Computational and Experimental Modeling of Epigenetic DNA Methylation

描述（由申请人提供）：DNA甲基化是一种影响基因组组织和功能的表观遗传修饰，在正常发育和疾病中都起着关键作用。亚硫酸氢盐将未甲基化的Cs转化为Ts，然后进行深度测序（BS-seq），已成为单核苷酸分辨率下研究全基因组DNA甲基化的金标准。虽然新一代测序技术（NGS）的进步使得全基因组BS-seq （WGBS）的成本越来越低，但对由此产生的大量数据的解释需要有效的生物信息学方法。在本提案中，我们将开发一系列新的生物信息学方法用于BS-seq数据分析。首先，在BSMAP项目早期成功的基础上，我们将开发下一代亚硫酸盐对准剂。我们将使用IUPAC代码和动态Burrows-Wheeler转换（DBWT）构建亚硫酸盐和SNP“感知”的基因组索引，用于读取映射。我们还将区分CpG甲基化和C/T SNP，并使用GPU硬件加速来提高映射速度。其次，我们将开发一个强大的差异甲基化分析算法，可以考虑到这两者

DESCRIPTION (provided by applicant): DNA methylation, an epigenetic modification affecting the organization and function of the genome, plays a critical role in both normal development and disease. Bisulfite based conversion of unmethylated Cs to Ts followed by deep sequencing (BS-seq) has emerged as the gold standard to study the genome-wide DNA methylation at single-nucleotide resolution. While progress in next-generation sequencing (NGS) allows increasingly affordable whole-genome BS-seq (WGBS), interpretation of the resulting massive amount of data requires efficient bioinformatics methods. In this proposal, we will develop a series of novel bioinformatics methods for BS-seq data analysis. First, building on the early success of our BSMAP program, we will develop the next generation of bisulfite aligner. We will construct a bisulfite- and SNP-"aware" genome indexing for read mapping with IUPAC code and dynamic Burrows-Wheeler transformation (DBWT). We will also distinguishing CpG methylation from C/T SNP and use GPU hardware acceleration to improve the mapping speed. Second, we will develop a powerful differential methylation analysis algorithm that can take into account both sampling variation from sequencing and biological variation between replicates. We will also introduce a novel metric for evaluating both the statistical and biological significance of differential methylation. This model will have enough power to detect single-CpG resolution differential methylation in low-CpG-density regulatory regions, such as enhancers, with as low as 5-10 fold sequencing depth. Third, we will develop a comprehensive BS-seq data analysis pipeline using the Galaxy web interface and cloud computing. We will integrate all the BS-seq tools we are developing and other public algorithms on a continuous basis according to the emerging needs of the epigenetic community. This pipeline will empower experimental biologists to perform most analyses on their own. These bioinformatics methods will undergo extensive testing and experimental validation by our collaborators. Although focused on CpG methylation using conventional BS-seq in this proposal, our bioinformatics methods can be immediately used in other modified BS-seq protocols, such as oxBS-Seq and TAB-Seq recently developed for 5mC and 5hmC, respectively. Finally, as a case study, we will apply these new methods to unravel the in vivo role of DNA methylation in hematopoietic malignancies. These experiments and follow-up validations will also enable us to improve the efficacy of our bioinformatics methods.