Single-molecule direct RNA sequencing reveals the shaping of epitranscriptome across multiple species
Abstract N6-methyladenosine (m6A) is an essential RNA modification that regulates gene expression and influences diverse cellular processes. Yet, fully characterizing its transcriptome-wide landscape and biogenesis mechanisms remains challenging. Traditional next-generation sequencing (NGS) methods...
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Nature Portfolio
2025-06-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-60447-4 |
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| author | Ying-Yuan Xie Zhen-Dong Zhong Hong-Xuan Chen Ze-Hui Ren Yuan-Tao Qiu Ye-Lin Lan Fu Wu Jin-Wen Kong Ru-Jia Luo Delong Zhang Biao-Di Liu Yang Shu Feng Yin Jian Wu Zigang Li Zhang Zhang Guan-Zheng Luo |
| author_facet | Ying-Yuan Xie Zhen-Dong Zhong Hong-Xuan Chen Ze-Hui Ren Yuan-Tao Qiu Ye-Lin Lan Fu Wu Jin-Wen Kong Ru-Jia Luo Delong Zhang Biao-Di Liu Yang Shu Feng Yin Jian Wu Zigang Li Zhang Zhang Guan-Zheng Luo |
| author_sort | Ying-Yuan Xie |
| collection | DOAJ |
| description | Abstract N6-methyladenosine (m6A) is an essential RNA modification that regulates gene expression and influences diverse cellular processes. Yet, fully characterizing its transcriptome-wide landscape and biogenesis mechanisms remains challenging. Traditional next-generation sequencing (NGS) methods rely on short-reads aggregation, overlooking the inherent heterogeneity of RNA transcripts. Third-generation sequencing (TGS) platforms offer direct RNA sequencing (DRS) at the resolution of individual RNA molecules, enabling simultaneous detection of RNA modifications and RNA processing events. In this study, we introduce SingleMod, a deep learning model tailored for precise detection of m6A modification on individual RNA molecules from DRS data. SingleMod innovatively employs a multiple instance regression (MIR) framework, leveraging extensive methylation-rate labels provided by the quantitative NGS-based method, and achieves ROC AUC and PR AUC of ~0.95 for single-molecule m6A prediction. Applying SingleMod to human cell lines, we systematically dissect the transcriptome-wide m6A landscape at single-molecule and single-base resolution, characterizing m6A heterogeneity in RNA molecules from the same transcript. Through comparative analyzes across eight diverse species, we quantitatively elucidate three distinct m6A distribution patterns correlated with phylogenetic relationships and suggest divergent regulatory mechanisms. This study provides a framework for understanding the shaping of epitranscriptome in a single-molecule perspective. |
| format | Article |
| id | doaj-art-e4090075d1104788b9f625c076401ca6 |
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| issn | 2041-1723 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-e4090075d1104788b9f625c076401ca62025-08-20T02:05:38ZengNature PortfolioNature Communications2041-17232025-06-0116111710.1038/s41467-025-60447-4Single-molecule direct RNA sequencing reveals the shaping of epitranscriptome across multiple speciesYing-Yuan Xie0Zhen-Dong Zhong1Hong-Xuan Chen2Ze-Hui Ren3Yuan-Tao Qiu4Ye-Lin Lan5Fu Wu6Jin-Wen Kong7Ru-Jia Luo8Delong Zhang9Biao-Di Liu10Yang Shu11Feng Yin12Jian Wu13Zigang Li14Zhang Zhang15Guan-Zheng Luo16State Key Laboratory of Biocontrol, MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, School of Life Sciences, Sun Yat-sen UniversityState Key Laboratory of Biocontrol, MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, School of Life Sciences, Sun Yat-sen UniversityState Key Laboratory of Biocontrol, MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, School of Life Sciences, Sun Yat-sen UniversityState Key Laboratory of Biocontrol, MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, School of Life Sciences, Sun Yat-sen UniversityState Key Laboratory of Biocontrol, MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, School of Life Sciences, Sun Yat-sen UniversityState Key Laboratory of Biocontrol, MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, School of Life Sciences, Sun Yat-sen UniversityState Key Laboratory of Biocontrol, MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, School of Life Sciences, Sun Yat-sen UniversityState Key Laboratory of Biocontrol, MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, School of Life Sciences, Sun Yat-sen UniversityState Key Laboratory of Biocontrol, MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, School of Life Sciences, Sun Yat-sen UniversityState Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, South China Agricultural UniversityState Key Laboratory of Biocontrol, MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, School of Life Sciences, Sun Yat-sen UniversityState Key Laboratory of Biocontrol, MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, School of Life Sciences, Sun Yat-sen UniversityPingshan Translational Medicine Center, Shenzhen Bay LaboratoryState Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, South China Agricultural UniversityPingshan Translational Medicine Center, Shenzhen Bay LaboratoryState Key Laboratory of Biocontrol, MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, School of Life Sciences, Sun Yat-sen UniversityState Key Laboratory of Biocontrol, MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, School of Life Sciences, Sun Yat-sen UniversityAbstract N6-methyladenosine (m6A) is an essential RNA modification that regulates gene expression and influences diverse cellular processes. Yet, fully characterizing its transcriptome-wide landscape and biogenesis mechanisms remains challenging. Traditional next-generation sequencing (NGS) methods rely on short-reads aggregation, overlooking the inherent heterogeneity of RNA transcripts. Third-generation sequencing (TGS) platforms offer direct RNA sequencing (DRS) at the resolution of individual RNA molecules, enabling simultaneous detection of RNA modifications and RNA processing events. In this study, we introduce SingleMod, a deep learning model tailored for precise detection of m6A modification on individual RNA molecules from DRS data. SingleMod innovatively employs a multiple instance regression (MIR) framework, leveraging extensive methylation-rate labels provided by the quantitative NGS-based method, and achieves ROC AUC and PR AUC of ~0.95 for single-molecule m6A prediction. Applying SingleMod to human cell lines, we systematically dissect the transcriptome-wide m6A landscape at single-molecule and single-base resolution, characterizing m6A heterogeneity in RNA molecules from the same transcript. Through comparative analyzes across eight diverse species, we quantitatively elucidate three distinct m6A distribution patterns correlated with phylogenetic relationships and suggest divergent regulatory mechanisms. This study provides a framework for understanding the shaping of epitranscriptome in a single-molecule perspective.https://doi.org/10.1038/s41467-025-60447-4 |
| spellingShingle | Ying-Yuan Xie Zhen-Dong Zhong Hong-Xuan Chen Ze-Hui Ren Yuan-Tao Qiu Ye-Lin Lan Fu Wu Jin-Wen Kong Ru-Jia Luo Delong Zhang Biao-Di Liu Yang Shu Feng Yin Jian Wu Zigang Li Zhang Zhang Guan-Zheng Luo Single-molecule direct RNA sequencing reveals the shaping of epitranscriptome across multiple species Nature Communications |
| title | Single-molecule direct RNA sequencing reveals the shaping of epitranscriptome across multiple species |
| title_full | Single-molecule direct RNA sequencing reveals the shaping of epitranscriptome across multiple species |
| title_fullStr | Single-molecule direct RNA sequencing reveals the shaping of epitranscriptome across multiple species |
| title_full_unstemmed | Single-molecule direct RNA sequencing reveals the shaping of epitranscriptome across multiple species |
| title_short | Single-molecule direct RNA sequencing reveals the shaping of epitranscriptome across multiple species |
| title_sort | single molecule direct rna sequencing reveals the shaping of epitranscriptome across multiple species |
| url | https://doi.org/10.1038/s41467-025-60447-4 |
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