All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.
Research Article

Genetic diversity between and within half-sib families of Brazil nut tree (Bertholletia excelsa Bonpl.) originating from native forest of the Brazilian Amazon

Received: September 11, 2017
Accepted: November 08, 2017
Published: November 29, 2017
Genet.Mol.Res. 16(4): gmr16039839
DOI: 10.4238/gmr16039839

Abstract

Brazil nut tree is a species of economic importance for the Amazon region, known for the commercialization of its almonds. The objective of this work was to study the genetic diversity among half-sib progenies from different Brazil nut trees present in native forest in the municipality of Itaúba, MT, belonging to the Brazilian Amazon. In a native forest area of nine hectares, fruits of nine parent trees, randomly selected in the plot, were collected. The seeds were planted at greenhouse and they were named, according to their origin, identifying seed tree and fruit. After the seed germination and initial development of the seedlings, leaves were collected for DNA extraction and analyzed with microsatellite molecular markers. It was performed analysis of molecular variance and cluster analysis of progenies and seed trees. There is greater genetic diversity between families than among progenies from the same family. The clustering of progenies from different families in the same group can be explained by the low dissimilarity between the seed trees. Among the loci analyzed in this study, eight were informative for evaluations of genetic diversity in Brazil nut, except BET12 and BET16 loci

Introduction

Brazil nut tree (Bertholletia excelsa Bonpl.) is a species of economic importance for the Amazon region, known for the commercialization of its almonds (Salomão, 2009). It presents good development in hot and humid climate (Lorenzi, 2000; Santos et al., 2006) and occurs in countries such as Venezuela, Colombia, Peru, Bolivia, Guianas and Brazil (Lorenzi, 2000).

The species reproduces by cross fertilization (allogamy), and its pollination occurs by an exclusive group of bees that can access the flowers reproductive organs (Müller, 1995; Maués, 2002). The fruits are collected in native forests, after maturation, when they fall on the soil, which usually occurs in the rainy season (Borges et al., 2016). They can store approximately 15 to 25 seeds, which have lengths ranging from 4 to 7 cm. The seeds are lined with a ligniform shell, with a single almond inside (Moritz, 1984) and has a recalcitrant behavior (Cunha et al., 1996).

Brazil nut germination process is slow and uneven, and may take between six and eighteen months to occur when there is no treatment, such as breaking the tegument (Müller et al., 1980; Camargo, 1997). The regeneration of the species in native forest is not affected by extractivism (Wadt et al., 2008; Scoles and Gribel, 2011; Ribeiro et al., 2014; Scoles and Gribel, 2015), but deforestation and fires are considered as obstacles to the maintenance of natural populations, genetic diversity and conservation of the species (Maués and Oliveira, 2010).

The maintenance of genetic diversity is the basis for conservation strategies and obtaining improved populations (Yeeh et al., 1996). The distribution of genetic variability in natural populations is influenced by the mode of reproduction, population size, geographic distribution and gene flow (Hamrick, 1982). Tropical forest tree species generally have a high proportion of polymorphic loci, and most genetic variation is maintained within populations rather than between them (Hamrick ,1994; Baldoni et al., 2017).

Knowledge of genetic variability, both within and between populations, can guide genetic breeding programs aiming at improving a specific trait or group of traits by selecting, crossing and / or recombining individuals with high frequency of favorable alleles (Erickson et al., 2004). In addition, studies on genetic diversity can help in the maintenance and conservation of germplasm banks by eliminating redundant individuals (replicates).

In Brazil nut tree, several studies have shown different levels of genetic diversity (Buckley et al., 1988; Kanashiro et al., 1997; O’Malley, 1998; Serra et al., 2006; Sujii, 2011; Silva et al., 2012; Vieira, 2014; Wadt et al., 2015; Baldoni et al., 2017; Cabral et al., 2017), being, in the majority of them, considered high. An important technique available for detecting genetic diversity at the DNA level is the microsatellite markers. Also known as SSR, these are one of the most polymorphic classes of markers currently available, are codominant and easily reproducible, besides have frequent and random distribution, allowing wide genome coverage (Caixeta, 2016).

Studying genetic diversity through molecular markers is important for breeding programs because of the absence of environmental factors. Excoffier et al., (1992) proposed an analysis of molecular variance (AMOVA) to analyze the distribution of genetic variability between and within populations. The method uses a hierarchical analysis scheme to analyze the distance among all pairs of genotypes.

The objective of this work was to study the genetic diversity among half-sib progenies from different seed trees of Brazil nut present in native forest in the municipality of Itaúba, MT, belonging to the Brazilian Amazon.

Material and Methods

In a native forest area of nine hectares, which constitutes a permanent plot, Santo Ângelo Farm, located approximately 30 km from the municipality of Itaúba, MT, Brazil, fruits of nine seed trees, randomly selected in the plot, were collected. The name of each seed tree and its location are represented in Figure 1. The trunk vascular cambium of these trees was collected for DNA extraction.

brazilian-amazon-excelsa-trees

Figure 1: Geographic location of the nine Bertholletia excelsa trees used for collecting seeds.

A total of 98 fruits were collected in December 2014 and taken to Embrapa Agrossilvipastoril, Sinop, MT, Brazil. Before planting the seeds, the seeds teguments were removed to accelerate the germination, taking care not to damage its endosperm, mainly in the regions where the apical meristems are located. After removal of the tegument, the almonds were treated with a fungicide solution according to Müller (1982) and seeded in a sandbox in the greenhouse with 50% shading, in January 2015.

The seeds were planted in rows, where each row was composed of seeds from the same fruit. These seeds were named according to their origin, identifying seed tree and fruit. After the seed germination and initial development of the seedlings, leaves were collected for DNA extraction.

The collection of trunk vascular cambium from the seeds tree and progeny leaves were performed according to Cabral et al., (2017). Genomic DNA extraction followed the protocol proposed by Doyle and Doyle (1987), with modifications (CTAB 4%). Ten microsatellite primers already developed for Brazil nut were used, namely BET12, BET14, BET15, BET16, BEX02, BEX09, BEX22, BEX27, BEX33 and BEX37 (Reis et al., 2009; Sujii et al., 2013), as shown in Table 2. Amplification and genotyping were performed according to Cabral et al., (2017). Considering that progenies from the same seed tree constitute a half-sib family (HSF), we used nine HSF. The present study considered each of these families as a different population, and the individuals that composed them were used to study the divergence between and within families. The results from the microsatellite data were used to perform the analysis of molecular variance (AMOVA) for each locus (primer), according to the statistical model, as shown in Equation 1:

Name of seed tree DBH (cm) Number of fruits per tree Number of seeds planted Number of seeds germinated
M1 58.80 20 253 78
M2 73.10 08 109 10
M3 46.70 10 138 31
M4 101.22 10 146 37
M5 62.40 10 142 22
M6 55.50 10 145 31
M7 147.05 10 115 35
M8 93.90 10 162 41
M9 75.30 10 138 15
Total   98 1348 300

Table 1: Name of seed tree, diameter at breast height (DBH), number of fruits collected per tree, number of seeds planted and germinated of B. excelsa

Locus Sequence SF (bp) AT ºC
BET12 F: ATAAGGACCGCCCATCATC
R: ATAGCGAGAGCAACCTTTGAAC
112-118 56
BET14 F: GTGTACTTCTCTGGTTGGGGC
R: CCCGAGTTCATTACCCAAACT
106-120 56
BET15 F: ACTGCCATCACCAGCATGTAG
R: GTCCCTTGTGGTCTCTCACAAT
184-202 56
BET16 F: TCTTCAAACACTCAAAGGGACA
R: TGTCTATAAATAGGGGCCTCCC
128-130 56
BEX02 F: GCCATGTTCTCTACAGTCTC
R: AGTCGGACATCCTTCGTGCT
108-130 56
BEX09 F: TATTCCATGGTCCTCCGT
R: AGTCAATCATCTTCAAGAGT
108-138 56
BEX22 F: GCATTCTCTCATTTTCGCTTG
R: CCCTAGCAATCGTCGTCTTC
124-150 56
BEX27 F: ACTGTTCTGATCCGCCATGT
R: TTTCGACCGTTCAAATACGC
128-136 56
BEX33 F: CAAGTCTCTGACTCATCGCCTA
R: ACCAGGTTCAGCAGACGTTC
195-249 56
BEX37 F: TGCATGCTATGTTTCATTGCT
R: CACGCAACCTCACAGTCTTG
184-212 56

Table 2: Relationship of microsatellite primers used, with sequence, size found in base pairs (SF), and annealing temperature

Xijk = μ + Pi + I/Pij + Gijk          1

Where: Xijk is the variable that identifies the presence of a given Ak allele in the genotype of the j-th progeny of the i-th family; μ is the average frequency of the allele Ak in the studied families; Pi is the effect of the i-th family (i = 1, 2, ..., 9) with equation I/Pij is the effect of the j-th progeny within the i-th family (j = 1, 2, ..., 300) withequation Gijk is the effect of the presence or absence of the k-th allele (k = 1, 2) with equation

Wrigth (1951) statistics were estimated according to Equations 2, 3 and 4, respectively:

equation      2

equation       3

equation     4

Subsequently, the distances between the progenies were estimated according to the complement of the unweighted index (Cii’), as shown in Equation 5:

equation

where: L is the total number of loci studied; cj: number of common alleles between the progeny pairs i and i '. All analyses were performed with Genes software (Cruz, 2013).

With the distance matrix between genotypes, the HSF together with their seed trees were clustered by the modified Ward method, following a proposal by Tardin et al., (2007). Ward's minimum variance method, for initial group formation, considers the individuals that provide the smallest sum of squared deviations. It is assumed that at any stage there is loss of information due to the clustering formed, which can be quantified by the ratio of the sum of squared deviations within the forming group and the total sum of squared deviations. While calculating the sum of squared deviations within the group, considering only the genotypes within the forming group, the total sum of squared deviations considers all individuals available for cluster analysis (Cruz and Carneiro, 2003). The clustering is carried out from the sum of squared deviations between genotypes or, alternatively, from the squared distance between genotypes. In the case of this work, the Ward's method was modified, because instead of using the Euclidean distance, the squared distance between genotypes obtained by the arithmetic complement of the unweighted index was used.

Results

Table 3 contains the summary of the analysis of variance, proposed by Excoffier et al. (1992) from the ten microsatellite loci evaluated between and within nine half-sib families (HSF) of Brazil nut. Significant differences were observed between the families for the majority of the loci evaluated, that is, from the ten loci used, eight allowed differentiating the nine families, being important for the genetic diversity analysis. It was found that there was no significant difference between the HSF only for the BET12 and BET16 loci. These results show that all the HSF evaluated in this study presented similar polymorphism for these loci, indicating that they did not contribute to the study on genetic diversity in the present study.

There was no significance of the effect of progenies within the family for any of the loci evaluated in this study (Table 3), demonstrating a progenies trend from the same seed tree (family) to present the same alleles.

Sources of variation DF MS
BET 12 BET 14 BET 15 BET 16 BEX 02
Families 8 1.04ns 4.10* 6.05* 0.25ns 2.41*
Progenies/Families 300 0.16ns 0.42ns 0.50ns 0.13ns 0.40ns
Allele/Progenies 309 0.83 0.45 0.61 0.86 0.44
    BEX 09 BEX 22 BEX 27 BEX 33 BEX 37
Families 8 4.23* 4.90* 3.30* 3.86* 9.24*
Progenies/Families 300 0.34ns 0.37ns 0.13ns 0.51ns 0.50ns
Allele/Progenies 309 0.34 0.50 0.17 0.57 0.60

Table 3. Summary of molecular analysis of variance (AMOVA) with their sources of variation and respective degrees of freedom (DF) and mean squares (MS) for the ten loci quantified in nine families and 300 progenies of Brazil nut, by microsatellite markers.

Figure 2 contains the clustering of the seed trees and their progenies based on the complement of the unweighted index. It can to check the distinction of five well-defined groups. Group I allocated the majority of the progenies originated from M1, besides M1 itself, M3 and M7. Group II allocated M6 and its progenies. The other groups presented different constitution allocating progenies from different seed trees. The greatest distance was observed among the genotypes M1-F1-2 and M6-F5-1 (0.85).

Variability within families can be observed by the occurrence of several subgroups within the five large groups formed in the dendrogram (Figure 2), indicating the possibility of selecting genotypes with genotypic variance for use in breeding programs. The clustering by Ward's hierarchical method also showed a coincidence among 29 pairs of genotypes, which presented null value of genetic dissimilarity. In the present study, replicate cases were observed, highlighting the progenies from the family 4, in which five genotypes had null genetic distance between them (M4-F6-6, M4-F6-4, M4-F3-3, M4-F3-1 and M4-F3-2). It was also observed that many replicates occurred between plants from the same tree and same fruit (M1-F8-1 and M1-F8-2; M1-F9-8 and M1-F9-10; M4-F3-1, M4-F3-2 and M4-F3-3; M4-F6-4 and M4-F6-6).

Clustering of nine families into five large groups (Figure 2), by Ward's hierarchical method, demonstrated that some of the progenitors are genetically close to each other. This was observed by the calculated values of genetic dissimilarity between the nine seed trees, according to Table 4.

brazilian-amazon-progenies-brazil

Figure 2: Clustering of nine seed trees and 300 progenies of Brazil nut by the Ward method, based on the complement of the unweighted index.

Seed tree M2 M3 M4 M5 M6 M7 M8 M9
M1 0.2 0.2 0.2 0.2 0.25 0.15 0.1 0.2
M2   0.2 0.35 0.3 0.3 0.2 0.2 0.25
M3     0.25 0.15 0.3 0.3 0.3 0.3
M4       0.1 0.35 0.15 0.2 0.15
M5         0.3 0.25 0.2 0.25
M6           0.4 0.25 0.35
M7             0.15 0.1
M8             0.1

Table 4: Genetic dissimilarity values among the nine Brazil nut trees.

Among the seed trees evaluated, M6 and M7 presented the highest dissimilarity values (0.4). In M6, the highest dissimilarity values were also observed in relation to the other trees (Table 4), as well as in the clustering (Figure 2), in which most progenies from this family were allocated into the same group (Group II). The smallest distances were observed between the trees M1 and M8, M4 and M5, M7 and M9, M8 and M9 (0.1), e consequently, the progenies from these trees were clustered together.

Discussion

The molecular analysis of variance (AMOVA) from the ten microsatellite loci evaluated between and within nine half-sib families (HSF) of Brazil nut showed that progenies trend from the same seed tree (family) to present the same alleles (Table 3). These results are important because they show that even Brazil nut being an allogamous species (Baldoni et al., 2017), the gene flow is low, that is, with small diversity within the family.

In the literature, the genetic diversity evaluated at the Brazil nut population level showed greater diversity within than between populations (Sujii et al., 2015; Wadt et al., 2015; Baldoni et al., 2017). In the present study, the evaluation was performed at the individual level, that is, the genetic diversity of the progenies from the same seed tree (family) was evaluated. In this case, a lower diversity was observed among the progenies from the same family when compared to the diversity among the families. It should also be considered that the progenies from each family evaluated are half-sib, that is, they initially have 50% of the genetic constitution in common, which explains the results observed here.

The variability within families can be observed by the occurrence of several subgroups within the five large groups formed by the clustering dendrogram of the Ward method (Figure 2). These results indicate the possibility of selection genotypes between and within half-sib families with genotypic variance for use in breeding programs.

Twenty-nine pairs of genotypes with null value of genetic dissimilarity were observed, demonstrating the efficiency in using the markers in diversity studies, to identify replicates in germplasm banks, for example, which would allow eliminating replicates and hence reducing maintenance costs of banks. It was also observed that many replicates occurred between plants from the same tree and same fruit, which can be explained by the action of pollinating agents, bees belonging the genus Bombus, Xylocopa and Centris (Müller, 1995; Maués, 2002), which can carry the pollen to different flowers of the same tree (Baldoni et al. 2017). As Brazil nut is reproduced by cross fertilization, another hypothesis would be the existence of apomixis, as already reported for other forest species (Kaur et al., 1978; Goldenberg and Shepherd, 1998; Chaves et al., 2017).

Studies on genetic dissimilarity, through the use of molecular markers, such as microsatellites, contribute to breeding programs (Caixeta et al., 2013), since it is possible to identify replicates, information on levels of heterozygosity, and to identify genotypic differences of the seed trees. Identification of replicates is important in the maintenance and conservation of genetic resources in germplasm banks. The molecular markers used in this study were able to identify the replicates, in addition to being significant in the genetic diversity analysis of the families evaluated.

Conclusion

There is greater genetic diversity between families than among progenies from the same family. The clustering of progenies from different families in the same group can be explained by the low dissimilarity between the seed trees. Among the loci analyzed in this study, eight were informative for evaluations of genetic diversity in Brazil nut, except BET12 and BET16 loci.

Conflicts of interest

The authors declare no conflict of interest.

Acknowledgments

Research supported by grants from Embrapa (Empresa Brasileira de Pesquisa Agropecuária), CNPq (National Counsel of Technological and Scientific Development), and FAPEMAT (Fundação de Amparo à Pesquisa do Estado de Mato Grosso). Flávio D. Tardin is the recipient of a research fellowship from CNPq.

About the Authors

Corresponding Author

A.B. Baldoni

Empresa Brasileira de Pesquisa Agropecuária, EMBRAPA Agrossilvipastoril, Sinop, Mato Grosso, Brazil

Email:
diazcastro@unemat.br

References

  • Baldoni AB Wadt LHO Campos T (2017). Contemporary pollen and seed dispersal in natural populations of Bertholletia excelsa (Bonpl.). Genetics and Molecular Research 16(3):gmr16039756.
  • Borges FA, Tonini H, Baldoni AB (2016). Tamanho da amostra para estimar produção de sementes de castanheiras nativas. Nativa. 4(3):166-169.
  • Buckley DP, O‟Malley DM, Apsit V (1988). Genetics of Brazil nut (Bertholletia excelsa Humb. & Bonpl.: Lecythidaceae). I. Genetic variation in natural populations. Theoretical and Applied Genetics, Germany. 76:923-928.
  • Cabral JC, Baldoni AB, Tonini H (2017). Diversity and genetic structure of the native Brazil nut tree Bertholletia excelsa Bonpl.) population. Genetics and Molecular Research 16(3):gmr16039702.
  • Caixeta ET, Ferrão LFV, Maciel-Zambolim E (2013). Marcadores Moleculares. In: Borém A and Fritscher-Neto R. Biotecnologia Aplicada ao Melhoramento de Plantas, 2nd edn. Viçosa, Minas Gerais. 31-68.
  • Caixeta TE, Oliveira ACB, Brito GB (2016). Tipos de Marcadores Moleculares. In: Borém A and Caixeta E. Marcadores Moleculares, 1st edn. Viçosa, Minas Gerais. 10-93.
  • Camargo IP (1997). Estudos sobre a propagação da castanheira-do-brasil (Bertholletia excelsa Humb. & Bonpl.).Doctoral thesis. Universidade Federal de Lavras, UFLA, Lavras.
  • Chaves C, Sebbenn A, Baranoski A (2017). Gene dispersal via seeds and pollen and their effects on genetic structure in the facultative-apomictic Neotropical tree Aspidosperma polyneuronSilvae Genetica.65:2. 
  • Cruz CD (2013). GENES - a software package for analysis in experimental statistics and quantitative genetics. Acta Sci Agron. 35:271-276.
  • Cruz CD and Carneiro PCS (2003). Modelos biométricos aplicados ao melhoramento genético. Viçosa, Minas Gerais
  • Cunha R, Prado MA, Carvalho JEU (1996). Morphological studies in the development of the recalcitrant seeds of the Bertholletia excelsa H. B. K. (Brazil nut). Seed Science and Tecnology Zurich. 24(3):581-584.
  • Doyle JJ and Doyle JL (1987). Isolation of plant DNA from fresh tissue. Focus. 12:13-15.
  • Erickson DL, Hamrick JL, Kochert GD (2004). Ecological determinants of genetic diversity in an expanding population of the shrub Myrica cerifera. Molecular Ecology. 13:1655-1664.
  • Excoffier L, Smouse PE, Quattro JM (1992). Analysis of molecular variance inferred from metric distance among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics. 131:479-491.
  • Goldenberg R and Shepherd GJ (1998). Studies on the reproductive biology of Melastomataceae in “cerrado” vegetation. Plant Systematics and Evolution. 211:13-29.
  • Hamrick JL (1982). Distribuition of genetic whitin and among natural forest population. In: Chambers SM, Macbide B, Thomas WL (Eds.) Shonewald-cox.
  • Hamrick JL (1994). Genetic diversity and conservation in tropical forest. In: Drysdale M, John S Yapa AC (eds) Proc. Int. Symp. Genetic Conservation Production of Tropical Forest Tree Seed. Asean-Canada Forest Tree Seed Center. 1-9.
  • Kanashiro M, Harris SA, Simons A (1997). RAPD Diversity in Brazil Nut (Bertholletia excelsa Humb. And Bonpl., Lecythidaceae). Silvae Genetica. 46(4):219-223.
  • Kaur A, Ha CO, Jong K (1978). Apomixis may be widespread among trees of the climax rain forest. Nature 271:440-442.
  • Lorenzi H (2000). Árvores brasileiras: manual de identificação e cultivo de plantas arbóreas nativas do Brasil. Nova Odessa, São Paulo.
  • Maués MM (2002). Reproductive phenology and pollination of the Brazil nut tree (Bertholletia excelsa Humb. & Bonpl. Lecythidaceae) in Eastern Amazonia. In: Kevan P, Imperatriz-Fonseca VL (eds.). Pollinating Bees – The conservation Link Between Agriculture and Nature. Ministry of Environment, Brasília, Distrito Federal. 245-254.
  • Maués MM and Oliveira PEAM (2010). Conseqüências da fragmentação do habitat na ecologia reprodutiva de espécies arbóreas em florestas tropicais, com ênfase na Amazônia. Oecologia Australis. 14(1): 238-250.
  • Moritz A (1984). Estudos biológicos da Castanha-do-Brasil (Bertholletia excelsa H.B.K.). In: Embrapa/CPATU, Documentos 29:1. Belém, Pará. 82
  • Müller CH, Rodrigues IA, Müller AA (1980). Castanha-do-Brasil, resultados de pesquisa. In: EMBRAPA/CPATU, Miscelanias, 2, Belém, Pará, 25 p.
  • Müller CH (1982). Quebra da dormência das sementes e enxertia em castanha-do-Brasil. In: EMBRAPRA/CPATU. Documentos,16, Belém, Pará. 40
  • Müller CH, Figueiredo FJC, Kato AK (1995). A castanha-do-Brasil. In: Coleção plantar, EMBRAPA/SPI, Brasília, Distrito Federal. 65
  • O‟Malley DM, Buckley DP, Prance GT (1988). Genetics of Brazil nut (Bertholletia excelsa Humb. & Bonpl.: Lecythidaceae). Theoretical and Applied Genetics 76:929-932.
  • Reis AM, Braga AC, Lemes MR (2009). Development and characterization of microsatellite markers for the Brazil nut tree Bertholletia excelsa Humb. & B. Lecythidaceae). Molecular Ecology Resources.  9:920-923.
  • Ribeiro MBN, Jerozolimski A, Robert P (2014). Brazil nut stock and harvesting at different spatial scales in southeastern Amazonia. Forest Ecology and Management. 319:67-74.
  • Salomão RP (2009). Densidade, estrutura e distribuição espacial da castanheira-do-brasil (Bertholletia excelsa H. & B.) em uma floresta tropical de platô na Amazônia Setentrional. In: Boletim do Museu Paraense Emílio Goeldi, Ciências Naturais 4:11-25.
  • Santos D, Sarrouh B, Santos J (2006). Potencialidades e aplicações da fermentação semi-sólida em Biotecnologia. Janus 4:164-183.
  • Serra AGP, Paiva R, Paiva E (2006). Estudo da divergência genética em castanha-do-brasil (Bertholletia excelsa) utilizando marcadores moleculares RAPD (Random Amplified Polymorphic DNA). Magistra 18(1):42-47.
  • Silva VS, Martins K, Campos T, et al. (2012). Diversidade genética de populações naturais de castanheira (Bertholletia excelsa) com marcadores ISSR. In: Congresso Brasileiro de Recursos Genéticos, Belém, Pará. http://ainfo.cnptia.embrapa.br/digital/bitstream/item/71859/1/24499.pdf Accessed September 20, 2017.
  • Scoles R and Gribel R (2015). Human Influence on the Regeneration of the Brazil Nut Tree (Bertholletia excelsa Bonpl., Lecythidaceae) at Capanã Grande Lake, Manicoré, Amazonas, Brazil. Human Ecology 43:843-854.
  • Scoles R and Gribel R (2011). Population structure of Brazil nut (Bertholletia excelsa, Lecythidaceae) stands in two areas with different occupation histories in the Brazilian Amazon. Human Ecology 39:455-464.
  • Sujii PS (2011). Diversidade e estrutura genética de Bertholletia excelsa, uma espécie da Amazônia de ampla distribuição. Master’s thesis. Universidade Estadual de Campinas, UNICAMP, Campinas.
  • Sujii PS, Ciampi AY, Solferini VN (2013). Isolation and characterization of microsatellite markers for Bertholletia excelsa (Lecythidaceae) population genetics analysis. Genetics and Molecular Research 12(4):5278-5282.
  • Sujii PS, Martins K, Wadt LHO (2015). Genetic structure of Bertholletia excelsa populations from the Amazon at different spatial scales. Conserv Genet 16:955-964.
  • Tardin FD, Pereira MG, Gabriel APC (2007). Selection index and molecular markers in reciprocal recurrent selection in maize. Crop Breeding and Applied Biotechnology 7: 225-233.
  • Vieira FS (2014). Diversidade Genética e Estrutura Populacional de Populações Naturais de Castanha do Brasil (Bertholletia excelsa B.). Master’s thesis. Universidade do Estado de Mato Grosso, UNEMAT, Alta Floresta, Mato Grosso, Brazil.
  • Wadt LHO, Kainer KA, Staudhammer CL (2008). Sustainable forest use in Brazilian extractive reserves: Natural regeneration of Brazil nut in exploited populations. Biological Conservation 141:322-346.
  • Wadt LHO, Baldoni AB, Silva VS (2015). Mating system variation among populations, individuals and within and among fruits in Bertholletia excelsa. Silvae Genetica. 64:5-6.
  • Wrigth S (1951). The genetic structure of population. Annual of Eugenics. 15:313-354.
  • Yeh FC, Yang RC, Boyle T (1999). POPGENE. Microsoft Windows-based freeware for population genetic analysis. Release 1.31. Edmonton: University of Alberta.

Keywords:
Download:
Full PDF