Identification of SNP markers responsible for drought tolerance in sessile oak populations: results of basic research for sustainable oak management

Benke Attila; Köbölkuti Zoltán Attila; Cseke Klára; Borovics Attila; Tóth Endre György

Bulletin of Forestry Science / Volume 12 / Issue 2 / Pages 77-90
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Attila Benke, Attila Zoltán Köbölkuti, Klára Cseke, Attila Borovics & György Endre Tóth

Correspondence

Correspondence: Benke Attila

Postal address: H-9600 Sárvár, Várkerület 30/A.

e-mail: benke.attila[at]uni-sopron.hu

Abstract

The genetic information concerning the adaptation of main tree species to different environmental conditions could provide considerable knowledge to determine forest management responses to climate change. In the present study, we carried out a parallel mapping of SNP markers revealed in 18 Middle- and Southeast-European sessile oak [Quercus petraea (Matt.) Liebl.] populations and EST sequences of stress-responsive loci downloaded from an EST repository to determine the group of those SNPs, which are associated with the genetic background of adaptation processes in oaks. Regression analysis revealed 16 significant correlations between four outlier SNP loci representing high F_ST values and 94 climatic variables. All variables with significant correlations were found to be related to precipitation or temperature. The stress-responsive loci identified in this study may serve as a basis for common research to support future sustainable management of sessile oak in Hungary.

Keywords: sessile oak, SNP markers, drought selection, genotype-environment association (GEA)

References55

1.	Baird N.A., Etter P.D., Atwood T.S., Currey M.C., Shiver A.L., Lewis Z.A., Selker E.U., Cresko W.A. & Johnson E.A. 2008: Rapid SNP Discovery and Genetic Mapping Using Sequenced RAD Markers. PLoS ONE 3(10): e3376. DOI: 10.1371/journal.pone.0003376
2.	Batley J. & Edwards D. 2007: SNP Applications in Plants. In: Oraguzie N.C., Rikkerink E.H.A., Gardiner S.E. & De Silva H.N. (eds.): Association Mapping in Plants. Springer, New York, NY, USA. 95–102., DOI: 10.1007/978-0-387-36011-9_6
3.	Beckage B., Osborne B., Gavin D.G., Pucko C., Siccama T. & Perkins T. 2008: A rapid upward shift of a forest ecotone during 40 years of warming in the Green Mountains of Vermont. Proceedings of the National Academy of Sciences 105: 4197. DOI: 10.1073/pnas.0708921105
4.	Blanc‑Jolivet C., Bakhtina S., Yanbaev R., Yanbaev Y., Mader M., Guichoux E. & Degen B. 2020: Development of new SNPs loci on Quercus robur and Quercus petraea for genetic studies covering the whole species’ distribution range. Conservation Genetics Resources 12: 597–600. DOI: 10.1007/s12686-020-01141-z
5.	Bordács S., Popescu F., Slade D., Csaikl U.M., Lesur I., Borovics A., Kézdy P., König A.O., Gömöry D., Brewer S., Burg K. & Petit R.J. 2002: Chloroplast DNA variation of white oaks in northern Balkans and in the Carpathian Basin. Forest Ecology and Management 156(1-3): 197-209. DOI: 10.1016/S0378-1127(01)00643-0
6.	Borovics A. & Mátyás Cs. 2013: Decline of genetic diversity of sessile oak at the retracting (xeric) limits. Annals of Forest Science 70: 835–844. DOI: 10.1007/s13595-013-0324-6
7.	Bradbury P.J., Zhang Z., Kroon D.E., Casstevens T.M., Ramdoss Y. & Buckler E.S. 2007: TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23: 2633–2635. DOI: 10.1093/bioinformatics/btm308
8.	Catchen J., Hohenlohe P.A., Bassham S., Amores A. & Cresko W.A. 2013: Stacks: an analysis tool set for population genomics. Molecular Ecology 22: 3124–3140.
9.	Chakraborty D., Móricz N., Rasztovits E., Dobor L. & Schueler S. 2021: Provisioning forest and conservation science with high‑resolution maps of potential distribution of major European tree species under climate change. Annals of Forest Science 78: 26. DOI: 10.1007/s13595-021-01029-4
10.	Czúcz B., Gálhidy L. & Mátyás Cs. 2013: A bükk és a kocsánytalan tölgy elterjedésének szárazsági határa. Erdészettudományi Közlemények, 3(1): 39-53. full text
11.	Excoffier L., Hofer T. & Foll M. 2009: Detecting loci under selection in a hierarchically structured population. Heredity 103: 285–298. DOI: 10.1038/hdy.2009.74
12.	Foll M. & Gaggiotti O. 2008: A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective. Genetics 180: 977–993. DOI: 10.1534/genetics.108.092221
13.	Frichot E., Schoville S.D., Bouchard G. & François O. 2013: Testing for associations between loci and environmental gradients using latent factor mixed models. Molecular Biology and Evolution 30: 1687–1699. DOI: 10.1093/molbev/mst063
14.	García C., Guichoux E. & Hampe A. 2018: A comparative analysis between SNPs and SSRs to investigate genetic variation in a juniper species (Juniperus phoenicea ssp. turbinata). Tree Genetics & Genomes 14: 87. DOI: 10.1007/s11295-018-1301-x
15.	Gencsi L. & Vancsura R. 1997: Dendrológia. Mezőgazda Kiadó, Budapest, 240–246.
16.	Goudet J. 2005: Hierfstat, a package for R to compute and test hierarchical F‐statistics. Molecular Ecology Notes 5: 184–186. DOI: 10.1111/j.1471-8286.2004.00828.x.
17.	Hamrick J.L., Godt M.J.W. & Sherman-Broyles, S.L. 1992: Factors influencing levels of genetic diversity in woody plant species. New Forests 6: 95–124.
18.	Hijmans R.J., Cameron S.E., Parra J.L., Jones P.G. & Jarvis A. 2005: Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965–1978. DOI: 10.1002/joc.1276
19.	Járó Z. 1966: A fafajok hazai elterjedése. In: Babos I., Horváthné Proszt S., Járó Z., Király L., Szodfridt I. & Tóth B. 1966: Erdészeti termőhelyfeltárás és térképezés. Akadémiai Kiadó, Budapest, 136 p.
20.	Járó Z. 1972: Az erdészeti termőhelyértékelés rendszere. In: Danszky I. (ed.) 1972: Erdőművelés - Irányelvek, eljárások, technológiák I. – Erdőfelújítás, erdőtelepítés, fásítás. Mezőgazdasági Könyvkiadó Vállalat, Budapest, 53–71.
21.	Jombart T. & Ahmed I. 2011: adegenet 1.3-1: new tools for the analysis of genome-wide SNP data. Bioinformatics 27: 3070–3071. DOI: 10.1093/bioinformatics/btr521
22.	Kamvar Z.N., Tabima J.F. & Grünwald N.J. 2014: Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ 2: e281. DOI: 10.7717/peerj.281
23.	Keresztesi B. 1971: Magyar erdők. Akadémiai Kiadó, Budapest, 79 p.
24.	Konar A., Choudhury O., Bullis R., Fiedler L., Kruser J.M., Stephens M.T., Gailing O., Schlarbaum S., Coggeshall M.V., Staton M.E., Carlson J.E., Emrich S. & Romero-Severson J. 2017: High-quality genetic mapping with ddRADseq in the non-model tree Quercus rubra. BMC Genomics (2017) 18: 417. DOI: 10.1186/s12864-017-3765-8
25.	Lê S., Josse J. & Husson F. 2008: FactoMineR: an R package for multivariate analysis. Journal of Statistical Software 25(1): 1–18. DOI: 10.18637/jss.v025.i01
26.	Li H. 2013: Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv preprint arXiv:1303.3997. DOI: 10.48550/arXiv.1303.3997
27.	Luu K., Bazin E. & Blum M.G. 2017: pcadapt: an R package to perform genome scans for selection based on principal component analysis. Molecular Ecology Resources 17: 67–77. DOI: 10.1111/1755-0998.12592
28.	Machar I., Vlckova V., Bucek A., Vozenilek V., Salek L. & Jerabkova L. 2017: Modelling of Climate Conditions in Forest Vegetation Zones as a Support Tool for Forest Management Strategy in European Beech Dominated Forests. Forests 8(3): 82. DOI: 10.3390/f8030082
29.	Majer A. 1972: Célállományok jellemzése. In: Danszky I. (ed.) 1972: Erdőművelés - Irányelvek, eljárások, technológiák I. – Erdőfelújítás, erdőtelepítés, fásítás. Mezőgazdasági Könyvkiadó Vállalat, Budapest, 102–103.
30.	Marees A.T., de Kluiver H., Stringer S., Vorspan F., Curis E., Marie‐Claire C. & Derks E.M. 2018: A tutorial on conducting genome‐wide association studies: Quality control and statistical analysis. International Journal of Methods in Psychiatric Research 27: e1608. DOI: 10.1002/mpr.1608
31.	Masoudi-Nejad A., Tonomura K., Kawashima S., Moriya Y., Suzuki M., Itoh M. & Goto S. 2006: EGassembler: online bioinformatics service for large-scale processing, clustering and assembling ESTs and genomic DNA fragments. Nucleic Acids Research 34: W459-W462. DOI: 10.1093/nar/gkl066
32.	Mátyás Cs. 1999: Molekuláris markerek alkalmazása az erdészeti növények nemesítésében. In: Hajósné Novák M. (ed.): Genetikai variabilitás a növénynemesítésben. Mezőgazda Kiadó, Budapest, 65-78.
33.	Móricz N., Rasztovits E., Gálos B., Berki I., Eredics A. & Loibl W. 2013: Modelling the Potential Distribution of Three Climate Zonal Tree Species for Present and Future Climate in Hungary. Acta Silvatica et Lignaria Hungarica 9: 85–96. DOI: 10.2478/aslh-2013-0007 full text
34.	Nagy K. (ed.) 2021: Nemzeti szisztematikus erdőleltár. Nemzeti Földügyi Központ, Erdészeti Főosztály, Budapest ISBN 978-615-6287-00-7
35.	Nazareno A.G., Bemmels J.B., Dick C.W, & Lohmann L.G. 2017: Minimum sample sizes for population genetics: an empirical study from an Amazonian plant species. Molecular Ecology Resources 17(6): 1136-1147. DOI: 10.1111/1755-0998.12654
36.	Nei M. 1973: Analysis of gene diversity in subdivided populations. Proceedings of the National Academy of Sciences 70:3321-3. DOI: 10.1073/pnas.70.12.3321
37.	Petit R.J., Brewer S., Bordács S., Burg K., Cheddadi R., Coart E., Cottrell J., Csaikl U.M., Deans J.D., Fineschi S., Finkeldey R., Glaz I., Goicoechea P.G., Jensen J.S., König A.O., Lowe A.J., Madsen S.F., Mátyás G., Munro R.C., Popescu F., Slade D., Tabbener H., van Dam B., Ziegenhagen B., de Beaulieu J.L. & Kremer A. 2002: Identification of refugia and postglacial colonisation routes of European white oaks based on chloroplast DNA and fossil pollen evidence. Forest Ecology and Management 156(1-3): 49-74. DOI: 10.1016/S0378-1127(01)00634-X
38.	Plomion C., Aury J.M., Amselem J., Leroy T., Murat F., Duplessis S. & Lesur I. 2018: Oak genome reveals facets of long lifespan. Nature Plants 4: 440–452. DOI: 10.1111/1755-0998.12425
39.	R Core Team 2021: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
40.	Rafalski J. A. 2002: Novel genetic mapping tools in plants: SNPs and LD-based approaches. Plant Science 162: 329–333. DOI: 10.1016/S0168-9452(01)00587-8
41.	Raj A., Stephens M. & Pritchard J.K. 2014: fastSTRUCTURE: variational inference of population structure in large SNP data sets. Genetics 197: 573–589. DOI: 10.1093/genetics/197.2.NP
42.	Rasztovits E., Móricz N., Berki I., Pötzelsberger E. & Mátyás Cs. 2012: Evaluating the performance of stochastic distribution models for European beech at low-elevation xeric limits. Időjárás 116(3): 173–194.
43.	Robinson J.T., Thorvaldsdóttir H., Winckler W., Guttman M., Lander E.S., Getz G. & Mesirov J.P. 2011: Integrative genomics viewer. Nature Biotechnology 29: 24–26. DOI: 10.1038/nbt.1754
44.	Rochette N.C., Rivera‐Colón A.G. & Catchen J.M. 2019: Stacks 2: Analytical methods for paired‐end sequencing improve RADseq‐based population genomics. Molecular Ecology 28: 4737–4754. DOI: 10.1111/mec.15253
45.	Rubel F., Brugger K., Haslinger K. & Auer I. 2017: The climate of the European Alps: Shift of very high resolution Köppen-Geiger climate zones 1800–2100. Meteorologische Zeitschrift 26(2): 115–125.
46.	Shastry B.S. 2009: SNPs: Impact on Gene Function and Phenotype. In: Komar A.A. (ed.): Single Nucleotide Polymorphisms. Methods in Molecular Biology. Humana Totowa, NJ, 3–4. eBook ISBN: 978-1-60327-411-1
47.	Slade D., Kvorc Z.S., Ballian D., Gracan J. & Papes D. 2008: The Chloroplast DNA Polymorphisms of White Oaks of Section Quercus in The Central Balkans. Silvae Genetica 57(1-6): 227-234. DOI: 10.1515/sg-2008-0035
48.	Stojanović D.B., Matović B., Orlović S., Kržič A., Trudić B., Galić Z., Stojnić S. & Pekeč S. 2014: Future of the Main Important Forest Tree Species in Serbia from the Climate Change Perspective. South-east European Forestry 5(2): 117–124. DOI: 10.15177/seefor.14-16
49.	Title P.O. & Bemmels J.B. 2018: ENVIREM: an expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling. Ecography 41: 291–307. DOI: 10.1111/ecog.02880
50.	Tóth E.G., Köbölkuti Z.A., Cseke K., Kámpel J.D., Takács R., Tomov V.T., Ábrán P., Stojnic S., Vastag E., Mataruga M., Daničić V., Tahirukaj E., Zhelev P., Orlovic S., Benke A. & Borovics A. 2021: A genomic dataset of singlenucleotide polymorphisms generated by ddRAD tag sequencing in Q. petraea (Matt.) Liebl. populations from Central-Eastern Europe and Balkan Peninsula. Annals of Forest Science 78: 43. DOI: 10.1007/s13595-021-01051-6
51.	Ujváriné Jármay É. 1988: A nemesítési kutatásokról. Az Erdő 37(10): 436–440. full text
52.	Winter D.J. 2017: rentrez: An R package for the NCBI eUtils API. The R Journal 9(2): 520–526. ISSN 2073-4859
53.	Wu T.D. & Watanabe C.K. 2005: GMAP: a genomic mapping and alignment program for mRNA and EST sequences. Bioinformatics 21: 1859–1875. DOI: 10.1093/bioinformatics/bti310
54.	Xiong S., Hao Y., Rao S., Huang W., Hu B. & Wang Y. 2009: Effects of cutoff thresholds for minor allele frequencies on HapMap resolution: A real dataset-based evaluation of the Chinese Han and Tibetan populations. Chinese Science Bulletin 54: 2069–2075. DOI: 10.1007/s11434-009-0302-4
55.	Zanetto A. & Kremer A. 1995: Geographical structure of gene diversity in Quercus petraea (Matt.) Liebl. I. Monolocus patterns of variation. Heredity 75(5): 506–517. DOI: 10.1038/hdy.1995.167

Baird N.A., Etter P.D., Atwood T.S., Currey M.C., Shiver A.L., Lewis Z.A., Selker E.U., Cresko W.A. & Johnson E.A. 2008: Rapid SNP Discovery and Genetic Mapping Using Sequenced RAD Markers. PLoS ONE 3(10): e3376. DOI: 10.1371/journal.pone.0003376

Batley J. & Edwards D. 2007: SNP Applications in Plants. In: Oraguzie N.C., Rikkerink E.H.A., Gardiner S.E. & De Silva H.N. (eds.): Association Mapping in Plants. Springer, New York, NY, USA. 95–102., DOI: 10.1007/978-0-387-36011-9_6

Beckage B., Osborne B., Gavin D.G., Pucko C., Siccama T. & Perkins T. 2008: A rapid upward shift of a forest ecotone during 40 years of warming in the Green Mountains of Vermont. Proceedings of the National Academy of Sciences 105: 4197. DOI: 10.1073/pnas.0708921105

Blanc‑Jolivet C., Bakhtina S., Yanbaev R., Yanbaev Y., Mader M., Guichoux E. & Degen B. 2020: Development of new SNPs loci on Quercus robur and Quercus petraea for genetic studies covering the whole species’ distribution range. Conservation Genetics Resources 12: 597–600. DOI: 10.1007/s12686-020-01141-z

Bordács S., Popescu F., Slade D., Csaikl U.M., Lesur I., Borovics A., Kézdy P., König A.O., Gömöry D., Brewer S., Burg K. & Petit R.J. 2002: Chloroplast DNA variation of white oaks in northern Balkans and in the Carpathian Basin. Forest Ecology and Management 156(1-3): 197-209. DOI: 10.1016/S0378-1127(01)00643-0

Borovics A. & Mátyás Cs. 2013: Decline of genetic diversity of sessile oak at the retracting (xeric) limits. Annals of Forest Science 70: 835–844. DOI: 10.1007/s13595-013-0324-6

Bradbury P.J., Zhang Z., Kroon D.E., Casstevens T.M., Ramdoss Y. & Buckler E.S. 2007: TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23: 2633–2635. DOI: 10.1093/bioinformatics/btm308

Catchen J., Hohenlohe P.A., Bassham S., Amores A. & Cresko W.A. 2013: Stacks: an analysis tool set for population genomics. Molecular Ecology 22: 3124–3140.

Chakraborty D., Móricz N., Rasztovits E., Dobor L. & Schueler S. 2021: Provisioning forest and conservation science with high‑resolution maps of potential distribution of major European tree species under climate change. Annals of Forest Science 78: 26. DOI: 10.1007/s13595-021-01029-4

Czúcz B., Gálhidy L. & Mátyás Cs. 2013: A bükk és a kocsánytalan tölgy elterjedésének szárazsági határa. Erdészettudományi Közlemények, 3(1): 39-53. full text

Excoffier L., Hofer T. & Foll M. 2009: Detecting loci under selection in a hierarchically structured population. Heredity 103: 285–298. DOI: 10.1038/hdy.2009.74

Foll M. & Gaggiotti O. 2008: A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective. Genetics 180: 977–993. DOI: 10.1534/genetics.108.092221

Frichot E., Schoville S.D., Bouchard G. & François O. 2013: Testing for associations between loci and environmental gradients using latent factor mixed models. Molecular Biology and Evolution 30: 1687–1699. DOI: 10.1093/molbev/mst063

García C., Guichoux E. & Hampe A. 2018: A comparative analysis between SNPs and SSRs to investigate genetic variation in a juniper species (Juniperus phoenicea ssp. turbinata). Tree Genetics & Genomes 14: 87. DOI: 10.1007/s11295-018-1301-x

Gencsi L. & Vancsura R. 1997: Dendrológia. Mezőgazda Kiadó, Budapest, 240–246.

Goudet J. 2005: Hierfstat, a package for R to compute and test hierarchical F‐statistics. Molecular Ecology Notes 5: 184–186. DOI: 10.1111/j.1471-8286.2004.00828.x.

Hamrick J.L., Godt M.J.W. & Sherman-Broyles, S.L. 1992: Factors influencing levels of genetic diversity in woody plant species. New Forests 6: 95–124.

Hijmans R.J., Cameron S.E., Parra J.L., Jones P.G. & Jarvis A. 2005: Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965–1978. DOI: 10.1002/joc.1276

Járó Z. 1966: A fafajok hazai elterjedése. In: Babos I., Horváthné Proszt S., Járó Z., Király L., Szodfridt I. & Tóth B. 1966: Erdészeti termőhelyfeltárás és térképezés. Akadémiai Kiadó, Budapest, 136 p.

Járó Z. 1972: Az erdészeti termőhelyértékelés rendszere. In: Danszky I. (ed.) 1972: Erdőművelés - Irányelvek, eljárások, technológiák I. – Erdőfelújítás, erdőtelepítés, fásítás. Mezőgazdasági Könyvkiadó Vállalat, Budapest, 53–71.

Jombart T. & Ahmed I. 2011: adegenet 1.3-1: new tools for the analysis of genome-wide SNP data. Bioinformatics 27: 3070–3071. DOI: 10.1093/bioinformatics/btr521

Kamvar Z.N., Tabima J.F. & Grünwald N.J. 2014: Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ 2: e281. DOI: 10.7717/peerj.281

Keresztesi B. 1971: Magyar erdők. Akadémiai Kiadó, Budapest, 79 p.

Konar A., Choudhury O., Bullis R., Fiedler L., Kruser J.M., Stephens M.T., Gailing O., Schlarbaum S., Coggeshall M.V., Staton M.E., Carlson J.E., Emrich S. & Romero-Severson J. 2017: High-quality genetic mapping with ddRADseq in the non-model tree Quercus rubra. BMC Genomics (2017) 18: 417. DOI: 10.1186/s12864-017-3765-8

Lê S., Josse J. & Husson F. 2008: FactoMineR: an R package for multivariate analysis. Journal of Statistical Software 25(1): 1–18. DOI: 10.18637/jss.v025.i01

Li H. 2013: Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv preprint arXiv:1303.3997. DOI: 10.48550/arXiv.1303.3997

Luu K., Bazin E. & Blum M.G. 2017: pcadapt: an R package to perform genome scans for selection based on principal component analysis. Molecular Ecology Resources 17: 67–77. DOI: 10.1111/1755-0998.12592

Machar I., Vlckova V., Bucek A., Vozenilek V., Salek L. & Jerabkova L. 2017: Modelling of Climate Conditions in Forest Vegetation Zones as a Support Tool for Forest Management Strategy in European Beech Dominated Forests. Forests 8(3): 82. DOI: 10.3390/f8030082

Majer A. 1972: Célállományok jellemzése. In: Danszky I. (ed.) 1972: Erdőművelés - Irányelvek, eljárások, technológiák I. – Erdőfelújítás, erdőtelepítés, fásítás. Mezőgazdasági Könyvkiadó Vállalat, Budapest, 102–103.

Marees A.T., de Kluiver H., Stringer S., Vorspan F., Curis E., Marie‐Claire C. & Derks E.M. 2018: A tutorial on conducting genome‐wide association studies: Quality control and statistical analysis. International Journal of Methods in Psychiatric Research 27: e1608. DOI: 10.1002/mpr.1608

Masoudi-Nejad A., Tonomura K., Kawashima S., Moriya Y., Suzuki M., Itoh M. & Goto S. 2006: EGassembler: online bioinformatics service for large-scale processing, clustering and assembling ESTs and genomic DNA fragments. Nucleic Acids Research 34: W459-W462. DOI: 10.1093/nar/gkl066

Mátyás Cs. 1999: Molekuláris markerek alkalmazása az erdészeti növények nemesítésében. In: Hajósné Novák M. (ed.): Genetikai variabilitás a növénynemesítésben. Mezőgazda Kiadó, Budapest, 65-78.

Móricz N., Rasztovits E., Gálos B., Berki I., Eredics A. & Loibl W. 2013: Modelling the Potential Distribution of Three Climate Zonal Tree Species for Present and Future Climate in Hungary. Acta Silvatica et Lignaria Hungarica 9: 85–96. DOI: 10.2478/aslh-2013-0007 full text

Nagy K. (ed.) 2021: Nemzeti szisztematikus erdőleltár. Nemzeti Földügyi Központ, Erdészeti Főosztály, Budapest ISBN 978-615-6287-00-7

Nazareno A.G., Bemmels J.B., Dick C.W, & Lohmann L.G. 2017: Minimum sample sizes for population genetics: an empirical study from an Amazonian plant species. Molecular Ecology Resources 17(6): 1136-1147. DOI: 10.1111/1755-0998.12654

Nei M. 1973: Analysis of gene diversity in subdivided populations. Proceedings of the National Academy of Sciences 70:3321-3. DOI: 10.1073/pnas.70.12.3321

Petit R.J., Brewer S., Bordács S., Burg K., Cheddadi R., Coart E., Cottrell J., Csaikl U.M., Deans J.D., Fineschi S., Finkeldey R., Glaz I., Goicoechea P.G., Jensen J.S., König A.O., Lowe A.J., Madsen S.F., Mátyás G., Munro R.C., Popescu F., Slade D., Tabbener H., van Dam B., Ziegenhagen B., de Beaulieu J.L. & Kremer A. 2002: Identification of refugia and postglacial colonisation routes of European white oaks based on chloroplast DNA and fossil pollen evidence. Forest Ecology and Management 156(1-3): 49-74. DOI: 10.1016/S0378-1127(01)00634-X

Plomion C., Aury J.M., Amselem J., Leroy T., Murat F., Duplessis S. & Lesur I. 2018: Oak genome reveals facets of long lifespan. Nature Plants 4: 440–452. DOI: 10.1111/1755-0998.12425

R Core Team 2021: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

Rafalski J. A. 2002: Novel genetic mapping tools in plants: SNPs and LD-based approaches. Plant Science 162: 329–333. DOI: 10.1016/S0168-9452(01)00587-8

Raj A., Stephens M. & Pritchard J.K. 2014: fastSTRUCTURE: variational inference of population structure in large SNP data sets. Genetics 197: 573–589. DOI: 10.1093/genetics/197.2.NP

Rasztovits E., Móricz N., Berki I., Pötzelsberger E. & Mátyás Cs. 2012: Evaluating the performance of stochastic distribution models for European beech at low-elevation xeric limits. Időjárás 116(3): 173–194.

Robinson J.T., Thorvaldsdóttir H., Winckler W., Guttman M., Lander E.S., Getz G. & Mesirov J.P. 2011: Integrative genomics viewer. Nature Biotechnology 29: 24–26. DOI: 10.1038/nbt.1754

Rochette N.C., Rivera‐Colón A.G. & Catchen J.M. 2019: Stacks 2: Analytical methods for paired‐end sequencing improve RADseq‐based population genomics. Molecular Ecology 28: 4737–4754. DOI: 10.1111/mec.15253

Rubel F., Brugger K., Haslinger K. & Auer I. 2017: The climate of the European Alps: Shift of very high resolution Köppen-Geiger climate zones 1800–2100. Meteorologische Zeitschrift 26(2): 115–125.

Shastry B.S. 2009: SNPs: Impact on Gene Function and Phenotype. In: Komar A.A. (ed.): Single Nucleotide Polymorphisms. Methods in Molecular Biology. Humana Totowa, NJ, 3–4. eBook ISBN: 978-1-60327-411-1

Slade D., Kvorc Z.S., Ballian D., Gracan J. & Papes D. 2008: The Chloroplast DNA Polymorphisms of White Oaks of Section Quercus in The Central Balkans. Silvae Genetica 57(1-6): 227-234. DOI: 10.1515/sg-2008-0035

Stojanović D.B., Matović B., Orlović S., Kržič A., Trudić B., Galić Z., Stojnić S. & Pekeč S. 2014: Future of the Main Important Forest Tree Species in Serbia from the Climate Change Perspective. South-east European Forestry 5(2): 117–124. DOI: 10.15177/seefor.14-16

Title P.O. & Bemmels J.B. 2018: ENVIREM: an expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling. Ecography 41: 291–307. DOI: 10.1111/ecog.02880

Tóth E.G., Köbölkuti Z.A., Cseke K., Kámpel J.D., Takács R., Tomov V.T., Ábrán P., Stojnic S., Vastag E., Mataruga M., Daničić V., Tahirukaj E., Zhelev P., Orlovic S., Benke A. & Borovics A. 2021: A genomic dataset of singlenucleotide polymorphisms generated by ddRAD tag sequencing in Q. petraea (Matt.) Liebl. populations from Central-Eastern Europe and Balkan Peninsula. Annals of Forest Science 78: 43. DOI: 10.1007/s13595-021-01051-6

Ujváriné Jármay É. 1988: A nemesítési kutatásokról. Az Erdő 37(10): 436–440. full text

Winter D.J. 2017: rentrez: An R package for the NCBI eUtils API. The R Journal 9(2): 520–526. ISSN 2073-4859

Wu T.D. & Watanabe C.K. 2005: GMAP: a genomic mapping and alignment program for mRNA and EST sequences. Bioinformatics 21: 1859–1875. DOI: 10.1093/bioinformatics/bti310

Xiong S., Hao Y., Rao S., Huang W., Hu B. & Wang Y. 2009: Effects of cutoff thresholds for minor allele frequencies on HapMap resolution: A real dataset-based evaluation of the Chinese Han and Tibetan populations. Chinese Science Bulletin 54: 2069–2075. DOI: 10.1007/s11434-009-0302-4

Zanetto A. & Kremer A. 1995: Geographical structure of gene diversity in Quercus petraea (Matt.) Liebl. I. Monolocus patterns of variation. Heredity 75(5): 506–517. DOI: 10.1038/hdy.1995.167

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Benke, A., Köbölkuti, Z. A., Cseke, K., Borovics, A. & Tóth, E. Gy. (2022): Identification of SNP markers responsible for drought tolerance in sessile oak populations: results of basic research for sustainable oak management. Bulletin of Forestry Science, 12(2): 77-90. (in Hungarian) DOI: 10.17164/EK.2022.05

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Volume 12, Issue 2
Pages: 77-90

DOI: 10.17164/EK.2022.05

First published:
26 January 2023

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by this authors

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9.	Kocsis, Z., Németh, G., Börcsök, Z., Polgár, A., Király, É., Kóczán, Zs. & Borovics, A. (2022): Specifying logistics and energy consumption conversion factors related to the carbon footprint analysis of the wood industry processes. Bulletin of Forestry Science, 12(1): 57-73.

Benke, A., Cseke, K. & Borovics, A. (2011): Population genetic inventory of transdanubian Leuce poplars applying RAPD and cpDNA markers. Bulletin of Forestry Science, 1(1): 83-93.

Cseke, K., Benke, A. & Borovics, A. (2011): Identification of poplar genotypes based on DNA fingerprinting method. Bulletin of Forestry Science, 1(1): 107-114.

Cseke, K., Bordács, S. & Borovics, A. (2011): Taxonomic and genetic study of a mixed oak stand. Bulletin of Forestry Science, 1(1): 95-105.

Cseke, K., Jobb, Sz., Koltay, A. & Borovics, A. (2014): The genetic pattern of oak decline. Bulletin of Forestry Science, 4(2): 135-147.

Bordács, S., Nagy, L., Pintér, B., Bach, I., Borovics, A., Kottek, P., Szepesi, A., Fekete, Z., Wisnovszky, K. & Mátyás, Cs. (2013): State of Hungary’s forest genetic resources, 2010-2011. Bulletin of Forestry Science, 3(1): 21-37.

Mátyás, Cs. & Borovics, A. (2014): "Agrárklíma". Bulletin of Forestry Science, 4(2): 7-8.

Borovics, A., Illés, G., Juhász, J., Móricz, N., Rasztovits, E., Nimmerfroh-Pletscher, B., Unghváry, F., Pintér, T., Pödör, Z. & Jereb, L. (2018): The necessity and steps of establishing a forestry climate centre. Bulletin of Forestry Science, 8(2): 5-8.

Kollár, T. & Borovics, A. (2021): The updated methodological directives of data processing and maintainance of the hungarian long term forestry experimental network, and its most important results. Bulletin of Forestry Science, 11(2): 95-114.

Kocsis, Z., Németh, G., Börcsök, Z., Polgár, A., Király, É., Kóczán, Zs. & Borovics, A. (2022): Specifying logistics and energy consumption conversion factors related to the carbon footprint analysis of the wood industry processes. Bulletin of Forestry Science, 12(1): 57-73.

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