Acessibilidade / Reportar erro

Development and characterization of microsatellite markers for two subspecies of Handroanthus chrysanthus

Abstract

An understanding of the genetic diversity and structure of plant species is essential in order to comprehend the degree of biodiversity loss and to develop successful restoration programs. Handroanthus is an important genus that presents one of the most valuable timbers of South America. Handroanthus chrysanthus is an important species distributed in Central and South America. Microsatellite markers are not previously developed for this species. Ten microsatellites for Handroanthus chrysanthus developed using high-throughput sequencing are presented here. The usefulness of these microsatellite loci for the genetic analysis of subspecies H. chrysanthus subsp. chrysanthus (distributed in coastal dry forests) and subspecies H. chrysanthus subsp. meridionalis (distributed in premontane moist forests) is analyzed. At least eight polymorphic microsatellites are useful for each subspecies, seven of which can be used in both subspecies.

Key words
dry forest; Ecuador; Guayacán; Handroanthus chrysanthus; microsatellites; premontane forest; subspecies

Resumen

Comprender de la diversidad y estructura genética genética de las especies vegetales es esencial para entender el grado de pérdida de la biodiversidad y para desarrollar programas de restauración exitosos. Handroanthus es un género importante que presenta una de las maderas más valiosas de Sudamérica. Handroanthus chrysanthus es una especie importante, distribuida en América Central y del Sur. Sin embargo, no se han desarrollado previamente marcadores de microsatélites para esta especie. En este trabajo presentamos diez marcadores microsatellites desarrollados para Handroanthus chrysanthus mediante secuenciación de alto rendimiento. Se analiza la utilidad de estos loci microsatélites para el análisis genético de la subespecie H. chrysanthus subsp. chrysanthus (distribuida en bosques secos) y la subespecie H. chrysanthus subsp. meridionalis (distribuida en bosques húmedos premontanos). Por lo menos ocho microsatélites polimórficos son útiles para cada subespecie, siete de los cuales pueden utilizarse en ambas subespecies.

Palabras clave
bosque seco; Ecuador; Guayacán; Handroanthus chrysanthus; microsatélites; bosque premontano; subespecie

Knowledge about species biodiversity is increasing in Ecuador (ter Steege et al. 2019ter Steege H, Mota de Oliveira S, Pitman NCA, Sabatier D, Antonelli A, Guevara Andino JE, Aymard GA & Salomão RP (2019) Towards a dynamic list of Amazonian tree species. Scientific Reports 9: 1-5. <https://doi.org/10.1038/s41598-019-40101-y>.), but knowledge about genetic diversity at the population level is still very poor. Such information is important in order to fight habitat loss and deforestation, the main pressures that affect Southern Ecuador (Tapia-Armijos et al. 2015Tapia-Armijos MF, Homeier J, Espinosa CI, Leuschner C & De La Cruz M (2015) Deforestation and forest fragmentation in south Ecuador since the 1970s - losing a hotspot of biodiversity. PLoS ONE 10: 1-18. <https://doi.org/10.1371/journal.pone.0133701>) and cause species extinctions (Ehrlich & Pringle 2009Ehrlich PR & Pringle RM (2009) Where does biodiversity go from here? A grim business-as-usual forecast and a hopeful portfolio of partial solutions. In the Light of Evolution 2: 329-346.). Species extinction is the final step in the long process of population decline (Ceballos et al. 2017Ceballos G, Ehrlich PR & Dirzo R (2017) Biological annihilation via the ongoing sixth mass extinction signaled by vertebrate population losses and declines. Proceedings of the National Academy of Sciences of the United States of America 114: E6089-E6096. <https://doi.org/10.1073/pnas.1704949114>) and decreasing genetic diversity. An understanding of genetic population structure and diversity is also crucial for the establishment of successful restoration projects, and can mean the difference between achieving or not achieving project goals, including long term plant persistence and restoration of functioning ecosystems (Kettenring et al. 2014Kettenring KM, Mercer KL, Reinhardt-Adams C & Hines J (2014) Application of genetic diversity-ecosystem function research to ecological restoration. Journal of Applied Ecology 51: 339-348. <https://doi.org/10.1111/1365-2664.12202>).

Handroanthus Mattos (Bignoniaceae) is a genus that comprises 30 species distributed throughout Central and South America with one species in the Antilles (Grose & Olmstead 2007Grose SO & Olmstead G (2007) Taxonomic revisions in the polyphyletic genus Tabebuia s.l. (Bignoniaceae). Systematic Botany 32: 660-670.). Handroanthus chrysanthus (Jacq.) S. Grose is an emblematic species of the genus with a broad distribution in Central and South America. Although the species is not considered on the IUCN red list, the three subspecies described for H. chrysanthus are widely distributed in Ecuador (Jørgensen & León-Yánez 1999Jørgensen PM & León-Yánez S (1999) Catalogue of the vascular plants of Ecuador. Missouri Botanical Garden Press, St. Louis. 1169p.) in regions with a highest pressure caused by deforestation (Rahbek et al. 2019Rahbek C, Borregaard MK, Colwell RK, Dalsgaard B, Holt BG, Morueta-Holme N, Nogues-Bravo D, Whittaker RJ & Fjeldså J (2019) Humboldt’s enigma: what causes global patterns of mountain biodiversity? Science 365: 1108-1113. <https://doi.org/10.1126/science.aax0149>; Tapia-Armijos et al. 2015Tapia-Armijos MF, Homeier J, Espinosa CI, Leuschner C & De La Cruz M (2015) Deforestation and forest fragmentation in south Ecuador since the 1970s - losing a hotspot of biodiversity. PLoS ONE 10: 1-18. <https://doi.org/10.1371/journal.pone.0133701>; Manchego et al. 2017Manchego CE, Hildebrandt P, Cueva J, Espinosa CI, Stimm B & Günter S (2017) Climate change versus deforestation: implications for tree species distribution in the Dry Forests of Southern Ecuador. PLoS ONE 12: 15-19. <https://doi.org/10.1371/journal.pone.0190092>). Moreover, the species have one of the more valuable timber of South America, and its use caused overexploitation and subsequent threat (Schulze et al. 2008Schulze M, Grogan J, Uhl C, Lentini M & Vidal E (2008) Evaluating ipê (Tabebuia, Bignoniaceae) logging in Amazonia: sustainable management or catalyst for forest degradation? Biological Conservation 141: 2071-2085.).

Microsatellite loci primers to study population diversity in Handroanthus has been developed for H. billbergii (Bur & K. Schum) S. Gorse (Morillo et al. 2016Morillo E, Buitron J, Limongi R, Vignes H & Argout X (2016) Characterization of microsatellites identified by next-generation sequencing in the neotropical tree Handroanthus billbergii (Bignoniaceae). Applications in Plant Sciences 4: 1500135. <https://doi.org/10.3732/apps.1500135>). In that study, microsatellite loci primers were also tested on H. chrysanthus with a high rate of amplification; however, they did not report which subspecies was used for cross-amplification assays.

In this work we describe 10 microsatellite loci that have been developed and proved for two H. chrysanthus subspecies with different distribution patterns. Handroanthus chrysanthus subsp. chrysanthus (Jacq.) S. Grose is present in the coastal dry forest below 500 m and H. chrysanthus subsp. meridionalis (A. H. Gentry) S. Grose is distributed in the premontane moist forest at 1,200–2,000 m (Patzelt 1996Patzelt E (1996) Flora del Ecuador. Banco Central del Ecuador, Quito. 192p.). The timber of both subspecies is used in construction and subsp. chrysanthus is also used in agroforestry projects (De la Torre et al. 2008De la Torre L, Navarrete H, Muriel P, Macía MJ & Balslev H (2008) Enciclopedia de las plantas útiles del Ecuador. Herbario QCA de la Escuela de Ciencias Biológicas de la Pontificia Universidad Católica del Ecuador & Herbario AAU del Departamento de Ciencias Biológicas de la Universidad de Aarhus. Quito & Aarhus. 956p.).

The genomic DNA from two specimens, one from the dry forest and one from the premontane moist forests population was isolated from 20 mg of dry leaf material using the protocol from Curto et al. (2013)Curto MA, Tembrock LR, Puppo P, Nogueira M, Simmons MP & Meimberg H (2013) Evaluation of microsatellites of Catha edulis (Qat; Celastraceae) identified using pyrosequencing. Biochemical Systematics and Ecology 49: 1-9. <https://doi.org/10.1016/j.bse.2013.02.002>. Libraries prepared as described in Deck et al. (2016)Deck LMG, Habel JC, Curto M, Husemann M, Sturm S, Garitano-Zavala A & Meimberg H (2016) New microsatellite markers for two sympatric Tinamou species, the Ornate Tinamou (Nothoprocta ornata) and Darwin’s Nothura (Nothura darwinii). Avian Biology Research 9: 139-146. <https://doi.org/10.3184/175815515X14503747783157> were sequenced in a 300 bp paired-end sequencing run on an Illumina MiSeq system (Illumina, USA). This was done on the genomic service unit from the Ludwig Maximillian University of Munich. The quality of the resulting reads was evaluated with FASTQC (Andrews 2010Andrews S (2010) FastQC: a quality control tool for high throughput sequence data. Available at <http://www.bioinformatics.babraham.ac.uk/projects/fastqc/>.
http://www.bioinformatics.babraham.ac.uk...
) and low-quality regions and adapter sequences were trimmed out with cutadapt (Martin 2011Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet Journal 17: 10. <https://doi.org/10.14806/ej.17.1.200>). This was done with a 20 bp sliding window starting at the 3’ end excluding regions with an average quality below 20. The Illumina TrueSeq adapter sequences were used to find potential adapters in the reads using cutadpat default settings. Paired reads showing a significant 15 bp overlap were merged using PEAR (Zhang et al. 2014Zhang J, Kobert K, Flouri T & Stamatakis A (2014) PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30: 614-620. <https://doi.org/10.1093/bioinformatics/btt593>.). After quality control 3533155 and 524591 reads were kept, to each library respectively, and used for SSR search. 2672 and 1860 sequences contained microsatellite motifs and were used for primer design. The screened for di-, tri- and tetra-nucleotide microsatellite motifs using MSATCOMMANDER program (Faircloth 2008Faircloth BC (2008) MSATCOMMANDER: detection of microsatellite repeat arrays and automated, locus-specific primer design. Molecular Ecology Resources 8: 92-94. <https://doi.org/10.1111/j.1471-8286.2007.01884.x>). PRIMER3Web was used (Untergasser et al. 2012Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth BC, Remm M & Rozen SG (2012) Primer3 - new capabilities and interfaces. Nucleic Acids Research 40: 1-12. <https://doi.org/10.1093/nar/gks596>.) to search locus-specific primers considering PCR products within a size range between 100 and 300 bp, optimal melting temperature between 58–62 °C and GC content between 40 and 60%. One primer per locus was tagged with a M13 universal sequence on its 5’end (Tab. S1, available on supplementary material <https://doi.org/10.6084/m9.figshare.16569636.v1>) to use the dye-labeling method (Godinho et al. 2011Godinho R, Llaneza L, Blanco JC, Lopes S, Álvares F, García EJ, Palacios V, Cortés Y, Talegón J & Ferrand N (2011) Genetic evidence for multiple events of hybridization between wolves and domestic dogs in the Iberian peninsula. Molecular Ecology 20: 5154-5166. <https://doi.org/10.1111/j.1365-294X.2011.05345.x>). The OLIGO-ANALYZER 3.1 (Integrated DNA Technologies) was used to estimate the presence of self-dimers, heterodimers and hairpins among the primers.

According to Koskinen et al. (2004)Koskinen MT, Hirvonen H, Landry PA & Primmer CR (2004) The benefits of increasing the number of microsatellites utilized in genetic population studies: an empirical perspective. Hereditas 141: 61-67., Vartia et al. (2014)Vartia S, Collins PC, Cross TF, Fitzgerald RD, Gauthier DT, McGinnity P, Mirimin L & Carlsson J (2014) Multiplexing with Three-primer PCR for rapid and economical microsatellite validation. Hereditas 151: 43-54. and Arthofer et al. (2018)Arthofer W, Heussler C, Krapf P, Schlick-Steiner BC, & Steiner FM (2018) Identifying the minimum number of microsatellite loci needed to assess population genetic structure: a case study in fly culturing. Fly Times 12: 13-22. 8 to 20 loci are enough to detect population structure. A total of 28 primers were designed. These primers were initially tested in samples of the two subspecies (five samples per subspecies). These PCRs (Polymerase Chain Reactions) were performed in a final volume of 20 mL, containing 1X PCR buffer, 0.1 mM of each dNTP, 0.2 mM of each primer, 1.5 mM MgCl2, 0.2 unit of Go TAQ DNA polymerase (Promega) and 30–50 ng of DNA template. The products were amplified with the following conditions: one cycle at 94 °C for 3 min, 35 cycles at 94 °C for 30 sec, annealing temperature according to each primer pair for 45 sec and 72 °C for 1 min, and one cycle at 72 °C for 10 min. PCR amplification was verified by electrophoresis in a 2% agarose gel. Ten primers that amplified well and presented evidence of polymorphism were selected to standardize posterior multiplex PCRs.

Two multiplex PCRs were used for a total of 107 samples, 47 specimens from two populations: (Arenillas and Mangahurco) of H. chrysanthus subsp. chrysanthus using 8 loci and 60 specimens from two populations (Chitoque and Valladolid) of H. chrysanthus subsp. meridionalis using 9 loci (Tab. S2, available on supplementary material <https://doi.org/10.6084/m9.figshare.16569636.v1>). Vouchers of both subspecies are placed at the Herbarium of Universidad Técnica Particular de Loja (HUTPL14150 - HUTPL14255). The four populations are located in Southern Ecuador (Fig. 1).

Figure 1
Location of the populations of Handroanthus chrysanthus subsp. chrysanthus (Arenillas and Mangahurco) and Handroanthus chrysanthus subsp. meridionalis (Chitoque and Valladolid).

Both PCRs were performed in a final volume of 7 mL containing 1X QIAGEN multiplex master mix and 10–60 ng of genomic DNA. The first multiplex grouped primers: Hchrys2-F (0.006 mM), Hchrys2-R (0.06 mM), Hchrys9-F (0.007 mM), Hchrys9-R (0.07 mM), Hchrys12-F (0.006 mM), Hchrys12-R (0.06 mM), Hchrys16-F (0.01 mM), Hchrys16-R (0.1 mM), Hchrys25-F (0.009 mM), Hchrys25-R (0.09 mM), Hchrys26-F (0.014 mM), Hchrys26-R (0.14 mM), 6-FAM-M13 (0.09 mM), PET-M13 (0.13 mM), NED-M13 (0.07 mM) and VIC-M13 (0.06 mM). The second multiplex grouped primers: Hchrys4-F (0.009 mM), Hchrys4-R (0.09 mM), Hchrys6-F (0.0043 mM), Hchrys6-R (0.043 mM), Hchrys15-F (0.009 mM), Hchrys15-R (0.09 mM), Hchrys28-F (0.01 mM), Hchrys28-R (0.1 mM), 6-FAM-M13 (0.09 mM), PET-M13 (0.09 mM), NED-M13 (0.043 mM) and VIC-M13 (0.1 mM). Both PCRs were amplified using a touchdown PCR procedure: initial denaturation at 95 °C for 15 min, 13 cycles of 94 °C for 30 sec, 60 °C for 50 sec (with a decrease of 0.5 °C each cycle), 72 °C for 1 min, 22 cycles of 94 °C for 30 sec, 54 °C for 50 sec, 72 °C for 1 min and a final extension at 72 °C for 10 min.

For fragment separation 1 mL of the PCR product was mixed with 10 mL of Hi-Di Formamide and 0.15 mL of GeneScan LIZ 600 size standard and analyzed on a 3500 Genetic Analyzer (Applied biosystem, USA) according to manufacturer’s instructions and recorded in GeneMapper version 4.1 software (Applied biosystem).

The Number of alleles (A), observed heterozygosity (Ho) and expected heterozygosity (He) for each locus and population were analyzed with GenAlEx 6.50 (Peakall & Smouse 2012Peakall R & Smouse PE (2012) GenALlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research - an update. Bioinformatics 28: 2537-2539. <https://doi.org/10.1093/bioinformatics/bts460>). The exact Hardy-Weinberg global test of heterozygosity deficiency and linkage disequilibrium was calculated in GENEPOP on the Web (Raymond & Rousset 1995Raymond M & Rousset F (1995) Genepop 1.2: population genetics software for exact test and ecumenicism. Journal of Heredity 86: 248-249.; Rousset 2008Rousset F (2008) Genepop’007: a complete re-implementation of the Genepop software for Windows and Linux. Molecular Ecology Resources 8: 103-106. <https://doi.org/10.1111/j.1471-8286.2007.01931.x>). Parentage analysis was performed using Cervus program (Slate et al. 2000Slate J, Marshall TC & Pemberton JM (2000) A retrospective assessment of the accuracy of the paternity inference program CERVUS. Molecular Ecology 9: 801-808. <https://doi.org/http://dx.doi.org/10.1046/j.1365-294x.2000.00930.x>). Null allele frequencies were calculated using FreeNA (Chapuis & Estoup 2007Chapuis MP & Estoup A (2007) Microsatellite null alleles and estimation of population differentiation. Molecular Biology and Evolution 24: 621-631. <https://doi.org/10.1093/molbev/msl191>; Chapuis et al. 2008Chapuis MP, Lecoq M, Michalakis Y, Loiseau A, Sword GA, Piry S & Estoup A (2008) Do outbreaks affect genetic population structure? A worldwide survey in Locusta migratoria, a pest plagued by microsatellite null alleles. Molecular Ecology 17: 3640-3653. <https://doi.org/10.1111/j.1365-294X.2008.03869.x>).

A total of 28 microsatellites were tested from which 10 amplified well and presented evidence of polymorphism when evaluated by 2% agarose gel electrophoresis. Each multiplex genotyping PCR was repeated at least three times. If one locus failed to amplify in some samples we tried the amplification of this single locus to be sure that it was not a result of PCR problems. The amplification success and null allele frequencies were different for each subspecies (Tab. S1, available on supplementary material <https://doi.org/10.6084/m9.figshare.16569636.v1>). For H. chrysanthus subsp. chrysanthus two loci (Hchry16 and Hchrys26) did not amplify in more than 50% of the samples, and locus Hchrys16 also had a null allele frequency higher than 10%. For H. chrysanthus subsp. meridionalis a different locus (Hchrys4) failed to amplified in almost 100% of the samples. For this locus the null allele frequency was high (more than 30%). A total of 90 and 92 alleles were scored for subsp. chrysanthus and subsp. meridionalis, respectively (Tab. S1, available on supplementary material <https://doi.org/10.6084/m9.figshare.16569636.v1>).

We genotyped a total of 107 specimens from two subspecies (Tab. S2, available on supplementary material <https://doi.org/10.6084/m9.figshare.16569636.v1>). Loci that had a high percentage of failed amplification were not considered for each subspecies. Any of the 10 loci exhibit linkage disequilibrium. When parentage analysis was performed we did not find any parent offspring relationship. A good probability of identity (0.0001 or less) was achieved using 6 loci for subsp. chrysanthus and 5 for subsp. meridionalis so that even if the less polymorphic loci are not considered in future studies a good probability of identity can still be achieved. High overall observed heterozygosity (0.524 and 0.542) and expected heterozygosity (0.518 and 0.541) were found in the screened populations of subsp. chrysanthus. For subspecies meridionalis, similar values were found (Ho: 0.524 and 0.428, He: 0.556 and 0.564) except for the observed heterozygosity in the Valladolid population. The exact test of heterozygosity deficiency showed different levels of significance in the two subspecies. In subsp. meridionalis 6 of the 9 loci have significant values in the Valladolid population, but only one locus deviated from Hardy-Weinberg equilibrium in the Chitoque population. This could be more related to the specific characteristics of the populations rather than to issues with specific loci in this subspecies. Seven microsatellite loci are common to both subspecies.

We presented the characterization of ten microsatellites which can be used for the analysis of H. chrysanthus subsp. chrysanthus and meridionalis and potentially for H. chrysanthus subsp. pluvicola. The microsatellites can be used in future studies of population diversity and structure of this species. Our results confirm the necessity to verify the applicability of specific microsatellite loci when intraspecific genetic variation is present.

Acknowledgements

The authors thank I. Arnelas, for her contribution in taxonomic subspecies identification; Anabel Cueva, for her help with the map; and Chris Brinegar, for the critical review of the manuscript.

This work was supported by the Deutsche Forschungsgemeinschaft (DFG) project entitled “Improvement of forest management key strategies: a contribution to conservation and sustainable land use” (No 227674494) and by Universidad Técnica Particular de Loja (Project No. PY1902).

References

  • Andrews S (2010) FastQC: a quality control tool for high throughput sequence data. Available at <http://www.bioinformatics.babraham.ac.uk/projects/fastqc/>.
    » http://www.bioinformatics.babraham.ac.uk/projects/fastqc/
  • Arthofer W, Heussler C, Krapf P, Schlick-Steiner BC, & Steiner FM (2018) Identifying the minimum number of microsatellite loci needed to assess population genetic structure: a case study in fly culturing. Fly Times 12: 13-22.
  • Ceballos G, Ehrlich PR & Dirzo R (2017) Biological annihilation via the ongoing sixth mass extinction signaled by vertebrate population losses and declines. Proceedings of the National Academy of Sciences of the United States of America 114: E6089-E6096. <https://doi.org/10.1073/pnas.1704949114>
  • Chapuis MP & Estoup A (2007) Microsatellite null alleles and estimation of population differentiation. Molecular Biology and Evolution 24: 621-631. <https://doi.org/10.1093/molbev/msl191>
  • Chapuis MP, Lecoq M, Michalakis Y, Loiseau A, Sword GA, Piry S & Estoup A (2008) Do outbreaks affect genetic population structure? A worldwide survey in Locusta migratoria, a pest plagued by microsatellite null alleles. Molecular Ecology 17: 3640-3653. <https://doi.org/10.1111/j.1365-294X.2008.03869.x>
  • Curto MA, Tembrock LR, Puppo P, Nogueira M, Simmons MP & Meimberg H (2013) Evaluation of microsatellites of Catha edulis (Qat; Celastraceae) identified using pyrosequencing. Biochemical Systematics and Ecology 49: 1-9. <https://doi.org/10.1016/j.bse.2013.02.002>
  • De la Torre L, Navarrete H, Muriel P, Macía MJ & Balslev H (2008) Enciclopedia de las plantas útiles del Ecuador. Herbario QCA de la Escuela de Ciencias Biológicas de la Pontificia Universidad Católica del Ecuador & Herbario AAU del Departamento de Ciencias Biológicas de la Universidad de Aarhus. Quito & Aarhus. 956p.
  • Deck LMG, Habel JC, Curto M, Husemann M, Sturm S, Garitano-Zavala A & Meimberg H (2016) New microsatellite markers for two sympatric Tinamou species, the Ornate Tinamou (Nothoprocta ornata) and Darwin’s Nothura (Nothura darwinii). Avian Biology Research 9: 139-146. <https://doi.org/10.3184/175815515X14503747783157>
  • Ehrlich PR & Pringle RM (2009) Where does biodiversity go from here? A grim business-as-usual forecast and a hopeful portfolio of partial solutions. In the Light of Evolution 2: 329-346.
  • Faircloth BC (2008) MSATCOMMANDER: detection of microsatellite repeat arrays and automated, locus-specific primer design. Molecular Ecology Resources 8: 92-94. <https://doi.org/10.1111/j.1471-8286.2007.01884.x>
  • Godinho R, Llaneza L, Blanco JC, Lopes S, Álvares F, García EJ, Palacios V, Cortés Y, Talegón J & Ferrand N (2011) Genetic evidence for multiple events of hybridization between wolves and domestic dogs in the Iberian peninsula. Molecular Ecology 20: 5154-5166. <https://doi.org/10.1111/j.1365-294X.2011.05345.x>
  • Grose SO & Olmstead G (2007) Taxonomic revisions in the polyphyletic genus Tabebuia s.l (Bignoniaceae). Systematic Botany 32: 660-670.
  • Jørgensen PM & León-Yánez S (1999) Catalogue of the vascular plants of Ecuador. Missouri Botanical Garden Press, St. Louis. 1169p.
  • Kettenring KM, Mercer KL, Reinhardt-Adams C & Hines J (2014) Application of genetic diversity-ecosystem function research to ecological restoration. Journal of Applied Ecology 51: 339-348. <https://doi.org/10.1111/1365-2664.12202>
  • Koskinen MT, Hirvonen H, Landry PA & Primmer CR (2004) The benefits of increasing the number of microsatellites utilized in genetic population studies: an empirical perspective. Hereditas 141: 61-67.
  • Manchego CE, Hildebrandt P, Cueva J, Espinosa CI, Stimm B & Günter S (2017) Climate change versus deforestation: implications for tree species distribution in the Dry Forests of Southern Ecuador. PLoS ONE 12: 15-19. <https://doi.org/10.1371/journal.pone.0190092>
  • Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet Journal 17: 10. <https://doi.org/10.14806/ej.17.1.200>
  • Morillo E, Buitron J, Limongi R, Vignes H & Argout X (2016) Characterization of microsatellites identified by next-generation sequencing in the neotropical tree Handroanthus billbergii (Bignoniaceae). Applications in Plant Sciences 4: 1500135. <https://doi.org/10.3732/apps.1500135>
  • Patzelt E (1996) Flora del Ecuador. Banco Central del Ecuador, Quito. 192p.
  • Peakall R & Smouse PE (2012) GenALlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research - an update. Bioinformatics 28: 2537-2539. <https://doi.org/10.1093/bioinformatics/bts460>
  • Rahbek C, Borregaard MK, Colwell RK, Dalsgaard B, Holt BG, Morueta-Holme N, Nogues-Bravo D, Whittaker RJ & Fjeldså J (2019) Humboldt’s enigma: what causes global patterns of mountain biodiversity? Science 365: 1108-1113. <https://doi.org/10.1126/science.aax0149>
  • Raymond M & Rousset F (1995) Genepop 1.2: population genetics software for exact test and ecumenicism. Journal of Heredity 86: 248-249.
  • Rousset F (2008) Genepop’007: a complete re-implementation of the Genepop software for Windows and Linux. Molecular Ecology Resources 8: 103-106. <https://doi.org/10.1111/j.1471-8286.2007.01931.x>
  • Schulze M, Grogan J, Uhl C, Lentini M & Vidal E (2008) Evaluating ipê (Tabebuia, Bignoniaceae) logging in Amazonia: sustainable management or catalyst for forest degradation? Biological Conservation 141: 2071-2085.
  • Slate J, Marshall TC & Pemberton JM (2000) A retrospective assessment of the accuracy of the paternity inference program CERVUS. Molecular Ecology 9: 801-808. <https://doi.org/http://dx.doi.org/10.1046/j.1365-294x.2000.00930.x>
  • Tapia-Armijos MF, Homeier J, Espinosa CI, Leuschner C & De La Cruz M (2015) Deforestation and forest fragmentation in south Ecuador since the 1970s - losing a hotspot of biodiversity. PLoS ONE 10: 1-18. <https://doi.org/10.1371/journal.pone.0133701>
  • ter Steege H, Mota de Oliveira S, Pitman NCA, Sabatier D, Antonelli A, Guevara Andino JE, Aymard GA & Salomão RP (2019) Towards a dynamic list of Amazonian tree species. Scientific Reports 9: 1-5. <https://doi.org/10.1038/s41598-019-40101-y>.
  • Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth BC, Remm M & Rozen SG (2012) Primer3 - new capabilities and interfaces. Nucleic Acids Research 40: 1-12. <https://doi.org/10.1093/nar/gks596>.
  • Vartia S, Collins PC, Cross TF, Fitzgerald RD, Gauthier DT, McGinnity P, Mirimin L & Carlsson J (2014) Multiplexing with Three-primer PCR for rapid and economical microsatellite validation. Hereditas 151: 43-54.
  • Zhang J, Kobert K, Flouri T & Stamatakis A (2014) PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30: 614-620. <https://doi.org/10.1093/bioinformatics/btt593>.

Supplementary Material

See supplementary material at <https://doi.org/10.6084/m9.figshare.16569636.v1>

Edited by

Area Editor: Dra. Cassia Sakuragui

Publication Dates

  • Publication in this collection
    27 Sept 2021
  • Date of issue
    2021

History

  • Received
    15 May 2020
  • Accepted
    28 Sept 2020
Instituto de Pesquisas Jardim Botânico do Rio de Janeiro Rua Pacheco Leão, 915 - Jardim Botânico, 22460-030 Rio de Janeiro, RJ, Brasil, Tel.: (55 21)3204-2148, Fax: (55 21) 3204-2071 - Rio de Janeiro - RJ - Brazil
E-mail: rodriguesia@jbrj.gov.br