Genetic structure and diversity among individuals of Copaifera langsdorffii Desf. from Mato Grosso, Brazilian Amazon, using ISSR markers

The Amazon is the largest tropical forest in the world and is home to around 20% of all the biodiversity on the planet, among the species present in the Amazon is Copaifera langsdorffii , exploited mainly for the extraction of oil-resin and wood, often in ways incorrect, which can cause the loss of genetic variability. The aim of this study was to evaluate the genetic structure and diversity among individuals of C. langsdorffii located in Mato Grosso, Brazil, using ISSR markers. We sampled leaves from 27 adult individuals of C. langsdorffii , whose total genomic DNA was extracted. A total of 12 ISSR primers were used for the molecular characterization of the individuals. A grouping analysis was performed using the unweighted pair group method, Bayesian analysis and characterized by the genetic diversity. The genetic diversity among and within the groups was demonstrated by the AMOVA. As a result, 106 fragments were amplified and 98.11% were polymorphic. The polymorphic information content of each primer ranged from 0.45 to 0.81. The dendrogram showed the formation of 4 distinct groups. The greatest genetic variability is found within the groups and not between them. The percentage of polymorphism, genetic dissimilarity values and genetic diversity indexes indicate that there is high genetic variability among Copaifera langsdorffii individuals, suggesting that ISSR primers were efficient in detecting polymorphism in this species and that the individuals have potential for compose programs aimed at the preservation of the species and the ability to integrate germplasm banks. 0.81. ,


Introduction
With approximately 6.7 million km2, the Amazon Rainforest is considered the largest tropical forest in the world, and 60% of its extension is in Brazilian territory (Ferreira et al., 2010). As such, it is home to about 20% of all biodiversity on the planet . Among the species present in the Amazon, the Copaifera langsdorffii Desf. (Copaíba) stands out and is widely distributed in Brazil (Lorenzi, 1992;Reis et al., 2016). It is exploited mainly for the extraction of its resinous oil, which is used in popular medicine as an anti-inflammatory and bactericide (Lisboa et al., 2018), and in industries: pharmacological, drug development; cosmetics: for the production of fixatives for fragrances, cosmetics and soaps; and in varnishes and solvents, for their production (Veiga & Pinto, 2002). Copaiba oil also stands out as a raw material for the manufacture of soaps and soaps by small Family businessses, fostering regional trade (Sousa et al., 2016). And its wood, in the production of plywood (Lisboa et al., 2018).
Inadequate management of C. langsdorffii, as well as forest fragmentation, influence the genetic composition of populations. This also causes a decrease in the number of individuals, which in the long term can lead to an increase in inbreeding, a reduction in genetic variability and consequently the loss of the adaptive capacity of the species .
Intraspecific genetic variability is fundamental for the persistence of species in nature, therefore knowing how much genetic variation exists and how it is distributed geographically in each species is necessary in order to characterize its conservation status (Santos et al., 2010). Thus, many studies have used genetic markers as a tool to map the variability and genetic distribution of species.
According to Turchetto-Zolet et al. (2017), a genetic marker is any visible character or phenotype that is somehow analyzable, by which alleles in individual loci segregate in a Mendelian manner. DNA molecular markers are effective tools for revealing the presence of genetic polymorphism, and are widely used in genetic studies of plant populations (Borém & Caixeta, 2016;Cordeiro et al., 2020). Among them, those based on polymerase chain reaction (PCR) stand out since they can be applied to non-model species and can be classified according to the type of allelic inheritance in dominant and codominant markers (Turchetto-Zolet et al., 2017), and the dominant markers do not distinguish between dominant homozygotes and heterozygotes (Zietjiewicz et al., 1994;Costa et al., 2015). Research, Society andDevelopment, v. 10, n. 16, e187101623025, 2021 (CC BY 4.0) | ISSN 2525-3409 | DOI: http://dx.doi.org/10.33448/rsd-v10i16.23025 3 Among the dominant markers based on PCR are ISSR (Inter Simple Sequence Repeat), widely used in studies related to genetic characterization, due to low cost and high reproducibility (Ng & Tan, 2015). Polymorphisms between individuals are identified in electrophoretic analyses by the presence or absence of amplicons.
Thus, the objective herein was to evaluate the diversity and genetic structure among individuals of Copaifera langsdorffii Desf. from Mato Grosso in the Brazilian Amazon, using ISSR markers.

Sampling
We sampled the leaves of 27 adult individuals of C. langsdorffii found in the location known as Pista do Cabeça (S 10° 23' 22", W 56° 24' 27"), in the municipality of Alta Floresta, located in the north of the state of Mato Grosso (Figure 1), whose climate according to Alvares, Stape, Sentelhas, Gonçalves, and Sparovek (2013) is classified as AM type (tropical humid or subhumid). The average temperature is 24°C and precipitation is from 2800 to 3100 mm. The collection points were geo-referenced with the aid of a GPS (Global System Position). The individuals were collected at points where there was already evidence of the existence of the species in question, with of a the help local resident. They are later grouped into four sample subunits according to their geographic proximity. Samples subunits: I (AF1, AF6, AF7 and AF8); II (AF2, AF3, AF4, AF5 and AF9); III (AF10, AF11, AF12, AF13, AF14, AF15, AF16, AF17, AF18 and AF19) and IV (AF20, AF21, AF22, AF23, AF24, AF25, AF26 and AF27) [ Figure 1D]. Sample subunit IV is further away from the others, being 36 km from III, 41 km from I and 44 km from II. The closest subunits are I and III (7 km). Source: Authors (2020). Research, Society and Development, v. 10, n. 16, e187101623025, 2021 (CC BY 4.

DNA extraction and quantification
The laboratory procedures were performed at the Laboratory of Genetics and Molecular Biology of the University of Mato Grosso Carlos Alberto Reyes Maldonado (UNEMAT) in Alta Floresta/Mato Grosso. Total genomic DNA was extracted from approximately 300 mg of leaves from each sample, following the CTAB (cetyltrimethylammonium bromide) protocol described by Doyle and Doyle (1987). The evaluation of the quality of the extracted DNA, as well as the quantification, were performed using electrophoresis in 0.8% agarose gel (m/V) stained with ethidium bromide (0.6 µg/µL-1) for 20 minutes. After quantification, the extracted DNA samples were diluted in autoclaved distilled water and standardized to a concentration of approximately 10 ng µL-1.

Statistical analysis
The matrix of presence (1) and absence (0) of the amplicons was obtained from visual evaluation of the most defined fragments for each primer in the 27 subjects studied. Based on the matrix, the genetic similarities between the individuals of C.
langsdorffii were determined using the Jaccard coefficient, and a grouping analysis was performed using the unweighted pair group method with arithmetic mean (UPGMA); the cutoff point was defined according to the methodology proposed by Mojena (1977). The bootstrap reliability index was also estimated based on 1000 repetitions, as well as the cophenetic correlation coefficient (r). The analyses were performed using the GENES program (Cruz, 2016). The Structure program (Pritchard et al., 2000), based on Bayesian analysis, was used to infer the structure of the population, which indicated distinct genetic groups (K) and assigned individuals to these groups. In all, 20 runs were performed for each K value (K = 4), 200,000 initial interactions (burn-ins) and 500,000 Markov chain Monte Carlo (MCMC) simulations. The criteria described by Pritchard and Wen (2004) and Evanno et al., (2005) were used to define the most likely K in relation to those proposed. To characterize the genetic variability between the genetic groups constituted by the Bayesian analysis, the genetic diversity of Nei (He) (Nei, 1978), the Shannon diversity index (I) (Lewontin, 1972) and the percentage of polymorphic loci (%P) were calculated from the analysis of the binary matrix of presence and absence, using the program POPGENE 1.32 (Yeh et al., 2000). Genetic diversity among and within groups was demonstrated using AMOVA (analysis of molecular variance), according to Excoffier et al., (1992) and with the aid of the Arlequin 3.01 program (Excoffier et al., 2007).

Results
The extracted DNA showed high quality. The 12 primers that were used amplified 106 fragments, and were 98.11% polymorphic. The number of amplified fragments ranged from 6 (UBC-828 and UBC-873) to 16 (UBC-810), with an average of 8.83 fragments per primer (Table 1) The values of genetic dissimilarity observed among individuals ranged from 0.24 to 0.69. The least genetically dissimilar individuals were AF20 and AF21, and AF24 and AF25, both pairs with 0.24, and all belonged to sample subunit IV.
The most dissimilar were AF5 and AF27 with 0.69, and belonged to sample subunits II and IV respectively, as more distant from each other geographically, it may be a question of belonging to parents from other regions. Among the combinations, 41% are within the range 0.41-0.50 ( Figure 2). The mean dissimilarity found was 0.49.

Figure 2. Distribution of genetic dissimilarity between pairs of individuals of Copaifera langsdorffii.
Source: Authors.  6 Among the clustering methods tested, the UPGMA presented higher cophenetic correlation coefficient (CCC) (0.728), lower stress (10.39) and distortion (1.08). The genetic dissimilarity dendrogram based on the ISSR was generated by the UPGMA method, and based on the dissimilarity matrix, forming 4 groups (GI, GII, GIII, GIV) (Figure 3). Bayesian analysis demonstrated the existence of 2 distinct groups (k = 2) named A and B (Figure 4).  The analysis of molecular variance (AMOVA), also based on the two groups obtained by Bayesian analysis, indicated that the greatest genetic variability is within each group (85.84% of total variance) and not between them. The group genetic differentiation value (FST) was 0.14162, with 1023 random permutations, indicating that, between the groups, the variation is approximately 14% (p<0.000).

Discussion
The primers used herein were effective in the detection of genetic polymorphism of C. langsdorffii and there is genetic diversity among the individuals sampled. The high percentage of polymorphism (99.80%) found in this study is similar to that found by Dúcar, Rewers, Jedrzejczyk, Mártonfi, and Sliwinska (2018), who evaluated the genetic diversity of eight species of Lotus sp. (Fabaceae), as well as that observed by Bagheri, Abbasi, Mahmoodi, Roofigar, and Blattner (2020) (97.60%), who studied the genetic variability of Astragalus subrecognitus (Fabaceae), which demonstrates the effectiveness of ISSR markers in the detection of polymorphism in species of the Fabaceae family.
The polymorphic information content (PIC) demonstrated that 11 of the 12 primers used in this study can be considered as very informative for C. langsdorffii, since they presented PIC values above 0.5. Only the primer UBC-816 showed a value Research, Society andDevelopment, v. 10, n. 16, e187101623025, 2021 (CC BY 4.0) | ISSN 2525-3409 | DOI: http://dx.doi.org/10.33448/rsd-v10i16.23025 8 between 0.25 and 0.50, which makes it moderately informative. For Botstein, White, and Davis (1980), molecular markers that present PIC values below 0.25 are considered to be poorly informative, whereas those with values between 0.25 and 0.50 are classified as moderately informative and above 0.50 are very informative.
The mean dissimilarity found was similar to that found by Brito et al. (2016) for the species Varronia curassavica, which, according to the authors, indicates a high genetic diversity among many pairs of individuals. Dissimilarity data indicate that there is no evidence of genetically identical individuals, and these therefore present potential for the composition of germplasm banks. The CCC value obtained in the UPGMA is considered satisfactory according to Rohlf (1970), since it is above 0.70, and indicates a good adjustment between the dissimilarity matrix and the cophenetic matrix.
Considering the results obtained by UPGMA and Bayesian analysis, the disposition of individuals from different sample subunits in the same genetic grouping can be explained by the fact that their main dispersers are birds (Rabello, Ramos, & Hasui, 2010), and this type of dispersion allows dispersion over long distances. According to Trolliet, Forget, Doucet, Gillet, and Hambuckers (2017) and Oliveira et al. (2020), this plant-frugivore relationship has a fundamental role in the forest structure, and may be one of the main mechanisms of dispersal of plant species.
High genetic diversity in Copaifera langsdorffii was also observed by Martins, Santos, Gaiotto, Moreno, and Kageyama (2008) who studied populations in Pontal do Paranapanema, in the state of São Paulo, using the analysis of microsatellite markers, as well as by Sebbenn et al. (2010), who evaluated a population of C. langsdorffii in the municipality of São Jose do Rio Preto, State of São Paulo. Indicating that even with the pressure exerted by exploration and deforestation, individuals with high genetic diversity can still be found that demonstrate the capacity to be used in the conservation of the species.
The Shannon index (I) resembled that found by Guerra, Gómez, Gutierrez, and Hahn (2018) (between 0.36 and 0.39) who evaluated genetic diversity in Adesmia bijuga Phil using ISSR markers. Group B has the highest genetic diversity, as well as the highest values for the Shannon and Nei indices, which may be associated with the geographical distance between the individuals, since this group is basically composed of the individuals sampled in subunits III and IV. AMOVA indicated that the greatest genetic variability is within each group, and allows a greater number of combinations between individuals, which, according to Demartelaere et al. (2020), is important for determine possible adaptations in the face of environmental changes. Nybom (2004) found, while analyzing studies performed with dominant markers, that long-lived, allogamous and latesuccessional plants presented greater genetic variability within populations, which is in accordance with the characteristics and lifestyle of Copaifera langsdorffii.
Given the scenario of forest degradation in Brazil, the genetic diversity found among individuals of Copaifera langsdorffii corroborate the importance of forest preservation and conservation, since, according to Fonseca et al. (2021), the area deforested in the 2021 deforestation calendar (August 2020 and July 2021) was 10476 km², 57% larger than that recorded in the previous year. The possible creation of ecological corridors between the fragments to connect them or bring them closer together would make the gene flow more viable. Martins et al. (2008) state that the connectivity between fragments facilitates the maintenance of genetic diversity and allows the movement of fauna, enabling the dispersal of seeds of zoochoric species (Trolliet et al., 2017;Oliveira et al., 2020).

Conclusion
The results herein indicate that the evaluated individuals of C. langsdorffii have high genetic diversity, and thus have potential to compose programs aimed at the preservation and conservation of the species and may be integrated in germplasm banks. They also evidenced the efficiency of the DNA extraction and amplification method using the ISSR markers described in this work, confirming the possibility of applying these for the genetic study with other populations the species.