Abstract Motivation The Oxford Nanopore sequencing enables to directly detect methylation states of bases in DNA from reads without extra laboratory techniques. Novel computational methods are required to improve the accuracy and robustness of DNA methylation state prediction using Nanopore reads. Results In this study, we develop DeepSignal, a deep learning method to detect DNA methylation states from Nanopore sequencing reads. Testing on Nanopore reads of Homo sapiens (H. sapiens), Escherichia coli (E. coli) and pUC19 shows that DeepSignal can achieve higher performance at both read level and genome level on detecting 6 mA and 5mC methylation states comparing to previous hidden Markov model (HMM) based methods. DeepSignal achieves similar performance cross different DNA methylation bases, different DNA methylation motifs and both singleton and mixed DNA CpG. Moreover, DeepSignal requires much lower coverage than those required by HMM and statistics based methods. DeepSignal can achieve 90% above accuracy for detecting 5mC and 6 mA using only 2× coverage of reads. Furthermore, for DNA CpG methylation state prediction, DeepSignal achieves 90% correlation with bisulfite sequencing using just 20× coverage of reads, which is much better than HMM based methods. Especially, DeepSignal can predict methylation states of 5% more DNA CpGs that previously cannot be predicted by bisulfite sequencing. DeepSignal can be a robust and accurate method for detecting methylation states of DNA bases. Availability and implementation DeepSignal is publicly available at https://github.com/bioinfomaticsCSU/deepsignal. Supplementary information Supplementary data are available at bioinformatics online.
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DNA methylation profiling of a cnidarian-algal symbiosis using nanopore sequencing
Abstract Symbiosis with protists is common among cnidarians such as corals and sea anemones and is associated with homeostatic and phenotypic changes in the host that could have epigenetic underpinnings, such as methylation of CpG dinucleotides. We leveraged the sensitivity to base modifications of nanopore sequencing to probe the effect of symbiosis with the chlorophyte Elliptochloris marina on methylation in the sea anemone Anthopleura elegantissima. We first validated the approach by comparison of nanopore-derived methylation levels with CpG depletion analysis of a published transcriptome, finding that high methylation levels are associated with CpG depletion as expected. Next, using reads generated exclusively from aposymbiotic anemones, a largely complete draft genome comprising 243 Mb was assembled. Reads from aposymbiotic and symbiotic sea anemones were then mapped to this genome and assessed for methylation using the program Nanopolish, which detects signal disruptions from base modifications as they pass through the nanopore. Based on assessment of 452,841 CpGs for which there was adequate read coverage (approximately 8% of the CpGs in the genome), symbiosis with E. marina was, surprisingly, associated with only subtle changes in the host methylome. However, we did identify one extended genomic region with consistently higher methylation among symbiotic individuals. The region was associated with a DNA polymerase zeta that is noted for its role in translesion synthesis, which opens interesting questions about the biology of this symbiosis. Our study highlights the power and relative simplicity of nanopore sequencing for studies of nucleic acid base modifications in non-model species.
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- Award ID(s):
- 1947838
- PAR ID:
- 10472773
- Editor(s):
- Andrews, B
- Publisher / Repository:
- Oxford
- Date Published:
- Journal Name:
- G3 Genes|Genomes|Genetics
- Volume:
- 11
- Issue:
- 7
- ISSN:
- 2160-1836
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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