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Fourteen simple-sequence repeats newly developed for population genetic studies in Prosopis africana (FabaceaeMimosoideae)



There is very limited genetic knowledge in Prosopis africana, an important sub-Saharan multi-purpose tree species. Availability of highly polymorphic genetic markers would be helpful for future genetic work.


Leaf samples from 15 trees were used to develop simple sequence repeat (SSR) markers. Size-selected fragments from genomic DNA were enriched for repeats and the library was analyzed on an Illumina MiSeq platform. Fourteen SSRs were selected and applied in two Burkinabe populations (40 adult trees each). The number of alleles varied from 4 to 20, evenness (effective number of alleles/observed number of alleles) averaged to 0.54 and unbiased heterozygosity ranged from 0.305 to 0.925 over all loci and populations. Null alleles were not detected.


Due to the high level of polymorphism and lack of null alleles the developed SSRs can be effectively employed in population genetic studies.


African mesquite (Prosopis africana [Fabaceae: Mimosoideae]) is a valuable, medium-sized (up to 20 m height), multi-purpose tree in sub-Saharan Africa. It is the only species of the genus Prosopis native to Africa and occurs at sites with 600–1500 mm annual rainfall [1] (and references therein). The modeled species distribution covers savannas and dry forests of tropical Africa within an approximately 500 km wide band from Senegal to Sudan (Gaisberger et al. unpublished results). The hard wood has a high calorific value making it highly valuable as fuel wood and for charcoal production. The leaves, bark and roots are used for various medicinal purposes. Its pods are preferred fodder for livestock and wildlife. Seeds are dispersed endozoochorously and germinate freely after passing through the digestive system of ungulates. Fermented seeds serve as seasoning ([1] and references therein).

Genetic knowledge of African mesquite is very scarce as only results from a single provenance trial with material originating from Niger and Burkina Faso are at hand. Survival, growth and wood density seem to be related to humidity of the seed source [1, 2]. So far no specific genetic markers have been available for P. africana. However, simple-sequence repeat markers (SSRs) were developed for other Prosopis species [3,4,5]. Unfortunately, cross-species amplification of SSRs developed by Mottura et al. [4] was not successful (Zerbo et al. unpublished results). Hence, the major objective of this study was to develop highly polymorphic SSRs for this species.

Materials and methods


For primer development DNA was extracted from leaves collected from adult trees in two populations from Burkina Faso. Twelve individuals were selected as screening panel in Yeimzuro (13°36′40.07″N, 2°9′44.30″W) and three in Padiali (11°8′35.50″N, 0°48′55.60″E). An emphasis was put on selecting more trees in Yeimzuro due to its location in the North of Burkina Faso as less diversity is expected in that region as observed by Schmidt et al. at the species level [6].

The polymorphism of the developed markers was tested and the population structure was estimated using leaves collected from 40 trees per site in two other populations: Raguitenga (12°47′2.74″N, 1°6′55.88″W) and Bandougou (10°58′43.90″N, 4°51′24.43″W). The former is located in the Sudano-Sahelian climatic zone with a savannah type of vegetation and tree density is low; in the latter, tree density is high and the site is located in the Sudanian climatic zone with dry forest vegetation type. These populations are separated by about 500 km, occurring in two different climatic zones, which were chosen to obtain a better genetic diversity estimate of the species over a larger area.

DNA extraction and SSRs development

DNA was extracted using the DNeasy Plant Mini Kit and the DNeasy 96 Plant Kit (QIAGEN, Hombrechtikon, Switzerland) following the manufacturer’s protocols. SSRs were developed by Ecogenics (Balgach, Switzerland). Size-selected fragments from genomic DNA were enriched for SSR content by using magnetic streptavidin beads and biotin-labeled CT and GT repeat oligonucleotides. The SSR-enriched library was analysed on an Illumina MiSeq platform using the Nano 2 × 250 v2 format. After assembly, 3′635 contigs or singlets contained a microsatellite insert with a tetra- or a trinucleotide of at least 6 repeat units or a dinucleotide of at least 10 repeat units. Suitable primer design was possible in 2′232 microsatellite candidates by Ecogenics (Balgach, Switzerland) using the Primer3 software [7]; for subsequent analysis 14 random loci were selected which was deemed a sufficient number for population genetic studies. To determine polymorphisms of these newly developed markers, the approach originally described by Schuelke [8] was used by adding a universal 18 base pair M13 tail to the 5′-end of forward primers. Multiplex PCR amplification was optimized to be performed in a 10 μl reaction volume containing 2–10 ng of genomic DNA, 5 μl HotStarTaq Master Mix (Qiagen), double distilled water, and 0.1–0.3 µM of forward and reverse primer each. The following cycling protocol on a TC-412 programmable thermal controller (Techne) was used: 35 cycles with 94 °C for 30 s, 56 °C for 90 s, and 72 °C for 60 s. Before the first cycle, a prolonged denaturation step (95 °C for 15 min) was included and the last cycle was followed by a 30 min extension at 72 °C. For determination of allele sizes on an ABI3730 (applied biosystems) M13 primers were labelled either with Atto565, Atto550, Atto532 (Sigma Aldrich), or FAM (applied biosystems) and an internal size standard (LIZ500; applied biosystems) was added.

Statistical analysis of genetic parameters

Standard genetic parameters were estimated with GenAlEx 6.5 [9]. Micro-Checker version 2.2.3 [10] was used to test the presence of null alleles. Linkage disequilibrium (LD) was analysed by Genepop V4.4 [11, 12] setting Markov chain parameter to 10 000 for the dememorization number, 100 for the number of batches with 5000 iterations per batch. To detect possible population size reduction, the program BOTTLENECK V1.2.02 was used [13]. The infinite alleles model (IAM), the stepwise mutation model (SMM) and the two-phase mutation model (TPM) were applied using 70% of SMM in TPM with 1 000 iterations to perform the Wilcoxon test which produce the most reliable results [14].

Results and discussion

SSRs characterization

The 14 newly developed primers were utilized for further analysis of two Burkinabe populations (Raguitenga and Bandougou). All the fourteen tested SSRs were polymorphic for 2-bp perfect tandem repeats and the number of alleles ranged from 6 to 14 in the screening panel. The characteristics of the developed markers are summarized in Table 1.

Table 1 Description of 14 SSRs developed for Prosopis africana

Genetic characterization of populations

In both populations investigated to test the usefulness of these markers for genetic analysis (Raguitenga and Bandougou) all 14 loci were polymorphic (Table 2). The number of alleles ranged from four to 21. Neither null alleles nor linkage disequilibrium were detected between locus pairs after Bonferroni corrections. The average fixation index over all populations was close to zero.

Table 2 Population genetic parameters based on 14 SSRs developed for Prosopis africana

When the sample size was progressively increased from 10 to 80 (all individuals studied), the number of alleles remained quite constant at four in the locus with the lowest number of alleles (Proafr_11069c), while this number ranged from 10 to 21 for Proafr_12199s, which was the locus with the largest number of alleles (Fig. 1). It was thus concluded that sample sizes of 50 individuals are sufficient for population genetic analysis. For a paternity analysis utilizing the developed markers it is particularly useful to know how many loci will be required. Using only the first four loci from Table 2 (showing a moderate number of alleles) for paternity analysis, the exclusion probability for excluding a putative parent pair already amounted to 0.998; therefore already a subset of the markers will be adequate for paternity analysis. Using all 14 loci the exclusion probability in both populations studied was larger than 0.9999.

Fig. 1

Number of alleles detected in relation to the sample size for the most (Proafr_12199s dotted line) and the least polymorphic locus (Proafr_11069c solid line)

The Mnsr (maximum number of sequence repeats) per locus ranged from 20 to 45 in Raguitenga and from 20 to 35 in Bandougou indicating the potential finding of additional alleles in other P. africana populations. In total five loci (one in Raguitenga and four in Bandougou) showed significant deviation from HWE (Hardy–Weinberg expectation). While the Raguitenga population consisted of even-aged mature trees, in Bandougou different age classes were sampled; therefore we expected a higher number of deviations in Bandougou as in tree species with mixed-mating young cohorts often deviate more strongly from HWE (e.g., [15]).

The evenness of the allele distribution (Ne/Na) which theoretically ranges from 0 (lack of evenness) to 1 (complete evenness) varied from 0.28 (Proafr_09196c) to 0.77 (Proafr_10663c) with an average value of 0.5 for each population. At least seven loci showed an evenness value above the average evenness. Loci with a high evenness and high number of alleles should be selected for the analysis when the number of loci is restricted [16].

Generally the degree of polymorphism detected in our data was high. The number of alleles and unbiased heterozygosity was much higher in our populations than in those developed for P. alba, P. chilensis, P. flexuosa, P. rubriflora and P. ruscifolia [3,4,5]. However, we should keep in mind that the sample sizes were smaller in these studies (<20 individuals per population).

Both populations showed bottleneck effects (P < 0.05) under the IAM and only Raguitenga under the SMM (Table 3). According to Cornuet and Luikart [17] the SMM is the most conservative model for testing significant heterozygosity excess caused by a bottleneck. Raguitenga is located in a dry area where generally few tree species are found at a low density. Prosopis africana is overexploited in this area leading to a reduction of its population size. Therefore the observed bottleneck effect in this population was not unexpected.

Table 3 Wilcoxon test results for the three models IAM, TPM and SMM


All our 14 newly developed markers were highly polymorphic and no null alleles were detected. Using these SRRs, it was possible to quantify the genetic structure of two populations. These SSRs are very valuable for population genetic studies including the analysis of the mating system and gene flow parameters especially when markers which will be employed having a high Na and a high Na/Ne-ratio.


  1. 1.

    Weber JC, Larwanou M, Abasse TA, Kalinganire A. Growth and survival of Prosopis africana provenances tested in Niger and related to rainfall gradients in the West African Sahel. For Ecol Manag. 2008;256:585–92.

    Article  Google Scholar 

  2. 2.

    Weber JC, Montes CS, Kalinganire A, Abasse T, Larwanou M. Genetic variation and clines in growth and survival of Prosopis africana from Burkina Faso and Niger: comparing results and conclusions from a nursery test and a long-term field test in Niger. Euphytica. 2015;205:809–21.

    Article  Google Scholar 

  3. 3.

    Mottura MC, Finkeldey R, Verga AR, Gailing O. Development and characterization of microsatellite markers for Prosopis chilensis and Prosopis flexuosa and cross-species amplification. Mol Ecol Notes. 2005;5:487–9.

    CAS  Article  Google Scholar 

  4. 4.

    Bessega CF, Pometti CL, Miller JT, Watts R, Saidman BO, Vilardi JC. New microsatellite loci for Prosopis alba and P. chilensis (Fabaceae). Appl Plant Sci. 2013;1:1200324.

    Article  Google Scholar 

  5. 5.

    Alves FM, Zucchi MI, Azevedo-Tozzi AMG, Sartori ÂLB, Souza AP. Characterization of microsatellite markers developed from Prosopis rubriflora and Prosopis ruscifolia (Leguminosae-Mimosoideae), legume species that are used as models for genetic diversity studies in Chaquenian areas under anthropization in South America. BMC Res Notes. 2014;7:375.

    Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Schmidt M, Kreft H, Thiombiano A, Zizka G. Herbarium collections and field data-based plant diversity maps for Burkina Faso. Divers Distrib. 2005;11:509–16.

    Article  Google Scholar 

  7. 7.

    Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth BC, Remm M, Rozen SG. Primer3—new capabilities and interfaces. Nucleic Acids Res. 2012;40:e115.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Schuelke M. An economic method for the fluorescent labeling of PCR fragments. Nat Biotechnol. 2000;18:233–4.

    CAS  Article  PubMed  Google Scholar 

  9. 9.

    Peakall R, Smouse PE. GenAlEx 6.5: genetic analysis in excel. Population genetic software for teaching and research–an update. Bioinformatics. 2012;28:2537–9.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P. Micro-checker: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes. 2004;4:535–8.

    Article  Google Scholar 

  11. 11.

    Raymond M, Rousset F. Genepop (version 1.2): population genetics software for exact tests and ecumenicism. J Hered. 1995;86:248–9.

    Article  Google Scholar 

  12. 12.

    Rousset F. Genepop’007: a complete re-implementation of the genepop software for Windows and Linux. Mol Ecol Resour. 2008;8:103–6.

    Article  PubMed  Google Scholar 

  13. 13.

    Piry S, Luikart G, Cornuet J-M. Bottleneck: a computer program for detecting recent reductions in the effective size using allele frequency data. J Hered. 1999;90:502–3.

    Article  Google Scholar 

  14. 14.

    Kim KS, Sappington TW. Microsatellite data analysis for population genetics. In: Kantartzi SK, editor. Microsatellites: methods protocols. Totowa: Humana Press; 2013. p. 271–95.

    Google Scholar 

  15. 15.

    Morgante M, Vendramin GG, Rossi P. Effects of stand density on outcrossing rate in two Norway spruce (Picea abies) populations. Can J Bot. 1991;69:2704–8.

    Article  Google Scholar 

  16. 16.

    Kalinowski ST. How many alleles per locus should be used to estimate genetic distances? Heredity. 2002;88:62–5.

    CAS  Article  PubMed  Google Scholar 

  17. 17.

    Cornuet JM, Luikart G. Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics. 1996;144:2001–14.

    CAS  PubMed  PubMed Central  Google Scholar 

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Authors’ contributions

GCZ and HK designed and implemented the experiment for the study under the supervision of TG. They also drafted the manuscript. TG proceeded in the interpretation of the results and the finalisation of the manuscript. MO participated in data collection and helped drafting the manuscript. All authors read and approved the final manuscript.


The authors thanks the Austrian Agency for International Cooperation in Education and Research (OeAD-GmbH) for providing the scholarship to GCZ and the Austrian Federal Ministry of Agriculture, Forestry, Environment and Water Management for funding the project “Fighting climate change in Burkina Faso through technical cooperation and knowledge transfer in the agro-forestry sector” (FCC-TECKTAFOR) within which this study was undertaken.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The SRRs sequences developed in our study are available at the National Center for Biotechnology Information (NCBI) GenBank ( with the Genbank accession numbers provided in Table 1.

Vouchers and dried leaves used for this study are stored at the herbarium at the Centre National des Semences Forestrières (CNSF), Route de Kaya, Ouagadougou, Burkina Faso. Information on collection site and material code in the herbarium are available in the Additional file 1: Appendix 1.

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Correspondence to Thomas Geburek.

Additional file

Additional file 1: Appendix 1.

Information on samples of Prosopis africana used in the study. Table giving information on the samples used in the study.

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Zerbo, G.C., Konrad, H., Ouedraogo, M. et al. Fourteen simple-sequence repeats newly developed for population genetic studies in Prosopis africana (FabaceaeMimosoideae). BMC Res Notes 10, 437 (2017).

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  • African mesquite
  • Genetic characterization
  • Microsatellites