Functional genomic approaches to duplicate gene evolution

描述（由申请人提供）：我实验室的长期目标是了解具有新功能的新基因是如何产生的，以及这些分子创新如何促进生物体的生存、适应和进化。基因复制被广泛认为是新基因的主要来源，但对重复基因功能分化的一般模式和机制尚不清楚。利用高通量基因组技术和前所未有的功能基因组数据，我们提出了实验和计算功能基因组方法来研究重复基因进化，有四个具体目标。首先，利用蛋白-蛋白相互作用（PPI）作为蛋白质功能的衡量指标，我们计划研究出芽酵母酿酒酵母（Saccharomyces cerevisiae）及其近亲瓦氏克卢维菌（Kluyveromyces waltii）之间复制和未复制基因的蛋白质功能变化率。该菌株在分离后不久发生了全基因组重复（WGD），并保留了约450对WGD重复序列。来自cerevisiae的PPI信息是公开的，而waltii的相应PPI将进行实验测试。其次，我们建议定制waltii基因表达微阵列，并将其与酿酒酵母的全基因组基因表达模式进行比较，以研究无重复和重复基因的表达模式在进化过程中的变化。类似的分析也将对公开可用的人类和小鼠的高质量微阵列数据进行。第三，关于单个生物体中的基因复制是否通过提供额外的蛋白质产品而立即获得适合度，是否通过浪费能量来制造不需要的额外产品而立即失去适合度，或者是否没有适合度变化，存在着相互竞争的假设。利用公开可用的酵母和哺乳动物的功能基因组数据，我们将通过计算来检验这些假设。然后，我们将使用酵母中不需要的外源蛋白质，实验测量酵母在不同水平上生产蛋白质的适应成本。第四，基因是否能在功能上弥补其复制副本的损失，这是一个有争议的问题。我们提出通过酵母实验对这种补偿假设进行严格的检验，在酵母实验中，我们测量了由用其平行基因的编码区替换基因编码区所引起的适应度变化。完全的蛋白质补偿预示着适应度不会改变，而缺乏补偿则会导致适应度降低。总之，这些研究有望显著提高我们对重复基因进化模式和机制的理解。

DESCRIPTION (provided by applicant): The long-term objective of my laboratory is to understand how new genes with novel functions originate and how these molecular innovations contribute to the survival, adaptation, and evolution of organisms. Gene duplication is wildly regarded as the primary source of new genes, but the general patterns and mechanisms of functional divergence of duplicate genes are not well understood. Taking advantage of high-throughput genomic technologies and unprecedented amount of functional genomic data, we propose experimental and computational functional genomic approaches to duplicate gene evolution, with four specific aims. First, using protein-protein interaction (PPI) as a measure of protein function, we plan to study the rate of protein functional change in duplicated and unduplicated genes between the budding yeast Saccharomyces cerevisiae and its relative Kluyveromyces waltii. The S. cerevisiae lineage experienced a whole-genome duplication (WGD) shortly after its separation from K. waltii and has retained ~450 pairs of WGD-duplicates. PPI information from S. cerevisiae is publicly available, while the corresponding PPIs in K. waltii will be experimentally tested. Second, we propose to make custom gene expression microarrays of K. waltii and compare its genome- wide gene expression pattern with that of S. cerevisiae to study how expression patterns of unduplicated and duplicated genes change in evolution. A similar analysis will also be conducted on the publicly available high-quality microarray data of the human and mouse. Third, competing hypotheses exist on whether gene duplication in an individual organism causes an immediate fitness gain by providing extra protein products, an immediate fitness loss by wasting energy for making extra products that are not needed, or no fitness change. Using publicly available functional genomic data of yeast and mammals, we will examine these hypotheses computationally. We will then experimentally measure in yeast the fitness cost of protein production at various levels, using foreign proteins that are not needed in yeast. Fourth, it is controversial as whether a gene can functionally compensate the loss of its duplicate copy. We propose a critical examination of this compensation hypothesis by a yeast experiment in which we measure the fitness change caused by replacing the coding region of a gene with that of its paralog. Complete protein compensation predicts no fitness change whereas an absence of compensation leads to fitness reduction. Together, these studies are expected to improve significantly our understanding of the patterns and mechanisms of duplicate gene evolution. PUBLIC HEALTH RELEVANCE: Our projects will increase understanding of mechanisms of gene evolution and aid many studies of how new biological functions arise. Our study is of human health relevance, because many gene copy number variations, generated by gene duplication, are involved in human diseases. Furthermore, different functional relationships among duplicate genes (e.g., completely redundant, partially overlapping, or distinctly different) would predict different consequences of mutations to the likelihood and severity of genetic diseases. A clear understanding of these relationships helps clarify the exact molecular basis of human diseases, a necessary step in the treatment and prevention of these diseases.