Abstract
• Premise of the study: Spartina alterniflora is one of the nine most notoriously invasive plants in China. Microsatellite markers were developed for this species to investigate its invasiveness and genetic diversity.
• Methods and Results: Fifteen polymorphic and seven monomorphic simple sequence repeat (SSR) markers derived from expressed sequence tags (ESTs) were identified and screened in 60 samples of S. alterniflora. The number of alleles per polymorphic locus ranged from two to eight, with an average of 3.8 alleles per polymorphic locus. The expected heterozygosity and observed heterozygosity based on seven disomic loci ranged from 0.27 to 0.46 and 0.21 to 0.51, respectively. The average Shannon index ranged from 0.26 to 0.94 in eight nondisomic loci.
• Conclusions: The SSR markers described here may be useful for further investigation of population genetics and invasion dynamics of S. alterniflora.
Keywords: invasive species, microsatellite, Poaceae, Spartina alterniflora, transcriptome
Spartina alterniflora Loisel. (Chloridoideae, Poaceae) is a perennial grass native to the Atlantic and Gulf coasts of North America, and has been used in coastal restoration programs in many countries (Daehler and Strong, 1996). However, S. alterniflora is highly invasive in many parts of the world where it is introduced. In China, the species has been listed as one of the nine most notoriously invasive plants (Zhi et al., 2007). Recently, we have sequenced the transcriptome of S. alterniflora using the next-generation sequencing platform Illumina Genome Analyzer II to understand its invasion in China (Guo et al., unpublished data). The transcriptome sequences contain abundant simple sequence repeat (SSR) markers, which should be very useful in population genetic studies. Here, for the first time, we identified several thousand expressed sequence tag (EST)–derived simple sequence repeat (ESSR) markers from the RNA-seq data of S. alterniflora. Compared to genomic SSR markers, ESSRs are easier and less expensive to develop, as well as more transferable across taxonomic boundaries (Ellis and Burke, 2007).
METHODS AND RESULTS
Transcriptome sequencing of S. alterniflora was conducted using the Illumina Genome Analyzer II system. In total, 14.55 million 90-nucleotide paired-end reads were obtained and assembled into 69899 contigs with an average length of 503 nucleotides by using two short-read assemblers—Trinity and CAP3 (Huang and Madan, 1999; Grabherr et al., 2011). These unique sequences (i.e., ESTs) were further screened for the presence of microsatellites using MISA (http://pgrc.ipk-gatersleben.de/misa). A total of 3052 potential ESSRs were identified. The microsatellites were defined as di-, tri-, tetra-, penta-, and hexanucleotide SSRs with a minimum of four contiguous repeat units. The most abundant repeat type was trinucleotide (47.8%, 1460), followed by dinucleotide (38.7%, 1182), tetranucleotide (8.1%, 247), pentanucleotide (3.7%, 114), and hexanucleotide (1.6%, 49) repeat units. Primer3 software (Rozen and Skaletsky, 2000) was used to design 50 primer pairs with an expected product size ranging from 100 to 300 bp. Sixty individuals of S. alterniflora representing five populations in China (Appendix 1) were used to evaluate the polymorphisms of the microsatellite loci.
Genomic DNA from each individual was extracted from silica gel–dried leaves using the cetyltrimethylammonium bromide (CTAB) method (Doyle, 1991). PCR amplifications were performed in a final volume of 20 μL, containing 2 μL 10× PCR buffer, 2 μL of 2 mM each dNTPs, 1.2 μL 25 mM MgCl2, 1 μL 10 pM forward primer, 1 μL 10 pM reverse primer, 2 U Taq DNA polymerase (Sangon, Shanghai, China), and 10 ng of genomic DNA. The PCR reactions were conducted with the following conditions in a thermocycler (Bio-Rad Laboratories, Hercules, California, USA): initial denaturation at 94°C for 5 min, followed by 34 cycles of 94°C for 30 s, 60°C for 30 s, and 72°C for 45 s, with a final extension cycle at 72°C for 10 min. PCR products were electrophoresed on 8% polyacrylamide denaturing gel and visualized by silver staining. The band size was estimated by comparison with a 20-bp DNA ladder (Fermentas, Vilnius, Lithuania). Twenty-six (52%) of the primer pairs failed to amplify products, two (4.0%) generated complex band patterns that were difficult to genotype, seven (14%) were monomorphic, and 15 (30%) displayed clear polymorphisms (Table 1). To determine the function of polymorphic SSR-associated unigenes, ESSRs were evaluated for connections with genes of known functions; those 22 sequences (including seven monomorphic and 15 polymorphic loci, respectively) were blasted against the GenBank nonredundant database using BLASTX (Altschul et al., 1997) with an E-value of 10−10. All of the sequences showed significant similarities to known genes (Table 1). The allele number (A) and polymorphism information content (PIC) were calculated for each of the loci using a Web-based calculator (http://www.genomics.liv.ac.uk/animal/pic.html). The number of alleles per polymorphic locus ranged from two to eight, with an average of 3.80 alleles per polymorphic locus. The number of alleles per individual ranged from one to six, which was consistent with the hexaploidy of S. alterniflora. Seven (46.67%) of 15 polymorphic loci showed the disomic pattern with a maximum of two alleles per individual. These 15 polymorphic microsatellite loci are further characterized in Tables 2 and 3. The expected heterozygosity (He) and observed heterozygosity (Ho) for each disomic locus were calculated using POPGENE (version 1.32; Yeh and Boyle, 1997). The Shannon index for each nondisomic locus was calculated using POLYSAT (version 1.2-1; Clark and Jasieniuk, 2011). The He for those loci was also calculated using the Web-based calculator (http://www.genomics.liv.ac.uk/animal/pic.html), assuming Hardy–Weinberg equilibrium (HWE). In general, S. alterniflora showed a moderate level of genetic polymorphisms in China. The average Ho ranged from 0.21 to 0.51, and the He ranged from 0.27 to 0.46 based on seven disomic loci. The average Shannon index (I) ranged from 0.26 to 0.94 in eight nondisomic loci. Five disomic loci (including SaESP06 in all five populations; SaESP09 in the Fujian, Shanghai, and Jiangsu populations; SaESP13 in the Taiwan and Hong Kong populations; SaESP18 in the Taiwan population; and SaESP19 in the Fujian population) deviated significantly from HWE (P < 0.05). It is likely that the observed departures from HWE are due to the presence of null alleles or a result of mixed reproductive modes (selfing and outcrossing) in S. alterniflora. The monomorphism at some loci observed for some populations may also reflect nonequilibrium population dynamics resulting from its recent introduction and spread in China (Tables 2 and 3).
Table 1.
Characteristics of 15 polymorphic and seven monomorphic ESSRs developed in Spartina alterniflora.
| ESSR locus | Primer sequences (5′–3′) | Repeat motif | Size (bp) | Ta (°C) | Location | A | PIC | GenBank accession no. | Putative function |
| SaESP01 | F: TATCCCCAGACACCCACAGT | (TC)10 | 268 | 60 | 3′ UTR | 6 | 0.70 | JU981477 | grancalcin |
| R: CATTCTCTGGGTCTGCAACA | |||||||||
| SaESP02 | F: GAAGAGACCGTTCAGGTTGG | (TGA)6 | 214 | 60 | 5′ UTR | 3 | 0.42 | JU981475 | cytochrome c |
| R: CCCGGCGACTAACTCTCAT | |||||||||
| SaESP03 | F: CGTGCCGACCAAGTAAAGTT | (CTC)6 | 256 | 60 | ORF | 4 | 0.53 | JU981468 | AIR12 precursor |
| R: ACCGACAGCGTGTTCCTC | |||||||||
| SaESP04 | F: AGCGAAGGGAAGATCTCGAC | (TC)9 | 155 | 60 | 5′ UTR | 3 | — | JW662119 | acyl-desaturase |
| R: GGAGGCCTTTTTAATAGCCG | |||||||||
| SaESP05 | F: CTTGCAGCGGCTATCCTTAC | (GCG)6 | 245 | 60 | ORF | 1 | — | JW662116 | DNA binding protein |
| R: ACGAGACCTTCGCTTTTGAA | |||||||||
| SaESP06 | F: AACCTGAAGTGCGTAAGCGT | (AT)9 | 245 | 60 | ORF | 5 | 0.46 | JU981466 | large secreted protein, putative |
| R: CTTCCCCCAACACTTCGATA | |||||||||
| SaESP07 | F: CCCAGCACCTCTGATTTGAT | (TTC)6 | 132 | 60 | 3′ UTR | 3 | 0.58 | JU981470 | bZIP transcription factor |
| R: ATCCACCTCTACCATGCGTC | |||||||||
| SaESP08 | F: TGCTAAGATTGGAGCAGGGT | (TAC)6 | 266 | 60 | 3′ UTR | 1 | — | JW662120 | serine acetyltransferase 3 |
| R: GCTTACATTACCGCCAAAGC | |||||||||
| SaESP09 | F: GACTTTACCGCGAAGAGCC | (TTC)7 | 192 | 60 | 5′ UTR | 3 | 0.43 | JU981464 | mitogen-activated protein kinase kinase kinase 2–like |
| R: AGGAAGCCCAAAACACACAC | |||||||||
| SaESP10 | F: CGAAAGGTTAAGCCAATCCA | (CT)9 | 211 | 60 | 5′ UTR | 8 | 0.82 | JU981473 | hypothetical protein |
| R: ACGAAAGTTGCGGGTACAAC | |||||||||
| SaESP11 | F: ACAAACTCGGCCTCCTCTTT | (CT)8 | 171 | 60 | 5′ UTR | 3 | — | JW662118 | CBL-interacting protein kinase 1 |
| R: ATAAGTACCCGCCCTTGTCC | |||||||||
| SaESP12 | F: GGAGCAACAAAGACAGAGCC | (CAC)6 | 215 | 60 | ORF | 1 | — | JW662115 | hypothetical protein |
| R: CGACTCGTGGTTGGTGAAG | |||||||||
| SaESP13 | F: CGATCCACTGGTACTGGGAC | (TGCC)5 | 196 | 60 | 3′ UTR | 2 | 0.37 | JU981471 | ribokinase |
| R: GGCTGCCATTATCGATTGTT | |||||||||
| SaESP14 | F: TCGTCACGTTGACTTGTGGT | (GA)8 | 249 | 60 | 3′ UTR | 4 | 0.62 | JU981469 | hypothetical protein |
| R: TGCTGCTTCCCTTTGATCTT | |||||||||
| SaESP17 | F: TGCTTCATGCGTTGATTAGC | (CA)9 | 150 | 60 | 3′ UTR | 5 | 0.58 | JU981465 | glycosyltransferase |
| R: TGAGATGAAGCCTGTGGAGA | |||||||||
| SaESP18 | F: GCCACAACAAGAGTTGGGTT | (AAT)6 | 171 | 60 | 3′ UTR | 4 | 0.45 | JU981474 | transcription factor |
| R: GCTGGTCCAAAGAAATCAGA | |||||||||
| SaESP19 | F: GCGCCATTACCACAGAGG | (CT)7 | 165 | 60 | 5′ UTR | 5 | 0.63 | JU981467 | choline/ethanolamine kinase |
| R: ATACGATCTGCCCTGTTTCG | |||||||||
| SaESP20 | F: TGTAGCTGTTAGCATTGGCG | (AG)10 | 170 | 60 | 3′ UTR | 3 | 0.54 | JU981476 | transcription factor |
| R: AGGACCAGCAGAGGACAGAG | |||||||||
| SaESP21 | F: ATACCGCAACGAAAGCAAAG | (TTC)6 | 205 | 60 | 3′ UTR | 1 | — | JW662114 | xyloglucan xyloglucosyl transferase |
| R: CTACTGCACCGACAAGTGGA | |||||||||
| SaESP22 | F: CCAGCGTCTCCTCTACAACC | (TTC)6 | 277 | 60 | 3′ UTR | 1 | — | JW662117 | hypothetical protein |
| R: CAGGAAACAAACGGACATGA | |||||||||
| SaESP23 | F: ATCCGTGCGTCTCTGTCTCT | (GTCA)5 | 255 | 60 | 3′ UTR | 2 | 0.24 | JU981478 | cyclophilin |
| R: CCACCATGATGCATAACAGC | |||||||||
| SaESP24 | F: ACCCTGCTAGATATGCACGC | (CCT)6 | 263 | 60 | ORF | 2 | 0.37 | JU981472 | hypothetical protein |
| R: TTGTCGAAGGAGTAGGAGGC |
Note: A = number of alleles detected; PIC = polymorphism information content; Ta = optimal annealing temperature.
Table 2.
Characterization of seven disomic polymorphic microsatellite loci in Spartina alterniflora.
| Fujian (N = 12) | Taiwan (N = 12) | Shanghai (N = 12) | Jiangsu (N = 12) | Hong Kong (N = 12) | |||||||||||
| Disomic locus | A | Ho | He | A | Ho | He | A | Ho | He | A | Ho | He | A | Ho | He |
| SaESP06 | 4 | 1.0000+ | 0.7536 | 2 | 1.0000+ | 0.5217 | 4 | 1.0000+ | 0.6014 | 2 | 1.0000+ | 0.5217 | 2 | 1.0000+ | 0.5217 |
| SaESP09 | 2 | 0.1667* | 0.5217 | 2 | 0.5000 | 0.3913 | 2 | 0.0000* | 0.2899 | 3 | 0.1667* | 0.4203 | 1 | 0.0000 | 0.0000 |
| SaESP13 | 2 | 0.7500 | 0.5181 | 2 | 0.0000* | 0.4638 | 2 | 0.3333 | 0.5072 | 2 | 0.6667 | 0.5072 | 1 | 0.1667* | 0.4638 |
| SaESP18 | 3 | 0.3333 | 0.3007 | 2 | 0.0000* | 0.5072 | 2 | 0.0833 | 0.0833 | 2 | 0.2500 | 0.2283 | 1 | 0.4167 | 0.5181 |
| SaESP19 | 3 | 0.0833* | 0.3587 | 1 | 0.0000 | 0.0000 | 4 | 0.5833 | 0.4855 | 4 | 0.8333 | 0.7065 | 1 | 0.1667 | 0.1594 |
| SaESP23 | 2 | 0.1667 | 0.1594 | 1 | 0.0000 | 0.0000 | 2 | 0.5833 | 0.4312 | 2 | 0.2500 | 0.4312 | 1 | 0.0000 | 0.0000 |
| SaESP24 | 2 | 0.5000 | 0.3913 | 1 | 0.0000 | 0.0000 | 2 | 0.3636 | 0.4156 | 2 | 0.4167 | 0.4312 | 1 | 0.7273 | 0.5195 |
Note: A = number of alleles; He = expected heterozygosity; Ho = observed heterozygosity.
Heterozygote deficiency (P < 0.05).
Heterozygote excess (P < 0.05).
Table 3.
Characterization of eight nondisomic polymorphic microsatellite loci in Spartina alterniflora.
| Fujian (N = 12) | Taiwan (N = 12) | Shanghai (N = 12) | Jiangsu (N = 12) | Hong Kong (N = 12) | |||||||||||
| Nondisomic locus | A | I | He | A | I | He | A | I | He | A | I | He | A | I | He |
| SaESP01 | 6 | 0.5868 | 0.7140 | 3 | 0.0000 | 0.0000 | 6 | 0.5623 | 0.7733 | 6 | 0.5661 | 0.7285 | 3 | 0.0000 | 0.0000 |
| SaESP02 | 3 | 0.8676 | 0.5694 | 2 | 0.0000 | 0.0000 | 2 | 0.5623 | 0.0000 | 3 | 0.9596 | 0.5952 | 2 | 0.0000 | 0.0000 |
| SaESP03 | 3 | 0.8240 | 0.6145 | 4 | 1.1187 | 0.6076 | 4 | 0.8370 | 0.5826 | 3 | 0.5661 | 0.4545 | 3 | 0.8240 | 0.5947 |
| SaESP07 | 3 | 0.2868 | 0.6661 | 3 | 0.6365 | 0.6531 | 3 | 0.6931 | 0.6250 | 3 | 0.6792 | 0.6420 | 3 | 0.6792 | 0.6420 |
| SaESP10 | 6 | 0.8676 | 0.6304 | 3 | 0.0000 | 0.0000 | 8 | 1.4735 | 0.8247 | 7 | 0.8877 | 0.8328 | 6 | 0.5623 | 0.3822 |
| SaESP14 | 3 | 0.5623 | 0.0988 | 2 | 0.0000 | 0.0000 | 4 | 1.1988 | 0.6973 | 4 | 1.5171 | 0.6811 | 4 | 0.8676 | 0.6990 |
| SaESP17 | 3 | 1.0114 | 0.0000 | 2 | 0.0000 | 0.0000 | 5 | 1.3144 | 0.6961 | 5 | 1.4241 | 0.7267 | 2 | 0.0000 | 0.0000 |
| SaESP20 | 3 | 1.1269 | 0.6454 | 3 | 0.2868 | 0.5406 | 3 | 0.8877 | 0.5261 | 2 | 0.4506 | 0.0000 | 2 | 0.0000 | 0.0000 |
Note: A = number of alleles; He = expected heterozygosity; I = Shannon index.
CONCLUSIONS
In this study, we report the development and characterization of a set of ESSRs, which was derived from a large-scale transcriptome sequencing of S. alterniflora using the Illumina Genome Analyzer II system. Fifteen polymorphic and seven monomorphic microsatellite markers were identified. Seven of those polymorphic loci display disomic inheritance. These newly developed ESSRs should be valuable for population genetic studies of this invasive species, and they can be used as new tools to trace its invasion history in China.
Appendix 1.
Voucher information for five populations of S. alterniflora used in this study. All vouchers are deposited at the Herbarium of National Sun Yat-Sen University.
| Voucher no. | Collection locality | Geographic coordinates |
| Shi 091105 | Fuzhou, Fujian, China | 26°01′04″N, 119°37′19″E |
| Xia 110401 | Mipu, Hong Kong, China | 22°29′45″N, 114°02′47″E |
| Xia 110411 | Nantong, Jiangsu, China | 32°33′96″N, 121°01′67″E |
| Xia 110415 | Chongming, Shanghai, China | 31°36′21″N, 121°49′85″E |
| Shi 101015 | Taibei, Taiwan, China | 25°07′34″N, 121°27′30″E |
LITERATURE CITED
- Altschul S. F., Maddens T. L., Schaffer A. A., Zhang J., Zhang Z., Miller W., Lipman D. 1997. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs. Nucleic Acids Research 25: 3389–3402 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Clark L. V., Jasieniuk M. 2011. POLYSAT: An R package for polyploidy microsatellite analysis. Molecular Ecology Resources 11: 562–566 [DOI] [PubMed] [Google Scholar]
- Daehler C. C., Strong D. R. 1996. Status, prediction and prevention of introduced cordgrass Spartina spp. invasion in Pacific estuaries, USA. Biological Conservation 78: 51–58 [Google Scholar]
- Doyle J. J. 1991. DNA protocols for plants—CTAB total DNA isolation. In G. M. Hewitt and A. Johnston [eds.], Molecular techniques in taxonomy, 283–293. Springer-Verlag, Berlin, Germany. [Google Scholar]
- Ellis J. R., Burke J. M. 2007. EST-SSRs as a resource for population genetic analyses. Heredity 99: 125–132 [DOI] [PubMed] [Google Scholar]
- Grabherr M. G., Haas B. J., Yassour M., Levin J. Z., Thompson D. A., Amit I., Adiconis X., et al. 2011. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nature Biotechnology 29: 644–652 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Huang X. Q., Madan A. 1999. CAP3: A DNA sequence assembly program. Genome Research 9: 868–877 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Rozen S., Skaletsky H. 2000. Primer3 on the WWW for general users and for biologist programmers. Methods in Molecular Biology (Clifton, N.J.) 132: 365–386 [DOI] [PubMed] [Google Scholar]
- Yeh F. C., Boyle T. J. B. 1997. Population genetic analysis of codominant and dominant markers and quantitative traits. Belgian Journal of Botany 129: 157 [Google Scholar]
- Zhi Y. B., Li H. L., An S. Q., Zhao L., Zhou C. F., Deng Z. 2007. Inter-specific competition: Spartina alterniflora is replacing Spartina anglica in coastal China. Estuarine, Coastal and Shelf Science 74: 437–448 [Google Scholar]