The distribution of epistatic effects within and between genes

突变是进化和遗传病的重要组成部分。突变对生物体的影响可以是积极的、消极的或中性的。然而，单独产生一种类型影响的突变，当与基因组其他地方的另一种突变结合时，可能会产生相反的效果。这种现象被称为上位性，明显影响进化机制和遗传性疾病，但人们对其影响的程度或程度知之甚少。这项研究将提供迄今为止关于两个基因内和两个基因之间上位性的最广泛的系统研究。收集和分析的数据将为未来的实验室和模拟实验提供信息，以解决关于进化和遗传病潜在机制的重要问题。在本次研究过程中，将对两名博士前学生和一名本科生进行研究培训。这项由基金资助的研究将被纳入由首席研究员教授的蛋白质工程课程。这项计划将检查(1)细菌基因TEM1β-内酰胺酶(TEM1)和β-内酰胺酶抑制蛋白(BLIP)几乎所有单一氨基酸突变的适合度分布，(2)每个基因内5000个双突变等位基因的广泛集合的适合度分布，(3)每个基因都有一个氨基酸突变的5000对TEM1和BLIP的广泛等位基因的适合度分布。将使用首席研究人员开发的新的DNA突变和带通基因选择技术，并广泛使用下一代测序，来评估每一株系的适合度指数。上位性效应的分布将通过将来自单个氨基酸替换的适合度数据与来自双突变系中相同替换的适合度数据进行定量比较来确定。这种适合度效应的分布将被用来评估整个基因组上位性相互作用的频率和强度。

Mutations are an important part of evolution and genetic diseases. A mutation's effect on an organism can be positive, negative or neutral. However, mutations that have one type of effect in isolation can have the opposite effect when combined with another mutation elsewhere in the genome. This phenomenon, termed epistasis, clearly affects evolutionary mechanisms and genetic diseases, yet relatively little is known about its extent or degree of impact. This research will provide the most extensive systematic study of epistasis within and between two genes to date. The data collected and analyzed will inform future laboratory and modeling experiments to address important questions about evolution and the mechanisms underlying genetic disease. During the course of this research, two pre-doctoral students and one undergraduate will be trained in research. The research supported by the grant will be incorporated into a class on protein engineering taught by the principle investigator.This project will examine (1) the fitness distribution of nearly all single amino acid mutations for the bacterial genes TEM1 beta-lactamase (TEM-1) and the beta-lactamase inhibitor protein (BLIP), (2) the fitness distribution of an extensive set of 5000 double mutant alleles within each of those genes, (3) the fitness distribution of an extensive set of 5000 pairs of alleles of TEM-1 and BLIP in which each gene has one amino acid mutation. An index of fitness will be estimated for each line using novel DNA mutagenesis and band-pass genetic selection technologies developed by the principal investigator with the extensive use of next generation sequencing. The distribution of epistatic effects will be determined by a quantitative comparison of the fitness data from the single amino acid substitutions with the fitness data from those same substitutions in the double mutant lines. This distribution of fitness effects will be used assess the frequency and strength of epistatic interactions across the genome.