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Article

Cross-Species Transferability of Specific SSR Markers from Carex curvula (Cyperaceae) to Other Carex Species

1
Department of Experimental Biology, Institute of Biological Research, Branch of National Institute of Research and Development for Biological Sciences, 48 Republicii Street, 400015 Cluj-Napoca, Romania
2
A. Borza Botanic Garden, Babeș-Bolyai University, 42 Republicii Street, 400015 Cluj-Napoca, Romania
3
Center for Systematic Biology, Biodiversity and Bioresources—3B, Faculty of Biology and Geology, Babeș-Bolyai University, 1 Kogălniceanu Street, 400084 Cluj-Napoca, Romania
4
Emil G. Racoviță Institute, Babeș-Bolyai University, 400084 Cluj-Napoca, Romania
5
Doctoral School of Integrative Biology, Babeș-Bolyai University, 1 Kogălniceanu Street, 400084 Cluj-Napoca, Romania
6
Department of Molecular Biology and Biotechnology, Faculty of Biology and Geology, Babeș-Bolyai University, 1 Kogălniceanu Street, 400084 Cluj-Napoca, Romania
7
University Grenoble Alpes, University Savoie Mont Blanc, CNRS, LECA, F-38000 Grenoble, France
*
Author to whom correspondence should be addressed.
Diversity 2024, 16(2), 73; https://doi.org/10.3390/d16020073
Submission received: 29 November 2023 / Revised: 19 January 2024 / Accepted: 20 January 2024 / Published: 23 January 2024
(This article belongs to the Special Issue DNA Barcoding for Biodiversity Conservation and Restoration)

Abstract

:
Microsatellites are codominant markers that, due to their high polymorphism, are a common choice for detecting genetic variability in various organisms, including fungi, plants, and animals. However, the process of developing these markers is both costly and time-consuming. As a result, the cross-species amplification has become a more rapid and more affordable alternative in biological studies. The objective of this study was to assess the applicability of 13 SSR markers, originally designed for Carex curvula, in other 14 species belonging to different sections of the genus. All the markers were successfully transferred with a mean of 90.76%, and 100% transferability was reached in two species (C. baldensis and C. rupestris). The lowest transferability was registered in the G165 marker, which did not produce amplification in six species. Together, the microsatellites amplified a total of 183 alleles, ranging from 10 to 19 alleles per locus, with an average of 14.07. The mean number of different alleles ranged from 0.846 to a maximum of 2.077 per locus. No significant departures from the Hardy–Weinberg equilibrium were detected in polymorphic loci. The transferability of the 13 SSR markers proved highly successful in various Carex species, across different clades and sections of the genus.

1. Introduction

Microsatellite markers, also known as simple sequence repeats (SSRs), are intensively used in genetic studies for several distinctive features:, as follows: each marker is locus-specific and capable of revealing multiple alleles, they are inherited as codominant markers, they demonstrate a high level of reproducibility, and they offer broad genomic coverage [1,2]. Owing to the substantial variability between the number of tandem repeats present in individual loci, SSRs are recognized as one of the most polymorphic types of genetic markers [3].
Currently, microsatellites are the markers of choice in evolutionary biology studies for the assessment of genetic diversity among species, the determination of population structures, phylogenetic reconstructions, phylogeographic patterns, genetic mapping, evolutionary analyses, and molecular breeding [4,5].
When genomic data for specific species are unavailable, the use of microsatellites in genetic studies encounters a major bottleneck. This challenge primarily involves considerable time, research efforts, and financial resources for the development of customized primers to amplify distinct SSR loci. Therefore, overall, the information on SSR markers for less economically important species is still limited. A different approach to address this issue involves using the cross-amplification potential of microsatellite markers. This method allows for the exploration of genetic variability in various species, utilizing the conserved DNA sequences adjacent to these SSRs [6,7]. The efficacy of this method relies heavily on the degree of nucleotide similarity in the SSRs’ flanking regions across various species. Consequently, it is anticipated that phylogenetically related taxa will exhibit a greater likelihood of success in achieving amplification due to their closer genetic relationships and more similar genomic structures [8,9]. Heterologous amplification has been extensively applied across a broad spectrum of plant species, at intergeneric (e.g., [10,11,12,13,14]) and infrageneric levels (e.g., [15,16,17]). As expected, the greatest success in terms of using cross-amplification was found when applying this approach at the infrageneric level (success rate of about 60% [8]).
Carex L. (Cyperaceae), with ca. 2061 accepted species, is the fourth most diverse angiosperm genus [18,19]. This genus is present all over the world, except in Antarctica [20,21]. Carex exhibits greater species diversity in the Northern Hemisphere, in temperate and boreal biomes [22]. In contrast, its diversity significantly diminishes in tropical regions, where its presence is largely confined to montane ecosystems [23].
The tremendous diversity of the genus has rendered the classification and taxonomic treatment of Carex species particularly challenging. Traditionally, the Carex genus has been divided into four subgenera, as follows: subg. Psyllophora (Degl.) Peterm.; subg. Vignea (P. Beauv. ex T. Lestib.) Peterm.; subg. Vigneastra (Tuck.) Kük.; and subg. Carex [24,25]. However, recent molecular studies have demonstrated that this treatment does not accurately reflect the phylogenetic relationships between taxa. Furthermore, the genera Cymophyllus Mack., Kobresia Willd., Schoenoxiphium Nees, and Uncinia Pers. have been reevaluated and included in Carex [21,26]. The most recent studies [18,26] divided the Carex genus into six subgenera (subg. Siderosticta Waterway, subg. Psyllophorae (Degl.) Peterm., subg. Uncinia (Pers.) Peterm., subg. Vignea (P. Beauv. ex T. Lestib.) Heer, subg. Euthyceras Peterm., and subg. Carex), which are further subdivided into 62 sections and groups.
Despite its enormous species diversity, only a few microsatellite markers have been specifically developed in the Carex genus. Initially, microsatellite markers studies targeted only few species (e.g., Carex scabrifolia, C. moorcroftii, C. helodes, C. angustisquama, C. kobomugi, C. macrocephala, C. pumila [27,28,29,30,31,32,33,34]), but more recently, 42 and 17 markers, respectively, were tested for 106 Carex accessions [33,35]. Almost all taxa included in these studies belong to the Carex or Vignea subgenera. There have been even fewer attempts to assess the transferability of microsatellite loci within the genus. Consequently, in a previous study, we developed and characterized a set of 13 polymorphic SSR markers in the alpine sedge, Carex curvula All. (C. c. subsp. curvula and C. c. subsp. rosae Gilomen), and we tested their applicability in species phylogeography and subspecies delimitation [36].
In the present study, we explored the transferability of these genomic SSR markers, which were specifically developed for C. curvula, to 15 populations belonging to 14 species of Carex. We specifically targeted species within the Euthyceras–Psyllophorae Clade [18]. To the best of our knowledge, only one study has been conducted on a single species from this clade, namely, Carex onoei [35]. This particular clade is intricate, encompassing species that were formerly placed within the obsolete genera, Schoenoxiphium and Kobresia.

2. Materials and Methods

  • Plant sample collection and DNA extraction
Young, healthy, green leaves from two randomly chosen individuals per species/population were sampled from 15 locations across the Carpathians, Alps, Pyrenees, and Svalbard (Table 1). After collection, the plant material was stored in tubes filled with silica gel, at room temperature, until DNA extraction.
The total genomic DNA was extracted from 13 to 15 mg of silica gel-dried leaf tissue, using TissueLyser II (Qiagen, Hilden, Germany) and the innuPREP DNA Mini Kit (Analytik Jena AG, Jena, Germany), in accordance with the manufacturer’s protocol; however, the final elution took place in 50 μL in order to increase the DNA concentration. DNA quality was estimated using a 1% agarose gel stained with ethidium bromide, and the concentration was quantified using a NanoDrop 1000 Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA).
The nomenclature of the species listed in Table 1 adheres to the taxonomy provided in the Plants of the World Online (POWO) database [19].
  • Biological validation
The amplification of the 13 SSR markers previously developed in C. curvula was tested on DNA extracted from 15 populations/14 species of Carex. According to [18], nine of the studied species are included in the Euthyceras–Psyllophorae Clade (subgenus Psyllophorae: C. baldensis, C. pulicaris; subgenus Euthyceras: C. simpliciuscula, C. myosuroides, C. microglochin, C. nardina, C. rupestris, C. pauciflora, C. pyrenaica), three species in subgenus Vignea (C. parallela, C. dioica, C. maritima), and two are included in the subgenus Carex (C. nigra, C. dacica).
PCR protocol was followed in accordance with the one described by [36], as summarized below:
(i) PCR cycling conditions. Three min at 94 °C, 35 cycles for 1 min at 94 °C, 1 min at 55 °C (except VG139 and VG100, at an annealing temperature of 57 °C) and 2 min at 72 °C, followed by 7 min at 72 °C. PCR cycling was performed in a Mastercycler ep gradient S thermal cycler (Eppendorf, Hamburg, Germany).
(ii) PCR reaction conditions in a total volume of 10 µL. Here, 0.4 U KAPA Taq DNA Polymerase (Kapa Biosystems, Wilmington, MA, USA), 1× KAPA Taq Buffer A (MgCl2 1.5 mM included), 0.2 µM of each primer (the forward primer was fluorescently labelled with 6FAM: VG139, VG152, VG100, VG168, G110, VG203; NED: VG153, VG174, VG131, VG119; or HEX: VG175, VG108, G165), 0.25 mM of each dNTP (Thermo Fisher Scientific), 0.1 mg/mL BSA (Ambion, now part of Thermo Fisher Scientific), and 1.5 µL of DNA template (diluted four times) were used.
More details about the primers (including their sequences), the purification of the PCR products, and the subsequent separation that occurred through capillary electrophoresis can be found in [36].
  • Microsatellite data analysis
GeneMapper v.4.0 software (Applied Biosystems, now part of Thermo Fisher Scientific) was used for scoring the alleles.
The reliability of the experiment was assessed via a comparison of two duplicates from different populations. Only the unambiguous and repeatable peaks between duplicates were scored.
The number of alleles, number of private alleles, percentage of polymorphic markers, observed (Ho) and expected heterozygosity (He), and departure from the Hardy–Weinberg equilibrium (HWE) were determined using GenAlEx 6.5 [37,38].

3. Results

The SSR markers developed for C. curvula showed great success in cross transferability in the analysed species. The amplification bands were scored to reveal polymorphism based on the presence or absence of alleles, and variations in allele size, at the same locus. The size range of these reproducible bands is presented in Table 2.
All the 13 SSR primers were successfully transferred with a mean percentage of 90.76. Of the 13 primer pairs, only five primer pairs produced amplification in all 15 populations, namely, VG174, G110, VG119, VG108, and VG153, indicating 100% transferability. Moreover, 93.33% transferability was recorded for VG139, VG168, and VG131. A lower percentage of transferability was exhibited by VG152, VG100, VG203 (86.66%), and VG175 (80%), and the lowest transferability (only 60%) was registered in G165.
One hundred percent transferability for all 13 SSR primers was recorded in two species (C. baldensis and C. rupestris). This was followed by 92.3% transferability in eight species (C. pyrenaica, C. microglochin, C. nardina, C. parallela, C. maritima, C. pulicaris, C. dacica, and C. simpliciuscula), and 84.61% in five populations (C. pauciflora, C. dioica, C. nigra, and the two populations of C. myosuroides).
A total of 183 alleles were identified at these 13 amplified loci, ranging from 10 (G165) to 19 (VG168) alleles per locus, with an average of 14.07 (Table 2).
All the 13 SSR markers that were successfully transferred from C. curvula were polymorphic across the 15 evaluated Carex populations (Table 2). However, none of the populations showed polymorphism for all the loci (100% polymorphism), and the average percent of polymorphism was 27.69% (Table 3). C. rupestris was noted as the most polymorphic species, with only two invariable loci (84.6%), followed by C. dacica (69.23%) and C. baldensis (53.85%). C. pauciflora and C. nardina were the only two species monomorphic for all the 13 loci (0.00% polymorphism). Nevertheless, low values of polymorphism were noted for C. microglochin, C. nigra, and C. simpliciuscula (7.69%), followed by C. myosuroides (population 1) and C. pulicaris, with a value of 23.08% for the polymorphic loci (Table 3).
The mean number of different alleles ranged from 0.846 in the case of C. pauciflora and C. dioica, to a maximum of 2.077 per locus in the case of C. rupestris (Table 3). The number of private alleles (defined as the number of alleles unique to a single population) ranged from 0.154 in the case of C. myosuroides (population 1), to 1.385 for C. rupestris and C. dacica (Table 3). Expected heterozygosity ranged from 0.000 (for monomorphic species C. pauciflora and C. nardina) to 0.404 (C. rupestris), with an average of 0.131 across all Carex populations (Table 3). Observed heterozygosity ranged from 0.000 (for species C. pauciflora, C. microglochin, and C. nardina) to 0.462 (C. baldensis), with a mean of 0.174 across all Carex populations (Table 3). The departure from the Hardy–Weinberg equilibrium was noted as non-significant for all polymorphic loci.

4. Discussion

  • Interspecific transferability potential
Our research findings once again emphasize the value of the cross-species transferability of microsatellites, highlighting its role as a cost-effective method for the generation of genetic markers across various species within the same genus. A set of 13 SSR markers, previously developed for C. curvula, were evaluated for polymorphism in 15 different populations/14 species of Carex. The cross-amplification experiment was successful, and a total of 183 alleles were detected, with a range of 10 to 19, and an average of 14.07 alleles per locus. The total number of alleles and mean per locus, as revealed by these SSR markers, were higher than the values exhibited by C. curvula, 137 alleles and a mean of 10.53 alleles per locus respectively [36]. Furthermore, our values were relatively high, even compared with previous studies amplifying other SSR loci in different Carex species, such as the study by [35], which found a total of 173 alleles produced by 17 pairs of primers and an average of 10.18 for each locus. Similarly, the study by [33], reported 178 alleles in 79 Carex accessions, with an average of 4.3 alleles per microsatellite, generated by 42 SSR primer pairs.
The transferability rate varied from 60% to 100%, the lowest transferability being registered in G165, which did not produce amplification in six species. One hundred percent amplification for all 13 SSR primers was recorded in C. baldensis; this species is very closely related to C. curvula, and it belongs to the same clade (Curvula Clade). However, 100% amplification was also registered for C. rupestris, which is part of another clade, the Pauciflora Clade. Moreover, a high percentage of amplification (92.3%) was detected for species belonging to different clades and sections of the Carex genus, as follows: Capitata Clade, Kobresia Clade 2, Disticha Clade, Section Physoglochin, and Section Psyllophorae.
The percentage of polymorphism exhibited by the 15 Carex populations ranged from 0.00% to 84.6%, with an average value of 27.69% (Table 3). These values might be considered to be very low in comparison with the values noted for C. curvula (mean value = 87.97%). However, the present polymorphism results should be treated with caution, given that sample size in each population was lower than that of the C. curvula populations (five individuals) mentioned in [36]. This would suggest that, for an exhaustive assessment of genetic variation in natural populations, increasing the number of sampled individuals per locality would offer a better resolution of the genetic structure of these species.
Nevertheless, we tested how the sample size actually influenced the polymorphism rates in the case of these 13 SSR markers, by including additional individuals (data not shown) of C. pauciflora (up to a total of four individuals) and C. myosuroides (five for each of the two populations) in the analysis. In the case of C. pauciflora, the polymorphism value increased slightly, from 0.00% to 7.69%, whereas in C. myosuroides (both populations), it remained unchanged (15.38% and 33.85%) despite the addition of three more individuals.
  • Inter-populational discriminative potential
Carex myosuroides was represented in the present study by two populations sampled from different massifs in the Pyrenees, specifically to test how informative these SSR markers might be in the case of phylogeographic studies on other Carex species besides C. curvula. Both populations showed inconsistent amplification for the same SSRs (VG152 and VG100) and displayed identical alleles for VG119, VG131, G165, VG153, and VG168 markers (Table 2). Again, both populations were recorded as being among the poorest in terms of number of private alleles. However, the population from the Aston Massif proved to contain more unique alleles, with a value of 0.385, compared with 0.154 for the other population (from the Maladeta Massif). Their values of Ho, He, and percentage of polymorphic loci were very similar (Table 3). The number of alleles per population ranged from 0 to 2, depending on the marker, and it reached a maximum of three alleles for both populations. These results remained unchanged when analysing five individuals per population. The number of alleles displayed by both populations of C. myosuroides in the case of these 13 SSR markers was lower compared with several other studies reporting SSR markers in the Carex genus. For example, an analysis of 14 microsatellite loci in six populations of C. kobomugi revealed two to eight alleles per marker [27], and another analysis of nine microsatellite loci in four populations of Carex scabrifolia reported two to seven alleles [28], whereas an analysis of 30 SSR markers in three populations of C. pumila discovered four to twelve alleles [34]. The low number of alleles and the high level of monomorphism were also reported by [32], for three populations of C. angustisquama, analysed using 20 SSR markers, resulting an average of one to five alleles per marker.
Nevertheless, the most important finding was that these SSR markers were able to successfully delineate different populations of the same species.

5. Conclusions

In this study, we have revealed the successful cross-species amplification of 13 SSR loci, specifically developed for Carex curvula, in 14 other Carex species. Moreover, to the best of our knowledge, this study represents the first report focused on the identification of SSR markers suitable for genetic variation assessments in Carex species from the Euthyceras-Psyllophorae Clade.
All 13 primers were successfully transferred, with a mean percentage of 90.76, though only five primer pairs produced amplification in all 14 species andachieved 100% transferability. In addition, all the primers generated polymorphic alleles. In conclusion, our successful cross-amplification results extend the potential usefulness of these loci to other related taxa.

Author Contributions

Conceptualization, D.Ș. and M.P.; methodology, D.Ș. and M.P.; software, D.Ș.; validation, D.Ș. and M.P.; formal analysis, D.Ș., I.B. and Z.R.B.; investigation, D.Ș., I.B. and Z.R.B.; resources, D.Ș. and M.P.; data curation, D.Ș.; writing—original draft preparation, D.Ș.; writing—review and editing, D.Ș., M.P. and P.C.; visualization, M.P. and P.C.; supervision, M.P. and P.C.; project administration, M.P. and P.C; funding acquisition, M.P and P.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by ODYSSEE (ANR-13-ISV7-0004, PN-II-ID-JRP-RO-FR-2012) and BioDivMount projects (BRANCUSI No. 32660WB and PN-II-CT-ROFR-2014-2-0011), funded by ANR France and UEFISCDI Romania (coordinators P.C. and M.P.). D.Ș. and I.B. received funding from the Core Project BIORESGREEN, subproject BioClimpact no. 7N/03.01.2023, code 23020401.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to M.P., upon reasonable request.

Acknowledgments

We thank Inger G. Alsos, Pernille Bronken Eidesen, Patrik Mráz, Tudor Ursu and Daniel Dítě for help with field sampling. We also extend our gratitude to three anonymous reviewers for their insightful feedback on earlier versions of this manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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Table 1. The Carex species used in the study (Clade/Section are in accordance with [18]).
Table 1. The Carex species used in the study (Clade/Section are in accordance with [18]).
SpeciesClade/
Section
CountryRangeMassifLongitude (E)Latitude (N)
Carex pauciflora Lightf.PaucifloraRomaniaCarpathiansVlădeasa22.6946.44
Carex pyrenaica Wahlenb.PaucifloraRomaniaCarpathiansFăgăraș24.7445.6
Carex parallela (Laest.) Sommerf.PhysoglochinNorwaySvalbardNy-Friesland, Flatøyrdalen15.9979.28
Carex dioica L.PhysoglochinSlovakiaCarpathiansLow Tatras19.3548.94
Carex baldensis L.CurvulaItalyAlpsGarda Mountains10.3645.61
Carex maritima GunnerusDistichaNorwaySvalbardNy-Friesland, Wijdefjorden, Ringhorndalen15.9979.28
Carex pulicaris L.PsyllophoraeFranceAlpsPlateau Matheysin5.7744.99
Carex nardina Fr.CapitataNorwaySvalbardNy-Friesland, Flatøyrdalen16.0279.28
Carex microglochin Wahlenb.CapitataFranceAlpsVanoise Massif7.145.37
Carex rupestris All.CapitataRomaniaCarpathiansBucegi25.4645.41
Carex dacica Heuff.PhacocystisRomaniaCarpathiansFăgăraș24.6245.59
Carex nigra (L.) ReichardPhacocystisSlovakiaCarpathiansHigh Tatras20.149.16
Carex simpliciuscula Wahlenb.Kobresia 2RomaniaCarpathiansBucegi25.4645.41
Carex myosuroides Vill. (pop. 1)Kobresia 1SpainPyreneesMaladeta Massif0.6842.59
Carex myosuroides Vill. (pop. 2)Kobresia 1AndorraEastern PyreneesAston Massif1.742.58
Table 2. Cross-species amplification: size range of reproductible bands and number of alleles for 13 microsatellite loci developed for Carex curvula across 15 populations of Carex. IA = inconsistent amplification; NA = non-existent amplification.
Table 2. Cross-species amplification: size range of reproductible bands and number of alleles for 13 microsatellite loci developed for Carex curvula across 15 populations of Carex. IA = inconsistent amplification; NA = non-existent amplification.
Species/PopulationVG139VG175VG152VG100VG174G165VG168G110VG119VG203VG108VG131VG153
Carex pauciflora12626114173165NA20399113NA90120143
Carex pyrenaica118173–17814173166NA188–19790107–122259109118171
Carex nardina11818515979151NA16697110194105124145
Carex parallela1421711337516722017794–97105–110206–216193NA138–166
Carex baldensis142–148149134–16090–9714614615786109–122196–22394–100119131–136
Carex maritima139242158–18480164NA156–17097105248–257224–259119137–138
Carex pulicaris1432031438616392NA8761193100–103117–118143
Carex microglochin147NA13979–801581681508710018287130145
Carex rupestris149–151271–274132–13973–88160–170165–178168–17486–9293–10920898119–122149–152
Carex dacica137–175NA15183–92160147–161161–16587–96107–114382–40191–96113132–134
Carex nigraNANA15277–93157–161165–171145–19389–92107368–39896–113117134
Carex dioica118–14220313887164–167NA175–17986–98128–130NA198–199122–125145
Carex simpliciuscula14239314192167NA161111107–109207107120140
Carex myosuroides (1)151103–134IAIA1691851539310324290–98124140
Carex myosuroides (2)136–153103IAIA15918515399103242–24498–102124140
No. of alleles17131312141019121317181114
Table 3. Average number of different alleles (NA); average number of private alleles (NAP); observed heterozygosity (Ho); expected heterozygosity (He); and percentage of polymorphic loci (%P) for 13 microsatellite loci developed for Carex curvula across 15 populations of Carex sp.
Table 3. Average number of different alleles (NA); average number of private alleles (NAP); observed heterozygosity (Ho); expected heterozygosity (He); and percentage of polymorphic loci (%P) for 13 microsatellite loci developed for Carex curvula across 15 populations of Carex sp.
Species/PopulationNANAPHeHo%P
Carex pauciflora0.8460.3080.0000.0000.00
Carex pyrenaica1.2310.6920.1150.19223.08
Carex nardina0.9230.4620.0000.0000.00
Carex parallela1.2310.8460.1540.30830.77
Carex baldensis1.5381.0770.2500.46253.85
Carex maritima1.3080.8460.1920.30838.46
Carex pulicaris1.0770.6920.0670.11515.38
Carex microglochin1.0000.6150.0380.0007.69
Carex rupestris2.0771.3850.4040.30884.62
Carex dacica1.8461.3850.3170.38569.23
Carex nigra1.4620.8460.1920.26938.46
Carex dioica0.8460.6920.0380.0777.69
Carex simpliciuscula1.0000.3850.0290.0387.69
Carex myosuroides (1)1.0000.1540.0770.07715.38
Carex myosuroides (2)1.0770.3850.0960.07723.08
Mean1.2310.7180.1310.17427.69
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MDPI and ACS Style

Șuteu, D.; Pușcaș, M.; Băcilă, I.; Balázs, Z.R.; Choler, P. Cross-Species Transferability of Specific SSR Markers from Carex curvula (Cyperaceae) to Other Carex Species. Diversity 2024, 16, 73. https://doi.org/10.3390/d16020073

AMA Style

Șuteu D, Pușcaș M, Băcilă I, Balázs ZR, Choler P. Cross-Species Transferability of Specific SSR Markers from Carex curvula (Cyperaceae) to Other Carex Species. Diversity. 2024; 16(2):73. https://doi.org/10.3390/d16020073

Chicago/Turabian Style

Șuteu, Dana, Mihai Pușcaș, Ioan Băcilă, Zoltán Robert Balázs, and Philippe Choler. 2024. "Cross-Species Transferability of Specific SSR Markers from Carex curvula (Cyperaceae) to Other Carex Species" Diversity 16, no. 2: 73. https://doi.org/10.3390/d16020073

APA Style

Șuteu, D., Pușcaș, M., Băcilă, I., Balázs, Z. R., & Choler, P. (2024). Cross-Species Transferability of Specific SSR Markers from Carex curvula (Cyperaceae) to Other Carex Species. Diversity, 16(2), 73. https://doi.org/10.3390/d16020073

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