Russian version English version
Volume 17   Issue 1   Year 2022
Gulyaeva E.N.1, Tarelkina T.V.2, Galibina N.A.2

Functional characteristics of EST-SSR markers available for Scots pine

Mathematical Biology & Bioinformatics. 2022;17(1):82-155.

doi: 10.17537/2022.17.82.

References

  1. Pravdin L.F. Scots Pine: Variation, Intraspecific Taxonomy and Selection. London: Annarbor Humphrey Science Publishers Ltd, 1969. 208 p.
  2. Mason W., Alía R. Current and future status of Scots pine (Pinus sylvestris L.) forests in Europe. Forest Systems. 2000;9:317–335.
  3. Krakau U.-K., Liesebach M., Aronen T., Lelu-Walter M.-A. Scots Pine (Pinus sylvestris L.). In: Forest Tree Breeding in Europe. Ed. Pâques L.E. Dordrecht: Springer Netherlands, 2013. P. 267–323. doi: 10.1007/978-94-007-6146-9_6
  4. Cañellas I., Martínez García F., Montero G.Silviculture and dynamics of Pinus sylvestris L. stands in Spain. Forest Systems. 2000;9:233–253.
  5. Nilsson U., Luoranen J., Kolström T., Örlander G., Puttonen P. Reforestation with planting in northern Europe. Scandinavian Journal of Forest Research. 2010;25(4):283–294. doi: 10.1080/02827581.2010.498384
  6. Sukhbaatar G., Ganbaatar B., Jamsran T., Purevragchaa B., Nachin B., Gradel A. Assessment of early survival and growth of planted Scots pine (Pinus sylvestris) seedlings under extreme continental climate conditions of northern Mongolia. Journal of Forestry Research. 2020;31(1):13–26. doi: 10.1007/s11676-019-00935-8
  7. Boratyński A. Range of natural distribution. In: Genetics of Scots Pine. Amsterdam: Elsevier, 1991. P. 19–30. doi: 10.1016/B978-0-444-98724-2.50006-7
  8. Eriksson G. Evolutionary forces influencing variation among populations of Pinus sylvestris. Silva Fennica. 1998;32:173–184. doi: 10.14214/sf.694
  9. Matías L., Jump A.S. Interactions between growth, demography and biotic interactions in determining species range limits in a warming world: The case of Pinus Sylvestris. Forest Ecology and Management. 2012;282:10–22. doi: 10.1016/j.foreco.2012.06.053
  10. Mullin T.J., Andersson B., Bastien J.-C., Beaulieu J., Burdon R.D., Dvorak W.S., King J.N., Kondo T., Krakowski J., Lee S.J., et al. Economic importance, breeding objectives and achievements. In: Genetics, Genomics and Breeding of Conifers. Boca Raton: CRC Press, 2011. P. 40–127. doi: 10.1201/b11075-3
  11. Ruotsalainen S., Persson T. Scots pine – Pinus sylvestris L. In: Best Practice for Tree Breeding in Europe. Uppsala: Skogforsk, 2013. P. 49–64.
  12. Sannikov S.N., Petrova I.V., Sannikova N.S., Afonin A.N., Chernodubov A.I., Egorov E.V. Genetic-climatologic-geographical principles of seed zoning of pine forests in Russia. Siberian Forest Journal. 2017(2):19–30. doi: 10.15372/SJFS20170203
  13. Wójkiewicz B., Cavers S., Wachowiak W. Current Approaches and Perspectives in Population Genetics of Scots Pine (Pinus sylvestris L.). Forest Science. 2016;62(3):343–354. doi: 10.5849/forsci.15-040
  14. Plomion C., Chagné D., Pot D., Kumar S., Wilcox P.L., Burdon R.D., Prat D., Peterson D.G., Paiva J., Chaumeil P., et al. Pines. In: Forest Trees. Berlin: Springer.2007. P. 29–92. doi: 10.1007/978-3-540-34541-1_2
  15. Parchman T.L., Geist K.S., Grahnen J.A., Benkman C.W., Buerkle C.A. Transcriptome sequencing in an ecologically important tree species: assembly, annotation, and marker discovery. BMC Genomics. 2010;11(1):1–16. doi: 10.1186/1471-2164-11-180
  16. Mackay J., Dean J.F.D., Plomion C., Peterson D.G., Cánovas F.M., Pavy N., Ingvarsson P.K., Savolainen O., Guevara M.Á., Fluch S., et al. Towards decoding the conifer giga-genome. Plant Molecular Biology. 2012;80(6):555–569. doi: 10.1007/s11103-012-9961-7
  17. Pellicer J., Leitch I.J. The Plant DNA C-values database (release 7.1): an updated online repository of plant genome size data for comparative studies. New Phytologist. 2020;226:301–305. doi: 10.1111/nph.16261
  18. Pyhäjärvi T., Kujala S.T., Savolainen O. 275 years of forestry meets genomics in Pinus sylvestris. Evolutionary Applications. 2020;13(1):11–30. doi: 10.1111/eva.12809
  19. Lu M.Z., Szmidt A.E., Wang X.R. Inheritance of RAPD fragments in haploid and diploid tissues of Pinus sylvestris (L.). Heredity. 1995;74(6):582–589. doi: 10.1038/hdy.1995.82
  20. Hurme P., Sillanpää M.J., Arjas E., Repo T., Savolainen O. Genetic basis of climatic adaptation in Scots pine by Bayesian quantitative trait locus analysis. Genetics. 2000;156(3):1309–1322. doi: 10.1093/genetics/156.3.1309
  21. Lerceteau E., Plomion C., Andersson B. AFLP mapping and detection of quantitative trait loci (QTLs) for economically important traits in Pinus sylvestris: a preliminary study. Molecular Breeding. 2000;6(5):451–458. doi: 10.1023/A:1026548716320
  22. Lerceteau E., Szmidt A.E., Andersson B. Detection of quantitative trait loci in Pinus sylvestris L. across years. Euphytica. 2001;121(2):117–122. doi: 10.1023/A:1012076825293
  23. Yazdani R., Nilsson J.E., Plomion C., Mathur G. Marker trait association for autumn cold acclimation and growth rhythm in Pinus Sylvestris. Scandinavian Journal of Forest Research. 2003;18(1):29–38. doi: 10.1080/0891060310002318
  24. Yin T.M., Wang X.R., Andersson B., Lerceteau-Köhler E. Nearly complete genetic maps of Pinus sylvestris L. (Scots pine) constructed by AFLP marker analysis in a full-sib family. Theoretical and Applied Genetics. 2003;106(6):1075–1083. doi: 10.1007/s00122-003-1194-3
  25. Abraham B., Miklossy I., Kovacs E., Tamas E., Meszaros I., Szilveszter S., Brezeanu A., Lanyi S. Genetic analysis of Pinus sylvestris L. and Pinus sylvestris forma turfosa L. using RAPD markers. Notulae Scientia Biologicae. 2010;2(1):129–132 doi: 10.15835/nsb213611
  26. Nowicka A, Ukalska J, Simińska J, Szyp-Borowska I. Characterization and mapping of QTL used in breeding of Scots pine (Pinus sylvestris L.). Folia Forestalia Polonica. Series A. Forestry. 2013;55(4):68–173. doi: 10.2478/ffp-2013-0018
  27. Androsiuk P., Ciaglo-Androsiuk S., Urbaniak L. Genetic diversity and differentiation of Pinus sylvestris L. from the IUFRO 1982 provenance trial revealed by AFLP analysis. Archives of Biological Sciences. 2015;67(4):1237–1249. doi: 10.2298/ABS150319100A
  28. Jones C.J., Edwards K.J., Castaglione S., Winfield M.O., Sala F., van de Wiel C., Bredemeijer G., Vosman B., Matthes M., Daly A. et al. Reproducibility testing of RAPD, AFLP and SSR markers in plants by a network of European laboratories. Molecular Breeding. 1997;3(5):381–390. doi: 10.1023/A:1009612517139
  29. Meudt H.M., Clarke A.C. Almost forgotten or latest practice? AFLP applications, analyses and advances. Trends in Plant Science. 2007;12(3):106–117. doi: 10.1016/j.tplants.2007.02.001
  30. Agarwal M., Shrivastava N., Padh H. Advances in molecular marker techniques and their applications in plant sciences. Plant Cell Reports. 2008;27(4):617–631 doi: 10.1007/s00299-008-0507-z
  31. Hamblin M.T., Warburton M.L., Buckler E.S. Empirical comparison of simple sequence repeats and single nucleotide polymorphisms in assessment of maize diversity and relatedness. PloS One. 2007;2(12):e136 doi: 10.1371/journal.pone.0001367
  32. Kalia R. K., Rai M. K., Kalia S., Singh R., Dhawan A. K. Microsatellite markers: an overview of the recent progress in plants. Euphytica. 2011;177(3):309–334. doi: 10.1007/s10681-010-0286-9
  33. Brumfield R.T., Beerli P., Nickerson D.A., Edwards S.V. The utility of single nucleotide polymorphisms in inferences of population history. Trends in Ecology & Evolution. 2003;18(5):249–256. doi: 10.1016/S0169-5347(03)00018-1
  34. Choudhary S., Sethy N. K., Shokeen B., Bhatia S. Development of chickpea EST-SSR markers and analysis of allelic variation across related species. Theoretical and Applied Genetics. 2009;118(3):591–608. doi: 10.1007/s00122-008-0923-z
  35. Nicolaï M., Pisani C., Bouchet J.P., Vuylsteke M., Palloix A. Discovery of a large set of SNP and SSR genetic markers by high-throughput sequencing of pepper (Capsicum annuum). Genetics and Molecular Research. 2012;11(3):2295–2300. doi: 10.4238/2012.August.13.3
  36. Hodel R.G., Segovia-Salcedo M.C., Landis J.B., Crowl A.A. Sun M., Liu X., Gitzendanner M.A., Douglas N.A., Germain-Aubrey C.C., Chen S., et al. The report of my death was an exaggeration: a review for researchers using microsatellites in the 21st century. Applications in Plant Sciences. 2016;4(6):1600025. doi: 10.3732/apps.1600025
  37. Flanagan S.P., Jones A.G. The future of parentage analysis: From microsatellites to SNPs and beyond. Molecular Ecology. 2019;28(3):544–567. doi: 10.1111/mec.14988
  38. Li Y.-C., Korol A.B., Fahima T., Nevo E. Microsatellites within genes: structure, function, and evolution. Molecular Biology and Evolution. 2004;21(6):991–1007. doi: 10.1093/molbev/msh073
  39. Varshney R.K., Graner A., Sorrells M.E. Genic microsatellite markers in plants: features and applications. TRENDS in Biotechnology. 2005;23(1):48–55. doi: 10.1016/j.tibtech.2004.11.005
  40. Zuo L., Zhang S., Zhang J., Liu Y., Yu X., Yang M., Wang J. Primer development and functional classification of EST-SSR markers in Ulmus species. Tree Genetics & Genomes. 2020;16(5):1-11. doi: 10.1007/s11295-020-01468-6
  41. Chagné D., Chaumeil P., Ramboer A., Collada C., Guevara A., Cervera M.T., Vendramin G.G., Garcia V., Frigerio J-M., Echt C., et al. Cross-species transferability and mapping of genomic and cDNA SSRs in pines. Theoretical and Applied Genetics. 2004;109(6):1204–1214. doi: 10.1007/s00122-004-1683-z
  42. Lesser M.R., Parchman T.L., Buerkle C.A. Cross‐species transferability of SSR loci developed from transciptome sequencing in lodgepole pine. Molecular Ecology Resources. 2012;12(3):448–455. doi: 10.1111/j.1755-0998.2011.03102.x
  43. Telfer E., Graham N., Macdonald L., Sturrock S., Wilcox P., Stanbra L. Approaches to variant discovery for conifer transcriptome sequencing. PLoS One. 2018;13(11):e0205835. doi: 10.1371/journal.pone.0205835
  44. Sebastiani F., Pinzauti F., Kujala S.T., González-Martínez S.C., Vendramin G.G. Novel polymorphic nuclear microsatellite markers for Pinus sylvestris L. Conservation Genetics Resources. 2012;4(2):231–234. doi: 10.1007/s12686-011-9513-5
  45. Liewlaksaneeyanawin C., Ritland C.E., El-Kassaby Y.A., Ritland K. Single-copy, species-transferable microsatellite markers developed from loblolly pine ESTs. Theoretical and Applied Genetics. 2004;109(2):361–369. doi: 10.1007/s00122-004-1635-7
  46. Fang P., Niu S., Yuan H., Li Z., Zhang Y., Yuan L., Li W. Development and Characterization of 25 EST-SSR markers in Pinus sylvestris var. mongolica (Pinaceae). Applications in Plant Sciences. 2014;2(1):1300057. doi: 10.3732/apps.1300057
  47. Zimin A., Stevens K.A., Crepeau M.W., Holtz-Morris A., Koriabine M., Marçais G., Puiu D., Roberts M., Wegrzyn J.L., de Jong P. J., et al. Sequencing and Assembly of the 22-Gb Loblolly Pine Genome. Genetics. 2014;196(3):875–890. doi: 10.1534/genetics.113.159715
  48. Kumar S., Stecher G., Li M., Tamura K. MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Molecular Biology and Evolution. 2018;35(6):1547–1549. doi: 10.1093/molbev/msy096
  49. Conesa A., Gotz S., Garcia-Gomez J.M., Terol J., Talón M., Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics. 2005;21(18):3674–3676. doi: 10.1093/bioinformatics/bti610
  50. Kanehisa M. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Research. 2000;28(1):27–30. doi: 10.1093/nar/28.1.27.
  51. Marchler-Bauer A., Bryant S.H. CD-Search: protein domain annotations on the fly. Nucleic Acids Research. 2004;32(suppl_2):W327–W331. doi: 10.1093/nar/gkh454
  52. Echt C.S., Saha S., Deemer D.L., Nelson C.D. Microsatellite DNA in genomic survey sequences and UniGenes of loblolly pine. Tree Genetics & Genomes. 2011a;7(4):773–780. doi: 10.1007/s11295-011-0373-7
  53. Echt C.S., Saha S., Krutovsky K.V., Wimalanathan K., Erpelding J. E., Liang C., Nelson, C.D. An annotated genetic map of loblolly pine based on microsatellite and cDNA markers. BMC Genetics. 2011b;12(1):1–16. doi: 10.1186/1471-2156-12-17
  54. Li X., Liu X., Wei J., Li Y., Tigabu M., Zhao X. Development and Transferability of EST-SSR Markers for Pinus koraiensis from Cold-Stressed Transcriptome through Illumina Sequencing. Genes. 2020;11(5):500. doi: 10.3390/genes11050500
  55. Doolittle R.F. Of URFs and ORFs: A Primer on How to Analyze Derived Amino Acid Sequences. Sausalito, Calif: University Science Books, 1986. 112 p.
  56. Powell W., Morgante M., Andre C., Hanafey M., Vogel J., Tingey S., Rafalski A. The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis. Molecular Breeding. 1996;2(3):225–238. doi: 10.1007/BF00564200
  57. Scalfi M., Troggio M., Piovani P., Leonardi S., Magnaschi G., Vendramin G.G., Menozzi P. A RAPD, AFLP and SSR linkage map, and QTL analysis in European beech (Fagus sylvatica L.). Theoretical and Applied Genetics. 2004;108(3):433–441. doi: 10.1007/s00122-003-1583-7
  58. Song Q.J., Shi J.R., Singh S., Fickus E.W., Costa J.M., Lewis J., Gill B.S., Ward R., Cregan P.B. Development and mapping of microsatellite (SSR) markers in wheat. Theoretical and Applied Genetics. 2005;110(3):550–560. doi: 10.1007/s00122-004-1871-x
  59. Chen L., Ma Q., Chen Y., Wang B., Pei D. Identification of major walnut cultivars grown in China based on nut phenotypes and SSR markers. Scientia Horticulturae. 2014;168:240–248. doi: 10.1016/j.scienta.2014.02.004
  60. Jeennor S., Volkaert H. Mapping of quantitative trait loci (QTLs) for oil yield using SSRs and gene-based markers in African oil palm (Elaeisguineensis Jacq.). Tree Genetics & Genomes. 2014;10(1):1–14. doi: 10.1007/s11295-013-0655-3
  61. Lin H., Li Y., Xue Z., Chen M., Zhu H., Wen Q. Analysis of SSR loci in transcriptome and development of molecular markers in Brassica oleraceavar. botrytis L. Journal of Northwest A & F University-Natural Science Edition. 2019;47(3):85–93.
  62. Jiang Y., Xu S., Wang R., Zhou J., Dou J., Yin Q., Wang R. Characterization, validation, and cross-species transferability of EST-SSR markers developed from Lycorisaurea and their application in genetic evaluation of Lycoris species. BMC Plant Biology. 2020;20(1):1–14. doi: 10.1186/s12870-020-02727-3
  63. Pavy N., Laroche J., Bousquet J., Mackay J. Large-scale statistical analysis of secondary xylem ESTs in pine. Plant Molecular Biology. 2005;57(2):203–224. doi: 10.1007/s11103-004-6969-7
  64. Cairney J., Zheng L., Cowels A., Hsiao J., Zismann V., Liu J., Ouyang S., Thibaud-Nissen F., Hamilton J., Childs K., et al. Expressed Sequence Tags from loblolly pine embryos reveal similarities with angiosperm embryogenesis. Plant Molecular Biology. 2006;62(4):485–501. doi: 10.1007/s11103-006-9035-9
  65. Nystedt B., Street N.R., Wetterbom A., Zuccolo A., Lin Y.-C., Scofield D.G., Vezzi F., Delhomme N., Giacomello S., Alexeyenko A. et al. The Norway spruce genome sequence and conifer genome evolution. Nature. 2013;497(7451):579–584. doi: 10.1038/nature12211
  66. De La Torre A.R., Piot A., Liu B., Wilhite B., Weiss M., Porth I. Functional and morphological evolution in gymnosperms: A portrait of implicated gene families. Evolutionary Applications. 2020;13(1):210–227. doi: 10.1111/eva.12839
  67. Nikolic B., Kovacevic D., Mladenovic-Drinic S., Nikolić A., Mitić Z., Bojović S., Marin P.D. Relationships among some pines from subgenera Pinus and Strobus revealed by nuclear EST-microsatellites. Genetika. 2018;50(1):69–84. doi: 10.2298/GENSR1801069N
  68. Navascués M. Genetic Diversity of The Endemic Canary Island Pine Tree, Pinus canariensis: PhD Theses. Norwich: University of East Anglia, 2005. 230 p.
  69. Sarac Z., Aleksic J., Dodos T., Rajcevic N., Bojović S., Marin P.D. Cross-species amplification of nuclear EST-microsatellites developed for other Pinus species in Pinus nigra. Genetika. 2015;47(1):205–217. doi: 10.2298/GENSR1501205S
  70. Kalko G.V., Kotova T.M. The microsatellite markers for estimation of genetic diversity of Scots pine. In: Proceedings of the Saint Petersburg Forestry Research Institute. 2018. P. 17–30. doi: 10.21178/2079-6080.2018.3-4.17
  71. Kormutak A., Galgoci M., Manka P., Koubova M., Jopcik M., Sukenikova D., Bolecek P., Gőmőry D. Field-based artificial crossings indicate partial compatibility of reciprocal crosses between Pinus sylvestris and Pinus mugo and unexpected chloroplast DNA inheritance. Tree Genetics & Genomes. 2017;13(3):1–13. doi: 10.1007/s11295-017-1152-x
  72. Kalko G.V. The testing of nuclear microsatellite markers of Scots pine. In: Proceedings of the Saint Petersburg Forestry Research Institute. 2017. P. 23–34. doi: 10.21178/2079-6080.2017.1.23
  73. Máchová P., Cvrčková H., Poláková L., Trčková O. Genetic variability of selected populations of Scots pine in the Czech Republic. Reports of forestry research-Zpravylesnickenovyzkumu. 2016;61(3):223–229.
  74. Tóth E.G., Vendramin G.G., Bagnoli F., Cseke K., Höhn M. High genetic diversity and distinct origin of recently fragmented Scots pine (Pinus sylvestris L.) populations along the Carpathians and the Pannonian Basin. Tree Genetics & Genomes. 2017;13(2):1–12. doi: 10.1007/s11295-017-1137-9
  75. Tóth E.G., Bede-Fazekas Á., Vendramin G.G., Bagnoli F., Höhn M. Mid-Pleistocene and Holocene demographic fluctuation of Scots pine (Pinus sylvestris L.) in the Carpathian Mountains and the Pannonian Basin: Signs of historical expansions and contractions. Quaternary International. 2019;504:202–213. doi: 10.1016/j.quaint.2017.11.024
  76. González-Díaz P., Jump A.S., Perry A., Wachowiak W., Lapshina E., Cavers S. Ecology and management history drive spatial genetic structure in Scots pine. Forest Ecology and Management. 2017;400:68–76. doi: 10.1016/j.foreco.2017.05.035
  77. Volkov V.A. Applying microsatellite DNA markers for establish fact of illegal logging of basic coniferous forest-forming species in North-West Russian area. Sinergiâ Nauk. 2018;30:2211–2219.
  78. Șofletea N., Mihai G., Ciocîrlan E., Curtu A.L. Genetic diversity and spatial genetic structure in isolated Scots Pine (Pinus sylvestris L.) populations native to Eastern and Southern Carpathians. Forests. 2020;11(10):1047. doi: 10.3390/f11101047
  79. Żukowska W.B., Wójkiewicz B., Litkowiec M., Wachowiak W. Cross-amplification and multiplexing of cpSSRs and nSSRs in two closely related pine species (Pinus sylvestris L. and P. mugoTurra). Dendrobiology. 2017;77:59–64. doi: 10.12657/denbio.077.005
  80. Ellis J.R., Burke J.M. EST-SSRs as a resource for population genetic analyses. Heredity. 2007;99(2):125–132. doi: 10.1038/sj.hdy.6801001
  81. Duran C., Singhania R., Raman H., Batley J., Edwards D. Predicting polymorphic EST - SSR s in silico. Molecular Ecology Resources. 2013;13(3):538–545. doi: 10.1111/1755-0998.12078
  82. Luro F.L., Costantino G., Terol J., Argout X., Allario T., Wincker P., Talon M., Ollitrault P., Morillon R. Transferability of the EST-SSRs developed on Nules clementine (Citrus clementinaHort ex Tan) to other Citrus species and their effectiveness for genetic mapping. BMC Genomics. 2008;9(1):1–13. doi: 10.1186/1471-2164-9-287
  83. Dutta S., Kumawat G., Singh B.P., Gupta D.K., Singh S., Dogra V., Gaikwad K., Sharma T.R., Raje R.S., Bandhopadhya T.K. et al. Development of genic-SSR markers by deep transcriptome sequencing in pigeonpea [Cajanus cajan (L.) Millspaugh]. BMC Plant Biology. 2011;11(1):1–13. doi: 10.1186/1471-2229-11-17
  84. Wu J., Cai C., Cheng F., Cui H., Zhou H. Characterisation and development of EST-SSR markers in tree peony using transcriptome sequences. Molecular Breeding. 2014;34(4):1853–1866. doi: 10.1007/s11032-014-0144-x
  85. Kuchma O., Vornam B., Finkeldey R. Mutation rates in Scots pine (Pinus sylvestris L.) from the Chernobyl exclusion zone evaluated with amplified fragment-length polymorphisms (AFLPs) and microsatellite markers. Mutation Research/Genetic Toxicology and Environmental Mutagenesis. 2011;725(1–2):29–35. doi: 10.1016/j.mrgentox.2011.07.003
  86. Danusevičius D., Kerpauskaite V., Kavaliauskas D., Fussi B., Konnert M., Baliuckas V. The effect of tending and commercial thinning on the genetic diversity of Scots pine stands. European Journal of Forest Research. 2016;135(6):1159–1174. doi: 10.1007/s10342-016-1002-7
  87. Shilkina E.A., Ibe A.A., Sheller M.A., Sukhikh T.V. Using methods of DNA-analysis in the examination of the illegal timber trade. Siberian Forest Journal. 2019;3:64–70. doi: 10.15372/SJFS20190308
  88. Tian A.G., Wang J., Cui P., Han Y.-J., Xu H., Cong L.-J., Huang·X.-G., Wang X.-L., Jiao Y.-Z., Wang·B.-J., et al. Characterization of soybean genomic features by analysis of its expressed sequence tags. Theoretical and Applied Genetics. 2004;108(5):903–913. doi: 10.1007/s00122-003-1499-2
  89. Gong Y.M., Xu S.C., Mao W.H., Hu Q.Z., Zhang G.W., Ding J., Li Y.D. Developing new SSR markers from ESTs of pea (Pisum sativum L.). Journal of Zhejiang University Science B. 2010;11(9):702–707. doi: 10.1631/jzus.B1000004
  90. Cloutier S., Miranda E., Ward K., Radovanovic N., Reimer E., Walichnowski A., Datla R., Rowland G., Duguid S., Ragupathy R. Simple sequence repeat marker development from bacterial artificial chromosome end sequences and expressed sequence tags of flax (Linum usitatissimum L.). Theoretical and Applied Genetics. 2012;125(4):685–694. doi: 10.1007/s00122-012-1860-4
  91. Tóth G., Gáspári Z., Jurka J. Microsatellites in different eukaryotic genomes: survey and analysis. Genome Research. 2000;10(7):967–981. doi: 10.1101/gr.10.7.967
  92. Metzgar D., Bytof J., Wills C. Selection against frameshift mutations limits microsatellite expansion in coding DNA. Genome Research. 2000;10(1):72–80.
  93. Lawson M.J., Zhang L. Housekeeping and tissue-specific genes differ in simple sequence repeats in the 5′-UTR region. Gene. 2008;407(1–2):54–62. doi: 10.1016/j.gene.2007.09.017
  94. Vinces M.D., Legendre M., Caldara M., Hagihara M., Verstrepen K.J. Unstable tandem repeats in promoters confer transcriptional evolvability. Science. 2009;324(5931):1213–1216. doi: 10.1126/science.1170097
  95. Ince A.G., Karaca M., Naci Onus A. Differential expression patterns of genes containing microsatellites in Capsicum annuum L. Molecular Breeding. 2010;25(4):645–658. doi: 10.1007/s11032-009-9362-z
  96. Joshi-Saha A., Reddy K.S. Repeat length variation in the 5ʹUTR of myo -inositol monophosphatase gene is related to phytic acid content and contributes to drought tolerance in chickpea (Cicer arietinum L.). Journal of Experimental Botany. 2015;66(19):5683–5690. doi: 10.1093/jxb/erv156
  97. Kumar S., Bhatia S. A polymorphic (GA/CT) n-SSR influences promoter activity of Tryptophan decarboxylase gene in Catharanthus roseus L. Scientific Reports. 2016;6(1):1–12. doi: 10.1038/srep33280
  98. Abedini D., Monfared S.R., Abbasi A. The effects of promoter variations of the N-Methylcanadine 1-Hydroxylase (CYP82Y1) gene on the noscapine production in opium poppy. Scientific Reports. 2018;8(1):1–11. doi: 10.1038/s41598-018-23351-0
  99. Sangwan I., O’Brian M.R. Identification of a Soybean Protein That Interacts with GAGA Element Dinucleotide Repeat DNA. Plant Physiology. 2002;129(4):1788–1794. doi: 10.1104/pp.002618
  100. Zhang L., Zuo K., Zhang F., Cao Y., Wang J., Zhang Y., Sun X., Tang K. Conservation of noncoding microsatellites in plants: implication for gene regulation. Bmc Genomics. 2006;7(1):1–14. doi: 10.1186/1471-2164-7-323
  101. Mignone F., Gissi C., Liuni S., Pesole G. Untranslated regions of mRNAs. Genome Biology. 2002;3(3):1–10. doi: 10.1186/gb-2002-3-3-reviews0004
  102. Heller G., Adomas A.G., Li G., Osborne J., van Zyl L., Sederoff R., Finlay R.D., Stenlid J., Asiegbu F.O. Transcriptional analysis of Pinus sylvestris roots challenged with the ectomycorrhizal fungus Laccaria bicolor. BMC Plant Biology. 2008;8(1):1–13. doi: 10.1186/1471-2229-8-19
  103. Fernández-Pozo N., Canale J., Guerrero-Fernández D., Villalobos D.P., Díaz-Moreno S.M., Bautista R., Flores-Monterroso A., Guevara M.Á., Perdiguero P., Collada C. et al. EuroPineDB: a high-coverage web database for maritime pine transcriptome. BMC Genomics. 2011;12(1):1–11. doi: 10.1186/1471-2164-12-366
  104. Niu S.H., Li Z.X., Yuan H.W., Chen X.Y., Li Y., Li W. Transcriptome characterisation of Pinus tabuliformisand evolution of genes in the Pinus phylogeny. Bmc Genomics. 2013;14(1):1–12. doi: 10.1186/1471-2164-14-263
  105. Du J., Zhang Z., Zhang H., Junhong T. EST–SSR marker development and transcriptome sequencing analysis of different tissues of Korean pine (Pinus koraiensisSieb. et Zucc.). Biotechnology & Biotechnological Equipment. 2017;31(4):679–689. doi: 10.1080/13102818.2017.1331755
  106. Chano V., López de Heredia U., Collada C., Soto Á. Transcriptomic analysis of juvenile wood formation during the growing season in Pinus canariensis. Holzforschung. 2017;71(12):919–937. doi: 10.1515/hf-2017-0014
  107. Brown G.R., Bassoni D.L., Gill G.P., Fontana J.R., Wheeler N.C., Megraw R.A., Davis M.F., Sewell M.M., Tuskan G.A., Neale D.B. Identification of quantitative trait loci influencing wood property traits in loblolly pine (Pinus taeda L.). III. QTL verification and candidate gene mapping. Genetics. 2003;164(4):1537–1546. doi: 10.1093/genetics/164.4.1537
  108. Dillon S.K., Nolan M.F., Wu H., Southerton S.G. Association genetics reveal candidate gene SNPs affecting wood properties in Pinus radiata. Australian Forestry. 2010;73(3):185–190. doi: 10.1080/00049158.2010.10676326
  109. Lepoittevin C., Harvengt L., Plomion C., Garnier-Géré P. Association mapping for growth, straightness and wood chemistry traits in the Pinus pinaster Aquitaine breeding population. Tree Genetics & Genomes. 2012;8(1):113–126. doi: 10.1007/s11295-011-0426-y
  110. Li Z., Hallingbäck H.R., Abrahamsson S., Fries A., Gull B.A., Sillanpää M.J., García-Gil M.R. Functional multi-locus QTL mapping of temporal trends in scots pine wood traits. G3: Genes, Genomes, Genetics. 2014;4(12):2365–2379. doi: 10.1534/g3.114.014068
  111. Calleja-Rodriguez A., Li Z., Hallingbäck H.R., Sillanpää M.J., Abrahamsson S., García-Gil M.R. Functional Quantitative Trait Loci (QTL) analysis for adaptive traits in a three-generation Scots pine pedigree. bioRxiv. 2018:297986. doi: 10.1101/297986
  112. Groover A., Devey M., Fiddler T., Lee J., Megraw R., Mitchel-Olds T., Sherman B., Vujcic S., Williams C., Nede D. Identification of quantitative trait loci influencing wood specific gravity in an outbred pedigree of loblolly pine. Genetics. 1994;138(4):1293–1300. doi: 10.1093/genetics/138.4.1293
  113. Chagné D., Brown G., Lalanne C., Madur D., Pot D., Neale D., Plomion C. Comparative genome and QTL mapping between maritime and loblolly pines. Molecular Breeding. 2003;12(3):185–195. doi: 10.1023/A:1026318327911
  114. González-Martínez S.C., Wheeler N.C., Ersoz E., Nelson C.D., Neale D.B. Association genetics in Pinus taeda L. I. Wood property traits. Genetics. 2007;175(1):399–409.  doi: 10.1534/genetics.106.061127
  115. Lorenz W.W., Dean J.F. SAGE profiling and demonstration of differential gene expression along the axial developmental gradient of lignifying xylem in loblolly pine (Pinus taeda). Tree Physiology. 2002;22(5):301–310. doi: 10.1093/treephys/22.5.301
  116. Kirst M., Johnson A.F., Baucom C., Erin U., Hubbard K., Staggs R., Paule C., Retzel E., Whetten R., Sederoff R. Apparent homology of expressed genes from wood-forming tissues of loblolly pine (Pinus taeda L.) with Arabidopsis thaliana. Proceedings of the National Academy of Sciences. 2003;100(12):7383–7388. doi: 10.1073/pnas.1132171100
  117. Yang S.H., van Zyl L., No E.G., Loopstra C.A. Microarray analysis of genes preferentially expressed in differentiating xylem of loblolly pine (Pinus taeda). Plant Science. 2004;166(5):1185–1195. doi: 10.1016/j.plantsci.2003.12.030
  118. Li X., Wu H.X., Dillon S.K., Southerton S.G. Generation and analysis of expressed sequence tags from six developing xylem libraries in Pinus radiata D. Don. BMC Genomics. 2009;10(1):1–18. doi: 10.1186/1471-2164-10-41
  119. Li X., Wu H.X., Southerton S.G. Seasonal reorganization of the xylem transcriptome at different tree ages reveals novel insights into wood formation in Pinus radiata. New Phytologist. 2010;187(3):764–776. doi: 10.1111/j.1469-8137.2010.03333.x
  120. Li X., Wu H.X., Southerton S.G. Identification of putative candidate genes for juvenile wood density in Pinus radiata. Tree Physiology. 2012;32(8):1046–1057. doi: 10.1093/treephys/tps060
  121. Zhang D., Hrmova M., Wan C.-H., Wu C., Balzen J., Cai W., Wang J., Densmore L.D., Fincher G.B., Zhang H., Haigler C.H. Members of a New Group of Chitinase-Like Genes are Expressed Preferentially in Cotton Cells with Secondary Walls. Plant Molecular Biology. 2004;54(3):353–372. doi: 10.1023/B:PLAN.0000036369.55253.dd
  122. Aspeborg H., Schrader J., Coutinho P.M., Stam M., Kallas A., Djerbi S., Nilsson P., Denman S., Amini B., Sterky F., et al. Carbohydrate-active enzymes involved in the secondary cell wall biogenesis in hybrid aspen. Plant Physiology. 2005;137(3):983–997. doi: 10.1104/pp.104.055087
  123. de Carvalho M.C.D.C.G., Caldas D.G.G., Carneiro R.T., Moon D.H., Salvatierra G.R., Franceschini L.M., de Andrade ., Celedon P.A.F., Oda S., Labate C.A. SAGE transcript profiling of the juvenile cambial region of Eucalyptus grandis. Tree Physiology. 2008;28(6):905–919. doi: 10.1093/treephys/28.6.905
  124. Sánchez-Rodríguez C., Bauer S., Hématy K., Saxe F., Ibáñez A. B., Vodermaier V., Konlechner C., Sampathkumar A., Rüggeberg M., Aichinger E., et al. CHITINASE-LIKE1/POM-POM1 and Its Homolog CTL2 Are Glucan-Interacting Proteins Important for Cellulose Biosynthesis in Arabidopsis. The Plant Cell. 2012;24(2):589–607. doi: 10.1105/tpc.111.094672
  125. Pirttilä A., Laukkanen H., Hohtola A. Chitinase production in pine callus (Pinus sylvestris L.): a defense reaction against endophytes? Planta. 2002;214(6):848–852. doi: 10.1007/s00425-001-0709-x
  126. Bischoff V., Nita S., Neumetzler L., Schindelasch D., Urbain A., Eshed R., Persson S., Delmer D., Scheible W.-R. TRICHOME BIREFRINGENCE and Its Homolog AT5G01360 Encode Plant-Specific DUF231 Proteins Required for Cellulose Biosynthesis in Arabidopsis. Plant Physiology. 2010;153(2):590–602. doi: 10.1104/pp.110.153320
  127. Pauly M., Ramírez V. New insights into wall polysaccharide O-acetylation. Frontiers in Plant Science. 2018. 1210 p. doi: 10.3389/fpls.2018.01210
  128. Haigler C.H., Singh B., Wang G., Zhang D. Genomics of cotton fiber secondary wall deposition and cellulose biogenesis. In: Genetics and Genomics of Cotton. New York: Springer. 2009. P. 385–417. doi: 10.1007/978-0-387-70810-2_16
  129. Ubeda-Tomas S., Edvardsson E., Eland C., Singh S.K., Zadik D., Aspeborg H., Gorzsàs A., Teeri T.T., Sundberg B., Persson P., et al. Genomic-assisted identification of genes involved in secondary growth in Arabidopsis utilising transcript profiling of poplar wood-forming tissues. Physiologia Plantarum. 2007;129(2):415–428. doi: 10.1111/j.1399-3054.2006.00817.x
  130. Hodgson-Kratky K., Perlo V., Furtado A., Choudhary H.,·Gladden J.M., Simmons B.A., Botha F. Henry R.J. Association of gene expression with syringyl to guaiacyl ratio in sugarcane lignin. Plant Molecular Biology. 2021;106(1):173–192. doi: 10.1007/s11103-021-01136-w
  131. Gui J., Luo L., Zhong Y., Sun J., Umezawa T., Li L. Phosphorylation of LTF1, an MYB transcription factor in Populus, acts as a sensory switch regulating lignin biosynthesis in wood cells. Molecular Plant. 2019;12(10):1325–1337. doi: 10.1016/j.molp.2019.05.008
  132. Patzlaff A., McInnis S., Courtenay A., Surman C., Newman L.J., Smith C., Bevan M.W., Mansfield S., Whetten R.W., Sederoff R.R., Campbell M.M. Characterisation of a pine MYB that regulates lignification. The Plant Journal. 2003;36(6):743–754. doi: 10.1046/j.1365-313X.2003.01916.x
  133. Bedon F., Grima-Pettenati J., Mackay J. Conifer R2R3-MYB transcription factors: sequence analyses and gene expression in wood-forming tissues of white spruce (Picea glauca). BMC Plant Biology. 2007;7(1):1–17. doi: 10.1186/1471-2229-7-17
  134. Bomal C., Bedon F., Caron S., Mansfield S.D., Levasseur C., Cooke J.E.K., Blais S., Tremblay L., Morency M.-J., Pavy N., et al. Involvement of Pinus taeda MYB1 and MYB8 in phenylpropanoid metabolism and secondary cell wall biogenesis: a comparative in planta analysis. Journal of Experimental Botany. 2008;59(14):3925–3939. doi: 10.1093/jxb/ern234
  135. Ni Z., Han X., Yang Z., Xu M., Feng Y., Chen Y., Xu L. A. Integrative analysis of wood biomass and developing xylem transcriptome provide insights into mechanisms of lignin biosynthesis in wood formation of Pinus massoniana. International Journal of Biological Macromolecules. 2020;163:1926–1937. doi: 10.1016/j.ijbiomac.2020.08.253
  136. Kim M.-H., Tran T.N.A., Cho J.-S., Park E.J., Lee H., Kim D.G., Hwang S., Ko J.H. Wood transcriptome analysis of Pinus densiflora identifies genes critical for secondary cell wall formation and NAC transcription factors involved in tracheid formation. Tree Physiology. 2021;41(7):1289–1305. doi: 10.1093/treephys/tpab001
  137. Ko J., Prassinos C., Han K. Developmental and seasonal expression of PtaHB1, a Populus gene encoding a class III HD-Zip protein, is closely associated with secondary growth and inversely correlated with the level of microRNA (miR166). New Phytologist. 2006;169(3):469–478. doi: 10.1111/j.1469-8137.2005.01623.x
  138. Côté C.L., Boileau F., Roy V., Ouellet M., Levasseur C., Morency M.J., Cooke J.E.K., Séguin A., MacKay J.J. Gene family structure, expression and functional analysis of HD-Zip III genes in angiosperm and gymnosperm forest trees. BMC Plant Biology. 2010;10(1):1–17. doi: 10.1186/1471-2229-10-273
  139. Gao J., Lan T. Functional characterization of the late embryogenesis abundant (LEA) protein gene family from Pinus tabuliformis (Pinaceae) in Escherichia coli. Scientific Reports. 2016;6(1):1–10. doi: 10.1038/srep19467
  140. Veluthakkal R., Dasgupta M.G. Pathogenesis-related genes and proteins in forest tree species. Trees. 2010;24(6):993–1006. doi: 10.1007/s00468-010-0489-7
  141. Mageroy M.H., Parent G., Germanos G., Giguère I., Delvas N., Maaroufi H., Bauce E., Bohlmann J., Mackay J.J. Expression of the β‐glucosidase gene Pgβglu‐1 underpins natural resistance of white spruce against spruce budworm. The Plant Journal. 2015;81(1):68–80. doi: 10.1111/tpj.12699
  142. Porth I., White R., Jaquish B., Ritland K. Partial correlation analysis of transcriptomes helps detangle the growth and defense network in spruce. New Phytologist. 2018;218(4):1349–1359. doi: 10.1111/nph.15075
  143. De La Torre A.R., Puiu D., Crepeau M.W., Stevens K., Salzberg S.L., Langley C.H., Neale D.B. Genomic architecture of complex traits in loblolly pine. New Phytologist. 2019;221(4):1789–1801. doi: 10.1111/nph.15535
  144. Elsik C.G., Minihan V.T., Hall S.E., Scarpa A.M., Williams C.G. Low-copy microsatellite markers for Pinus taeda L. Genome. 2000;43(3):550–555. doi: 10.1139/g00-002
  145. Komulainen P., Brown G.R., Mikkonen M., Karhu A., Garcia-Gil M. R., O'malley D., Lee B., Neale D.B., Savolainen O. Comparing EST-based genetic maps between Pinus sylvestris and Pinus taeda. Theoretical and Applied Genetics. 2003;107(4):667–678. doi: 10.1007/s00122-003-1312-2
  146. Waldmann P., García-Gil M.R., Sillanpää M.J. Comparing Bayesian estimates of genetic differentiation of molecular markers and quantitative traits: an application to Pinus sylvestris. Heredity. 2005;94(6):623–629. doi: 10.1038/sj.hdy.6800672
  147. Varis S., Santanen A., Pakkanen A., Pulkkinen P. The importance of being the first pollen in the strobili of Scots pine. Canadian Journal of Forest Research. 2008;38(12):2976–2980. doi: 10.1139/X08-138
  148. García-Gil M.R., Olivier F., Kamruzzahan S., Waldmann P. Joint analysis of spatial genetic structure and inbreeding in a managed population of Scots pine. Heredity. 2009;103(1):90–96. doi: 10.1038/hdy.2009.33
  149. Torimaru T., Wang X.-R., Fries A., Andersson B., Lindgren D. Evaluation of pollen contamination in an advanced Scots pine seed orchard. Silvae Genetica. 2009;58(1–6):262–269. doi: 10.1515/sg-2009-0033
  150. Torimaru T., Wennström U., Lindgren D., Wang X.-R. Effects of male fecundity, interindividual distance and anisotropic pollen dispersal on mating success in a Scots pine (Pinus sylvestris) seed orchard. Heredity. 2012;108(3):312–321. doi: 10.1038/hdy.2011.76
  151. Torimaru T., Wennström U., Andersson B., Almqvist C., Wang X.-R. Reduction of pollen contamination in Scots pine seed orchard crop by tent isolation. Scandinavian Journal of Forest Research. 2013;28(8):715–723. doi: 10.1080/02827581.2013.838298
  152. Wang X.-R., Torimaru T., Lindgren D., Fries A. Marker-based parentage analysis facilitates low input ‘breeding without breeding’ strategies for forest trees. Tree Genetics & Genomes. 2010;6(2):227–235. doi: 10.1007/s11295-009-0243-8
  153. Baumanis I., Veinberga I., Ļubinskis L., Almqvist C., Wang X.R. Seed quality and genetic polymorphism in Scots pine seed orchards. Mežzinātne. 2012;26:74–87.
  154. Abrahamsson S., Ahlinder J., Waldmann P., García-Gil M.R. Maternal heterozygosity and progeny fitness association in an inbred Scots pine population. Genetica. 2013;141(1):41–50. doi: 10.1007/s10709-013-9704-y
  155. Korecký J., Klápště J., Lstibůrek M., Kobliha J., Nelson C.D., El-Kassaby Y.A. Comparison of genetic parameters from marker-based relationship, sibship, and combined models in Scots pine multi-site open-pollinated tests. Tree Genetics & Genomes. 2013;9(5):1227–1235. doi: 10.1007/s11295-013-0630-z
  156. Demkovich A.E., Korshikov I.I., Politov D.V., Mudrik A., Los S.A. Genetic polymorphism of. Pinus sylvestris L. plus trees and their progenies by SSR loci. Plant Physiology and Genetics. 2014(46):395–405.
  157. Sheykina O.V., Unzhenina O.V., GladkovYu.F. Selection of SSR-markers for identification of pine genotypes. In: Reproduction of Forest Plants in Vitro Culture as a Basis for Plantation Forestry. Yoshkar-Ola: Volga State University of Technology, 2014. P. 35–39.
  158. Ilinov A.A., Raevsky B.V. Analysis of the Pinus sylvestris L. plus tree gene pool in Karelia using microsatellite loci. Transactions of Karelian Research Centre of the Russian Academy of Sciences. 2018;6:124–134. doi: 10.17076/eb840
  159. Ilinov A.A., Raevsky B.V. Comparative evaluation of the genetic diversity of natural populations and clonal seed orchards of Pinus sylvestris L. and Picea × fennica (Regel) Kom. in Karelia. Russian Journal of Genetics: Applied Research. 2015;7:607–616. doi: 10.1134/S2079059717060065
  160. Ilinov A.A., Raevsky B.V. The current state of Pinus sylvestris L. gene pool in Karelia. Siberian Journal of Forest Science. 2016(5):45–54. doi: 10.15372/SJFS20160504
  161. Ilinov A.A., Raevsky B.V., Chirva O.V. The state of gene pool of the basic forest-forming species of the White Sea watershed (on the example of a Picea × fennica (Regel) Kom. and Pinus sylvestris L.). Ecological Genetics. 18:185–202. doi: 10.17816/ecogen19006
  162. Funda T., Wennström U., Almqvist C., Torimaru T., Gull B.A., Wang X.R. Low rates of pollen contamination in a Scots pine seed orchard in Sweden: the exception or the norm? Scandinavian Journal of Forest Research. 2015;30(7):573–586. doi: 10.1080/02827581.2015.1036306
  163. Funda T., Wennström U., Almqvist C., Andersson Gull B., Wang X.R. Mating dynamics of Scots pine in isolation tents. Tree Genetics & Genomes. 2016;12(6):1–17. doi: 10.1007/s11295-016-1074-z
  164. Wójkiewicz B., Litkowiec M., Wachowiak W. Contrasting patterns of genetic variation in core and peripheral populations of highly outcrossing and wind pollinated forest tree species. AoB Plants. 2016;8:plw054. doi: 10.1093/aobpla/plw054
  165. Čepl J., Holá D., Stejskal J., Korecký J., Kočová M., Lhotáková Z., Tomášková I., Palovská M., Rothová O., Whetten R.W., et al. Genetic variability and heritability of chlorophyll afluorescence parameters in Scots pine (Pinus sylvestris L.). Tree physiology. 2016;36(7):883–895. doi: 10.1093/treephys/tpw028
  166. Sheykina O., Gladkov Y. Simulation of the indices of genetic diversity depending on the number of plus trees of Scots pine. Vestnik of Volga State University of Technology. Les. Ekologiya. Prirodopolzovanie. 2018;1(37):33–44. doi: 10.15350/2306-2827.2018.1.33
  167. González-Díaz P., Cavers S., Iason G., Booth A., Russell J., Jump A. S. Weak isolation by distance and geographic diversity gradients persist in Scottish relict pine forest. iForest-Biogeosciences and Forestry. 2018;11:449–458. doi: 10.3832/ifor2454-011
  168. Gladkov Y., Sheykina O. Genetic polymorphism of Scots pine trees from adjacent bawl and dry cenopopulations in nuclear microsatellite loci. Vestnik of Volga State University of Technology. Les. Ekologiya. Prirodopolzovanie. 2019;4(44):70–79 doi: 10.25686/2306-2827.2019.4.70
  169. Shuvaev D.N., Ibe A.A., Shcherba Yu.., Sukhikh T.V., Shilkina E.., Usova .., Lisotova .V., Repyah M.V., Stupakova .. A panel of nuclear microsatellite markers for the identification of Scots pine illegal logs on the Krasnoyarsk territory. Conifers Boreal Area. 2020(38):297–304.
  170. Ganea S., Garcia Gil M.R. Multiplex nuclear SSR amplification in Scots pine (Pinus sylvestris L.). Bulletin UASVM Horticulture. 2011;68(1):47–53.
  171. Ranade S.S., Ganea L.-S., Razzak A.M., García Gil M.R. Fungal infection increases the rate of somatic mutation in Scots pine (Pinus sylvestris L.). Journal of Heredity. 2015;106(4):386–394. doi: 10.1093/jhered/esv017
  172. García Gil M.R., Floran V., Östlund L., Mullin T.J., Andersson Gull B. Genetic diversity and inbreeding in natural and managed populations of Scots pine. Tree Genetics & Genomes. 2015;11(2):1–12. doi: 10.1007/s11295-015-0850-5
  173. Ganea S., Ranade S.S., Hall D., Abrahamsson S., García-Gil M.R. Development and transferability of two multiplexes nSSR in Scots pine (Pinus sylvestris L.). Journal of Forestry Research. 2015;26(2):361–368. doi: 10.1007/s11676-015-0042-z
  174. Bernhardsson C., Floran V., Ganea S.L., García-Gil M.R. Present genetic structure is congruent with the common origin of distant Scots pine populations in its Romanian distribution. Forest Ecology and Management. 2016;361:131–143. doi: 10.1016/j.foreco.2015.10.047
  175. Zimmer K., Sønstebø J.H. A preliminary study on the genetic structure of Northern European Pinus sylvestris L. by means of neutral nuclear microsatellite markers. Scandinavian Journal of Forest Research. 2018;33(1):6–13. doi: 10.1080/02827581.2017.1337919
  176. Nowakowska J.A. Application of DNA markers against illegal logging as a new tool for the Forest Guard Service. Folia Forestalia Polonica. Series A. Forestry. 2011;53(2):142–149.
  177. Nowakowska J.A., Oszako T., Tereba A., Konecka A. Forest tree species traced with a DNA-based proof for illegal logging case in Poland. In: Evolutionary Biology: Biodiversification from Genotype to Phenotype. Cham: Springer International Publishing, 2015. P. 373–388. doi: 10.1007/978-3-319-19932-0_19
  178. Lewandowski A., Kowalczyk J., Litkowiec M., Urbaniak L., Rzońca M. Selection of elite plus trees of Scots pine and European larch for the establishment of 1.5 generation seed orchards. Sylwan. 2017;161(11):917–926.
  179. Konecka A., Tereba A., Bieniek J., Nowakowska J.A. Comparison of the genetic variability of Scots pine trees and their progeny from nursery production based on DNA analyses. Sylwan. 2018;162:32–40.
  180. Konecka A., Tereba A., Studnicki M., Nowakowska J.A. Rare and private alleles as a measure of gene pool richness in Scots pine planting material. Sylwan. 2019;163:948–956. doi: 10.26202/SYLWAN.2019068
  181. Wójkiewicz B., Żukowska W.B., Urbaniak L., Kowalczyk J., Litkowiec M., Lewandowski A. Determination of the origin of the rychtal Scots pine (Pinus sylvestris L.) seed tree stands using microsatellite markers. Sylwan. 2019;163:637–644. doi: 10.26202/SYLWAN.2019059
  182. Kalko G., Kotova T. Real-Time PCR and analysis of amplicon melting curves to assess the suitability of SSR loci of Scots pine for multiplexing. IOP Conference Series: Earth and Environmental Science. 2019;392(1):012015.  doi: 10.1088/1755-1315/392/1/012015
  183. Tereba A., Konecka A. Comparison of microsatellites and SNP markers in genetic diversity level of two Scots pine stands. Environmental Sciences Proceedings. 2021;3(1):1–3. doi: 10.3390/IECF2020-07776
  184. Przybylski P., Mohytych V., Rutkowski P., Tereba A., Tyburski Ł., Fyalkowska K. Relationships between some biodiversity indicators and crown damage of Pinus sylvestris L. in natural old growth pine forests. Sustainability. 2021;13(3):1239. doi: 10.3390/su13031239
  185. Saari S.K., Campbell C.D., Russell J., Alexander I.J., Anderson I.C. Pine microsatellite markers allow roots and ectomycorrhizas to be linked to individual trees. New Phytologist. 2005;165:295–304. doi: 10.1111/j.1469-8137.2004.01213.x
  186. Kerpauskaite V., Danusevicius D., Kavaliauskas D., Fussi B., Konnert M., Baliuckas V., Augustaitis A. A methodological approach for assessment of the spatial genetic structure within Scots pine stands based on DNA markers. In: Rural Development. Kaunas: Aleksandras Stulginskis University, 2013. P. 324–331.
  187. Kavaliauskas D. Genetic Structure and Genetic Diversity of Scots Pine (Pinus sylvestris L.) Populations in Lithuania: PhD Thesis. Kaunas: Aleksandras Stulginskis University, 2015. 146 p.
  188. Danusevičius D., Kavaliauskas D., Fussi B. Optimum sample size for SSR-based estimation of representative allele frequencies and genetic diversity in Scots pine populations. Baltic Forestry. 2016;22:194–202.
  189. Danusevičius D., Buchovska J., Žulkus V., Daugnora L., Girininkas A. DNA markers reveal genetic associations among 11,000-year-old Scots pine (Pinus sylvestris L.) found in the Baltic Sea with the present-day gene pools in Lithuania. Forests. 2021;12(3):317. doi: 10.3390/f12030317
  190. Łabiszak B., Zaborowska J., Wójkiewicz B., Wachowiak W. Molecular and paleo-climatic data uncover the impact of an ancient bottleneck on the demographic history and contemporary genetic structure of endangered Pinus uliginosa. Journal of Systematics and Evolution. 2021;59(3):596–610.
  191. Sobierajska K., Wachowiak W., Zaborowska J., Łabiszak B., Wójkiewicz B., Sękiewicz M., Jasinska A.K., Sekiewicz K., Boratyńska K., Marcysiak K., BoratyŃski A. Genetic consequences of hybridization in relict isolated trees Pinus sylvestris and the Pinus mugo complex. Forests. 2020;11(10):1086. doi: 10.3390/f11101086
  192. Verbylaitė R., Pliūra A., Lygis V., Suchockas V., Jankauskienė J., Labokas J. Genetic diversity and its spatial distribution in self-regenerating Norway spruce and Scots pine stands. Forests. 2017;8(12):470. doi: 10.3390/f8120470
  193. PadutovA.V. Study of the genetic half-sib progeny structure of scots pine clones on forest-seed order II orchads. Molekulyarnaya I Prikladnaya Genetika. 2018;25:92–98.
  194. Torbik D., Bedrickaya T., Vlasova M., Sinelnikov I. Genetic diversity of natural populations of Pinus sylvestris. In: Science - to the Forestry of the North. Arkhangelsk: SevNIILH, 2019. P. 92–99.
  195. Hebda A., Wójkiewicz B., Wachowiak W. Genetic characteristics of Scots pine in Poland and reference populations based on nuclear and chloroplast microsatellite markers. Silva Fennica. 2017;51(2):1721. doi: 10.14214/sf.1721
  196. Pyataev A.S., Ibe A.A., Shilkina E.A. Genetic markers combination calculation in wood samples identification. In: Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes. Berdsk: CEUR, 2019. P. 501–506.
  197. Miao Y., Zhu X., Li Z., Jia F., Li W. Genetic evaluation of breeding resources of Pinus sylvestris var. mongolica from different improved generations. Journal of Beijing Forestry University. 2017;39(12):71–78. doi: 10.13332/j.1000-1522.20170194
Table of Contents Original Article
Math. Biol. Bioinf.
2022;17(1):82-155
doi: 10.17537/2022.17.82
published in English

Abstract (eng.)
Abstract (rus.)
Full text (eng., pdf)
References

 

  Copyright IMPB RAS © 2005-2024