Evolutionary Modeling/Prediction of ncRNA Genes in Flies

描述(申请人提供)：概率进化模型的使用是比较基因组学不可分割的一部分。应用包括进化基因寻找软件的设计；筛选被选择位点的编码DNA序列；识别基因组中的调控元件；改进同源基因的检测；以及有害SNPs的预测。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，人们对这类基因的生物医学兴趣与日俱增：microRNAs现在被怀疑调节广泛的靶标，并被病毒用来沉默宿主转录；小干扰RNAs正被探索作为一种治疗方法；存在专门针对RNA结构的药物(例如细菌核糖体或逆转录病毒结合部位，如HIV的REV反应元件)；被称为“核糖开关”的RNA基序，呼应了最近在原核生物中发现的具有区别结合小分子配体能力的基因工程的“适配子”；许多催化的ncRNAs(“核酶”)在人类和细菌细胞中具有活性；许多上述技术(例如核糖开关/适配子/核酶)正开始被合成生物学家利用，例如作为具有巨大生物医学潜力的新型报告结构。 在这里，我们建议为一个集中的、生物可检验的案例研究开发ncRNA进化模型：通过对12个果蝇基因组的比较分析来识别ncRNA基因。在计算上，我们将使用这个例子来推动我们在RNA分析和进化建模方面的正在进行的方法开发，使我们成功的“xrate”和“stemloc”程序用于进化随机上下文无关文法。在实验上，我们将在我们的合作者和当地可用的资源(如伯克利果蝇基因组计划的cDNA文库)的帮助下，通过RT-PCR和测序等湿实验室验证方法来验证我们的预测。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.