Adaptive evolution of non coding DNA and gene expression divergence in Drosophila

果蝇非编码DNA的适应性进化和基因表达差异

基本信息

批准号：
8114194
负责人：
Peter Andolfatto
金额：
$ 29.33万
依托单位：
PRINCETON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-09-01 至 2014-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8114194
关键词：
Animals Biological Biological Assay Biological Models Biology Code Computing Methodologies Conserved Sequence Control Locus DNA DNA Databases Data Databases Development Drosophila genus Drosophila melanogaster Elements Evolution Experimental Models Functional RNA Gene Expression Gene Expression Process Gene Frequency Genes Genetic Genetic Models Genetic Polymorphism Genetic Transcription Genetic Variation Genetic screening method Genome Genomics Human Individual Introns Intuition Length Link Maps Measures Messenger RNA Methodology Methods MicroRNAs Molecular Genetics Natural Selections Nucleotides Organism Pattern Performance Population Population Genetics Predisposition Property Proteins Reading Recurrence Regulation Regulator Genes Regulatory Element Reporter Research Series Site Site-Directed Mutagenesis Surveys Testing Transcript Transgenes Transgenic Organisms Work base fitness genetic analysis genome-wide human disease improved innovation insight novel novel strategies pressure public health relevance research study trait

项目摘要

DESCRIPTION (provided by applicant): A growing body of evidence supports the view that regulatory evolution - the evolution of where and when a gene is expressed - is the primary genetic mechanism behind the modular organization, functional diversification, and origin of novel traits in higher organisms. Most elements regulating gene expression in eukaryotic genomes reside in noncoding DNA (i.e. DNA that does not encode protein). Recent studies suggest that much of the noncoding portion of the Drosophila melanogaster genome is evolutionarily constrained, implying that these regions are important for an organism<s fitness and may be the target of substantial adaptive evolution. We propose to use a combination of novel computational and experimental approaches to 1) identify cis-regulatory untranslated transcribed regions (UTRs) that may have been targets of recurrent adaptive evolution and 2) experimentally test the effects of putatively functional substitutions on levels of gene expression divergence between species. We will begin by collecting population genomic variability data from 25 naturally occurring strains of D. simulans for all 5< and 3<UTRs with full length transcripts (~2.2Mb) and a control reference panel of closely-linked short introns and coding sequence (~5.8Mb). We will use and further develop computational methods to identify UTRs that have accumulated adaptive sequence divergence between species using population genetic data of this kind. Specifically, we will explore to what extent using the allelic frequency spectrum and integrating this new data with emerging population genomic data for D. melanogaster can improve the fidelity of population genetic tests for selection. We will then use D. melanogaster as an experimental model to functionally verify predictions based on computational methods. Specifically, we will use a transgene co-placement method to determine the effects of 3<UTR divergence on gene expression divergence and test alternative hypotheses about how individual functional substitutions interact and contribute to changes in gene expression. These experiments will, in turn, be used to refine our computational prediction methods. This research will identify new cis- regulatory elements, develop novel methodologies for mapping such elements and provide important insights into how gene regulatory changes have led to the evolution of new species and diversity in animal forms. The computational methods and biological intuitions we develop will be widely applicable to other model systems, including humans. PUBLIC HEALTH RELEVANCE: Changes in genetic regulation contribute to adaptations in natural populations and influence susceptibility to human diseases (Gilad et al. 2008; Gobbi et al. 2006). Despite their potential phenotypic importance, the selective pressures acting on regulatory processes and gene expression levels in particular are largely unknown. Our research combines computational and experimental approaches to study how natural selection acts on genetic variation underlying both beneficial and detrimental functional differences in gene expression. This work will significantly improve our understanding of biology of human diseases caused by the misexpression of genes.

描述（由申请人提供）：越来越多的证据支持这一观点，即调控进化（基因表达地点和时间的进化）是高等动物中模块化组织、功能多样化和新性状起源背后的主要遗传机制。有机体。真核基因组中调节基因表达的大多数元件位于非编码 DNA（即不编码蛋白质的 DNA）中。最近的研究表明，果蝇基因组的许多非编码部分在进化上受到限制，这意味着这些区域对于生物体的适应性很重要，并且可能是实质性适应性进化的目标。我们建议结合使用新颖的计算和实验方法来1）识别可能是循环适应性进化目标的顺式调节非翻译转录区域（UTR），2）通过实验测试推定的功能替代对基因表达水平的影响物种之间的分歧。我们将首先从 25 个天然存在的拟假丝虫菌株中收集所有 5< 和 3<UTR 的群体基因组变异数据，这些数据具有全长转录本 (~2.2Mb) 以及紧密相连的短内含子和编码序列的对照参考面板 ( ~5.8Mb）。我们将使用并进一步开发计算方法来识别利用此类群体遗传数据在物种之间积累了适应性序列分歧的UTR。具体来说，我们将探索在多大程度上使用等位基因频谱并将这些新数据与黑腹果蝇的新兴群体基因组数据相结合可以提高群体遗传选择测试的保真度。然后，我们将使用黑腹果蝇作为实验模型，对基于计算方法的预测进行功能验证。具体来说，我们将使用转基因共置方法来确定 3<UTR 差异对基因表达差异的影响，并测试关于个体功能替换如何相互作用并导致基因表达变化的替代假设。这些实验反过来将用于完善我们的计算预测方法。这项研究将识别新的顺式调控元件，开发绘制这些元件图谱的新方法，并为基因调控变化如何导致新物种的进化和动物形态的多样性提供重要见解。我们开发的计算方法和生物直觉将广泛适用于包括人类在内的其他模型系统。公共卫生相关性：遗传调控的变化有助于自然种群的适应并影响对人类疾病的易感性（Gilad 等人，2008 年；Gobbi 等人，2006 年）。尽管它们具有潜在的表型重要性，但作用于调控过程和基因表达水平的选择压力在很大程度上还是未知的。我们的研究结合了计算和实验方法来研究自然选择如何作用于基因表达中有益和有害的功能差异背后的遗传变异。这项工作将显着提高我们对基因错误表达引起的人类疾病生物学的理解。