Combinatorial and graph theoretical approach to systems biology and mol. evo.

系统生物学和分子生物学的组合和图论方法。

• 批准号: 8558125
• 负责人: Teresa Przytycka
• 金额: $ 171.37万
• 依托单位: NATIONAL LIBRARY OF MEDICINE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8558125
• 关键词: Binding; Bioinformatics; Biological; Cells; Collaborations; Complex; Computational Biology; Computing Methodologies; Copy Number Polymorphism; DNA; DNA Structure; Data; Dependency; Disease; Dose; Drug resistance; Elements; Environmental Risk Factor; Evolution; Gene Dosage; Gene Expression; Gene Expression Regulation; Genes; Genetic; Genetic Polymorphism; Genetic Recombination; Genetic Transcription; Genetic Variation; Genome; Genotype; Graph; Growth Factor Gene; Language; Link; Malignant Neoplasms; Manuscripts; Maps; Measures; Methods; Molecular; Mutation; Nature; Noise; Oral; Organism; Pharmaceutical Preparations; Phenotype; Plasmodium; Play; Population; Property; Proteins; Publications; Publishing; RNA; Regulatory Element; Research; Role; Sauna; Signal Transduction; Single Nucleotide Polymorphism; Son; Structure; System; Systems Biology; TATA Box; Technology; Tertiary Protein Structure; Transfer RNA; Translations; Vaccines; Variant; Work; Yeasts; aptamer; base; biological systems; combinatorial; computer studies; conformer; fly; gene function; indexing; insight; interest; mathematical model; mutant; research study; response; symposium; theories; tool; trait

My group continued to work on computational methods to study the dynamics of biological networks, impact of genetic variations and structural variation on gene expression, organismal phenotype and complex diseases. In particular we continued to work on methods to delineate genetic interactions underlying complex traits. We focused on epistatic interactions, that is interactions which are characterized by a non-additive/non-independent effect of two loci on a quantitative trait. In our recent publication (1) we developed a new method to predict epistatic interactions and applied it to study the interaction map in Plasmodium discovering epistatic interaction hotspots present in the genome of this organism. We also initiated studies on loci interactions underlying yeast drug resistance phenotype. We continued to work on the question on the impact of copy number variation son gene expression. Copy number variations (CNV) are a frequent type of polymorphisms and often a disease causing genetic aberration especially in cancer. Understanding the effect of copy number on gene expression is prerequisite for systematic study of the effect of such variation on the whole molecular system. It is often assumed that increased gene copy number implies increased expression of a given gene. In collaboration with Brian Oliver group we preformed experimental and computational studies of the impact gene dose on gene expression and the propagation of these effects in the fly interaction network (2). Our studies demonstrated that relation between CNV variations and gene expression is more complex and gene dependent. Another line of our research relates to the DNA and RNA structures. Namely, we continued to study the relation of DNA structure and gene expression (collaboration with David Levens and Rafael Casellas) and the impact of mutations on RNA structure and their relation to disease (collaboration with Michael Gottesman; Chava Kimchi-Sarfaty). Single Nucleotide Polymorphisms (SNPs) are often linked to critical phenotypes such as diseases, or responses to vaccines, medications, and environmental factors. However, the specific molecular mechanisms by which a causal SNP acts is usually not obvious and changes in RNA secondary structure increasingly emerge as a possible explanation. We postulated that to measure such effects one has to consider whole Boltzmann ensemble of RNA conformers and compare Boltzmann enables of the native structure and the mutant. This postulate was the basis in our work on a new powerful method to measure the impact of a SNP/mutation on RNA structure has been selected for oral presentation on RECOMB 2012, which belong to the top conferences in Computational Biology. The manuscript describing this work is in submission. We also added a new aspect to our work on RNA structure. Specifically in collaboration with Zuben Sauna, FDA, we began experimental and computational studies of the properties of Aptamers. In particular we have developed a computational approach to identify sequence/structure motifs of SELEX derived aptamers. This work has been recently published in Bioinformatics (3) and selected for oral presentation at ISMB 2012 which is another top computational biology conference. We have extended our interest in developing computational methods to analyze heterogeneous data from study of complex diseases to analysis of singe cell expression. Within isogenic cell population, the stochastic nature of gene expression promotes cell-to-cell differences in protein level, usually referred to as noise. Several transcription features, including presence of TATA box has been linked to increased expression noise. We have investigated the question of to what extent sequence features known or postulated to accompany translation efficiency can also be associated with noise differential. Strikingly, we found that the impact on noise strength associated with high tRNA adaptation index is comparable to the impact of the presence of a TATA box indicating that the translation originated noise has been greatly underappreciated. We have recently published these results in PloS Computational Biology (4). Finally we continue to apply our computational expertise in collaboration with other group including evolutionary analysis (5,6), disease studies (7), and recombination hotspots (8).

我的小组继续研究计算方法，以研究生物网络的动力学，遗传变异的影响以及结构变异对基因表达，有机表型和复杂疾病的影响。 特别是，我们继续致力于描述复杂性状基础的遗传相互作用的方法。我们专注于上皮相互作用，即相互作用，其特征是两个基因座对定量性状的非腺激/非独立效应。在我们最近的出版物（1）中，我们开发了一种新方法来预测上皮相互作用，并将其应用于疟原虫中的相互作用图，发现该生物体基因组中存在的上皮相互作用热点。 我们还开始了有关酵母耐药性表型的基因座相互作用的研究。 我们继续谈到有关拷贝数变异儿子基因表达的影响的问题。拷贝数变化（CNV）是一种常见的多态性类型，通常是导致遗传像差的疾病，尤其是在癌症中。了解拷贝数对基因表达的影响是系统研究这种变异对整个分子系统的影响的先决条件。通常认为增加的基因拷贝数意味着给定基因的表达增加。 与Brian Oliver组合作，我们对基因剂量对基因表达的影响和计算研究进行了实验和计算研究，以及在蝇相互作用网络中这些影响的传播（2）。我们的研究表明，CNV变异与基因表达之间的关系更为复杂和依赖性。 我们研究的另一行与DNA和RNA结构有关。也就是说，我们继续研究DNA结构和基因表达的关系（与David Levens和Rafael Casellas的合作）以及突变对RNA结构的影响及其与疾病的关系（与Michael Gottesman的合作； Chava Kimchi-Sarfaty）。单核苷酸多态性（SNP）通常与关键表型有关，例如疾病或对疫苗，药物和环境因素的反应。 但是，因果SNP行为的特定分子机制通常并不明显，而RNA二级结构的变化越来越多地出现为可能的解释。我们假设要测量这种效果，必须考虑RNA构象异构体的整个Boltzmann集合，并比较Boltzmann启用天然结构和突变体。这一假设是我们在一种新的强大方法的工作中衡量SNP/突变对RNA结构的影响的基础，该方法已在RECOMB 2012上的口头呈现中选择，该方法属于计算生物学的顶级会议。 描述这项工作的手稿是在提交的。 我们还为RNA结构的工作添加了一个新方面。特别是与FDA的Zuben Sauna合作，我们开始对适体性质进行实验和计算研究。特别是我们开发了一种计算方法来识别SELEX衍生的适体的序列/结构基序。 这项工作最近发表在生物信息学（3）上，并在ISMB 2012上选择了口头介绍，这是另一个顶级计算生物学会议。 我们已经扩展了对开发计算方法的兴趣，以分析从研究复杂疾病的研究到分析单细胞表达的异质数据。在等生细胞群体中，基因表达的随机性促进了蛋白质水平的细胞对细胞差异，通常称为噪声。包括塔塔盒的存在，包括表达噪声增加的几个转录特征。我们已经研究了一个问题，即在何种程度上伴随翻译效率的序列特征也可能与噪声差异有关。令人惊讶的是，我们发现与高tRNA适应指数相关的噪声强度的影响与塔塔盒的存在的影响相媲美，这表明翻译起源的噪声被大大低估了。我们最近在PLOS计算生物学中发表了这些结果（4）。 最后，我们继续将计算专业知识应用于与其他小组的合作，包括进化分析（5,6），疾病研究（7）和重组热点（8）。