Review Article

Genomic tools for behavioural ecologists to understand repeatable individual differences in behaviour

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Abstract

Behaviour is a key interface between an animal’s genome and its environment. Repeatable individual differences in behaviour have been extensively documented in animals, but the molecular underpinnings of behavioural variation among individuals within natural populations remain largely unknown. Here, we offer a critical review of when molecular techniques may yield new insights, and we provide specific guidance on how and whether the latest tools available are appropriate given different resources, system and organismal constraints, and experimental designs. Integrating molecular genetic techniques with other strategies to study the proximal causes of behaviour provides opportunities to expand rapidly into new avenues of exploration. Such endeavours will enable us to better understand how repeatable individual differences in behaviour have evolved, how they are expressed and how they can be maintained within natural populations of animals.

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References

  1. 1.

    Dingemanse, N. J., Both, C., Drent, P. J., van Oers, K. & van Noordwijk, A. J. Repeatability and heritability of exploratory behaviour in great tits from the wild. Anim. Behav. 64, 929–938 (2002).

  2. 2.

    Sih, A., Bell, A. & Johnson, J. C. Behavioral syndromes: an ecological and evolutionary overview. Trends Ecol. Evol. 19, 372–378 (2004).

  3. 3.

    Pruitt, J. N. & Keiser, C. N. The personality types of key catalytic individuals shape colonies’ collective behaviour and success. Anim. Behav. 93, 87–95 (2014).

  4. 4.

    Bengston, S. E. & Dornhaus, A. Be meek or be bold? A colony-level behavioural syndrome in ants. Proc. R. Soc. B 281, 20140518 (2014).

  5. 5.

    Mackay, T. F. C. Epistasis and quantitative traits: using model organisms to study gene-gene interactions. Nat. Rev. Genet. 15, 22–33 (2014).

  6. 6.

    Stamps, J. A. & Biro, P. A. Personality and individual differences in plasticity. Curr. Opin. Behav. Sci. 12, 18–23 (2016).

  7. 7.

    Dingemanse, N. J. & Wolf, M. Between-individual differences in behavioural plasticity within populations: causes and consequences. Anim. Behav. 85, 1031–1039 (2013).

  8. 8.

    Grafen, A. in Behavioural Ecology 2nd edn (eds Krebs, J. & Davies, N.) 62–84 (Blackwell, Oxford, 1984).

  9. 9.

    Bateson, P. & Laland, K. N. Tinbergen’s four questions: an appreciation and an update. Trends Ecol. Evol. 28, 712–718 (2013).

  10. 10.

    Stamps, J. Behavioural processes affecting development: Tinbergen’s fourth question comes of age. Anim. Behav. 66, 1–13 (2003).

  11. 11.

    Travisano, M. & Shaw, R. G. Lost in the map. Evolution 67, 305–314 (2013).

  12. 12.

    Paaby, A. B. & Rockman, M. V. The many faces of pleiotropy. Trends Genet. 29, 66–73 (2013).

  13. 13.

    Zuk, M. & Balenger, S. L. Behavioral ecology and genomics: new directions, or just a more detailed map? Behav. Ecol. 25, 1277–1282 (2014).

  14. 14.

    Fitzpatrick, M. J. et al. Candidate genes for behavioural ecology. Trends Ecol. Evol. 20, 96–104 (2005).

  15. 15.

    West-Eberhard, M. J. Developmental Plasticity and Evolution. (Oxford University Press: New York, 2003).

  16. 16.

    Saltz, J. B., Hessel, F. C. & Kelly, M. W. Trait correlations in the genomics era. Trends Ecol. Evol. 32, 279–290 (2017).

  17. 17.

    Sabeti, P. C. et al. Genome-wide detection and characterization of positive selection in human populations. Nature 449, 913–918 (2007).

  18. 18.

    Rittschof, C. C. et al. Neuromolecular responses to social challenge: common mechanisms across mouse, stickleback fish, and honey bee. Proc. Natl Acad. Sci. USA 111, 17929–17934 (2014).

  19. 19.

    Whitfield, C. W., Cziko, A.-M. & Robinson, G. E. gene expression profiles in the brain predict behavior in individual honey bees. Science 302, 296–299 (2003).

  20. 20.

    van Oers, K. & Mueller, J. C. Evolutionary genomics of animal personality. Phil. Trans. R. Soc. B 365, 3991–4000 (2010).

  21. 21.

    Stamps, J. A. & Frankenhuis, W. E. Bayesian models of development. Trends Ecol. Evol. 31, 260–268 (2016).

  22. 22.

    Sih, A. et al. Animal personality and state–behaviour feedbacks: a review and guide for empiricists. Trends Ecol. Evol. 30, 50–60 (2015).

  23. 23.

    Snell-Rood, E. C. An overview of the evolutionary causes and consequences of behavioural plasticity. Anim. Behav. 85, 1004–1011 (2013).

  24. 24.

    Hirschhorn, J. N. & Daly, M. J. Genome-wide association studies for common diseases and complex traits. Nat. Rev. Genet. 6, 95–108 (2005).

  25. 25.

    Slate, J. From beavis to beak color: a simulation study to examine how much QTL mapping can reveal about the genetic architecture of quantitative traits. Evolution 67, 1251–1262 (2013).

  26. 26.

    Shaw, K. L. & Lesnick, S. C. Genomic linkage of male song and female acoustic preference QTL underlying a rapid species radiation. Proc. Natl Acad. Sci. USA 106, 9737–9742 (2009).

  27. 27.

    Lynch, M. & Walsh, B. Genetics and Analysis of Quantitative Traits (Sinauer Associates, Sunderland, 1998).

  28. 28.

    Küpper, C. et al. A supergene determines highly divergent male reproductive morphs in the ruff. Nat. Genet. 48, 79–83 (2016).

  29. 29.

    Bendesky, A. et al. The genetic basis of parental care evolution in monogamous mice. Nature 544, 434–439 (2017).

  30. 30.

    Berens, A. J., Hunt, J. H. & Toth, A. L. Comparative transcriptomics of convergent evolution: different genes but conserved pathways underlie caste phenotypes across lineages of eusocial insects. Mol. Biol. Evol. 32, 690–703 (2015).

  31. 31.

    Anholt, R. R. H. et al. The genetic architecture of odor-guided behavior in Drosophila: epistasis and the transcriptome. Nat. Genet. 35, 180–184 (2003).

  32. 32.

    Bell, A. M. & Robinson, G. E. Behavior and the dynamic genome. Science 332, 1161–1162 (2011).

  33. 33.

    Lawniczak, M. K. & Begun, D. J. A genome-wide analysis of courting and mating responses in Drosophila melanogaster females. Genome 47, 900–910 (2004).

  34. 34.

    Mack, P. D., Kapelnikov, A., Heifetz, Y. & Bender, M. Mating-responsive genes in reproductive tissues of female Drosophila melanogaster. Proc. Natl Acad. Sci. USA 103, 10358–10363 (2006).

  35. 35.

    Carney, G. E. A rapid genome-wide response to Drosophila melanogaster social interactions. BMC Genom. 8, 288 (2007).

  36. 36.

    Cummings, M. E. et al. Sexual and social stimuli elicit rapid and contrasting genomic responses. Proc. R. Soc. B 275, 393–402 (2008).

  37. 37.

    McGraw, L. A., Clark, A. G. & Wolfner, M. F. Post-mating gene expression profiles of female Drosophila melanogaster in response to time and to four male accessory gland proteins. Genetics 179, 1395–1408 (2008).

  38. 38.

    Fraser, B. A., Janowitz, I., Thairu, M., Travis, J. & Hughes, K. A. Phenotypic and genomic plasticity of alternative male reproductive tactics in sailfin mollies. Proc. R. Soc. B 281, 20132310 (2014).

  39. 39.

    Mori, T. et al. Genetic basis of phenotypic plasticity for predator-induced morphological defenses in anuran tadpole, Rana pirica, using cDNA subtraction and microarray analysis. Biochem. Biophys. Res. Commun. 330, 1138–1145 (2005).

  40. 40.

    Sanogo, Y. O., Hankison, S., Band, M., Obregon, A. & Bell, A. M. Brain transcriptomic response of threespine sticklebacks to cues of a predator. Brain Behav. Evol. 77, 270–285 (2011).

  41. 41.

    Becks, L., Ellner, S. P., Jones, L. E. & Hairston, N. G. The functional genomics of an eco-evolutionary feedback loop: linking gene expression, trait evolution, and community dynamics. Ecol. Lett. 15, 492–501 (2012).

  42. 42.

    Lavergne, S. G., McGowan, P. O., Krebs, C. J. & Boonstra, R. Impact of high predation risk on genome-wide hippocampal gene expression in snowshoe hares. Oecologia 176, 613–624 (2014).

  43. 43.

    Alaux, C. et al. Honey bee aggression supports a link between gene regulation and behavioral evolution. Proc. Natl Acad. Sci. USA 106, 15400–15405 (2009).

  44. 44.

    Sanogo, Y. O., Band, M., Blatti, C., Sinha, S. & Bell, A. M. Transcriptional regulation of brain gene expression in response to a territorial intrusion. Proc. R. Soc. B 279, 4929–4938 (2012).

  45. 45.

    Rittschof, C. C. & Robinson, G. E. Manipulation of colony environment modulates honey bee aggression and brain gene expression. Genes Brain Behav. 12, 802–811 (2013).

  46. 46.

    Rittschof, C. C. & Robinson, G. E. in Current Topics in Developmental Biology, Vol. 119 (ed Orgogozo, V.) 157–204 (Academic: Cambridge, 2016).

  47. 47.

    Jandt, J. M., Thomson, J. L., Geffre, A. C. & Toth, A. L. Lab rearing environment perturbs social traits: a case study with Polistes wasps. Behav. Ecol. 26, 1274–1284 (2015).

  48. 48.

    Tylee, D. S., Kawaguchi, D. M. & Glatt, S. J. On the outside, looking in: a review and evaluation of the comparability of blood and brain ‘-omes’. Am. J. Med. Genet. B 162, 595–603 (2013).

  49. 49.

    Nikolova, Y. S. & Hariri, A. R. Can we observe epigenetic effects on human brain function? Trends Cogn. Sci. 19, 366–373 (2015).

  50. 50.

    Hannon, E., Lunnon, K., Schalkwyk, L. & Mill, J. Interindividual methylomic variation across blood, cortex, and cerebellum: implications for epigenetic studies of neurological and neuropsychiatric phenotypes. Epigenetics 10, 1024–1032 (2015).

  51. 51.

    Derks, M. F. L. et al. Gene and transposable element methylation in great tit (Parus major) brain and blood. BMC Genom. 17, 332 (2016).

  52. 52.

    Cullinan, W. E., Herman, J. P., Battaglia, D. F., Akil, H. & Watson, S. J. Pattern and time course of immediate early gene expression in rat brain following acute stress. Neuroscience 64, 477–505 (1995).

  53. 53.

    Aubin-Horth, N. & Renn, S. C. P. Genomic reaction norms: using integrative biology to understand molecular mechanisms of phenotypic plasticity. Mol. Ecol. 18, 3763–3780 (2009).

  54. 54.

    Bukhari, S. A. et al. Temporal dynamics of neurogenomic plasticity in response to social interactions in male threespined sticklebacks. PLoS Genet. 13, e1006840 (2017).

  55. 55.

    Bell, A. M., Bukhari, S. A. & Sanogo, Y. O. Natural variation in brain gene expression profiles of aggressive and nonaggressive individual sticklebacks. Behaviour 153, 1723–1743 (2016).

  56. 56.

    Trucchi, E. et al. BsRADseq: screening DNA methylation in natural populations of non-model species. Mol. Ecol. 25, 1697–1713 (2016).

  57. 57.

    Glastad, K. M., Gokhale, K., Liebig, J. & Goodisman, M. A. D. The caste- and sex-specific DNA methylome of the termite Zootermopsis nevadensis. Sci. Rep. 6, 37110 (2016).

  58. 58.

    Verhulst, E. C. et al. Evidence from pyrosequencing indicates that natural variation in animal personality is associated with DRD 4 DNA methylation. Mol. Ecol. 8, 1801–1811 (2016).

  59. 59.

    Laine, V. N. et al. Evolutionary signals of selection on cognition from the great tit genome and methylome. Nat. Commun. 7, 10474 (2016).

  60. 60.

    Cronican, A. A. et al. Genome-wide alteration of histone H3K9 acetylation pattern in mouse offspring prenatally exposed to arsenic. PLoS ONE 8, e53478 (2013).

  61. 61.

    Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).

  62. 62.

    Hunter, C. P. Genetics: a touch of elegance with RNAi. Curr. Biol. 9, R440–R442 (1999).

  63. 63.

    Hsu, P. D., Lander, E. S. & Zhang, F. Development and applications of CRISPR-Cas9 for genome engineering. Cell 157, 1262–1278 (2014).

  64. 64.

    Straub, C., Granger, A. J., Saulnier, J. L. & Sabatini, B. L. CRISPR/Cas9-mediated gene knock-down in post-mitotic neurons. PLoS ONE 9, e105584 (2014).

  65. 65.

    Swiech, L. et al. In vivo interrogation of gene function in the mammalian brain using CRISPR-Cas9. Nat. Biotechnol. 33, 102–106 (2015).

  66. 66.

    Peng, R., Lin, G. & Li, J. Potential pitfalls of CRISPR/Cas9-mediated genome editing. FEBS J. 283, 1218–1231 (2016).

  67. 67.

    Chandrasekaran, S. et al. Behavior-specific changes in transcriptional modules lead to distinct and predictable neurogenomic states. Proc. Natl Acad. Sci. USA 108, 18020–18025 (2011).

  68. 68.

    Wang, J. et al. A Y-like social chromosome causes alternative colony organization in fire ants. Nature 493, 664–668 (2013).

  69. 69.

    Reidenbach, K. R. et al. Patterns of genomic differentiation between ecologically differentiated M and S forms of Anopheles gambiae in west and central Africa. Genome Biol. Evol. 4, 1202–1212 (2012).

  70. 70.

    Lawniczak, M. K. N. et al. Widespread divergence between incipient Anopheles gambiae species revealed by whole genome sequences. Science 330, 512–514 (2010).

  71. 71.

    Chalfin, L. et al. Mapping ecologically relevant social behaviours by gene knockout in wild mice. Nat. Commun. 5, 4569 (2014).

  72. 72.

    Jandt, J. M. et al. Behavioural syndromes and social insects: personality at multiple levels. Biol. Rev. 89, 48–67 (2014).

  73. 73.

    Purcell, J., Brelsford, A., Wurm, Y., Perrin, N. & Chapuisat, M. Convergent genetic architecture underlies social organization in ants. Curr. Biol. 24, 2728–2732 (2014).

  74. 74.

    Rausher, M. D. & Delph, L. F. Commentary: when does understanding phenotypic evolution require identification of the underlying genes? Evolution 69, 1655–1664 (2015).

  75. 75.

    Lang, G. I., Murray, A. W. & Botstein, D. The cost of gene expression underlies a fitness trade-off in yeast. Proc. Natl Acad. Sci. USA 106, 5755–5760 (2009).

  76. 76.

    Cash, A. C., Whitfield, C. W., Ismail, N. & Robinson, G. E. Behavior and the limits of genomic plasticity: power and replicability in microarray analysis of honeybee brains. Genes Brain Behav. 4, 267–271 (2005).

  77. 77.

    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).

  78. 78.

    Cardoso, S. D., Teles, M. C. & Oliveira, R. F. Neurogenomic mechanisms of social plasticity. J. Exp. Biol. 218, 140–149 (2015).

  79. 79.

    Réale, D. et al. Personality and the emergence of the pace-of-life syndrome concept at the population level. Phil. Trans. R. Soc. B 365, 4051–4063 (2010).

  80. 80.

    Sanogo, Y. O. & Bell, A. M. Molecular mechanisms and the conflict between courtship and aggression in three-spined sticklebacks. Mol. Ecol. 25, 4368–4376 (2016).

  81. 81.

    Zinzow-Kramer, W. M. et al. Genes located in a chromosomal inversion are correlated with territorial song in white-throated sparrows. Genes Brain Behav. 14, 641–654 (2015).

  82. 82.

    Gibson, G. & Muse, S. V. A Primer of Genome Science. (Sinauer Associates: Sunderland, 2009).

  83. 83.

    Flicek, P. & Birney, E. Sense from sequence reads: methods for alignment and assembly. Nat. Methods 6, S6–S12 (2009).

  84. 84.

    McGary, K. L. et al. Systematic discovery of nonobvious human disease models through orthologous phenotypes. Proc. Natl Acad. Sci. USA 107, 6544–6549 (2010).

  85. 85.

    Ashburner, M. et al. Gene ontology: tool for the unification of biology. Nat. Genet. 25, 25–29 (2000).

  86. 86.

    Baker, E. J., Jay, J. J., Bubier, J. A., Langston, M. A. & Chesler, E. J. GeneWeaver: a web-based system for integrative functional genomics. Nucleic Acids Res. 40, D1067–D1076 (2012).

  87. 87.

    Rittschof, C. C. & Robinson, G. E. Genomics: moving behavioural ecology beyond the phenotypic gambit. Anim. Behav. 92, 263–270 (2014).

  88. 88.

    Biro, P. A. & Stamps, J. A. Do consistent individual differences in metabolic rate promote consistent individual differences in behavior? Trends Ecol. Evol. 25, 653–659 (2010).

  89. 89.

    Biro, P. A. & Stamps, J. A. Are animal personality traits linked to life-history productivity? Trends Ecol. Evol. 23, 361–368 (2008).

  90. 90.

    Sih, A. & Giudice, M. D. Linking behavioural syndromes and cognition: a behavioural ecology perspective. Phil. Trans. R. Soc. B 367, 2762–2772 (2012).

  91. 91.

    Tieleman, B. I., Williams, J. B., Ricklefs, R. E. & Klasing, K. C. Constitutive innate immunity is a component of the pace-of-life syndrome in tropical birds. Proc. R. Soc. B 272, 1715–1720 (2005).

  92. 92.

    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).

  93. 93.

    Goodson, J. L. The vertebrate social behavior network: evolutionary themes and variations. Horm. Behav. 48, 11–22 (2005).

  94. 94.

    Newman, S. W. The medial extended amygdala in male reproductive behavior. A node in the mammalian social behavior network. Ann. NY Acad. Sci. 877, 242–257 (1999).

  95. 95.

    Newman, M. The structure and function of complex networks. SIAM Rev. 45, 167–256 (2003).

  96. 96.

    Newman, M. E. J. & Clauset, A. Structure and inference in annotated networks. Nat. Commun. 7, 11863 (2016).

  97. 97.

    Wong-Riley, M. Changes in the visual system of monocularly sutured or enucleated cats demonstrable with cytochrome oxidase histochemistry. Brain Res. 171, 11–28 (1979).

  98. 98.

    Laiho, J. E. et al. Relative sensitivity of immunohistochemistry, multiple reaction monitoring mass spectrometry, in situ hybridization and PCR to detect Coxsackievirus B1 in A549 cells. J. Clin. Virol. 77, 21–28 (2016).

  99. 99.

    Knight, Z. A. et al. Molecular profiling of activated neurons by phosphorylated ribosome capture. Cell 151, 1126–1137 (2012).

  100. 100.

    Cong, L. et al. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819–823 (2013).

  101. 101.

    Sternberg, S. H., Redding, S., Jinek, M., Greene, E. C. & Doudna, J. A. DNA interrogation by the CRISPR RNA-guided endonuclease Cas9. Nature 507, 62–67 (2014).

  102. 102.

    Shalem, O., Sanjana, N. E. & Zhang, F. High-throughput functional genomics using CRISPR-Cas9. Nat. Rev. Genet. 16, 299–311 (2015).

  103. 103.

    Wright, A. V., Nuñez, J. K. & Doudna, J. A. Biology and applications of CRISPR systems: harnessing nature’s toolbox for genome engineering. Cell 164, 29–44 (2016).

  104. 104.

    Ketting, R. F. The many faces of RNAi. Dev. Cell 20, 148–161 (2011).

  105. 105.

    Qi, L. S. et al. Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell 152, 1173–1183 (2013).

  106. 106.

    Liu, X. S. et al. Editing DNA methylation in the mammalian genome. Cell 167, 233–247.e17 (2009).

  107. 107.

    Katz, P. S. ‘Model organisms’ in the light of evolution. Curr. Biol. 26, R649–R650 (2016).

  108. 108.

    Saltz, J. B. Genetic composition of social groups influences male aggressive behaviour and fitness in natural genotypes of Drosophila melanogaster. Proc. R. Soc. B 280, 20131926 (2013).

  109. 109.

    Egan, R. J. et al. Understanding behavioral and physiological phenotypes of stress and anxiety in zebrafish. Behav. Brain Res. 205, 38–44 (2009).

  110. 110.

    Amdam, G. V. & Page, R. E. Jr The developmental genetics and physiology of honeybee societies. Anim. Behav. 79, 973–980 (2010).

  111. 111.

    Simola, D. F. et al. Epigenetic (re)programming of caste-specific behavior in the ant Camponotus floridanus. Science 351, aac6633 (2016).

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Acknowledgements

The workshop that led to this series of papers was funded by the National Science Foundation (NSF-IOS 1623898; PI: A.M.B.), the NSF Sociogenomics Research Coordination Network and the Carl R. Woese Institute for Genomic Biology at the University of Illinois Urbana Champaign. We wish to thank other workshop participants for their feedback in the development of these ideas and comments on drafts of the manuscript.

Author information

Affiliations

  1. Department of BioSciences, Rice University, Houston, TX, USA

    • Sarah E. Bengston
  2. School of Life Sciences, Arizona State University, Tempe, USA

    • Romain A. Dahan
  3. Department of Molecular, Cellular, and Developmental Biology, and Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA

    • Zoe Donaldson
  4. Department of Integrative Biology, University of Texas Austin, Austin, TX, USA

    • Steven M. Phelps
  5. Department of Animal Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, The Netherlands

    • Kees van Oers
  6. Department of Environmental Science and Policy, University of California Davis, Davis, CA, USA

    • Andrew Sih
  7. Department of Animal Biology, The University of Illinois, Urbana-Champaign, Urbana, IL, USA

    • Alison M. Bell
  8. Carl R. Woese Institute for Genomic Biology, The University of Illinois, Urbana-Champaign, Urbana, IL, USA

    • Alison M. Bell

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Contributions

S.E.B. contributed to conception of the manuscript, drafted sections of the manuscript, contributed to the conceptualization and generation of figures and tables, edited the manuscript and facilitated the collaboration between authors. R.A.D. drafted sections of the manuscript, contributed to the conceptualization and generation of figures and tables and provided feedback. Z.D. contributed to conception of the manuscript, drafted sections of the manuscript and provided feedback. S.M.P. contributed to conception of the manuscript, drafted sections of the manuscript and provided feedback. K.v.O. contributed to conception of the manuscript and provided feedback. A.S. contributed to conception of the manuscript and provided feedback. A.M.B. contributed to the conception of the manuscript, drafted sections of the manuscript, provided feedback and edited the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Sarah E. Bengston.