Translator Disclaimer
29 August 2014 Microsatellite Primers for the Gynodioecious Grassland Perennial Saxifraga granulata (Saxifragaceae)
Author Affiliations +

The genus Saxifraga L. consists of about 400 species that are mainly distributed across the arctic and northern temperate zones (Gornall, 1987). Species within this genus are morphologically very diverse and occur in a wide range of habitats, including grasslands, woodland margins, tundra vegetation, and rocky slopes. Saxifraga granulata L. is an insect-pollinated, perennial, rosette-forming herb that can reproduce sexually and clonally, by formation of small bulbils at the base of the plant, and has been described as being gynodioecious (Stevens and Richards, 1985; Stevens, 1988). Saxifraga granulata mainly occurs in mesic to dry grasslands in Western Europe and North Africa (Andersson, 1996). In Belgium, most populations can be found in riparian meadows and grasslands along river systems. In recent decades, many populations throughout Europe have become smaller and more isolated due to habitat loss and fragmentation (Walisch et al., 2012). Because of the species' close association with riparian habitats in Belgium, rivers can be expected to be important in maintaining genetic connectivity of increasingly isolated populations. The nine polymorphic microsatellite markers presented here will be used to assess how rivers affect levels of gene flow and consequently shape the genetic diversity and structure of riparian plant populations, and to estimate whether levels of gene flow between populations are sufficient to maintain genetic diversity within populations.


Leaf samples of four individuals from four different populations were collected during the flowering season of 2012. All populations were located in central Belgium, were at least 1 km and at most 11 km apart, and contained more than 300 individuals. DNA was extracted from ∼20 mg of dried plant material that was homogenized to a fine powder using a grinder (Mini Bead-Beater-16, BioSpec Products, Bartlesville, Oklahoma, USA) and 10 small ceramic beads (MagNA Lyser Green Beads, Roche, Basel, Switzerland). Genomic DNA was extracted using the DNeasy Plant Mini Kit (QIAGEN, Hilden, Germany), and DNA concentration and quality were measured using a NanoDrop ND-1000 spectrophotometer (Thermo Scientific, Wilmington, Delaware, USA). The purified genomic DNA, of four individuals from different populations, was mixed in equimolar ratio and used for further analyses. The DNA was prepared for an Illumina paired-end (IPE) shotgun library according to the manufacturer's guidelines (Illumina, San Diego, California, USA) and run on a HiSeq 2000 system (Illumina). The reads were imported in PAL Finder version 0.02.04 software (Castoe et al., 2012) to extract simple sequence repeats (SSRs) and to develop primer pairs for amplification. The sequence data generated in this study has been deposited at the National Center for Biotechnology Information (NCBI) in the Sequence Read Archive (SRA) database (accession no.: SRX665162). Forty primer pairs were designed (two with tetra-, 16 with tri-, and 22 with dinucleotide repeats) and tested for amplification quality and polymorphism. A total of 21 loci, nine polymorphic and 12 monomorphic, were selected after amplification in 25 individuals from five populations (Table 1). Sampled individuals were at least 1 m apart to avoid collecting clones.

The nine polymorphic primer pairs were then optimized into two PCR multiplex reactions and further tested on 100 individuals from five populations collected along the Dijle River in central Belgium (Table 2). Both PCR multiplexes were performed in a 2720 Thermal Cycler (Applied Biosystems, Carlsbad, California, USA) with Saxgra-06, Saxgra-09, Saxgra-22, Saxgra-33, and Saxgra-38 in the first multiplex and Saxgra-10, Saxgra-16, Saxgra-23, and Saxgra-29 in the second multiplex. The total PCR multiplex reaction volume contained 5 µL of QIAGEN Multiplex PCR Master Mix (QIAGEN), 3 µL of RNase-free water, 1 µL of one of the two multiplexed primer combinations, and 1 µL of template DNA. Both PCR multiplexes followed the same thermocycler program with initial denaturation of 15 min at 95°C; 27 cycles of 30 s at 95°C, 1.5 min at 58°C, and 1 min at 72°C; and a final elongation of 30 min at 60°C. Then, 1 µL of the PCR reaction was added to a solution of 8.8 µL formamide and 0.2 µL of GeneScan 500 LIZ Size Standard (Applied Biosystems). Fragments were sized on an ABI Prism and analyzed by capillary electrophoresis using the 3130-Avant Genetic Analyzer (Applied Biosystems). The raw genetic data were scored using GeneMapper software version 4.0 (Applied Biosystems) using the default settings for microsatellites. Panels and bins were manually constructed, and all data were visually checked to make sure that the loci were identified correctly.

Table 1.

Characterization of 21 microsatellite loci developed for Saxifraga granulata.a


Genotypes at locus Saxgra-06 consisted of a maximum of eight different alleles, whereas genotypes at loci Saxgra-22, Saxgra-33, and Saxgra-38 consisted of no more than six alleles. At loci Saxgra-09, Saxgra-10, Saxgra-16, Saxgra-23, and Saxgra-29, we found genotypes that consisted of three to five alleles. It was known that S. granulata is polyploid; Redondo et al. (1996) mention 52 chromosomes, and older data give chromosome numbers ranging from 46 to 60 chromosomes, assuming a basic number of x = 8 (Philp, 1934; Darlington and Wylie, 1955). In many polyploid systems, diploid and polyploid cytotypes differ in geographical distribution (Lewis, 1980). Based on the maximum number of alleles per locus per genotype, we assumed that S. granulata is octoploid in the study area for further analyses. Furthermore, as allele combinations were completely random, S. granulata is most likely an autopolyploid rather than an allopolyploid. Allopolyploids usually display disomic inheritance due to pairing of homologue chromosomes (i.e., fixed heterozygosity), while allopolyploids show random chromosome pairing with one of its seven homologues in octoploid species (Trapnell et al., 2011).

As a result of the polyploid nature of S. granulata in the study area, population genetic data were analyzed using the program GenoDive 2.0 (Meirmans and van Tienderen, 2004). Three measures of genetic diversity (Nei, 1987) were calculated and corrected for unknown dosage of alleles: the number of alleles, the effective number of alleles, and gametic heterozygosity (Hs; Moody et al., 1993). Genetic diversity of the microsatellite loci studied in five populations of S. granulata was high. The number of alleles varied between three and 18 (mean = 6.7; Table 2) and the number of effective alleles (i.e., the number of alleles in a population weighted for their frequencies) varied between 1.3 and 13.6 (mean = 4.0; Table 2). Gametic heterozygosity, which is equivalent to the expected heterozygosity in diploid species (Meirmans and Hedrick, 2011), varied between 0.26 (at locus Saxgra-16) and 0.94 (at locus Saxgra-06; Table 2). Six out of nine loci (Saxgra-06, Saxgra-10, Saxgra-16, Saxgra-22, Saxgra-23, and Saxgra-38) showed significant negative deviations from Hardy–Weinberg equilibrium (HWE) based on calculations of inbreeding coefficient GIS, performed with 9999 permutations. Negative GIS values indicate an excess of heterozygous genotypes. Loci Saxgra-09, Saxgra-29, and Saxgra-33 showed no significant deviation from HWE.

Table 2.

Characterization of nine polymorphic loci tested in five Saxifraga granulata populations.a,b



The nine newly developed microsatellite markers are the first reported for S. granulata and are especially suitable for population genetic studies due to the highly polymorphic character of the loci. The markers will be used for studying genetic diversity and spatial genetic structure of populations along river systems and to assess levels of gene flow between populations. We expect that these microsatellite markers will provide critical insights into the processes affecting genetic diversity and therefore will contribute to the conservation of this declining species in Europe.



S. Andersson 1996. Floral variation in Saxifraga granulata: Phenotypic selection, quantitative genetics and predicted response to selection. Heredity 77: 217–223. Google Scholar


T. A. Castoe , A. W. Poole , A. P. J. de Koning , K. L. Jones , D. F. Tomback , S. J. Oyler-McCance , J. A. Fike , et al. 2012. Rapid Microsatellite Identification from Illumina paired-end genomic sequencing in two birds and a snake. PLoS ONE 7: e30953. Google Scholar


C. D. Darlington , and A. P. Wylie . 1955. Chromosome atlas of flowering plants. Allen & Unwin, London, United Kingdom. Google Scholar


R. J. Gornall 1987. An outline of a revised classification of Saxifraga. Botanical Journal of the Linnean Society 95: 273–292. Google Scholar


W. H. Lewis 1980. Polyploidy in species populations. In W. H. Lewis [ed.], Polyploidy: Biological relevance, 104–143. Plenum Press, New York, New York, USA. Google Scholar


P. G. Meirmans , and P. W. Hedrick . 2011. Assessing population structure: FST and related measures. Molecular Ecology Resources 11: 5–18. Google Scholar


P. G. Meirmans , and P. H. van Tienderen . 2004. GENOTYPE and GENODIVE: Two programs for the analysis of genetic diversity of asexual organisms. Molecular Ecology Notes 4: 792–794. Google Scholar


M. E. Moody , L. D. Mueller , and D. E. Soltis . 1993. Genetic variation and random drift in autotetraploid populations. Genetics 134: 649–657. Google Scholar


M. Nei 1987. Molecular evolutionary genetics. Colombia University Press, New York, New York, USA. Google Scholar


J. Philp 1934. Note on the cytology of Saxifraga granulata L., S. rosacea Moench, and their hybrids. Journal of Genetics 29: 197–201. Google Scholar


N. Redondo , M. Horjales , S. Brown , and C. Villaverde . 1996. Biometric and cytometric study of nuclear DNA within Saxifraga granulata L. Boletim da Sociedade Broteriana 67: 287–301. Google Scholar


D. P. Stevens 1988. On the gynodioecious polymorphism in Saxifraga granulata L. (Saxifragaceae). Biological Journal of the Linnean Society 35: 15–28. Google Scholar


D. P. Stevens , and A. J. Richards . 1985. Gynodioecy in Saxifraga granulata L. (Saxifragaceae). Plant Systematics and Evolution 151: 43–54. Google Scholar


D. W. Trapnell , J. L. Hamrick , K. C. Parker , K. W. Braungart , and T. C. Glenn . 2011. Evaluating the utility of microsatellites for investigations of autopolyploid taxa. Journal of Heredity 102: 473–478. Google Scholar


T. J. Walisch , G. Colling , M. Poncelet , and D. Matthies . 2012. Effects of inbreeding and interpopulation crosses on performance and plasticity of two generations of offspring of a declining grassland plant. American Journal of Botany 99: 1300–1313. Google Scholar


[1] The authors would like to thank J. S. van Zweden and K. Van Acker for assistance in the field and T. Reijnders for assistance in the laboratory. This work was supported by the Flanders Research Foundation (FWO, project 11G1715N, S.M.) and the European Research Council (ERC starting grant 260601, MYCASOR, H.J.).

Sascha van der Meer, Jeroen K. J. Van Houdt, Gregory E. Maes, Bart Hellemans, and Hans Jacquemyn "Microsatellite Primers for the Gynodioecious Grassland Perennial Saxifraga granulata (Saxifragaceae)," Applications in Plant Sciences 2(9), (29 August 2014).
Received: 14 May 2014; Accepted: 1 June 2014; Published: 29 August 2014

Back to Top