Genome organization around nuclear speckles drives mRNA splicing efficiency
- Creators
- Bhat, Prashant
- Chow, Amy
- Emert, Benjamin
- Ettlin, Olivia
- Quinodoz, Sofia A.
- Strehle, Mackenzie
- Takei, Yodai
- Burr, Alex
- Goronzy, Isabel N.
- Chen, Allen W.
- Huang, Wesley
- Ferrer, Jose Lorenzo M.
- Soehalim, Elizabeth
- Goh, Say-Tar
- Chari, Tara
- Sullivan, Delaney K.
- Blanco, Mario R.
- Guttman, Mitchell1
Abstract
The nucleus is highly organized, such that factors involved in the transcription and processing of distinct classes of RNA are confined within specific nuclear bodies1,2. One example is the nuclear speckle, which is defined by high concentrations of protein and noncoding RNA regulators of pre-mRNA splicing3. What functional role, if any, speckles might play in the process of mRNA splicing is unclear4,5. Here we show that genes localized near nuclear speckles display higher spliceosome concentrations, increased spliceosome binding to their pre-mRNAs and higher co-transcriptional splicing levels than genes that are located farther from nuclear speckles. Gene organization around nuclear speckles is dynamic between cell types, and changes in speckle proximity lead to differences in splicing efficiency. Finally, directed recruitment of a pre-mRNA to nuclear speckles is sufficient to increase mRNA splicing levels. Together, our results integrate the long-standing observations of nuclear speckles with the biochemistry of mRNA splicing and demonstrate a crucial role for dynamic three-dimensional spatial organization of genomic DNA in driving spliceosome concentrations and controlling the efficiency of mRNA splicing.
Copyright and License
© The Author(s), under exclusive licence to Springer Nature Limited 2024.
Acknowledgement
We thank D. Honson, E. Detmar and D. Perez for experimental help; B. Riviere, L. Pachter and N. Ollikainen for computational help; M. Flynn for the bidirectional reporter plasmid; L. Cai, M. Elowitz and A. Raj for reagents; F. Ding, H. Yin, J. Jachowicz, L. Frankiw and Y. Luo for discussions; B. Yeh for discussions about splicing efficiency calculations; I. Antoshechkin for sequencing; G. Spigola for microscopy advice; A. Lin for sequencing advice; B. Yeh, D. Honson and K. Leslie for critical comments on the manuscript; R. Maehr and K. Mohan Parsi for H1 ES cell lines; B. Wold and B. Williams for myocyte cell lines; and S. Hiley for editing. Illustrations in Figs. 1a,c–d,e,g2a,b, 3a,b, 4a, 5a–c and 6 and Extended Data Figs. 4b and 9 were created by I.-M. Strazhnik, Caltech. Imaging was performed at the Biological Imaging Facility with the support of the Caltech Beckman Institute and the Arnold and Mabel Beckman Foundation. This work was funded by NIH T32 GM 7616-40, NIH NRSA CA247447, the UCLA-Caltech Medical Scientist Training Program, a Chen Graduate Innovator Grant, and the Josephine De Karman Fellowship Trust (P.B.); and a HHMI Gilliam Fellowship, NSF GRFP Fellowship, and the HHMI Hanna H. Gray Fellows Program (S.A.Q.). This work was funded by the NIH 4DN program (U01 DK127420), NIH Directors’ Transformative Research Award (R01 DA053178), the NYSCF, CZI Ben Barres Early Career Acceleration Award, and funds from Caltech.
Contributions
P.B. and M.G. conceived the study, analysed data, interpreted results and wrote the manuscript. P.B., A.C. and M.G. designed experiments. B.E. performed RNA FISH and image analyses, including nuclear segmentation and spot detection. P.B., A.C., O.E. and W.H. generated plasmids for the MCP–MS2 experiments and performed co-transfection experiments for FACS. S.A.Q., E.S. and S.-T.G. generated mouse MM14 myocyte SPRITE data. M.R.B. generated H1 human ES cell SPRITE data. M.S. processed imaging data. P.B. and A.B. performed SC35 immunofluorescence combined with fluorescence microscopy for mCherry constructs. P.B. and A.W.C. performed 5EU RNA-seq. P.B and J.L.M.F. performed DNA FISH combined with SRRM1 immunofluorescence. Y.T analysed seqFISH+ data. I.N.G. generated computational assignment of speckle hubs for human SPRITE data. D.K.S. processed myocyte split-seq data using kallisto, and T.C. developed analytical methods for comparison of splicing efficiency between cell types. P.B. and M.G. supervised the work and M.G. acquired funding.
Data Availability
Sequencing datasets have been deposited into the GEO with accession identifier GSE247833.
Code Availability
Additional scripts and data are available at GitHub (https://github.com/GuttmanLab/speckle).
Conflict of Interest
S.A.Q. and M.G. are inventors on a patent covering the SPRITE method.
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Additional details
- ISSN
- 1476-4687
- URL
- https://rdcu.be/dHOqr
- California Institute of Technology
- Beckman Institute
- Arnold and Mabel Beckman Foundation
- National Institutes of Health
- NIH Predoctoral Fellowship T32 GM 7616-40
- National Institutes of Health
- NIH Predoctoral Fellowship NRSA CA247447
- National Institutes of Health
- NIH Predoctoral Fellowship UCLA-Caltech Medical Scientist Training Program
- California Institute of Technology
- Tianqiao and Chrissy Chen Institute for Neuroscience
- Josephine De Karman Fellowship Trust
- Howard Hughes Medical Institute
- National Science Foundation
- NSF Graduate Research Fellowship
- National Institutes of Health
- U01 DK127420
- National Institutes of Health
- R01 DA053178
- New York Stem Cell Foundation
- Chan Zuckerberg Initiative (United States)
- Caltech groups
- Division of Biology and Biological Engineering, Tianqiao and Chrissy Chen Institute for Neuroscience