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A framework for studying behavioral evolution by reconstructing ancestral repertoires

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...

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Autores principales: Hernández, Damián G, Rivera, Catalina, Cande, Jessica, Zhou, Baohua, Stern, David L, Berman, Gordon J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8445618/
https://www.ncbi.nlm.nih.gov/pubmed/34473052
http://dx.doi.org/10.7554/eLife.61806
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author Hernández, Damián G
Rivera, Catalina
Cande, Jessica
Zhou, Baohua
Stern, David L
Berman, Gordon J
author_facet Hernández, Damián G
Rivera, Catalina
Cande, Jessica
Zhou, Baohua
Stern, David L
Berman, Gordon J
author_sort Hernández, Damián G
collection PubMed
description 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.
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spelling pubmed-84456182021-09-17 A framework for studying behavioral evolution by reconstructing ancestral repertoires Hernández, Damián G Rivera, Catalina Cande, Jessica Zhou, Baohua Stern, David L Berman, Gordon J eLife Evolutionary Biology 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. eLife Sciences Publications, Ltd 2021-09-02 /pmc/articles/PMC8445618/ /pubmed/34473052 http://dx.doi.org/10.7554/eLife.61806 Text en © 2021, Hernández et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Evolutionary Biology
Hernández, Damián G
Rivera, Catalina
Cande, Jessica
Zhou, Baohua
Stern, David L
Berman, Gordon J
A framework for studying behavioral evolution by reconstructing ancestral repertoires
title A framework for studying behavioral evolution by reconstructing ancestral repertoires
title_full A framework for studying behavioral evolution by reconstructing ancestral repertoires
title_fullStr A framework for studying behavioral evolution by reconstructing ancestral repertoires
title_full_unstemmed A framework for studying behavioral evolution by reconstructing ancestral repertoires
title_short A framework for studying behavioral evolution by reconstructing ancestral repertoires
title_sort framework for studying behavioral evolution by reconstructing ancestral repertoires
topic Evolutionary Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8445618/
https://www.ncbi.nlm.nih.gov/pubmed/34473052
http://dx.doi.org/10.7554/eLife.61806
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