Fitness analyses of all possible point mutations for regions of genes in yeast.

Fitness analyses of all possible point mutations for regions of genes in yeast.
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DOI:
10.1038/nprot.2012.069
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发表时间:
2012-06-21
期刊:
影响因子:
14.8
通讯作者:
Bolon, Daniel N. A.
Bolon, Daniel N. A.
中科院分区:
生物学1区
文献类型:
--
作者:
Hietpas, Ryan;Roscoe, Benjamin;Jiang, Li;Bolon, Daniel N. A.

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深度测序可以在单个批量竞争实验中准确测量数百个突变体的相对丰度,这可以直接读出每个突变体的适应度。在这里,我们描述了一个协议,我们以前开发和优化,以测量所有可能的个人密码子取代的健身效果的10个氨基酸区域的必需基因在酵母。从条件菌株(即,温度敏感菌株),我们描述了如何有效地产生点突变体的质粒文库,然后可以转化点突变体以产生酵母文库。酵母文库在选择突变体功能的条件下竞争。深度测序分析用于确定所有突变体的相对适合度。与分析单独分离的突变体相比,这种方法对于每个突变体更快、更便宜。该方案可以在约4周内进行,并且可以平行分析许多10个氨基酸区域。
Deep sequencing can accurately measure the relative abundance of hundreds of mutants in a single bulk competition experiment, which can give a direct readout of the fitness of each mutant. Here, we describe a protocol that we previously developed and optimized to measure the fitness effects of all possible individual codon substitutions for 10 amino acid regions of essential genes in yeast. Starting with a conditional strain (i.e., a temperature sensitive strain), we describe how to efficiently generate plasmid libraries of point mutants that can then be transformed to generate libraries of yeast. The yeast libraries are competed under conditions that select for mutant function. Deep sequencing analyses are used to determine the relative fitness of all mutants. This approach is faster and cheaper per mutant compared to analyzing individually isolated mutants. The protocol can be performed in ~4 weeks and many 10 amino acid regions can be analyzed in parallel.
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发表时间: 2010-11-05
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影响因子: 56.9
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