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28 September 2017 Fungus-Specific SSR Markers in the Antarctic Lichens Usnea antarctica and U. aurantiacoatra (Parmeliaceae, Ascomycota)
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Lichens constitute an important component of Antarctic terrestrial biota. The most common lichen species in the maritime Antarctic are Usnea aurantiacoatra (Jacq.) Bory and U. antarctica Du Rietz (Lecanoromycetes, Parmeliaceae). The two species occupy similar habitats but show different dispersal strategies, morphology, and distribution. Usnea antarctica usually propagates asexually by so-called soredia, while U. aurantiacoatra has apothecia and its thalli are usually larger. Usnea antarctica is reported to be circumpolar and to have the widest ecological amplitude and distribution of any Antarctic macrolichen (Øvstedal & Lewis Smith, 2001), while U. aurantiacoatra is absent from the continental Antarctic. Phylogenetic analysis, performed on several Southern Hemisphere Usnea Dill. ex Adans. species, showed that the two species are closely related, and they are considered a single group. Some authors have suggested that the two species might constitute a species pair, in which U. aurantiacoatra represents the fertile and U. antarctica the sterile counterpart, but phylogenetic studies indicated that they could be conspecific (Wirtz et al., 2012). Here, we developed highly variable microsatellite loci to better understand the genetic differences between the two lichen species and to investigate gene flow between maritime Antarctica and South America.


Total genomic DNA was extracted from a thallus of U. antarctica from population C1 and from one thallus of U. aurantiacoatra from a population that was not included in the later primer design (Appendix 1) from King George Island, Antarctica, in the austral summer of 2015/2016. Twenty milligrams of thallus were pretreated with acetone to remove secondary metabolites and ground with liquid nitrogen using a sterilized mortar and pestle. DNA was extracted using a modified cetyltrimethylammonium bromide (CTAB) protocol (Cubero and Crespo, 2002). Paired-end libraries (300 bp) were prepared and sequenced on a MiSeq version 3 (2 × 300-bp) Illumina sequencer (LGC Genomics GmbH, Berlin, Germany).

We obtained 3,098,758 raw reads for U. antarctica and 1,755,882 for U. aurantiacoatra. Raw data were adapter-, quality- (PHREAD = 26), and length- (>150 bp) filtered using Trimmomatic version 0.35 (Bolger et al., 2014). Forward and reverse reads were assembled with Paired-End reAd mergeR (PEAR) software (Zhang et al., 2014). The resulting overlapping, paired, and singleton reads were then assembled with SPAdes version 3.9 (Nurk et al., 2013). Scaffolds were taxonomically binned using Metawatt (Strous et al., 2012). Scaffolds assigned to the phylum Ascomycota were used to search for mycobiont-specific microsatellite motifs. Simple sequence repeat (SSR) motifs repeated at least six times were searched in both genomes with the MIcroSAtellite Identification Tool (MISA) (Thiel et al., 2003), and primers were designed for 3–4-bp repeats using the Primer3 plugin in Geneious 10 (Kearse et al., 2012). A total of 150 SSRs were identified in the two species. Each repeat from one genome was BLASTed against the other genome. Due to the partial coverage of both genomes, only 30 SSRs were found to share the same flanking regions in silico. We designed primers for these 30 markers and tested them on four samples of U. antarctica and U. aurantiacoatra in single touchdown PCR reactions. After sequencing we selected 23 markers (Table 1) with perfectly matching flanking regions to be tested in multiplex reactions and on algal pure cultures to confirm that they were fungal specific. The remaining seven markers were excluded because of insertions and/or deletions in the flanking regions.

A fluorescent dye-associated tag was attached to the forward primers. Four different tails were selected to multiplex the reactions (FAM: GCCTCCCTCGCGCCA, VIC: GCCTTGCCAGCCCGC, NED: CAGGACCAGGCTACCGTG, PET: CGGAGAGCCGAGAGGTG) (Blacket et al., 2012). PCRs were performed in 25-µL reactions using illustra PuReTaq Ready-To-Go PCR Beads (GE Healthcare Life Sciences, Little Chalfont, Buckinghamshire, United Kingdom) according to the manufacturer's protocol with the following touchdown conditions: initial hot start at 94°C for 15 min; five cycles of 94°C for 45 s, 65°C for 45 s, 72°C for 45 s; five cycles of 94°C for 45 s, 60°C for 45 s, 72°C for 45 s; 10 cycles of 94°C for 45 s, 57°C for 45 s, 72°C for 45 s; 20 cycles of 94°C for 45 s, 55°C for 45 s, 72°C for 45 s; and final elongation at 72°C for 15 min. The PCR products were sent to Macrogen Europe (Amsterdam, The Netherlands) for sequencing to check the stability of the flanking regions in both species. To confirm that the chosen SSRs are indeed fungal loci, the primers were also tested on four axenic cultures of Trebouxia jamesii (Hildreth and Ahmadjian) Gärtner isolated from U. antarctica, U. aurantiacoatra, U. lambii (Imshaug) Wirtz & Lumbsch, and U. trachycarpa (Stirt.) Müll. Arg. (Appendix 1). The PCRs were performed under the same conditions as above, and no amplifications were observed.

Table 1.

Characteristics of 23 fungus-specific SSR primers developed for Usnea antarctica and U. aurantiacoatra.a


After fungal specificity of the primers was confirmed, 77 samples from two populations of U. antarctica and U. aurantiacoatra (sampled in the same areas on King George Island) were chosen to evaluate the variability of the markers. All samples were tested with multiplexed PCRs of seven to eight markers with the Type-it Multiplex Kit (QIAGEN, Hilden. Germany). PCR reactions were conducted in 10-µL volumes containing 1.5 µg of genomic DNA, 5 µL of PCR Master Mix, and 3 µL of primer multiplex (0.25 µM of each forward primer and fluorescent dye, 0.125 µM of each reverse primer). PCR products were amplified using the same touchdown program as above. PCR amplicons were electrophoresed using an Applied Biosystems 3730 platform, with the LIZ 600 Size Standard (Applied Biosystems, Foster City, California, USA), and allele sizes were manually scored using the Geneious 10 microsatellite tool (Kearse et al., 2012).

Table 2.

Allelic richness and genetic diversity of SSR loci in four populations of Usnea spp. collected on King George Island.a


The variability of each microsatellite locus was measured by counting the number of alleles and calculating Nei's unbiased gene diversity using GenAlEx 6.5 (Peakall and Smouse, 2012). All of the 23 markers amplified in both species. In U. aurantiacoatra, all of the SSR markers were polymorphic, while five were monomorphic in U. antarctica (Table 2).

Linkage disequilibrium was tested with GENEPOP (Raymond and Rousset, 1995; Rousset, 2008) twice: separately for each species to estimate P values and with the two species together to perform a global test (Fisher's method) for each pair of loci across populations and species. Holm-Bonferroni correction (Holm, 1979) of the P values resulting from the last test using the implementation by Gaetano (2013) revealed significant evidence for linkage disequilibrium between loci Ua3, Ua4, and Ua6 (Ua3–Ua4: P = 0.001, Ua3–Ua6: P = 0.006, Ua4–Ua6: P = 0.0).

Cross-species amplification was tested on DNA extracts of U. sphacelata R. Br. and U. trachycarpa, two related species from Usnea subgenus Neuropogon (Nees & Flotow) Jatta (Truong et al., 2013). First, we tested a population of eight samples of U. sphacelata with the multiplex protocol. To verify the identity and stability of the flanking regions, we then selected two samples with different peaks for single PCR amplification and sequencing. The multiplex analysis was omitted for U. trachycarpa. Thirteen markers showed the same flanking regions in all three species, five markers had deletions and/or insertions in the flanking regions in U. sphacelata and U. trachycarpa, and for four markers the PCRs failed. Marker Ua18 shared the flanking region only with U. sphacelata, while it had a deletion in U. trachycarpa (Table 3).

Table 3.

Cross-amplification of SSR markers developed for Usnea antarctica and U. aurantiacoatra with related species of Usnea subgenus Neuropogon.



The markers developed here are suitable to study population structure and gene flow in U. antarctica and U. aurantiacoatra. The markers shared the same flanking regions in the two species and showed high variability even within a small geographic area. Nineteen of these microsatellite primers also cross-amplify in related species from Usnea subgenus Neuropogon; however, the flanking regions of some markers are less stable. The usability of the newly developed SSR markers for cross-amplification in other Usnea species therefore requires further validation using a broader taxon sampling and a higher number of replicates per species. We conclude that the newly developed SSR markers presented here can be used to infer gene flow within Southern Hemisphere lichen populations and resolve connectivity patterns among populations of U. antarctica and U. aurantiacoatra.


The authors thank the staff of the Alfred Wegener Institute (AWI; Bremerhaven, Germany) and the Argentinian research station Carlini (KGI) for logistic support. This work was supported by the Deutsche Forschungsgemeinschaft (DFG) in the framework of the priority program “Antarctic Research with comparative investigations in Arctic ice areas” by grant PR 567/18-1.


  1. Blacket, M. J., C. Robin, R. T. Good, S. F. Lee, and A. D. Miller. 2012. Universal primers for fluorescent labelling of PCR fragments—An efficient and cost-effective approach to genotyping by fluorescence. Molecular Ecology Resources 12: 456–463. Google Scholar

  2. Bolger, A. M., M. Lohse, and B. Usadel. 2014. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114–2120. Google Scholar

  3. Cubero, O. F., and A. Crespo. 2002. Isolation of nucleic acids from lichens. In I. C. Kranner, R. P. Beckett, and A. K. Varma [eds.], Protocols in lichenology: Culturing, biochemistry, ecophysiology, and use in biomonitoring, 381–391. Springer, Berlin, Germany. Google Scholar

  4. Gaetano, J. 2013. Holm-Bonferroni sequential correction: An Excel calculator (1.2). Website 242331583_Holm-Bonferroni_Sequential_Correction_An_EXCEL_ Calculator_-_Ver._1.2 [accessed 8 June 2017]. Google Scholar

  5. Holm, S. 1979. A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics 6: 65–70. Google Scholar

  6. Kearse, M., R. Moir, A. Wilson, S. Stones-Havas, M. Cheung, S. Sturrock, S. Buxton, et al. 2012. Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28: 1647–1649. Google Scholar

  7. Nurk, S., A. Bankevich, D. Antipov, A. A. Gurevich, A. Korobeynikov, A. Lapidus, A. D. Prjibelski, et al. 2013. Assembling genomes and mini-metagenomes from highly chimeric reads. In M. Deng, R. Jiang, F. Sun, and X. Zhang [eds.], Research in computational molecular biology, vol. 7821, 158–170. Springer, Berlin, Germany. Google Scholar

  8. Øvstedal, D. O., and R. I. Lewis Smith. 2001. Lichens of Antarctica and South Georgia. Studies in Polar Research. Cambridge University Press, Cambridge, United Kingdom. Google Scholar

  9. Peakall, R., and P. E. Smouse. 2012. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research–An update. Bioinformatics 28: 2537–2539. Google Scholar

  10. Raymond, M., and F. Rousset. 1995. GENEPOP (version 1.2): Population genetics software for exact tests and ecumenicism. Journal of Heredity 86: 248–249. Google Scholar

  11. Rousset, F. 2008. GENEPOP'007: A complete reimplementation of the GENEPOP software for Windows and Linux. Molecular Ecology Resources 8: 103–106. Google Scholar

  12. Strous, M., B. Kraft, R. Bisdorf, and H. E. Tegetmeyer. 2012. The binning of metagenomic contigs for microbial physiology of mixed cultures. Frontiers in Microbiology 3: 410. Google Scholar

  13. Thiel, T., W. Michalek, R. K. Varshney, and A. Graner. 2003. Exploiting EST databases for the development and characterization of genederived SSR-markers in barley (Hordeum vulgare L.). Theoretical and Applied Genetics 106: 411–422. Google Scholar

  14. Truong, C., P. K. Divakar, R. Yahr, A. Crespo, and P. Clerc. 2013. Testing the use of ITS rDNA and protein-coding genes in the generic and species delimitation of the lichen genus Usnea (Parmeliaceae, Ascomycota). Molecular Phylogenetics and Evolution 68: 357–372. Google Scholar

  15. Wirtz, N., C. Printzen, and H. T. Lumbsch. 2012. Using haplotype networks, estimation of gene flow and phenotypic characters to understand species delimitation in fungi of a predominantly Antarctic Usnea group (Ascomycota, Parmeliaceae). Organisms Diversity and Evolution 12: 17–37. Google Scholar

  16. Zhang, J., K. Kobert, T. Flouri, and A. Stamatakis. 2014. PEAR: A fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30: 614–620. Google Scholar


Appendix 1.

Locality and collection data for Usnea samples used in this study.

Elisa Lagostina, Francesco Dal Grande, Sieglinde Ott, and Christian Printzen "Fungus-Specific SSR Markers in the Antarctic Lichens Usnea antarctica and U. aurantiacoatra (Parmeliaceae, Ascomycota)," Applications in Plant Sciences 5(9), (28 September 2017).
Received: 19 May 2017; Accepted: 1 July 2017; Published: 28 September 2017

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