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Variability and genetic structure in fragments of Eugenia involucrata De Candolle established through microsatellite markers

Variabilidade e estruturação genética em fragmentos de Eugenia involucrata de Candolle utilizando marcadores microssatélites

ABSCTRACT:

Eugenia involucrata DC. is a forest species with high environmental and economic potential. The objective of this study was to quantify the genetic variability and analyzed the genetic structure of three natural fragments located in the central region of the Rio Grande do Sul state, Brazil. We used four microsatellite loci developed for the congener species Eugenia uniflora and using GenAlEx 6.5 software, parameters of genetic variability and its partition among and within fragments were estimated for each locus. We observed high levels of genetic variability (3.67 alleles per locus; HO = 0.815; HE = 0.625; FIS = −0.294), most of which (93%) were distributed within the fragments, suggesting that these individuals came from a single original population. Gene flow between fragments was high (2.35 to 4.56 migrants per generation), resulting in low genetic differentiation indexes (FST values ranging from 0.052 to 0.096). The fragments showed high genetic variability, distributed within the remnants themselves, and low genetic differentiation. Our results have repercussions for planning locally adapted germplasm collections for forest restoration programs, thereby avoiding the implantation of populations with an exogamous depression.

Key words:
forest species; gene flow; population genetics

RESUMO:

Eugenia involucrata DC. é uma espécie florestal com elevado potencial ambiental e econômico. O presente trabalho teve por objetivo quantificar a variabilidade e analisar a estruturação genética em três fragmentos naturais localizados na região central do estado do Rio Grande do Sul, Brasil. Com o emprego de quatro locos microssatélites desenvolvidos para a espécie congênere Eugenia uniflora e usando-se o software GenAlEx 6.5, foram estimados parâmetros de variabilidade genética, para cada loco, e sua partição entre e dentro dos fragmentos. Foram observados altos índices de variabilidade genética (3,67 alelos por loco; HO = 0,815; HE = 0,625; FIS = -0,294), com a maior proporção (93%) distribuída dentro dos fragmentos, sugerindo que os indivíduos estudados são provenientes de uma única população original. O fluxo gênico foi elevado entre os fragmentos, variando de 2,35 a 4,56 migrantes por geração, resultando em baixo índice de diferenciação genética (FST), entre 0,052 a 0,096. Os fragmentos estudados apresentam elevada variabilidade genética, a maior parte distribuída dentro dos próprios remanescentes, e baixa diferenciação genética. Os resultados observados têm repercussões no planejamento de coleta de germoplasma com adaptação local para programas de restauração florestal, assim evitando a implantação de populações com depressão exogâmica.

Palavras-chave:
espécie florestal; fluxo gênico; genética de populações

Eugenia involucrata (Myrtaceae) is a tree species native to Brazil and is classified as autogamous. It reaches reproductive age between 6 and 7 years of age, being pollinated by bees (Apis mellifera) and dispersed by different birds. Its flowers are melliferous and can be used in beekeeping. Its fruits are used in animal and human food and can be consumed fresh or used in the preparation of sweets, jellies and liquors (CARVALHO, 2009CARVALHO, P. E. R. Cerejeira - Eugenia involucrata. Colombo, PR: Comunicado Técnico 224, 2009.; LISBÔA et al., 2011LISBÔA, G. N. et al. Eugenia involucrata.In: CORADIN, L. et al. Espécies nativas da flora brasileira de valor econômico atual ou potencial: plantas para o futuro - Região Sul. Brasília: MMA, 2011. Cap.5, p.163-166.). The wood is compact, elastic, highly resistant, and highly durable. It can be used in civil construction to make tool handles, slats, and agricultural tools, as well as general use as firewood and charcoal of excellent quality (CARVALHO, 2009CARVALHO, P. E. R. Cerejeira - Eugenia involucrata. Colombo, PR: Comunicado Técnico 224, 2009.).

Its natural occurrence in Brazil occurs in the Atlantic Forest biome, more specifically in the ecosystems of Dense Ombrophilous, Semideciduous Seasonal, and Mixed Ombrophilous forests. It can be found in the states of Rio de Janeiro, São Paulo, Minas Gerais, Paraná, Santa Catarina and Rio Grande do Sul (LISBÔA et al., 2011LISBÔA, G. N. et al. Eugenia involucrata.In: CORADIN, L. et al. Espécies nativas da flora brasileira de valor econômico atual ou potencial: plantas para o futuro - Região Sul. Brasília: MMA, 2011. Cap.5, p.163-166.).

However, the perpetuation of this important forest resource is threatened because of the growing fragmentation that the biome suffered, primarily during the last 60 years, by anthropic activities, such as logging, construction of cities and highways, agricultural practices, and pollution. This conversion of a continuous area into small fragments leads to the spatial isolation of individuals and under these circumstances the performance of genetic processes, such as inbreeding and drift, can affect the viability of natural plant populations, leading to their extinction (CARVALHO, 2009CARVALHO, P. E. R. Cerejeira - Eugenia involucrata. Colombo, PR: Comunicado Técnico 224, 2009.; MATESANZ et al., 2017MATESANZ, S. et al. Habitat fragmentation differentially affects genetic variation, phenotypic plasticity and survival in populations of a gypsum endemic. Frontiers in Plant Science, v.8, p.843, 2017. Available from: <Available from: https://doi.org/10.3389/fpls.2017.00843 >. Accessed: Nov. 18, 2019. doi: 10.3389/fpls.2017.00843.
https://doi.org/10.3389/fpls.2017.00843...
).

Studies related to the quantification of genetic variability and analyses of the genetic structure of their natural populations using DNA markers can provide subsidies for the conservation of forest resources, providing the appropriate selection of management strategies (CARVALHO, 2009CARVALHO, P. E. R. Cerejeira - Eugenia involucrata. Colombo, PR: Comunicado Técnico 224, 2009.; CONSON et al., 2013CONSON, A. R. et al. Genetic structure of the Atlantic Rainforest tree species Luehea divaricata (Malvaceae). Genetica, v.141, n.4-6, 205-215, 2013. Available from: <Available from: https://doi.org/10.1007/s10709-013-9719-4 >. Accessed: Nov. 20, 2019. doi: 10.1007/s10709-013-9719-4.
https://doi.org/10.1007/s10709-013-9719-...
). In this study, microsatellite primers developed for the congener species Eugenia uniflora were used to quantify the variability and analyze the genetic structure in three natural fragments of E. involucrata located in the central region of the state of Rio Grande do Sul, Brazil.

Leaf samples were collected from 24 adult individuals from the three fragments, located in the municipalities of Quevedos (2921′09″S; 5404′18″W), Santa Maria (2941′03″S; 534825″W), and Silveira Martins (2938′33″S; 5335′08″W). According to reports by residents in nearby places (data not shown), individual trees from Quevedos were approximately 100 years old, whereas those from Santa Maria and Silveira Martins, were approximately 60 years old. Genomic DNA was obtained using the CTAB protocol (Doyle and Doyle, 1990DOYLE, J. J.; DOYLE, J. L. Isolation ofplant DNA from fresh tissue. Focus, v.12, n.13, p.39-40, 1990.). Working solutions at 50 ng μL-1 were amplified via polymerase chain reaction (PCR), and 11 microsatellite loci developed by SARZI et al. (2019SARZI, D. S. et al. Discovery and characterization of SSR markers in Eugenia uniflora L. (Myrtaceae) using low coverage genome sequencing. Anais da Academia Brasileira de Ciências, v.91, n.1, p.1-8, 2019. Available from: <Available from: http://dx.doi.org/10.1590/0001-3765201920180420 >. Accessed: Nov. 02, 2019. doi: 10.1590/0001-3765201920180420.
http://dx.doi.org/10.1590/0001-376520192...
) were initially evaluated (Pit 26, Pit 32, Pit 34, Pit 38, Pit 48, Pit 53, Pit 57, Pit 64, Pit 66, Pit 71, and Pit 72).

The amplification reactions were performed in a BIO-RAD C1000 Touch® thermocycler (BioRad Co., Hercules, CA, USA) in a final volume of 12.5 μL, which were prepared using Eppendorf epMotion® 5070 (Eppendorf AG, Hamburg, Germany), containing 50 ng of DNA, 0.25 μM of buffer, 0.5 μM of MgCl2, 1 U of Taq DNA polymerase, 0.05 μM of each dNTP, 0.125 μM of forward primer, 0.125 μM of reverse primer, and 0.125 μM of the M-13 primer (50-TGTAAAACGACGGCCAGT-30) labeled with AlexaFluor 680 fluorescence (Invitrogen®). PCR reactions consisted of an initial denaturation step at 94 °C for 3 min, followed by 30 cycles of denaturation at 94 °C for 45 s, annealing at 50 °C (Pit 26, 34, 48, and 57) or 52 °C (the other primers) for 30 s, an extension at 72 °C for 1 min, with a final extension at 72 °C for 10 min. Subsequently, the fragments were separated by electrophoresis on a 6% (w/v) polyacrylamide gel using a Li-Cor 4300S® automatic DNA sequencer (LiCor Inc., Lincoln, NB, USA) and were analyzed using SAGA-GT Software® (LiCor Inc.). Population genetic parameters were estimated using GenAlEx 6.5 software (PEAKALL & SMOUSE, 2012PEAKALL, R.; SMOUSE, P. E. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics, v.28, p.2537-2539, 2012. Available from: <Available from: https://doi.org/10.1111/j.1471-8286.2005.01155.x >. Accessed: Nov. 18, 2019. doi: 10.1111/j.1471-8286.2005.01155.x.
https://doi.org/10.1111/j.1471-8286.2005...
). For each locus, the total number of alleles (A), observed heterozygosity (H O ), expected heterozygosity (H E ), population fixation index (F IS ), genetic differentiation index (F ST ), and Hardy-Weinberg equilibrium (HWE) were tested. To quantify the distribution of genetic variability between and within fragments, an analysis of molecular variance (AMOVA) was performed. Gene flow was also estimated for each pair of fragments, considered to be the number of migrants by generation (Nm), based on the equation: Nm=141FST-1 where Nm is the number of migrants per generation and F ST is the index of genetic differentiation (WRIGHT, 1949WRIGHT, S. The genetical structure of populations. Annals of Eugenics, v.15, n.1, p.323-354, 1949. Available from: <Available from: https://onlinelibrary.wiley.com/doi/10.1111/j.1469-1809.1949.tb02451.x >. Accessed: Nov. 12, 2019. doi: 10.1111/j.1469-1809.1949.tb02451.x
https://onlinelibrary.wiley.com/doi/10.1...
). Of the tested loci, only four (Pit 26, Pit 57, Pit 64 and Pit 66) were amplified in all studied individuals, indicating a low transferability rate between the two species. Polymorphism was observed, with Pit 57 producing the highest number of alleles (5) in Quevedos, whereas Pit 26, Pit 57, and Pit 66 in Santa Maria, and Pit 64 and Pit 66 in Silveira Martins exhibited the lowest number (three alleles). Similarly, 3.5 alleles per locus were recorded in E. brasiliensis, whereas higher numbers were detected in other similar species: eight in E. uniflora, 7.9 in E. piriformis, and 8.3 in E. francavilleana (FERREIRA-RAMOS et al., 2014FERREIRA-RAMOS, R. et al. Genetic diversity assessment for Eugenia uniflora L., E. pyriformis Cambess., E. brasiliensis Lam. and E. francavilleana O. Berg neotropical tree species (Myrtaceae) with heterologous SSR markers. Genetic resources and crop evolution, v.61, n.1, p.267-272, 2014. Available from: <Available from: https://doi.org/10.1007/s10722-013-0028-7 >. Accessed: Nov. 10, 2019. doi: 10.1007/s10722-013-0028-7.
https://doi.org/10.1007/s10722-013-0028-...
). Quevedos, which in general presented the highest levels of genetic diversity (A = 4.250; H O = 0.850, H E = 0.690; Table 1), also indicated the presence of exclusive alleles (Table 1). Values close to diversity indices were observed in E. uniflora in the Pampa biome, also with microsatellites (SARZI et al., 2019SARZI, D. S. et al. Discovery and characterization of SSR markers in Eugenia uniflora L. (Myrtaceae) using low coverage genome sequencing. Anais da Academia Brasileira de Ciências, v.91, n.1, p.1-8, 2019. Available from: <Available from: http://dx.doi.org/10.1590/0001-3765201920180420 >. Accessed: Nov. 02, 2019. doi: 10.1590/0001-3765201920180420.
http://dx.doi.org/10.1590/0001-376520192...
).

Table 1
Estimation of genetic parameters by microsatellite locus and fragment of Eugenia involucrata. A is the average number of alleles per locus per fragment; H O is the heterozygosity observed, H E is the heterozygosity expected, F IS is the Fixation Index, n is the number of individuals analyzed, At is the total number of alleles, and A excl is the number of unique alleles.

The largest proportion of genetic variability was distributed within (93%) the studied remnants, suggesting that the individuals studied came from a single original population. This result also indicated that crosses in this population would be predominant, which is contrary to the classification of the species as autogamous (CARVALHO, 2009CARVALHO, P. E. R. Cerejeira - Eugenia involucrata. Colombo, PR: Comunicado Técnico 224, 2009.). Thus, the fragments studied in the present work were classified as mixed with a predominance of crossings (DESTRO & MONTALVÁN, 1999DESTRO, D.; MONTALVÁN, R. Melhoramento genético de plantas. Londrina: Ed. UEL, 1999.). Corroborating this result, Golle (2010GOLLE, D. P. Estabelecimento, multiplicação, calogênese, organogênese in vitro e análise da diversidade genética em acessos de Eugenia involucrata DC. 2010. 161f. Tese (Doutorado em Engenharia Florestal) - Curso de Pós-graduação em Engenharia Florestal,Universidade Federal de Santa Maria.) recorded greater variability within five populations of E. involucrata.

The analyzed loci revealed average observed heterozygosity (H O ) that did not differ significantly from the expected heterozygosity (H E ), with values of 0.815 and 0.625 (Table 1), respectively, indicating that they were in HWE. As a result, the fixation index did not differ from zero (F IS = −0.294; Table 1). This behavior, observed in three of the four loci being studied, was the opposite of that expected in autogamous population and even more so in populations in the process of fragmentation, suggesting that the time in which fragmentation occurred has not been long enough to promote genetic differentiation between fragments. Pit 64 was an exception, in that its heterozygosity estimates indicated a deficiency (H O = 0.475 versus H E = 0.564; Table 1), demonstrating that this locus was not in HWE, which suggested the existence of some evolutionary factor.

Gene flow estimates were high (2.35 for Quevedos and Santa Maria, 3.85 for Quevedos and Silveira Martins, and 4.56 for Silveira Martins and Santa Maria), and subsequently, resulted in low F ST values, ranging from 0.052 (Silveira Martins and Santa Maria) to 0.096 (Quevedos and Santa Maria). Among populations of the same species in the South, Southeast, and Northeast regions of Brazil, moderate genetic differentiation was obtained (F ST = 0.211) (SALGUEIRO et al., 2004SALGUEIRO, F. et al. Even population differentiation for maternal and biparental gene markers in Eugenia uniflora, a widely distributed species from the Brazilian coastal Atlantic rain forest. Diversity and Distributions, v.10, n.3, p.201-210, 2004. Available from: <Available from: https://doi.org/10.1111/j.1366-9516.2004.00078.x >. Accessed: Nov. 12, 2019. doi: 10.1111/j.1366-9516.2004.00078.x.
https://doi.org/10.1111/j.1366-9516.2004...
). Our research revealed high genetic variability in the studied fragments, a greater proportion of which was distributed within the fragments as a result of crosses between individuals. There was also high gene flow, and consequently, low genetic differentiation among the remnants, which guarantees the maintenance of high levels of genetic variability, which is important to the survival of populations facing changes in their environment. The observed results also have consequences in the planning of germplasm collection for local adaptation for forest restoration programs, thereby avoiding the implantation of populations with an exogamous depression.

ACKNOWLEDGSMENTS

This study was financed in part by the Conselho Nacional de Desenvolvimento Científico e Tecnológico - Brasil (CNPq) and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES - Finance Code 001).

REFERENCES

  • CARVALHO, P. E. R. Cerejeira - Eugenia involucrata Colombo, PR: Comunicado Técnico 224, 2009.
  • CONSON, A. R. et al. Genetic structure of the Atlantic Rainforest tree species Luehea divaricata (Malvaceae). Genetica, v.141, n.4-6, 205-215, 2013. Available from: <Available from: https://doi.org/10.1007/s10709-013-9719-4 >. Accessed: Nov. 20, 2019. doi: 10.1007/s10709-013-9719-4.
    » https://doi.org/10.1007/s10709-013-9719-4.» https://doi.org/10.1007/s10709-013-9719-4
  • DESTRO, D.; MONTALVÁN, R. Melhoramento genético de plantas. Londrina: Ed. UEL, 1999.
  • DOYLE, J. J.; DOYLE, J. L. Isolation ofplant DNA from fresh tissue. Focus, v.12, n.13, p.39-40, 1990.
  • FERREIRA-RAMOS, R. et al. Genetic diversity assessment for Eugenia uniflora L., E. pyriformis Cambess., E. brasiliensis Lam. and E. francavilleana O. Berg neotropical tree species (Myrtaceae) with heterologous SSR markers. Genetic resources and crop evolution, v.61, n.1, p.267-272, 2014. Available from: <Available from: https://doi.org/10.1007/s10722-013-0028-7 >. Accessed: Nov. 10, 2019. doi: 10.1007/s10722-013-0028-7.
    » https://doi.org/10.1007/s10722-013-0028-7.» https://doi.org/10.1007/s10722-013-0028-7
  • GOLLE, D. P. Estabelecimento, multiplicação, calogênese, organogênese in vitro e análise da diversidade genética em acessos de Eugenia involucrata DC. 2010. 161f. Tese (Doutorado em Engenharia Florestal) - Curso de Pós-graduação em Engenharia Florestal,Universidade Federal de Santa Maria.
  • LISBÔA, G. N. et al. Eugenia involucrataIn: CORADIN, L. et al. Espécies nativas da flora brasileira de valor econômico atual ou potencial: plantas para o futuro - Região Sul. Brasília: MMA, 2011. Cap.5, p.163-166.
  • MATESANZ, S. et al. Habitat fragmentation differentially affects genetic variation, phenotypic plasticity and survival in populations of a gypsum endemic. Frontiers in Plant Science, v.8, p.843, 2017. Available from: <Available from: https://doi.org/10.3389/fpls.2017.00843 >. Accessed: Nov. 18, 2019. doi: 10.3389/fpls.2017.00843.
    » https://doi.org/10.3389/fpls.2017.00843.» https://doi.org/10.3389/fpls.2017.00843
  • PEAKALL, R.; SMOUSE, P. E. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics, v.28, p.2537-2539, 2012. Available from: <Available from: https://doi.org/10.1111/j.1471-8286.2005.01155.x >. Accessed: Nov. 18, 2019. doi: 10.1111/j.1471-8286.2005.01155.x.
    » https://doi.org/10.1111/j.1471-8286.2005.01155.x.» https://doi.org/10.1111/j.1471-8286.2005.01155.x
  • SALGUEIRO, F. et al. Even population differentiation for maternal and biparental gene markers in Eugenia uniflora, a widely distributed species from the Brazilian coastal Atlantic rain forest. Diversity and Distributions, v.10, n.3, p.201-210, 2004. Available from: <Available from: https://doi.org/10.1111/j.1366-9516.2004.00078.x >. Accessed: Nov. 12, 2019. doi: 10.1111/j.1366-9516.2004.00078.x.
    » https://doi.org/10.1111/j.1366-9516.2004.00078.x.» https://doi.org/10.1111/j.1366-9516.2004.00078.x
  • SARZI, D. S. et al. Discovery and characterization of SSR markers in Eugenia uniflora L. (Myrtaceae) using low coverage genome sequencing. Anais da Academia Brasileira de Ciências, v.91, n.1, p.1-8, 2019. Available from: <Available from: http://dx.doi.org/10.1590/0001-3765201920180420 >. Accessed: Nov. 02, 2019. doi: 10.1590/0001-3765201920180420.
    » https://doi.org/10.1590/0001-3765201920180420.» http://dx.doi.org/10.1590/0001-3765201920180420
  • WRIGHT, S. The genetical structure of populations. Annals of Eugenics, v.15, n.1, p.323-354, 1949. Available from: <Available from: https://onlinelibrary.wiley.com/doi/10.1111/j.1469-1809.1949.tb02451.x >. Accessed: Nov. 12, 2019. doi: 10.1111/j.1469-1809.1949.tb02451.x
    » https://doi.org/10.1111/j.1469-1809.1949.tb02451.x» https://onlinelibrary.wiley.com/doi/10.1111/j.1469-1809.1949.tb02451.x
  • CR-2020-0008.R1

Publication Dates

  • Publication in this collection
    08 Mar 2021
  • Date of issue
    2021

History

  • Received
    06 Jan 2020
  • Accepted
    19 Oct 2020
  • Reviewed
    02 Dec 2020
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