Abstract
Poly(A) tails are added to the 3′ ends of most mRNAs in a non-templated manner and play essential roles in post-transcriptional regulation, including mRNA export, stability and translation. Measuring poly(A) tails is critical for understanding their regulatory roles in almost every aspect of biological and medical studies. Previous methods for analyzing poly(A) tails require large amounts of input RNA (microgram-level total RNA), which limits their application. We recently developed a poly(A) inclusive full-length RNA isoform-sequencing method (PAIso-seq) at single-oocyte-level sensitivity (a single mammalian oocyte contains ~0.5 ng of total RNA) based on PacBio sequencing that enabled accurate measurement of the poly(A) tail length and non-A residues within the body of poly(A) tails along with the full-length cDNA, providing the opportunity to study precious in vivo samples with very limited input material. Here, we describe a detailed protocol for PAIso-seq library preparation from single mouse oocytes or bulk oocyte samples. In addition, we provide a complete bioinformatic pipeline to perform the analysis from the raw data to downstream analysis. The minimum time required is ~14.5 h for PAIso-seq double-stranded cDNA preparation, 2 d for PacBio sequencing in HiFi mode and 8 h for the initial data analysis.
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Data availability
The data used in this study for bioinformatic analysis are from our published dataset18. The PAIso-seq CCS reads in fastq format we previously deposited18 are available in the NCBI Sequence Read Archive under the accession number PRJNA529588. For this protocol, we uploaded the raw subread data for the GV_rep2 and SCGV datasets, which had not been deposited before, to the GSA hosted by the National Genomic Data Center (https://ngdc.cncb.ac.cn/gsa/) under the accession number CRA005547. The CCS read data containing the PSIs in fastq format are available in GSA under the accession number CRA005706, and the accompanying pass number files are available in GitHub (https://github.com/Lulab-IGDB/PAIso-seq_scripts/blob/main/polyA_spike-in_pass_file/).
Code availability
Custom scripts used for data analysis are available at GitHub: https://github.com/Lulab-IGDB/PAIso-seq_scripts.
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Acknowledgements
We thank Hu Nie for help in the bioinformatic analysis. This work was supported by the National Key Research and Development Program of China (2018YFA0107001), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA24020203), the National Natural Science Foundation of China (31970588, 32170606 and 81891001), the Natural Science Foundation of Heilongjiang province (YQ2020C003), the China Postdoctoral Science Foundation (2020M670516 and 2020T130687) and the State Key Laboratory of Molecular Developmental Biology.
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Y.L., J.W. and F.L. conceived and designed the study. Y.L. developed the method and performed the experiments. Y.Z. performed part of the bioinformatic analysis. Y.L., J.W. and F.L. designed the computational pipeline, analyzed the data and wrote the manuscript.
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Y.L. and F.L. are named inventors on a patent (number: 201910837492.2) filed by the Institute of Genetics and Developmental Biology covering the PAIso-seq method. The other authors declare no competing interests.
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Nature Protocols thanks Qingshun Quinn Li and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Additional initial assessment was performed by informal referee Andrzej Dziembowski.
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Liu, Y. et al. Nat. Commun. 10, 5292 (2019): https://doi.org/10.1038/s41467-019-13228-9
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Liu, Y., Zhang, Y., Wang, J. et al. Transcriptome-wide measurement of poly(A) tail length and composition at subnanogram total RNA sensitivity by PAIso-seq. Nat Protoc 17, 1980–2007 (2022). https://doi.org/10.1038/s41596-022-00704-8
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DOI: https://doi.org/10.1038/s41596-022-00704-8
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