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Published April 2021 | Supplemental Material
Journal Article Open

PANDORA-seq expands the repertoire of regulatory small RNAs by overcoming RNA modifications

Abstract

Although high-throughput RNA sequencing (RNA-seq) has greatly advanced small non-coding RNA (sncRNA) discovery, the currently widely used complementary DNA library construction protocol generates biased sequencing results. This is partially due to RNA modifications that interfere with adapter ligation and reverse transcription processes, which prevent the detection of sncRNAs bearing these modifications. Here, we present PANDORA-seq (panoramic RNA display by overcoming RNA modification aborted sequencing), employing a combinatorial enzymatic treatment to remove key RNA modifications that block adapter ligation and reverse transcription. PANDORA-seq identified abundant modified sncRNAs—mostly transfer RNA-derived small RNAs (tsRNAs) and ribosomal RNA-derived small RNAs (rsRNAs)—that were previously undetected, exhibiting tissue-specific expression across mouse brain, liver, spleen and sperm, as well as cell-specific expression across embryonic stem cells (ESCs) and HeLa cells. Using PANDORA-seq, we revealed unprecedented landscapes of microRNA, tsRNA and rsRNA dynamics during the generation of induced pluripotent stem cells. Importantly, tsRNAs and rsRNAs that are downregulated during somatic cell reprogramming impact cellular translation in ESCs, suggesting a role in lineage differentiation.

Additional Information

© 2021 Nature Publishing Group. Received 13 July 2020; Accepted 23 February 2021; Published 05 April 2021. We thank T. Lowe at the University of California, Santa Cruz for early discussion on the project, and Z. Li from the Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences for assistance with operating the mass spectrometer. This work is in part supported by MOST (2019YFA0802600 to Ying Zhang (Chinese Academy of Sciences) and Yunfang Zhang; 2018YFC1004500 to Ying Zhang (Chinese Academy of Sciences) and M.Y.), startup funds from the University of California, Riverside (to Q.C. and S.C.) and the NIH (R01HD092431 to Q.C.; R01ES032024 to Q.C. and T.Z.; P50HD098593 to T.Z. and Q.C.; R35GM128854 to L. Zhao). This work includes data generated at the University of California, San Diego IGM Genomics Center funded by the NIH (P30DK063491, P30CA023100 and P30DK120515). Q.Z. is funded by the NSFC (31630037). Ying Zhang (University of California, Riverside) is funded by a State Scholarships Fund (201908500039). Yunfang Zhang is funded by the NSFC (82022029) and the Natural Science Foundation of Chongqing (cstc2019jcyjjqX0010). M.Y. is funded by the NSFC (31670830) and is a fellow of the Innovative Research Team of High-Level Local Universities in Shanghai. M.S. is funded by an Advanced EMBO fellowship. K.M. is funded by a BBSRC scholarship. Work in the laboratory of M.Z.-G. is funded by the Wellcome Trust (207415/Z/17/Z), ERC (669198) and Open Philanthropy. R.F. is supported by UC Riverside's Eugene Cota-Robles Fellowship. Data availability: RNA-seq datasets have been deposited in the Gene Expression Omnibus under the accession code GSE144666. LC-MS/MS data have been deposited in Figshare (https://figshare.com/articles/dataset/_/14033003). All other data supporting the findings of this study are available from the corresponding authors upon reasonable request. Source data are provided with this paper. Code availability: The sncRNA annotation pipeline SPORTS1.1 is available from GitHub (https://github.com/junchaoshi/sports1.1). The scripts used for data processing and statistical analysis were written in Perl or R and are available upon reasonable request. These authors contributed equally: Junchao Shi, Yunfang Zhang, Dongmei Tan, Xudong Zhang, Menghong Yan, Ying Zhang, Reuben Franklin. Author Contributions: Q.C., T.Z. and J.S. designed the project. Yunfang Zhang, D.T. and J.S. developed and optimized the enzymatic treatment protocol for PANDORA-seq. J.S., T.Z., Ying Zhang (Chinese Academy of Sciences) and Q.C. designed and developed the scope of data analyses. S.C., J.M. and R.F. generated iPSCs from MEFs and contributed to related analyses. X.Z. and R.F. performed the functional assays of mESCs under the supervision of S.C. and Q.C. J.S. and T.Z. developed the computational tools and analysed all of the datasets with input from Ying Zhang (Chinese Academy of Sciences) and Q.C. X.Z. and Ying Zhang (University of California, Riverside) developed and performed northern blot analyses for tissues/cells with help from D.T. and S.L. Yunfang Zhang tested and validated T4PNK's effect in improving adapter ligation. M.Y. and X.Z. contributed to the LC-MS/MS RNA modification analyses with the help from Y.W. M.Y. designed and generated the AlkB plasmid and generated the AlkB enzyme with help from W.Z., Q.Z. and L. Zhao. L. Zhang and Y.Q. collected mature sperm samples under the supervision of Ying Zhang (Chinese Academy of Sciences). M.S., K.M. and M.Z.-G. performed experiments to contribute mESCs, primed hESCs and naive hESCs for analyses. B.R.C. contributed to data interpretation in regard to piRNAs and rsRNAs and the Discussion section, with input from D.T.C., J.G. and E.R.J. X.C. contributed to data interpretation in regard to miRNA and miRBase. P.S., X.-l.Y. and B.K. contributed to data interpretation of mitochondrial tsRNAs and discussed the evolutionary aspects. L. Zhao, C.Z., W.G., D.T.C., J.G. and E.R.J. contributed to the interpretation and discussion of data. Q.C. T.Z., Ying Zhang (Chinese Academy of Sciences) and J.S. wrote the main manuscript and integrated input from all authors. The authors declare no competing interests. Peer review information: Nature Cell Biology thanks the anonymous reviewers for their contribution to the peer review of this work.

Errata

Shi, J., Zhang, Y., Tan, D. et al. Author Correction: PANDORA-seq expands the repertoire of regulatory small RNAs by overcoming RNA modifications. Nat Cell Biol (2021). https://doi.org/10.1038/s41556-021-00687-w

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Additional details

Created:
August 22, 2023
Modified:
December 22, 2023