Variability in size and shape of wings in longevity-selected strains of house fly (Musca Domestica L.): geometric morphometrics

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Background. The aim of the study is evaluate the long-term morphogenetic consequences of the housefly mass selection by the lifespan of two formed strains with different longevity.

Materials and methods. Two control groups were detached from the strains Sh gen (short-living adults) after 65th and L gen (long-living) after 45th generations of selection for early or late reproduction. Geometric morphometrics of the fly’s wing shape are made from the configurations of 17 homologous Landmarks positioned on the wings images. The direction and magnitude of the interstrain differences were estimated using the canonical analysis of Procrustes coordinates, which characterized the variability of the wing shape. The degree of intra-group morphological disparity from the values of the first two canonical variables was analyzed by the nearest neighbour point pattern analysis.

Results. Significant interstrain and sex differences in the shape and size of the wing were revealed. The size of the wing plate of males and females of the Sh gen strain and the level of intragroup disparity are significantly larger than in the L gen strain. The pattern of intragroup disparity of the wing shape of the Sh gen adults is characterized by a significant effect of ordinates overdispersion.

Conclusion. A hypothesis has been put forward that the revealed morphogenetic rearrangements in individuals of both strain formed on the base of historically existing potent ontogenetic trajectories of species. It is assumed that the basis for morphogenesis rearrangements are the primary epigenetic changes due to the transposition of the mobile elements of the genome.

Tansulpan T. Akhmetkireeva

Institute of Biochemistry and Genetics, Ufa Scientific Center of RAS

Author for correspondence.

Russian Federation, Ufa

Senior Laboratory Assistant, Laboratory of Molecular Genetic of Human

Galina V. Ben'kovskaya

Institute of Biochemistry and Genetics, Ufa Scientific Center of RAS


Russian Federation, Ufa

Dr. Biol. Sci., Leading Researcher, Laboratory of Physiological Genetics

Aleksei G. Vasil'ev

Institute of Plant and Animal Ecology UB RAS


Russian Federation, Yekaterinburg

Dr. Biol. Sci., Prof., Chief of Lab, Laboratory of Evolution Ecology

  1. Brakefield PM. Evo-devo and constraints on selection. TRENDS in Ecology and Evolution. 2006;21(7):362-8. doi: 10.1016/j.tree.2006.05.001.
  2. Jablonka E, Raz G. Transgenerational epigenetic inheritance: prevalence, mechanisms, and implications for the study of heredity and evolution. Qvart Rev Biol. 2009;84:131-176. doi: 10.1086/598822.
  3. Bonduriansky R, Crean AJ, Day T. The implications of nongenetic inheritance for evolution in changing environments. Evol Appl. 2012;5:192-201. doi: 10.1111/j.1752-4571.2011.00213.x.
  4. Mazzio EA, Soliman KFA. Basic concepts of epigenetics. Impact of environmental signals on gene expression. Epigenetics. 2012;7(2):119-130. doi: 10.4161/epi.7.2.18764.
  5. Ledón-Rettig CC. Ecological Epigenetics: An Introduction to the symposium. Integrative and Comparative Biology. 2013;53:307-318. doi: 10.1093/icb/ict053.
  6. Duncan EJ, Gluckman P.D, Dearden PK. Epigenetics, plasticity and evolution: How do we link epigenetic change to phenotype? J Exp Zool. Part B. Molecular and Developmental Evolution. 2014;322B;208-220. doi: 10.1002/jez.b.22571.
  7. Benkovskaya G. Opportunities and limitations of changes in lifespan in laboratory experiment. Advan ces in Gerontology. 2011;1(3):255-259. doi: 10.1134/s2079057011030039.
  8. Беньковская Г.В., Никоноров Ю.М. Ассортативность спаривания и поддержание внутрипопуляционного полиморфизма в природных популяциях и лабораторных культурах насекомых // Журнал общей биологии. – 2015. – Т. 76. – № 6. – С. 421–428. [Ben’kovskaya GV Nikonorov YuM. Аssortativnost’ sparivaniya i podderzhanie vnutripopulyatsionnogo polimorfizma v prirodnykh populyatsiyakh i laboratornykh kul’turakh nasekomykh. Zhurnal obshhej biologii. 2015;76(6):421-428. (In Russ.)]
  9. Маркина Т.Ю., Беньковская Г.В. Механизмы поддержания гомеостаза в лабораторных популяциях насекомых // Экология. – 2015. – № 4. – С. 294–299. [Markina TY, Benkovskaya GV. Mechanisms of homeostasis maintenance in laboratory populations of insects. Russian Journal of Ecology. 2015;46(4):365-9. (In Russ).]. doi: 10.1134/s1067413615040128.
  10. Rohlf FJ, Slice D. Extension of the Procrustes method for the optimal superimposition of landmarks. Syst Zoo logy. 1990;39(1):40-59. doi: 10.2307/2992207.
  11. Quenouille M. Approximate tests of correlation in time series. Journal of the Royal Statistical Society B. 1949;11:18-44.
  12. Zelditch ML, Swiderski DL, Sheets HD, et al. Geometric morphometrics for biologists: a primer. Elsevier: Acad. Press; 2004. 443 p.
  13. Klingenberg CP. MorphoJ: an integrated software package for geometric morphometrics. Mol Ecol Resour. 2011; 11:353-357. doi: 10.1111/j.1755-0998.2010.02924.x.
  14. Adams DC, Otárola-Castillo E. Geomorph: an R package for the collection and analysis of geometric morphometric shape data. Methods in Ecology and Evolution. 2013;4:393-399. doi: 10.1111/2041-210x.12035.
  15. Sheets HD, Zelditch ML. Studying ontogenetic trajectories using resampling methods and landmark data. Hystrix. The Italian Journal of Mammalogy. 2013;24(1):67-74.
  16. Васильев А.Г., Большаков В.Н., Васильева И.А., и др. Оценка эффектов неизбирательной элиминации в сообществе грызунов методами геометрической морфометрии // Экология. – 2016. – № 4. – С. 290–299. [Vasil’ev AG, Bol’shakov VN, Vasil’eva IA, et al. Assessment of nonselective elimination effects in rodent communities by methods of geometric morphometrics. Russian Journal of Eco logy [Internet]. 2016 Jul;47(4):383-91. (In Russ).]. doi: 10.1134/s1067413616040159.
  17. Rohlf FJ. TpsUtil, file utility program. version 1.60. Department of Ecology and Evolution, State University of New York at Stony Brook; 2013a (program).
  18. Rohlf FJ. TpsDig2, digitize landmarks and outlines, version 2.17. Department of Ecology and Evolution, State University of New York at Stony Brook; 2013b (program).
  19. Hammer Ø, Harper DAT, Ryan PD. PAST: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontologia Electronica. 2001;4(1):1-9.
  20. Mitteroecker P, Gunz P, Windhager S, Schaefer K. A brief review of shape, form, and allometry in geometric morphometrics, with applications to human facial morphology. Hystrix. The Italian Journal of Mammalogy. 2013;24(1):63-69. doi: 10.4404/hystrix-24.1-63-69.
  21. Anderson MJ. A new method for non-parametric multivariate analysis of variance. Australian Eco logy. 2001;26;32-46. doi: 10.1111/j.1442-9993.2001. 01070.pp.x.
  22. Дэвис Д.С. Статистический анализ данных в геологии. – Кн. 2. – М.: Недра, 1990. – 427 с. [Devis DS. Statisticheskii analiz dannykh v geologii. Vol. 2. Moscow: Nedra; 1990. 427 p. (In Russ.)]
  23. Hammer Ø. New methods for the statistical analysis of point alignments. Computers and Geosciences. 2009;35:659-666. doi: 10.1016/j.cageo.2008.03.012.
  24. Donnelly KP. Simulations to determine the variance and edge effect of total nearest neighbor distance. In: Simulation studies to archeology. Ed by I. Hodder. Cambridge: Cambridge Univ. Press; 1978. P. 91-95.
  25. Shapiro SS, Wilk MB. An analysis of variance test for normality (complete samples). Biometrika. 1965;52;591-611.
  26. Hedges LV, Olkin I. Statistical methods for Meta-Analysis. New York: Academic Press; 1985. 369 p.
  27. Cohen J. A power primer. Psychological Bulletin. 1992;112(1):155-159. doi: 10.1037/0033-2909.112. 1.155.
  28. Васильев А.Г., Васильева И.А. Гомологическая изменчивость морфологических структур и эпигенетическая дивергенция таксонов: основы популяционной мерономии. – М.: Тов-во науч. изд. КМК, 2009. – 511 с. [Vasil’ev AG, Vasil’eva IA. Gomologicheskaya izmenchivost’ morfologicheskikh struktur i epigeneticheskaya divergentsiya taksonov: osnovy populyatsionnoi meronomii. Moscow: Tov-vo nauch. izd. KMK; 2009. 511 p. (In Russ.)]
  29. West-Eberhard MJ. Phenotypic accommodation: Adaptive innovation due to developmental plasticity. J of Experimental Zool. (Mol Dev Evol). 2005;304B: 610-618. doi: 10.1002/jez.b.21071.
  30. Reed DH, Bryant EH. The evolution of senescence under curtailed life span in laboratory populations of Musca domestica (the housefly) J Hered. 2000;85(2):115-121. doi: 10.1046/j.1365-2540.2000.00737.x.
  31. Васильева Л.А., Юнакович Н., Ратнер В.А., Забанов С.А. Анализ изменений локализации МГЭ дрозофилы после селекции и температурного воздействия методом блот-гибридизации по Саузерну // Генетика. – 1995. – Т. 31. – № 3. – С. 333–341. [Vasil’eva LA, Yunakovich N, Ratner VA, Zabanov SA. Analiz izmenenii lokalizatsii MGE drozofily posle selektsii i temperaturnogo vozdeistviya metodom blot-gibridizatsii po Sauzernu. Genetika. 1995;31(3):333-41. (In Russ.)]
  32. Ратнер В.А., Васильева Л.А. Индукция транспозиций мобильных генетических элементов стрессовыми воздействиями // Соросовский образовательный журнал. – 2000. – Т. 6. – № 6. – С. 14–20. [Ratner VA, Vasil’eva LA. Induktsiya transpozitsii mobil’nykh geneticheskikh elementov stressovymi vozdeistviyami. Sorosovskii obrazovatel’nyi zhurnal. 2000;6(6):14-20. (In Russ.)]
  33. Антосюк О.Н. Нестабильность генома Drosophila melanogaster в условиях радиационного и химического стресса: Автореф. дис. … канд. биол. наук. – Екатеринбург, 2016. – 25 с. [Antosiuk ON. Nestabilnost genoma Drosophila melanogaster v uslovyiah radiazionnogo i khimicheskogo stressa. [dissertation] Ekaterinburg; 2016. 25 p. (In Russ.)]
  34. Никоноров Ю.М., Беньковская Г.В. Механизмы поддержания полиморфизма по продолжительности жизни в лабораторных линиях комнатной мухи // Успехи геронтологии. – 2013. – Т. 26. – № 4. – С. 594–600. [Nikonorov YM, Benkovskaya GV. The mechanisms of lifespan polymorphism maintenance in the house fly laboratory strain. Advances in Gerontology [Internet]. Pleiades Publi shing Ltd; 2014;4(3):163-8. (In Russ.)]. doi: 10.1134/s2079057014030059.

Supplementary files

Supplementary Files Action
1. Fig. 1. Locations of landmarks (1–17) on wing of house fly View (72KB) Indexing metadata
2. Fig. 2. Results of canonical analysis of Procrustes coordinates characterizing shape variation of the wing in males (1, 3) and females (2, 4) of Sh gen (1, 2) and L gen (3, 4) strains of house fly. Contour images of wing deformations – outlines correspond to the maximum and minimum values on the canonical axes. Ellipsoids include 95% of sample dispersion View (55KB) Indexing metadata
3. Fig. 3. Results of UPGMA cluster analysis of a generalized Mahalanobis distance (D2) matrix between males and females samples of Sh gen and L gen strains of house fly View (16KB) Indexing metadata


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Copyright (c) 2018 Akhmetkireeva T.T., Ben'kovskaya G.V., Vasil'ev A.G.

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