CAREER: Computational Analyses of the Interactions between DNA and Chromatin Structure

在这个项目中，研究人员将开发严格的数学方法来分析最近的高通量酵母核小体作图数据，并为研究DNA序列，核小体稳定性和核小体定位之间的关系提供新的计算工具。真核DNA具有复杂的三维结构，称为染色质，由数百万个核小体组成，核小体是蛋白质-DNA复合物，含有146个DNA碱基对，包裹着8个组蛋白。核小体通过控制DNA的可及性和调节转录因子的结合活性在调节基因表达中起着关键作用。因此，核小体是至关重要的，但目前还不存在严格的计算工具来研究生物信号，调节其定位和稳定性。本研究将发展分析核小体和连接DNA的光谱分解方法，包括从DNA柔性的分子测量导出的它们的物理性质。宋博士将应用统计理论分析分类时间序列的最大频谱，以回答一个长期存在的问题，即某些周期性DNA特性是否优先存在于单个核小体中。此外，将DNA包裹在组蛋白周围会引入超螺旋应力，我们发现这通常会被DNA序列依赖性稳定性的增加所抵消。所开发的计算工具将有助于解开DNA弯曲性和稳定能量之间的新联系，从而促进在重要的调控位点发现新的核小体定位信号。我们目前还不了解染色质结构是如何在细胞分裂时忠实地遗传的，DNA序列中包含的遗传信息可能会显着影响表观遗传的过程。更好地理解DNA的数学和物理特性将提高我们对染色质结构的理解。这个项目是独一无二的，将宋博士在计算表观基因组学方面的研究与创新的教育计划相结合，将大大促进生物学学生在数学和统计学方面的培训。该项目将通过协同不同的研究生群体，帮助改善教育和研究的基础设施。该项目将支持研究和教育的纵向一体化，其中拟议的研究将构成定量科学家表观遗传学教学和数学教学的一个重要主题。申请人将继续教授他设计的统计学课程，从基因组学中汲取例子。还将教授高通量测序技术和系统生物学的专题迷你课程，以传播申请人当前的研究活动，并帮助学生和博士后做好准备，进行自己的基因组学研究。本科生也将有机会参与研究，宋博士将参与当地高中生。该项目将展示应用数学和统计学解决生物学重要问题的丰富可能性。计算工具将被应用到开源软件中，其他研究染色质结构的研究人员也可以使用。有关该项目的更多信息，请访问PI实验室网站http://song.igb.illinois.edu。

In this project, the investigator will develop rigorous mathematical methods for analyzing the recent high-throughput nucleosome mapping data in yeasts and provide novel computational tools for studying the relations among DNA sequence, nucleosome stability, and nucleosome positioning. Eukaryotic DNA has a complicated three-dimensional structure called chromatin consisting of millions of nucleosomes, the protein-DNA complexes that contain 146 base pairs of DNA wrapping around eight histones. Nucleosomes play a critical role in regulating gene expression by controlling the accessibility of DNA and modulating transcription factor binding activities. Nucleosomes are thus of paramount importance, but there currently do not exist rigorous computational tools for studying the biological signals that regulate their positioning and stability. This research will devlop spectral decomposition methods for analyzing nucleosomal and linker DNA, including their physical properties derived from the molecular measurements of DNA flexibility. Dr. Song will apply a statistical theory for analyzing the maximal frequency spectrum of categorical time series in order to answer a long-standing question of whether certain periodic DNA properties preferentially exist in individual nucleosomes. Furthermore, wrapping DNA around histones introduces superhelical stress, which we show to be often countered by increased sequence-dependent stabilization of DNA. The developed computational tools will help unravel new connections between DNA bendability and stabilization energy and, thus, facilitate the discovery of novel nucleosome positioning signals at important regulatory sites. We currently do not understand how chromatin structure is faithfully inherited upon cell division, and it is likely that the genetic information contained in DNA sequences may significantly influence the process of epigenetic inheritance. Better understanding the mathematical and physical properties of DNA will enhance our understanding of chromatin structure.This project is uniquely positioned to integrate Dr Song's research in computational epigenomics with innovative educational programs that will significantly advance the training of biology students in mathematics and statistics. The project will help improve the infrastructure for education and research by synergizing different graduate groups. The project will support vertical integration of research and education, whereby the proposed research will constitute an important theme for teaching epigenetics to quantitative scientists and for teaching mathematics. The applicant will continue to teach a statistics course that he has designed, drawing examples from genomics. Topical mini-courses on high-throughput sequencing technology and systems biology will be also taught in order to disseminate the applicant's current research activities and to help prepare students and postdocs conduct their own research in genomics. Undergraduate students will also have opportunities to participate in the research, and Dr Song will involved local high school students. The project will exemplify the rich possibility of applying mathematics and statistics to solving biologically important questions. Computational tools will be implemented into open source software that will be accessible to other researchers studying chromatin structure. Further information about the project may be obtained from the PI's lab website at http://song.igb.illinois.edu.