Cargando…

Individual differences in honey bee behavior enabled by plasticity in brain gene regulatory networks

Understanding the regulatory architecture of phenotypic variation is a fundamental goal in biology, but connections between gene regulatory network (GRN) activity and individual differences in behavior are poorly understood. We characterized the molecular basis of behavioral plasticity in queenless...

Descripción completa

Detalles Bibliográficos
Autores principales: Jones, Beryl M, Rao, Vikyath D, Gernat, Tim, Jagla, Tobias, Cash-Ahmed, Amy C, Rubin, Benjamin ER, Comi, Troy J, Bhogale, Shounak, Husain, Syed S, Blatti, Charles, Middendorf, Martin, Sinha, Saurabh, Chandrasekaran, Sriram, Robinson, Gene E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755388/
https://www.ncbi.nlm.nih.gov/pubmed/33350385
http://dx.doi.org/10.7554/eLife.62850
_version_ 1783626344748285952
author Jones, Beryl M
Rao, Vikyath D
Gernat, Tim
Jagla, Tobias
Cash-Ahmed, Amy C
Rubin, Benjamin ER
Comi, Troy J
Bhogale, Shounak
Husain, Syed S
Blatti, Charles
Middendorf, Martin
Sinha, Saurabh
Chandrasekaran, Sriram
Robinson, Gene E
author_facet Jones, Beryl M
Rao, Vikyath D
Gernat, Tim
Jagla, Tobias
Cash-Ahmed, Amy C
Rubin, Benjamin ER
Comi, Troy J
Bhogale, Shounak
Husain, Syed S
Blatti, Charles
Middendorf, Martin
Sinha, Saurabh
Chandrasekaran, Sriram
Robinson, Gene E
author_sort Jones, Beryl M
collection PubMed
description Understanding the regulatory architecture of phenotypic variation is a fundamental goal in biology, but connections between gene regulatory network (GRN) activity and individual differences in behavior are poorly understood. We characterized the molecular basis of behavioral plasticity in queenless honey bee (Apis mellifera) colonies, where individuals engage in both reproductive and non-reproductive behaviors. Using high-throughput behavioral tracking, we discovered these colonies contain a continuum of phenotypes, with some individuals specialized for either egg-laying or foraging and ‘generalists’ that perform both. Brain gene expression and chromatin accessibility profiles were correlated with behavioral variation, with generalists intermediate in behavior and molecular profiles. Models of brain GRNs constructed for individuals revealed that transcription factor (TF) activity was highly predictive of behavior, and behavior-associated regulatory regions had more TF motifs. These results provide new insights into the important role played by brain GRN plasticity in the regulation of behavior, with implications for social evolution.
format Online
Article
Text
id pubmed-7755388
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher eLife Sciences Publications, Ltd
record_format MEDLINE/PubMed
spelling pubmed-77553882020-12-23 Individual differences in honey bee behavior enabled by plasticity in brain gene regulatory networks Jones, Beryl M Rao, Vikyath D Gernat, Tim Jagla, Tobias Cash-Ahmed, Amy C Rubin, Benjamin ER Comi, Troy J Bhogale, Shounak Husain, Syed S Blatti, Charles Middendorf, Martin Sinha, Saurabh Chandrasekaran, Sriram Robinson, Gene E eLife Ecology Understanding the regulatory architecture of phenotypic variation is a fundamental goal in biology, but connections between gene regulatory network (GRN) activity and individual differences in behavior are poorly understood. We characterized the molecular basis of behavioral plasticity in queenless honey bee (Apis mellifera) colonies, where individuals engage in both reproductive and non-reproductive behaviors. Using high-throughput behavioral tracking, we discovered these colonies contain a continuum of phenotypes, with some individuals specialized for either egg-laying or foraging and ‘generalists’ that perform both. Brain gene expression and chromatin accessibility profiles were correlated with behavioral variation, with generalists intermediate in behavior and molecular profiles. Models of brain GRNs constructed for individuals revealed that transcription factor (TF) activity was highly predictive of behavior, and behavior-associated regulatory regions had more TF motifs. These results provide new insights into the important role played by brain GRN plasticity in the regulation of behavior, with implications for social evolution. eLife Sciences Publications, Ltd 2020-12-22 /pmc/articles/PMC7755388/ /pubmed/33350385 http://dx.doi.org/10.7554/eLife.62850 Text en © 2020, Jones et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Ecology
Jones, Beryl M
Rao, Vikyath D
Gernat, Tim
Jagla, Tobias
Cash-Ahmed, Amy C
Rubin, Benjamin ER
Comi, Troy J
Bhogale, Shounak
Husain, Syed S
Blatti, Charles
Middendorf, Martin
Sinha, Saurabh
Chandrasekaran, Sriram
Robinson, Gene E
Individual differences in honey bee behavior enabled by plasticity in brain gene regulatory networks
title Individual differences in honey bee behavior enabled by plasticity in brain gene regulatory networks
title_full Individual differences in honey bee behavior enabled by plasticity in brain gene regulatory networks
title_fullStr Individual differences in honey bee behavior enabled by plasticity in brain gene regulatory networks
title_full_unstemmed Individual differences in honey bee behavior enabled by plasticity in brain gene regulatory networks
title_short Individual differences in honey bee behavior enabled by plasticity in brain gene regulatory networks
title_sort individual differences in honey bee behavior enabled by plasticity in brain gene regulatory networks
topic Ecology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755388/
https://www.ncbi.nlm.nih.gov/pubmed/33350385
http://dx.doi.org/10.7554/eLife.62850
work_keys_str_mv AT jonesberylm individualdifferencesinhoneybeebehaviorenabledbyplasticityinbraingeneregulatorynetworks
AT raovikyathd individualdifferencesinhoneybeebehaviorenabledbyplasticityinbraingeneregulatorynetworks
AT gernattim individualdifferencesinhoneybeebehaviorenabledbyplasticityinbraingeneregulatorynetworks
AT jaglatobias individualdifferencesinhoneybeebehaviorenabledbyplasticityinbraingeneregulatorynetworks
AT cashahmedamyc individualdifferencesinhoneybeebehaviorenabledbyplasticityinbraingeneregulatorynetworks
AT rubinbenjaminer individualdifferencesinhoneybeebehaviorenabledbyplasticityinbraingeneregulatorynetworks
AT comitroyj individualdifferencesinhoneybeebehaviorenabledbyplasticityinbraingeneregulatorynetworks
AT bhogaleshounak individualdifferencesinhoneybeebehaviorenabledbyplasticityinbraingeneregulatorynetworks
AT husainsyeds individualdifferencesinhoneybeebehaviorenabledbyplasticityinbraingeneregulatorynetworks
AT blatticharles individualdifferencesinhoneybeebehaviorenabledbyplasticityinbraingeneregulatorynetworks
AT middendorfmartin individualdifferencesinhoneybeebehaviorenabledbyplasticityinbraingeneregulatorynetworks
AT sinhasaurabh individualdifferencesinhoneybeebehaviorenabledbyplasticityinbraingeneregulatorynetworks
AT chandrasekaransriram individualdifferencesinhoneybeebehaviorenabledbyplasticityinbraingeneregulatorynetworks
AT robinsongenee individualdifferencesinhoneybeebehaviorenabledbyplasticityinbraingeneregulatorynetworks