The genus Atriplex L. (Amaranthaceae) numbers about 270 species (McArthur and Sanderson, 1984) distributed mainly in the deserts and semideserts in southwestern North America, in southern Australia, in southern Central Asia, in southwestern South America (Osmond et al., 1980; McArthur and Sanderson, 1984), or in coastal and solonchak regions of the Northern Hemisphere (Osmond et al., 1980). Most previous population studies in Atriplex used allozymes (Mandák et al., 2005, 2006a, 2006b), and highly variable microsatellites have been employed only in the study of the Australian species A. nummularia Lindl. (Byrne et al., 2008). To date, no nuclear simple sequence repeat markers (SSRs) have been developed specifically for A. tatarica L. and successfully cross-amplified to closely related Atriplex and Chenopodium L. species to enable population-level assessment of various representatives of the genus. Given the number of species in both the genus and the whole family, we expect that these markers will have broad applicability for conservation and population-level analyses.
Atriplex tatarica is an annual diploid (2n = 2x = 18) with a mixed mating system (Mandák et al., 2005) and is native to a wide area of Eurasia (Kochánková and Mandák, 2008). Along with 13 other species, it belongs to the section Sclerocalymma (Asch.) Asch. & Graebn. The distribution center of this section is located in southern Central Asia (Kochánková and Mandák, 2008). In Europe the species has a continental distribution. The northwestern border of its current continuous European range runs through the Czech Republic (southern Moravia), southern Slovakia, eastern Poland, and central Belarus, and its expansion in these countries has recently been reported (Kochánková and Mandák, 2008). The species possesses remarkable heterocarpy, which is morphologically manifested in the shape and size of bracteoles and in the size and color of fruits. Heterocarpy enables colonizing species such as A. tatarica to survive both major disturbances and unfavorable conditions (by ensuring that at least some seeds persist) and to expand during periods of favorable conditions (by ensuring that some seeds effectively spread and germinate) (Doudová et al., 2017). In this paper, we report the development and characterization of 16 novel microsatellite loci for A. tatarica. Additionally, we cross-amplified these loci in four and seven species of the genera Atriplex and Chenopodium, respectively.
METHODS AND RESULTS
Microsatellite development—Total genomic DNA of A. tatarica was extracted from 20–25 mg of silica gel-dried leaf tissue from seven samples of different population origin (Appendix 1) using the DNeasy Plant Mini Kit (QIAGEN, Hilden, Germany). These samples were used by GenoScreen (Lille, France) to develop microsatellite loci following the protocol of Malausa et al. (2011) based on GS FLX Titanium pyrosequencing (454 Life Sciences, a Roche Company, Branford, Connecticut, USA) of microsatellite-enriched DNA libraries. Microsatellite enrichment was carried out using eight microsatellite probes [(AG)10, (AC)10, (AAC)8, (AGG)8, (ACG)8, (AAG)8, (ACAT)6, (ATCT)6]. The sequencing yielded 32,229 reads, and 1956 of these contained microsatellite motifs. Primers were designed based on reads of the positive strands using QDD software (Meglécz et al., 2010).
Characteristics of 16 polymorphic microsatellite loci of Atriplex tatarica.
Biological validation—Forty-seven candidate loci possessing perfect repeat motifs and different expected amplicon lengths within the 100–400-bp interval were selected and tested for amplification from all seven individuals. The PCR reactions were performed in 5-µL reaction volumes containing 1 µL of genomic DNA, 0.1 µM of both primers, and 1× QIAGEN Multiplex PCR Master Mix (QIAGEN). Reactions were performed with the following conditions: an initial denaturation step at 95°C for 15 min; followed by 40 cycles of denaturation at 94°C for 30 s, annealing at 55°C for 30 s, and extension at 72°C for 1 min; and a final extension at 72°C for 10 min. The PCR products were checked on 2% agarose gels. Of the markers that amplified successfully from all seven individuals, 24 were selected and used for initial polymorphism tests. In this step, PCRs were performed as described above, but only the forward primers were labeled by fluorescent dyes (6-FAM, VIC, PET, NED; Applied Biosystems, Foster City, California, USA). The PCR products were diluted 5×, and 1.0 µL of the dilution was added to a mix of 12.0 µL Hi-Di Formamide (Applied Biosystems) and 0.1 µL GeneScan 500 LIZ Size Standard (Applied Biosystems) for sequencing on an ABI PRISM 3130 Automated Capillary DNA Sequencer (Applied Biosystems). In the end, 16 polymorphic markers with well-scorable peaks were selected and combined into two multiplexes (Table 1). The sequences of the 454 reads containing these microsatellite loci have been deposited in the GenBank database of the National Center for Biotechnology Information (NCBI) (Table 1). These two multiplexes (Table 1) were tested for polymorphism in 120 individuals from six geographically well-separated populations collected across Europe (Appendix 1).
Using the same reaction conditions as specified above, the primers were tested on DNA extracted from A. oblongifolia Waldst. & Kit. (15 individuals tested), A. patula L. (15), A. prostrata DC. (3), A. sagittata Borkh. (20), C. bonus-henricus L. (7), C. hybridum L. (6), C. polyspermum L. (4), C. pumilio R. Br. (6), C. rubrum L. (4), C. suecicum Murr (6), and C. urbicum L. (4) (Appendix 1).
Microsatellite data analysis—Allele size was determined using Gene-Marker 2.6.4 (SoftGenetics, State College, Pennsylvania, USA). FSTAT 2.9.3 (Goudet, 1995) was used to calculate summary statistics for SSR loci such as the average number of alleles per locus and Weir and Cockerham's parameter f (FIS; Weir and Cockerham, 1984) as a measure of departure from within-population random mating. Observed and expected heterozygosities were calculated using GENEPOP (Rousset, 2008), and the deviation from Hardy-Weinberg equilibrium was determined based on 10,000 permutations in FSTAT 2.9.3 (Goudet, 1995). MICRO-CHECKER version 2.2.3 (van Oosterhout et al., 2004) was used to test for evidence of stuttering, allele dropout, and the presence of null alleles at each locus. The Brookfield 1 equation (Brookfield, 1996) was used to calculate null allele frequencies.
We identified 143 alleles at 16 microsatellite loci, with an average of 8.9 alleles per locus. The summary statistics for genetic variability across and within populations are presented in Table 2. The deficit of heterozygotes, computed over all populations and loci, was significant, as indicated by a relatively high inbreeding coefficient (f = 0.171). Eight out of 16 loci were not in Hardy–Weinberg equilibrium (Table 2), which might be due to high levels of self-pollination and the strong bottleneck effect of newly founded expanding populations. No signs of stuttering or large allele dropout were detected. The average null allele frequency for each locus calculated using the Brookfield method detected the presence of null alleles at five loci (Table 2).
Fifteen microsatellite loci were successfully cross-amplified from some of the species tested (Table 3). The cross-amplification was more successful with closely related species of the genus Atriplex than of Chenopodium (Table 3).
Genetic characterization of 16 newly developed polymorphic microsatellite loci across six populations of Atriplex tatarca.a
Results of cross-amplification (allele size ranges) of 16 microsatellite loci developed for Atriplex tatarica tested in seven Chenopodium and four other Atriplex species.a
Sixteen polymorphic microsatellite loci were developed for A. tatarica. These markers will be valuable for investigating the population genetic structure, mating system, and phylogeographic pattern of this species. The cross-species amplification of these markers indicates that they may be widely useful in related Amaranthaceae species. We conclude that the SSRs described here will facilitate ecological and evolutionary studies of A. tatarica and related species.
This research was supported by grant no. 15-06632S from the Grant Agency of the Czech Republic and by the long-term research development project RVO 67985939. The authors thank Lucia Marková and Martina Slavíčková for their help in the laboratory and Fred Rooks for help with English editing.
- Brookfield, J. 1996. A simple new method for estimating null allele frequency from heterozygote deficiency. Molecular Ecology 5: 453–455. Google Scholar
- Byrne, M., M. Hankinson, J. F. Sampson, and S. Stankovski. 2008. Microsatellite markers isolated from a polyploid saltbush, Atriplex nummularia Lindl. (Chenopodiaceae). Molecular Ecology Resources 8: 1426–1428. Google Scholar
- Doudová, J., J. Douda, and B. Mandák. 2017. The complexity underlying invasiveness precludes the identification of invasive traits: A comparative study of invasive and non-invasive heterocarpic Atriplex congeners. PLoS ONE 12: e0176455. Google Scholar
- Goudet, J. 1995. FSTAT (Version 1.2): A computer program to calculate F-statistics. Journal of Heredity 86: 485–486. Google Scholar
- Kochánková, J., and B. Mandák. 2008. Biological flora of Central Europe: Atriplex tatarica L. Perspectives in Plant Ecology , Evolution and Systematics 10: 217–229. Google Scholar
- Malausa, T., A. Gilles, E. Meglécz, H. Blanquart, S. Duthoy, C. Costedoat, V. Dubut, et al. 2011. High-throughput microsatellite isolation through 454 GS-FLX Titanium pyrosequencing of enriched DNA libraries. Molecular Ecology Resources 11: 638–644. Google Scholar
- Mandák, B., K. Bímová, I. Plačková, V. Mahelka, and J. Chrtek. 2005. Loss of genetic variation in geographically marginal populations of Atriplex tatarica (Chenopodiaceae). Annals of Botany 96: 901–912. Google Scholar
- Mandák, B., K. Bímová, and I. Plačková. 2006a. Genetic structure of experimental populations and reproductive fitness in a heterocarpic plant Atriplex tatarica (Chenopodiaceae). American Journal of Botany 93: 1640–1649. Google Scholar
- Mandák, B., K. Bímová, V. Mahelka, and I. Plačková. 2006b. How much genetic variation is stored in the seed bank? A study of Atriplex tatarica (Chenopodiaceae). Molecular Ecology 15: 2653–2663. Google Scholar
- McArthur, E. D., and S. C. Sanderson. 1984. Distribution, systematics, and evolution of Chenopodiaceae: An overview. In A. R. Tiedmann, A. D. McArthur, H. C. Stutz, R. Stevens, and K. L. Johnson [eds.], Proceedings—symposium on the biology of Atriplex and related chenopods, 14–24. Intermountain Forest and Range Experiment Station, U.S. Department of Agriculture, Forest Service, Provo, Utah, USA. Google Scholar
- Meglécz, E., C. Costedoat, V. Dubut, A. Gilles, T. Malausa, N. Pech, and J. F. Martin. 2010. QDD: A user-friendly program to select microsatellite markers and design primers from large sequencing projects. Bioinformatics (Oxford, England) 26: 403–404. Google Scholar
- Osmond, C. B., O. Björkman, and D. J. Anderson. 1980. Physiological processes in plant ecology: Towards a synthesis with Atriplex. Springer, Heidelberg, Germany. Google Scholar
- Rousset, F. 2008. GENEPOP'007: A complete reimplementation of the GENEPOP software for Windows and Linux. Molecular Ecology Resources 8: 103–106. Google Scholar
- van Oosterhout, C., W. F. Hutchinson, D. P. M. Wills, and P. Shipley. 2004. MICRO-CHECKER: Software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes 4: 535–538. Google Scholar
- Weir, B. S., and C. C. Cockerham. 1984. Estimating F-statistics for the analysis of population structure. Evolution 38: 1358–1370. Google Scholar