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

加州大学旧金山分校获得了一项资助，用于开发严格的数学方法来分析酵母中最近的高通量核小体定位数据，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。真核生物的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，蛋白质-DNA复合物包含146个碱基对的DNA，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至关重要的作用。因此，核小体是至关重要的，但目前还没有严格的计算工具来研究调节其定位和稳定性的生物信号。本研究将开发用于分析核小体和连接体DNA的光谱分解方法，包括从DNA柔韧性的分子测量中获得的物理特性。宋博士将运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，我们发现这通常会通过增加DNA序列依赖的稳定性来抵消。开发的计算工具将有助于揭示DNA可弯曲性和稳定能量之间的新联系，从而促进在重要调控位点发现新的核小体定位信号。我们目前还不清楚细胞分裂时染色质结构是如何忠实地遗传的，很可能DNA序列中包含的遗传信息会显著影响表观遗传的过程。更好地理解DNA的数学和物理性质将增强我们对染色质结构的理解。该项目具有独特的优势，将宋博士在计算表观基因组学方面的研究与创新的教育项目相结合，将大大促进加州大学旧金山分校生物学专业学生在数学和统计学方面的培训。该项目将通过协同UCSF的不同研究生群体，帮助改善UCSF的教育和研究基础设施。该项目将支持研究和教育的垂直整合，由此提出的研究将构成向定量科学家教授表观遗传学和向UCSF学生教授数学的重要主题。申请人将继续教授他最近在生物和医学信息学研究生项目中设计的一门新的统计学课程，以基因组学为例。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在基因组学方面进行自己的研究。来自其他机构的本科生也将有机会通过加州大学伯克利分校暑期实习计划参与我们的研究。宋博士将通过加州大学旧金山分校的科学与健康教育伙伴关系（SEP）让当地高中生参与其中。SEP邀请来自旧金山公立高中的有前途的高年级学生，并将他们置于UCSF研究人员的指导下，进行为期8周的暑期研究项目。该项目将举例说明应用数学和统计学来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这些软件。有关该项目的进一步信息可从PI的实验室网站http://songlab.ucsf.edu/Welcome.html获得。

The University of California - San Francisco is awarded a grant to 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 at UCSF. The project will help improve the infrastructure for education and research at UCSF by synergizing different graduate groups at UCSF. 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 to students at UCSF. The applicant will continue to teach a new statistics course that he has recently designed in the Biological and Medical Informatics graduate program, 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 from other institutions will also have opportunities to participate in our research through the UC Berkeley Summer Internship Program. Dr Song will involved local high school students through the Science and Health Education Partnership (SEP) at UCSF. SEP invites promising seniors from San Francisco's public high schools and places them under the guidance of UCSF investigators for 8-week-long summer research projects. 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://songlab.ucsf.edu/Welcome.html.