Genome-wide Detection of Cytosine Methylations in Plant from Nanopore Data Using Deep Learning

Release time:2025-03-05

DOI number:10.1038/s41467-021-26278-9

Journal:NATURE COMMUNICATIONS

Key Words:DNA METHYLATION，EPIGENOME，REPEATS

Abstract:In plants, cytosine DNA methylations (5mCs) can happen in three sequence contexts as CpG, CHG, and CHH (where H = A, C, or T), which play different roles in the regulation of biological processes. Although long Nanopore reads are advantageous in the detection of 5mCs comparing to short-read bisulfite sequencing, existing methods can only detect 5mCs in the CpG context, which limits their application in plants. Here, we develop DeepSignal-plant, a deep learning tool to detect genome-wide 5mCs of all three contexts in plants from Nanopore reads. We sequence Arabidopsis thaliana and Oryza sativa using both Nanopore and bisulfite sequencing. We develop a denoising process for training models, which enables DeepSignal-plant to achieve high correlations with bisulfite sequencing for 5mC detection in all three contexts. Furthermore, DeepSignal-plant can profile more 5mC sites, which will help to provide a more complete understanding of epigenetic mechanisms of different biological processes. Existing methods cannot profile genome-wide cytosine DNA methylations (5mCs) in all three contexts with acceptable accuracy. Here, the authors develop a deep learning tool to detect genome-wide 5mCs of all three contexts in plants with high accuracy from Nanopore reads.

Note:Ni, P (Ni, Peng) [1] , [2] ; Huang, N (Huang, Neng) [1] , [2] ; Nie, F (Nie, Fan) [1] , [2] ; Zhang, J (Zhang, Jun) [1] , [2] ; Zhang, Z (Zhang, Zhi) [1] , [2] ; Wu, B (Wu, Bo) [3] ; Bai, L (Bai, Lu) [4] ; Liu, WD (Liu, Wende) [4] ; Xiao, CL (Xiao, Chuan-Le) [5] ; Luo, F (Luo, Feng) [3] ; Wang, JX (Wang, Jianxin) [1] , [2]

Indexed by:Journal paper

Volume:12

Issue:1

Translation or Not:no

Date of Publication:2021-10-13

Included Journals:SCI