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CrY2H-seq: a massively multiplexed assay for deep-coverage interactome mapping

Nature Methods volume 14, pages 819825 (2017) | Download Citation

Abstract

Broad-scale protein–protein interaction mapping is a major challenge given the cost, time, and sensitivity constraints of existing technologies. Here, we present a massively multiplexed yeast two-hybrid method, CrY2H-seq, which uses a Cre recombinase interaction reporter to intracellularly fuse the coding sequences of two interacting proteins and next-generation DNA sequencing to identify these interactions en masse. We applied CrY2H-seq to investigate sparsely annotated Arabidopsis thaliana transcription factors interactions. By performing ten independent screens testing a total of 36 million binary interaction combinations, and uncovering a network of 8,577 interactions among 1,453 transcription factors, we demonstrate CrY2H-seq′s improved screening capacity, efficiency, and sensitivity over those of existing technologies. The deep-coverage network resource we call AtTFIN-1 recapitulates one-third of previously reported interactions derived from diverse methods, expands the number of known plant transcription factor interactions by three-fold, and reveals previously unknown family-specific interaction module associations with plant reproductive development, root architecture, and circadian coordination.

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Acknowledgements

This material is based upon work supported by US Department of Energy grant DOE-DE SC0007078 (to J.R.E.); National Science Foundation grants IOS-1650227 (to J.R.E.), IOS1456950, and IOS1546873 (to M.G.); and the Graduate Research Fellowship Program under grant number DGE-1650112 (to S.A.T.). J.R.E. is an Investigator of the Howard Hughes Medical Institute. S.A.T. is supported in part by the Mary K. Chapman Foundation. We thank M. Hofree, B. Haas, S. Navlakha, A.R. Carvunis, H. Carter, and T. Ideker for network analysis advice; S. Heinz, J. Chory, J. Law, L. Song, H. Chen, Y. He, M. Hariharan, B. Kellman, J. Reyna, L. Gai, and V. Lundblad lab members for advice and discussion; J. Pruneda-Paz (UCSD, California) for the TF ORF collection; H. Yu (Cornell University, New York) for pDEST-AD and pDEST-DB plasmids; and D. Hill (CCSB DFCI, Massachusetts) for Y8930 and Y8800 yeast strains.

Author information

Author notes

    • Adeline Goubil
    • , Joseph Feeney
    • , Ronan O'Malley
    •  & Mary Galli

    Present addresses: National Institute for Agricultural Research, Paris, France (A.G.); Goodreads, Amazon Inc., San Francisco, California, USA (J.F.); United States Department of Energy Joint Genome Institute, Walnut Creek, California, USA (R.O.); Waksman Institute of Microbiology, Rutgers University, Piscataway, New Jersey, USA (M.G.).

Affiliations

  1. Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, California, USA.

    • Shelly A Trigg
    • , Renee M Garza
    • , Andrew MacWilliams
    • , Joseph R Nery
    • , Anna Bartlett
    • , Rosa Castanon
    • , Adeline Goubil
    • , Joseph Feeney
    • , Ronan O'Malley
    • , Shao-shan C Huang
    • , Zhuzhu Z Zhang
    • , Mary Galli
    •  & Joseph R Ecker
  2. Division of Biological Sciences, University of California, San Diego, La Jolla, California, USA.

    • Shelly A Trigg
  3. Plant Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, California, USA.

    • Ronan O'Malley
    • , Shao-shan C Huang
    •  & Joseph R Ecker
  4. Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, California, USA.

    • Shao-shan C Huang
    •  & Joseph R Ecker

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Contributions

J.R.E. conceived the project. S.A.T., R.M.G., R.O., M.G., and J.R.E. designed and/or advised research. S.A.T., R.M.G., A.M., J.R.N., A.B., R.C., A.G., and M.G. performed experiments. S.A.T. established bioinformatics pipelines and performed computational analysis with contributions from J.F., R.O., S.C.H., and Z.Z.Z. S.A.T., M.G., and J.R.E. prepared the manuscript.

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–15

  2. 2.

    Supplementary Protocol

    CrY2H-seq interactome screening

Excel files

  1. 1.

    Supplementary Table 1

    Primers used for adding CRE reporter to yeast strain, adding lox sites to plasmids, and detecting Cre-recombined ORFs.

  2. 2.

    Supplementary Table 2

    a) CrY2H-seq prey and bait libraries screened.b) An expanded Arabidopsis transcrition factor network. AtTFIN-1 interactions indicated by replicate and NPIF values. Literature and database interactions are listed with a value of 1, except for AraNet and STRING for which overlap is listed with the value given by the respective database. Gene family names are taken from TableS3 from Pruneda-Paz et al. Protein names are taken from AraPort (https://www.araport.org/) and from UniProt (http://www.uniprot.org/).c) Bait and prey orientations that could be determined for 4264 AtTFIN-1 interactions.

  3. 3.

    Supplementary Table 3

    a) All TFs detected with empty pADlox plasmid and determined to be self-activating proteins.b) All PPIs detected with self-activating proteins including linkages with empty pADlox plasmid that were removed from the data (ccdB_gene denotes the pADlox plasmid sequence). 'Rep' refers to the CrY2Hseq replicate screen each interaction was detected in. The number of normalized protein interaction fragments is listed for each CrY2H-seq replicate the interaction was detected.

  4. 4.

    Supplementary Table 4

    AtTFIN-1 pairs retested in 1x1 Y2H. 1x1 retest score, 0 = negative,1=positve, SA = Self-activated

  5. 5.

    Supplementary Table 5

    a) AtTFIN-1 pairs tested in wNAPPA.b) wNAPPA normalization pairs.

  6. 6.

    Supplementary Table 6

    Literature and database protein-protein interaction data sources used for assessing AtTFIN-1.

Zip files

  1. 1.

    Supplementary Software

    1) CrY2H-seq analysis pipeline.2) Generating datasets of random pairs.3) Estimating screening saturation (related to Fig. 3c and Supplementary Fig. 7).4) Bait and prey orientation analysis pipeline.

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DOI

https://doi.org/10.1038/nmeth.4343

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