The distribution of epistatic effects within and between genes

突变是进化和遗传疾病的重要组成部分。突变对生物体的影响可以是积极的，消极的或中性的。 然而，单独具有一种效应的突变在与基因组中其他地方的另一种突变组合时可能具有相反的效应。这种现象被称为上位性，显然会影响进化机制和遗传疾病，但对其影响的范围或程度知之甚少。 这项研究将提供最广泛的系统研究内和两个基因之间的上位性。收集和分析的数据将为未来的实验室和建模实验提供信息，以解决有关进化和遗传疾病机制的重要问题。在这项研究的过程中，两个博士前的学生和一个本科生将在研究培训。该研究将被纳入由主要研究者教授的蛋白质工程课程中。该项目将检查（1）细菌基因TEM 1 β-内酰胺酶（TEM-1）和β-内酰胺酶抑制剂蛋白（BLIP）的几乎所有单个氨基酸突变的适合度分布，（2）在这些基因中的每一个内的5000个双突变等位基因的广泛集合的适合度分布，（3）TEM-1和BLIP的5000对等位基因的适合度分布，其中每个基因都有一个氨基酸突变。将使用主要研究者开发的新型DNA诱变和带通遗传选择技术（广泛使用下一代测序）估计各品系的适应性指数。上位效应的分布将通过来自单氨基酸取代的适合度数据与来自双突变体系中那些相同取代的适合度数据的定量比较来确定。这种适合度效应的分布将用于评估整个基因组中上位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.