Brain transcriptomics of agonistic behaviour in the weakly electric fish Gymnotus omarorum, a wild teleost model of non-breeding aggression

Author:

Eastman Guillermo,Valiño Guillermo,Radío Santiago,Young Rebecca L.ORCID,Quintana Laura,Zakon Harold H.,Hofmann Hans A.ORCID,Sotelo-Silveira José,Silva AnaORCID

Abstract

AbstractDifferences in social status are often mediated by agonistic encounters between competitors. Robust literature has examined social status-dependent brain gene expression profiles across vertebrates, yet social status and reproductive state are often confounded. It has therefore been challenging to identify the neuromolecular mechanisms underlying social status independent of reproductive state. Weakly electric fish, Gymnotus omarorum, display territorial aggression and social dominance independent of reproductive state. We use wild-derived G. omarorum males to conduct a transcriptomic analysis of non-breeding social dominance relationships. After allowing paired rivals to establish a dominance hierarchy, we profiled the transcriptomes of brain sections containing the preoptic area (region involved in regulating aggressive behaviour) in dominant and subordinate individuals. We identified 16 differentially expressed genes (FDR < 0.05) and numerous genes that co-varied with behavioural traits. We also compared our results with previous reports of differential gene expression in other teleost species. Overall, our study establishes G. omarorum as a powerful model system for understanding the neuromolecular bases of social status independent of reproductive state.

Funder

Agencia Nacional de Investigación e Innovación

Programa de Desarrollo de las Ciencias Básicas

National Science Foundation BEACON Science and Technology Center

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3