Abstract
Premise of the study:
We developed microsatellite (simple sequence repeat [SSR]) markers in the Neotropical tree Handroanthus billbergii (Bignoniaceae), to be applied in assessment of genetic diversity in this species as a reference for inferring the impact of dry forest fragmentation in Ecuador.
Methods and Results:
Using next-generation sequencing, we detected a total of 26,893 putative SSRs reported here. Using an ABI 3500xl sequencer, we identified and characterized a set of polymorphic markers in 23 individuals belonging to three populations of H. billbergii.
Conclusions:
We report a set of 30 useful SSR markers for H. billbergii and a large list of potential microsatellites for developing new markers for this or related species.
Keywords: Bignoniaceae, Handroanthus billbergii, microsatellites, next-generation sequencing (NGS)
Handroanthus billbergii (Bureau & K. Schum.) S. O. Grose (syn. Tabebuia billbergii (Bureau & K. Schum.) Standl.) (Bignoniaceae), known as “guayacan negro” in Spanish, is a characteristic deciduous tree species of tropical dry forests in the Tumbesian region. This region, recognized as one of the most endangered biodiversity hotspots, is included among the most threatened ecosystems in Ecuador (Espinosa et al., 2011). According to the most recent taxonomic revision, H. billbergii belongs to the genus Handroanthus Mattos, a group of trees known for wood that is among the heaviest and hardest known in the world (Grose and Olmstead, 2007). Because this species produces very hard, durable, and high-quality wood, it has been overexploited by the local people and dominates the market, and therefore its diversity is declining rapidly (Détienne and Vernay, 2011).
To study the impact of forest fragmentation on H. billbergii populations in Ecuador, a survey of genetic diversity using highly polymorphic and codominant markers is proposed. Microsatellite markers (also known as simple sequence repeats [SSRs]) are available in the closely related species Tabebuia aurea (Silva Manso) Benth. & Hook. f. (Braga et al., 2007), but transferability of these markers to H. billbergii was almost null. Furthermore, a genetic survey with inter-simple sequence repeats (ISSRs) revealed low polymorphism rates, primarily at the intra-population level (Rueda, 2015). In this study, we report the development of SSR markers in H. billbergii by applying next-generation sequencing (NGS). We also report an estimation of the genetic information content of a set of 30 polymorphic markers surveyed in a representative group of individuals from three different populations.
METHODS AND RESULTS
As biological material for the DNA library, we used samples from two representative trees referenced in populations 1 and 2 (Appendix 1) during field prospecting expeditions in Ecuador. Genomic DNA was isolated from dried leaf samples using a procedure reported in Rueda (2015). The DNA library was prepared using the Nextera DNA Sample Kit (Ref. GAO9115; Illumina, San Diego, California, USA). DNA fragmentation started with 50 ng of purified DNA, followed by end-polishing and sequencing adapter ligation to prepare di-tagged DNA fragment libraries. The quality of the libraries was assessed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, California, USA), and the concentration was quantified using the KAPA Library Quantification Kit for Illumina Sequencing (KR0390; Kapa Biosystems, Woburn, Massachusetts, USA). The sequencing was performed on a MiSeq Sequencer (Illumina) using the 2 × 300-bp read mode. To reduce the raw data set and maximize the length of the sequences, an assembly of the 2,169,901 reads was performed with the ABYSS assembler (Simpson et al., 2009). To search for microsatellite markers among the assembled contigs (856,149), we used the MIcroSAtellite identification tool (MISA; Thiel et al., 2003). The search used specific criteria for the design of primers; these included motifs 2–6 bp in size, with a minimum repeat number of four repetitions, and with a maximum difference between two SSRs of 100 bp. The primers would thus amplify one or more repeats, effectively encompassing them as the same repeat motif if these were 100 bp or less from each other.
Among the 61,074 SSRs identified, primers were designed for 26,893 SSRs, of which 11,438 were dinucleotide, 8119 were trinucleotide, 3545 were tetranucleotide, 941 were pentanucleotide, 336 were hexanucleotide, and 2514 contained complex SSR motifs (Appendix S1 (14.4MB, xls) ).
For the SSR screening, we selected primer pairs flanking di- and trinucleotide SSR motifs with a minimum of 10 repetitions and amplifying fragments between 400 and 1000 bp in length. We screened a set of 55 primers: 25 primer pairs corresponding to dinucleotide SSR motifs and 30 primer pairs corresponding to trinucleotide SSR motifs. Amplification of the expected SSR fragments was first observed using agarose gel electrophoresis. Eight primer pairs that did not yield a single, well-amplified PCR product were excluded from the polymorphism survey. For screening the 47 remaining primer pairs, 23 individuals of three H. billbergii populations located in Ecuador (Appendix 1) were analyzed on an ABI 3500xl sequencer (Applied Biosystems, Waltham, Massachusetts, USA). The forward primers were end-labeled with an M13 extension (5′-CACGACGTTGTAAAACGAC-3′), and the SSR amplifications were multiplexed in a 10-μL volume reaction using FAM, NED, PET, and VIC chemistries. We used 20 ng of DNA template, 1× buffer (including MgCl2 with a final concentration of 1.5 mM), 0.08 μM of the M13-labeled primer, 0.1 μM of the reverse primer, 0.1 μM of M13 fluorescent primer, 0.5 mM of MgCl2, 200 μM dNTP, and 0.05 U/mL of Taq DNA polymerase. The following program was used in a 384 multiplex PCR arrangement: 94°C for 5 min, 35 cycles at 94°C for 45 s, 55°C for 60 s, 72°C for 75 s, including a touchdown of 10 cycles at 94°C for 45 s, 60°C decreasing 0.5°C per cycle, and a final elongation step of 72°C for 30 min. Electropherograms were analyzed with GeneMapper version 4.1 using GeneScan 600 LIZ as a size standard (Applied Biosystems). Allele calling was obtained by checking for each data point in the amplification peaks. The scoring edition of the SSR profiles allowed us to obtain a good genotype assignment and the identification of null alleles and possible scoring errors. Statistical parameters as number of alleles per locus, observed (Ho) and expected heterozygosities (He), polymorphism information content (PIC) of each locus, and the presence of linkage disequilibrium (LD) were calculated with PowerMarker version 3.25 (Liu and Muse, 2005).
Thirty microsatellite loci showing good genetic profiles and clear allelic size variability were characterized as polymorphic markers (Table 1). Among the 23 genotyped individuals, a total of 197 alleles were scored with a mean of 6.5 alleles per locus (Table 2). Primers mTb017, mTb019, and mTb020 showed the greatest number of alleles and therefore have higher PIC values (0.87–0.91). Based on polymorphism interpretation of PIC values (Botstein et al., 1980), only eight markers with PIC values lower than 0.5 showed moderate genetic diversity and the remaining 24 markers were very informative, with PIC values higher than 0.5. He and Ho mean values ranged from 0.51 to 0.641 and 0.482 to 0.664, respectively, in the three screened populations, and evidence of significant LD was found for 24 of the 435 possible SSR pairwise combinations after Bonferroni corrections. However, a further analysis with more individuals will be useful for confirming possible genetic associations between the reported SSR markers. Finally, primer transferability was also tested in the sympatric related species H. chrysanthus (Jacq.) S. O. Grose, showing good results of cross-amplification in all but one of the 30 markers (Table 2).
Table 1.
Locusa | Primer sequences (5′–3′) | Repeat motif | Allele size range (bp) | GenBank accession no. |
mTb002 | F: GGAACGTGCTAGTGTGTGTG | (GT)15 | 235–297 | KT715664 |
R: AGAGAGTGAGTTGCAACAAAAGT | ||||
mTb003 | F: GACCTTCTGCTTGTGTTCC | (TG)15 | 142–157 | KT715665 |
R: CTGTAAGTGTTAATTCTGCTGCT | ||||
mTb005 | F: GCAAGGGTGGGGTAGAG | (TC)16 | 186–218 | KT715666 |
R: GGGCAACGCATCTTGT | ||||
mTb006 | F: GGGCTTCACATTGGTTG | (TC)18 | 162–172 | KT715667 |
R: GGCATTTCCCAAGAACA | ||||
mTb011 | F: TAATTTCCGGGTGCAGA | (AG)17 | 167–193 | KT715668 |
R: CACTGGTCTCTCACATTTCAC | ||||
mTb013 | F: CTTCTCATTCATTTTGGTGG | (TC)15 | 354–368 | KT715669 |
R: GCTTCAACACTTTCACACATC | ||||
mTb014 | F: TCAGTGCAACTCCATTCC | (CT)15 | 247–259 | KT715670 |
R: AATGAACGGCATCATCTTT | ||||
mTb015 | F: AGCAACACAAGGAGCATTT | (TC)21 | 275–301 | KT715671 |
R: GTCAGACCCAATAACTTACCTTC | ||||
mTb016 | F: CCAGCCTCAGTTTCAGTTC | (AG)15 | 126–156 | KT715672 |
R: CCATTGGGATCTCTGCTT | ||||
mTb017 | F: TGAACATGGAACAGAGCAA | (AG)16 | 216–274 | KT715673 |
R: AGCCCAAGCGGATACA | ||||
mTb018 | F: GTGGTGCAGCGACTTCT | (CT)15 | 230–238 | KT715674 |
R: ACATCATCGTCATCCTCATC | ||||
mTb019 | F: CAAATAAAAGTCATAGCAGAGG | (AG)19 | 272–312 | KT715675 |
R: TGGCATTGAACACAACTC | ||||
mTb020 | F: CATTGACTCGTTGTCCC | (AG)15 | 305–341 | KT715676 |
R: GATCCTACAGTCTCACATAGAAG | ||||
mTb021 | F: ATTGTTGATGAAGGGCAAA | (TC)18 | 269–277 | KT715677 |
R: GGGCAAGGCTAAAGGAA | ||||
mTb022 | F: AGATCCACGAACCCAAAA | (AG)15 | 202–240 | KT715678 |
R: GAACGCCGAAGTGTGAG | ||||
mTb023 | F: AGCGCAATGTGATAAGAGCT | (AC)14 | 252–262 | KT715679 |
R: GCCCTTCATTCTTGGTGAGC | ||||
mTb024 | F: CCATTTGCTTGCCTTACCCA | (TA)12 | 199–209 | KT715680 |
R: AAGCAAACAACCACTCTGCA | ||||
mTb025 | F: CAAAGTGAGAGGAACTGAAAA | (AT)11 | 354–368 | KT715681 |
R: GGACACGAGCCAAGAAG | ||||
mTb027 | F: TTTTCACAACCAGTAACTTC | (ATT)15 | 165–201 | KT715682 |
R: GGTGTTTGGCATTACTTT | ||||
mTb028 | F: TGGCAAGGACATAATCTTCAAGA | (TAA)17 | 185–215 | KT715683 |
R: AAAACCCCAAATTCACTCCCT | ||||
mTb029 | F: AACGAAAGAGGCGAGGT | (TTA)13 | 273–282 | KT715684 |
R: TCCACCCATGTCCAATC | ||||
mTb031 | F: TGCAAGTCCTGGGAAGCATA | (CTT)12 | 194–215 | KT715685 |
R: GCACGAACAGAATGTCCAGG | ||||
mTb032 | F: CGTCGAATATCTAGTGTGGG | (AAT)13 | 189–213 | KT715686 |
R: ACAGATGAAGAGAAAACCAAAG | ||||
mTb033 | F: ACAAGGAAGTAAATTGCAACTCG | (ATT)15 | 171–205 | KT715687 |
R: ACCAGACTCCAAACACGACT | ||||
mTb035 | F: TCCTAATTCACCAACTTCC | (ATT)15 | 151–183 | KT715688 |
R: GTCTGTAAGCCACATAGACTG | ||||
mTb036 | F: CGACTTCCACCATCCAA | (TTA)14 | 149–170 | KT715689 |
R: CCTTTCTTTTGCAGCCC | ||||
mTb037 | F: TCTTGTTGGGAATAATTGGA | (AAT)15 | 235–265 | KT715690 |
R: GCATTAGGCAAAATTCGAG | ||||
mTb041 | F: CGACATTCTTGCTCCCAATCA | (TAA)16 | 221–260 | KT715691 |
R: AAACAGCGGCAAGAAAGGTT | ||||
mTb043 | F: GGTCTAGCACGTGACTAACC | (ATT)16 | 232–275 | KT715692 |
R: CCCAATACGAGGCATATGTGA | ||||
mTb052 | F: TGACAGTGAAAAGTTGCCACA | (AAT)18 | 147–171 | KT715693 |
R: TCATCGCAATATGTACACGATTG |
Annealing temperature for all loci was 55°C.
Table 2.
Population 1 (Mangahurco) (N = 9) | Population 2 (Puna) (N = 7) | Population 3 (Arenillas) (N = 7) | Total | |||||||||
Locus | A | He | Ho | A | He | Ho | A | He | Ho | A | PIC | CAb |
mTb002 | 6 | 0.76 | 0.80 | 5 | 0.75 | 1.00 | 6 | 0.78 | 1.00 | 8 | 0.80 | + |
mTb003 | 2 | 0.18 | 0.20 | 2 | 0.50 | 0.60 | 2 | 0.42 | 0.60 | 2 | 0.33 | + |
mTb005 | 3 | 0.62 | 0.20 | 3 | 0.61 | 0.66 | 3 | 0.65 | 0.25 | 8 | 0.84 | + |
mTb006 | 3 | 0.53 | 0.75 | 3 | 0.64 | 0.60 | 4 | 0.72 | 0.80 | 4 | 0.65 | + |
mTb011 | 3 | 0.59 | 0.50 | 3 | 0.66 | 0.80 | 4 | 0.48 | 0.40 | 5 | 0.58 | + |
mTb013 | 1 | 0 | 0 | 2 | 0.32 | 0 | 3 | 0.62 | 0 | 4 | 0.42 | + |
mTb014 | 2 | 0.48 | 0.40 | 3 | 0.66 | 0.40 | 3 | 0.62 | 1.00 | 4 | 0.66 | — |
mTb015 | 3 | 0.56 | 0.40 | 4 | 0.58 | 0.80 | 3 | 0.54 | 0.60 | 6 | 0.56 | + |
mTb016 | 3 | 0.53 | 0.75 | 5 | 0.68 | 0.40 | 8 | 0.84 | 1.00 | 9 | 0.79 | + |
mTb017 | 5 | 0.78 | 0.75 | 8 | 0.86 | 1.00 | 10 | 0.90 | 1.00 | 17 | 0.91 | + |
mTb018 | 3 | 0.46 | 0.40 | 2 | 0.42 | 0.60 | 2 | 0.48 | 0.80 | 3 | 0.42 | + |
mTb019 | 8 | 0.86 | 0.60 | 7 | 0.78 | 0.80 | 7 | 0.84 | 0.80 | 14 | 0.87 | + |
mTb020 | 7 | 0.82 | 0.60 | 5 | 0.75 | 1.00 | 7 | 0.82 | 0.80 | 12 | 0.89 | + |
mTb021 | 4 | 0.72 | 0.60 | 3 | 0.64 | 1.00 | 4 | 0.72 | 0.40 | 5 | 0.73 | + |
mTb022 | 6 | 0.80 | 0.80 | 6 | 0.80 | 0.80 | 5 | 0.72 | 1.00 | 9 | 0.77 | + |
mTb023 | 2 | 0.32 | 0.40 | 2 | 0.18 | 0.20 | 1 | 0 | 0 | 3 | 0.17 | + |
mTb024 | 2 | 0.42 | 0.60 | 4 | 0.71 | 1.00 | 4 | 0.64 | 1.00 | 5 | 0.58 | + |
mTb025 | 2 | 0.44 | 0 | 6 | 0.82 | 0.40 | 4 | 0.66 | 0.20 | 6 | 0.69 | + |
mTb027 | 2 | 0.37 | 0.50 | 6 | 0.80 | 1.00 | 5 | 0.77 | 1.00 | 8 | 0.84 | + |
mTb028 | 3 | 0.62 | 1.00 | 8 | 0.84 | 1.00 | 3 | 0.50 | 0.66 | 8 | 0.77 | + |
mTb029 | 2 | 0.50 | 1.00 | 3 | 0.58 | 1.00 | 2 | 0.27 | 0.33 | 3 | 0.48 | + |
mTb031 | 2 | 0.18 | 0.20 | 3 | 0.54 | 0.40 | 2 | 0.32 | 0 | 3 | 0.32 | + |
mTb032 | 1 | 0 | 0 | 4 | 0.65 | 0.50 | 2 | 0.18 | 0.20 | 5 | 0.34 | + |
mTb033 | 4 | 0.70 | 0.40 | 4 | 0.72 | 0.80 | 4 | 0.64 | 0.60 | 6 | 0.68 | + |
mTb035 | 3 | 0.56 | 0.80 | 3 | 0.58 | 0.40 | 4 | 0.66 | 0.60 | 5 | 0.58 | + |
mTb036 | 2 | 0.32 | 0 | 3 | 0.46 | 0.20 | 2 | 0.32 | 0 | 4 | 0.36 | + |
mTb037 | 6 | 0.78 | 0.60 | 6 | 0.81 | 0.75 | 3 | 0.62 | 0.80 | 8 | 0.82 | + |
mTb041 | 5 | 0.68 | 0.80 | 3 | 0.56 | 0.60 | 5 | 0.72 | 0.60 | 6 | 0.69 | + |
mTb043 | 4 | 0.70 | 0.40 | 4 | 0.58 | 0.40 | 5 | 0.74 | 0.80 | 9 | 0.74 | + |
mTb052 | 1 | 0 | 0 | 5 | 0.72 | 0.80 | 5 | 0.76 | 1.00 | 8 | 0.75 | + |
Mean | 3.3 | 0.510 | 0.482 | 4.1 | 0.641 | 0.664 | 4 | 0.599 | 0.608 | 6.5 | 0.638 |
Note: A = number of alleles; He = expected heterozygosity; Ho = observed heterozygosity; N = number of individuals sampled; PIC = polymorphism information content.
Locality and voucher information are provided in Appendix 1.
Cross-amplification in the sympatric species H. chrysanthus: + = successful amplification; — = no amplification.
CONCLUSIONS
The set of 30 SSR markers reported here will be used for surveying genetic diversity in a larger sample size of H. billbergii populations in the dry forests in Ecuador. In addition, the list of 26,893 SSRs published here (Appendix S1 (14.4MB, xls) ) is available for developing other markers in H. billbergii or related species.
Supplementary Material
Appendix 1.
Species | Collection locality | Geographic coordinates | N |
H. billbergii (Bureau & K. Schum.) S. O. Grose | Mangahurco, Loja, Ecuador (Population 1) | 4°8′6.108″S, 80°26′22.812″W | 9 |
H. billbergii | Puna, Guayas, Ecuador (Population 2) | 2°42′57.204″S, 80°5′27.204″W | 7 |
H. billbergii | Arenillas, El Oro, Ecuador (Population 3) | 3°29′2.112″S, 80°6′28.583″W | 7 |
H. chrysanthus (Jacq.) S. O. Grose | Mangahurco, Loja, Ecuador | 4°8′6.108″S, 80°26′22.812″W | 3 |
Note: N = number of analyzed individuals.
Representative trees (codes Tb24 and Tb37) used for developing the markers were sampled from population 1.
LITERATURE CITED
- Botstein D., White R. L., Skolnick M., Davis R. W. 1980. Construction of a genetic linkage map in man using restriction fragment length polymorphisms. American Journal of Human Genetics 32: 314–341. [PMC free article] [PubMed] [Google Scholar]
- Braga A. C., Reis A. M. M., Leoi L. T., Pereira R. W., Collevatti R. G. 2007. Development and characterization of microsatellite markers for the tropical tree species Tabebuia aurea (Bignoniaceae). Molecular Ecology Notes 7: 53–56. [Google Scholar]
- Detienne P., Vernay M. 2011. Les espèces du genre Tabebuia susceptibles de fournir le bois d’ipé. Bois et Forêts des Tropiques 307: 69–77. [Google Scholar]
- Espinosa C. I., Cabrera O., Luzuriaga A. L., Escudero A. 2011. What factors affect diversity and species composition of endangered Tumbesian dry forests in Southern Ecuador? Biotropica 43: 15–22. [Google Scholar]
- Grose S. O., Olmstead R. G. 2007. Taxonomic revisions in the polyphyletic genus Tabebuia s.l. (Bignoniaceae). Systematic Botany 32: 660–670. [Google Scholar]
- Liu K., Muse S. V. 2005. PowerMarker: Integrated analysis environment for genetic marker data. Bioinformatics 21: 2128–2129. [DOI] [PubMed] [Google Scholar]
- Rueda A.2015. Estudio de la diversidad genética de poblaciones de guayacán sabanero (Tabebuia billbergii) de bosques secos del Ecuador. Tesis Ing. Biotecnología, ESPE, Sangolquí, Ecuador.
- Simpson J. T., Wong K., Jackman S. D., Schein J. E., Jones S. J., Birol I. 2009. ABySS: A parallel assembler for short read sequence data. Genome Research 19: 1117–1123. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Thiel T., Michalek W., Varshney R. K., Graner A. 2003. Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.). Theoretical and Applied Genetics 10: 411–422. [DOI] [PubMed] [Google Scholar]
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