Dissecting epitranscriptomic signal from complex tissues

标题：从复杂组织中分离epitranscriptomic信号 项目概要： RNA表观遗传学是近年来出现的一个令人兴奋和活跃的研究领域 该领域研究基因表达的转录后调控。RNA的修饰起着重要的作用 在基因表达调控中起重要作用，并参与神经发育和许多神经系统疾病。 甲基化RNA免疫沉淀测序（MeRIP-seq）是一种新开发的用于检测甲基化RNA的技术。 RNA表观遗传修饰的转录组分析。MeRIP-seq导致了 在基础和临床研究中的应用，但面临着许多挑战，在分析其独特的 数据特征，包括1）由于序列内容和样本而存在技术伪影 MeRIP特有的制备程序; 2）缺乏适当的方法来识别和比较 RNA甲基化区域; 3）缺乏解释组织样品异质性的方法。 在本提案中，我们将应对这些挑战，并开发一系列新颖的统计方法， MeRIP-seq数据预处理和分析。它们包括一个数据规范化过程， 用于RNA甲基化位点检测和比较的技术偏差、准确和有效的方法以及信号 去卷积方法，以基于来自组织样品的数据得出细胞类型特异性推断。所有方法 在这个项目中开发的软件将作为免费的开源软件来实现和发布， 表观基因组学研究社区，包括从事遗传学，表观遗传学，基因 调节和细胞发育，以及寻找疾病生物标志物的临床医生。

Title: Dissecting epitranscriptomic signal from complex tissues PROJECT SUMMARY: “RNA epigenetics” or “epitranscriptomics” has emerged in recent years as an exciting and active research field to study post-transcriptional regulation of gene expressions. The RNA modifications play important roles in gene expression regulation, and are involved in neurodevelopment and a number of neurological diseases. Methylated RNA Immunoprecipitation Sequencing (MeRIP-seq) is a newly developed technology for transcriptome-wise profiling of the RNA epigenetic modifications. MeRIP-seq leads to an expansion of applications in both basic and clinical research, but faces a number of challenges in analysis with its unique data characteristics, including 1) the presence of technical artifacts due to sequence content and sample preparation procedures unique to MeRIP; 2) lack of appropriate methods for identification and comparison of RNA methylated regions; and 3) lack of methods to account for the heterogeneity of tissue samples. In this proposal, we will address these challenges and develop a series of novel statistical methods for MeRIP-seq data preprocessing and analyses. They include a data normalization procedure to remove technical bias, accurate and efficient methods for RNA methylation site detection and comparison, and signal deconvolution methods to draw cell type specific inferences based on data from tissue samples. All methods developed in this project will be implemented and released as free, open source software to benefit the epigenomics research community, including basic scientists working on genetics, epigenetics, gene regulation and cell development, as well as clinicians looking for disease biomarkers.