A framework for studying behavioral evolution by reconstructing ancestral repertoires

  1. Damián G Hernández
  2. Catalina Rivera
  3. Jessica Cande
  4. Baohua Zhou
  5. David Stern
  6. Gordon J Berman  Is a corresponding author
  1. Centro Atómico Bariloche and Instituto Balseiro, Argentina
  2. Emory University, United States
  3. Janelia Research Campus, Howard Hughes Medical Institute, United States

Abstract

Although different animal species often exhibit extensive variation in many behaviors, typically scientists examine one or a small number of behaviors in any single study. Here, we propose a new framework to simultaneously study the evolution of many behaviors. We measured the behavioral repertoire of individuals from six species of fruit flies using unsupervised techniques and identified all stereotyped movements exhibited by each species. We then fit a Generalized Linear Mixed Model to estimate the intra- and inter-species behavioral covariances, and, by using the known phylogenetic relationships among species, we estimated the (unobserved) behaviors exhibited by ancestral species. We found that much of intra-specific behavioral variation has a similar covariance structure to previously described long-time scale variation in an individual’s behavior, suggesting that much of the measured variation between individuals of a single species in our assay reflects differences in the status of neural networks, rather than genetic or developmental differences between individuals. We then propose a method to identify groups of behaviors that appear to have evolved in a correlated manner, illustrating how sets of behaviors, rather than individual behaviors, likely evolved. Our approach provides a new framework for identifying co-evolving behaviors and may provide new opportunities to study the mechanistic basis of behavioral evolution.

Data availability

All behavioral region information is submitted with the article and will be posted publically, if accepted, on GitHub (https://github.com/bermanlabemory/behavioral-evolution). The original video data are too large to post (tens of TB), but will be made available upon request.

Article and author information

Author details

  1. Damián G Hernández

    Department of Medical Physics, Centro Atómico Bariloche and Instituto Balseiro, Bariloche, Argentina
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8995-7495
  2. Catalina Rivera

    Department of Physics, Emory University, Atlanta, United States
    Competing interests
    No competing interests declared.
  3. Jessica Cande

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    No competing interests declared.
  4. Baohua Zhou

    Department of Physics, Emory University, Atlanta, United States
    Competing interests
    No competing interests declared.
  5. David Stern

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1847-6483
  6. Gordon J Berman

    Department of Biology, Emory University, Atlanta, United States
    For correspondence
    gordon.berman@emory.edu
    Competing interests
    Gordon J Berman, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3588-7820

Funding

National Institute of Mental Health (MH115831-01)

  • Gordon J Berman

Human Frontiers Science Program (RGY0076/2018)

  • Gordon J Berman

Howard Hughes Medical Institute

  • Jessica Cande
  • David Stern
  • Gordon J Berman

Research Corporation for Science Advancement (25999)

  • Gordon J Berman

National Science Foundation (1806833)

  • Catalina Rivera

Ministerio de Ciencia y Tecnología, Gobierno de la Provincia de Córdoba

  • Damián G Hernández

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

Reviewing Editor

  1. Jesse H Goldberg, Cornell University, United States

Version history

  1. Preprint posted: July 17, 2020 (view preprint)
  2. Received: August 5, 2020
  3. Accepted: September 1, 2021
  4. Accepted Manuscript published: September 2, 2021 (version 1)
  5. Version of Record published: September 16, 2021 (version 2)

Copyright

© 2021, Hernández 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.

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  1. Damián G Hernández
  2. Catalina Rivera
  3. Jessica Cande
  4. Baohua Zhou
  5. David Stern
  6. Gordon J Berman
(2021)
A framework for studying behavioral evolution by reconstructing ancestral repertoires
eLife 10:e61806.
https://doi.org/10.7554/eLife.61806

Share this article

https://doi.org/10.7554/eLife.61806

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