Evolutionary Modeling/Prediction of ncRNA Genes in Flies

描述（由申请人提供）：概率进化模型的使用是比较基因组学的组成部分。应用包括进化基因发现软件的设计;筛选编码DNA序列的选择下的网站;在基因组中的调控元件的鉴定;改进同源物的检测;和预测有害的SNP。这样的进化模型仍然不发达，特别是对于仅表达为非编码RNA（ncRNA）的基因亚类。然而，对这类基因的生物医学兴趣越来越大：现在怀疑microRNA调节广泛的靶点，并被病毒用来沉默宿主转录;小干扰RNA正在被探索作为治疗方法;存在专门靶向RNA结构的药物。（例如细菌核糖体，或逆转录病毒结合位点，如HIV的Rev反应元件）;最近在原核生物中发现了称为“核糖开关”的RNA基序，其在区别性结合小分子配体的能力方面与基因工程的“适体”相呼应;许多催化ncRNA（“核酶”）在人和细菌细胞中是有活性的;并且许多上述技术（例如核糖开关/适体/核酶）开始被合成生物学家开发，例如作为具有巨大生物医学潜力的新型报道构建体。 在这里，我们建议开发ncRNA进化模型的一个重点，生物学上可测试的案例研究：12果蝇基因组的比较分析的ncRNA基因的识别。在计算方面，我们将使用这个例子来推动我们正在进行的RNA分析和进化建模方法的发展，调整我们成功的“xrate”和“stemloc”程序，用于进化随机上下文无关语法。在实验上，我们将通过湿实验室验证方法（如RT-PCR和测序），在我们的合作者和当地可用资源（如伯克利果蝇基因组计划的cDNA文库）的帮助下，测试我们的预测。我们所有的软件都将在网上免费提供。

DESCRIPTION (provided by applicant): The use of probabilistic evolutionary models is an integral part of comparative genomics. Applications include design of evolutionary genefinding software; screening of coding DNA sequences for sites under selection; identification of regulatory elements in genomes; improved detection of homologues; and prediction of deleterious SNPs. Such evolutionary models remain under-developed, particularly for the subclass of genes expressed solely as noncoding RNA (ncRNA). However, there is increasing biomedical interest in this class of genes: microRNAs are now suspected to regulate a wide range of targets, and are used by viruses to silence host transcription; small interfering RNAs are being explored as a therapeutic treatment; drugs exist that specifically target RNA structure (e.g. bacterial ribosomes, or retroviral binding sites such as HIV's Rev Response Element); RNA motifs known as "riboswitches", echoing genetically- engineered "aptamers" in their ability to discriminatively bind small-molecule ligands, have recently been discovered in prokaryotes; many catalytic ncRNAs ("ribozymes") are active in human and bacterial cells; and many of the above technologies (e.g. riboswitches/ aptamers/ ribozymes) are beginning to be exploited by synthetic biologists e.g. as novel reporter constructs, with great biomedical potential. Here, we propose to develop ncRNA evolutionary models for a focused, biologically testable case study: the identification of ncRNA genes by comparative analysis of twelve fruit fly genomes. Computationally, we will use this example to drive forward our ongoing methods development in RNA analysis and evolutionary modeling, adapting our successful "xrate" and "stemloc" programs for use with evolutionary stochastic context-free grammars. Experimentally, we will test our predictions by wet-lab validation methods such as RT-PCR and sequencing, with the help of our collaborators and locally available resources such as the Berkeley Drosophila Genome Project's cDNA libraries. All our software will be freely available online.