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Genetic diversity and structure of Hancornia speciosa Gomes populations characterized by microsatellites markers

Abstract

Hancornia speciosaGomes, a native fruit tree, plays an important socio-economic role in Brazil's traditional communities. The objective was to estimate the genetic structure of 176 individuals from eight locations in the Cerrado, Caatinga and Atlantic Forest biomes, based on six microsatellite markers. The analyzes revealed the formation of five population groups: A- Pernambuco, Paraíba and Sergipe (Atlantic Forest), B- Maranhão (Cerrado); both, var. speciosa, C- Bahia (Caatinga / Cerrado transition zone) and Ceará (Caatinga), D- Goiás (Cerrado) and E- Minas Gerais (Cerrado,) being groups C, D and E possibly var. pubescens. Most of the genetic variation is within the groups (65.61%, Fst = 0.34, p <0.001). Although group A had the highest Ho (0.66), it had a negative fixation index (f = -0.02), while the other had positive values. Our results revealed high levels of genetic diversity and provide support the development of more efficient conservation strategies for H. speciosa.

Keywords:
Conservation genetics; native fruit; mangaba; Brazilian biomes

INTRODUCTION

The mangabeira (Hancornia speciosa Gomes, Apocynaceae) is a tropical species of great socioeconomic importance and great potential for commercial exploitation in Brazil. Its fruits are highly appreciated in natura and in the production of juices, ice creams, jams and jellies (Silva Júnior et al. 2017Silva JúniorJFMotaDMLédoASMunizAVCSSchmitzHRodriguesRFA2017 Mangaba (Hancornia speciosa Gomes). In Burle M and Faleiro FG (eds) Frutales nativos con importancia actual y potencial para del Cono Sur. Procisur, Montevideu, 27p). This species belongs to the Apocynaceae family, in which the monotypic genus is formed by six botanical varieties: H. speciosa var. speciosa Gomes that occurs predominantly in coastal and restinga plateaus, both belonging to the Atlantic Forest biome; H. speciosa var. maximiliani A. DC., H. speciosa var. cuyabensis Malme, H. speciosa var. lundii A. DC., H. speciosa var. gardneri (A. DC.) Muell. Arg. and H. speciosa var. pubescens (Nees and Martius) Muell. Arg., all widely distributed in the Cerrado of the Midwest of Brazil (Monachino 1945MonachinoJA1945 A revision of Hancornia (Apocynaceae). Lilloa 11:19-48) and also in North (Koch et al. 2015KochIRapiniASimõesAOKinoshitaLSSpinaAPCastelloACD2015 Apocynaceae. In Lista de espécies da flora do Brasil. Jardim Botânico do Rio de Janeiro. Available at <Available at http://floradobrasil.jbrj.gov.br/jabot/floradobrasil/FB26640 >. Accessed on December 15, 2019.
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, Silva Júnior et al. 2017Silva JúniorJFMotaDMLédoASMunizAVCSSchmitzHRodriguesRFA2017 Mangaba (Hancornia speciosa Gomes). In Burle M and Faleiro FG (eds) Frutales nativos con importancia actual y potencial para del Cono Sur. Procisur, Montevideu, 27p). However, currently, only two varieties are recognized: pubescens and speciosa, according to Koch et al. (2015KochIRapiniASimõesAOKinoshitaLSSpinaAPCastelloACD2015 Apocynaceae. In Lista de espécies da flora do Brasil. Jardim Botânico do Rio de Janeiro. Available at <Available at http://floradobrasil.jbrj.gov.br/jabot/floradobrasil/FB26640 >. Accessed on December 15, 2019.
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).

Regarding the reproductive and phenological aspects, mangaba is facultative autogamous, self-incompatible and has the pollination carried out by insects of the many families (Darrault and Schlindwein 2005DarraultROSchlindweinD2005 Limited fruit production in Hancornia speciosa (Apocynaceae) and pollination by nocturnal and diurnal insects. Biotropica 37:381-388). This species is in the domestication process (Silva et al. 2019SilvaAVCVitóriaMFAzevedoVRRSáAJNascimentoALSCardosoMNSoaresANRSilva JúniorJFLedoAS2019 Genetic diversity of the mangaba GeneBank using microsatellites. Genetics and Molecular Research 18: gmr18108.); however, significant parts of its genetic resources are being lost due to the reduction of native vegetation in the area of occurrence, mostly in the Cerrado, Caatinga and Atlantic Forest biomes (Costa et al. 2015CostaDFVieiraFAFajardoCGChagasKPT2015 Diversidade genética e seleção de iniciadores ISSR em uma população natural de mangaba (Hancornia speciosa Gomes) (Apocynaceae). Revista Brasileira de Fruticultura 37:970-976). Due to its great economic importance, wide natural distribution and mainly because it is under intense anthropic pressure, it is essential to know the genetic diversity and structure of the remaining populations mangaba in order to elaborate efficient conservation strategies both in situ and ex situ (Costa et al. 2015CostaDFVieiraFAFajardoCGChagasKPT2015 Diversidade genética e seleção de iniciadores ISSR em uma população natural de mangaba (Hancornia speciosa Gomes) (Apocynaceae). Revista Brasileira de Fruticultura 37:970-976).

Several molecular markers are available to estimate the level of diversity and genetic structure of plant populations. Among the available molecular markers, microsatellites (SSR-Simple Sequence Repeats) have been widely used. These are regions of DNA that have one to ten base pairs repeated in tandem, distributed throughout the genome of most eukaryotes; they are still highly polymorphic, multi-allelic, codominant and have high reproducibility (Vieira et al. 2016VieiraMLCSantiniLDinizALMunhozCF2016 Microsatellite markers: what they mean and why they are so useful. Genetics and Molecular Biology 39:312-328, Moura et al. 2017MouraRFDawsonDANogueiraDM2017 The use of microsatellite markers in neotropical studies of wild birds: A literature review. Anais da Academia Brasileira de Ciências 89:145-154).

It is worth mentioning that no study, as far as we know, has been carried out covering mangaba populations from different biomes. In this context, the objectives of this study were: 1) to analyze the polymorphism of microsatellite loci in H. speciosa; 2) to estimate genetic diversity and population structure of mangaba within and between the Atlantic Forest, Cerrado and Caatinga biomes; and 3) to propose appropriate strategies for the collection and conservation of H. speciosa.

MATERIAL AND METHODS

Sampling and DNA extraction

Young leaves from adult individuals were collected in eight locations distributed between the Midwest (Cerrado biome) and Northeast (Atlantic Forest and Caatinga biomes) regions of Brazil (red in Figure S1). A total of 176 individuals were sampled between the states of Paraíba (24), Pernambuco (24), Sergipe (24) and Maranhão (24), all possibly from var. speciosa; and Goiás (20), Minas Gerais (20), Bahia (20) and Ceará (20), all possibly from var. pubescens. The leaves packed in silica and stored in a -30 °C were used for DNA extraction according to the protocol of Doyle and Doyle (1990DoyleJJDoyle JL1990 A rapid total DNA preparation procedure for fresh plant tissue. Focus 12:13-15). The quantification and quality of DNA were analyzed after electrophoresis on 1% agarose gel.

PCR amplification and genotyping

Six specific SSR primers, developed by Rodrigues et al. (2015RodriguesAJLYamaguishiATChavesLJCoelhoASGLimaJSTellesMPC2015 Development of microsatellites markers for Hancornia speciosa Gomes (Apocynaceae). Genetics and Molecular Research 14:7274-7278), were tested (Table S1). PCR amplifications were performed in the final 50 μL volume containing: 1 µL of genomic DNA at 20 ng µL-1, 5 μL of reaction buffer, 1.5 mM MgCl2, 0.2 mM dNTP, 1.25 U Taq DNA polymerase, 0.5 µL forward and reverse primers (10 pmol each) labeled with 6-FAM. The amplification program used had an initial denaturation phase at 95 °C for 10 min, followed by 15 cycles under the following conditions: 30s for denaturation at 94 °C, annealing temperature of 55-60 °C for 1 min, an additional 20 cycles at 89 °C for 1 min and annealing at 55-60 °C for 1 min, and extension at 72 °C for 1 min. The final extension was performed at 72 °C for 1 hour. The PCR reactions were performed in a thermocycler (BioCycler), and the PCR products subjected to capillary electrophoresis in a 3500 genetic analyzer (Applied Biosystems Inc., Foster City, CA, USA), using GeneScanTM 600 Liz® (Applied Biosystems) as a standard size.

Analysis of diversity and population genetic structure

The allele number (Na), expected heterozygosity (H E ), observed heterozygosity (H O ) and Hardy-Weinberg balance deviation (HWE) were obtained using the R Pegas package (Paradis et al. 2017ParadisEGosselinTGoudetJJombartTSchliepK2017 Linking genomics and population genetics with R. Molecular Ecology Resources 17:54-66) and the R PopGenReport 3.0 package (Gruber and Adamack 2017GruberBAdamackA2017 PopGenReport: A simple framework to analyze population and landscape genetic data. Available at <Available at https://github.com/green-striped-gecko/PopGenReport >. Accessed on December 15, 2019.
https://github.com/green-striped-gecko/P...
). The Principal Component Discriminant Analysis (DAPC) was performed in the R adegenet 2.0 package (Jombart and Ahmed 2011JombartTAhmedI2011 Adegenet 1.3-1: new tools for the analysis of genome-wide SNP data. Bioinformatics 27:3070-3071) using the K-means and α-score method to retain the best number of PCAs, considering at least 70% probability of ancestry in one of the clusters (q ≥ 0.7). The population genetic structure was estimated using the R Geneland 2.0.9 package (Estoup et al. 2007EstoupAGuillotGSantosF2007 Geneland: simulation and MCMC inference in landscape genetics. R package version 2.0.5. Available at <Available at http:/cran.r-project.org/ >. Accessed on December 20, 2020.
http:/cran.r-project.org/...
). The spatial analysis of molecular variance was performed using the Spatial Analysis of Molecular Variation (SAMOVA) software (Dupanloup et al. 2002DupanloupISchneiderSExcoffierL2002 A simulated annealing approach to define the genetic structure of populations. Molecular Ecology 11:2571-2581). This approach uses simulations to determine groups of populations (k) that are geographically homogeneous and that maximize differences between groups. SAMOVA analyzes were performed using 1000 permutations for k = {2, …, 8} groups. In addition, STRUCTURE 2.3.4 (Hubisz et al. 2009HubiszMJFalushDStephensMPritchardJK2009 Inferring weak population structure with the assistance of sample group information. Molecular Ecology Resources 9:1322-1332) was used to estimate the data log-likelihood for predefined k values. The k populations were determined using the Geneland package (Estoup et al. 2007EstoupAGuillotGSantosF2007 Geneland: simulation and MCMC inference in landscape genetics. R package version 2.0.5. Available at <Available at http:/cran.r-project.org/ >. Accessed on December 20, 2020.
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). Gene flow (Nm) between populations was estimated using the values obtained from Fst, based on the formula Nm= 1-Fst/4Fst (Slatkin and Barton 1989SlatkinMBartonNH1989 A comparison of three indirect methods for estimating average levels of gene flow. Evolution 43:1349-1368). We estimated effective population size (Ne) using the molecular co-ancestry method of Nomura (2008NomuraT2008 Estimation of effective number of breeders from molecular coancestry of single cohort sample. Evolutionary Applications 1:462-474), as implemented in NeEstimator V2.1 (Do et al. 2014DoCWaplesRSPeelDMacbethGMTillettBJOvendenJR2014 NeEstimator V2: re-implementation of software for the estimation of contemporary effective population size (Ne) from genetic data. Molecular Ecology Resources 14:209-214). The frequency of null alleles was calculated for each locus using Chakraborty et al. (1994ChakrabortyRZhongYJinLBudowleB1994 Nondetectability of restriction fragments and independence of DNA fragment sizes within and between loci in RFLP typing of DNA. American Journal of Human Genetics 55:391-401), implemented in R PopGenReport 3.0 package (Gruber and Adamack 2017) and Dempster et al. (1977DempsterAPLairdNMRubinDB1977 Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, Series B (Methodological) 39:1-38) using GENEPOP (Raymond and Rousset 1995RaymondMRoussetF1995 GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. Journal of Heredity 86:248-249).

RESULTS AND DISCUSSION

The microsatellite regions studied in the populations, when submitted to DAPC analysis, enabled the identification of two large groups (Figure 1): I- individuals from the states of Paraíba, Pernambuco and Sergipe (Atlantic Forest, H. speciosa var. speciosa) and Maranhão (Cerrado, H. speciosa var. speciosa); II- individuals from the states of Goiás (Cerrado), Bahia (Cerrado / Caatinga transition zone), Minas Gerais (Cerrado) and Ceará (Caatinga); possibly belonging the var. pubescens. With the exception of individuals from Maranhão (Cerrado, possibly var. speciosa) who are in group I, all individuals from Cerrado and Caatinga (Goiás, Minas Gerais, Bahia and Ceará), seem to be closer genetically. While the individuals from the Atlantic Forest (Paraíba, Pernambuco and Sergipe) seem to be more divergent.

Figure 1
The discriminant analysis of principal components (DAPC) carried out based on six microsatellite loci for populations from eight states: Pernambuco, Paraíba and Sergipe (Atlantic Forest,), Maranhão (Cerrado); H. speciosa var. speciosa, Bahia (Cerrado/Caatinga Transition zone), Ceará (Caatinga,), Goiás (Cerrado) and Minas Gerais (Cerrado); probably belonging H. speciosa var. pubescens. The colours represent the groups determine by DAPC.

The analysis of population structure resulted in five genetic groups: A- individuals from the states of Pernambuco, Paraíba and Sergipe (Atlantic Forest), B- individuals from the state of Maranhão (Cerrado); both var. speciosa, C- individuals from the states of Bahia (transition zone between Caatinga and Cerrado) and Ceará (Caatinga), D- individuals from the states of Goiás (Cerrado) and E- individuals from the state of Minas Gerais (Cerrado); probably var. pubescens (Figure 2). In this analysis, except for Maranhão, the populations of the Cerrado and Caatinga are closer genetically, while the populations of the Atlantic Forest have more divergent genotypes, corroborating with the DAPC. These groups were used to estimate the parameters of genetic diversity.

Figure 2
Population genetic structure obtained by structure software. The groups A to E were determined by SAMOVA and Geneland analyses, being: A - individuals from the states of Pernambuco, Paraíba and Sergipe (Atlantic Forest, H. speciosa var. speciosa), B - individuals from the states of Maranhão (Cerrado), C - individuals from the states of Bahia (Transition zone Cerrado/Caatinga) and Ceará (Caatinga), D - individuals from the states of Goiás (Cerrado, H. speciosa var. pubescens) and E- individuals from the states of Minas Gerais (Cerrado); probably belonging the H. speciosa var. pubescens. The colours represent the groups determine by structure.

The genetic diversity of the population groups obtained revealed an average of 49 alleles (Table 1), of which group A had an average of 10.33 alleles. In comparison, the other groups had an average between 7 and 8.33 alleles. The average H O ranged from 0.49 (group B) to 0.66 (group A), and the HE ranged from 0.57 (group B) to 0.80 (group E). The value of f, whose average was 0.15, ranged from -0.02 (group A) to 0.29 (group E). Only population group A had a negative fixation index, while the other groups had positive values.

Table 1
Genetic diversity parameters for the five population groups determined by Structure, SAMOVA and Geneland analyses: A- individuals from the states of Pernambuco, Paraíba and Sergipe (Atlantic Forest); B- individuals from the states of Maranhão (Cerrado); C- individuals from the states of Bahia (Transition zone Cerrado/Caatinga) and Ceará (Caatinga); D- individuals from the states of Goiás (Cerrado); and E- individuals from the states of Minas Gerais (Cerrado)

There was an average of 69.7% of alleles shared between population groups, ranging from 61.3% (group A) to 77.1% (group C) (Table 1). Group A showed 24 private alleles, groups D and E showed 18 and 12, respectively, while groups B and C revealed 11 private alleles (Figures 3A and 3B). It was observed that groups A and B, formed by individuals from the Atlantic Forest and Cerrado from Maranhão, shared more alleles among themselves, while groups C, D and E, formed by individuals from Caatinga and Cerrado revealed more shared alleles.

Figure 3
Distribution of the microsatellite alleles by heatmap (A) and Venn diagram (B). The groups A to E were determined by SAMOVA and Geneland analyses, being: A- individuals from the states of Pernambuco, Paraíba and Sergipe (Atlantic Forest), B- individuals from the states of Maranhão (Cerrado,); belonging H. speciosa var. speciosa, C- individuals from the states of Bahia (Transition zone Cerrado/Caatinga) and Ceará (Caatinga), D- individuals from the states of Goiás (Cerrado) and E- individuals from the states of Minas Gerais (Cerrado,); probably belonging the H. speciosa var. pubescens. The colours represent the groups determined by the structure.

The spatial analysis of the molecular variation (SAMOVA) demonstrated that most of the genetic variation is distributed within the groups (65.61%), although significant differences are shown between the population groups obtained (31.5%, F ST = 0.34, p <0.001) (Table 2). When comparing pairs of population groups using the F ST statistic, the genetic structure was observed between them (Table S2). The greatest structuring was observed between groups B (Cerrado of Maranhão) in relation to D (Cerrado of Goiás) and E (Cerrado of Minas Gerais), both with F ST equal to 0.65, while the less divergent groups were C (zone of transition between Cerrado/Caatinga in Bahia and Caatinga in Ceará) and E (Cerrado of Minas Gerais), with F ST equal to 0.07.

Table 2
Spatial Analysis of Molecular Variance (SAMOVA) within and between mangaba population groups obtained by structuring based on six simple sequence repeats (ncSSR): Group A (Mata Atlântica - Paraíba, Pernambuco, Sergipe); Group B (Cerrado - Maranhão); Group C (Transição Cerrado/Caatinga - Bahia, Caatinga - Ceará); Group D (Cerrado - Goiás); Group E (Cerrado - Minas Gerais)

The Nm values also estimated from genetic differentiation (F ST ) between population groups show low gene flow between groups B in relation to D and E (Nm = 0.14), while groups C and E showed gene flow rate very high (Nm = 3.32) (Table S2). High values of gene flow were also observed among the populations of Bahia and Ceará (group C), Goiás (group D) and Minas Gerais (group E), with Nm = 1.68.

Dynamics of genetic variability in mangaba populations

The results obtained in this study made it possible to understand the diversity and genetic structure of eight populations of mangaba from three different Brazilian biomes (Caatinga, Cerrado and Atlantic Forest). These populations comprised individuals located in the occurrence area of two possibly botanical varieties (H. speciosa var. speciosa and H. speciosa var. pubescens) described initially by Monachino (1945MonachinoJA1945 A revision of Hancornia (Apocynaceae). Lilloa 11:19-48). The two major genetic groups (possibly from the two varieties mentioned above) were also observed in the DAPC analysis, whose populations in Pernambuco, Paraíba, Sergipe and Maranhão, where the only var. speciosa was reported, formed a group, while the populations of Goiás, Bahia, Minas Gerais and Ceará, possibly var. pubescens, formed another group (Figure 1). Although the genetic resources of the species are widely distributed in Brazil, there seems to be a correlation between botanical varieties and the Brazilian states where the populations are found. However, it is necessary to highlight that the genetic variation between populations does not necessarily correspond to the morphological variation between individuals; this is the basis for the classification of botanical varieties proposed by Monachino (1945MonachinoJA1945 A revision of Hancornia (Apocynaceae). Lilloa 11:19-48).

Although there is evidence of a correlation between the botanical varieties and the Brazilian states where the populations are found, this study did not observe a clear correlation between the genetic structure of the varieties and biomes (Figures 2 and 3), because despite being constituted by populations of var. pubescens; possibly, group C was formed by individuals from Caatinga (Ceará) and from the transition zone between Cerrado and Caatinga (Bahia). The populations of the Cerrado of Goiás and Minas Gerais formed two distinct groups, D and E, respectively. Also, groups A (Paraíba, Pernambuco and Sergipe) and B (Maranhão), despite being formed by populations from var. speciosa, come from the Atlantic Forest (sandbank and coastal plateaus) and the Cerrado, respectively. Still based on the genetic structure, except for the population of the Cerrado from Maranhão, which again forms a distinct group, the populations of the Caatinga and Cerrado are genetically closer. The populations of the Atlantic Forest, on the other hand, have more divergent genotypes.

These results demonstrate that the populations of H. speciosa var. speciosa from the Atlantic Forest are more genetically distant from the populations of the Cerrado, despite forming a single group, precisely because they are subject to different selection pressures. The populations of the Cerrado and Caatinga (most of the possibly var. pubescens) were genetically closer, although the collection areas had a greater geographical distance. The environmental conditions in the Cerrado and Caatinga, including in the transition zone between these two biomes, are more similar, which reduces the selection pressure between the populations of these two biomes. It is worth mentioning that the mangaba is a native species of different ecosystems, as it adapts to different types of soil and climate (Silva Júnior and Ledó 2006Silva JúniorJFLedóAS2006 A cultura da mangaba. Embrapa Tabuleiros Costeiros, Aracaju, 253p).

High levels of genetic diversity were observed in all population groups obtained in this study, with H O values greater than 0.49 and H E values greater than 0.57 (Table 1). With the exception of group A, formed by Paraíba, Pernambuco and Sergipe (f = -0.02), all other population groups showed HE values higher than the H O values, as expected for a population in Hardy-Weinberg equilibrium. The positive intrapopulation index obtained in most population groups indicates the lack of random mating between individuals, crossing between related genotypes and increased self-fertilization rate. The average values of H O , H E and f obtained in this study are within the standards reported for other populations of H. speciosa (Amorim et al. 2015AmorimJAEMataLRLédoASAzevedoVCRSilvaAVC2015 Diversity and genetic structure of mangaba remnants in states of northeastern Brazil. Genetics and Molecular Research 14:823-833) and are in accordance with the parameters expected for tree and allogamous species, such as mangaba (Santos et al. 2011SantosKLDucroquetJPHJNodariRO2011 Caracterização genética de populações naturais de goiabeira-serrana (Acca sellowiana) com marcadores microssatélites heterólogos. Biotemas 24:75-83, Alves et al. 2013AlvesMFBarrosoPACiampiAYHoffmannLVAzevedoVCRCavalcanteU2013 Diversity and genetic structure among subpopulations of Gossypium mustelinum (Malvaceae). Genetic Molecular Resources 12:597-609).

The SAMOVA analysis revealed that despite the existence of genetic variation between groups (31.5%), the greatest variability was found within populations (65.61%, F ST = 0.34) (Table 2). These results also agree with those obtained by Amorim et al. (2015AmorimJAEMataLRLédoASAzevedoVCRSilvaAVC2015 Diversity and genetic structure of mangaba remnants in states of northeastern Brazil. Genetics and Molecular Research 14:823-833) when they analyzed the remnants of six mangaba populations in the Northeastern states of Brazil (Ceará, Pernambuco and Sergipe), and also observed a higher percentage of variation within the populations (83.18%).

The F ST pair-by-pair matrix in the present study (Table S2) revealed moderate (F ST = 0.13) to high (F ST above 0.24) genetic differentiation between most population groups. Low differentiation was found only between the populations of Bahia, Ceará and Minas Gerais (F ST = 0.07), all from the Cerrado and Caatinga. Therefore, despite the low level, the difference was relevant. This difference may be important for future adap tation of populations with low levels of genetic variability among individuals (Diniz-Filho et al. 2012Diniz-FilhoJACollevattiRGChavesLJSoaresTNNaboutJCRangeRangeTFTFMeloDBLimaJSTellesMPC2012 Geographic shifts in climatically suitable areas and loss of genetic variability in Dipteryx alata (“Baru” Tree; Fabaceae). Genetic Molecular Resources 11:1618-1626).

Despite the low Nm values among the majority of the mangaba population groups (Table S2), the high level of genetic variation within populations suggests an intense intrapopulation gene flow, indicating that the genetic distance between mangaba populations in Brazil does not necessarily imply isolation by geographical distance or environmental conditions. This fact can be confirmed in the high values of Nm among the populations of the Cerrado and Caatinga distributed among the States of Bahia, Ceará, Goiás and Minas Gerais, probably attributed to the displacement of fruits between the two groups made by the inhabitants of these regions. Collevatti et al. (2018CollevattiRGRodriguesEEVitorinoLCLima-RibeiroMSChavesLJTellesMPC2018 Unravelling the genetic differentiation among varieties of the Neotropical savanna tree Hancornia speciosa Gomes. Annals of Botany 122:973-984), when trying to unveil the patterns of genetic differentiation of mangaba varieties described by Monachino, based on seven microsatellite loci, observed a high mixture between varieties and between populations. The genetic differentiation between varieties was less than between populations within the varieties, with greater inbreeding within the population. These results suggest that there was high historical connectivity between populations of this species, but due to the fragmentation of the biomes, this flow may be lost over time.

The population structure of central Brazil using the Geneland approach was different from that obtained by Collevatti et al. (2018CollevattiRGRodriguesEEVitorinoLCLima-RibeiroMSChavesLJTellesMPC2018 Unravelling the genetic differentiation among varieties of the Neotropical savanna tree Hancornia speciosa Gomes. Annals of Botany 122:973-984), who found five clusters, while this study was found two groups, probably because the sample in the Cerrado was smaller in the present study. Based on the result of the present study, structuring and differentiation F ST values among population groups, it is in agreement with the recent classification into only two botanic varieties (Koch et al. 2015KochIRapiniASimõesAOKinoshitaLSSpinaAPCastelloACD2015 Apocynaceae. In Lista de espécies da flora do Brasil. Jardim Botânico do Rio de Janeiro. Available at <Available at http://floradobrasil.jbrj.gov.br/jabot/floradobrasil/FB26640 >. Accessed on December 15, 2019.
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), in which the populations of northeast Brazil (groups A and B) correspond to H. speciosa var. speciosa and groups C, D and E correspond possibly the botanical variety H. speciosa var.pubescens.

Implications for conservation

The conservation of genetic resource should be carried out using the knowledge of the diversity and genetic structure of its populations. Genetic diversity can also be used to select more divergent individuals according to the research study objective (Nunes et al. 2021NunesVVSilva-MannRSouzaJLCalazansCC2021 Geno-phenotypic diversity in natural population of Hancornia speciosa Gomes: implications for conservation and improvement. Genetic Resources and Crop Evolution 68:2869-2882) and is also the basis for genetic improvement (Fajardo et al. 2018FajardoCGCostaDFChagasKPTVieiraFA2018 Genetic diversity in natural populations of mangabeira (Hancornia speciosa Gomes): implications for conservation of genetic resources. Ciência e Agrotecnologia 42:623-630). However, some species have particularities concerning the physiologic aspect, reproductive system, etc., which also is very important and demand specific strategies to conserve their genetic resources.

Mangaba is a perennial, cross pollination and self-incompatible species (Darrault and Schlindwein 2005DarraultROSchlindweinD2005 Limited fruit production in Hancornia speciosa (Apocynaceae) and pollination by nocturnal and diurnal insects. Biotropica 37:381-388); thus, their individuals are heterozygous and genetically distinct in natural populations. Therefore, the choice or sampling of individuals by seeds does not reproduce the same characters as the parent due to genetic recombination. Thus, if it is intended to maintain some phenotypic characteristics of the plant, it is necessary to collect vegetative parts for direct propagation or grafting. In addition, mangaba has recalcitrant seeds making it impossible to maintain a seed bank. In this sense, a reasonable strategy for ex situ conservation of the mangaba's genetic resources would be the installation of orchards, which requires a large area to maintain the adequate number of accesses; as the adult tree is a few meters tall, a minimum of 10 square meters is required for each tree. Considering these particularities and the wide distribution of populations in different biomes and ecological niches, in situ conservation is more appropriate for mangaba and should be prioritized, in parallel with the enrichment of the already installed germplasm banks (orchards), as well as the creation of new banks. According to Nass et al. (2012NassLLSigristMSRibeiroCSCReifschneiderFJB2012 Genetic resources: the basis for sustainable and competitive plant breeding. Crop Breeding Applied Biotechnology 12:75-86), this is a way to reconcile the conservation of diversity with sustainable development.

The enrichment of natural populations in situ, mainly the least vulnerable with the participation of the local population, and forest restoration in Conservation Units using propagules from different areas, especially those with high genetic diversity, are good strategies to conserve a greater volume of the resource genetics of mangaba.

In this sense, the results of this study indicate that the population of group E, from Minas Gerais, should be prioritized for conservation because it presents greater diversity (H E = 0.80) (Table 1) and the consequently greater probability of finding genotypes with characteristics of agronomic interest. To enrich the population of Minas Gerais (group E), Maranhão genotypes (group B) are more suitable. This is because they were more divergent (F ST = 0.65) and had a lower estimate of genetic flow (Nm = 0.14), which should provide more diversified genetic recombination in subsequent generations (Table S2). Based on the FST and Nm, group B genotypes are also indicated to enrich populations in groups C and D. For the same reason, to enrich the population in group B, individuals in groups C, D and E are option more suitable.

It is also noteworthy that for the in situ conservation of the mangaba genetic resources, special attention is needed to cultural aspects, considering the different customs of the local populations, mainly of communities that use mangaba populations as an extractivism of their fruits. In this context, the transmission of technical knowledge and training of local populations that do extractivism in mangaba populations is pointed out as good practices for the sustainable conservation of the genetic diversity of natural populations (Silva Júnior et al. 2017Silva JúniorJFMotaDMLédoASMunizAVCSSchmitzHRodriguesRFA2017 Mangaba (Hancornia speciosa Gomes). In Burle M and Faleiro FG (eds) Frutales nativos con importancia actual y potencial para del Cono Sur. Procisur, Montevideu, 27p). Strategies for in situ conservation of the mangaba genetic resource in Brazil need to be associated with the National Nature Conservation System, which is currently one of the most notable systems of conservation units in the world, according to Padua (2018PaduaJG2018 Conservation of crop genetic resources in Brazil in the context of the target 9 of the global strategy for plant conservation. Rodriguésia 69:1557-1565). As mangaba has wide occurrence in different biomes, the conservation of its genetic resources should be with efforts to conserve as many natural populations as possible with less vulnerability.

ACKNOWLEDGMENTS

This work was supported by the project CNPq (process number 484847/2013-9) that the authors gratefully acknowledge. Additional Tables S1 and S2 can be required to the author by e-mail (silvaedsonf@hotmail.com).

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Publication Dates

  • Publication in this collection
    01 July 2022
  • Date of issue
    2022

History

  • Received
    02 July 2021
  • Accepted
    23 Feb 2022
  • Published
    31 May 2022
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