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Morphogenetic Consequences of Short-Term Thermal Stress in Short and Long Life House Fly Lines (Musca Domestica L.): Geometric Wing Morphometrics

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Abstract

The morphogenetic consequences of exposure to short-term heat stress (STHS) in two housefly strains mass-selected for lifespan were studied based on the assessment of adult wing variability by geometric morphometrics. Significant differences in the size and shape of the wing between the control and impact groups of different genders in the strains were revealed. Shg (short lived) and Lg (long-lived). The STHS effect manifested in an increase in the size of the wing and a directed change in its shape. The between-group hierarchy of gender and stress-induced differences is expressed in the same way in both strains of flies. The range of linear differences is significantly higher than the gender differences, which, in turn, are higher than the level of stress-induced ones. Instability of imago wing development (Vm) in Shg was significantly higher than the Lg strains, and higher in all groups of females, but in most cases significantly lower in impact groups (taking into account the increase in size, the latter may be associated with the effect of hormesis). It is hypothesized that the directed morphogenetic effects of STHS are based on latent species modifications, the appearance of which in the phenotype is due to stress-induced epigenetic genome rearrangements that cause similar morphological changes in the wing in groups of adult males and females of both strains. The phenotypic plasticity of strains during selection for different lifespans and the changes induced by STHS directly indicate the reality of stress-induced rapid morphogenetic rearrangements under a sharp change in environmental conditions.

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REFERENCES

  1. Zherikhin, V.V., Izbrannye trudy po paleoekologii i filotsenogenetike (Selected Issues on Paleoecology and Phylocoenogenetics), Moscow: KMK, 2003.

  2. Ceballos, G., Ehrlich, P.R., Barnosky, A.D., et al., Accelerated modern human-induced species losses: Entering the sixth mass extinction, Sci. Adv., 2015, vol. 1, no. 5, p. e1400253. https://doi.org/10.1126/sciadv.1400253

    Article  PubMed  PubMed Central  Google Scholar 

  3. Parmesan, C., Ecological and evolutionary responses to recent climate change, Annu. Rev. Ecol., Evol., Syst., 2006, vol. 37, pp. 637–669.

    Article  Google Scholar 

  4. Steffen, W., Grinevald, J., Crutzen, pp., and McNeil, J., The Anthropocene: Conceptual and historical perspectives, Philos. Trans. R. Soc., A, 2011, vol. 369, pp. 842–867.

  5. Alberti, M., Eco-evolutionary dynamics in an urbanizing planet, Trends Ecol. Evol., 2015, vol. 30, no. 2, pp. 114–126.

    Article  PubMed  Google Scholar 

  6. McGill, B.J., Enquist, B.J., Weiher, E., and Westoby, M., Rebuilding community ecology from functional traits, Trends Ecol. Evol., 2006. vol. 21, no. 4. pp. 178–185.

    Article  PubMed  Google Scholar 

  7. Violle, C., Enquist, B.J., McGill, B.J., et al., The return of the variance: Intraspecific variability in community ecology, Trends Ecol. Evol., 2012, vol. 27, no. 4, pp. 244–252.

    Article  PubMed  Google Scholar 

  8. Mouillot, D., Graham, N.A.J., Villéger, S., et al., A functional approach reveals community responses to disturbance, Trends Ecol. Evol., 2013, vol. 28, no. 3, pp. 167–177.

    Article  PubMed  Google Scholar 

  9. Fontaneto, D., Panisi, M., Mandrioli, M., et al., Estimating the magnitude of morphoscapes: How to measure the morphological component of biodiversity in relation to habitats using geometric morphometrics, Sci. Nat., 2017, vol. 104, p. 55. https://doi.org/10.1007/s00114-017-1475-3

    Article  CAS  Google Scholar 

  10. Blonder, B., Hypervolume concepts in niche- and trait-based ecology, Ecography, 2018, vol. 41, pp. 1441–1455.

    Article  Google Scholar 

  11. Vasil'ev, A.G., Kontseptsiya morfonishi i evolyutsionnaya ekologiya (The Concept of Morphoniche and Evolutionary Ecology), Moscow: KMK, 2021.

  12. West-Eberhard, M.J., Developmental Plasticity and Evolution, Oxford: Oxford Univ. Press, 2003.

    Book  Google Scholar 

  13. Bonduriansky, R., Rethinking heredity, again, Trends Ecol. Evol., 2012, vol. 27, no. 6, pp. 330–336.

    Article  CAS  PubMed  Google Scholar 

  14. Duncan, E.J., Gluckman, P.D., and Dearden, P.K., Epigenetics, plasticity and evolution: How do we link epigenetic change to phenotype?, J. Exp. Zool., Part B, 2014, vol. 322, pp. 208–220.

    CAS  Google Scholar 

  15. Donelan, S.C., Hellmann, J.K., Bell, A.M., et al., Transgenerational plasticity in human-altered environments, Trends Ecol. Evol., 2020, vol. 35, no. 2, pp. 115–124.

    Article  PubMed  Google Scholar 

  16. Herman, J. and Sultan, S., Adaptive transgenerational plasticity in plants: Case studies, mechanisms, and implications for natural populations, Front. Plant Sci., 2011, vol. 2, p. 102.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Bell, A.M. and Hellmann, J.K., An integrative framework for understanding the mechanisms and multigenerational consequences of transgenerational plasticity, Annu. Rev. Ecol., Evol., Syst., 2019, vol. 50, pp. 97–118. https://doi.org/10.1146/annurev-ecolsys-110218-024-613

    Article  PubMed  Google Scholar 

  18. Jablonka, E. and Raz, G., Transgenerational epigenetic inheritance: prevalence, mechanisms, and implications for the study of heredity and evolution, Q. Rev. Biol., 2009, vol. 84, pp. 131–176.

    Article  PubMed  Google Scholar 

  19. Becker, C. and Weigel, D., Epigenetic variation: Origin and transgenerational inheritance, Curr. Opin. Plant. Biol., 2012, vol. 15, pp. 562–567.

    Article  CAS  PubMed  Google Scholar 

  20. Bošković, A. and Rando, O.J., Transgenerational epigenetic inheritance, Annu. Rev. Genet., 2018, vol. 52, pp. 21–41.

    Article  PubMed  Google Scholar 

  21. Rohlf, F.J. and Slice, D., Extensions of the Procrustes method for the optimal superimposition of landmarks, Syst. Biol., 1990, vol. 39, no. 1, pp. 40–59.

    Google Scholar 

  22. Zelditch, M.L., Swiderski, D.L., Sheets, H.D., and Fink, W.L., Geometric Morphometrics for Biologists: A Primer, New York: Elsevier, 2004.

    Google Scholar 

  23. Klingenberg, C.P. MorphoJ: An integrated software package for geometric morphometrics, Mol. Ecol. Resour., 2011, vol. 11, pp. 353–357.

    Article  PubMed  Google Scholar 

  24. Zelditch, M.L., Wood, A.R., Bonett, R.M., and Swiderski, D.L., Modularity of the rodent mandible: Integrating bones, muscles, and teeth, Evol. Dev., 2008, vol. 10, pp. 756–768.

    Article  PubMed  Google Scholar 

  25. Sheets, H.D. and Zelditch, M.L., Studying ontogenetic trajectories using resampling methods and landmark data, Hystrix, 2013, vol. 24, no. 1, pp. 67–73.

    Google Scholar 

  26. Vasil’eva, L.A., Yunakovich, N., Ratner, V.A., and Zabanov, S.A., Analysis of changes in MGE localization of Drosophila after selection and temperature treatment using Southern blot-hydridization, Genetika, 1995, vol. 31, no. 3, pp. 333–341.

    PubMed  Google Scholar 

  27. Vasil’eva, L.A., Antonenko, O.V., and Zakharov, I.K., Role of transposable elements in the Drosophila melanogaster genome, Vavilovskii Zh. Genet. Sel., 2011, vol. 15, no. 2, pp. 225–260.

    Google Scholar 

  28. Zabanov, S.A., Vasil’eva, L.A., and Ratner, V.A., Multiple induction of MGE B104 transpositions by severe heat shock in Drosophila, Genetika, 1994, vol. 30, no. 2, pp. 218–224.

    CAS  PubMed  Google Scholar 

  29. Zabanov, S.A., Vasil’eva, L.A., and Ratner, V.A., Induction of MGE Dm412 transitions by γ-irradiation in a Drosophila melanogaster isogenic line, Russ. J. Genet., 1995, vol. 31, no. 6, pp. 683–687.

    CAS  Google Scholar 

  30. Biemont, C. and Terzian, C., MDG-1 mobile element polymorphism in selected Drosophila melanogaster population, Genetica, 1988, vol. 76, no. 1, pp. 7–14.

    Article  CAS  PubMed  Google Scholar 

  31. Biemont, C. and Vieira, C., What transposable elements tell us about genome organization and evolution: The case of Drosophila, Cytogenet. Genome Res., 2005, vol. 110, no. 1, pp. 25–34.

    Article  CAS  PubMed  Google Scholar 

  32. Vasil’eva, L.A., The effect of isogenization on the phenotypic manifestation of quantitative traits in Drosophila melanogaster, Russ. J. Genet., 2004, vol. 40, pp. 859–862.

    Article  Google Scholar 

  33. Feder, M.E. and Hofmann, G.E., Heat-shock proteins, molecular chaperones, and the stress response: Evolutionary and ecological physiology, Annu. Rev. Physiol., 1999, vol. 61, pp. 243–282.

    Article  CAS  PubMed  Google Scholar 

  34. Åkerfelt, M., Morimoto, R.I., and Sistonen, L., Heat-shock factors: Integrators of cell stress, development and lifespan, Nat. Rev. Mol. Cell Biol., 2010, vol. 11, pp. 545–555.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Barua, D. and Heckathorn, S.A., Acclimation of the temperature set-points of the heat-shock response, J. Therm. Biol., 2004, vol. 29, pp. 185–193.

    Article  Google Scholar 

  36. Machado, H.E., Bergland, A.O., O’Brien, K.R., et al., Comparative population genomics of latitudinal variation in Drosophila simulans and Drosophila melanogaster, Mol. Ecol., 2016, vol. 25, no. 3, pp. 723–740.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Stratman, R. and Markow, T.A., Resistance to thermal stress in desert Drosophila, Funct. Ecol., 1998, vol. 12, no. 6, pp. 965–970. https://doi.org/10.1007/s00114-017-1475-3

    Article  CAS  Google Scholar 

  38. Bogaerts-Márquez, M., Guirao-Rico, S., Gautier, M., and González, J., Temperature, rainfall and wind variables underlie environmental adaptation in natural populations of Drosophila melanogaster, Mol. Ecol., 2021, vol. 30, no. 4, pp. 938–954.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Debat, V., Bégin, M., Legout, H., and David, J.R., Allometric and nonallometric components of Drosophila wing shape respond differently to developmental temperature, Evolution, 2003, vol. 57, no. 12, pp. 2773–2784.

    PubMed  Google Scholar 

  40. Debat, V., Debelle, A., and Dworkin, I., Plasticity, canalization, and developmental stability of the Drosophila wing: Joint effects of mutations and developmental temperature, Evolution, 2009, vol. 63, no. 11, pp. 2864–2876.

    Article  PubMed  Google Scholar 

  41. Bryant, E.H., Morphometric adaptation of the housefly Musca domestica (L.) in the United States, Evolution, 1977, vol. 31, pp. 580–596.

    Article  PubMed  Google Scholar 

  42. Bryant, E.H. and Turner, C.R., Comparative morphometric adaptation of the housefly and face fly in United States, Evolution, 1978, vol. 32, pp. 759–770.

    Article  PubMed  Google Scholar 

  43. Asiri, B.M.K., The influence of environmental factors on biological parameters of Musca domestica (Diptera: Muscidae), Int. J. Chin. Med., 2017, vol. 1, no. 3, pp. 81–87.

    Google Scholar 

  44. Akhmetkireeva, T.T., Ben’kovskaya, G.V., and Vasil’ev, A.G., Variability in size and shape of wings in longevity-selected strains of house fly (Musca domestica L.): Geometric morphometrics, Ekol. Genet., 2018, vol. 16, no. 1, pp. 35–44.

    Article  Google Scholar 

  45. Ben’kovskaya, G.V., Opportunities and limitations of changes in lifespan in laboratory experiment, Adv. Gerontol., 2011, vol. 1, pp. 255–259.

    Article  Google Scholar 

  46. Ben'kovskaya, G.V. and Mustafina, R.Sh., Effect of light regime on biochemical parameters of development of stress-reactions of Musca domestica L. Lines with different lifespan, J. Evol. Biochem. Physiol., 2012, vol. 48, pp. 493–499.

    Article  CAS  Google Scholar 

  47. Akhmetkireeva, T.T., Ben’kovskaya, G.V., Kitaev, K.A., and Dolmatova, I.Yu., The housefly as an object of ecological genetics: The structure of the laboratory population and resistance to stress, Vestn. Bashk. Gos. Agrar. Univ., 2014, no. 3, pp. 34–37.

  48. Akhmetkireeva, T.T. and Kitaev, K.A., The effect of short-term heat stress on the indices of variability in laboratory lines of the housefly, Materialy Vserossiiskoi konferentsii molodykh uchenykh, posvyashch. 115-letiyu N.V. Timofeeva-Resovskogo “Ekologiya. Genetika. Evolyutsiya” (Proc. All-Russ. Conf. Young Scientists, Dedicated to the 115th Anniversary of N.V. Timofeev-Resovsky “Ecology. Genetics. Evolution”), Yekaterinburg: Goshchitskii, 2015, pp. 4–7.

  49. Rohlf, F.J., TpsDig2, digitize landmarks and outlines, version 2.30. Department of Ecology and Evolution, State University of New York at Stony Brook, 2017.

  50. Rohlf, F.J., TpsUtil, file utility program, version 1.74. Department of Ecology and Evolution, State University of New York at Stony Brook, 2017.

  51. Davis, J.S., Statistical Data Analysis in Geology, London: Wiley, 2002.

  52. STATISTICA. StatSoft, version 10, 2011.

  53. Lovich, J.E. and Gibbons, J.W., A review of techniques for quantifying sexual size dimorphism, Growth, Dev. Aging, 1992, vol. 56, pp. 269–281.

    CAS  PubMed  Google Scholar 

  54. Barber, C.B., Dobkin, D.P., and Huhdanpaa, H.T., The Quickhull algorithm for convex hulls, ACM Trans. Math. Software, 1996, vol. 22, no. 4, pp. 469–483.

    Article  Google Scholar 

  55. Cornwell, W.K., Schwilk, D.W., and Ackerly, D.A., A trait-based test for habitat filtering: Convex hull volume, Ecology, 2006, vol. 87, pp. 1465–1471.

    Article  PubMed  Google Scholar 

  56. Blonder, B., Hypervolume. R package version 1.0.1.2019. https://cran.r-project.org/package=hypervolume.

  57. Efron, B. and Tibshirani, R., Bootstrap methods for standard errors. Confidence intervals and other measures of statistical accuracy, Stat. Sci., 1986, vol. 1, pp. 54–77.

    Google Scholar 

  58. Hammer, Ø., Harper, D.A.T., and Ryan, P.D., PAST: Paleontological statistics software package for education and data analysis, Palaeontol. Electron., 2001, vol. 4, p. 4.

    Google Scholar 

  59. Cohen, J., A power primer, Psychol. Bull., 1992, vol. 112, no. 1, pp. 155–159. https://doi.org/10.1037/0033-2909.112.1.155

    Article  CAS  PubMed  Google Scholar 

  60. Damuth, J. D., Jablonski, D., Harris, R.M., et al., Taxon-free characterization of animal communities, in Terrestrial Ecosystems Through Time: Evolutionary Paleoecology of Terrestrial Plants and Animals, Beherensmeyer, A.K., Damuth, J.D., and DiMichele, W.A., Eds., Chicago: Univ. Chicago, 1992, pp. 183–203.

    Google Scholar 

  61. Kim, J.O. and Mueller, C.W., Factor Analysis: Statistical Methods and Practical Issues, London: Sage, 1978.

  62. Kendall, M. and Stuart, A., The Advanced Theory of Statistics, London: Griffin, 1961.

  63. Ayrinhac, A., Debat, V., Gibert, P., et al., Cold adaptation in geographical populations of Drosophila melanogaster: Phenotypic plasticity is more important than genetic variability, Funct. Ecol., 2004, vol. 18, pp. 700–706.

    Article  Google Scholar 

  64. Berry, R. and López-Martínez, G., A dose of experimental hormesis: When mild stress protects and improves animal performance, Rev. Comp. Biochem. Physiol., 2020, vol. 242, p. 110658. https://doi.org/10.1016/j.cbpa.2020.110658

    Article  CAS  Google Scholar 

  65. Rix, R.R. and Cutler, G.C., Review of molecular and biochemical responses during stress induced stimulation and hormesis in insects, Sci. Total Environ., 2022, vol. 827, p. 154085. https://doi.org/10.1016/j.scitotenv.2022.154085

    Article  CAS  PubMed  Google Scholar 

  66. Coulson, S.J. and Bale, J.S., Characterisation and limitations of the rapid cold-hardening response in the housefly Musca domestica (Diptera: Muscidae), J. Insect Physiol., 1990, vol. 36, no. 3, pp. 207–211.

    Article  Google Scholar 

  67. Hercus, M.J., Loeschcke, V., and Rattan, S.I.S., Lifespan extension of Drosophila melanogaster through hormesis by repeated mild heat stress, Biogerontology, 2003, vol. 4, pp. 149–156.

    Article  CAS  PubMed  Google Scholar 

  68. Sørensen, J.G., Kristensen, T.N., Kristensen, K.V., and Loeschcke, V., Sex specific effects of heat induced hormesis in Hsf-deficient Drosophila melanogaster, Exp. Gerontol., 2007, vol. 42. pp. 1123–1129.

    Article  PubMed  Google Scholar 

  69. Le Bourg, E., A mild heat stress increases resistance to heat of dFOXO Drosophila melanogaster mutants but less in wild-type flies, Biogerontology, 2021, vol. 22, pp. 237–251.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Nikonorov, Yu.M. and Ben’kovskaya, G.V., The mechanisms of lifespan polymorphism maintenance in the house fly laboratory strain, Adv. Gerontol., 2013, vol. 4, pp. 163–168.

    Article  Google Scholar 

  71. Machado, H.E., Bergland, A.O., Taylor, R., et al., Broad geographic sampling reveals the shared basis and environmental correlates of seasonal adaptation in Drosophila, eLife, 2021, vol. 10, p. e67577. https://doi.org/10.7554/eLife.67577

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Timofeev-Resovskii, N.V. and Svirezhev, Yu.M., On adaptive polymorphism in populations of Adalia bipunctata, in Problemy kibernetiki (Problems of Cybernetics), Moscow: Nauka, 1966, vol. 16, pp. 137–146.

  73. Shvarts, S.S., Ekologicheskie zakonomernosti evolyutsii (Ecological Patterns of Evolution), Moscow: Nauka, 1980.

  74. Skidmore, P., The biology of the Muscidae of the world, in Series Entomologica, Berlin: Springer, 1985, vol. 29, pp. 1–150.

    Google Scholar 

  75. López-Martínez, G. and Hahn, D.A., Early life hormetic treatments decrease irradiation-induced oxidative damage, increase longevity, and enhance sexual performance during old age in the Caribbean fruit fly, PLoS One, 2014, vol. 9, no. 1, p. e88128. https://doi.org/10.1371/journal.pone.0088128

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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ACKNOWLEDGMENTS

The authors are grateful to Ph.D. K.A. Kitaev for invaluable help in planning and organizing the cycle of experimental work, as well as discussion of the results.

Funding

A comparative study of the between-group variability of the control and short-term heat stressed groups of flies was supported by the Russian Foundation for Basic Research (grant no. 15-04-04801), and the analysis of the levels of within-group disparity and stability of the development of model strains using geometric morphometrics was carried out as part of the state task of the Institute of Plant and Animal Ecology, Ural Branch, Russian Academy of Sciences (project no. 122021000091-2).

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  1. Institute of Plant and Animal Ecology, Ural Branch, Russian Academy of Sciences, 620144, Yekaterinburg, Russia

    A. G. Vasil’ev

  2. Institute of Biochemistry and Genetics, Ufa Federal Research Center, Russian Academy of Sciences, 450054, Ufa, Russia

    G. V. Ben’kovskaya & T. T. Akhmetkireeva

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  1. A. G. Vasil’ev
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Vasil’ev, A.G., Ben’kovskaya, G.V. & Akhmetkireeva, T.T. Morphogenetic Consequences of Short-Term Thermal Stress in Short and Long Life House Fly Lines (Musca Domestica L.): Geometric Wing Morphometrics. Russ J Ecol 54, 366–382 (2023). https://doi.org/10.1134/S1067413623050132

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