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Biosystems
Diversitv
Biosystems
Diversity
ISSN 2519-8513 (Print) ISSN 2520-2529 (Online) Biosyst. Divers., 26(4), 269-275 doi: 10.15421/011841
Studying the genetic structure of Quercus robur forest stands on anthropogenically transformed territories using introns of the ß-tubulin gene
Y. V. Pirko*, A. E. Demkovich*, L. O. Kalafat*, Y. B. Blume*, О. A Lykholat**
*Institute of Food Biotechnology and Genomics of the National Academy of Sciences of Ukraine, Kyiv, Ukraine **University of Customs and Finance, Dnipro, Ukraine
Article info
Received 11.10.2018 Received in revised form
07.11.2018 Accepted 10.11.2018
Institute of Food Biotechnology and Genomics ofthe National Academy of Sciences of Ukraine, Osipovskogo st., 2a, Kyiv, 04123, Ukraine. Tel.: +38-050-961-48-09. E-mail: yarvp1@gmail. com
University of Customs and Finance, Volodymyr Vernadsky st., 2/4, Dnipro, 49000, Ukraine. E-mail: [email protected]
Introduction
Pirko, Y. V., Demkovich, A. E., Kalafat, L. O., Blume, Y. B., & Lykholat, O. A. (2018). Studying the genetic structure of Quercus robur forest stands on anthropogenically transformed territories using introns of the P-tubulin gene. Biosystems Diversity, 26(4), 269-275. doi:10.15421/011841
Based on the analysis of the intron polymorphism of P-tubulin genes, the genetic variability of old Quercus robur L. trees from "Holosiivsky" NPP was investigated. The genotyping of 55 old Q. robur trees was carried out; 40 polymorphic and one monomorphic (about 880 bp) TBR fragments were found. High frequency (70-90%) of occurrence of fragments with an approximate molecular weight of275, 490, 500, and 1110 bp was observed.The genetic polymorphism of old Q. robur trees was assessed as quite high: PIC is 0.22 - 0.39, the effective number of alleles per locus was 1.174-1.268. The Shannon information index was in the range of 0.204-0.269.The geographical differentiation of the genetic structure of centuries-old oak trees from "Holosiivsky" NPP was not pronounced. The share of inter-selection genetic variability (AMOVA) accounts for about 6% of genetic variability, and the geographic component - about 1%. Around 93% of genetic variability is concentrated on the individual level. Using the TBP method, we found that Q. robur forest stands do not have a stabilized genetic and visible spatial structure, but at the same time they possess a sufficiently large genetic diversity. The absence of a spatial genetic structure may indicate the artificial origin of Q. robur trees from different seed materials, and also that a small number of the plants have survived to this time. In this case, the main influence on the structure of oak stands in "Holosiivsky" NPP was from anthropogenic factors, both in the form of cutting down trees and, possibly, the introduction of alien seed material.
Keywords: spatial structure; molecular markers; polymerase chain reaction
The common oak {Quercus robur L.) is a native species of the Ukrainian flora, one of the main forest-forming species, which covers around 24% of the total forest area of Ukraine (Derzhavne Ahentstvo Lisovykh Resursiv Ukrayiny [State Forest Resources Agency of Ukraine], http://dklg.kmu.gov.ua/forest/control/uk/publish/article?art_id=62921&). It is characterized by high ecological flexibility and has great economic importance. This species can exist in various ecotopes and edaphotopes, distributed from the north of Scandinavia to the south of Europe, from the Iberian Peninsula to the Ural Mountains, and is the key species in many biomes. Historically, over the process of evolution, the oak has divided into separate species, and the process of exchange of genetic material existed and continues to exist (Leroy et al., 2017; McVay et al., 2017).
The common oak is a wind-pollinated (anemogamous) plant, but the majority of acorns spread near the mother plants, and acorns cover significant distances only because of carriers - birds, rodents, humans (Gerber et al., 2014).
This species prefers fertile soil, but is rather resistant to industrial emissions and is actively used in the creation of sanitary zones of industrial enterprises, inner city woodlands and in green building. Oak is used as the main species in field-protection and anti-erosion plantations (Bry-gadyrenko, 2015). As cities around the world become more and more overloaded and polluted (Blanco et al., 2009), trees can reduce air pollution by absorbing some atmospheric pollutants (Nowak et al., 2006).
Green plantations can also reduce the temperature of the environment by 6 °C (Wenting et al., 2012), which reduces the overheating of urban residents (Nowak et al., 1998; Cummins & Jackson, 2001; Wolch, 2014). Suburban oak forests can efficiently absorb the polluting substances, including reducing concentrations of gaseous NH3, with an
average reduction by 29-38% (García-Gómez et al., 2016). So the powerful structure, hardiness and resistance of Q. robur along with its high decorative properties determine its widespread use in green building.
Kyiv has a centuries-long history, during which local forests were actively used, and subsequently artificially renewed. Q. robur was one of the main species which were cut down and replanted. So, nowadays, along with young oak species of artificial and natural origin, age-old oak trees are quite common, which may be the remaining part of the former natural forests. A significant proportion of Q. robur has protected status and needs more detailed study of origin, belonging to local tree stands, etc.
Holosiivsky forest belongs to the territory of Kyiv which is rich in old trees. This forest is a remnant of a native forest, which located on the southwest approaches to Kyiv at the time of Kievan Rus (Vasilyuk et al., 2012). Now the Holosiivsky forest is Kyivs largest forest territory, completely surrounded by residential areas. This forest area of more than 1000 hectares is located in the southern part of Kyiv. This is mainly hornbeam-oak forest, formed on gray and light-gray forest soils on loess sediments (Onyshchenko, 2013). The greater part of the forest belongs to the Holosiivsky National Park (HNP) (Pryrodno-zapovidnyy fond Ukrayiny [Nature Reserve Fund of Ukraine], http://pzf.land.kiev.ua/pzf-obl-10.html).
According to the data of surveys of the forests, within the territory, the constantly used area of the NNP is the forest areas with the age of the tree stand of200 years or older (up to 240), and equals 143 ha (20% of the area of forest vegetation), in all cases the main dominant species, for which the age is determined, is Q. robur (Onyshchenko, 2013). Adult oak plants in the area of the "Holosiivsky" park are positioned quite close one to another. Often there is a pattern of growth of old trees along the central paths of the park, in contrast to younger trees. The origin of these tree stands, the source of their seed material, is unknown.
The strong development, the long life of common oak plants make it a model for diverse assessment of the genetic processes, with reforestation in anthropogenically disturbed territories or the preservation of existing tree stands in conditions of intense technogenic load (Petit, 2002; Neophytou, 2010; Frouz, 2015). Due to the popularity of Q. robur, depending on the orientations of the study, the following methods are used: morphological (Semerikov, 1976), isoenzyme polymerase chain reaction (PCR) (Kremer, 1993; Aldrich et al., 2003; Grivet et al., 2008; Hampe et al., 2013) and genome sequencing (Plomion et al., 2016).
The variability of Q. robur as a subject of research has long been exploited (Semerikov, 1976). To determine the genetic relations, researchers used methods of qualitative phenetics, protein electrophoresis from seeds, isoenzyme analysis, while its genetic diversity with the use of molecular markers, based on polymerase chain reaction (PCR), has been studied within its range in Europe for more than 20 years (Kremer, 1993; Sork et al., 2002; Aldrich et al., 2003; Hampe et al., 2013).
At the same time, introns are becoming increasingly popular as a source of DNA polymorphism. It has been determined that introns are involved in numerous important molecular events as the control of gene expression through the mechanism of alternative splicing and other mechanisms (Rose, 2002; Leet al., 2003; Li et al., 2007; Morello & Breviario,
2008; Braglia, 2010), they are hyper variable regions, comparable in polymorphism terms with microsatellite loci and may have different nucleotide composition and length, even within the limits of one taxonomic unit. In general, the polymorphism of the intron length of the P-tubulin gene is a stable working system of molecular-genetic markers of different species of terrestrial plants, which can be used in genetic analysis of plants (Breviario et al., 2007; Blume et al., 2010; Pirko, 2011; Rabocon et al., 2015).
The objective of the study was to obtain data on the polymorphism of the samples of centuries-old trees of Q. robur from Holosiivsky NNP on the basis of genotyping according to the TBR locus, analyzing the spatial component of genetic variability, assessing the anthropogenic impact on the genetic structure of the natural tree species.
Materials and methods
The material from Q. robur trees was selected during 2016 in "Holosiivsky" Park, Kyiv (Fig. 1). Q. robur trees older than 100 years (we selected trees with the largest trunk diameter) were used, some of the trees have protected status. In total, material from 55 trees was selected.
Fig. 1. A common oak tree in Holosiivsky Forest
The trees selected for analysis were divided into five population samples: 1 - trees growing on the side of the "Holosiivsky Desert" (8 plants), 2 - trees from the upper slope of the ravine (19 plants), 3 -trees from the bottom the slope of the ravine (7 plants), 4 - the trees located between the Main Astronomical Observatory of the National Academy of Sciences of Ukraine and the Museum "Pirogovo" (6 plants),
5 - trees in the area of the Observatory and its surroundings (15 plants) (Fig. 2). As material, the leaf laminae were taken and put into zipper packets with dry silica gel. The dried laminae were maintained at -80 °C
The geodata, in relation to the location of the source of the material, were collected at the same time as the material. For this geotags, separated from the photos of the plants from which the material was collected, were processed using scripts in the statistical programming environment "R" (R Core Team, 2011; R Foundation for Statistical Computing, Vienna, Austria; www.R-project.org), packages "googleVis" and "geosphere". The obtained geodata were exported to the GenAlEX package (Peakall
6 Smouse, 2006).
Isolation of DNA and PCR. Genomic DNA was extracted from the laminae using the CTAB-method (2012). The quality and quantity of DNA were checked using electrophoresis in 1.5% agarose gel and spect-rophotometrically on an Eppendorf biophotometer with the determination of the concentration and degree of DNA contamination. DNA samples were maintained at -20 °C.
The TBP analysis was conducted according to Breviario (Bardini et al., 2004). Primer sequences (Breviario et al., 2007):
TBP-F: 5 '-AACTGGGCBAARGGNCAYTAYAC-3';
TBP-R: 5'-ACCATRCAYTCRTCDGCRTTYTC-3 '. The PCR was performed on the Thermal Cycler 2720 amplifier (Applied Biosystems, USA). The reaction mixture (10 ^l) contained a fivefold-diluted PCR buffer with ammonium sulfate, 2.5 mmoles of MgCl2, 50 ng of plant DNA, 1 ^M of each primers, 0.2 mm of each dNTPs, 0.5 units of Taq polymerase (Fermentas, Lithuania). The amplification was carried out in accordance with the following protocol: initial denaturation (94 °C
during 3 min); 35 cycles of amplification (denaturation 94°C - 30 s, annealing of primers at 55 °C - 40 s, extension 72 °C - 90 s); final extension of 72 °C - 8 minutes, 15 °C - maintenance (Bardini et al., 2004).
Fig. 2. Locations of oaks in the Holosiivsky park, from which the material was collected
Each PCR reaction was performed at least in triple replication using negative control so during the following electrophoretic analysis, there would be a possibility of detecting nonspecific amplification products differing in the same reactions. Amplification products (0.5 ^l) were distributed by electrophoresis in a 6% non-denaturing polyacrylamide gel in 1 x TBE buffer (Green & Sambrook, 2012) at 300 V for 5 hours. Visualization of the fragments was carried out by silver nitrate staining (Rahman et al., 2000; Benbouza et al., 2004). After electrophoresis, the gel was photographed in visible light and the resulting images were subjected to further analysis.
The analysis of the electrophoretic gels was carried out in the GelAna-lyzer program. The length of the reproducible and distinct bands was determined using a DNA marker (O'Gene Ruler™ 100bp Plus DNA Ladder, ready-to-use; "Fermentas", Lithuania). TBP bands were recorded in the binary code: the presence of the band - one, the absence - zero.
Statistical processing of data. Primary statistical processing of genetic data was carried out in the program GenAlEX (Peakall, 2006). This program assessed the frequency of alleles on locus Ne, and the main parameters of polymorphism (present heterozygosity - HO, expected heterozygosity - HE, Shannon's information index - I), we performed an analysis of the molecular variance (AMOVA). For TBP-markers, we used Binary Diploid format of data, for SSR CodominantDiploid. The analysis was performed on the basis of the matrices of genetic distances, calculated in GenAlEX, we conducted the analysis in the same program
using the method of the main coordinates. The comparison of genetic distance matrices, calculated on the basis of different classes, was performed on the basis of Mantel's test in GenAlEX.
The level of polymorphism of the markers was assessed using the Polymorphism Information Content Index (PIC) using the formula:
PIC _ SiLlC1- ~ fai~ fct) 11
where, n - the total number of evaluated polymorphic fragments, fa -the frequency of cases (organisms) in which this fragment was absent, and fp - the frequency of organisms in which this allele was present (Hongtrakul et al., 1997; Breviario et al., 2007).
Results
Analysis of TBP loci in 55 Q. robur trees in total showed 41 bands (Fig. 3). Of these, 40 out of 41 fragments were polymorphic. A fragment with an approximate molecular weight of 880 base pair (bp) was mono-morphic in all the samples. The number of polymorphic fragments in the analyzed groups of the oak trees directly correlated with the group size. Accordingly, group 4 (consisting of 6 trees) was characterized by presence of 19 polymorphic fragments, and group 5 (15 trees) - 30 polymorphic fragments. The distribution zone of all fragments was in the approximate range from 250 to 1300 bp.
Fig. 3. Electrophoregram with amplicones of P-tubulin genes introns of centuries-old Q. robur trees: 1 - 55 (from above) - sample numbers of five groups; m - DNA marker
The allele frequencies obtained by the TBP markers in Q. robur plants are presented in Figure 4.
Fig. 4. Frequencies of TBP-markers in leaves of centuries-old Q. robur trees from Holosiivsky Park
The frequency of most of the fragments (namely 27) was less than 20%: 19 fragments with a frequency of less than 10% and 8 fragments
with a frequency 10-19% There are 6 fragments in the range 20-39%, and only 3 fragments in the range 30-69%. Most common were fragments with an approximate molecular weight of275, 490, 500, 1110 bp (frequency ranging 70-90%) and 880 bp (100% frequency). So, as can be seen in the figure, the largest share of the fragments belongs to the rare ones.
The assessment of the allelic polymorphism, performed in each particular selection, demonstrated practically the same effective number of alleles per locus (1.174-1.268), taking into account the errors of the obtained values (Fig. 5). According to the Shannon information index (0.204-0.269), the differences between the studied groups were within the error. That is, there were no significant differences in the genetic polymorphism between all studied groups of old Q. robur plants.
Since the TDR method belongs to biallelic markers, it is advisable to use a polymorphic information content index (PIC) to assess the genetic diversity. The lowest value of PIC (0.22) was found in group 2, which included trees from the upper slope of the ravine, and the highest value of PIC (0.39) was in group 4, which included 6 trees from the territory between the Main Astronomical Observatory and Museum
"Pirogovo". In general, the average PIC for all studied groups equals about 0.3. This can be considered a high value, given that for any biallelic marker the maximum PIC equals 0.5.
Fig. 5. Main parameters of the allele diversity in the analyzed groups of common oak in relation to TBP-markers
Further analysis of the molecular variance (AMOVA) revealed almost complete absence of inter-sampling subdivision (Fig. 6). Thus, within the general genetic heterogeneity of the species, 93% of the genetic diversity of Q. robur has an internal sampling polymorphism, and only 6% is the fraction of inter-sampling polymorphism (geographical polymorphism can be ignored for its share accounts for only 1%).
Fig. 6. Distribution of the molecular variations (AMOVA) within the population of old Q. robur trees from Holosiivsky Park
Mantel's test between the matrix of geographical and genetic distances in relation to TBP, assesses the significance level of the non-randomness of the distribution of geographic and genetic distances between individual trees at the level (P < 0.034), at the same time a direct correlation between geographic and genetic distances was practically absent (Fig. 7).
Fig. 7. Mantel's test between the representatives of all studied groups of old Q. robur trees on TBR markers and geographic distances
Mantel's test for matrices of distance between oaks, calculated using TBP markers, revealed no significant correlations (Fig. 8). The present
correlation coefficient was not distinguished from the selection of distances of correlation coefficients, randomly generated on the basis of these two matrices, with probability of 0.11.
Fig. 8. Distribution of the generated correlation coefficients in Mantel's test and available correlation coefficient (red) for the Q. robur studied groups
The analysis of the representatives of the tree stands of common oak using the method of principal components also did not show a high degree of ordination of the principal components of the representatives of the selections in the space (Fig. 9).
38 3*4 ♦ 45 »7 ♦ 44 39 ♦ 3 ♦ 43 ♦ 41 A 28 ♦ 50 1H_ j au4M
A 34 ♦ 54 4 53 A 31 1 14 ♦ 42 1 13 ♦47 « m ♦ 49 A 32 ► 46 is 1 26 * 5 ♦ 52
♦ popl pop2
Apop3 pop4
♦ pop5
Coord. 1
Fig. 9. Ordination of Q. robur representatives in the space of the first two principal components
The results of the spatial genetic structure analysis of all specimens determined that neither single selection, nor all samples together have any correlation between genetic distances and the geographical distance between the trees (Fig. 10). That is, there is no spatial genetic structure at the level of separate groups, and in the studied area in general.
-Correlation coefficient .......Limits of The bootstrap confidence interval Dt--''" a /
\ / .......W
O V; O <Ti O Ti O <Ti O <Ti O <Ti O <Ti O <Ti O <Ti O Ti O <Ti O Ti O <Ti O Ti O <Ti O Ti O <Ti O <Ti O <Ti O f 1 fi I O f 1 IT, I O f 1 IT, I O f 1 IT, I O f 1 IT, I O f 1 IT, I O f 1 IT, I O f 1 IT, I Z f 1 fi I Z f 1 Ti I Z
HHwHriMMMmmcKfiffltfl " ,r ,r ,r 'O 'O 'O 'O r r r-r-œœcocoaioioiaio Classes of distances
Fig. 10. Results of the analysis of spatial genetic structure of oak tree stands
Discussion
The level of genetic diversity of species is often associated with certain characteristics, such as length of life cycle, pairing and reproduction, size of the geographical range and genetic exchange (Gaudeul et al., 2000;
Hellmanna & Pineda-Kerch, 2007; Li et al., 2008). In our study, most of the fragments found during the analysis of TBR-polymorphisms are rare. Only 3 fragments were found in 30-70% of trees. At the same time, for each of the samples, an effective number of alleles per locus (1,1741,268) was observed.
As has been demonstrated (Plomion et al., 2018), such large polymorphism may be related to the mechanisms of oak resistance by increasing genetic variability at the individual level. At the same time, according to the Shannon information index (0.204-0.269), the differences between the samples are within the error and no reliable differences in the genetic polymorphism in all studied groups of common species of oak were found. Similar results were observed for 3 natural populations of Q. petrea (Pospísková & Dostálek, 2010).
It should be noted that one of the sources of variability for the oak, as a hardy plant, can be manifestations of somatic variability, which may be due to the mechanisms of plant resistance (Plomion et al., 2018).
The absence of intraspecific subdivision, demonstrated by molecular variation analysis (AMOVA), may be due to a number of causes. Thus, for similar studies of natural populations of sawtoothed oak (Q. acutis-sima), the reduction of inter-sample variability compared to individual variability is associated with a high level of outcrossing in oak woodlands (Chung, 2002).
In Italy a similar study using AFLP in more than 300 trees in three Q. suber stands has also demonstrated a very low level of variability at the inter-population level. Thus, among the all studied Q. suber Ht = 0.253, only 1.7% were attributed to the differences between the populations. AMOVA analysis, similar to ours, showed that majority of the genetic variability is maintained at the 9% probability level, and among certain populations it equaled 3.6% (Fst = 0.036, P < 0.001).
At the same time, differences between populations in geographical boundaries are also proved by a very low level of genetic variability as 2.6% (Fsc = 0.026, P < 0.001) of the overall variation and only 1.3% (Fct = 0.013, P = 0.007) by the results of the variation between regions, which characterizes a small differentiation of populations in the range of 700 km (Coelho et al., 2006). In the study of natural populations of oaks (Q. acutissima), the variability associated with the population structure was seven times lower than interindividual variability, which is likely associated with prevailing outcrossing in oak woodlands (Chunget al., 2002).
In our study, the Mantel test between the TMR geographic and genetic distances assesses the level of significance of the correlations between genetic and geographical distances between trees at the level (P < 0.034), direct correlations between geographic and genetic distances were absent. In general, the high genetic variability observed in oak populations is associated with biological signs of long-living species such as air pollution, cross-over, large effective population size and a large pollen flow among the population (Sork et al., 2002; Sork & Smouse, 2006; Young & Pickup, 2010). Thus, the assessment of genetic diversity found in our study was close to the assessments for other species of Quercus in South and North America and Europe (Fernández & Sork, 2005; Aldrich & Cavender-Bares, 2011; Ashley et al., 2015; Oyamaetal., 2018).
According to the results of the autocorrelation analysis of the spatial genetic structure of all samples, it was determined that some samples as well as all samples have no global correlation between the genetic distances and the geographical distance between the trees (Fig. 10). There was no spatial genetic structure at the level of individual groups, and in the studied area in general. At the same time, two classes of distances (575 and 600 m) were found, for which there is a certain positive coefficient of autocorrelation.
Examination offour closely related oak species (Q. robur, Q. petraea, Q. pubescens and Q. frainetto) from Romania (covering a small area), along with a high diversity, demonstrated the presence of spatial genetic auto-correlation at distance of 25 m (Curtu et al., 2015) and its absence at larger distances. Similar studies of red oak (Q. rubra) and northern pin oak (Q. ellipsoidalis) have demonstrated the presence of a spatial genetic structure at distances up to 83 m in the Q. rubra population (Lind-Riehl& Gailing, 2015).
In natural populations of red oak, undergoing minimal anthropogenic impact, American scientists have found a fairly significant degree of spatial autocorrelation (Feng et al., 2008). A certain degree of spatial
autocorrelation has been observed for Q. petraea in Denmark (Jensen et al., 2003). However, for Q. robur seed plantations the spatial correlation was not observed (Katicic et al., 2018). Thus, on the basis of the assessed spatial genetic structure of the tree stands of the "Holosiivsky" NNP we can conclude that there are both primary elements of the spatial structure characteristic for natural populations and populations under anthropogenic influence, which most likely consist of planting of a specific seed material (Katicic et al., 2018) and possibly selective felling.
Conclusion
Expeditionary study and material collection of old Q. robur trees has been carried out, the scheme of the location of the samples was developed, the geographical coordinates of the trees on the territory of NNP (Kyiv) were determined.
The genotyping of 55 old trees was carried out. We found 40 polymorphic and one monomorphic (about 880 bp) TBR fragments. The high frequency of occurrence of fragments with an approximate molecular weight of275, 490, 500, 1110 bp (70-90%) is noted.
The genetic polymorphism of old Q. robur trees was quite high: PIC equaled 0.22-0.39, the effective number of alleles per locus was 1.174-1.268, the Shannon information index was 0.204-0.269.
There was no pronounced geographical differentiation of the genetic structure of the samples of old Q. robur trees from the Holosiivsky NPP. The share of intraspecific genetic variability (AMOVA) accounts for about 6% of genetic variability, and the geographic component -about 1%. About 93% of genetic variability is concentrated on the individual level.
Using the TBP method, we found that the studied Q. robur woodlands had no stabilized genetic and visible spatial structure, but at the same time they had a sufficiently large genetic diversity. The absence of spatial genetic structure in the analyzed old trees may indicate the artificial origin of the trees from different seed materials and, at the same time, a small number of the plants have survived to this time, which destroys the spatial genetic structure of the oak forests. The main factor in this case was anthropogenic impact both in the form of felling, and, possibly, the cultivation of non-adventive material.
References
Aldrich, P. R., & Cavender-Bares, J. (2011). Quercus. In: Kole, C. (Ed.) Wild crop relatives: Genomic and breeding resources, forest trees. Springer-Verlag, Berlin. Pp. 89-129.
Aldrich, P. R., Jagtap, M., Michler, C. H., & Romero-Severson, J. (2003). Amplification of North American red oak microsatellite markers in european white oaks and chinese chestnut. Silvae Genetica, 52(3-4), 176-179. Ashley, M. V., Abraham, S. T., Backs, J. R., & Koenig, W. D. (2015). Landscape genetics and population structure in Valley Oak (Quercus lobata Née). American Journal of Botany, 102(12), 2124-2131. Bardini, M., Lee, D., Donini, P., Mariani, A., Giani, S., Toschi, M., Lowe, C., & Breviario, D. (2004). Tubulin-based polymorphism (TBP): A new tool, based on functionally relevant sequences, to assess genetic diversity in plant species. Genome, 47(2), 281-291. Benbouza, H., Jacquemin, J.-M., Baudoin, J.-P., & Mergeai, G. (2006). Optimization of a reliable, fast, cheap and sensitive silver staining method to detect SSR markers in polyacrylamide gels. Biotechnology, Agronomy, Society and Environment, 10(2), 77-81. Blanco, H., Alberti, M., Forsyth, A., Krizek, K. J., Rodriguez, D. A., Talen, E., & Ellis, C. (2009). Hot, congested, crowded and diverse: Emerging research agendas in planning. Progress in Planning, 71(4), 153-205. Blume, Y., Yemets, A., Sheremet, Y., Nyporko, A., Sulimenko, V., Sulimenko T., & Draber P. (2010). Exposure of beta-tubulin regions defined by antibodies on an Arabidopsis thaliana microtubule protofilament model and in the cells. BMC Plant Biology, 2010, 10-29. Braglia, L., Manca, A., Mastromauro, F., & Breviario, D. (2010). cTBP: A successful intron length polymorphism (ILP)-based genotyping method targeted to well defined experimental needs. Diversity, 2(4), 572-585. Breviario, D., Baird, W. V., Sangoi, S., Hilu, K., Blumetti, P., & Giani, S. (2007). High polymorphism and resolution in targeted fingerprinting with combined p-tubulin introns. Molecular Breeding, 20(3), 249-259. Brygadyrenko, V. V. (2015). Community structure of litter invertebrates of forest belt ecosystems in the Ukrainian steppe zone. International Journal of Environmental Research, 9(4), 1183-1192.
Chung, M. Y., Nason, J., Chung, M. G., Kim, K.-J., Pak, C.-W., Sun, B.-Y., & Pak, J.-H. (2002). Landscape-level spatial genetic structure in Quercus acu-tissima (Fagaceae). American Journal of Botany, 89(8), 1229-1236.
Coelho, A. C., Lima, M. B., Neves, D., & Cravador, A. (2006). Genetic diversity of two evergreen oaks (Quercus suber L. and Q. (ilex) rotundifolia Lam.) in Portugal using AFLP markers. Silvae Genetica 55(3), 105-118.
Cummins, S. K., & Jackson, R. J. (2001). The built environment and children's health. Pediatric Clinics of North America, 48(5), 1241-1252.
Curtu, A. L., Craciunesc, I., Enescu, C. M., Vidalis, A., & Sofletea, N. (2015). Fine-scale spatial genetic structure in a multi-oak-species (Quercus spp.) forest. iForest - Biogeosciences and Forestry, 8(3), 324-332.
Feng, Y., Sun, W., & Romero-Severson, J. (2008). Heterogeneity and spatial autocorrelation for chloroplast haplotypes in three old growth populations of Northern red oak. Silvae Genetica, 57, 212-220.
Fernández, M. J. F., & Sork, V. L. (2005). Mating patterns of a subdivided population of the Andean oak (Quercus humboldtii Bonpl., Fagaceae). Journal of Heredity, 96, 635-643.
Frouz, J., Voborilová, V., Janousová, I., Kadochová, S., & Matejícek, L. (2015). Spontaneous establishment of late successional tree species English oak (Quercus robur) and European beech (Fagus sylvatica) at reclaimed alder plantation and unreclaimed post mining sites. Ecological Engineering, 77, 1-8.
García-Gómez, H., Aguillaume, L., Izquieta-Rojano, S., Valiño, F., Avila, A., Elustondo, D., Santamaría, J. M., Alastuey, A., Calvete-Sogo, H., González-Fernández, I., & Alonso, R (2016). Atmospheric pollutants in peri-urban forests of Quercus ilex. Evidence of pollution abatement and threats for vegetation. Environmental Science and Pollution Research, 23, 6400.
Gaudeul, M., Taberlet, P., & Till-Bottraud, I. (2000). Genetic diversity in an endangered alpine plant, Eryngium alpinum L. (Apiaceae), inferred from amplified fragment length polymorphism markers. Molecular Ecology, 9, 1625-1637.
Gerber, S., Chadreuf, J., Gugerli, F., Lascoux, M., Buiteveld, J., Cottrell, J., Dounavi, A., Fineschi, S., Forrest, L. L., Fogelqvist, J., Goicoechea, P. G., Jensen, J. S., Salvini, D., Vendramin, G. G., & Kremer, A. (2014). High rates of gene flow by pollen and seed in oak populations across Europe. PLoS One, 9(1), e85130.
Green, M. R., & Sambrook, J. (2012). Molecular cloning. Cold Spring Harbor Laboratory Press, Cold Spring Harbor.
Grivet, D., Sork, V. L., Westfall, R. D., & Davis, F. W. (2008). Conserving the evolutionary potential of California valley oak (Quercus lobata Née). A mul-tivariate genetic approach to conservation planning. Molecular Ecology, 17(1), 139-156.
Hampe, A., Pemonge, M.-H., & Petit, R. J. (2013). Efficient mitigation of founder effects during the establishment of a leading-edge oak population. Proceedings ofthe Royal Society B, 280(1764), 20131070.
Hellmanna, J. J., & Pineda-Krch, M. (2007). Constraints and reinforcement on adaptation under climate change. Selection of genetically correlated traits. Biological Conservation, 137(4), 599-609.
Hongtrakul, V., Huestis, G. M., & Knapp, S. J. (1997). Amplified fragment length polymorphisms as a tool for DNA fingerprinting sunflower germplasm. Genetic diversity among oilseed inbred lines. TAG Theoretical and Applied Genetics, 95(3), 400-407.
Jensen, J. S., Olrik, D. C., Siegismund, H. R., & Lowe, A. J. (2003). Population genetics and spatial autocorrelation in an unmanaged stand of Quercus petraea in Denmark. Scandinavian Journal of Forest Research, 18(4), 295-304.
Katicic Bogdan, I., Kajba, D., Satovic, Z., Schüler, S., & Bogdan, S. (2018). Genetic diversity of Pedunculate oak (Quercus robur L.) in clonal seed orchards in Croatia, assessed by nuclear and chloroplast microsatellites. South-East European Forestry, 9(1), 29-46.
Kremer, A., & Petit, R. J. (1993). Gene diversity in natural populations of oak species. Annals of Forest Science, 50(Suppl. 1), 186-202.
Le Hir, H., Nott, A., & Moore, M. J. (2003). How introns influence and enhance eukaryotic gene expression. Trends in Biochemical Sciences, 28(4), 215-220.
Leroy, T., Roux, C., Villate, L., Bodénes, C., Romiguier, J., Paiva, J. A. P., Dossat, C., Aury, J.-M., Plomion, C., & Kremer, A. (2017). Extensive recent secondary contacts between four European white oak species. New Phytologist, 214, 865-878.
Li, J. H., Jin, Z. X., Lou, W. Y., & Li, J. M. (2008). Genetic diversity of Lithocar-pus harlandii populations in three forest communities with different succession stage. Frontiers of Forestry in China, 3(1), 106-111.
Li, S.-C., Tang, P., & Lin, W.-C. (2007). Intronic microRNA. Discovery and biological implications. DNA and Cell Biology, 26(4), 195-207.
Lind-Riehl, J., & Gailing, O. (2015). Fine-scale spatial genetic structure of two red oak species, Quercus rubra and Quercus ellipsoidalis. Plant Systematics and Evolution, 301(6), 1601-1612.
McVay, J. D., Hipp, A. L., & Manos, P. S. (2017) A genetic legacy of introgression confounds phylogeny and biogeography in oaks. Proceedings of the Royal Society B, 284, 20170300.
Morello, L., & Breviario, D. (2008). Plant spliceosomal introns: Not only cut and paste. Current Genomics, 9(4), 227-238.
Neophytou, C., Aravanopoulos, F., Fink, S., & Dounavi, A. (2010). 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 Ecology and Management, 259(10), 2026-2035.
Nowak, D. J., Crane, D. E., & Stevens, J. C. (2006). Air pollution removal by urban trees and shrubs in the United States. Urban Forestry and Urban Greening,
4, 115-123.
Nowak, D. J., McHale, P. J., Ibarra, M., Crane, D. E., Stevens, J. C., & Luley, C. J. (1998). Modeling the effects of urban vegetation on air pollution. In: Gryning, S.-E., & Chaumerliac, N. (Eds.). Air pollution modeling and its application XII. Plenum Press, New York. Pp. 399-407.
Onyshchenko, V. A. (2013). Lisova roslynnist' ur. Holosiyivs'kyy lis (m. Kyiv) [Forest vegetation of Holosiyivsky wood (Kyiv)]. Biolohichni Systemy, 2013, 5(1), 93-115.
Onyshchenko, V. A. (2015). Vikovi duby Holosiyivs'koho lisu [Old oaks of Holosiyivsky wood]. Zapovidna Sprava, 21, 19-23 (in Ukrainian).
Oyama, K., Rami'rez-Toro, W., Peñaloza-Ramirez, J. M., Pedraza, A. E. P., Torres-Miranda, C. A., Ruiz-Sánchez, E., & González-Rodríguez, A. (2018). High genetic diversity and connectivity among populations of Quercus candicans, Quercus crassifolia, and Quercus castanea in a heterogeneous landscape in Mexico. Tropical Conservation Science, 11, 1-14.
Peakall, R., & Smouse, P. (2006). GenAlEx 6: Genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes, 6(1), 288-295.
Petit, R. J., Csaikl, U. M., Bordács, S., Burg, K., Coart, E., Cottrell, J., Dam, B., Deans, J. D., Dumolin-Lapegue, S., Fineschi, S., Finkeldey, R., Gillies, A., Glaz, I., Goicoechea, P. G., Jensen, J. S., König, A. O., Lowe, A. J., Madsen,
5. F., Mátyás, G., Munro, R. C., Olalde, M., Pemonge, M.-H., Popescu, F., Slade, D., Tabbener, H., Taurchini, D., de Vries, S. G. M., Ziegenhagen, B., & Kremer, A. (2002). Chloroplast DNA variation in European white oaks. Phylogeography and patterns of diversity based on data from over 2600 populations. Forest Ecology and Management, 156(1-3), 5-26.
Pirko, Y. V. (2011). Issledovaniye geneticheskoy izmenchivosti raznykh vidov rasteniy s pomoshch'yu analiza polimorfizma intronov genov ß-tubulina [Studying of genetic diversity different species of plants by analyzing polymorphism of introns of ß-tubulin genes]. Industrial Botany, 11, 152-156 (in Ukrainian).
Plomion, C., Aury, J. M., Amselem, J., Alaeitabar, T., Barbe, V., Belser, C., Berges, H., Bodénes, C., Boudet, N., Boury, C., Canaguier, A., Couloux, A., Da Silva, C., Duplessis, S., Ehrenmann, F., Estrada-Mairey, B., Fouteau, S., Francillonne, N., Gaspin, C., Guichard, C., Klopp, C., Labadie, K., Lalanne, C., Le Clainche, I., Leplé, J. C., Le Provost, G., Leroy, T., Lesur, I., Marlin, F., Mercier, J., Michotey, C., Murat, F., Salin, F., Steinbach, D., Faivre-Ram-pant, P., Wincker, P., Salse, J., Quesneville, H., & Kremer, A. (2016). Decoding the oak genome: Public release of sequence data, assembly, annotation and publication strategies. Molecular Ecology Resources, 16(1), 254-265.
Plomion, C., Aury, J. M., Amselem, J., Leroy, T., Murat, F., Duplessis, S., Faye, S., Francillonne, N., Labadie, K., Le Provost, G., Lesur, I., Bartolomé, J., Faivre-Rampant, P., Kohler, A., Leplé, J. C., Chantret, N., Chen, J., Diévart, A., Alaeitabar, T., Barbe, V., Belser, C., Berges, H., Bodénes, C., Bogeat-Triboulot, M. B., Bouffaud, M. L., Brachi, B., Chancerel, E., Cohen, D., Couloux, A., Da Silva, C., Dossat, C., Ehrenmann, F., Gaspin, C., Grima-Pettenati, J., Guichoux, E., Hecker, A., Herrmann, S., Hugueney, P., Hummel, I., Klopp, C., Lalanne, C., Lascoux, M., Lasserre, E., Lemainque, A., Desprez-Loustau, M. L., Luyten, I., Madoui, M. A., Mangenot, S., Marchal C., Maumus, F., Mercier, J., Michotey, C., Panaud, O., Picault, N., Rouhier, N., Rué, O., Rustenholz, C., Salin, F., Soler, M., Tarkka, M., Velt, A., Zanne, A E., Martin, F., Wincker, P., Quesneville, H., Kremer, A., & Salse, J. (2018). Oak genome reveals facets of long lifespan. Nature Plants, 4(7), 440-452.
Pospísková, M., & Dostálek, J. (2010). Quercus petraea populations: A case study from the Kñvoklátsko Protected Landscape Area (Czech Republic). Biodiversity Research and Conservation, 13(1), 37-42.
Rabokon, A. N., Demkovych, A. Y., Pirko, Y. V., & Blume, Y. B. (2015). Polimor-fizm dliny intronov genov beta-tubulina kak effektivnyy instrument genotipi-rovaniya rasteniy [Intron length polymorphism of ß-tubulin gene as an effective tool for genotyping of plants]. Molecular and Applied Genetics (Mimsk), 19, 35-44 (in Russian).
Rahman, M. H., Jaquish, B., & Khasa, P. D. (2000). Optimization of PCR protocol in microsatellite analysis with silver and SYBR® stains. Plant Molecular Biology Reporter, 18(4), 339-348.
Rose, A. B. (2002). Requirements for intron-mediated enhancement of gene expression in Arabidopsis. RNA (New York, N.Y.): RNA Society, Cold Spring Harbor Laboratory Press, 8(11), 1444-1453.
Semerikov, L. F. (1976). Izmenchivost' duba chereshchatogo (Quercus robur L.) na vostochnoy granites areala [Variability of the oak quiver (Quercus robur L.) on the eastern border ofthe range]. Ecology, 5, 13-21 (in Russian).
Sork, V. L., & Smouse, P. E. (2006). Genetic analysis of landscape connectivity in tree populations. Landscape Ecology, 21, 821-836.
Sork, V. L., Davis, F. W., Smouse, P. E., Apsit, V. J., Dyer, R. J., Fernandez, J. F., & Kuhn, B. (2002). Pollen movement in declining populations of California valley oak, Quercus lobata: Where have all the fathers gone? Molecular Ecology, 11(9), 1657-1668.
Vasylyuk, O., Kostyushyn, V., Norenko, K., Plyha, A., Prekrasna, Y. E., Kolomy-tsev, H., & Fatikova, M. (2012). Pryrodno-zapovidnyy fond Kyyivs'koyi oblasti [Natural reserve fund of the Kiev region]. National Ecological Center of Ukraine, Kyiv (in Ukrainian).
Wenting, W., Yi, R., & Hengyu, Z. (2012). Investigation on temperature dropping effect of urban green space in summer in Hangzhou. Energy Procedia, 14, 217-222.
Wolch, J. R., Byrn, J., & Newell, J. P. (2014). Urban green space, public health, and environmental justice: The challenge of making cities 'just green enough'. Landscape and Urban Planning, 125, 234-244.
Young, A. G., & Pickup, M. (2010). Low S allele numbers limit mate availability, reduce seed set and skew fitness in small populations of a self-incompatible plant. Journal of Applied Ecology, 47, 541-548.
