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Physiology and Molecular Biology of Plants

, Volume 25, Issue 3, pp 799–805 | Cite as

Genetic characterization of Portuguese allochthonous populations of Pinus nigra using ISSRs and SCoTs and extrapolation of their infraspecific taxonomy

  • Alexandra Dias
  • Maria Lemos
  • Ivo Pavia
  • Maria João Gaspar
  • Maria Emília Silva
  • José Luís Louzada
  • José Lima-Brito
  • Ana CarvalhoEmail author
Short Communication

Abstract

The Pinus nigra distribution in Portugal is restricted to six allochthonous populations with unknown origin and infraspecific taxonomy. This work intends to evaluate their genetic diversity, structure and relationships, and to infer about their infraspecific taxonomy by comparing molecular patterns produced by inter-simple sequence repeat and Start Codon Targeted markers among Portuguese and foreign samples with known taxonomy and provenance. 127 Portuguese P. nigra individuals were clustered per population. The genetic differentiation was higher within rather than among populations. The pooled molecular data indicated high genetic proximity among the Portuguese and foreign samples of subspecies laricio. However, the separate analysis per marker system demonstrated that two varieties of subspecies laricio (corsicana and calabrica) may have been used in the plantations of the Portuguese P. nigra stands performed in the last century. The genetic characterization and extrapolation of the intraspecific taxonomy of these populations provide useful information for forest management, afforestation and germplasm use.

Keywords

European black pine Genetic structure Infraspecific taxa Molecular markers 

Notes

Acknowledgements

The authors acknowledge to Prof. Bruno Fady (INRA, Avignon, France) and Dr. Marc Calvignac (Vilmorin S.A., La Ménitré, France) that kindly provided dehydrated needles and certified seeds, respectively, representative of different Pinus nigra taxa.

Funding

This study was funded by “Fundação para a Ciência e a Tecnologia” (FCT) (grant SFRH/BD/91781/2012 co-financed by “Fundo Social Europeu” under the POPH-QREN program and projects UID/AGR/04033/2019 (to CITAB/UTAD), UID/MULTI/04046/2019 (to BioISI), and POCI-01-0145-FEDER-006958 - FEDER/COMPETE/POCI – Operational Competitiveness and Internationalization Program (to CITAB/UTAD).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Supplementary material

12298_2019_649_MOESM1_ESM.pdf (114 kb)
Supplementary material 1 (PDF 114 kb)
12298_2019_649_MOESM2_ESM.pdf (11 kb)
Supplementary material 2 (PDF 11 kb)
12298_2019_649_MOESM3_ESM.pdf (65 kb)
Supplementary material 3 (PDF 65 kb)

References

  1. Afzal-Rafii Z, Dodd RS (2007) Chloroplast DNA supports a hypothesis of glacial refugia over postglacial recolonization in disjunct populations of black pine (Pinus nigra) in Western Europe: phylogeography of European black pine. Mol Ecol 16:723–736CrossRefPubMedGoogle Scholar
  2. Akkemik Ü, Yılmaz H, Oral D et al (2010) Some changes in taxonomy of pines (Pinus L.) native to Turkey. J Fac For Istanbul U 61(1):63–78Google Scholar
  3. Alikhani L, Rahmani M-S, Shabanian N et al (2014) Genetic variability and structure of Quercus brantii assessed by ISSR, IRAP and SCoT markers. Gene 552:176–183CrossRefPubMedGoogle Scholar
  4. Barbéro M, Loisel R, Quézel P et al (1998) Pines of the Mediterranean basin. In: Richardson DM (ed) Ecology and biogeography of Pinus. Cambridge University Press, Cambridge, 527 ppGoogle Scholar
  5. Bonavita S, Vendramin GG, Bernardini V et al (2016) The first SSR-based assessment of genetic variation and structure among Pinus laricio Poiret populations within their native area. Plant Biosyst 150:1271–1281CrossRefGoogle Scholar
  6. Cabo S, Ferreira L, Carvalho A et al (2014) Potential of Start Codon Targeted (SCoT) markers for DNA fingerprinting of newly synthesized tritordeums and their respective parents. J Appl Genet 55:307–312CrossRefPubMedGoogle Scholar
  7. Candel Pérez D (2014) Pinus nigra Arn. ssp. salzmannii forest management in the context of climate change: ecological and genetic factors. Tesis Doctoral, Universidad de Castilla-La Mancha, AlbaceteGoogle Scholar
  8. Carvalho A, Matos M, Lima-Brito J et al (2005) DNA fingerprint of F1 interspecific hybrids from the Triticeae tribe using ISSRs. Euphytica 143:93–99CrossRefGoogle Scholar
  9. Christensen K (1997) Pinaceae, Cupressaceae, Taxaceae, Ephedraceae, Salicaceae, Juglandaceae, Betulaceae, Fagaceae, Ulmaceae Moraceae. In: Strid A, Tan K (eds) Flora Hellenica. Koeltz Scientific Books, KönigsteinGoogle Scholar
  10. Cipriano J, Carvalho A, Fernandes C et al (2016) Evaluation of genetic diversity of Portuguese Pinus sylvestris L. populations based on molecular data and inferences about the future use of this germplasm. J Genet 93(2):41–48.  https://doi.org/10.1007/s12041-013-0241-3 CrossRefGoogle Scholar
  11. Collard BCY, Mackill DJ (2009) Start Codon Targeted (SCoT) Polymorphism: a simple, novel DNA marker technique for generating gene-targeted markers in plants. Plant Mol Biol Rep 27:86–93CrossRefGoogle Scholar
  12. Dias A, Gaspar MJ, Carvalho A et al (2018) Within- and between-tree variation of wood density components in Pinus nigra at six sites in Portugal. Ann For Sci 75:58.  https://doi.org/10.1007/s13595-018-0734-6 CrossRefGoogle Scholar
  13. Doyle JJ, Doyle JL (1987) A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem Bull 19:11–15Google Scholar
  14. Earl DA, vonHoldt BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4:359–361CrossRefGoogle Scholar
  15. Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131(2):479–491PubMedPubMedCentralGoogle Scholar
  16. Falush D, Stephens M, Pritchard JK (2007) Inference of population structure using multilocus genotype data: dominant markers and null alleles: technical article. Mol Ecol Notes 7:574–578CrossRefPubMedPubMedCentralGoogle Scholar
  17. Farjon A (1998) World checklist and bibliography of conifers. Royal Botanic Gardens, KewGoogle Scholar
  18. Farjon A (2010) A handbook of The World’s Conifers, vol 1. Brill Leiden, BostonCrossRefGoogle Scholar
  19. Felsenstein J (1985) Confidence limits on phylogenies: an approach using the bootstrap. Evolution 39:783–791CrossRefGoogle Scholar
  20. Gaussen H, Heywood VH, Chater AO (1964) The genus Pinus L. In: Tutin TG, Heywood VH, Burgers NA, Valentine DH, Walters SM, Webb DA (eds) Flora Europaea, vol 1. Cambridge University Press, Cambridge, pp 32–35Google Scholar
  21. Giovannelli G, Roig A, Spanu I et al (2017) A new set of nuclear microsatellites for an ecologically and economically important conifer: the European Black Pine (Pinus nigra Arn.). Plant Mol Biol Rep 35(3):379–388CrossRefGoogle Scholar
  22. Hamrick JL, Godt MJW, Sherman-Broyles SL (1992) Factors influencing levels of genetic diversity in woody plant species. New For 6:95–124CrossRefGoogle Scholar
  23. Hedges SB (1992) The number of replications needed for accurate estimation of the bootstrap p value in phylogenetic studies. Mol Biol Evol 9:366–369PubMedGoogle Scholar
  24. Liber Z, Nikolic T, Mitic B et al (2003) RAPD markers and black pine (Pinus nigra Arnold) intraspecies taxonomy-evidence from the study of nine populations. Acta Soc Bot Pol 72:249–257CrossRefGoogle Scholar
  25. Little E, Critchfield W (1969) Subdivisions of the genus Pinus (Pines). U.S. Department of Agriculture Forest Services, Miscellaneous Publications, WashingtonGoogle Scholar
  26. Louro V (1982) O pinheiro larício: Pinus nigra Arnold em Portugal. Direcção Geral do Ordenamento e Gestao Florestal, LisboaGoogle Scholar
  27. Lucas Borja ME, Candel Pérez D, Molero Carrasco J et al (2013) Utilización de los marcadores ISSR para la determinación de diversidad genética en poblaciones de Pinus nigra Arn.. 6º Congreso Forestal Español, 10-14 junio 2013, Vitoria-Gasteiz, pp 1–10. ISBN: 978-84-937964-9-5Google Scholar
  28. Naydenov KD, Tremblay FM, Fenton NJ et al (2006) Structure of Pinus nigra Arn. populations in Bulgaria revealed by chloroplast microsatellites and terpenes analysis: provenance tests. Biochem Syst Ecol 34:562–574CrossRefGoogle Scholar
  29. Peakall R, Smouse PE (2006) GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol Ecol Notes 6:288–295CrossRefGoogle Scholar
  30. Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update. Bioinformatics 28:2537–2539CrossRefPubMedPubMedCentralGoogle Scholar
  31. Price RA, Liston A, Strauss SH (1998) Phylogeny and systematics of Pinus. In: Richardson DM (ed) Ecology and biogeography of Pinus. Cambridge University Press, London, pp 49–68Google Scholar
  32. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedPubMedCentralGoogle Scholar
  33. Reis E (1997) Estatística multivariada aplicada. Edições Sílabo, Lda., LisboaGoogle Scholar
  34. Rohlf FJ (1998) NTSYS-pc ver. 2.02. Numerical taxonomy and multivariate analysis system. Exeter Publishing, SetauketGoogle Scholar
  35. Rubio Moraga A, Candel Pérez D, Lucas Borja ME et al (2012) Genetic diversity of Pinus nigra Arn. populations in Southern Spain and Northern Morocco revealed by Inter-Simple Sequence Repeat profiles. Int J Mol Sci 13:5645–5658CrossRefPubMedPubMedCentralGoogle Scholar
  36. Šarac Z, Aleksic J, Dodos T et al (2015) Cross-species amplification of nuclear EST-microsatellites developed for other Pinus species in Pinus nigra. Genetika 47:205–217CrossRefGoogle Scholar
  37. Savolainen O, Pyhäjärvi T, Knürr T (2007) Gene flow and local adaptation in trees. Annu Rev Ecol Evol Syst 38:595–619CrossRefGoogle Scholar
  38. Scaltsoyiannes A, Rohr R, Panetsos KP, Tsaktsira M (1994) Allozyme frequency distributions in 5 European populations of black pine (Pinus nigra Arnold). 1. Estimation of genetic variation within and among populations. 2. Contribution of isozyme analysis to the taxonomic status of the species. Silvae Genet 43:20–30Google Scholar
  39. Yap I, Nelson R (1996) Winboot: a program for performing bootstrap analysis of binary data to determine the confidence limits of UPGMA-based dendrograms. International Rice Research Institute (IRRI), ManilaGoogle Scholar
  40. Yeh FC, Yang RC, Boyle TB et al (1999) POPGENE version 1.32, the user-friendly shareware for population genetic analysis. Molecular Biology and Biotechnology Centre, University of Alberta, EdmontonGoogle Scholar
  41. Zhang J, Xie W, Wang Y et al (2015) Potential of Start Codon Targeted (SCoT) markers to estimate genetic diversity and relationships among Chinese Elymus sibiricus accessions. Molecules 20:5987–6001CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Prof. H.S. Srivastava Foundation for Science and Society 2019

Authors and Affiliations

  1. 1.Center of Research and Technology of Agroenvironmental and Biological Sciences (CITAB)University of Tras-os-Montes and Alto DouroVila RealPortugal
  2. 2.University of Tras-os-Montes and Alto DouroVila RealPortugal
  3. 3.BioISI - Biosystems & Integrative Sciences Institute, University of Tras-os-Montes and Alto Douro (BioISI/UTAD)Vila RealPortugal
  4. 4.Forest Research Centre (CEF), Instituto Superior de Agronomia (ISA)University of LisbonLisbonPortugal
  5. 5.Department of Genetics and Biotechnology (DGB), Ed. Blocos Laboratoriais, A1.09University of Tras-os-Montes and Alto DouroVila RealPortugal

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