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：
8303418
负责人：
Peter Andolfatto
金额：
$ 29.31万
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/8303418
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 Expression Profile 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了这样一种观点，即监管进化 - 表达基因的何时何时和何时表达基因的演变 - 是模块化组织，功能多样化和新型特征在较高生物体中的主要遗传机制。调节真核基因组基因表达的大多数元素都存在于非编码DNA中（即未编码蛋白质的DNA）。最近的研究表明，果蝇果蝇基因组的许多非编码部分在进化上都是限制的，这意味着这些区域对有机体的适应性很重要，并且可能是实质性适应性进化的目标。我们建议将新型计算方法和实验方法的组合组合到1）确定可能是经常性适应性进化的靶标的顺式调节的未翻译转录区（UTRS），并且2）实验测试了推杆功能替代对基因表达水平之间的影响的影响。我们将首先收集来自所有5 <and 3 <utrs的25个天然发生的D. simulans菌株的种群基因组变异性数据，这些菌株具有全长转录本（〜2.2MB）（〜2.2Mb）和密切链接的短篇内含子和编码序列（〜5.8MB）的控制参考面板。我们将使用并进一步开发计算方法来识别使用这种种群遗传数据在物种之间积累自适应序列差异的UTR。具体而言，我们将使用等位基因频率谱探索在多大程度上，并将这些新数据与新兴的人群基因组数据集成为D. Melanogaster可以提高种群基因测试的选择的忠诚度。然后，我们将使用D. melanogaster作为实验模型来基于计算方法在功能上验证预测。具体而言，我们将使用转基因共序列方法来确定3 <utr差异对基因表达差异的影响，并检验有关单个功能替代如何相互作用并有助于基因表达变化的替代假设。这些实验将依次用于完善我们的计算预测方法。这项研究将确定新的调节元素，开发出新的方法来映射此类元素，并提供有关基因调节变化如何导致新物种发展和动物形式多样性的重要见解。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：遗传调节的变化有助于自然种群的适应和影响对人类疾病的易感性（Gilad等，2008； Gobbi等，2006）。尽管具有潜在的表型重要性，但在很大程度上尚不清楚作用于调节过程和基因表达水平的选择性压力。我们的研究结合了研究自然选择如何对基因表达中有益和有害功能差异的基础遗传变异作用的计算方法和实验方法。这项工作将大大提高我们对基因的症状引起的人类疾病生物学的理解。