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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2021
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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. |
format | Online Article Text |
id | pubmed-8445618 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
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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