DRME – count-based differential RNA methylation analysis at small sample size scenario

Differential methylation, which concerns difference in the degree of epigenetic regulation via methylation between two conditions, has been formulated as a beta or beta-binomial distribution to address the within-group biological variability in sequencing data. However, a beta or beta-binomial model is usually difficult to infer at small sample size scenario with discrete reads count in sequencing data. On the other hand, as an emerging research field, RNA methylation has drawn more and more attention recently, and the differential analysis of RNA methylation is significantly different from that of DNA methylation due to the impact of transcriptional regulation.

Researchers at Northwestern Polytechnical University, China have developed DRME to better address the differential RNA methylation problem. The proposed model can effectively describe within-group biological variability at small sample size scenario and handles the impact of transcriptional regulation on RNA methylation. the researchers tested the newly developed DRME algorithm on simulated and 4 MeRIP-Seq case-control studies, and compared it with Fisher’s exact test. It is in principle widely applicable to several other RNA-related data types as well, including RNA Bisulfite sequencing, PAR-CLIP, etc.

Difference in DNA and RNA methylation.


The DNA copy numbers are mostly the same between two experimental conditions (WT and KO); while the copy numbers can be quite different for RNA molecules. It is possible that, as shown in the figure above, while the absolute amount of methylated RNA molecules increases in KO condition compared with WT condition, the amount relative to unmodified RNA molecules decreases, which represents a hypo-methylation phenomenon. In DNA-templated epigenetic studies, because the DNA copies remain the same between two experimental conditions, the input sample is often not needed. Differential analysis of ChIP-Seq or MeDIP-Seq can be conducted without the Input sample which measures the total amount of input DNA. However, in RNA methylation differential analysis, the Input sample can be invaluable conveying the abundance of RNA molecule under each condition.

Availability – The code together with a MeRIP-Seq dataset is available online at: https://github.com/lzcyzm/DRME

Liu L, Zhang SW, Gao F, Zhang Y, Huang Y, Chen R, Meng J. (2016) DRME: count-based differential RNA methylation analysis at small sample size scenario. Anal Biochem [Epub ahead of print]. [abstract]

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