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

我的团队继续致力于研究计算方法，以研究生物网络的动态，遗传变异和结构变异对基因表达的影响，生物表型和复杂疾病。 特别是，我们继续致力于描述复杂性状背后的遗传交互作用的方法。我们关注的是上位性互作，即两个基因座对数量性状的非加性/非独立效应。在我们最近发表的(1)中，我们发展了一种预测上位性相互作用的新方法，并将其应用于研究疟原虫的相互作用图谱，发现了这种生物基因组中存在的上位性相互作用热点。我们还启动了酵母耐药表型基因座相互作用的研究。 我们继续研究拷贝数变化对SON基因表达的影响这个问题。拷贝数变异(CNV)是一种常见的多态类型，常引起遗传异常，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影响的前提。人们通常认为，基因拷贝数的增加意味着某一特定基因的表达增加。与Brian Oliver小组合作，我们对基因剂量对基因表达的影响以及这些影响在苍蝇相互作用网络中的传播进行了实验和计算研究(2)。我们的研究表明，CNV变异与基因表达之间的关系更加复杂和依赖于基因。 我们的另一项研究涉及DNA和RNA结构。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合作)以及突变对RNA结构的影响及其与疾病的关系(与Michael Gottesman合作；Chava Kimchi-Sarfaty)。单核苷酸多态(SNPs)常与疾病或对疫苗、药物和环境因素的反应等关键表型相关。然而，引起SNP的具体分子机制通常并不明显，RNA二级结构的变化越来越多地成为一种可能的解释。我们假设，为了测量这种影响，人们必须考虑RNA构象的整个Boltzmann集合，并比较天然结构和突变体的Boltzmann使能。这一假设是我们工作的基础，我们研究了一种新的强大的方法来衡量SNP/突变对RNA结构的影响，该方法已被选为RECOMB 2012的口头报告，该会议属于计算生物学的顶级会议。描述这部作品的手稿已提交。 我们还在RNA结构方面的工作中增加了一个新的方面。具体地说，我们与FDA Zuben Sauna合作，开始了对适配子性质的实验和计算研究。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，并被选为ISMB 2012的口头报告，这是另一个顶级计算生物学会议。 从复杂疾病的研究到单细胞表达的分析，我们已经扩展了对开发计算方法来分析不同数据的兴趣。在同基因细胞群体中，基因表达的随机性促进了细胞间蛋白质水平的差异，通常被称为噪声。包括TATA盒的存在在内的几个转录特征与表达噪音的增加有关。我们研究了已知或假定伴随翻译效率的序列特征在多大程度上也与噪声差异相关的问题。值得注意的是，我们发现与高tRNA适应指数相关的对噪声强度的影响与TATA盒的存在的影响相当，这表明翻译起源的噪声被大大低估了。我们最近在《公共科学图书馆·计算生物学》上发表了这些结果。 最后，我们继续与其他小组合作，应用我们的计算专业知识，包括进化分析(5，6)、疾病研究(7)和重组热点(8)。

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).