Benchmarking metabolic RNA labeling techniques for high-throughput single-cell RNA sequencing
Abstract Metabolic RNA labeling with high-throughput single-cell RNA sequencing (scRNA-seq) enables precise measurement of gene expression dynamics in complex biological processes, such as cell state transitions and embryogenesis. This technique, which tags newly synthesized RNA for detection throug...
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Nature Portfolio
2025-07-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-61375-z |
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| author | Xiaowen Zhang Mingjian Peng Jianghao Zhu Xue Zhai Chaoguang Wei He Jiao Zhichao Wu Songqian Huang Mingli Liu Wenhao Li Wenyi Yang Kai Miao Qiongqiong Xu Liangbiao Chen Peng Hu |
| author_facet | Xiaowen Zhang Mingjian Peng Jianghao Zhu Xue Zhai Chaoguang Wei He Jiao Zhichao Wu Songqian Huang Mingli Liu Wenhao Li Wenyi Yang Kai Miao Qiongqiong Xu Liangbiao Chen Peng Hu |
| author_sort | Xiaowen Zhang |
| collection | DOAJ |
| description | Abstract Metabolic RNA labeling with high-throughput single-cell RNA sequencing (scRNA-seq) enables precise measurement of gene expression dynamics in complex biological processes, such as cell state transitions and embryogenesis. This technique, which tags newly synthesized RNA for detection through induced base conversions, relies on conversion efficiency, RNA integrity, and transcript recovery. These factors are influenced by the chosen chemical conversion method and platform compatibility. Despite its potential, a comprehensive comparison of chemical methods and platform compatibility has been lacking. Here, we benchmark ten chemical conversion methods using the Drop-seq platform, analyzing 52,529 cells. We find that on-beads methods, particularly the meta-chloroperoxy-benzoic acid/2,2,2-trifluoroethylamine combination, outperform in-situ approaches. To assess in vivo applications, we apply these optimized methods to 9883 zebrafish embryonic cells during the maternal-to-zygotic transition, identifying and experimentally validating zygotically activated transcripts, which enhanced zygotic gene detection capabilities. Additionally, we evaluate two commercial platforms with higher capture efficiency and find that on-beads iodoacetamide chemistry is the most effective. Our results provide critical guidance for selecting optimal chemical methods and scRNA-seq platforms, advancing the study of RNA dynamics in complex biological systems. |
| format | Article |
| id | doaj-art-9d41b2816a124f028e12a7fc044f3c5f |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-9d41b2816a124f028e12a7fc044f3c5f2025-08-20T03:45:35ZengNature PortfolioNature Communications2041-17232025-07-0116111710.1038/s41467-025-61375-zBenchmarking metabolic RNA labeling techniques for high-throughput single-cell RNA sequencingXiaowen Zhang0Mingjian Peng1Jianghao Zhu2Xue Zhai3Chaoguang Wei4He Jiao5Zhichao Wu6Songqian Huang7Mingli Liu8Wenhao Li9Wenyi Yang10Kai Miao11Qiongqiong Xu12Liangbiao Chen13Peng Hu14Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean UniversityKey Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean UniversityKey Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean UniversityKey Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean UniversityKey Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean UniversityKey Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean UniversityKey Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean UniversityKey Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean UniversityKey Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean UniversityKey Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean UniversityKey Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean UniversityMOE Frontier Science Centre for Precision Oncology, University of MacauKey Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean UniversityKey Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean UniversityKey Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean UniversityAbstract Metabolic RNA labeling with high-throughput single-cell RNA sequencing (scRNA-seq) enables precise measurement of gene expression dynamics in complex biological processes, such as cell state transitions and embryogenesis. This technique, which tags newly synthesized RNA for detection through induced base conversions, relies on conversion efficiency, RNA integrity, and transcript recovery. These factors are influenced by the chosen chemical conversion method and platform compatibility. Despite its potential, a comprehensive comparison of chemical methods and platform compatibility has been lacking. Here, we benchmark ten chemical conversion methods using the Drop-seq platform, analyzing 52,529 cells. We find that on-beads methods, particularly the meta-chloroperoxy-benzoic acid/2,2,2-trifluoroethylamine combination, outperform in-situ approaches. To assess in vivo applications, we apply these optimized methods to 9883 zebrafish embryonic cells during the maternal-to-zygotic transition, identifying and experimentally validating zygotically activated transcripts, which enhanced zygotic gene detection capabilities. Additionally, we evaluate two commercial platforms with higher capture efficiency and find that on-beads iodoacetamide chemistry is the most effective. Our results provide critical guidance for selecting optimal chemical methods and scRNA-seq platforms, advancing the study of RNA dynamics in complex biological systems.https://doi.org/10.1038/s41467-025-61375-z |
| spellingShingle | Xiaowen Zhang Mingjian Peng Jianghao Zhu Xue Zhai Chaoguang Wei He Jiao Zhichao Wu Songqian Huang Mingli Liu Wenhao Li Wenyi Yang Kai Miao Qiongqiong Xu Liangbiao Chen Peng Hu Benchmarking metabolic RNA labeling techniques for high-throughput single-cell RNA sequencing Nature Communications |
| title | Benchmarking metabolic RNA labeling techniques for high-throughput single-cell RNA sequencing |
| title_full | Benchmarking metabolic RNA labeling techniques for high-throughput single-cell RNA sequencing |
| title_fullStr | Benchmarking metabolic RNA labeling techniques for high-throughput single-cell RNA sequencing |
| title_full_unstemmed | Benchmarking metabolic RNA labeling techniques for high-throughput single-cell RNA sequencing |
| title_short | Benchmarking metabolic RNA labeling techniques for high-throughput single-cell RNA sequencing |
| title_sort | benchmarking metabolic rna labeling techniques for high throughput single cell rna sequencing |
| url | https://doi.org/10.1038/s41467-025-61375-z |
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