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1 October 2013 Isolation, via 454 Sequencing, and Characterization of Microsatellites for Vachellia farnesiana(Fabaceae: Mimosoideae)
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Mimosa bush, Vachellia farnesiana (L.) Wight & Arn. (synonym Acacia farnesiana (L.) Willd.), is a woody mimosoid legume with a pantropical distribution. It has several common names in its native range, including mimosa bush, sweet acacia, cassie, and huizache. Acacia Mill., if treated in the broad sense (sensu lato [s.l.]), is a large polyphyletic genus, with at least five lineages that may be recognized as genera: Acacia sensu stricto (s.s.), Acaciella Britton & Rose, Mariosousa Seigler & Ebinger, Senegalia Raf., and Vachellia Wight & Arn. (Maslin, 2008; Bouchenak-Khelladi et al., 2010). The genus Vachellia is composed of a predominantly African clade and a predominantly American clade (Bouchenak-Khelladi et al., 2010). Vachellia farnesiana is part of the American clade, but has a distribution that extends well beyond the Americas, and it is considered invasive in some countries. Its arrival date in Australia, and hence its status as native or alien, remains unknown, but V. farnesiana may have arrived prior to European colonization (Bean, 2007). The Spanish and Portuguese introduced the species to Europe in the 17th century. At this time, the two countries had a strong colonial presence around the Indian Ocean, through which further dispersal of the plant was possible. However, natural ocean currents and pre-European indigenous traders may have played a role in earlier dispersals. Genetic data from V. farnesiana may be useful in determining the dispersal pathways of this plant to populations outside of the Americas. Microsatellite markers have been developed previously for the invasive V. nilotica (L.) P. J. H. Hurter & Mabb. (Wardill et al., 2004). However, only a total of five loci were developed, and it is unknown how many of these will cross amplify in V. farnesiana. It was, therefore, necessary to develop new markers for V. farnesiana to facilitate our investigations of population genetics and plant dispersal out of the native range.

METHODS AND RESULTS

Genomic DNA (5 µg) was isolated from one individual of V. farnesiana from silica gel-dried leaves with the QIAGEN DNeasy Plant Mini Kit (QIAGEN, Valencia, California, USA) as per the manufacturer's protocol. The DNA was sent to the Australian Genomic Research Facility (AGRF) in Brisbane, Australia, for shotgun sequencing on a Titanium GS-FLX (454 Life Sciences, a Roche Company, Branford, Connecticut, USA) following Gardner et al. (2011). The sample occupied 12.5% of a plate and produced 59,289 individual sequences, with an average fragment size of 307 bp; 1.9% of the sequences contained microsatellites. The raw data from shotgun sequencing were deposited in the Dryad Digital Repository (doi:10.5061/dryad.jd183; Meglécz et al., 2012). We used the program QDD version 1.3 (Meglécz et al., 2010) to screen the raw sequences with eight or more di-, tri-, tetra-, or pentabase repeats. Redundant sequences were removed and primers were designed with a specified PCR product length of 80–480 bp using Primer3 (Rozen and Skaletsky, 2000) in QDD; default settings were maintained for all parameters except product length. The software identified and designed primers for a total of 68 loci, of which 47 contained simple repeats and 21 contained tandem repeats (Table 1).

We followed the procedure outlined in Gardner et al. (2011) for further development of the 47 loci containing simple repeats. The 47 loci were trialed for amplification using seven V. farnesiana individuals, each from a different population (Appendix 1), and 10-µL reactions containing 1× buffer, 0.5 U HotStarTaq DNA polymerase (QIAGEN), 1.5 mM MgCl2, 0.25 mM of each dNTP, 250 nM each forward and reverse locus-specific primer, and 10–50 ng genomic DNA. The following PCR conditions were used: 95°C for 15 min; followed by 28 cycles at 95°C for 30 s, 58°C for 90 s, and 72°C for 30 s; and a final elongation step at 60°C for 30 min. PCR products were visualized on a 1.5% agarose gel stained with ethidium bromide. Twenty-eight loci amplified a product of the expected size for all seven samples, with no unexpected secondary bands. These 28 loci were tested for polymorphism using forward primers tagged with 454A sequence tags and 454A sequencing tags labeled with either 6-FAM, NED, HEX, or PET (Applied Biosystems, Foster City, California, USA) following the method of James et al. (2011) and were run by Macrogen (Seoul, Korea) on a 3730x1 DNA sequencer (Applied Biosystems) with a GeneScan 500 LIZ Size Standard (Applied Biosystems). Of the 28 loci tested, 26 loci (93%) were polymorphic, one (3.6%) was monomorphic, and one (3.6%) did not amplify for all samples under these conditions. Of the 26 polymorphic loci, 11 (42%) produced alleles that were affected by stuttering or amplified weakly and were removed from further consideration. The remaining 15 (54%) polymorphic loci (Table 1) were screened for variation in 20 recently collected individuals from a single population from southern Mexico, one herbarium specimen also from southern Mexico, and 20 recently collected individuals from northwestern Australia (Table 2), with DNA isolation, PCR, and fragment length analysis as described above. For each locus, we calculated the number and range of alleles, observed (Ho) and expected heterozygosity (He), and deviation from Hardy-Weinberg equilibrium (HWE) using GenAlEx (Peakall and Smouse, 2006). P values from HWE tests were adjusted for multiple tests of significance using the sequential Bonferroni method (Holm, 1979). The number of alleles per locus ranged from one to 12 across these 41 individuals, and He ranged from 0 to 0.84. Within the Mexican samples, seven polymorphic loci were in HWE, five significantly deviated from HWE, and three were monomorphic. Within the Australian samples, nine polymorphic loci were in HWE, five significantly deviated from HWE, and one was monomorphic (Table 2). We used MICRO-CHECKER 2.2.3 (van Oosterhout et al., 2004) to check each locus for further evidence of null alleles, scoring error due to stuttering, and large allele dropout. Four loci (Af03, Af47, Af32, Af26) showed significant null allele frequencies at the target site, or evidence of scoring error due to stuttering. None of the loci showed evidence of large allele dropout. We checked all pairs of loci for linkage disequilibrium in GENEPOP and none were significant after sequential Bonferroni adjustment.

TABLE 1.

Characterization of 15 polymorphic microsatellite loci of Vachellia farnesiana.

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Primers for the 15 selected loci were also tested for amplification and cross-species transferability in 12 individuals of V. nilotica (8 recently collected and 4 herbarium specimens), two herbarium specimens of V. aroma (Gillies ex Hook. & Arn.) Seigler & Ebinger, and one each of the Australian species V. ditricha (Pedley) Kodela and V. suberosa (A. Cunn. ex Benth.) Kodela (Appendix 2). Isolation of DNA, PCR, and fragment analysis were as described above. Thirteen of the 15 loci amplified successfully in the majority of individuals of V. nilotica, and eight of these were polymorphic for the small number of individuals examined. Amplification success was lower for the remaining species (5–12 of 15 loci), possibly due to the use of DNA isolated from herbarium specimens.

CONCLUSIONS

These markers will be used to document the genetic diversity of V. farnesiana and to investigate the dispersal pathways leading to its current pantropical distribution. Given the successful cross-amplification of these loci for a broad range of Vachellia species, the primers may be useful for studies of the genetic diversity of other Vachellia species.

TABLE 2.

Genetic properties of 15 microsatellite loci of Vachellia farnesiana.a

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LITERATURE CITED

1.

A. R. Bean 2007. A new system for determining which plant species are indigenous in Australia. Australian Systematic Botany 20: 1–43. Google Scholar

2.

Y. Bouchenak-Khelladi , O. Maurin , J. Hurter , and M. Van Der Bank . 2010. The evolutionary history and biogeography of Mimosoideae (Leguminosae): An emphasis on African acacias. Molecular Phylogenetics and Evolution 57: 495–508. Google Scholar

3.

M. G. Gardner , A. J. Fitch , T. Bertozzi , and A. J. Lowe . 2011. Rise of the machines: Recommendations for ecologists when using next generation sequencing for microsatellite development. Molecular Ecology Resources 11: 1093–1101. Google Scholar

4.

S. Holm 1979. A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics 6: 65–70. Google Scholar

5.

E. A. James , G. K. Brown , R. Citroen , M. Rossetto , and C. Porter . 2011. Development of microsatellite loci in Triglochin procera (Juncaginaceae), a polyploidy wetland plant. Conservation Genetics Resources 3: 103–105. Google Scholar

6.

B. R. Maslin 2008. Generic and subgeneria names in Acacia following retypification of the genus. Muelleria 26: 7–9. Google Scholar

7.

E. Meglécz , 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

8.

E. Meglécz , G. Nève , E. Biffin , and M. G. Gardner . 2012. Breakdown of phylogenetic signal: A survey of microsatellite densities in 454 shotgun sequences from 154 non model eukaryote species. PLoS ONE 7: e40861. Google Scholar

9.

R. E. Peakall , and P. E. Smouse . 2006. GenAlEx6: Genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6: 288–295. Google Scholar

10.

S. Rozen , and H. J. Skaletsky . 2000. Primer3 on the WWW for general users and for biologist programmers. In S. Misener and S. A. Krawetz [eds.], Methods in molecular biology, vol. 132: Bioinformatics methods and protocols, 365–386. Humana Press, Totowa, New Jersey, USA. Google Scholar

11.

C. van Oosterhout , 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

12.

T. J. Wardill , K. D. Scott , G. C. Graham , and M. P. Zalucki . 2004. Isolation and characterization of microsatellite loci from Acacia nilotica ssp. indica (Mimosaceae). Molecular Ecology Notes 4: 361–363. Google Scholar

Appendices

APPENDIX 1.

Locality data for the seven individuals of Vachellia farnesiana used in the initial screening of 47 loci.

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APPENDIX 2.

Voucher information for Vachellia species used in this study.

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Notes

[1] This project was funded through an Australian Research Council Discovery Project grant (DP1093100 to H. Rangan, D.J.M., and C. A. Kull). The authors thank Alison Fitch (Flinders University) for assistance and support; R. van Klinken (CSIRO Ecosystem Sciences), N. March (Department of Environment and Natural Resources, Queensland), R. Segura (CSIRO Mexican Field Station), J. Miller (CSIRO Plant Industries), the Missouri Botanical Garden, and Arizona State University Vascular Plant Herbarium for providing samples; and J. Birch (Royal Botanic Gardens, Melbourne) for comments on an early draft.

Karen L. Bell, Daniel J. Murphy, and Michael G. Gardner "Isolation, via 454 Sequencing, and Characterization of Microsatellites for Vachellia farnesiana(Fabaceae: Mimosoideae)," Applications in Plant Sciences 1(10), (1 October 2013). https://doi.org/10.3732/apps.1300035
Received: 1 May 2013; Accepted: 1 June 2013; Published: 1 October 2013
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