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Development of novel polymorphic nuclear and chloroplast microsatellite markers in coast redwood (Sequoia sempervirens)

Published online by Cambridge University Press:  04 December 2018

Natalie Breidenbach ,
Oliver Gailing  and
Konstantin V. Krutovsky Open the ORCID record for Konstantin V. Krutovsky [Opens in a new window]
Natalie Breidenbach
Affiliation:
Department of Forest Genetics and Forest Tree Breeding, Georg-August University of Göttingen, Büsgenweg 2, Göttingen 37077, Germany
Oliver Gailing
Affiliation:
Department of Forest Genetics and Forest Tree Breeding, Georg-August University of Göttingen, Büsgenweg 2, Göttingen 37077, Germany
Konstantin V. Krutovsky*
Affiliation:
Department of Forest Genetics and Forest Tree Breeding, Georg-August University of Göttingen, Büsgenweg 2, Göttingen 37077, Germany Laboratory of Population Genetics, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119991, Gubkina Str. 3, Russian Federation Laboratory of Forest Genomics, Genome Research and Education Center, Institute of Fundamental Biology and Biotechnology, Siberian Federal University, Akademgorodok 50a/2, Krasnoyarsk 660036, Russian Federation Department of Ecosystem Sciences and Management, Texas A&M University, College Station, Texas 77843-2138, USA
*
*Corresponding author. E-mail: [email protected]
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Abstract

The range-wide genetic structure of the highly productive and valuable timber species Sequoia sempervirens (D. Don) Endl. is still insufficiently studied, although published data based on different genetic markers (nuclear and chloroplast microsatellites, AFLP, RFLP and isozymes) demonstrated relatively low population structure. However, more genetic markers are needed to increase the efficiency of population genetic studies in coast redwood. Therefore, we developed seven nuclear and five chloroplast microsatellite or simple sequence repeat (SSR) markers based on expressed sequence tags (ESTs) and the complete chloroplast genome sequence, respectively. All selected markers were tested in a range-wide sample representing trees from 16 locations. They are highly polymorphic microsatellite loci with the number of alleles ranging from 3 to 17, and the number of effective alleles from 1.1 to 2.48. Coast redwood is a hexaploid species, and its chloroplasts are paternally inherited. Therefore, the chloroplast SSR markers are especially useful for this species, because their genotyping is not affected by nuclear genome ploidy. Moreover, they showed high gene diversity for each locus within and across all populations and can be used to study range-wide population genetic structure, pollen-based gene flow and long-distance gene transfer. Coast redwood can propagate clonally, and nuclear polymorphic EST-SSRs can be used for clonal identification. They are linked with expressed genes and their variation can reflect variation in genes under selection, including those that could be potentially important for local adaptation of coast redwood considering the threat of climate change.

Keywords

coast redwoodcpSSREST-SSRmicrosatellitesSequoia sempervirens
Type
Short Communication
Information
Plant Genetic Resources , Volume 17 , Issue 3 , June 2019 , pp. 293 - 297
Copyright
Copyright © NIAB 2018 

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References

Bouk, A and Vision, T (2007) The molecular ecologist's guide to expressed sequence tags. Molecular Ecology 16: 907–924.Google Scholar
Brinegar, C (2011) Rangewide genetic variation in coast redwood populations at a chloroplast microsatellite locus. In: Standiford, RB, Weller, TJ, Piierto, DD and Stuart, JD (eds) Proceedings of the Coast Redwood Forests in A Changing California: A Symposium for Scientists and Managers. USDA Forest Service General Technical Report PSW-GTR-238. Albany, California, USA: USDA Forest Service, Pacific Southwest Research Station, pp. 241–249.Google Scholar
Bucci, G, Gonzalez-Martinez, SC, Le Provost, G, Plomion, C, Ribeiro, MM, Sebastiani, F, Alía, R and Vendramin, GG (2007) Range-wide phylogeography and gene zones in Pinus pinaster Ait. revealed by chloroplast microsatellite markers. Molecular Ecology 16: 2137–2153.Google Scholar
Clark, L and Jasieniuk, M (2011) Polysat: an R package for polyploid microsatellite analysis. Molecular Ecology Resources 11: 562–566.Google Scholar
Douhovnikoff, V and Dodd, RS (2011) Lineage divergence in coast redwood (Sequoia sempervirens), detected by a new set of nuclear microsatellite loci. The American Midland Naturalist 165: 22–37.Google Scholar
Douhovnikoff, V, Cheng, AM and Dodd, RS (2004) Incidence, size and spatial structure of clones in second-growth stands of coast redwood, Sequoia sempervirens (Cupressaceae). American Journal of Botany 91: 1140–1146.Google Scholar
Euyal, I, Sorrells, M, Baum, M, Wolters, P and Powell, W (2001) Assessment of genotypic variation among cultivated durum wheat based on EST-SSRs and genomic SSRs. Euphytica 119: 39–43.Google Scholar
Goudet, J and Jombart, T (2015) hierfstat: Estimation and Tests of Hierarchical F-Statistics. R-package version 0.04-22. https://CRAN.R-project.org/package=hierfstat.Google Scholar
Hall, GD and Langenheim, JH (1987) Geographic variation in leaf monoterpenes of Sequoia sempervirens. Biochemical Systematics and Ecology 15: 31–43.Google Scholar
Hoffmann, JI and Amos, W (2005) Microsatellite genotyping errors: detection approaches, common sources and consequences for paternal exclusion. Molecular Ecology 14: 599–612.Google Scholar
Ibañez, MT, Caru, M, Herrera, MA, Gonzalez, L, Martin, LM, Miranda, J and Navarro-Cerrillo, RM (2009) Clones identification of Sequoia sempervirens (D.Don) Endl. in Chile by using PCR-RAPDs technique. Journal of Zheijang University Science B 10: 112–119.Google Scholar
Kibbe, WA (2007) Oligocalc: an online oligonucleotide properties calculator. Nucleic Acids Research 35: W43–W46.Google Scholar
Kofler, R, Schlötterer, C and Lelley, T (2007) Sciroko: a new tool for whole genome microsatellite search and investigation. Bioinformatics Application Notes 23: 1683–1685.Google Scholar
Kubisiak, TL, Nelson, CD, Staton, ME, Zhebentyayeva, T, Smith, C, Olukolu, BA, Fang, G-C, Hebard, FV, Anagnostakis, S, Wheeler, N, Sisco, PH, Abbott, AG and Sederoff, RR (2013) A transcriptome-based genetic map of Chinese chestnut (Castanea mollissima) and identification of regions of segmental homology with peach (Prunus persica). Tree Genetics & Genomes 9: 557–571.Google Scholar
Narayan, L, Dodd, RS and O'Hara, KL (2015) A genotyping protocol for multiple tissue types from the polyploidy tree species Sequoia sempervirens (Cupressaceae). Applications in Plant Science 3: 1400110.Google Scholar
Neale, D, Marshall, K and Sederoff, R (1989) Chloroplast and mitochondrial DNA are paternally inherited in Sequoia sempervirens D.Don.Endl. Proceedings of the National Academy of Science 86: 9347–9349.Google Scholar
Nybom, H (2004) Comparison of different nuclear DNA markers for estimating intraspecific genetic diversity in plants. Molecular Ecology 13: 1143–1155.Google Scholar
Peakall, R and Smouse, PE (2006) GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6: 288–295.Google Scholar
Peakall, R and Smouse, PE (2012) Genalex 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics (Oxford, England) 28: 2537–2539.Google Scholar
Pfeiffer, T, Roschanski, AM, Pannell, JR, Korbecka, G and Schnittler, M (2011) Characterization of microsatellite loci and reliable genotyping in a polyploidy plant Mercurialis perennis (Euphorbiaceae). Journal of Heredity 102: 479–488.Google Scholar
Rogers, DL (2000) Genotypic diversity and clone size in old-growth populations of coast redwood (Sequoia sempervirens). Canadian Journal of Botany 78: 1408–1419.Google Scholar
Roy, DF (1966) Silvical characteristics of redwood (Sequoia sempervirens [D. Don] Endl.). USDA Forest Service Research Paper PSW-28. Berkeley, California, USA: Pacific Southwest Forest and Range Experiment Station. 20 pp.Google Scholar
Rungis, D, Bérubé, Y, Zhang, J, Ralph, S, Ritland, CE, Ellis, BE, Douglas, C, Bohlmann, J and Ritland, K (2004) Robust single sequence repeat markers for spruce (Picea spp.) from expressed sequence tags. Theoretical and Applied Genetics 109: 1283–1294.Google Scholar
Schuelke, M (2000) An economic method for the fluorescent labelling of PCR fragments. Nature Biotechnology 18: 233–234.Google Scholar
Scott, AD, Stenz, NWM, Ingvarsson, PK and Baum, DA (2016) Whole genome duplication in coast redwood (Sequoia sempervirens) and its implications for explaining the rarity of polyploidy in conifers. New Phytologist 211: 186–193.Google Scholar
Stebbin, GL Jr (1948) The chromosomes and relationships of Metasequoia and Sequoia. Science 108: 95–98.Google Scholar
Untergasser, A, Cutcutache, I, Koressaar, T, Ye, J, Faircloth, BC, Remm, M and Rozen, SG (2012) Primer3-new capabilities and interfaces. Nucleic Acids Research 40: e115.Google Scholar
Vendramin, GG, Degen, B, Petit, RJ, Anzidei, M, Madaghiele, A and Ziegenhagen, B (1999) High level of variation at Abies alba chloroplast microsatellite loci in Europe. Molecular Ecology 8: 1117–1126.Google Scholar
Viard, F, El-Kassaby, YA and Ritland, K (2001) Diversity and genetic structure in populations of Pseudotsuga menziesii (Pinaceae) at chloroplast microsatellite loci. Genome 44: 336–344.Google Scholar
Yeh, FC, Yang, RC, Boyle, TBJ, Ye, Z and Mao, JK (1997) Popgene, the user friendly shareware for population genetic analysis. Alberta, Canada: Molecular Biology and Biotechnology Centre, University of Alberta. Available at https://sites.ualberta.ca/~fyeh/popgene.htmlGoogle Scholar
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