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Adaptive transcription-splicing resynchronization upon losing an essential splicing factor


Essential genes form the core of a genome and are therefore thought to be indispensable for cellular viability. However, recent findings have challenged this notion in that cells may survive in the absence of some essential genes provided that relevant genetic modifiers are in existence. We therefore hypothesized that the loss of an essential gene may not always be fatefully detrimental; instead, it may pave the way towards genome evolution. We experimentally tested this hypothesis in the context of pre-messenger RNA splicing by evolving yeast cells harbouring a permanent loss of the essential splicing factor Prp28 in the presence of a genetic modifier. Here, we show that cellular fitness can be restored by compensatory mutations that alter either the splicing machinery per se or the Spt–Ada–Gcn5 acetyltransferase transcription co-activator complex in the cells with no Prp28. Biochemical and genetic analysis revealed that slowing down transcription compensates for splicing deficiency, which in turn boosts cellular fitness. In addition, we found that inefficient splicing also conversely decreases nascent RNA production. Taken together, our data suggest that transcription-splicing synchronization contributes to robustness in the gene-expression pathway and argue that the intrinsic interconnectivity within a biological system can be exploited for compensatory evolution and system re-optimization.

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Data availability

Genome sequencing and RNA-Seq data that support the findings of this study have been deposited in GenBank under BioProject identifier PRJNA431703.

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  1. 1.

    Rancati, G., Moffat, J., Typas, A. & Pavelka, N. Emerging and evolving concepts in gene essentiality. Nat. Rev. Genet. 19, 34–49 (2018).

  2. 2.

    Dowell, R. D. et al. Genotype to phenotype: a complex problem. Science 328, 469 (2010).

  3. 3.

    Liu, G. W. et al. Gene essentiality is a quantitative property linked to cellular evolvability. Cell 163, 1388–1399 (2015).

  4. 4.

    Chen, S., Zhang, Y. E. & Long, M. New genes in Drosophila quickly become essential. Science 330, 1682–1685 (2010).

  5. 5.

    Kim, D. U. et al. Analysis of a genome-wide set of gene deletions in the fission yeast Schizosaccharomyces pombe. Nat. Biotechnol. 28, 617–623 (2010).

  6. 6.

    Georgi, B., Voight, B. F. & Bucan, M. From mouse to human: evolutionary genomics analysis of human orthologs of essential genes. PLoS Genet. 9, e1003484 (2013).

  7. 7.

    Chen, W. & Moore, M. J. The spliceosome: disorder and dynamics defined. Curr. Opin. Struct. Biol. 24, 141–149 (2014).

  8. 8.

    Chang, T. H., Tung, L., Yeh, F. L., Chen, J. H. & Chang, S. L. Functions of the DExD/H-box proteins in nuclear pre-mRNA splicing. Biochim. Biophys. Acta 1829, 764–774 (2013).

  9. 9.

    Staley, J. P. & Guthrie, C. An RNA switch at the 5′ splice site requires ATP and the DEAD box protein Prp28p. Mol. Cell 3, 55–64 (1999).

  10. 10.

    Chen, J. Y. et al. Specific alterations of U1-C protein or U1 small nuclear RNA can eliminate the requirement of Prp28p, an essential DEAD box splicing factor. Mol. Cell 7, 227–232 (2001).

  11. 11.

    Hage, R. et al. A targeted bypass screen identifies Ynl187p, Prp42p, Snu71p, and Cbp80p for stable U1 snRNP/pre-mRNA interaction. Mol. Cell. Biol. 29, 3941–3952 (2009).

  12. 12.

    Du, H., Tardiff, D. F., Moore, M. J. & Rosbash, M. Effects of the U1C L13 mutation and temperature regulation of yeast commitment complex formation. Proc. Natl Acad. Sci. USA 101, 14841–14846 (2004).

  13. 13.

    Yona, A. H. et al. Chromosomal duplication is a transient evolutionary solution to stress. Proc. Natl Acad. Sci. USA 109, 21010–21015 (2012).

  14. 14.

    Szamecz, B. et al. The genomic landscape of compensatory evolution. PLoS Biol. 12, e1001935 (2014).

  15. 15.

    Han, Y., Luo, J., Ranish, J. & Hahn, S. Architecture of the Saccharomyces cerevisiae SAGA transcription coactivator complex. EMBO J. 33, 2534–2546 (2014).

  16. 16.

    Bonnet, J. et al. The SAGA coactivator complex acts on the whole transcribed genome and is required for RNA polymerase II transcription. Genes Dev. 28, 1999–2012 (2014).

  17. 17.

    Bhaumik, S. R. & Green, M. R. Differential requirement of SAGA components for recruitment of TATA-box-binding protein to promoters in vivo. Mol. Cell. Biol. 22, 7365–7371 (2002).

  18. 18.

    Braberg, H. et al. From structure to systems: high-resolution, quantitative genetic analysis of RNA polymerase II. Cell 154, 775–788 (2013).

  19. 19.

    Moehle, E. A., Braberg, H., Krogan, N. J. & Guthrie, C. Adventures in time and space: splicing efficiency and RNA polymerase II elongation rate. RNA Biol. 11, 313–319 (2014).

  20. 20.

    Munding, E. M., Shiue, L., Katzman, S., Donohue, J. P. & Ares, M. Competition between pre-mRNAs for the splicing machinery drives global regulation of splicing. Mol. Cell 51, 338–348 (2013).

  21. 21.

    Kaplan, C. D., Jin, H. Y., Zhang, I. L. & Belyanin, A. Dissection of pol II trigger loop function and pol II activity-dependent control of start site selection in vivo. PLoS Genet. 8, e1002627 (2012).

  22. 22.

    Herzel, L., Ottoz, D. S. M., Alpert, T. & Neugebauer, K. M. Splicing and transcription touch base: co-transcriptional spliceosome assembly and function. Nat. Rev. Mol. Cell Biol. 18, 637–650 (2017).

  23. 23.

    Chathoth, K. T., Barrass, J. D., Webb, S. & Beggs, J. D. A splicing-dependent transcriptional checkpoint associated with prespliceosome formation. Mol. Cell 53, 779–790 (2014).

  24. 24.

    Gunderson, F. Q. & Johnson, T. L. Acetylation by the transcriptional coactivator Gcn5 plays a novel role in co-transcriptional spliceosome assembly. PLoS Genet. 5, e1000682 (2009).

  25. 25.

    Pelechano, V., Chavez, S. & Perez-Ortin, J. E. A complete set of nascent transcription rates for yeast genes. PLoS ONE 5, e15442 (2010).

  26. 26.

    DiCarlo, J. E. et al. Genome engineering in Saccharomyces cerevisiae using CRISPR–Cas systems. Nucleic Acids Res. 41, 4336–4343 (2013).

  27. 27.

    Agarwal, R., Schwer, B. & Shuman, S. Structure–function analysis and genetic interactions of the Luc7 subunit of the Saccharomyces cerevisiae U1 snRNP. RNA 22, 1302–1310 (2016).

  28. 28.

    Bai, R., Wan, R., Yan, C., Lei, J. & Shi, Y. Structures of the fully assembled Saccharomyces cerevisiae spliceosome before activation. Science 360, 1423–1429 (2018).

  29. 29.

    Rancati, G. et al. Aneuploidy underlies rapid adaptive evolution of yeast cells deprived of a conserved cytokinesis motor. Cell 135, 879–893 (2008).

  30. 30.

    Van Leeuwen, J. et al. Exploring genetic suppression interactions on a global scale. Science 354, aag0839 (2016).

  31. 31.

    Guthrie, C. & Fink, G. R. Guide to Yeast Genetics and Molecular Biology Vol. 194 (Academic Press, San Diego, 1991).

  32. 32.

    Lu, Y. J., Swamy, K. B. & Leu, J. Y. Experimental evolution reveals interplay between Sch9 and polyploid stability in yeast. PLoS Genet. 12, e1006409 (2016).

  33. 33.

    Lieu, P. T., Jozsi, P., Gilles, P. & Peterson, T. Development of a DNA-labeling system for array-based comparative genomic hybridization. J. Biomol. Tech. 16, 104–111 (2005).

  34. 34.

    Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

  35. 35.

    Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013).

  36. 36.

    Roberts, A. & Pachter, L. Streaming fragment assignment for real-time analysis of sequencing experiments. Nat. Methods 10, 71–73 (2013).

  37. 37.

    Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L. & Wold, B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Methods 5, 621–628 (2008).

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We thank S.-Y. Tung, Y.-N. Chen and S.-T. Yu for help with genome sequencing, C. Kaplan for the rpb1 strains, J.-Y. Leu for the Cas9 plasmids, C.-F. Kao for advice on nascent transcript analysis, and M. J. McDonald, J.-Y. Leu, M. Ares, M.-C. Yao and members of the Yao and Chang laboratories for commenting on the manuscript. S.-L.C. was supported by an Academia Sinica Postdoctoral Fellowship. T.-H.C. was supported by grants from the Ministry of Science and Technology (MOST 105-2627-M-001-002 and 105-2311-B-001-059), Academia Sinica and MOST (MOST 106-0210-01-15-02 and 107-0210-01-19-01), and the Academia Sinica Thematic Project (AS-103-TP-B12).

Author information

S.-L.C. and T.-H.C. conceived the project. S.-L.C. designed and conducted the experiments. S.-L.C. and H.-K.W. conducted the bioinformatics analysis. S.-L.C., L.T. and T.-H.C. analysed the data. S.-L.C. and T.-H.C. wrote the paper.

Competing interests

The authors declare no competing interests.

Correspondence to Tien-Hsien Chang.

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Fig. 1: Evolved cells improved fitness and splicing.
Fig. 2: Attenuation of transcription improves fitness and splicing efficiency in the ancestor.
Fig. 3: Four additional evolved lines restored splicing efficiency and decreased nascent RNA production.
Fig. 4: Ancestral reconstruction of the adaptive alleles.