实验进化
生物
选择(遗传算法)
适应(眼睛)
基因组
计算生物学
DNA测序
遗传学
机制(生物学)
进化生物学
基因
计算机科学
机器学习
认识论
哲学
神经科学
作者
Célia Payen,Maitreya J. Dunham
出处
期刊:Methods in molecular biology
日期:2015-10-19
卷期号:: 361-374
被引量:5
标识
DOI:10.1007/978-1-4939-3079-1_20
摘要
Experimental evolution of microbes is a powerful tool to study adaptation to strong selection, the mechanism of evolution and the development of new traits. The development of high-throughput sequencing methods has given researchers a new ability to cheaply and easily identify mutations genome wide that are selected during the course of experimental evolution. Here we provide a protocol for conducting experimental evolution of yeast using chemostats, including fitness measurement and whole genome sequencing of evolved clones or populations collected during the experiment. Depending on the number of generations appropriate for the experiment, the number of samples tested and the sequencing platform, this protocol takes from 1 month to several months to be completed, with the possibility of processing several strains or mutants at once.
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