分类： 生物学 >> 生物物理学 >> 生物物理、生物化学与分子生物学 提交时间： 2016-05-12
摘要： With the rapid development of high-throughput sequencing technologies, the emerging of methylated RNA immunoprecipitation sequencing (MeRIP-seq) technology makes it possible to detect RNA epigenetic modifications in a large scale, which allows transcriptome-wide profiling of RNA methylation. Mining the patterns of global mRNA methylation from these MeRIP-seq data can help reveal the potential functional roles of these mRNA methylations in regulating gene expression, splicing, RNA editing and RNA stability, effectively guiding the therapeutic intervention of cancer. Here, the principle of MeRIP-seq sequencing was first introduced. Then, the recent progress of the processing and analysis of MeRIP-seq data were comprehensively discussed. In the end, the computational problems and challenges faced in the process of MeRIP-seq data processing were also summarized.
分类： 生物学 >> 生物物理学 >> 生物物理、生物化学与分子生物学 提交时间： 2016-05-11
Liu, Lian
Zhang, Shao-Wu
Zhang, Yu-Chen
Chen, Runsheng
Liu, Hui
Zhang, Lin
Chen, Runsheng
Huang, Yufei
Meng, Jia
摘要： Biochemical modifications to mRNA, especially N6-methyladenosine (m(6)A) and 5-methylcytosine (m(5)C), have been recently shown to be associated with crucial biological functions. Despite the intriguing advancements, little is known so far about the dynamic landscape of RNA methylome across different cell types and how the epitranscriptome is regulated at the system level by enzymes, i.e., RNA methyltransferases and demethylases. To investigate this issue, a meta-analysis of m(6)A MeRIP-Seq datasets collected from 10 different experimental conditions (cell type/tissue or treatment) is performed, and the combinatorial epitranscriptome, which consists of 42758 m(6)A sites, is extracted and divided into 3 clusters, in which the methylation sites are likely to be hyper- or hypo-methylated simultaneously (or co-methylated), indicating the sharing of a common methylation regulator. Four different clustering approaches are used, including K-means, hierarchical clustering (HC), Bayesian factor regression model (BFRM) and nonnegative matrix factorization (NMF) to unveil the co-methylation patterns. To validate whether the patterns are corresponding to enzymatic regulators, i.e., RNA methyltransferases or demethylases, the target sites of a known m(6)A regulator, fat mass and obesity-associated protein (FTO), are identified from an independent mouse MeRIP-Seq dataset and lifted to human. Our study shows that 3 out of the 4 clustering approaches used can successfully identify a group of methylation sites overlapping with FTO target sites at a significance level of 0.05 (after multiple hypothesis adjustment), among which, the result of NMF is the most significant (p-value 2.81 x 10(-06)). We defined a new approach evaluating the consistency between two clustering results which shows that clustering results of different methods are highly correlated strongly indicating the existence of co-methylation patterns. Consistent with recent studies, a number of cancer and neuronal disease-related bimolecular functions are enriched in the identified clusters, which are biological functions that can be regulated at the epitranscriptional level, indicating the pharmaceutical prospect of RNA N6-methyladenosine-related studies. This result successfully reveals the linkage between the global RNA co-methylation patterns embedded in the epitranscriptomic data under multiple experimental conditions and the latent enzymatic regulators, suggesting a promising direction towards a more comprehensive understanding of the epitranscriptome.
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