An expanded toolkit for Drosophila gene tagging using synthesized homology donor constructs for CRISPR mediated homologous recombination

  1. Oguz Kanca  Is a corresponding author
  2. Jonathan Zirin
  3. Yanhui Hu
  4. Burak Tepe
  5. Debdeep Dutta
  6. Wen-Wen Lin
  7. Liwen Ma
  8. Ming Ge
  9. Zhongyuan Zuo
  10. Lu-Ping Liu
  11. Robert W Levis
  12. Norbert Perrimon
  13. Hugo J Bellen  Is a corresponding author
  1. Baylor College of Medicine, United States
  2. Harvard Medical School, United States
  3. Carnegie Institution for Science, United States

Abstract

Previously, we described a large collection of Drosophila strains that each carry an artificial exon containing a T2AGAL4 cassette inserted in an intron of a target gene based on CRISPR-mediated homologous recombination (Lee et al., 2018). These alleles permit numerous applications and have proven to be very useful. Initially, the homologous recombination-based donor constructs had long homology arms (>500 bps) to promote precise integration of large constructs (>5kb). Recently, we showed that in vivo linearization of the donor constructs enables insertion of large artificial exons in introns using short homology arms (100-200 bps) (Kanca et al., 2019a). Shorter homology arms make it feasible to commercially synthesize homology donors and minimize the cloning steps for donor construct generation. Unfortunately, about 58% of Drosophila genes lack a suitable coding intron for integration of artificial exons in all of the annotated isoforms. Here, we report the development of new set of constructs that allow the replacement of the coding region of genes that lack suitable introns with a KozakGAL4 cassette, generating a knock-out/knock-in allele that expresses GAL4 similarly as the targeted gene. We also developed custom vector backbones to further facilitate and improve transgenesis. Synthesis of homology donor constructs in custom plasmid backbones that contain the target gene sgRNA obviates the need to inject a separate sgRNA plasmid and significantly increases the transgenesis efficiency. These upgrades will enable the targeting of nearly every fly gene, regardless of exon-intron structure, with a 70-80% success rate.

Data availability

Source data for the graphs in Supplementary table 1 is included above the graphs in Supplementary table 1. The list of all the generated alleles and the method used can be found in Supplementary table 2.

The following previously published data sets were used

Article and author information

Author details

  1. Oguz Kanca

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    For correspondence
    kanca@bcm.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5438-0879
  2. Jonathan Zirin

    Department of Genetics, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Yanhui Hu

    Department of Genetics, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Burak Tepe

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Debdeep Dutta

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Wen-Wen Lin

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Liwen Ma

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Ming Ge

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Zhongyuan Zuo

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Lu-Ping Liu

    Department of Genetics, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Robert W Levis

    Department of Embryology, Carnegie Institution for Science, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3453-2390
  12. Norbert Perrimon

    Department of Genetics, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7542-472X
  13. Hugo J Bellen

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    For correspondence
    hbellen@bcm.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5992-5989

Funding

National Institute of General Medical Sciences (R01GM067858)

  • Hugo J Bellen

Office of Research Infrastructure Programs, National Institutes of Health (R24OD031447)

  • Oguz Kanca
  • Hugo J Bellen

Office of Research Infrastructure Programs, National Institutes of Health (R24OD031447)

  • Hugo J Bellen

National Institute of Neurological Disorders and Stroke (U54NS093793)

  • Hugo J Bellen

Huffington Foundation

  • Hugo J Bellen

National Institute of General Medical Sciences (GM067761)

  • Jonathan Zirin
  • Yanhui Hu
  • Norbert Perrimon

National Institute of General Medical Sciences (GM084947)

  • Jonathan Zirin
  • Yanhui Hu
  • Norbert Perrimon

Howard Hughes Medical Institute

  • Norbert Perrimon

Carnegie Institution for Science

  • Robert W Levis

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2022, Kanca et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 4,714
    views
  • 1,002
    downloads
  • 57
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Oguz Kanca
  2. Jonathan Zirin
  3. Yanhui Hu
  4. Burak Tepe
  5. Debdeep Dutta
  6. Wen-Wen Lin
  7. Liwen Ma
  8. Ming Ge
  9. Zhongyuan Zuo
  10. Lu-Ping Liu
  11. Robert W Levis
  12. Norbert Perrimon
  13. Hugo J Bellen
(2022)
An expanded toolkit for Drosophila gene tagging using synthesized homology donor constructs for CRISPR mediated homologous recombination
eLife 11:e76077.
https://doi.org/10.7554/eLife.76077

Share this article

https://doi.org/10.7554/eLife.76077

Further reading

    1. Chromosomes and Gene Expression
    Pei-Tseng Lee, Jonathan Zirin ... Hugo J Bellen
    Tools and Resources Updated

    We generated a library of ~1000 Drosophila stocks in which we inserted a construct in the intron of genes allowing expression of GAL4 under control of endogenous promoters while arresting transcription with a polyadenylation signal 3’ of the GAL4. This allows numerous applications. First, ~90% of insertions in essential genes cause a severe loss-of-function phenotype, an effective way to mutagenize genes. Interestingly, 12/14 chromosomes engineered through CRISPR do not carry second-site lethal mutations. Second, 26/36 (70%) of lethal insertions tested are rescued with a single UAS-cDNA construct. Third, loss-of-function phenotypes associated with many GAL4 insertions can be reverted by excision with UAS-flippase. Fourth, GAL4 driven UAS-GFP/RFP reports tissue and cell-type specificity of gene expression with high sensitivity. We report the expression of hundreds of genes not previously reported. Finally, inserted cassettes can be replaced with GFP or any DNA. These stocks comprise a powerful resource for assessing gene function.

    1. Chromosomes and Gene Expression
    2. Genetics and Genomics
    Hans Tobias Gustafsson, Lucas Ferguson ... Oliver J Rando
    Research Article

    Among the major classes of RNAs in the cell, tRNAs remain the most difficult to characterize via deep sequencing approaches, as tRNA structure and nucleotide modifications can each interfere with cDNA synthesis by commonly-used reverse transcriptases (RTs). Here, we benchmark a recently-developed RNA cloning protocol, termed Ordered Two-Template Relay (OTTR), to characterize intact tRNAs and tRNA fragments in budding yeast and in mouse tissues. We show that OTTR successfully captures both full-length tRNAs and tRNA fragments in budding yeast and in mouse reproductive tissues without any prior enzymatic treatment, and that tRNA cloning efficiency can be further enhanced via AlkB-mediated demethylation of modified nucleotides. As with other recent tRNA cloning protocols, we find that a subset of nucleotide modifications leave misincorporation signatures in OTTR datasets, enabling their detection without any additional protocol steps. Focusing on tRNA cleavage products, we compare OTTR with several standard small RNA-Seq protocols, finding that OTTR provides the most accurate picture of tRNA fragment levels by comparison to "ground truth" Northern blots. Applying this protocol to mature mouse spermatozoa, our data dramatically alter our understanding of the small RNA cargo of mature mammalian sperm, revealing a far more complex population of tRNA fragments - including both 5′ and 3′ tRNA halves derived from the majority of tRNAs – than previously appreciated. Taken together, our data confirm the superior performance of OTTR to commercial protocols in analysis of tRNA fragments, and force a reappraisal of potential epigenetic functions of the sperm small RNA payload.