1. Genetics and Genomics
Download icon

Generation of a versatile BiFC ORFeome library for analyzing protein-protein interactions in live Drosophila

  1. Johannes Bischof
  2. Marilyne Duffraisse
  3. Edy Furger
  4. Leiore Ajuria
  5. Guillaume Giraud
  6. Solene Vanderperre
  7. Rachel Paul
  8. Mikael Björklund
  9. Damien Ahr
  10. Alexis W Ahmed
  11. Lionel Spinelli
  12. Christine Brun
  13. Konrad Basler
  14. Samir Merabet  Is a corresponding author
  1. University of Zurich, Switzerland
  2. Institut de Génomique Fonctionnelle de Lyon, France
  3. Zhejiang University, China
  4. Aix Marseille University, France
Tools and Resources
  • Cited 8
  • Views 3,649
  • Annotations
Cite this article as: eLife 2018;7:e38853 doi: 10.7554/eLife.38853

Abstract

Transcription factors achieve specificity by establishing intricate interaction networks that will change depending on the cell context. Capturing these interactions in live condition is however a challenging issue that requires sensitive and non-invasive methods. We present a set of fly lines, called 'multicolor BiFC library', which covers most of the Drosophila transcription factors for performing Bimolecular Fluorescence Complementation (BiFC). The multicolor BiFC library can be used to probe two different binary interactions simultaneously and is compatible for large-scale interaction screens. The library can also be coupled with established Drosophila genetic resources to analyze interactions in the developmentally relevant expression domain of each protein partner. We provide proof of principle experiments of these various applications, using Hox proteins in the live Drosophila embryo as a case study. Overall this novel collection of ready-to-use fly lines constitutes an unprecedented genetic toolbox for the identification and analysis of protein-protein interactions in vivo.

Article and author information

Author details

  1. Johannes Bischof

    Institute of Molecular Life Sciences, University of Zurich, Zürich, Switzerland
    Competing interests
    Johannes Bischof, involved in maintaining and distributing the fly lines via the not-for-profit FlyORF project. There are no other competing interests to declare.
  2. Marilyne Duffraisse

    ENS Lyon UMR5242, Institut de Génomique Fonctionnelle de Lyon, Lyon, France
    Competing interests
    No competing interests declared.
  3. Edy Furger

    Institute of Molecular Life Sciences, University of Zurich, Zürich, Switzerland
    Competing interests
    No competing interests declared.
  4. Leiore Ajuria

    ENS Lyon UMR5242, Institut de Génomique Fonctionnelle de Lyon, Lyon, France
    Competing interests
    No competing interests declared.
  5. Guillaume Giraud

    ENS Lyon UMR5242, Institut de Génomique Fonctionnelle de Lyon, Lyon, France
    Competing interests
    No competing interests declared.
  6. Solene Vanderperre

    ENS Lyon UMR5242, Institut de Génomique Fonctionnelle de Lyon, Lyon, France
    Competing interests
    No competing interests declared.
  7. Rachel Paul

    ENS Lyon UMR5242, Institut de Génomique Fonctionnelle de Lyon, Lyon, France
    Competing interests
    No competing interests declared.
  8. Mikael Björklund

    Zhejiang University-University of Edinburgh Institute, Zhejiang University, Haining, China
    Competing interests
    Mikael Björklund, involved in the development of the FlyORF resource. There are no other competing interests to declare.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2176-681X
  9. Damien Ahr

    ENS Lyon UMR5242, Institut de Génomique Fonctionnelle de Lyon, Lyon, France
    Competing interests
    No competing interests declared.
  10. Alexis W Ahmed

    ENS Lyon UMR5242, Institut de Génomique Fonctionnelle de Lyon, Lyon, France
    Competing interests
    No competing interests declared.
  11. Lionel Spinelli

    TAGC U1090, Aix Marseille University, Marseille, France
    Competing interests
    No competing interests declared.
  12. Christine Brun

    TAGC U1090, Aix Marseille University, Marseille, France
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5563-6765
  13. Konrad Basler

    Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
    Competing interests
    Konrad Basler, involved in maintaining and distributing the fly lines via the not-for-profit FlyORF project. There are no other competing interests to declare.
  14. Samir Merabet

    ENS Lyon UMR5242, Institut de Génomique Fonctionnelle de Lyon, Lyon, France
    For correspondence
    samir.merabet@ens-lyon.fr
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7629-703X

Funding

Fondation pour la Recherche Médicale (1122556)

  • Johannes Bischof
  • Marilyne Duffraisse
  • Edy Furger
  • Leiore Ajuria
  • Guillaume Giraud
  • Solene Vanderperre
  • Rachel Paul
  • Samir Merabet

Cefipra

  • Johannes Bischof
  • Marilyne Duffraisse
  • Edy Furger
  • Leiore Ajuria
  • Guillaume Giraud
  • Solene Vanderperre
  • Rachel Paul
  • Samir Merabet

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

Reviewing Editor

  1. K VijayRaghavan, National Centre for Biological Sciences, Tata Institute of Fundamental Research, India

Publication history

  1. Received: June 1, 2018
  2. Accepted: September 18, 2018
  3. Accepted Manuscript published: September 24, 2018 (version 1)
  4. Version of Record published: October 9, 2018 (version 2)

Copyright

© 2018, Bischof 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

  • 3,649
    Page views
  • 613
    Downloads
  • 8
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

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)

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

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

Further reading

    1. Evolutionary Biology
    2. Genetics and Genomics
    Paloma Diaz-Maroto et al.
    Research Article Updated

    The study of South American camelids and their domestication is a highly debated topic in zooarchaeology. Identifying the domestic species (alpaca and llama) in archaeological sites based solely on morphological data is challenging due to their similarity with respect to their wild ancestors. Using genetic methods also presents challenges due to the hybridization history of the domestic species, which are thought to have extensively hybridized following the Spanish conquest of South America that resulted in camelids slaughtered en masse. In this study, we generated mitochondrial genomes for 61 ancient South American camelids dated between 3,500 and 2,400 years before the present (Early Formative period) from two archaeological sites in Northern Chile (Tulán-54 and Tulán-85), as well as 66 modern camelid mitogenomes and 815 modern mitochondrial control region sequences from across South America. In addition, we performed osteometric analyses to differentiate big and small body size camelids. A comparative analysis of these data suggests that a substantial proportion of the ancient vicuña genetic variation has been lost since the Early Formative period, as it is not present in modern specimens. Moreover, we propose a domestication hypothesis that includes an ancient guanaco population that no longer exists. Finally, we find evidence that interbreeding practices were widespread during the domestication process by the early camelid herders in the Atacama during the Early Formative period and predating the Spanish conquest.

    1. Evolutionary Biology
    2. Genetics and Genomics
    Jordan A Anderson et al.
    Research Article

    Aging, for virtually all life, is inescapable. However, within populations, biological aging rates vary. Understanding sources of variation in this process is central to understanding the biodemography of natural populations. We constructed a DNA methylation-based age predictor for an intensively studied wild baboon population in Kenya. Consistent with findings in humans, the resulting 'epigenetic clock' closely tracks chronological age, but individuals are predicted to be somewhat older or younger than their known ages. Surprisingly, these deviations are not explained by the strongest predictors of lifespan in this population, early adversity and social integration. Instead, they are best predicted by male dominance rank: high-ranking males are predicted to be older than their true ages, and epigenetic age tracks changes in rank over time. Our results argue that achieving high rank for male baboons—the best predictor of reproductive success—imposes costs consistent with a 'live fast, die young' life history strategy.