Translator Disclaimer
11 May 2015 Development of 23 Polymorphic Microsatellite Loci in Invasive Silver Wattle, Acacia dealbata (Fabaceae)
Author Affiliations +

Silver wattle, Acacia dealbata Link (Fabaceae), is a tree species native to southeastern Australia, where it is widespread and common. It has been introduced since the 18th century in various parts of the world for ornamental or forestry purposes (Kull et al., 2011). It is now considered an invasive species in southern Europe, South Africa, India, Madagascar, New Zealand, Chile, and California (Kull et al., 2011). In those regions, A. dealbata invades woodland and disturbed environments where it outcompetes native species. Acacia dealbata has a long and complex history of worldwide introductions from Australia, at least since its introduction in the early 18th century in Europe (Kull et al., 2011). Silver wattle is the focus of research both because it is a model for the impact of landscape fragmentation in its native area (Broadhurst and Young, 2006) and because it is a famous invader (Lorenzo et al., 2010), classified on the Delivering Alien Invasive Species Inventories for Europe (DAISIE) list as one of the 100 European invaders with the most significant ecological impacts (DAISIE European Invasive Alien Species Gateway, 2006). In both cases, the use of highly polymorphic genetic markers could help answer questions related to the spatial genetic structure of A. dealbata populations.

Variable genetic markers such as microsatellite markers are a common tool used to infer invasion routes of invading species and specifically to identify the sources of invasive populations (Estoup and Guillemaud, 2010). They are also commonly used in conservation biology studies to decipher the impact of environmental disturbance on the genetic structure of tree species (e.g., Aldrich et al., 1998). Recently, next-generation sequencing technologies have been used to obtain very large numbers of shotgun sequences of genomic DNA from which microsatellites could be isolated (Guichoux et al., 2011). This method requires a large effort of sequencing to obtain a sufficient number of sequences containing microsatellites. Microsatellite enrichment of the genomic DNA prior to sequencing allows a drastic cost reduction (Malausa et al., 2011). Here we present the isolation and properties of 23 polymorphic microsatellite loci of A. dealbata using 454 GS FLX Titanium (Roche Applied Science, Penzberg, Germany) pyrosequencing of a microsatellite-enriched genomic DNA library.

METHODS AND RESULTS

Total genomic DNA was extracted from leaf material of a plant collected in southeastern Australia (34°30′51.498″S, 148°49′53.3892″E) using the DNeasy Plant Kit (QIAGEN, Hilden, Germany). We followed the procedure of Malausa et al. (2011) for enrichment and sequencing. Genomic DNA was submitted to sonication, ligation to standard adapters, and purification on a NucleoFast PCR plate (Macherey-Nagel, Düren, Germany). DNA was denatured and then hybridized for 20 min at 56°C to eight biotin-labeled oligonucleotides, the sequences of which are microsatellite motifs [(AG)10, (AC)10, (AAC)8, (AGG)8, (ACG)8, (AAG)8, (ACAT)6, and (ATCT)6].

We then used primers corresponding to the adapters (5′-GTTTAAGGCCTAGCTAGCAGAATC-3′ and 5′-GATTCTGCTAGCTAGGCCTT-3′) to amplify the microsatellite-enriched DNA. Preparation of the enriched library for emulsion PCR, sequencing, and analytical processing using the 454 GS FLX Titanium followed the manufacturer's protocols. We then sorted the obtained sequences, removed the sequence of the adapters, and selected sequences with desirable properties using QDD version 1 (Meglecz et al., 2010).

Among the 33,290 sequences obtained, a total of 201 sequences longer than 80 bp, containing microsatellite motifs with at least seven uninterrupted repeats and flanking regions free of tandem repetitions, were used to design PCR primer pairs. We tested the 201 primer pairs for amplification on seven individuals, and then tested the successful primer pairs for fluorescent PCR on 32 individuals collected in southeastern Australia, between latitudes 34°37′43.1″S and 34°29′08.9″S and between longitudes 148°50′28.3″E and 148°45′23.9″E (see Appendix 1 for individual coordinates). A representative voucher specimen (CANB77329, deposited in the Australian National Herbarium [CANB], Canberra, Australia) was previously collected in the same region as the samples studied here.

Table 1.

Characteristics and variability of 23 microsatellite loci of Acacia dealbata based on 32 individuals sampled in southeastern Australia.

t01_01.gif

These 32 individuals were used to test the amplification of these loci according to the following procedure: PCR amplifications were performed in a 10-µL volume containing 1× QIAGEN Multiplex Master Mix, 0.2 µM of each primer, and ca. 20 ng of genomic DNA extracted from individual leaves using the DNeasy Plant Kit (QIAGEN). The amplification reactions were performed in an Eppendorf (Hamburg, Germany) Mastercycler thermocycler and included a 15-min denaturation step at 95°C; followed by 35 cycles of 30 s at 94°C, 1.5 min at 56°C, and 1 min at 72°C; followed by a final extension step at 60°C for 30 min. Fifty primer pairs gave positive PCR amplification of the predicted size for the seven individuals. They were then used in fluorescent PCR to amplify the 32 individuals as described above but with forward primers labeled with a fluorescent dye on the 5′ end, and with 25 cycles of PCR instead of 35. Twenty-three polymorphic microsatellites could be unambiguously scored using an ABI 3700 sequencer (Applied Biosystems, Waltham, Massachusetts, USA) with the GeneScan 500 LIZ Size Standard (Applied Biosystems) and GeneMarker software (version 1.75; SoftGenetics LLC, State College, Pennsylvania, USA) (Table 1). The sequences containing the 23 microsatellites led to no significant similarity when blasted against National Center for Biotechnology Information (NCBI) nonredundant (NR) and expressed sequence tags (dbEST) databases.

Table 2.

Variability of the 23 microsatellite loci developed for Acacia dealbata based on 32 individuals sampled in southeastern Australia.

t02_01.gif

The number of alleles measured on 32 individuals sampled from a single Australian population varied from two to 11, and Nei's expected heterozygosity (Nei, 1987) varied from 0.11 to 0.88 and was larger than 0.5 for 14 loci (Table 2). Deviations from Hardy–Weinberg equilibrium (HWE) and linkage equilibrium were tested using GENEPOP 4.0 (Rousset, 2008). We took into account multiple testing (in the case of HWE tests) and nonindependence between tests (in the case of linkage tests) by using the false discovery rate (Benjamini and Hochberg, 1995) and the sequential Bonferroni (Sokal and Rolf, 1995: p. 236) adjustments, respectively. Five loci (Ad-145, Ad-41, Ad-59, Ad-116, and Ad-45) significantly departed from HWE after false discovery rate adjustment and displayed significant heterozygote deficiency (Table 1). Linkage disequilibrium was detected for three pairs of loci (between Ad-116 and Ad-137, Ad-116 and Ad-97, and Ad-49 and Ad-86). Twenty-one microsatellite loci could be amplified in two sets of PCR multiplex mixes, one with 14 and the other with seven primer pairs (Table 1). The two other primer pairs produced unspecific amplifications when used in multiplex PCR and thus were not included in any multiplex mix.

CONCLUSIONS

We chose to present all 23 primer pairs although some of them may display Hardy–Weinberg or linkage disequilibrium because those disequilibria may be specific to the population sampled for the current study. The microsatellite markers developed here for A. dealbata display a moderate to large level of polymorphism in individuals sampled in natura in the native area of the species. This level of polymorphism should, however, be large enough for population genetic analyses to provide valuable information regarding the biology and worldwide invasion routes of A. dealbata.

LITERATURE CITED

1.

P. R. Aldrich , J. L. Hamrick , P. Chavarriaga , and G. Kochert . 1998. Microsatellite analysis of demographic genetic structure in fragmented populations of the tropical tree Symphonia globulifera. Molecular Ecology 7: 933–944. Google Scholar

2.

Y. Benjamini , and M. Hochberg . 1995. Controlling the false discovery rate—A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B. Methodological 57: 289–300. Google Scholar

3.

L. M. Broadhurst , and A. G. Young . 2006. Reproductive constraints for the long-term persistence of fragmented Acacia dealbata (Mimosaceae) populations in southeast Australia. Biological Conservation 133: 512–526. Google Scholar

4.

DAISIE European Invasive Alien Species Gateway. 2006. Species Factsheet: Acacia dealbata. Website  http://www.europe-aliens.org/speciesFactsheet.do?speciesId=12749 [accessed 8 April 2015]. Google Scholar

5.

A. Estoup , and T. Guillemaud . 2010. Reconstructing routes of invasion using genetic data: Why, how and so what? Molecular Ecology 19: 4113–4130. Google Scholar

6.

E. Guichoux , L. Lagache , S. Wagner , P. Chaumeil , P. Léger , O. Lepáis , C. Lepoittevin , et al. 2011. Current trends in microsatellite genotyping. Molecular Ecology Resources 11: 591–611. Google Scholar

7.

C. A. Kull , C. M. Shackleton , P. J. Cunningham , C. Ducatillion , J. M. Dufour-Dror , K. J. Esler , J. B. Friday , et al. 2011. Adoption, use and perception of Australian acacias around the world. Diversity and Distributions 17: 822–836. Google Scholar

8.

P. Lorenzo , L. González , and M. J. Reigosa . 2010. The genus Acacia as invader: The characteristic case of Acacia dealbata Link in Europe. Annals of Forest Science 67: 101. Google Scholar

9.

T. Malausa , A. Gilles , E. Meglecz , 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

10.

E. Meglecz , 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 26: 403–404. Google Scholar

11.

M. Nei 1987. Molecular evolutionary genetics. Columbia University Press, New York, New York, USA. Google Scholar

12.

F. Rousset 2008. GENEPOP'007: A complete re-implementation of the GENEPOP software for Windows and Linux. Molecular Ecology Resources 8: 103–106. Google Scholar

13.

R. R. Sokal , and F. J. Rolf . 1995. Biometry: The principles and practice of statistics in biological research, 3rd ed. W. H. Freeman and Company, New York, New York, USA. Google Scholar

Appendices

Appendix 1.

Sampling information of the 32 Acacia dealbata individuals used in this study.

tA01_01.gif

Notes

[1] The authors thank the Institut national de la recherche agronomique (INRA) for providing the AIP BioRessources ‘EcoMicro’ grant to T.M.

Thomas Guillemaud, Linda Broadhurst, Isabelle Legoff, Martin Henery, Aurélie Blin, Catherine Ducatillion, Nathalie Ferrando, and Thibaut Malausa "Development of 23 Polymorphic Microsatellite Loci in Invasive Silver Wattle, Acacia dealbata (Fabaceae)," Applications in Plant Sciences 3(5), (11 May 2015). https://doi.org/10.3732/apps.1500018
Received: 20 February 2015; Accepted: 1 March 2015; Published: 11 May 2015
JOURNAL ARTICLE
PAGES


SHARE
ARTICLE IMPACT
Back to Top