits and to dissect the adaptation process.Availability and implementation STUN is implemented in Rust. Its source code is available at https://github.com/banklab/STUN and archived on Zenodo under doi: 10.5281/zenodo.10246377. The repository includes a link to the software's manual and binary files for Linux, macOS and Windows.
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页数:6
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