STATISTICAL APPROACHES TO INTEGRATION OF MASS SPECTRAL AND GENOMIC DATA OF YEAS

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 真核细胞中的基因活性受转录因子和染色质结构的共同调控。人们已经进行了广泛的研究，以了解不同的转录因子如何被招募来激活或抑制基因表达，以响应不同的环境条件。然而，在探讨染色质的调节作用方面的研究仍然非常有限。染色质的基本重复单位是核小体，核小体是一个八聚体，包含四个核心组蛋白的两个副本。这些组蛋白的共价修饰组合引导染色质-DNA相互作用，进而影响基因转录、复制和重组。尽管如此，确切的机制仍然难以捉摸。最近，用于检测和定位组蛋白修饰的高分辨率质谱学和全基因组微阵列已经成为可能，这为研究人员提供了一个前所未有的机会来描绘组蛋白修饰的调节作用。这项拟议的工作将结合酿酒酵母的高分辨率质谱学和基因组数据来建立计算模型，以估计组蛋白修饰对酵母中转铁蛋白结合和基因表达的影响。综上所述，这项拟议的工作将提供一个独特的视角，通过有效地整合来自序列、基因表达、组蛋白修饰和核小体数据的信息来验证组蛋白密码假说。我们将：1.开发用于多变量反应模型的无连接模型选择方法，以确定组蛋白修饰的靶基因。2.结合DNA序列、核占有率以及全基因组的组蛋白修饰数据，建立组蛋白修饰的DNA序列特征的计算和统计方法。3.发展计算和统计方法来预测组蛋白修饰及其相互作用。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Gene activities in eukaryotic cells are concertedly regulated by transcription factors and chromatin structure. Extensive studies have been done to understand how various transcription factors are recruited to activate or repress gene expression in response to different environmental conditions. However, researches in probing the regulatory role of chromatin are still very limited. The basic repeating unit of chromatin is the nucleosome, an octamer containing two copies of each of four core histones. Combinations of covalent modifications of these histones guide the chromatin-DNA interaction and in turn affects gene transcription, replication, and recombination. Nonetheless, the precise mechanism remains elusive. Recently, high resolution mass spectrometry and genome-wide microarray for detection and localization of histone modifications have become available, offering researchers an unprecedented opportunity to delineate the regulatory role of histone modifications. The proposed work will combine high-resolution mass spectral and genomic data for Saccharomyces cerevisiae to build computational models to estimate the effect of the histone modifications on TF binding and gene expression in yeast. Taken together, the proposed work will provide a unique perspective to test the histone code hypothesis through effectively integrating information from sequence, gene expression, histone modification, and nucleosome data. We will: 1. Develop link-free model selection methods for the multivariate response model to identify target genes of histone modifications. 2. Develop computational and statistical methods to identify the DNA sequence features of histone modifications through integrating the expression values of genes, with the combination of the DNA sequence, nuclesome occupancy as well as genome-wide histone modification data. 3. Develop computational and statistical methods to predict histone modifications and their interactions.