Mathematical and Statistical Models for Nucleosome

核小体的数学和统计模型

• 批准号: 6985538
• 负责人: JI-PING WANG
• 金额: $ 20.05万
• 依托单位: NORTHWESTERN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-04-01 至 2010-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6985538
• 关键词: cell component structure /function; functional /structural genomics; fungal genetics; genetic mapping; genetic registry /resource /referral center; mathematical model; model design /development; molecular cloning; nucleic acid sequence; nucleosomes; yeasts

DESCRIPTION (provided by applicant): The nucleosome is the fundamental packing unit of chromatin formed by association of DNA and histone octamer in eukaryotic chromosomes. The detailed locations of nucleosomes along genomic DNA are critical for proper gene regulation - and therefore for the health and development of humans and all other eukaryotes - yet, at present, we lack any methods for the "in-silico" prediction of nucleosome positioning sequence elements in genomes. The long-term goal of this project is to develop capability to predict nucleosome-forming propensity given DNA sequences and correlate the genome-wide distribution of nucleosome-forming sequences with chromosome function. Towards this goal, we propose to achieve the following five aims progressively in the subsequent years. (1) Experimentally collect 1000 yeast nucleosome core DNA sequences, and 1000 yeast di-nucleosome DNA sequences (two neighboring nucleosomes linked by linker DNA). These yeast nucleosome DNA sequences will form a new training set as well as a validating set for nucleosome positioning prediction across the yeast genome. (2) Develop and refine statistical methods to align nucleosome DNA sequences. A novel statistical model for nucleosorne DNA sequence alignment was proposed in the preliminary study. We will refine this model by introducing a weighting scheme based on the importance of different periodic di-nucleotide signals from free energy consideration. (3) Use the alignment in (2) to train a model to predict nucleosome positioning. An inhomogeneous Markov chain model and a "mixture train" model are under consideration to model the sequential dependent structure of nucleotides. (4) Generalize the model by incorporating knowledge in spacing properties of neighboring nucleosomes. The di-nucleosome sequences generated from (1) will provide distributional evidence for between-nucleosome space and dl1 greatly facilitate prediction of genome-wide nucleosome positioning. (5) Automate the developed tools and algorithms.

描述(申请人提供)：核小体是真核细胞染色体中DNA和组蛋白八聚体结合形成的染色质的基本包装单位。核小体在基因组DNA上的详细位置对于适当的基因调控至关重要，因此对人类和所有其他真核生物的健康和发育也是至关重要的。然而，目前我们还缺乏任何方法来对基因组中的核小体定位序列元件进行“电子”预测。该项目的长期目标是发展预测给定DNA序列的核小体形成倾向的能力，并将核小体形成序列的全基因组分布与染色体功能相关联。为了实现这一目标，我们建议在今后几年逐步实现以下五个目标。(1)实验收集了1000个酵母核小体核心DNA序列和1000个酵母双核小体DNA序列(两个相邻的核小体通过连接物DNA连接)。这些酵母核小体DNA序列将形成一个新的训练集以及一个验证集，用于整个酵母基因组中的核小体定位预测。(2)发展和完善核小体DNA序列比对的统计方法。在初步研究中，提出了一种新的核仁DNA序列比对统计模型。我们将通过引入基于自由能考虑的不同周期二核苷酸信号的重要性的加权方案来完善该模型。(3)使用(2)中的比对训练模型来预测核小体定位。考虑使用非齐次马尔可夫链模型和“混合序列”模型来模拟核苷酸的顺序依赖结构。(4)通过结合相邻核小体间距性质的知识来推广该模型。由(1)产生的双核小体序列将为核小体之间的空间分布提供证据，而DL1极大地促进了对 全基因组核小体定位。(5)将开发的工具和算法自动化。