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

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 ligati...

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Published inNature cell biology Vol. 23; no. 4; pp. 424 - 436
Main Authors Shi, Junchao, Zhang, Yunfang, Tan, Dongmei, Zhang, Xudong, Yan, Menghong, Zhang, Ying, Franklin, Reuben, Shahbazi, Marta, Mackinlay, Kirsty, Liu, Shichao, Kuhle, Bernhard, James, Emma R., Zhang, Liwen, Qu, Yongcun, Zhai, Qiwei, Zhao, Wenxin, Zhao, Linlin, Zhou, Changcheng, Gu, Weifeng, Murn, Jernej, Guo, Jingtao, Carrell, Douglas T., Wang, Yinsheng, Chen, Xuemei, Cairns, Bradley R., Yang, Xiang-lei, Schimmel, Paul, Zernicka-Goetz, Magdalena, Cheloufi, Sihem, Zhou, Tong, Chen, Qi
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 01.04.2021
Nature Publishing Group
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Summary: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. Shi et al. profiled small non-coding RNAs (sncRNAs) through PANDORA-seq, which identified tissue-specific transfer RNA- and ribosomal RNA-derived small RNAs, as well as sncRNAs, with dynamic changes during induced pluripotent stem cell reprogramming.
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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.
Author contributions
ISSN:1465-7392
1476-4679
1476-4679
DOI:10.1038/s41556-021-00652-7