IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-48626-1.html
   My bibliography  Save this article

Genome-scale analysis of interactions between genetic perturbations and natural variation

Author

Listed:
  • Joseph J. Hale

    (University of Southern California)

  • Takeshi Matsui

    (SLAC National Accelerator Laboratory)

  • Ilan Goldstein

    (University of Southern California)

  • Martin N. Mullis

    (University of Southern California)

  • Kevin R. Roy

    (Stanford University
    Stanford University School of Medicine)

  • Christopher Ne Ville

    (University of Southern California)

  • Darach Miller

    (SLAC National Accelerator Laboratory)

  • Charley Wang

    (University of Southern California)

  • Trevor Reynolds

    (University of Southern California)

  • Lars M. Steinmetz

    (Stanford University
    Stanford University School of Medicine
    Genome Biology Unit)

  • Sasha F. Levy

    (SLAC National Accelerator Laboratory
    BacStitch DNA)

  • Ian M. Ehrenreich

    (University of Southern California)

Abstract

Interactions between genetic perturbations and segregating loci can cause perturbations to show different phenotypic effects across genetically distinct individuals. To study these interactions on a genome scale in many individuals, we used combinatorial DNA barcode sequencing to measure the fitness effects of 8046 CRISPRi perturbations targeting 1721 distinct genes in 169 yeast cross progeny (or segregants). We identified 460 genes whose perturbation has different effects across segregants. Several factors caused perturbations to show variable effects, including baseline segregant fitness, the mean effect of a perturbation across segregants, and interacting loci. We mapped 234 interacting loci and found four hub loci that interact with many different perturbations. Perturbations that interact with a given hub exhibit similar epistatic relationships with the hub and show enrichment for cellular processes that may mediate these interactions. These results suggest that an individual’s response to perturbations is shaped by a network of perturbation-locus interactions that cannot be measured by approaches that examine perturbations or natural variation alone.

Suggested Citation

  • Joseph J. Hale & Takeshi Matsui & Ilan Goldstein & Martin N. Mullis & Kevin R. Roy & Christopher Ne Ville & Darach Miller & Charley Wang & Trevor Reynolds & Lars M. Steinmetz & Sasha F. Levy & Ian M. , 2024. "Genome-scale analysis of interactions between genetic perturbations and natural variation," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-48626-1
    DOI: 10.1038/s41467-024-48626-1
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-48626-1
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-024-48626-1?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. Ulrich Schlecht & Zhimin Liu & Jamie R. Blundell & Robert P. St.Onge & Sasha F. Levy, 2017. "A scalable double-barcode sequencing platform for characterization of dynamic protein-protein interactions," Nature Communications, Nature, vol. 8(1), pages 1-9, August.
    2. Suzanne L. Rutherford & Susan Lindquist, 1998. "Hsp90 as a capacitor for morphological evolution," Nature, Nature, vol. 396(6709), pages 336-342, November.
    3. Martin N. Mullis & Takeshi Matsui & Rachel Schell & Ryan Foree & Ian M. Ehrenreich, 2018. "The complex underpinnings of genetic background effects," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    4. Sasha F. Levy & Jamie R. Blundell & Sandeep Venkataram & Dmitri A. Petrov & Daniel S. Fisher & Gavin Sherlock, 2015. "Quantitative evolutionary dynamics using high-resolution lineage tracking," Nature, Nature, vol. 519(7542), pages 181-186, March.
    5. Matthew B. Taylor & Joann Phan & Jonathan T. Lee & Madelyn McCadden & Ian M. Ehrenreich, 2016. "Diverse genetic architectures lead to the same cryptic phenotype in a yeast cross," Nature Communications, Nature, vol. 7(1), pages 1-6, September.
    6. Christine Queitsch & Todd A. Sangster & Susan Lindquist, 2002. "Hsp90 as a capacitor of phenotypic variation," Nature, Nature, vol. 417(6889), pages 618-624, June.
    7. Giovanny Covarrubias-Pazaran, 2016. "Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-15, 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. Takeshi Matsui & Martin N. Mullis & Kevin R. Roy & Joseph J. Hale & Rachel Schell & Sasha F. Levy & Ian M. Ehrenreich, 2022. "The interplay of additivity, dominance, and epistasis on fitness in a diploid yeast cross," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    2. Pei Zhao & Chao Wang & Shuhong Sun & Xi Wang & William E. Balch, 2024. "Tracing genetic diversity captures the molecular basis of misfolding disease," Nature Communications, Nature, vol. 15(1), pages 1-22, December.
    3. Tracy Chih-Ting Koubkova-Yu & Jung-Chi Chao & Jun-Yi Leu, 2018. "Heterologous Hsp90 promotes phenotypic diversity through network evolution," PLOS Biology, Public Library of Science, vol. 16(11), pages 1-29, November.
    4. Saleh Alseekh & Annabella Klemmer & Jianbing Yan & Tingting Guo & Alisdair R. Fernie, 2025. "Embracing plant plasticity or robustness as a means of ensuring food security," Nature Communications, Nature, vol. 16(1), pages 1-12, December.
    5. Bryan Sands & Soo Yun & Alexander R. Mendenhall, 2021. "Introns control stochastic allele expression bias," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    6. D. Blanco-Obregon & K. El Marzkioui & F. Brutscher & V. Kapoor & L. Valzania & D. S. Andersen & J. Colombani & S. Narasimha & D. McCusker & P. Léopold & L. Boulan, 2022. "A Dilp8-dependent time window ensures tissue size adjustment in Drosophila," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    7. Casper J Breuker & James S Patterson & Christian Peter Klingenberg, 2006. "A Single Basis for Developmental Buffering of Drosophila Wing Shape," PLOS ONE, Public Library of Science, vol. 1(1), pages 1-7, December.
    8. Martina Hančová & Andrej Gajdoš & Jozef Hanč & Gabriela Vozáriková, 2021. "Estimating variances in time series kriging using convex optimization and empirical BLUPs," Statistical Papers, Springer, vol. 62(4), pages 1899-1938, August.
    9. Daniel P. G. H. Wong & Benjamin H. Good, 2024. "Quantifying the adaptive landscape of commensal gut bacteria using high-resolution lineage tracking," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    10. Luciano Rogério Braatz de Andrade & Massaine Bandeira e Sousa & Eder Jorge Oliveira & Marcos Deon Vilela de Resende & Camila Ferreira Azevedo, 2019. "Cassava yield traits predicted by genomic selection methods," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-22, November.
    11. Gaotian Zhang & Nicole M. Roberto & Daehan Lee & Steffen R. Hahnel & Erik C. Andersen, 2022. "The impact of species-wide gene expression variation on Caenorhabditis elegans complex traits," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    12. Sébastien Boyer & Lucas Hérissant & Gavin Sherlock, 2021. "Adaptation is influenced by the complexity of environmental change during evolution in a dynamic environment," PLOS Genetics, Public Library of Science, vol. 17(1), pages 1-27, January.
    13. Kaushik Bhattacharya & Samarpan Maiti & Szabolcs Zahoran & Lorenz Weidenauer & Dina Hany & Diana Wider & Lilia Bernasconi & Manfredo Quadroni & Martine Collart & Didier Picard, 2022. "Translational reprogramming in response to accumulating stressors ensures critical threshold levels of Hsp90 for mammalian life," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    14. Md. S. Islam & Per McCord & Quentin D. Read & Lifang Qin & Alexander E. Lipka & Sushma Sood & James Todd & Marcus Olatoye, 2022. "Accuracy of Genomic Prediction of Yield and Sugar Traits in Saccharum spp. Hybrids," Agriculture, MDPI, vol. 12(9), pages 1-22, September.
    15. Joao A. Ascensao & Kelly M. Wetmore & Benjamin H. Good & Adam P. Arkin & Oskar Hallatschek, 2023. "Quantifying the local adaptive landscape of a nascent bacterial community," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    16. Solip Park & Fran Supek & Ben Lehner, 2021. "Higher order genetic interactions switch cancer genes from two-hit to one-hit drivers," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    17. Ibrahim ElBasyoni & Mohamed Saadalla & Stephen Baenziger & Harold Bockelman & Sabah Morsy, 2017. "Cell Membrane Stability and Association Mapping for Drought and Heat Tolerance in a Worldwide Wheat Collection," Sustainability, MDPI, vol. 9(9), pages 1-16, September.
    18. Li Xie & Wenying Shou, 2021. "Steering ecological-evolutionary dynamics to improve artificial selection of microbial communities," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    19. Mathias Ruben Gemmer & Chris Richter & Yong Jiang & Thomas Schmutzer & Manish L Raorane & Björn Junker & Klaus Pillen & Andreas Maurer, 2020. "Can metabolic prediction be an alternative to genomic prediction in barley?," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-15, June.
    20. Reyna Persa & Martin Grondona & Diego Jarquin, 2021. "Development of a Genomic Prediction Pipeline for Maintaining Comparable Sample Sizes in Training and Testing Sets across Prediction Schemes Accounting for the Genotype-by-Environment Interaction," Agriculture, MDPI, vol. 11(10), pages 1-17, September.

    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:15:y:2024:i:1:d:10.1038_s41467-024-48626-1. 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.