UDC 638.123.54:575.174:[577.2.08+591.4.08

doi: 10.15389/agrobiology.2015.6.776eng

Acknowledgements:
The equipment of Bioresources and Bioengineering Center of L.K. Ernst All-Russian Research Institute of Animal Husbandry was used.
Supported by the Russian Science Foundation, project 14-36-00039

MORPHOMETRIC AND MOLECULAR GENETIC DIFFERENTIATION OF
Apis mellifera caucasica L. HONEY BEE LINES REARED IN SOCHI REGION

M.S. Fornara1, A.S. Kramarenko1, 2, S.V. Svistunov3, E.M. Lyubimov3,
S.S. Sokol’skii3, N.A. Zinovieva1

1L.K. Ernst All-Russian Research Institute of Animal Husbandry, Federal Agency of Scientific Organizations,
pos. Dubrovitsy, Podolsk Region, Moscow Province, 142132 Russia,
e-mail n_zinovieva@mail.ru;
2Mykolayiv State Agrarian University,
vul. Paris Commune, 9, Mykolayiv, 54020 Ukraine,
e-mail kssnail@mail.ru;
3Krasnopolyanskii Experimental Station of Beekeeping, Federal Agency of Scientific Organizations,
4, ul. Pchelovodov, pos. Moldovka, Sochi-A, 354393 Russia,
e-mail svistunov@list.ru

Received August 14, 2015

Creating specialized lines is one of the techniques of genetic improvement and conservation of breeds and populations of the honeybee. The aim of this study was a comparative assessment of the diversity and differentiation degree of A. m. caucasica lines based on morphometric analysis and microsatellites (MS). Material for this study was the worker bees of Gray Mountain Caucasian breed (lines I-V, n = 728) which were selected in five apiaries in the Greater Sochi of Krasnodar krai. Morphometric analysis included such measurements as the length of the proboscis (LP, mm), width of third tergite (W3T, mm) and cubital index (CI). Molecular genetic studies were based on seven MS loci (A024, A88, A113, AP043, HB-C16-05, HB-THE-03, HB-C16-01). The level of variation between families for morphometric parameters was determined by two-way hierarchical analysis of variance. Genetic differences between families for MS were estimated by paired comparison of Fst values. Fst matrix was used for PCA-analysis. To determine the quantitative estimation of variation between families within lines we calculated Fst, Rst (AMOVA). The degree of line’s differentiation for morphometric characters was evaluated by calculating the Euclidean distances. The obtained values were used to construct a dendrogram of similarity by a single bond (single linkage) of the hierarchical clustering algorithm. The differentiation of lines for MS was based on calculating the values of Nei genetic distances. Similarity dendrogram was constructed using the method of UPGMA. We performed summary statistic using the software STATISTICA, GenAlEx (v. 6.5.1), PAST (v. 3.03). Morphometric analysis showed the presence of significant differences between the lines for LP and W3T whereas there was no difference between the lines for CI. The greater heterogeneity concerning studied traits in the lines II and V was revealed, and on the contrary, there was more consolidation in the lines III and IV. Bees of line I differed significantly from the rest of the lines on both traits, but they were characterized by significant differences between families in LP. Analysis of MS profiles showed similar trends in assessing the level of intra- and interfamily variability. We observed an excess of heterozygotes in the line I (Fis = -0.048), which can be considered as an indication of the high heterogeneity. Bees of this line were characterized by a minimal individual (Fit = 0.052) and the maximal interfamily variability (Fst= 0,124). Lines II-V were characterized by a deficiency of heterozygotes (Fis= 0.062-0.128), a relatively higher individual variability (Fit = 0.143-0.189) and lower values of interfamily variability comparing to line I (Fst = 0.095-0.104). The lowest interfamily differences were observed in the lines III and IV (Fst = 0.096 and 0.095, respectively). Analysis of the differentiation of the studied lines for morphometric characteristics and MS revealed differences in the structure of the family tree. The dendrogram based on MS data is a reflection of the geographical origin of these lines. The structure of the family tree, based on morphometric characters, does not reflect the geographic closeness (differences) of origin or similarities (differences) in the economically useful traits of studied lines. Thus, the results of our studies of the morphometric parameters and MS show similar trends in assessing intra- and interline variation, but there are differences in assessing differentiation of lines using two methods. In the future complex approach will allow to identify not only breeds of bees with high accuracy, but also smaller taxonomic units. It is hoped that the research results in general can be used in breeding work to restore the purity of the honeybee breeds.

Keywords: honeybee, Apis mellifera caucasica L., DNA marker, morphometry, microsatellites, biodiversity.

 

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REFERENCES

  1. Brandorf A.Z. Pchelovodstvo, 2012, 7: 14-16.
  2. Ruttner F. Biogeography and taxonomy of honey bees. Germany, Berlin, Springer, 1988.
  3. Bilash G.D., Krivtsov N.I. Pchelovodstvo, 1984, 2: 12-13.
  4. Alpatov V.V. Porody medonosnoi pchely [Breeds of honey bees]. Moscow, 1948.
  5. Sokol'skii S.S. Materialy Mezhdunarodnoi nauchnoi konferentsii «Sovremennye napravlenii nauchno-tekhnicheskogo progressa v pchelovodstve» [Proc. Int. Conf. «Recent progress in honeybee rearing»]. Rybnoe, 2007: 80-82.
  6. Sokol'skii S.S., Savushkina L.H. Pchelovodstvo, 2006, 2: 17-18.
  7. Ruttner F., Tassencourt L., Louveaux J. Biometrical-statistical analysis of the geographic variability of Apis mellifera L. Apidologie, 1978, 9: 363-381 CrossRef
  8. Ruttner F. Tekhnika razvedeniya i selektsionnyi otbor pchel [Breeding and selection of honeybees]. Moscow, 2006.
  9. Oleksa A., Tofilski A. Wing geometric morphometrics and microsatellite analysis provide similar discrimination of honey bee subspecies. Apidologie, 2015, 46: 49-60 CrossRef
  10. Rahimi A., Mirmoayedi A., Kahrizi D., Abdolshahi R., Kazemi E., Ya-
    ri K. Microsatellite genetic diversity of Apis mellifera meda skorikov. Mol. Biol. Rep., 2014, 41(12): 7755-7761 CrossRef
  11. Ivanova E., Bienkowska M., Panasiuk B., Wilde J., Staykova T.,  Stoyanov I. Allozyme variability in populations of A. mellifera mellifera (Linnaeus 1758.), A. m. carnica (Pollman, 1879) and A. m. caucasica (Gorbachev, 1916) from Poland. Acta Zool. Bulg. Suppl., 2012, 4: 81-88.
  12. Kalashnikov A.E., Maslennikov I.V., Kolbina L.M., Udina I.G. Sel'skokhozyaistvennaya biologiya [Agricultural Biology], 2013, 4: 88-92 CrossRef, CrossRef
  13. Ilyasov R.A., Kutuev I.A., Petukhov A.V., Poskryakov A.V., Nikolenko  A.G. Phylogenetic relationships of dark European honeybees Apis mellifera mellifera L. from the Russian Ural and West European populations. J. Apic. Sci., 2011, 55: 67-76.
  14. Gruber K., Schöning C., Otte M., Kinuthia W., Hasselmann M. Distinct subspecies or phenotypic plasticity? Genetic and morphological differentiation of mountain honey bees in East Africa. Ecol. Evol., 2013, 3(10): 3204-3218 CrossRef
  15. Whitfield C.W., Behura S.K., Berlocher S.H., Clark A.G., Johnston J.S., Sheppard W.S., Smith D.R., Suarez A.V., Weaver D., Tsutsui N.D. Thrice out of Africa: Ancient and recent expansions of the honey bee Apis mellifera. Science, 2006, 314: 642-645 CrossRef
  16. Harpur B.A., Kenta C.F., Molodtsova D., Lebonb J.M.D., Alqarnic A.S., Owayssc A.A.,  Zayed A. Population genomics of the honey bee reveals strong signatures of positive selection on worker traits. PNAS USA, 2013, 111(7): 2614-2619 CrossRef
  17. Jensen A.B., Palmer K.A., Boomsma J.J., Pedersen B.V. Varying degrees of Apis mellifera ligustica introgression in protected populations of the black honeybee, Apis mellifera mellifera, in northwest Europe. Mol. Ecol., 2005, 14: 93-106 CrossRef
  18. Bodur C., Kence M., Kence A. Genetic structure of honeybee, Apis mellifera L. (Hymenoptera: Apidae) populations of Turkey inferred from microsatellite analysis. J. Apic. Res., 2007, 46: 50-56.
  19. Krivtsov N.I., Goryacheva I.I., Udina I.G., Borodachev A.V., Monakho-
    va M.A. Sel'skokhozyaistvennaya biologiya [Agricultural Biology], 2010, 6: 26-29.
  20. Zinov'eva N.A., Krivtsov N.I., Fornara M.S., Gladyr' E.A., Borodachev A.V., Lebedev V.I. Sel'skokhozyaistvennaya biologiya [Agricultural Biology], 2011, 6: 75-79.
  21. Krivtsov N.I., Gladyr' E.A., Volkova V.V., Fornara M.S., Lebe-
    dev V.I., Zinov'eva N.A. Problemy biologii produktivnykh zhivotnykh, 2011, 1: 41-45.
  22. Ostroverkhova N.V., Konusova O.L., Kucher A.N., Pogorelov Yu.L., Belykh E.A., Vorotov A.A. Biologiya, 2013, 1(21): 161-172.
  23. Garnery L., Franck P., Baudry E., Vautrin D., Cornuet J.M., Solig-
    nac M. Genetic diversity of the west European honey bee (Apis mellifera mellifera and A. m. iberica). II. Microsatellite loci. Genet. Sel. Evol., 1998, 30: 49-74 CrossRef
  24. Pritchard J.K., Stephens M., Donnelly P. Inference of population structure using multilocus genotype data. Genetics, 2000, 155: 945-959.
  25. Oleksa A., Chybicki I.J., Tofilski A., Burczyk J. Nuclear and mitochondrial patterns of introgression into native dark bees (Apis mellifera mellifera) in Poland. J. Apic. Res., 2011, 50: 116-129 CrossRef
  26. Alburaki M., Bertrand B.,LegoutH.,Moulin S.Alburaki A. SheppardW.S.,GarneryL. A fifth major genetic group among honeybees revealed in Syria. BMC Genetics, 2013, 14: 117 CrossRef
  27. Muñoz I., Dall’Olio R., Lodesani M., De La Rúa P. Population genetic structure of coastal Croatian honeybees (Apis mellifera carnica). Apidologie, 2009, 40: 617-626 CrossRef
  28. Zinov'eva N.A., Popov A.N., Ernst L.K., Marzanov N.S., Bochka-
    rev V.V., Strekozov N.I., Brem G. Metodicheskie rekomendatsii po ispol'zovaniyu metoda polimeraznoi tsepnoi reaktsii v zhivotnovodstve [Manual of PCR analysis technique in animal husbandry]. Dubrovitsy, 1998.
  29. Khalafyan A.A. STATISTICA 6. Statisticheskii analiz dannykh [STATISTICA 6. Statistical analysis]. Moscow, 2007.
  30. Kramarenko S.S. Vestnik zoologii, 2009, 43(1): 51-58.
  31. Weir B.S., Cockerham C.C. Estimating F-statistics for the analysis of population structure. Evolution, 1984, 38: 1358-1370 CrossRef
  32. Nei M., Koehn R. Genetic polymorphism and the role of mutation in evolution. In: Evolution Genes and Proteins. Sinauer, Sunderland, MA, 1983: 165-190.
  33. Slatkin M. A measure of population subdivision based on microsatellite allele frequencies. Genetics, 1995, 139: 457-462.
  34. Peakall R., Smouse P.E. GenAlEx 6.5: genetic analysis in Excel: population genetic software for teaching and research — an update. Bioinformatics, 2012, 28: 2537-2539 CrossRef

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