Abstract
Post-transcriptional regulation via the mRNA poly(A) tail is fundamental to gene expression, yet a comprehensive dataset across an entire organism is still lacking. Here, we generated a pan-organ atlas of poly(A) tail lengths across 18 murine organs using full-length nanopore sequencing that totaled 422 million reads. This dataset enables robust, single-molecule poly(A) profiling for an average of 7421 genes per sample (≥20 reads). We observed notably heterogeneous and organ-specific poly(A) tail length landscapes, ranging from profiles peaking at ~45 nt in pancreas to ~180 nt in reproductive tissues. Clustering isoforms by cross-organ poly(A) dynamics reveals functionally coherent regulatory modules that are statistically orthogonal to those derived from transcript abundance. This orthogonality is biologically informative, as poly(A) length co-regulation predicts known functional interactions even among genes with divergent expression. Together, these findings establish poly(A) tail dynamics as an independent, functionally coherent regulatory layer and provide a foundational resource for deciphering this dimension of transcriptome regulation (https://zhailab.bio.sustech.edu.cn/mouse_atlas).
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Data availability
The FLEP-seq2 data generated in this study have been deposited in the Genome Sequence Archive at the National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation, under accession number CRA028430. The brain DRS data used in this study were obtained from previously published study under accession number PRJEB2759021. To facilitate community exploration, we have developed the Mouse Poly(A) Tail Atlas Database [https://zhailab.bio.sustech.edu.cn/mouse_atlas], an interactive data portal for visualizing and querying poly(A) tail length and expression profiles across all 18 organs. Source data are provided with this paper.
Code availability
The code for analysis and visualization of this study is available in the GitHub [https://github.com/ZhaiLab-SUSTech/Mouse_polya_atlas], including the full source code for the R Shiny web application and associated processing scripts [https://github.com/ZhaiLab-SUSTech/Mouse_polya_atlas/tree/main/scripts/web_app], and is archived on Zenodo with the https://doi.org/10.5281/zenodo.1883407354.
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Acknowledgements
The group of J.Z. is supported by National Natural Science Foundation of China (32325031, 32470601) and Shenzhen Science and Technology Program (Grant No. ZDSYS20230626091659010); Y.P.L. (Yanping Long) is supported by National Key R&D Program of China (2025YFA0923400) and the National Natural Science Foundation of China (32300479); W.L. is supported by the Shenzhen Fundamental Research Program (JCYJ20250604144520027). Y.L. (Yan Li) is supported by National Natural Science Foundation of China (82372768) and Natural Science Foundation of Shenzhen (JCYJ20240813145421029); Z.Z. is supported by the National Science Fund for Distinguished Young Scholars (82025022), the Shenzhen Science and Technology Program (ZDSYS20210623091810030) and the Shenzhen High-level Hospital Construction Fund (23250G1003); S.L. is supported by National Natural Science Foundation of China (32222039); Y.P. is supported by Shenzhen Science and Technology Program (JCYJ20220530162816036). Y.F. is supported by Shenzhen Key Medical Discipline Construction Fund (SZXK079). This work was supported by Center for Computational Science and Engineering at Southern University of Science and Technology.
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J.Z., Y.L., Z.Z. and Y.F. conceived and designed the experiments. Y.P.L., S.W., X.W. and Y.P. performed the experiments. H.L., Y.P.L. and J.Z. analyzed the data. Z.L., W.L., Y.S., H.Z., M.Z., Y.G., S.L., L.R., Y.F. and Y.X. provided materials and conceptual insights. J.Z., Y.L., Z.Z. and Y.F. supervised the study. H.L., Y.P.L. and J.Z. wrote the manuscript, and all authors reviewed and revised the final version.
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Lei, H., Long, Y., Wu, S. et al. Pan-organ poly(A) atlas reveals a post-transcriptional regulatory layer independent of RNA abundance. Nat Commun (2026). https://doi.org/10.1038/s41467-026-71703-6
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DOI: https://doi.org/10.1038/s41467-026-71703-6
