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Applications in Plant Sciences logoLink to Applications in Plant Sciences
. 2017 Apr 11;5(4):apps.1700005. doi: 10.3732/apps.1700005

Development of microsatellite loci in Mediterranean sarsaparilla (Smilax aspera; Smilacaceae) using transcriptome data1

Zhe-Chen Qi 2,3, Chao Shen 2,3, Yu-Wei Han 2, Wei Shen 2, Man Yang 2, Jinliang Liu 2, Zong-Suo Liang 2,3,5, Pan Li 4,5, Cheng-Xin Fu 4
PMCID: PMC5400434  PMID: 28439478

Abstract

Premise of the study:

Although several microsatellite markers of Smilax aspera (Smilacaceae) have been reported in a previous study, due to universality issues in cross-population amplification, we have newly developed microsatellite markers for S. aspera based on transcriptome data to further investigate gene flow and genetic structure of its circum-Mediterranean, East African, and South Asian populations.

Methods and Results:

A total of 4854 simple sequence repeat (SSR) primer pairs were designed from 99,193 contigs acquired from public transcriptome data of S. bona-nox. Forty-six microsatellite loci were selected for further genotyping in 12 S. aspera populations. The number of alleles varied from three to 28, and 93.5% of the developed microsatellite markers could be cross-amplified in least one of three congeneric Smilax species.

Conclusions:

The SSR markers developed in this study will facilitate further studies on genetic diversity and phylogeographic patterns of S. aspera in intercontinental geographical scales.

Keywords: deep lineage divergence, intercontinental disjunction, microsatellites, Smilacaceae, Smilax aspera, Tethyan vegetation, transcriptome


Smilax aspera L. (Smilacaceae) is a prickly woody climber with sclerophyllous leaves, small dioecious flowers, and fleshy red berries. This species is widespread throughout the circum-Mediterranean region and has a disjunct distribution into the East African upland evergreen forest and South Asian seasonal forest. With its Tethyan disjunction pattern, S. aspera represents an ideal model to test the dynamics and evolutionary history of laurel forests in the Late Tertiary period (Mai, 1995; Chen et al., 2014). A previous phylogeographic study (Chen et al., 2014) detected a deep lineage split between Mediterranean and African-Asian populations of S. aspera and a complex biogeographical range evolution history based on cpDNA and ITS sequences. However, these markers could not reveal the recent gene flow by pollen dispersal, and they did not provide detailed insights into intra- and interpopulation gene flow and genetic drift. Therefore, more efficient codominant markers such as microsatellites should be developed to allow further study.

Xu et al. (2011) reported 14 simple sequence repeat (SSR) markers of S. aspera developed in Greek and Italian populations using dual-suppression PCR, but three of the published primers were not polymorphic. Also, through subsequent cross-population amplification investigation in eight populations from Africa, Asia, and the Mediterranean, they showed lack of universality. Our testing of these markers showed average amplification efficiency of 48.8%, and 71.4% of the markers had amplification efficiency below 60%. Hence more reliable microsatellite markers are needed. Here, we developed 46 variable microsatellite markers for S. aspera based on transcriptome data of S. bona-nox L. (Matasci et al., 2014), and further tested their cross-amplification in three congeneric Smilax L. species. These additional microsatellite markers will secure enough polymorphic loci and provide powerful information to assess genetic characteristics and lineage divergence in natural populations of S. aspera.

METHODS AND RESULTS

A total of 96 individuals of S. aspera from 12 populations (eight individuals per population) and three congeneric species were used in this study (Appendix 1). The populations of S. aspera encompass seven in the Mediterranean region, four in South Asia, and one in East Africa. Fresh leaves were collected from each individual and dried in silica gel. Total genomic DNA was extracted following a modified cetyltrimethylammonium bromide (CTAB) protocol (Narzary et al., 2015), which was aided by using a more efficient Plant DNAzol Kit (Thermo Fisher Scientific, Waltham, Massachusetts, USA). Then, DNA quality was examined on 1% agarose gel, and concentration was checked using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific).

In this study, we obtained the transcriptome of S. bona-nox, a congeneric species of S. aspera, as a source for batch primer design. The raw data were acquired from the National Center for Biotechnology Information (NCBI; accession no. ERR364398) and assembled by Geneious 9.0.2 software (Kearse et al., 2012). In total, 99,193 contigs were prepared for SSR targeting and primer design. Microsatellite (SSR) repeats in contigs were observed by MISA software (Thiel et al., 2003). The SSR search was performed for mono-, di-, tri-, tetra-, penta-, and hexanucleotide repeats with a minimum of 10, six, five, four, three, and three repeats, respectively. The maximum number of bases interrupting two SSRs in a compound microsatellite was 100 bp. Primer pairs were then designed using Primer3 software (Rozen and Skaletsky, 1999). The primer annealing temperature was set from 50°C to 65°C, primer size was between 18 and 27 bp with an optimal size of 20 bp, the product size was from 100 to 500 bp, and the other settings were left at default values. A total of 4854 SSR primer pairs were designed, and 153 pairs were selected randomly based on the proportion of different microsatellite repeats. A cost-effective fluorescent labeling method was applied following Schuelke (2000), and the protocol was optimized according to Sakaguchi and Ito (2014). For all loci, a forward primer was synthesized with an M13 sequence (5′-CACGACGTTGTAAAACGAC-3′) at the 5′ end, and a universal M13 primer (5′-CACGACGTTGTAAAACGAC-3′) labeled with one of four fluorophores (FAM, TAMRA, HEX, ROX) was added during PCR amplification.

The primer pairs were initially tested for successful PCR amplification in 12 individuals from 12 separate populations. PCR amplifications were performed on a T100 Thermal Cycler (Applied Biosystems, Life Technologies, Waltham, Massachusetts, USA) with a 10-μL reaction mixture that contained 1 μL of genomic DNA, 5 μL 2× Master Mix (TSINGKE, Hangzhou, Zhejiang, China), 0.2 μM of forward primers, and 0.2 μM of reverse primers. The PCR protocol used was as follows: an initial denaturation at 94°C for 5 min; followed by 35 cycles at 94°C for 45 s, a temperature gradient from 50°C to 65°C was applied for annealing for 45 s, and 72°C for 1 min; and a final extension at 72°C for 5 min. Amplification products were checked on 2% agarose gel stained with GeneGreen Nucleic Acid dye (TIANGEN, Beijing, China).

Fifty-three primer pairs generated specific amplification products and were used for amplification in 96 individuals from 12 populations, using the two-step PCR protocol described in Schuelke (2000). In the first step, the PCR reaction mixtures were in a final volume of 10 μL, which contained 1 μL of genomic DNA, 5 μL 2× Master Mix, 0.1 μM of forward primers, and 0.4 μM of reverse primers. The PCR conditions involved denaturation at 94°C for 5 min; followed by 35 cycles at 94°C for 45 s, at a locus-specific annealing temperature (Table 1) for 45 s, and 72°C for 1 min; and a final extension at 72°C for 5 min. In the second step, the reaction mixtures contained the same PCR products as in the first step, plus 5 μL 2× Master Mix and another 0.8 μL (5 μM) of fluorophore-labeled universal M13 primer for a final volume of 20 μL. The PCR conditions involved denaturation at 94°C for 3 min; followed by 20 cycles at 94°C for 30 s, annealing at 53°C for 30 s, and 72°C for 45 s; and a final extension at 72°C for 10 min. Then, 1 μL of the fluorescent PCR product was added to 8.8 μL of formamide and 0.2 μL of GeneScan 500 LIZ Size Standard (Applied Biosystems, Life Technologies). Reaction products were subsequently run on an ABI PRISM 3730xl Genetic Analyzer (Applied Biosystems). Genotypes were scored by Geneious version 9.0.2 software (Kearse et al., 2012). Finally, 46 of 53 primer pairs with clear and robust genotype information and suitable genetic variation were selected for further population genetic study. All of the selected loci can be stably amplified in 96 tested individuals (12 populations), except one (locus S062) that could not be amplified in population KL, which makes the amplification efficiency of these primers 97.8%. Information and GenBank accession numbers for the 46 microsatellites are provided in Table 1.

Table 1.

Characteristics of 46 microsatellite loci developed for Smilax aspera.

Locus Primer sequences (5′–3′) Repeat motif Allele size (bp) Ta (°C) A GenBank accession no.
S003 F: TCCCCATTTCTCCTCACTTG (TTTTC)5 100 53 4 KY358008
R: GCCACTACAACAACTTAGTGATTTTG
S004 F: GCCCACTTTCATTGCCTTTA (TCA)8 111 53 15 KY358009
R: AATGTGGGCGTGGTAAAAAG
S006 F: AAAGGGGATGAGGAGAAGGA (AAG)7 133 59 9 KY358010
R: AAACCACCATGACTCCTCCA
S007 F: CTGCTTCCAGACAGAGGAGG (TGGTT)5 139 59 8 KY358011
R: ACACTTCTTGGGTTGGCATC
S009 F: GAGTGAGGAGGGAGGAGCTT (TC)33 159 58 23 KY358012
R: CCGGAGAACCAGATGAAGAC
S016 F: AGAACTTGAGGGTGTGTGGG (T)10(TC)6 230 58 16 KY358013
R: TTCATGCATACTTTTGCCGA
S028 F: TAATCCCTCGCGAAATCAAG (GATC)5 120 53 3 KY358014
R: CCCAAAATCGATCGAGAAAA
S030 F: AAGCCAAGCAAACCCATTTA (GA)14 126 59 15 KY358015
R: CACCCTCTGACTCCGAAGAG
S034 F: CAGGGAGTTGGTCCTCAAAA (T)21 154 59 12 KY358016
R: ATGGTTGCAAAGAAACACCC
S046 F: CTAAGGCGATATCCTCAGCG (GTGGGC)5 226 59 7 KY358017
R: CAGCCACTTGGTATCCACCT
S049 F: AAGGGACATTTTTGTTCCCC (TAAA)6 248 59 4 KY358018
R: GCAAGTTAAGCAACACAGTTAAGG
S052 F: AGATCCACAGTTCCACCTGC (AAACTAT)10 266 59 8 KY358019
R: GCGCTTGATGTGCTCAAATA
S053 F: GATCTGGGTTTCTCGTTGGA (CTGGGA)5 269 59 6 KY358020
R: GGCCATTTGGAAGAGACTGA
S057 F: GAGATTTCCAGCAAAACCCA (CGAG)4 291 58 5 KY358021
R: AGTTTCTGGGCCCTCTGTCT
S060 F: CCATGGTGGACGACTTTCTT (GAT)6 311 59 3 KY358022
R: GCATGGAAACGCCTATGATT
S062 F: CTTGGCAACACCAATCAATG (TCCT)7 326 59 9 KY358023
R: TGCACGTGATCACTGGATCT
S063 F: CATTTCGATGAATCGTGTGG (CATCT)5(TC)23 332 59 21 KY358024
R: GTAGGGTTCGGTGCTGATGT
S066 F: TCGATTTCCACCCATTTCTC (CGCCAC)5 354 59 10 KY358025
R: GCTGAGTACTTGAGGGCGTC
S072 F: CAGTGCCTCTTCCTTGCTTC (TGG)5(GTGGCC)3 402 59 16 KY358026
R: TATACCCAGGTCTCCGAACG
S081 F: ATTTCGCCACTACCTTGCAC (CCCT)6 103 50 8 KY358027
R: ATCCTTCATTCAATGCCGAG
S083 F: GGACTGGATTCCGTTTTGCT (CCTCTA)4 105 50 4 KY358028
R: AGCCAGGACATTGCCTTTAC
S085 F: TGTTGGGTGAGCAAAACAAA (T)16 109 53 16 KY358029
R: ACCTTTCTCCCCACTTGCTT
S086 F: TAATTGGCTTCGGATTGACC (AG)9 112 50 28 KY358030
R: GGAATTCGTTCTTCCCCATT
S087 F: GGACTTGGTCATCAGGTCGT (TC)12TAGGTC(TCGGA)3 116 55 21 KY358031
R: TTGTGCAACCAAACTCCAGA
S089 F: CACAAGCTTGATGAGGTCCA (TGGTT)3 125 53 7 KY358032
R: AAGGACACGGACCATGAAAG
S090 F: AGCAGCCTTGGGCTTATTTT (TAAAC)3 132 53 5 KY358033
R: TTCTGTTGTGCGGATATTGG
S093 F: GAAGGGAGGGAGGAGAAGTG (AG)12 135 53 7 KY358034
R: CCGTTTAAAGATCCCGTCAA
S094 F: TGCTGGAAGAACAACGACTG (GCTGTT)4 143 50 4 KY358035
R: GTTACCGTTGGTCACCTGCT
S096 F: TGGATTCATGTGTTTGGCTG (A)22 145 55 8 KY358036
R: AAATCAGGCCTCCTCATTGTAA
S097 F: CACCTTCTCCTCCTCTTCCC (TTC)8 148 51 9 KY358037
R: TCATCTCCCCTCTTCTTCCC
S100 F: CTGGAGATCTCACCCTCTCG (CCCTCT)3 155 50 6 KY358038
R: CAATGAGACAGTCCGGATCA
S104 F: AATTGGGATTTGATGATCGC (TC)17 168 53 11 KY358039
R: CCAAAAACCCACGAGAGAAA
S105 F: GCTGGTACTTCTTCTTGCCG (GGCGGA)3 168 55 6 KY358040
R: ACTTCGAGAACAGCCTCCAA
S110 F: TCACGTGTGAGGTTCTAGCG (AG)7AA(AG)14 181 59 3 KY358041
R: TGGCGTCCCAGTGAGTGT
S113 F: ACGTAACTCTCGGTGCCATC (AG)11 185 55 5 KY358042
R: CGTGTGGAAGGGAGGTAAAA
S116 F: ATGACATCCCCTCCCTCTCT (TC)9 191 55 15 KY358043
R: CCCCACCATTGTCTTGAAGT
S120 F: AGGCCAAGACTATCAGCGAA (GTG)7 204 53 3 KY358045
R: TCTTTCTTGCTCCAGGCATT
S121 F: GGGAACACTACCTTCTGCCA (CGATCT)4 211 61 3 KY358046
R: TTGAGATCTGGGGAGGTTTG
S122 F: TGTGGTGCTTGATGAGCTTC (CTG)7 214 50 3 KY358047
R: CGTTGCACAGAGCGAATAAA
S126 F: CTTCTCCGCATACCACCTGT (CT)10 227 53 6 KY358048
R: GCTCTGCGTCTGTTCCATTT
S130 F: ATGCTTGACACGCTTGATTG (TGC)8 247 53 12 KY358049
R: AGCTGCTTGGACAGCAAAAT
S132 F: ACGGTCTCTTTCAAGAAGGG (AG)12 251 55 11 KY358050
R: GATGAAGGAGAACGCAAAGC
S134 F: GAGAGCCCACGTGAAGTGAT (GA)15 258 55 27 KY358051
R: CCCCATAAATGTGGGAGATG
S139 F: GCAAAGCTCTTCTCCTCCCT (TTC)5 282 50 7 KY358052
R: CTGGATGGCTTTGGATAGGA
S144 F: GACCCCATGGATACGAGAAC (GGGGTC)3 306 55 4 KY358053
R: CTAAACCCGACTCCCCAAAT
S148 F: AGAACCAGCAGAGCGACATT (CAG)7 350 55 4 KY358054
R: TTGCGTCAGCTTACCCTTCT

Note: A = number of alleles per locus; Ta = optimized annealing temperature.

Genetic diversity parameters were estimated using CERVUS 3.0 (Kalinowski et al., 2007), including the number of alleles, observed and expected heterozygosity, and polymorphism information content (Table 2). Deviations from Hardy–Weinberg equilibrium were tested through GENEPOP 4.2 (Rousset, 2008) (Table 2). All parameters were calculated for three groups of S. aspera (Mediterranean, East African, and South Asian; Table 2). The polymorphism information content ranged from zero to 0.918, the number of alleles ranged from one to 25, and the expected heterozygosity and observed heterozygosity varied from 0.000 to 0.932 and 0.000 to 1.000, respectively. Also, 10 loci showed significant deviation from expectations under Hardy–Weinberg equilibrium because of an excess of homozygotes. Wahlund effect, inbreeding, null alleles, and sampling effect are all potential causes of the deviation.

Table 2.

The genetic parameters (per locus) in three continental groups of Smilax aspera.a

Mediterranean groupb (N = 56) East African groupc (N = 8) South Asian groupd (N = 32)
Locus A Ho He PICe A Ho He PICe A Ho He PICe
S003 4 0.839 0.609 0.539*** 2 0.625 0.458 0.337 3 0.813 0.502 0.387*
S004 8 1.000 0.769 0.725* 4 1.000 0.675 0.570 10 1.000 0.847 0.812
S006 6 0.933 0.605 0.517*** 5 0.800 0.822 0.701 4 1.000 0.540 0.421***
S007 7 0.982 0.599 0.515*** 3 1.000 0.592 0.456* 5 1.000 0.676 0.618***
S009 20 0.648 0.909 0.892 5 0.250 0.800 0.712*** 12 0.719 0.799 0.763
S016 15 0.455 0.847 0.818 2 0.500 0.500 0.305 3 0.100 0.099 0.094
S028 3 0.821 0.557 0.480*** 2 1.000 0.533 0.375* 2 0.906 0.503 0.373***
S030 15 0.714 0.896 0.879 6 0.750 0.800 0.712 12 0.844 0.897 0.872
S034 5 0.964 0.662 0.592** 3 1.000 0.667 0.555 9 1.000 0.841 0.806
S046 6 0.714 0.561 0.513* 2 0.143 0.143 0.124 6 0.839 0.755 0.703
S049 3 0.682 0.498 0.382 3 1.000 0.644 0.492 3 0.423 0.429 0.347
S052 7 0.804 0.649 0.601 3 1.000 0.604 0.465 5 0.906 0.697 0.632
S053 2 0.196 0.179 0.161 3 0.500 0.542 0.428 6 0.533 0.727 0.683
S057 5 0.537 0.491 0.456 1 0.000 0.000 0.000 3 0.688 0.494 0.414
S060 3 0.327 0.375 0.335 1 0.000 0.000 0.000 1 0.000 0.000 0.000
S062 7 0.564 0.648 0.582 NA NA NA NA 2 0.036 0.036 0.034
S063 19 0.893 0.899 0.882 4 0.667 0.712 0.599 11 0.862 0.877 0.846
S066 10 0.905 0.852 0.823 3 1.000 0.733 0.535 8 0.933 0.848 0.798
S072 15 0.939 0.853 0.828 6 0.857 0.857 0.766 11 0.889 0.859 0.818
S081 7 0.661 0.610 0.530 3 1.000 0.633 0.511 6 0.906 0.687 0.621
S083 4 0.500 0.404 0.358 3 0.250 0.242 0.215 2 0.281 0.246 0.212
S085 13 0.735 0.619 0.578 3 0.500 0.591 0.460 9 0.875 0.708 0.659
S086 25 0.982 0.915 0.901 7 0.625 0.742 0.666 18 0.906 0.893 0.869
S087 15 0.820 0.916 0.900 4 0.714 0.780 0.674 10 0.556 0.830 0.792
S089 6 0.464 0.397 0.374 3 0.250 0.242 0.215 4 0.781 0.559 0.490
S090 5 0.714 0.533 0.480** 4 0.625 0.517 0.443 4 0.844 0.592 0.525**
S093 3 0.000 0.459 0.403 2 0.000 0.667 0.375 3 0.174 0.305 0.273
S094 4 0.491 0.490 0.384 2 0.500 0.429 0.305 2 0.406 0.329 0.271
S096 6 0.300 0.437 0.410 2 0.286 0.264 0.215 4 0.750 0.499 0.398
S097 9 0.536 0.444 0.414 4 0.625 0.517 0.443 4 0.750 0.554 0.493
S100 5 0.446 0.766 0.720 1 0.000 0.000 0.000 4 0.563 0.665 0.573
S104 6 0.536 0.767 0.726 3 0.125 0.542 0.428 9 0.281 0.754 0.705
S105 5 0.702 0.531 0.480* 1 0.000 0.000 0.000 4 0.938 0.669 0.588
S110 4 0.704 0.509 0.403 3 0.625 0.492 0.398 2 0.548 0.432 0.335
S113 10 0.596 0.569 0.536 4 0.667 0.800 0.620 9 0.458 0.796 0.748
S116 5 0.564 0.501 0.440 2 0.625 0.458 0.337 6 0.710 0.582 0.502
S120 3 0.434 0.453 0.356 2 0.429 0.363 0.280 2 0.633 0.481 0.361
S121 2 0.600 0.470 0.357 2 0.714 0.538 0.375 3 0.692 0.495 0.411
S122 3 0.393 0.449 0.387 1 0.000 0.000 0.000 1 0.000 0.000 0.000
S126 6 0.510 0.426 0.368 2 0.250 0.233 0.195 4 0.688 0.489 0.393
S130 6 0.558 0.524 0.442 3 0.750 0.667 0.555 10 0.742 0.811 0.772
S132 5 0.370 0.393 0.366 3 1.000 0.621 0.477 9 0.906 0.872 0.841
S134 22 1.000 0.932 0.918 4 1.000 0.692 0.592 14 1.000 0.852 0.822
S139 6 0.538 0.643 0.588 2 0.333 0.600 0.375 5 0.333 0.460 0.423
S144 1 0.000 0.000 0.000 1 0.000 0.000 0.000 4 0.226 0.546 0.483
S148 4 0.059 0.303 0.270 1 0.000 0.000 0.000 3 0.250 0.458 0.362
Mean 7.61 0.612 0.585 0.534 2.89 0.533 0.482 0.375 5.89 0.645 0.587 0.537

Note: A = number of alleles per locus; He = expected heterozygosity; Ho = observed heterozygosity; N = number of individuals sampled; NA = unsuccessful amplification; PIC = polymorphism information content.

a

Locality and voucher information are available in Appendix 1.

b

The Mediterranean Group consists of populations PL, SM, IR, IS, GA, GC, and TT.

c

The East African Group consists of population KL.

d

The South Asian Group consists of populations SRL, NS, CP, and CJ.

e

Significant deviations from Hardy–Weinberg equilibrium at *P < 0.05, **P < 0.01, and ***P < 0.001, respectively.

To test the congeneric transferability of the 46 selected markers, cross-amplification was performed in three congeneric species (S. riparia A. DC., S. china L., S. hugeri (Small) J. B. Norton ex Pennell; Appendix 1), with five individuals per species. Primer transferability was detected using 2% agarose gels, and amplification was considered successful when one clear distinct band was visible in the expected size range. In total, 93.5% of the developed microsatellite markers could be cross-amplified in at least one of three congeneric Smilax species. Specifically, the transferability values in each species were 87.0% in S. riparia, 78.3% in S. china, and 76.1% in S. hugeri (Table 3).

Table 3.

Cross-amplification efficiency of Smilax aspera in three congeneric species.a

Locus Smilax riparia (N = 5) Smilax china (N = 5) Smilax hugeri (N = 5)
S003 80.0% 100.0% 100.0%
S004 40.0% 100.0% 100.0%
S006 100.0% 100.0% 100.0%
S007 100.0% 100.0% 100.0%
S009 100.0% 100.0% 40.0%
S016 100.0% 0.0% 0.0%
S028 100.0% 80.0% 100.0%
S030 60.0% 0.0% 0.0%
S034 100.0% 100.0% 100.0%
S046 100.0% 80.0% 100.0%
S049 100.0% 100.0% 100.0%
S052 100.0% 0.0% 40.0%
S053 100.0% 100.0% 100.0%
S057 100.0% 40.0% 40.0%
S060 80.0% 100.0% 0.0%
S062 100.0% 0.0% 0.0%
S063 100.0% 100.0% 100.0%
S066 100.0% 100.0% 100.0%
S072 100.0% 100.0% 100.0%
S081 100.0% 100.0% 100.0%
S083 100.0% 100.0% 100.0%
S085 0.0% 0.0% 60.0%
S086 100.0% 100.0% 100.0%
S087 100.0% 0.0% 80.0%
S089 100.0% 100.0% 100.0%
S090 0.0% 100.0% 0.0%
S093 100.0% 100.0% 60.0%
S094 100.0% 100.0% 80.0%
S104 0.0% 0.0% 0.0%
S096 100.0% 100.0% 80.0%
S097 0.0% 0.0% 0.0%
S100 100.0% 100.0% 100.0%
S105 100.0% 100.0% 100.0%
S110 0.0% 100.0% 40.0%
S113 100.0% 100.0% 100.0%
S116 100.0% 100.0% 0.0%
S120 100.0% 100.0% 100.0%
S121 100.0% 0.0% 0.0%
S122 100.0% 100.0% 100.0%
S126 0.0% 0.0% 0.0%
S130 100.0% 100.0% 100.0%
S132 100.0% 100.0% 80.0%
S134 100.0% 100.0% 0.0%
S139 100.0% 100.0% 100.0%
S144 100.0% 100.0% 60.0%
S148 100.0% 100.0% 40.0%
Transferabilityb 40/46 = 87.0% 36/46 = 78.3% 35/46 = 76.1%
a

Locality and voucher information are available in Appendix 1.

b

Transferability = number of successfully cross-amplified loci/total number of microsatellites × 100%.

CONCLUSIONS

Forty-six highly polymorphic microsatellite markers were developed successfully in this study and can be applied to elucidate the population structure and possible intra- and interpopulation gene flow of S. aspera. The cross-amplification of these SSR primer pairs in three Smilax species was successful, which suggests the potential of these markers to clarify underlying genetic introgression as well as cryptic speciation events of Smilax species.

Appendix 1.

Locality and voucher information for populations of Smilax aspera, S. riparia, S. china, and S. hugeri used in this study. Voucher specimens are deposited at the herbarium of Zhejiang University (HZU), Hangzhou, Zhejiang, China.

Species Population code Voucher no. Locality Geographic coordinates Altitude (m) n
Smilax aspera L. PL HZU-0906014 Lisbon, Portugal 38°43′05″N, 09°11′24″W 110 8
SM HZU-906011 Málaga, Spain 36°38′52″N, 04°32′43″W 250–300 8
IR HZU-Q0906007 Rome, Italy 41°57′59″N, 12°48′18″E 200 8
IS HZU-Q0906003 Sardinia, Italy 39°12′59″N, 09°08′10″E 100–150 8
GA HZU-Q0906010 Athens, Greece 37°59′10″N, 23°49′24″E 400–625 8
GC HZU-Q0906011 Chania, Greece 35°30′59″N, 24°05′40″E 150 8
TT HZU-Z0906001 Termessos, Turkey 36°54′15″N, 30°30′11″E 374 8
KL HZU-Q10K001 Lumuru, Kenya 01°06′45″S, 36°40′57″E 2189 8
SRL HZU-F1012126 Nuwara Eliya, Mahagasthota, Sri Lanka 06°58′05″N, 80°45′38″E 1900–2000 8
NS HZU-BQ0908293 Shivapuri, Nepal 27°48′00″N, 85°22′00″E 2000 8
CP HZU-BQ0909326 Pihe, China 26°31′00″N, 98°55′00″E 1050 8
CJ HZU-BQ0908304 Jilong, China 28°19′00″N, 85°21′00″E 1600–2000 8
Smilax riparia A. DC. HZU-CY160344 Hengyang, China 27°16′33″N, 112°40′42″E 1000 5
Smilax china L. HZU-JXJ2016062604 Wenzhou, China 27°42′21″N, 119°40′30″E 741 5
Smilax hugeri (Small) J. B. Norton ex Pennell HZU-LP162465 Chattahoochee, Florida, USA 30°41′43″N, 85°08′46″W 34 5

Note: n = number of individuals per population.

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