Abstract
Understanding the evolution of mate choice requires dissecting the mechanisms of female preference, particularly how these differ among social contexts and preference phenotypes. Here, we studied the female neurogenomic response after only 10 min of mate exposure in both a sensory component (optic tectum) and a decision-making component (telencephalon) of the brain. By comparing the transcriptional response between females with and without preferences for colourful males, we identified unique neurogenomic elements associated with the female preference phenotype that are not present in females without preference. A network analysis revealed different properties for this response at the sensory-processing and the decision-making levels, and we show that this response is highly centralized in the telencephalon. Furthermore, we identified an additional set of genes that vary in expression across social contexts, beyond mate evaluation. We show that transcription factors among these loci are predicted to regulate the transcriptional response of the genes we found to be associated with female preference.
Similar content being viewed by others
Data availability
References
Zayed, A. & Robinson, G. E. Understanding the relationship between brain gene expression and social behavior: lessons from the honey bee. Annu. Rev. Genet. 46, 591–615 (2012).
O’Connell, L. A. & Hofmann, H. A. Genes, hormones, and circuits: an integrative approach to study the evolution of social behavior. Front. Neuroendocrinol. 32, 320–335 (2011).
Cummings, M. E. The mate choice mind: studying mate preference, aversion and social cognition in the female poeciliid brain. Anim. Behav. 103, 249–258 (2015).
Ghalambor, C. K. et al. Non-adaptive plasticity potentiates rapid adaptive evolution of gene expression in nature. Nature 525, 372–375 (2015).
Hitzemann, R. et al. Genes, behavior and next‐generation RNA sequencing. Genes Brain Behav. 12, 1–12 (2013).
Rosenthal, G. G. Mate Choice. The Evolution of Sexual Decision Making from Microbes to Humans (Princeton Univ. Press, Princeton, 2017).
Zahavi, A. Mate selection—a selection for a handicap. J. Theor. Biol. 53, 205–214 (1975).
Kokko, H., Brooks, R., Jennions, M. D. & Morley, J. The evolution of mate choice and mating biases. Proc. R. Soc. Lond. B 270, 653–664 (2003).
Robinson, G. E., Fernald, R. D. & Clayton, D. F. Genes and social behavior. Science 322, 896–900 (2008).
Whitney, O. et al. Core and region-enriched networks of behaviorally regulated genes and the singing genome. Science 346, 1256780 (2014).
Clayton, D. F. The genomic action potential. Neurobiol. Learn. Mem. 74, 185–216 (2000).
Wang, S. M. T., Ramsey, M. E. & Cummings, M. E. Plasticity of the mate choice mind: courtship evokes choice‐like brain responses in females from a coercive mating system. Genes Brain Behav. 13, 365–375 (2014).
Cardoso, S. D., Teles, M. C. & Oliveira, R. F. Neurogenomic mechanisms of social plasticity. J. Exp. Biol. 218, 140–149 (2015).
Cummings, M. E. et al. Sexual and social stimuli elicit rapid and contrasting genomic responses. Proc. R. Soc. B 275, 393–402 (2008)..
Lynch, K. S., Ramsey, M. E. & Cummings, M. E. The mate choice brain: comparing gene profiles between female choice and male coercive poeciliids. Genes Brain Behav. 11, 222–229 (2012).
Ramsey, M. E., Maginnis, T. L., Wong, R. Y., Brock, C. & Cummings, M. E. Identifying context-specific gene profiles of social, reproductive, and mate preference behavior in a fish species with female mate choice. Front. Neurosci. 6, 62 (2012).
Wong, R. Y., Oxendine, S. E. & Godwin, J. Behavioral and neurogenomic transcriptome changes in wild-derived zebrafish with fluoxetine treatment. BMC Genomics 14, 1 (2013).
Teles, M. C., Cardoso, S. D. & Oliveira, R. F. Social plasticity relies on different neuroplasticity mechanisms across the brain social decision-making network in zebrafish. Front. Behav. Neurosci. https://doi.org/10.3389/fnbeh.2016.00016 (2016).
Taborsky, B. & Oliveira, R. F. Social competence: an evolutionary approach. Trends. Ecol. Evol. 27, 679–688 (2012).
Weitekamp, C. A. & Hofmann, H. A. Evolutionary themes in the neurobiology of social cognition. Curr. Opin. Neurobiol. 28, 22–27 (2014).
Dukas, R. Evolutionary biology of animal cognition. Annu. Rev. Ecol. Evol. Syst. 35, 347–374 (2004).
Woolley, S. C. & Doupe, A. J. Social context–induced song variation affects female behavior and gene expression. PLoS Biol. 6, e62 (2008).
Houde, A. E. Sex, Color, and Mate Choice in Guppies (Princeton Univ. Press, Princeton, 1997).
Endler, J. A. Multiple-trait coevolution and environmental gradients in guppies. Trends Ecol. Evol. 10, 22–29 (1995).
Brooks, R. Variation in female mate choice within guppy populations: population divergence, multiple ornaments and the maintenance of polymorphism. Genetica 116, 343–358 (2002).
Houde, A. E. & Endler, J. A. Correlated evolution of female mating preferences and male color patterns in the guppy Poecilia reticulata. Science 248, 1405–1408 (1990).
Endler, J. A. & Houde, A. E. Geographic variation in female preferences for male traits in Poecilia reticulata. Evolution 49, 456–468 (1995).
Brooks, R. & Endler, J. A. Female guppies agree to differ: phenotypic and genetic variation in mate‐choice behavior and the consequences for sexual selection. Evolution 55, 1644–1655 (2001).
Sandkam, B., Young, C. M. & Breden, F. Beauty in the eyes of the beholders: colour vision is tuned to mate preference in the Trinidadian guppy (Poecilia reticulata). Mol. Ecol. 24, 596–609 (2015).
Hughes, K. A., Houde, A. E., Price, A. C. & Rodd, F. H. Mating advantage for rare males in wild guppy populations. Nature 503, 108–110 (2013).
Rodd, F. H., Hughes, K. A., Grether, G. F. & Baril, C. T. A possible non-sexual origin of mate preference: are male guppies mimicking fruit? Proc. R. Soc. Lond. B 269, 475–481 (2002).
Corral Lopez, A. et al. Female brain size affects the assessment of male attractiveness during mate choice. Sci. Adv. 3, e1601990 (2017).
Kotrschal, A. et al. Artificial selection on relative brain size in the guppy reveals costs and benefits of evolving a larger brain. Curr. Biol. 23, 168–171 (2013).
Chen, Y.-C. et al. Expression change in Angiopoietin-1 underlies change in relative brain size in fish. Proc. R. Soc. B 282, 20150872 (2015).
Replogle, K. et al. The Songbird Neurogenomics (SoNG) Initiative: community-based tools and strategies for study of brain gene function and evolution. BMC Genomics 9, 131 (2008).
Northcutt, R. G. Forebrain evolution in bony fishes. Brain Res. Bull. 75, 191–205 (2008).
Bshary, R., Gingins, S. & Vail, A. L. Social cognition in fishes. Trends Cogn. Sci. 18, 465–471 (2014).
Salas, C. et al. Neuropsychology of learning and memory in teleost fish. Zebrafish 3, 157–171 (2006).
Derycke, S. et al. Neurogenomic profiling reveals distinct gene expression profiles between brain parts that are consistent in Ophthalmotilapia cichlids. Front. Neurosci. 12, e1002962 (2018).
Lindholm, A. & Breden, F. Sex chromosomes and sexual selection in poeciliid fishes. Am. Nat. 160, S214–S24 (2010).
Kirkpatrick, M. & Hall, D. W. Sexual selection and sex linkage. Evolution 58, 683–691 (2004).
Kirkpatrick, M. & Ryan, M. J. The evolution of mating preferences and the paradox of the lek. Nature 350, 33–38 (1991).
Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinform. 9, 559 (2008).
Zhang, B. & Horvath, S. A general framework for weighted gene co-expression network analysis. Stat. Appl. Genet. Mol. Biol. 4, 17 (2005).
Iancu, O. D., Colville, A., Darakjian, P. & Hitzemann, R. Coexpression and cosplicing network approaches for the study of mammalian brain transcriptomes. Int. Rev. Neurobiol. 116, 73–93 (2014).
Cummings, M. E. Sexual conflict and sexually dimorphic cognition—reviewing their relationship in poeciliid fishes. Behav. Ecol. Sociobiol. 72, 73 (2018).
Galizia, G. & Lledo, P.-M. Neurosciences—From Molecule to Behavior: A University Textbook (Springer Science & Business Media, Berlin, 2013).
Langfelder, P. & Horvath, S. Fast R functions for robust correlations and hierarchical clustering. J. Stat. Softw. 46, i11 (2012).
Jeong, H., Mason, S. P., Barabási, A. L. & Oltvai, Z. N. Lethality and centrality in protein networks. Nature 411, 41–42 (2001).
Ramsey, M. E., Vu, W. & Cummings, M. E. Testing synaptic plasticity in dynamic mate choice decisions: N-methyl d-aspartate receptor blockade disrupts female preference. Proc. R. Soc. B 281, 20140047 (2014).
Krumm, N., O’Roak, B. J., Shendure, J. & Eichler, E. E. A de novo convergence of autism genetics and molecular neuroscience. Trends Neurosci. 37, 95–105 (2014).
Greco, B. et al. Autism-related behavioral abnormalities in synapsin knockout mice. Behav. Brain Res. 251, 65–74 (2013).
Larhammar, D., Nordström, K. & Larsson, T. A. Evolution of vertebrate rod and cone phototransduction genes. Phil. Trans. R. Soc. B 364, 2867–2880 (2009).
Moriguchi, S. et al. Reduced CaM kinase II and CaM kinase IV activities underlie cognitive deficits in NCKX2 heterozygous mice. Mol. Neurobiol. 21, 1–12 (2017).
Cummings, M. E. & Ramsey, M. E. Mate choice as social cognition: predicting female behavioral and neural plasticity as a function of alternative male reproductive tactics. Curr. Opin. Behav. Sci. 6, 125–131 (2015).
Wolf, C. & Linden, D. E. J. Biological pathways to adaptability—interactions between genome, epigenome, nervous system and environment for adaptive behavior. Genes Brain Behav. 11, 3–28 (2012).
Cui, R., Delclos, P. J., Schumer, M. & Rosenthal, G. G. Early social learning triggers neurogenomic expression changes in a swordtail fish. Proc. R. Soc. B 284, 20170701 (2017).
Okuyama, T. et al. A neural mechanism underlying mating preferences for familiar individuals in Medaka fish. Science 343, 91–94 (2014).
Minatohara, K., Akiyoshi, M. & Okuno, H. Role of immediate-early genes in synaptic plasticity and neuronal ensembles underlying the memory trace. Front. Mol. Neurosci. 8, 78 (2015).
Cummings, M. E. Looking for sexual selection in the female brain. Phil. Trans. R. Soc. B 367, 2348–2356 (2012).
Kowiański, P. et al. BDNF: a key factor with multipotent impact on brain signaling and synaptic plasticity. Cell. Mol. Neurobiol. 38, 579–593 (2018).
Reimand, J. et al. g:Profiler-a web server for functional interpretation of gene lists (2016 update). Nucleic Acids Res. 44, W83–W89 (2016).
Herbert, J. Peptides in the limbic system: neurochemical codes for co-ordinated adaptive responses to behavioural and physiological demand. Prog. Neurobiol. 41, 723–791 (1993).
O’Connell, L. A. & Hofmann, H. A. The vertebrate mesolimbic reward system and social behavior network: a comparative synthesis. J. Comp. Neurol. 519, 3599–3639 (2011).
O’Connell, L. A. & Hofmann, H. A. Evolution of a vertebrate social decision-making network. Science 336, 1154–1157 (2012).
Alexander, H. J., Taylor, J. S., Wu, S. S. T. & Breden, F. Parallel evolution and vicariance in the guppy (Poecilia reticulata) over multiple spatial and temporal scales. Evolution 60, 2352–2369 (2006).
Suk, H. Y. & Neff, B. D. Microsatellite genetic differentiation among populations of the Trinidadian guppy. Heredity 102, 425–434 (2009).
Kotrschal, A., Corral Lopez, A., Amcoff, M. & Kolm, N. A larger brain confers a benefit in a spatial mate search learning task in male guppies. Behav. Ecol. 26, 527–532 (2015).
van der Bijl, W., Thyselius, M., Kotrschal, A. & Kolm, N. Brain size affects the behavioural response to predators in female guppies (Poecilia reticulata). Proc. R. Soc. B 282, 20151132 (2015).
Kotrschal, A., Kolm, N. & Penn, D. J. Selection for brain size impairs innate, but not adaptive immune responses. Proc. R. Soc. B 283, 20152857 (2016).
Kotrschal, A., Corral Lopez, A., Szidat, S. & Kolm, N. The effect of brain size evolution on feeding propensity, digestive efficiency, and juvenile growth. Evolution 69, 3013–3020 (2015).
Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).
Corral Lopez, A., Eckerström-Liedholm, S., Der Bijl, W. V., Kotrschal, A. & Kolm, N. No association between brain size and male sexual behavior in the guppy. Curr. Zool. 61, 265–273 (2015).
Corral Lopez, A., Garate-Olaizola, M., Buechel, S. D., Kolm, N. & Kotrschal, A. On the role of body size, brain size, and eye size in visual acuity. Behav. Ecol. Sociobiol. 71, 179 (2017).
Kotrschal, A. et al. Brain size does not impact shoaling dynamics in unfamiliar groups of guppies (Poecilia reticulata). Behav. Processes 147, 13–20 (2018).
Kotrschal, A. et al. Evolution of brain region volumes during artificial selection for relative brain size. Evolution 71, 2942–2951 (2017).
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
Künstner, A. et al. The genome of the Trinidadian guppy, Poecilia reticulata, and variation in the Guanapo population. PLoS ONE 11, e0169087 (2016).
Grabherr, M . G. et al. Trinity: reconstructing a full-length transcriptome without a genome from RNA-seq data. Nat. Biotechnol. 29, 644–652 (2011).
Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinform. 12, 323 (2011).
Pertea, M., Kim, D., Pertea, G. M., Leek, J. T. & Salzberg, S. L. Transcript-level expression analysis of RNA-Seq experiments with HISAT, StringTie and Ballgown. Nat. Protoc. 11, 1650–1667 (2016).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2. Genome Biol. 15, 550 (2014).
Slonim, D. K. From patterns to pathways: gene expression data analysis comes of age. Nat. Genet. 32 Suppl., 502–508 (2002).
Dean, R. & Mank, J. E. Tissue specificity and sex-specific regulatory variation permit the evolution of sex-biased gene expression. Am. Nat. 188, E74–E84 (2016).
Greenbaum, D., Colangelo, C., Williams, K. & Gerstein, M. Comparing protein abundance and mRNA expression levels on a genomic scale. Genome Biol. 4, 117 (2003).
Futcher, B., Latter, G. I., Monardo, P., McLaughlin, C. S. & Garrels, J. I. A sampling of the yeast proteome. Mol. Cell. Biol. 19, 7357–7368 (1999).
Lundberg, E. et al. Defining the transcriptome and proteome in three functionally different human cell lines. Mol. Syst. Biol. 6, 450 (2010).
Inbar, E. et al. The transcriptome of Leishmania major developmental stages in their natural sand fly vector. mBio 8, e00029–17 (2017).
Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).
Maslov, S. & Sneppen, K. Specificity and stability in topology of protein networks. Science 296, 910–913 (2002).
Suzuki, R. & Shimodaira, H. Pvclust: an R package for assessing the uncertainty in hierarchical clustering. Bioinformatics 22, 1540–1542 (2006).
Acknowledgements
This work was funded by a Marie Sklodowska-Curie Fellowship (654699) and a National Science Foundation Postdoctoral Fellowship in Biology (1523669) to N.I.B., by grant agreements 260233 and 680951 from the European Research Council to J.E.M., a Swedish Research Council grant (2016-03435) to N.K. and a Knut and Alice Wallenberg grant (102 2013.0072) to N.K. We gratefully acknowledge support from a Royal Society Wolfson Merit Award to J.E.M. We thank P. Almeida, I. Darolti, J. Morris, V. Oostra, A. Wright and T. Price for valuable discussions and help with manuscript preparation. We thank the Oxford Genomics Centre at the Wellcome Centre for Human Genetics (funded by a Wellcome Trust grant (reference 203141/Z/16/Z)) for the generation and initial processing of the sequencing data, and the UCL Legion High Performance Computing Facility (Legion@UCL).
Author information
Authors and Affiliations
Contributions
N.I.B., A.C.-L., N.K. and J.E.M. conceived of the study and designed the experiments. A.K. and N.K. created the brain size selection lines. A.K. and S.D.B. performed laboratory work for fish housekeeping. A.C.-L. and S.D.B. selected fish for the experiments. A.C.-L. performed the behavioural tests and dissected the brain regions. N.I.B. performed all laboratory RNA work and analysed the data. All authors contributed to writing the manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Supplementary Information
Supplementary Figures and Tables
Supplementary Data 1
Optic tectum normalized count data for differentially expressed genes
Supplementary Data 2
Telencephalon normalized count data for differentially expressed genes
Rights and permissions
About this article
Cite this article
Bloch, N.I., Corral-López, A., Buechel, S.D. et al. Early neurogenomic response associated with variation in guppy female mate preference. Nat Ecol Evol 2, 1772–1781 (2018). https://doi.org/10.1038/s41559-018-0682-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41559-018-0682-4
- Springer Nature Limited
This article is cited by
-
Transcriptomic changes in the posterior pallium of male zebra finches associated with social niche conformance
BMC Genomics (2024)
-
Functional convergence of genomic and transcriptomic architecture underlies schooling behaviour in a live-bearing fish
Nature Ecology & Evolution (2023)
-
Visual mate preference evolution during butterfly speciation is linked to neural processing genes
Nature Communications (2020)
-
The neurogenomic transition from territory establishment to parenting in a territorial female songbird
BMC Genomics (2019)
-
Altering social cue perception impacts honey bee aggression with minimal impacts on aggression-related brain gene expression
Scientific Reports (2019)