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Behavioral idiosyncrasy reveals genetic control of phenotypic variability
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Abstract
Significance: If we could rear genetically identical individuals from a variety of genetic backgrounds and rear them in the same environment, how much phenotypic variation between individuals of the same genotype would we see? Would different genetic backgrounds differ in their degree of variability? What would account for these differences? We used Drosophila inbred lines to address these questions focusing on variability in locomotor handedness. We show that different genotypes vary dramatically in their propensity for variability, that phenotypic variability itself, as a trait, can be heritable, and that loci affecting variability can be mapped. The genetic control of variability has received little attention in quantitative genetics despite the important role variability plays in explaining phenotypic variation between individuals.
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“Our results also provide insight into mechanisms underlying individual differences in navigation behavior53,54.”
From Multimodal cue integration and learning in a neural representation of head direction (2025) · cites this paper as [53]
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“The nature of the forces influencing the evolution of alleles that affect variability has, more generally, been the focus of a rich theoretical literature explaining this phenomenon from a game theory perspective (36) or in terms of bet-hedging (37).”
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“Discussion In this study, we used a simple behavioral trait to show that individual genotypes vary considerably in their degree of intragenotypic variability (7, 15) and found that this variation is heritable.”
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“The nature of the forces influencing the evolution of alleles that affect variability has, more generally, been the focus of a rich theoretical literature explaining this phenomenon from a game theory perspective (36) or in terms of bet-hedging (37).”
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“Most recently, with the advent of genome-wide association studies, several groups (3, 4, 12, 13) have mapped quantitative trait loci affecting variance (vQTLs) by comparing phenotypic variances among individuals that share alleles.”
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“Going forward, our model may be able to provide a quantitative framework for understanding variability in individual differences in navigation, such as locomotor handedness (Ayroles et al., 2015; Buchanan et al., 2015).”
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BackgroundMethodInfluentialSelf-citationComplex dynamics and the development of behavioural individuality
Fisher, D. N., Brachmann, M., & Burant, J. (2018) · doi:10.1016/j.anbehav.2018.02.015 · Cited by 20
“Groothuis and Trillmich (2011) point out both how similar genetic information can lead to different behaviours (e.g., Ayroles et al., 2015), while different genes can produce the same behaviours through canalisation (Siegal & Bergman, 2002).”
BackgroundThalamic Regulation of a Visual Critical Period and Motor Behavior
Hageter, J., Starkey, J., & Horstick, E. J. (2022) · Cell Reports · doi:10.1016/j.celrep.2023.112287 · Cited by 26
“96,97 Alternatively, in our CP assay, the “occluded” eye likely receives some visual input.”
BackgroundHussain, W., Campbell, M. T., Jarquín, D., Walia, H., & Morota, G. (2020) · The Plant Genome · doi:10.1002/tpg2.20011 · Cited by 23
“…associated with diverse phenotypes, including the tendency to left-right turning and bristles (Mackay and Lyman, 2005) and locomotor handedness (Ayroles et al., 2015) in Drosophila; coat color (Nachman et al., 2003), circadian activity, and exploratory behavior (Corty et al., 2018) in mice;…”
BackgroundNegron, Y. L. S., Hansen, N. F., & Harbison, S. T. (2018) · G3 Genes Genomes Genetics · doi:10.1534/g3.118.200503 · Cited by 19
Collective Behavior: Social Digging in Drosophila Larvae.
Louis, M., & de Polavieja, G. D. (2017) · Current Biology · doi:10.1016/j.cub.2017.08.023 · Cited by 19
“Adult flies have different ‘personalities’ [17] and the same level of idiosyncrasy is expected for larvae.”
BackgroundNeuromodulation and Individuality
Maloney, R. T. (2021) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2021.777873 · Cited by 26
Genotype Influences Day-to-Day Variability in Sleep in Drosophila melanogaster
Wu, K. J., Kumar, S., Negron, Y. L. S., & Harbison, S. T. (2018) · Sleep · doi:10.1093/sleep/zsx205 · Cited by 16
Wei, W., Bowes, J., Plant, D., Viatte, S., Yarwood, A., Massey, J., Worthington, J., & Eyre, S. (2016) · Scientific Reports · doi:10.1038/srep25014 · Cited by 17
Cleal, M., Fontana, B. D., Hillman, C., & Parker, M. O. (2023) · Behavioural Processes · doi:10.1016/j.beproc.2023.104943 · Cited by 15
Krams, I. A., Krama, T., Krams, R., Trakimas, G., Popovs, S., Jõers, P., Munkevics, M., Elferts, D., Rantala, M. J., Makņa, J., et al. (2021) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2021.659331 · Cited by 24
“A genetic basis for variability has been found in several other Drosophila behaviors including locomotor bias (Ayroles et al., 2015) and odor preference (Honegger et al.”
BackgroundQTL Mapping on a Background of Variance Heterogeneity
Corty, R. W., & Valdar, W. S. J. (2018) · G3 Genes Genomes Genetics · doi:10.1534/g3.118.200790 · Cited by 13
The study of animal behaviour as a physical science
Brown, A. E. X., & de Bivort, B. (2017) · bioRxiv · doi:10.1101/220855 · Cited by 15
“As an example, tracking the centroids of many flies in parallel exploring simple arenas has permitted the measurement of individual behaviour from tens of thousands of individuals across hours and days 36,37 .”
A neurodevelopmental origin of behavioral individuality
Linneweber, G., Andriatsilavo, M., Dutta, S., Hellbruegge, L., Liu, G., Ejsmont, R., Fenk, L., Straw, A., Wernet, M. F., Hiesinger, P., et al. (2019) · bioRxiv · doi:10.1101/540880 · Cited by 14
Cross-species Analyses of Intra-species Behavioral Differences in Mammals and Fish
Demin, K. A., Lakstygal, A. M., Volgin, A. D., de Abreu, M. S., Genário, R., Alpyshov, E. T., Serikuly, N., Wang, D., Wang, J., Yan, D., et al. (2020) · Neuroscience · doi:10.1016/j.neuroscience.2019.12.035 · Cited by 17
“4 Common in various species, individual behavioral differences [39-44] are often affected by age, sex, size, social status and learned adaptive strategies [19, 45, 46].”
BackgroundCorty, R. W., Kumar, V., Tarantino, L. M., Takahashi, J. S., & Valdar, W. S. J. (2018) · G3 Genes Genomes Genetics · doi:10.1534/g3.118.200194 · Cited by 11
The Novel Concept of "Behavioural Instability" and Its Potential Applications
Pertoldi, C., Bahrndorff, S., Novicic, Z. K., & Rohde, P. D. (2016) · Symmetry · doi:10.3390/sym8110135 · Cited by 13
“Similarly, several genome-wide association studies (GWAS) studies are trying to associate genetic variation with variation in behavioral traits [35].”
BackgroundRohde, P. D., Madsen, L. S., Arvidson, S. M. N., Loeschcke, V., Demontis, D., & Kristensen, T. N. (2016) · Fly · doi:10.1080/19336934.2016.1158365 · Cited by 16
“, intragenotypic, such variation does exist.(17,18) The Y-maze assay”
BackgroundMultimodal cue integration and learning in a neural representation of head direction
Basnak, M. A., Kutschireiter, A., Okubo, T. S., Chen, A., Gorelik, P., Drugowitsch, J., & Wilson, R. I. (2025) · Nature Neuroscience · doi:10.1038/s41593-024-01823-z · Cited by 13
Variation and Variability in Drosophila Grooming Behavior
Mueller, J. M., Zhang, N., Carlson, J., & Simpson, J. (2020) · bioRxiv · doi:10.1101/2020.08.15.252627 · Cited by 12
Genetic variants and underlying mechanisms influencing variance heterogeneity in maize.
Li, H., Wang, M., Li, W.-J., He, L., Zhou, Y., Zhu, J.-T., Che, R., Warburton, M., Yang, X.-H., & Yan, J.-B. (2020) · The Plant Journal · doi:10.1111/tpj.14786 · Cited by 12
“The last two could contribute to genetic variance heterogeneity as described in previous literatures (Shen et al., 2012, Ayroles et al., 2015, Ek et al., 2018).”
BackgroundanTraX: high throughput video tracking of color-tagged insects
Gal, A., Saragosti, J., & Kronauer, D. (2020) · bioRxiv · doi:10.1101/2020.04.29.068478 · Cited by 12
“Such experiments are of increasing interest, as the study of behavior in classical model systems like Drosophila fruit flies is shifting toward understanding more complex behavioral phenomena such as social interactions, individuality and interspecies interactions [12,42–46].”
Backgroundvqtl: An R Package for Mean-Variance QTL Mapping
Corty, R., & Valdar, W. (2017) · G3: Genes, Genomes, Genetics · doi:10.1101/149377 · Cited by 12
“Nonetheless, although detection of vQTL has started to enter the main-stream of genetic analysis (Yang et al. 2012; Hulse and Cai 2013; Ayroles et al. 2015; Forsberg et al. 2015; Wei et al. 2016; Wang and Payseur 2017; Wei et al. 2017), statistical tools for this purpose remain heterogeneous.”
BackgroundShedding Light on Inter-Individual Variability of Olfactory Circuits in Drosophila
Rihani, K., & Sachse, S. (2022) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2022.835680 · Cited by 16
“, 2020), while the degree of variability in locomotor handedness is itself genetically determined and thus heritable (Ayroles et al., 2015; Buchanan et al., 2015).”
BackgroundWild flies hedge their thermal preference bets in response to seasonal fluctuations
Akhund-Zade, J., Yoon, D., Bangerter, A., Polizos, N. T., Campbell, M., Soloshenko, A., Zhang, T., Wice, E., Albright, A., Narayanan, A. K., et al. (2020) · bioRxiv · doi:10.1101/2020.09.16.300731 · Cited by 10
Self-citationAnimal Behavior: A Neural Basis of Individuality.
Takagi, S., & Benton, R. (2020) · Current Biology · doi:10.1016/j.cub.2020.04.052 · Cited by 10
Genetics of Genome-Wide Recombination Rate Evolution in Mice from an Isolated Island
Wang, R. J., & Payseur, B. A. (2017) · Genetics · doi:10.1534/genetics.117.202382 · Cited by 11
Genetic architecture of natural variation of cardiac performance from flies to humans
Saha, S., Spinelli, L., Castro-Mondragon, J., Kervadec, A., Lynott, M., Kremmer, L., Röder, L., Krifa, S., Torres, M., Brun, C., et al. (2021) · bioRxiv · doi:10.1101/2021.06.08.447524 · Cited by 9
Petrazzini, M. E. M., Pecunioso, A., Dadda, M., & Agrillo, C. (2020) · Symmetry · doi:10.3390/sym12081294 · Cited by 9
Zhang, W.-Y., Reeves, G., & Tautz, D. (2019) · Molecular Ecology · doi:10.1111/mec.15341 · Cited by 9
“Given the relatively small number of DGRP lines (n = 198 in our study), false positive or negative discovery associations may exist from our GWA and LD analysis, while still identifying candidate genes for further experimental follow-up (Ayroles et al., 2015; Turner & Miller, 2012).”
BackgroundGenetic control of variability in subcortical and intracranial volumes
Córdova‐Palomera, A., van der Meer, D., Kaufmann, T., Bettella, F., Wang, Y., Alnæs, D., Doan, N. T., Agartz, I., Bertolino, A., Buitelaar, J. K., et al. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-0664-1 · Cited by 17
Kielland, Ø. N., Bech, C., & Einum, S. (2017) · Ecology and Evolution · doi:10.1002/ece3.3556 · Cited by 9
“…our results, multiple studies show heritability in within- genotype phenotypic variation or demonstrate that evolution of DI is indeed plausible (Ayroles et al., 2015; Breno, Bots, & Van Dongen, 2013; Carter & Houle, 2011; Hansen et al., 2006; Leamy, 1997; Pélabon et al., 2010; Polak & Starmer,…”
ResultA Bayesian test to identify variance effectsPreprint
Dumitrascu, B., Darnell, G., Ayroles, J. F., & Engelhardt, B. E. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1512.01616 · Cited by 6
“These studies include diverse quantitative phenotypes, including left-right turning tendency in the fruit fly Drosophila melanogaster [6], coat color in the rock pocket mice Chaetodipus intermedius [8], and thermotolerance [9] and flowering time [10] in the plant Arabidopsis thaliana.”
BackgroundMethodSelf-citationA predisposed motor bias shapes individuality in vocal learning
Toji, N., Sawai, A., Wang, H., Ji, Y., Sugioka, R., Go, Y., & Wada, K. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2308837121 · Cited by 7
A reductionist paradigm for high-throughput behavioural fingerprinting in Drosophila melanogaster
Jones, H., Willis, J. A., Firth, L. C., Giachello, C. N., & Gilestro, G. F. (2023) · eLife · doi:10.7554/elife.86695 · Cited by 8
“…in part compatible with high-throughput approaches ( Wiltschko et al., 2020 ), especially when employed on small invertebrate animal models ( McDermott-Rouse et al., 2021 ; Ayroles et al., 2015 ; Branson et al., 2009 ; Kabra et al., 2013 ) or when aided by robotic handling ( Alisch et al., 2018 ).”
Background
Metadata
- Authors
- Ayroles, J. F., Buchanan, S. M., O’Leary, C., Skutt-Kakaria, K., Grenier, J. K., Clark, A. G., Hartl, D. L., & de Bivort, B. L.
- Affiliations
- Harvard University (US)
- Cornell University (US)
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2015-05-07
- Volume
- 112
- Issue
- 21
- Pages
- 6706-6711
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4450409
- OpenAlex
- W2112316313
- Cited by
- 218
- References
- 54
- Citations by year
- 2026: 22 · 2025: 22 · 2024: 20 · 2023: 20 · 2022: 18 · 2021: 20 · 2020: 22 · 2019: 13 · 2018: 24 · 2017: 15 · 2016: 14 · 2015: 8
- FWCI
- 9.49
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University) (cc-by)
- Funders
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (AI064950)
- Society of Fellows, Harvard University (N/A)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurobiology and Insect Physiology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Hemispheric Asymmetry in Neuroscience
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- phenotypic variability, central complex, brain gene expression, genotype-phenotype correlation, alternative alleles
- MeSH terms
- Animals, Behavior, Animal, Brain, Drosophila melanogaster, Female, Inbreeding, Locomotion, Male, Phenotype, Receptors, Cell Surface, Genetic Variation, Genes, Insect, Drosophila Proteins, Animals, Genetically Modified, RNA Interference, Quantitative Trait Loci, Genome-Wide Association Study, Gene Knockdown Techniques
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