Molecular Structure of Animal Viruses and Cells

我们的研究目标强调开发新颖，复杂的算法，集成了RNA折叠，模式搜索，序列和结构比较的统计和计算工具。这些工具可以发现非编码（ncrna）和功能性RNA元件，并能够分析完整的基因组序列。我们在过去一年中取得的科学成就总结如下：开发用于分析RNA结构的计算机算法，发现非RNA、RNA基序和RNA功能元件。功能性RNA具有独特的RNA结构基序，由碱基对和环区保守核苷酸的特定组合所代表。在全基因组搜索中发现不同的有序结构及其同源物将增强我们发现RNA结构基序的能力，并帮助我们突出它们与功能性ncrna和调控RNA元件的关联。与张教授实验室合作。（university of Computer Science, university of Western Ontario, London, Ontario, Canada），我们开发了一种新的计算机算法homstrscan，它采用单个RNA序列及其二级结构来搜索完整基因组中的同源RNA。这种新算法与目前使用的其他同源结构或结构基序的搜索算法在两个重要方面完全不同：首先，它详细考虑了查询RNA的一级序列和二级结构约束信息，包括双链中的每个碱基对和单链中的每个核苷酸；其次，同源RNA结构严格推断从一个稳健的统计分布的定量措施，最大相似性得分。该方法为任何同源结构rna的搜索提供了灵活、稳健和精细的工具。为了测试这个新程序，我们在细菌基因组数据库中搜索了5S rRNA和tRNA。我们对20多个细菌基因组的研究结果表明，homstrscan发现这些ncrna具有很高的灵敏度/特异性。我们对这些完整基因组序列的计算实验表明，homstrscan检测到100%的真实5S rRNAs，没有假阳性。此外，homstrscan在一些细菌基因组中发现了新的5S rRNA基因，这些基因目前没有在数据库中标注。homstrscan还可以以非常高的灵敏度/特异性比发现基因组序列中的trna，即使这些trna含有内含子。我们对K.lactis酵母基因组10.6 Mb的tRNA基因的测试正确预测了已发表数据库中列出的所有tRNA基因，并预测了另外31个tRNA，其中大多数在反密码子环内具有不同大小的内含子序列。总的来说，我们的方法可以用来搜索任何已经建立二级结构的RNA片段。对于已知的ncrna . b，正在使用homstrscan和rna_match进行大规模的ncrna搜索。开发用于基因组序列中局部良序结构统计推断的StemEd和SigStem计算机程序。microRNAs （miRNAs）的发现表明真核生物基因组中存在着一类小的非编码rna。这些mirna有可能形成独特的、向后折叠的茎环结构。基因组序列中这些有序折叠序列（WFS）的预测有助于我们理解基于RNA的基因调控以及确定具有结构依赖功能的局部RNA元件。以前，我们开发了EDscan和SigED，它们能够通过扫描序列的连续片段并评估自然序列和随机打乱序列计算的E_diff之间的差异来发现这种不同的WFS。这里给定RNA片段的E_diff度量与之前的EDscan方法定义的相同，E_diff是片段中折叠的全局最小能量结构与其对应的最优约束结构（ORS）之间的自由能差，其中最低自由能结构中的所有先前的碱基对都被禁止。使用标准z分数SigZscr，我们可以估计E_diff在真实生物段中的行为，并根据E_diff在被测随机样本中的一般行为做出稳健的统计推断。然而，EDscan和SigED的计算复杂度与扫描窗口长度的立方成正比。因此，在搜索整个人类基因组时，计算量非常大。由于对于miRNA，我们只对相对简单，独特的折叠，茎环结构感兴趣，因此在基因组序列中搜索这些miRNA前体时，我们改进了算法，只考虑茎环结构。因此，StemEd和SigStem算法包含了EDscan和SigED的所有功能，但计算复杂度降低到与窗口长度的平方成正比。此外，新方法的预测能力对扫描窗口的选择不太敏感。这对于发现基因组序列中未知的结构基序和ncrna尤其有利。我们的研究结果和所有已知miRNA前体的统计检验表明，StemEd和SigStem在基因组序列中检测到的具有统计学意义的WFS与miRNA前体中发现的已知折叠茎环一致。在统计检验中，我们包括了人类207个miRNA前体、小鼠208个、大鼠187个、鸡121个、黑腹果蝇78个、秀丽隐杆线虫116个、briggsae隐杆线虫50个、拟南芥92个和水稻122个miRNA前体。我们正在继续进行详细的分析，并打算在其他物种中发现不同的有序折叠模式，并期望它们是潜在的mirna。序列数据库中dsRNA大片段和RNA功能元件的数据挖掘。RNA沉默研究的最新进展表明，双链RNA （dsRNA）可以在真核生物中用于阻断相应细胞基因的表达。在RNAi途径中，dsRNAs作为初始触发器，被称为“Dicer”的核糖核酸酶剪切，并可能导致mRNA异常。我们在3'UTR数据库中搜索茎状dsrna。3'UTRs中dsRNA结构的发生率从植物的0.01%到脊椎动物mrna的0.30%不等。这些茎状的dsrna在蒙特卡罗模拟中被预测为非常重要的，并且在RNA结构预测中被很好地确定。数据库中不同的dsRNA结构可以用来检验3'UTR中内源性dsRNA的性质以及它们诱导RNAi的可能性的假设。我们与姜博士的实验室合作进行了HIV-1诱导和抑制RNA干扰的研究。(摩尔性研究。分子微生物实验室。， niaid, nih)。我们的研究结果表明，虽然短干扰rna已被人为地用于沉默病毒感染，但没有直接证据表明天然病毒序列在哺乳动物细胞中引起这种免疫。我们的计算在大约500个HIV和相关序列中发现了一系列19个碱基对的dsRNAs。保守的，自然产生的19个碱基对的dsRNA在人类细胞中引起抗病毒RNA干扰。有趣的是，HIV已经进化出一种RNA沉默抑制因子，体现在其Tat蛋白中，以对抗这种诱导的RNA干扰。它通过功能上废除Dicer活性来抑制RNA沉默。我们的研究结果表明，它是预处理的，短的，干扰siRNA，但不需要加工的长干扰liRNA或短发夹shRNA，应该是抑制HIV-1感染的首选考虑因素。

Our research goal emphasizes developing novel, sophisticated algorithms that integrate statistical and computational tools for RNA folding, pattern search, sequence and structure comparison. These tools find non-coding (ncRNAs) and functional RNA elements, and enable analyses of complete genome sequences. Our scientific accomplishments during the past year are summarized as follows:A. Development of computer algorithms for analyses of RNA structures and the discovery of ncRNAs, RNA motifs and RNA functional elements.Functional RNAs have characteristic RNA structural motifs represented by specific combinations of base pairings and conserved nucleotides in loop regions. Discovery of distinct well-ordered structures and their homologues in genome-wide searches will enhance our ability to discover RNA structural motifs and help us to highlight their association with functional ncRNAs and regulatory RNA elements. In collaboration with Prof. Zhang's Lab. (Dept. of Computer Science, Univ. of Western Ontario, London, Ontario, Canada), we developed a novel computer algorithm , HomoStRscan, that takes a single RNA sequence along with its secondary structure to search for homologous RNAs in complete genomes. This novel algorithm differs completely from other currently used search algorithms for homologous structures or structural motifs in two important aspects: first, it takes detailed account of information of both the primary sequence and the secondary structural constraints of the query RNA including each base-pair in duplexes and each nucleotide in the single strands; second, the homologous RNA structures are strictly inferred from a robust statistical distribution of a quantitative measure, maximal similarity score. The method provides a flexible, robust and fine search tool for any homologous structural RNAs. To test this novel program we searched for 5S rRNA and tRNA in bacterial genome databases. Our results from more than 20 bacterial genomes indicate that HomoStRscan discovers these ncRNAs with high sensitivity/specificity ratios. Our computational experiments for these complete genomic sequences indicate that HomoStRscan detects 100% of the true 5S rRNAs with no false positives. Moreover, HomoStRscan finds new 5S rRNA genes in several bacterial genomes that are not currently annotated in the database.HomoStRscan can also discover tRNAs in the genomic sequences with very high sensitivity/specificity ratios, even if those tRNAs have introns. Our test for tRNA genes in K.lactis yeast genome of 10.6 Mb correctly predicts all tRNA genes listed in published databases, and also predicts an additional 31 tRNAs, most of which have intron sequences of various sizes within the anticodon loop.In general, our method can be used to search for any RNA segments that have established secondary structure. The search for ncRNAs is being conducted on a large scale using HomoStRscan and rna_match for known ncRNAs.B. Development of computer programs StemEd and SigStem for the statistical inference of local well-ordered structures in genomic sequences.Discovery of microRNAs (miRNAs)suggests that there are a large class of small non-coding RNAs in eukaryotic genomes. These miRNAs have the potential to form distinct, fold-back, stem-loop structures. The prediction of these well-ordered, folding sequences (WFS) in genomic sequences is very helpful for our understanding of RNA-based gene regulation and the determination of local RNA elements with structure-dependent functions. Previously, we developed EDscan and SigED that have the power to discover such distinct WFS by scanning successive segments along a sequence and evaluating the difference between E_diff of the natural sequence and those computed from randomly shuffled sequences. The measure E_diff of a given RNA segment here is same as was defined in the previous EDscan method, where E_diff is the difference of free energies between the folded global, minimal energy structure in the segment and its corresponding optimal, restrained structure (ORS) where all the previous base pairings in the lowest free energy structure are forbidden. Using a standard z-score, SigZscr, we can estimate the behavior of E_diff in the real biological segment and make a robust statistical inference based on the general behavior of E_diff in the tested random sample. However, the computational complexity of EDscan and SigED is directly proportional to the cube of the scanning window length. Thus it is very compute intensive in searching the whole human genome. Since for miRNAs we are interested in relatively simple, distinct fold-back, stem-loop structures only in the search of those miRNA precursors in the genomic sequence we improved our algorithm to consider only stem-loop structures. Consequently, the new algorithms StemEd and SigStem contain all the power of EDscan and SigED, but the computational complexity was reduced to be directly proportional to the square of the window length. In addition, the predicting ability of the new method is less sensitive to the selection of the scanning window. This is especially advantageous in discovering unknown structural motifs and ncRNAs in genomic sequences.Our results and statistical test from all known miRNA precursors indicate that the statistically significant WFS detected by StemEd and SigStem in genomic sequences are coincident with known fold-back stem-loops found in the miRNA precursors. In statistical tests, we include 207 miRNA precursors of human, 208 of mouse, 187 of rat,121 of G. gallus, 78 of Drosophila melanogaster, 116 of Caenorhabditis elegans, 50 of Caenorhabditis briggsae, 92 of Arabidopsis thaliana and122 miRNA precursors of Oryza sativa.We are continuing the detailed analysis and intend to find distinct well-ordered folding patterns in other species and expect them to be potential miRNAs.C. Data mining of large dsRNA segments and RNA functional elements in sequence databases.Recent developments in the study of RNA silencing indicate that double-stranded RNA (dsRNA) can be used in eukaryotes to block expression of a corresponding cellular gene. In the RNAi pathway, dsRNAs serve as the initial triggers that are chopped by an ribonuclease termed "Dicer" and may result in aberrant mRNA. We search for the stalk-like dsRNAs in the 3'UTR database. The occurrence rate of the dsRNA structures in 3'UTRs ranges from 0.01% in plant to 0.30% in vertebrate mRNAs. These stalk-like dsRNAs are predicted to be very significant in Monte Carlo simulations and are well-determined' in RNA structure predictions. The distinct dsRNA structures in the database can be used to test the hypothesis for the nature of endogenous dsRNAs in the 3'UTR and the possibility that they can induce RNAi. We collaborated on studies of induction and suppression of RNA interference by HIV-1 with Dr. Jeang's Lab. (Mol. Virol. Section, Lab of Mol. Microbio., NIAID, NIH). Our results indicate that although short interfering RNAs have been used artificially to silence viral infections, no direct evidence exists that natural viral sequences provoke such immunity in mammalian cells. Our computation discovers a series of dsRNAs of 19 base-pair sin about 500 HIV and related sequences. The conserved, naturally occurring 19 base-pair dsRNA elicits antiviral RNA interference in human cells. Interestingly, HIV has evolved a suppressor of RNA silencing embodied in its Tat protein to combat this induced RNA interference. And Tat suppresses RNA silencing through a functional abrogation of Dicer activity. Our results suggest it is the pre-processed, short, interfering siRNA, but not processing-requiring long interfering liRNA nor short hairpin shRNA, that should be the preferred consideration for inhibiting HIV-1 infections.