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26 July 2017 Characterization of Microsatellite Markers in the African Tropical Tree Species Guibourtia ehie (Fabaceae, Detarioideae)
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Guibourtia ehie (A. Chev.) J. Léonard (Fabaceae, Detarioideae) is a timber species found in evergreen and semideciduous moist forests from Liberia to Gabon (Tosso et al., 2015). It is distributed on both sides of the Dahomey Gap, a portion of forest–savanna mosaic separating the Upper and Lower Guinean rainforest blocks (Salzmann and Hoelzmann, 2005). Guibourtia ehie is an insect-pollinated and wind-dispersed species (Tosso et al., 2015) exhibiting an abundant natural regeneration around the mother plant (Lemmens et al., 2008). Known as ovengkol in Gabon and amazakoué in Ivory Coast, it produces wood of high economic value. The major threat to this species (registered as vulnerable on the IUCN Red List) is logging, which causes local population declines (Hawthorne, 1995). Guibourtia ehie is therefore a good candidate to assess the impact of logging on gene flow (pollen and seed dispersal) and to study spatial genetic diversity issues before considering conservation plans. In addition, the wide spatial distribution of this species will likely be useful to better understand the history of African vegetation and the role of the Dahomey Gap in relation to successive past environmental changes. Because only a few of the microsatellites (simple sequence repeats [SSRs]) previously developed for G. tessmannii (Harms) J. Léonard (a central African species) cross-amplified in G. ehie (Tosso et al., 2016), we developed here a new set of polymorphic SSRs.


Development of microsatellites—To identify and characterize SSRs, total genomic DNA was extracted (from G. ehie dry leaf, voucher FT0272; Appendix 1) following the cetyltrimethylammonium bromide (CTAB) protocol described in Fu et al. (2005). We used the Illumina MiSeq platform (GIGA platform, Liège, Belgium; Illumina, San Diego, California, USA) to construct a nonenriched genomic DNA library following Mariac et al. (2014), generating 255,460 paired-end reads 145 ± 3 bp long, which were pair-assembled with PANDAseq (Masella et al., 2012). The software QDD with the default settings (Meglécz et al., 2014) was used to identify 3597 microsatellite loci following the three classical steps: (i) SSR detection, (ii) elimination of similar sequences, and (iii) primer design. Among the 3597 loci, we selected a subset of 64 loci according to the following criteria: (i) having at least eight di- or trinucleotide repeats, (ii) having primers located at least 20 bp from the SSR motif, and (iii) characterized by PCR products 130–300 bp long. To have a good distribution of loci sizes and to facilitate multiplexing in the next steps, we then selected 48 loci for amplification tests. Each locus was labeled with the fluorochromes FAM, NED, VIC, or PET by adding one of four possible linkers (Q1–Q4; Micheneau et al., 2011) to the 5′ end of the forward primer (Table 1).

Table 1.

Characteristics of 19 nuclear microsatellite markers developed for Guibourtia ehie.


Microsatellite screening—Amplification tests of 48 primer pairs were performed using two individuals of G. ehie (FT0288 and FT0478; Appendix 1) in 15-µL PCR reactions with the following conditions: 1.5 µL of buffer (10×), 0.6 µL of MgCl2 (25 mM), 0.45 µL of dNTPs (10 mM each), 0.3 µL of each primer (0.2 µM), 0.08 µL of TopTaq DNA Polymerase (5 U/µL; QIAGEN, Venlo, The Netherlands), 1.5 µL of Coral Load, 1 µL of template DNA (of ca. 10–50 ng/µL), and 9.27 µL of water. PCR conditions were: 94°C (4 min); 30 cycles of 94°C (30 s), 57°C (45 s), and 72°C (1 min); and a final extension at 72°C (10 min). Amplification products stained with 9 µL of TE 1× were examined using the QIAxcel DNA Screening Kit (method AL420; alignment marker 15–5000 bp; size marker 100–2500 bp; QIAGEN). Thirty loci amplified the expected target fragments out of the 48 primer pairs selected for the initial trial.

These 30 loci were further tested in eight individuals from Ghana and Cameroon (Appendix 1). PCR reactions were performed for each of the 30 loci in 15-µL total volumes: 0.15 µL of the reverse and 0.1 µL of the forward (0.2 µM for both) microsatellite primers, 0.15 µL of Q1–Q4 labeled primers (0.2 µM each), 7.5 µL of Type-it Microsatellite PCR Kit (QIAGEN), 3 µL of 5× Q-solution, 3.1 µL of H2O, and 1 µL of DNA. PCR conditions were: 5-min initial denaturation at 95°C; followed by 25 cycles of 95°C for 30 s, 57°C for 90 s, and 72°C for 1 min; 10 cycles of 94°C for 30 s, 53°C for 45 s, and 72°C for 60 s; and a final elongation step at 60°C for 30 min. All individuals were genotyped on an ABI3730 sequencer (Applied Biosystems, Lennik, The Netherlands) at the Department of Evolutionary Biology and Ecology, Université Libre de Bruxelles (Brussels, Belgium) using 1.1 µL of each PCR product, 12 µL of Hi-Di Formamide (Life Technologies, Carlsbad, California, USA), and 0.3 µL of Map-Marker 500 labeled with DY-632 (Eurogentec, Seraing, Belgium). We selected 19 primer pairs exhibiting clear chromatograms with no ambiguity in allele size determination. Eighteen primer pairs were polymorphic, and one locus (GuiE-ssr04) was monomorphic.

These loci were included in four multiplexed reactions (Table 1) using Multiplex Manager 1.0 software (Holleley and Geerts, 2009). To assess their polymorphism level, we genotyped between 15 and 23 individuals in each of four populations from Ghana, Ivory Coast, Liberia, and Cameroon, totaling 78 samples (Table 2, Appendix 1). We conducted multiplexed PCR reactions with the conditions as previously described, except that we readjusted the quantity of H2O to obtain a total volume of 15 µL.

Data analysis—INEst 1.0 (Chybicki and Burczyk, 2009) was used to calculate the following indices on each of the four populations: number of alleles per locus, observed and expected heterozygosities, and inbreeding coefficient. We also tested deviation from Hardy–Weinberg equilibrium for each locus with SPAGeDi (Hardy and Vekemans, 2002).

Table 2.

Genetic characterization of 19 newly developed microsatellite markers in four populations of Guibourtia ehie.a


The mean number of alleles per locus among the four populations was seven (range 1–11). The observed heterozygosity (mean ± SE) was 0.28 ± 0.10 (range 0–0.85), 0.18 ± 0.17 (range 0–0.48), 0.19 ± 0.09 (range 0–0.67), and 0.22 ± 0.07 (range 0–0.65) for the Ghana, Ivory Coast, Cameroon, and Liberia populations, respectively. The expected heterozygosity was 0.41 ± 0.11 (range 0–0.92), 0.59 ± 0.07 (range 0–0.88), 0.46 ± 0.10 (range 0–0.88), and 0.48 ± 0.08 (range 0–0.84) for the Ghana, Ivory Coast, Cameroon, and Liberia populations, respectively. Significant deviation from Hardy–Weinberg equilibrium was observed for 13 loci at least in one population, in part due to the presence of null alleles (Table 2). All these SSR sequences have been deposited in GenBank (Table 1).

Cross-amplification in other Guibourtia species—We tested the 19 loci on 13 congeneric species using the PCR conditions described above. Three to eight of the 19 loci successfully amplified in four species from subgenus Gorskia J. Léonard (to which G. ehie belongs), whereas two to six amplified for subgenus Pseudocopaiva J. Léonard and two to three amplified for subgenus Guibourtia (Table 3). The locus GuiE-ssr15 amplified in all species. The limited transferability of G. ehie SSRs, which was also observed for G. tessmannii SSRs (Tosso et al., 2016), indicates a rather deep molecular divergence among Guibourtia species.


In this study, we developed 18 polymorphic microsatellite markers in G. ehie. These microsatellite markers will be useful to study intraspecific diversity and gene flow. They are also suitable to study the demographic history of G. ehie and provide insights into the past changes in African moist forest cover.

Table 3.

Cross-amplification results of 19 microsatellite markers isolated from Guibourtia ehie and tested in 13 congeneric species belonging to three Guibourtia subgenera.a



This work received financial and technical support from the Fonds pour la Formation à la Recherche dans l'Industrie et l'Agriculture (FRIA), the Fonds de la Recherche Scientifique (F.R.S.-FNRS, grant T.0163.13), Belgian Science Policy (AFRIFORD project), Fonds Français pour l'Environnement Mondial (FFEM; DynAfFor project), CEB Precious Woods, Wijma Cameroun S.A., and Centre national de la recherche scientifique et technique (CENAREST). The authors acknowledge Bérengère Doucet and Toussaint Abessolo for sampling.


  1. Chybicki, I. J., and J. Burczyk. 2009. Simultaneous estimation of null alleles and inbreeding coefficients. Journal of Heredity 100: 106–113. Google Scholar

  2. Fu, X., Y. Huang, S. Deng, R. Zhou, G. Yang, X. Ni, W. Li, and S. Shi. 2005. Construction of a SSH library of Aegiceras corniculatum under salt stress and expression analysis of four transcripts. Plant Science 169: 147–154. Google Scholar

  3. Hardy, O. J., and X. Vekemans. 2002. SPAGeDi: A versatile computer program to analyse spatial genetic structure at the individual or population levels. Molecular Ecology Notes 2: 618–620. Google Scholar

  4. Hawthorne, W. D. 1995. Ecological profiles of Ghanaian forest trees. Tropical Forestry Papers 29. Oxford Forestry Institute, Oxford, United Kingdom. Google Scholar

  5. Holleley, C. E., and P. G. Geerts. 2009. Multiplex Manager 1.0: A crossplatform computer program that plans and optimizes multiplex PCR. BioTechniques 46: 511–517. Google Scholar

  6. Lemmens, R. H. M. J., D. Louppe, and A. A. Oteng-Amoako. 2008. Bois d'oeuvre, vol. 2. PROTA, Wageningen, The Netherlands. Google Scholar

  7. Mariac, C., N. Scarcelli, J. Pouzadou, A. Barnaud, C. Billot, A. Faye, A. Kougbeadjo, et al. 2014. Cost-effective enrichment hybridization capture of chloroplast genomes at deep multiplexing levels for population genetics and phylogeography studies. Molecular Ecology Resources 14: 1103–1113. Google Scholar

  8. Masella, A. P., A. K. Bartram, J. M. Truszkowski, D. G. Brown, and J. D. Neufeld. 2012. PANDAseq: Paired-end assembler for Illumina sequences. BMC Bioinformatics 13: 31. Google Scholar

  9. Meglécz, E., N. Pech, A. Gilles, V. Dubut, P. Hingamp, A. Trilles, R. Grenier, and J. F. Martin. 2014. QDD version 3.1: A user-friendly computer program for microsatellite selection and primer design revisited: Experimental validation of variables determining genotyping success rate. Molecular Ecology Resources 14: 1302–1313. Google Scholar

  10. Micheneau, C., G. Dauby, N. Bourland, J.-L. Doucet, and O. J. Hardy. 2011. Development and characterization of microsatellite loci in Pericopsis elata (Fabaceae) using a cost-efficient approach. American Journal of Botany 98: e268–e270. Google Scholar

  11. Salzmann, U., and P. Hoelzmann. 2005. The Dahomey Gap: An abrupt climatically induced rain forest fragmentation in West Africa during the late Holocene. Holocene 15: 190–199. Google Scholar

  12. Tosso, F., K. Daïnou, O. J. Hardy, B. Sinsin, and J.-L. Doucet. 2015. Le genre Guibourtia Benn., un taxon à haute valeur commerciale et sociétale (synthèse bibliographique). Biotechnologie, Agronomie, Société et Environnement 19: 71–88. Google Scholar

  13. Tosso, F., J.-L. Doucet, E. Kaymak, K. Daïnou, J. Duminil, and O. J. Hardy. 2016. Microsatellite development for the genus Guibourtia (Fabaceae, Caesalpinioideae) reveals diploid and polyploid species. Applications in Plant Sciences 4: 1600029. Google Scholar


Appendix 1.

Voucher information for the Guibourtia samples used in this study.a

Félicien Tosso, Jean-Louis Doucet, Jérémy Migliore, Kasso Daïnou, Esra Kaymak, Franck S. Monthe Kameni, and Olivier J. Hardy "Characterization of Microsatellite Markers in the African Tropical Tree Species Guibourtia ehie (Fabaceae, Detarioideae)," Applications in Plant Sciences 5(7), (26 July 2017).
Received: 18 March 2017; Accepted: 1 May 2017; Published: 26 July 2017

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