Evolutionary Modeling/Prediction of ncRNA Genes in Flies

描述（由申请人提供）：使用概率进化模型是比较基因组学的一个组成部分。应用包括设计进化基因查找软件；筛选待选位点的编码DNA序列；基因组调控元件的鉴定；改进了同源物的检测；以及有害snp的预测。这样的进化模型仍然不发达，特别是对于仅以非编码RNA （ncRNA）表达的基因亚类。然而，生物医学对这类基因的兴趣越来越大：现在怀疑microrna可以调节广泛的靶标，并被病毒用来沉默宿主转录；小干扰rna正在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位点，如HIV的Rev反应元件）；最近在原核生物中发现了被称为“核糖开关”的RNA基序，与基因工程的“适体”相呼应，它们具有区别性地结合小分子配体的能力；许多催化ncrna（“核酶”）在人类和细菌细胞中都很活跃；许多上述技术（如核开关/核酸适体/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。

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.