IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-37610-w.html
   My bibliography  Save this article

Chance promoter activities illuminate the origins of eukaryotic intergenic transcriptions

Author

Listed:
  • Haiqing Xu

    (University of Michigan
    Stanford University)

  • Chuan Li

    (University of Michigan
    Microsoft)

  • Chuan Xu

    (University of Michigan
    Shanghai Jiao Tong University)

  • Jianzhi Zhang

    (University of Michigan)

Abstract

It is debated whether the pervasive intergenic transcription from eukaryotic genomes has functional significance or simply reflects the promiscuity of RNA polymerases. We approach this question by comparing chance promoter activities with the expression levels of intergenic regions in the model eukaryote Saccharomyces cerevisiae. We build a library of over 105 strains, each carrying a 120-nucleotide, chromosomally integrated, completely random sequence driving the potential transcription of a barcode. Quantifying the RNA concentration of each barcode in two environments reveals that 41–63% of random sequences have significant, albeit usually low, promoter activities. Therefore, even in eukaryotes, where the presence of chromatin is thought to repress transcription, chance transcription is prevalent. We find that only 1–5% of yeast intergenic transcriptions are unattributable to chance promoter activities or neighboring gene expressions, and these transcriptions exhibit higher-than-expected environment-specificity. These findings suggest that only a minute fraction of intergenic transcription is functional in yeast.

Suggested Citation

  • Haiqing Xu & Chuan Li & Chuan Xu & Jianzhi Zhang, 2023. "Chance promoter activities illuminate the origins of eukaryotic intergenic transcriptions," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37610-w
    DOI: 10.1038/s41467-023-37610-w
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-37610-w
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-023-37610-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jason Gertz & Eric D. Siggia & Barak A. Cohen, 2009. "Analysis of combinatorial cis-regulation in synthetic and genomic promoters," Nature, Nature, vol. 457(7226), pages 215-218, January.
    2. Zhenyu Xu & Wu Wei & Julien Gagneur & Fabiana Perocchi & Sandra Clauder-Münster & Jurgi Camblong & Elisa Guffanti & Françoise Stutz & Wolfgang Huber & Lars M. Steinmetz, 2009. "Bidirectional promoters generate pervasive transcription in yeast," Nature, Nature, vol. 457(7232), pages 1033-1037, February.
    3. Helen Neil & Christophe Malabat & Yves d’Aubenton-Carafa & Zhenyu Xu & Lars M. Steinmetz & Alain Jacquier, 2009. "Widespread bidirectional promoters are the major source of cryptic transcripts in yeast," Nature, Nature, vol. 457(7232), pages 1038-1042, February.
    4. Joseph A. Martens & Lisa Laprade & Fred Winston, 2004. "Intergenic transcription is required to repress the Saccharomyces cerevisiae SER3 gene," Nature, Nature, vol. 429(6991), pages 571-574, June.
    5. Avihu H. Yona & Eric J. Alm & Jeff Gore, 2018. "Random sequences rapidly evolve into de novo promoters," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    6. Matthew J Hangauer & Ian W Vaughn & Michael T McManus, 2013. "Pervasive Transcription of the Human Genome Produces Thousands of Previously Unidentified Long Intergenic Noncoding RNAs," PLOS Genetics, Public Library of Science, vol. 9(6), pages 1-13, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bingnan Li & Patrice Zeis & Yujie Zhang & Alisa Alekseenko & Eliska Fürst & Yerma Pareja Sanchez & Gen Lin & Manu M. Tekkedil & Ilaria Piazza & Lars M. Steinmetz & Vicent Pelechano, 2023. "Differential regulation of mRNA stability modulates transcriptional memory and facilitates environmental adaptation," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    2. Jan Zrimec & Xiaozhi Fu & Azam Sheikh Muhammad & Christos Skrekas & Vykintas Jauniskis & Nora K. Speicher & Christoph S. Börlin & Vilhelm Verendel & Morteza Haghir Chehreghani & Devdatt Dubhashi & Ver, 2022. "Controlling gene expression with deep generative design of regulatory DNA," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    3. Komal Soni & Anusree Sivadas & Attila Horvath & Nikolay Dobrev & Rippei Hayashi & Leo Kiss & Bernd Simon & Klemens Wild & Irmgard Sinning & Tamás Fischer, 2023. "Mechanistic insights into RNA surveillance by the canonical poly(A) polymerase Pla1 of the MTREC complex," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    4. Charlotte Cautereels & Jolien Smets & Peter Bircham & Dries De Ruysscher & Anna Zimmermann & Peter De Rijk & Jan Steensels & Anton Gorkovskiy & Joleen Masschelein & Kevin J. Verstrepen, 2024. "Combinatorial optimization of gene expression through recombinase-mediated promoter and terminator shuffling in yeast," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    5. Muir Morrison & Manuel Razo-Mejia & Rob Phillips, 2021. "Reconciling kinetic and thermodynamic models of bacterial transcription," PLOS Computational Biology, Public Library of Science, vol. 17(1), pages 1-30, January.
    6. Hrant Hovhannisyan & Toni Gabaldón, 2021. "The long non-coding RNA landscape of Candida yeast pathogens," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    7. Manuel Cambón & Óscar Sánchez, 2022. "Thermodynamic Modelling of Transcriptional Control: A Sensitivity Analysis," Mathematics, MDPI, vol. 10(13), pages 1-18, June.
    8. Kota Hamamoto & Yusuke Umemura & Shiho Makino & Takashi Fukaya, 2023. "Dynamic interplay between non-coding enhancer transcription and gene activity in development," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    9. Travis L. LaFleur & Ayaan Hossain & Howard M. Salis, 2022. "Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    10. Xavier Contreras & David Depierre & Charbel Akkawi & Marina Srbic & Marion Helsmoortel & Maguelone Nogaret & Matthieu LeHars & Kader Salifou & Alexandre Heurteau & Olivier Cuvier & Rosemary Kiernan, 2023. "PAPγ associates with PAXT nuclear exosome to control the abundance of PROMPT ncRNAs," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    11. Farzaneh Khajouei & Saurabh Sinha, 2018. "An information theoretic treatment of sequence-to-expression modeling," PLOS Computational Biology, Public Library of Science, vol. 14(9), pages 1-24, September.
    12. Reiner-Benaim Anat & Davis Ronald W. & Juneau Kara, 2014. "Scan statistics analysis for detection of introns in time-course tiling array data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(2), pages 173-190, April.
    13. Benjamin J. E. Martin & LeAnn J. Howe, 2022. "Reply to: Pitfalls in using phenanthroline to study the causal relationship between promoter nucleosome acetylation and transcription," Nature Communications, Nature, vol. 13(1), pages 1-4, December.
    14. Rok Grah & Tamar Friedlander, 2020. "The relation between crosstalk and gene regulation form revisited," PLOS Computational Biology, Public Library of Science, vol. 16(2), pages 1-24, February.
    15. Kotchaphorn Mangkalaphiban & Lianwu Fu & Ming Du & Kari Thrasher & Kim M. Keeling & David M. Bedwell & Allan Jacobson, 2024. "Extended stop codon context predicts nonsense codon readthrough efficiency in human cells," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    16. Kroll, K.M. & Ferrantini, A. & Domany, E., 2010. "Introduction to biology and chromosomal instabilities in cancer," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(20), pages 4374-4388.
    17. Benjamin J. M. Tremblay & Cristina P. Santini & Yajiao Cheng & Xue Zhang & Stefanie Rosa & Julia I. Qüesta, 2024. "Interplay between coding and non-coding regulation drives the Arabidopsis seed-to-seedling transition," Nature Communications, Nature, vol. 15(1), pages 1-21, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37610-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.