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Ukr. Bot. J. 2018, 75(5): 489–500
https://doi.org/10.15407/ukrbotj75.05.489
Plant Physiology, Biochemistry, Cell and Molecular Biology

Genetic features of the phenological forms of Quercus robur (Fagaceae) according to the analysis of the introns polymorphism of β-tubulin genes and microsatellite loci

Pirko Ya.V.1, Netsvetov M.V.2, Kalafat L.O.1, Pirko N.M.1, Rabokon A.M.1, Privalikhin S.M.1, Demkovich A.Ye.1, Bilonozhko Yu.O.1, Blume Ya.B.1
Abstract

Early and late phenological forms of Quercus robur (Fagaceae) have been investigated using microsatellite markers and a DNA marker system based on the study of the intron's length polymorphism of the β-tubulin genes (TBP-markers). Relatively low indicators of genetic variability have been established (HO = 0.342 ± 0.208, HE = 0.566 ± 0.199 in the early and HO=0.288 ± 0.136, HE = 0.461 ± 0.216 in the late phenological groups) in 40 analyzed plants of two samples with microsatellite loci. The genetic differences between the early and late forms of Q. robur have been determined. The 9 unique alleles for microsatellite loci and 4 fragments for TBP loci among the trees of the early form, and 5 unique alleles for the microsatellite and TBP loci for the late form have been discovered. In particular, the differences in the frequency of prevalent alleles quru-GA-0C19-222 (practically absent at the late phenological sample) and quru-GA-0C19-226 (frequency reaches more than 80% in the early phenological form and only about 50% in the late) have been detected. The evaluation of the TBP polymorphism indices conducted for the investigated forms of Q. robur have revealed a lower number of fragments in the early (Ne = 1.218 ± 0.040) compared with the late phenological form of Q. robur (Ne = 1.294 ± 0.042). The value of PIC (Polymorphism Information Content) for this type of markers has been greater in the late phenological form Q. robur (PIC = 0.274 ± 0.025) than in the early form (PIC = 0.209 ± 0.022). Also, according to Shannon's information index, there are differences between the early (I = 0.253 ± 0.029) and the late (I = 0.320 ± 0.031) phenological forms of Q. robur. Analysis of the molecular variation by TBP markers (AMOVA) has been revealed slight differences in the investigated phenological forms of Q. robur. Thus, 91% of the genetic diversity of Q. robur is for intra-sample polymorphism, and 9% is inter-sampling in the overall genetic heterogeneity of the species. Our results showed that variation in seasonal timing in Q. robur is not only attributed to the variability in the growth condition but also genetically determined. More types of DNA markers are required for further researches on genetic profiling and certification of Q. robur phenological forms.

Keywords: Quercus robur, TBP-markers, microsatellites, genetic variability, phenological forms

Full text: PDF (Ukr) 1.43M

References
  1. Aldrich P.R., Michler C.H., Sun W., Romero-Severson J. Microsatellite markers for northern red oak (Fagaceae: Quercus rubra). Mol. Ecol. Notes, 2002, 2(4): 472–474. https://doi.org/10.1046/j.1471-8286.2002.00282.x
  2. Aldrich P.R., Parker G.R., Michler C.H., Romero-Severson J. Whole-tree silvic identifications and the microsatellite genetic structure of a red oak species complex in an Indiana old-growth forest. Can. J. Forest Res., 2003, 33(11): 2228–2237. https://doi.org/10.1139/X03-160
  3. Ballian D., Belletti P., Ferrazzini D., Bogunik F., Kajba D. Genetic variability of Pedunculate oak (Quercus robur L.) in Bosnia and Herzegovina. Periodicum Biologorum, 2010, 112(3): 353–362.
  4. Bardini M., Lee D., Donini P., Mariani A., Gianì S., Toschi M., Lowe C., Breviario D. Tubulin-based polymorphism (TBP): a new tool, based on functionally relevant sequences, to assess genetic diversity in plant species. Genome, 2004, 47(2): 281–291. https://doi.org/10.1139/g03-132
  5. Barna M.M., Barna L.S., Karpliuk N.A. Naukovi zapysky Ternopil National Pedagog. Univ. Ser. Biology, 2017, 4(71): 8–23.
  6. Batos B., Miljkovic D., Ninic-Todorovic J. Length of vegetation period as parameter of common oak (Quercus robur L.) phenological variability. Genetika, 2012, 44(1): 139–152. https://doi.org/10.2298/GENSR1201139B
  7. Benbouza H., Jacquemin J.-M., Baudoin J.-P., Mergeai G. Optimization of a reliable, fast, cheap and sensitive silver staining method to detect SSR markers in polyacrylamide gels. Biotechnology, Agronomy, Society and Environment, 2006, 10(2): 77–81.
  8. Breviario D., Baird W.V., Sangoi S., Hilu K., Blumetti P., Gianì S. High polymorphism and resolution in targeted fingerprinting with combined β-tubulin introns. Molecular Breeding, 2007, 20(3): 249–259. https://doi.org/10.1007/s11032-007-9087-9
  9. Carabeo M., Cosimo M., Marcello S., Chiara Ch., F. Mattia. Estimating the genetic diversity and structure of Quercus trojana Webb populations in Italy by SSRs: implications for management and conservation. Can. J. Forest Res., 2017, 47: 331–339. https://doi.org/10.1139/cjfr-2016-0311
  10. Chokheli V., Kozlovsky B., Sereda M., Lysenko V., Fesenko I., Varduny T., Kapralova O., Bondarenko E. Preliminary comparative analysis of phenological varieties of Quercus robur by ISSR-Markers. J. Botany, 2016: 1–7. https://doi.org/10.1155/2016/7910451
  11. Chung M.Y., Nason J., Chung M.G., Kim K.-J., Park C.-W., Sun B.-Y., Pak J.-H. Landscape-level spatial genetic structure in Quercus acutissima (Fagaceae). Amer. J. Bot., 2002, 89(8): 1229–1236. https://doi.org/10.3732/ajb.89.8.1229
  12. Cottrell J.E., Munro R.C., Tabbener H.E., Milner A.D., Forrest G.I., Lowe A.J. Comparison of fine-scale genetic structure using nuclear microsatellites within two British oak woods differing in population history. Forest Ecol. Management, 2003, 176(1–3): 287–303. https://doi.org/10.1016/S0378-1127(02)00289-X
  13. Coutinho J.P., Carvalho A., Lima-Brito J. Taxonomic and ecological discrimination of Fagaceae species based on internal transcribed spacer polymerase chain reactionrestriction fragment length polymorphism. AoB Plants, 2015, 7(1): 60–79. https://doi.org/10.1093/aobpla/plu079
  14. Dantec C.F., Ducasse H., Capdevielle X., Fabreguttes O., Delzon S., Desprez-Loustau M. Escape of spring frost and disease through phenological variations in oak populations along elevation gradients. J. Ecol., 2015, 103(4): 1044–1056. https://doi.org/10.1111/1365-2745.12403
  15. Demkovich A.Ye. Promyshlennaya botanika (Industrial botany), 2007, 7: 33–36.
  16. Demkovych A.Ye., Korshikov I.I., Makogon I.V. Factors in experimental evolution of organisms, 2014, 14: 17–21.
  17. Dow B.D., Ashley M.V., Howe H.F. Characterization of highly variable (GA/CT) n microsatellites in the bur oak, Quercus macrocarpa. Theor. Appl. Genetics, 1995, 91(1): 137–141. https://doi.org/10.1007/BF00220870
  18. Gelanalyzer.com [Electronic resource]. Available at: http://www.gelanalyzer.com/
  19. Green M. R., Sambrook J. Molecular cloning. Cold Spring Harbor (New York): Cold Spring Harbor Lab. Press, 2012, 1890 pp.
  20. Gugerli F., Brodbeck S., Holderegger R. Utility of multilocus genotypes for taxon assignment in stands of closely related European white oaks from Switzerland. Annals of botany, 2008, 102(5): 855–863. https://doi.org/10.1093/aob/mcn164
  21. Hongtrakul V., Huestis G.M., Knapp S.J. Amplified fragment length polymorphisms as a tool for DNA fingerprinting sunflower germplasm: genetic diversity among oilseed inbred lines. Theor. Appl. Genetics, 1997, 95(3): 400–407. https://doi.org/10.1007/s001220050576
  22. Jensen J., Larsen A., Nielsen L.R., Cottrell J. Hybridization between Quercus robur and Q. petraea in a mixed oak stand in Denmark. Ann. Forest Sci., 2009, 66(7): 706. https://doi.org/10.1051/forest/2009058
  23. Khlestkina E.K. Molecular markers in genetic studies and breeding. Russ. J. Genet. Appl. Res., 2014, 4(3): 236–244. https://doi.org/10.1134/S2079059714030022
  24. Matiashuk R.K., Nebesnyi V.B., Konyakin S.M., Tkachenko I.V., Prokopuk Yu.S. Naukovi dopovidi NUBIP Ukraine, 2014, 6: 40–48.
  25. Milenin A.I. Ecological features phenological varieties of English oak (Quercus robur L.) under the CCA: Cand. Sci. Diss. Abstract. Voronezh, 1997, 24 pp.
  26. Molchanov A.G. In: Structural and functional deviations from normal growth and development of plants: mat. distance conf. Karelian Research Centre. Petrozavodsk, 2011, pp. 204–208.
  27. Molchanov A.G. Lesovedenie, 2012, 4: 31–38.
  28. Neophytou C., Aravanopoulos F., Fink S., Dounavi A. Detecting interspecific and geographic differentiation patterns in two interfertile oak species (Quercus petraea (Matt.) Liebl. and Q. robur L.) using small sets of microsatellite markers. Forest Ecol. Management, 2010, 259(10): 2026–2035. https://doi.org/10.1016/j.foreco.2010.02.013
  29. Netsvetov M.V., Prokopuk Yu.S. Ukr. Bot. J., 2016, 73(2): 126–133. https://doi.org/10.15407/ukrbotj73.02.126
  30. Peakall R., Smouse P. GenAlEx 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes, 2006, 6: 288–295. https://doi.org/10.1093/bioinformatics/bts460
  31. Pérez-de-Lis G., Olano J.M., Rozas V. et al. Environmental conditions and vascular cambium regulate carbon allocation to xylem growth in deciduous oaks. Funct. Ecol., 2017, 31 (3): 592–603.
  32. Pirko N.N., Demkovych A.Ye., Kalafat L.O., Privalikhin S.N., Rabokon A.N., Pirko Ya.V., Blume Ya.B. Intron length polymorphism of β-tubulin genes in different representatives of Pinaceae Lindl. family. J. Bot., 2016, VIII, 2(13): 5–9.
  33. Puchałka R., Koprowski M., Gričar J., Przybylak R. Does tree-ring formation follow leaf phenology in Pedunculate oak (Quercus robur L.)? Eur. J. Forest Res., 2017, 136: 259–268. https://doi.org/10.1007/s10342-017-1026-7
  34. Rahman M. H., Jaquish B., Khasa P. D. Optimization of PCR protocol in microsatellite analysis with silver and SYBR® stains. Plant Mol. Biol. Reporter, 2000, 18(4): 339–348. https://doi.org/10.1007/BF02825061
  35. Rubtsov V.V., Zhirenko N.G., Utkina I.A. Lesovedenie, 2007, 5: 44–55.
  36. Silchenko I.I. Vestnik Bryansk. gos. un-ta (Herald Bryansk State University), 2012, 4: 158–161.
  37. Singh P., Mehta N., Sao A. Genetic purity assessment in linseed (Linum usitatissimum L.) varieties using microsatellite markers. Bioscan, 2015, 10(4): 2031–2036.
  38. Slepykh O.O. Biologichni systemy (Biological systems), 2016, 8(2): 272–279.
  39. Steinkellner H., Fluch S., Turetschek E., Lexer C., Streiff R., Kremer A., Burg K., Glossl J. Identification and characterization of (GA/CT) n-microsatellite loci from Quercus petraea. Plant Mol. Biol., 1997, 33(6): 1093–1096. https://doi.org/10.1023/A:1005736722794
  40. Utkina I.A., Rubtsov V.V. Studies of phenological forms of pedunculate oak. Contemporary Problems of Ecology, 2017, 10(7): 804–811. https://doi.org/10.1134/S1995425517070101
  41. Vranckx G., Jacquemyn H., Mergeay J., Cox K., Kint V., Muys B., Honnay O. Transmission of genetic variation from the adult generation to naturally established seedling cohorts in small forest stands of pedunculate oak (Quercus robur L.). Forest Ecol. Management, 2014, 312: 19–27. https://doi.org/10.1016/j.foreco.2013.10.027
  42. Xia X., Luan L.L., Qin G., Yu L.F., Wang Zh.W., Dong W.C., Song Y., Qiao Y., Zhang X.S., Sang Y.L., Yang L. Genome-wide analysis of SSR and ILP markers in trees: diversity profiling, alternate distribution, and applications in duplication. Scientific Reports, 2017, 7(1): 17902. https://doi.org/10.1038/s41598-017-17203-6