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Revista de Biología Tropical, ISSN: 2215-2075 Vol. 69(2): 640-648, April-June 2021 (Published May 17, 2021)

Diversity and genetic structure of Spondias tuberosa

(Anacardiaceae) accessions based on microsatellite loci

Viviane Nunes dos Santos

; https://orcid.org/0000-0003-1093-204X

Carlos Antônio Fernandes Santos

*; https://orcid.org/0000-0002-6932-6805

Viseldo Ribeiro de Oliveira

; https://orcid.org/0000-0002-5301-7637

Antonio Elton da Silva Costa

; https://orcid.org/0000-0003-4653-5660

Fabricio Francisco Santos da Silva

; https://orcid.org/0000-0001-7938-8308

1. Departamento de Biologia, Universidade Estadual de Feira de Santana, Bahia, Brazil; viviane7414@gmail.com

2. Embrapa Semiárido, Caixa Postal 23. 56300-970, Petrolina, Pernambuco, Brazil;

carlos-fernandes.santos@embrapa.br (*Correspondence), viseldo.oliveira@embrapa.br

3. Departamento de Agronomia, Universidade Federal Rural do Pernambuco, Recife, Pernambuco, Brazil;

antonioelton.agro@gmail.com

4. Universidade Federal do Vale do São Francisco, Núcleo de Ecologia e Monitoramento Ambiental, Petrolina,

Pernambuco, Brazil; fabriciofrancisco2006@gmail.com

Received 13-X-2020. Corrected 25-III-2021. Accepted 10-V-2021.

ABSTRACT

Introduction: Spondias tuberosa is a tree endemic to the semiarid region of Brazil with fruticulture potential.

Objective: To estimate the diversity and genetic structure of S. tuberosa accessions from four areas of the

semiarid region of Brazil, in order to facilitate conservation genetic resources studies in this species. Methods:

DNA was extracted, using the CTAB 2x method, from leaf samples of 24 accessions of S. tuberosa available

in the germplasm bank at Embrapa Semiárido, Brazil. Ten microsatellite loci were used in this study. Results:

The UPGMA dendrogram, generated with a Jaccard coefficient similarity matrix, contains four groups at a 0.44

cutoff point. The similarity coefficient ranged from 0.30 to 0.84, indicating great divergence among the acces-

sions. A Bayesian analysis conducted with the software Structure suggests there are two subpopulations, one

formed by accessions from the Januária region and another by accessions from the Juazeiro, Uauá and Petrolina

regions. The Φ

value of 0.12 for the analysis of molecular variance indicates moderate genetic differentiation

among the four populations, suggesting that the genetic variability is moderately structured in function of region.

Conclusions: Together, the analyses indicate that the genetic diversity of S. tuberosa is not uniformly distributed

in the studied regions. Thus, germplasm from a greater number of populations should be collected to increase

the germplasm bank genetic diversity of the species.

Key words: umbu tree; AMOVA; SSR.

Nunes dos Santos, V., Fernandes Santos, C.A., Ribeiro de

Oliveira, V., da Silva Costa, A.E., Santos da Silva, F.F.

(2021). Diversity and genetic structure of Spondias tuberosa

(Anacardiaceae) accessions based on microsatellite loci.

Revista de Biología Tropical, 69(2), 640-648. https://doi.

org/10.15517/rbt.v69i2.44194

https://doi.org/10.15517/rbt.v69i2.44194

The semiarid region of Brazil has a highly

rich flora and the genus Spondias is widely

found in this area. Many species of Spon-

dias occur in spontaneous and subspontaneous

forms, such as S. mombin L., S. purpurea L., S.

cytherea Sonn., Spondias sp., S. tuberosa x S.

mombin, and S. tuberosa Arruda) (Pires, 1990).

In particular, the umbu tree (S. tuberosa) spe-

cies has great relevance to the semiarid region

due to its production potential and drought

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resistance. Umbu tree fruits have many uses,

for example, they are eaten fresh and used in

sweets, juices, jellies and other local products.

In addition to its commercial potential, umbu is

also notable for its bioactive compounds, such

as phenolic, carotenoid, flavonoid and vita-

min C compounds that have beneficial health

effects (Silva & Alves, 2008).

Agronomic and genetic characterization

are important tools for genetic improvement

and possible agronomic exploitation. However,

there are few studies that focus on the genetic

variability of umbu tree. Santos, Rodrigues,

and Zucchi (2008) studied the genetic vari-

ability of umbu tree in the Brazilian semi-arid

region using AFLP markers and found high

variability in populations, suggesting that the

genetic diversity of umbu tree could be used

to improve the species. The Embrapa Semi-

árido in Brazil maintains an umbu tree germ-

plasm collection, with 80 accessions (Ramos,

Queiroz, Romão, & Silva Júnior, 2008).

Molecular markers have been increasingly

used due their widely applied in genetic stud-

ies (Turchetto-Zolet, Turchetto, Zanella, &

Passaia, 2017). Among these biotechnological

tools microsatellite markers or single sequence

repeats (SSRs) are widely employed due to

their ease of use, codominance, multiallelism

and high reproducibility. Due to the restriction

of SSR developed for species of Spondias sp.,

studies of marker transferability are common,

as in the study of Aguilar-Barajas et al. (2014).

Balbino, Martins, Morais, and Almeida (2019)

developed 18 polymorphic SSR markers useful

for studies of genetic population and conser-

vation and breeding activities. Estimations of

genetic diversity parameters, applying SSR, are

still rare with umbu tree, mainly among acces-

sions of the Embrapa Semiárido germplasm

collection, the most important one.

The objective of the present study was to

estimate the genetic diversity and structure of

accessions at the Embrapa Semiárido germ-

plasm bank of S. tuberosa from four areas

of the semiarid region in Brazil, which will

help guide future genetic resource studies of

this species.

MATERIALS AND METHODS

Plant material and DNA extraction and

quantification: Samples of young and healthy

leaves of 24 accessions from four areas of

the Brazil semiarid region (Fig. 1) were col-

lected from the umbu tree germplasm bank

at Embrapa Semiárido in Petrolina, Pernam-

buco, Brazil. The DNA was extracted using

the CTAB 2X protocol (Doyle & Doyle, 1990)

with some modifications. DNA quantification

and the integrity were verified in 0.8 % agarose

gel, followed by diluting the genomic DNA to

10 ng mL-1.

PCR protocols: The amplification reac-

tions were made using 10 primers, including

four developed by Aguilar-Barajas et al. (2014)

and six developed by Balbino et al. (2019).

The PCRs were adjusted to a final volume of

10 μL containing the following: 1µL of buf-

fer, 2 mM of MgCl2, 0.22 μM of each dNTP,

0.4 μM of each primer (forward and reverse),

a unit of Taq DNA polymerase and 10 ng of

genomic DNA.

The amplifications were made in a Biome-

tra thermocycler using the program proposed

by Aguilar-Barajas et al. (2014): 15 min at

94 ºC, followed by 35 cycles of 30 s at 94 ºC,

1 min 30 s at 59 or 60 ºC and 1 min at 72 ºC,

and a final extension of 10 min at 72 ºC. The

amplification products were observed using

polyacrylamide gel at a concentration of 6 %,

according to the methodology described by

Costa and Santos (2013), stained with silver

nitrate (Creste, Neto, & Figueira, 2001).

Cluster, population structure and

AMOVA analysis: the number of base pairs

(bp) of each allele was estimated using the

inverse mobility method based on the regression

of products of known size of a molecular marker

with 50 bp (Ludwig Biotec ®). The microsatel-

lites were analyzed for allelic presence (1) and

absence (2) to construct a Jaccard index of

similarity. A dendrogram was generated using

the UPGMA clustering method (unweighted,

based on the arithmetic mean). The dendrogram

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was tested using the cophenetic correlation coef-

ficient. The program NTSYSpc (Rohlf, 2000)

was used for these analyses.

The accessions were grouped using the

program STRUCTURE 2.3.4 (Pritchard, Ste-

phens, & Donnelly, 2000) and the Markov

Monte Carlo chain (MCMC), with 100 000 per-

mutations and 100 000 simulations for cluster

inferences. Ten runs were performed for each

K value (number of possible clusters). Using

STRUCTURE HARVEST (Earl & vonHoldt,

2012), the ΔK value was calculated to detect

the probable number of clusters (Evanno, Reg-

naut, & Goudet, 2005).

The analysis of molecular variance

(AMOVA) was conducted by decomposing the

total variation of the components between and

within populations using the square Euclidean

distance (Excoffier, Smouse, & Quattro, 1992).

The significance of the genetic parameters was

determined by the randomization method (999

permutations). Gene flow (Nm) was estimated

by the number of migrants, based on the F

parameter that is analogous to the Φ

, defined

as the function of the between-population

variance component and the within-popula-

tion variance component (Φ

= σ

/(σ

))

(Wright, 1949; Excoffier et al., 1992; Meir-

mans & Hedrick, 2011). The program GenAlEx

6.5 (Peakall & Smouse, 2006) was used for

the AMOVA.

Fig. 1. Sampling locations of the umbu tree accessions maintained in the germplasm bank at Embrapa Semiárido (BGU),

Brazil. Accessions were collected in the following Brazilian municipalities: Petrolina, Pernambuco (PE); Juazeiro and Uauá,

Bahia (BA); and Januária, Minas Gerais (MG).

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RESULTS

SSR polymorphism: All of the SSR loci

had a good amplification pattern in the poly-

acrylamide gel (6 %). The allelic diversity

ranged from two to seven alleles per locus, with

an average of 3.5 alleles per locus (Table 1).

The polymorphic information content ranged

from 0.195 to 0.778 (Table 1). The expected

heterozygosity varied from 0.195 to 0.822 and

the observed heterozygosity ranged from 0.167

to 0.958.

Cluster analysis: The clustering of the 24

individuals has a cophenetic correlation coef-

ficient of 1.0 (Fig. 2), indicating that the data

are reliable and there is good fit between the

genetic distances, original matrix and graphic

representation. The similarity matrix ranged

from 0.115 to 0.842, indicating high variability

among the individuals analyzed (Fig. 2).

Based on the microsatellite markers and

the similarity matrix of the umbu tree acces-

sions, it was possible to separate the accessions

into four groups, using the average distance

of 0.44 as the cutoff point. The groups are

formed by the following accessions: group I

by BGU56 (Januária); group II by BGU58,

BGU59 and BGU62 (Januária); group III

by BGU07, BGU32, BGU60 and BGU61

(Juazeiro, Uauá and Januária, respectively);

and group IV by 16 accessions, including

BGU01, BGU05, BGU16, BGU41, BGU42

(Juazeiro); BGU28, BGU31, BGU35, BGU37

and BGU38 (Uauá), and BGU12, BGU13,

BGU14, BGU22, BGU39 and BGU40 (Petro-

lina) (Fig. 2).

Genetic structure and gene flow: Two

groups were identified based on ΔK (K = 2)

(Fig. 3, Fig. 4). Of the clusters obtained from

the similarity matrices, there is a group of three

TABLE 1

Genetic parameters of ten microsatellite loci evaluated in 24 individuals of Spondias tuberosa

Locus Primer sequences (5’-3’)

Parameters in S. tuberosa

(ºC) NA BS PIC He Ho

SPO4 Forward: CGCTAGTTGTCATTCGCGG

Reverse: GCTTAACCTCTGGAAAGTCGC

62 7 548-696 0.778 0.822 0.958

SPO8 Forward: GCAGCAGCCATTTGTGAAC

Reverse: CACGTGTTCCCAGTTATGATTTG

60 4 505-529 0.486 0.552

0.458

SPO14 Forward: ACACCAACGTTTGCGGAG

Reverse: TCTAGGTAGACAGCGACAAATC

62 3 640-707 0.575 0.662

0.500

SPO18 Forward: TCTATTTGCGTCCAGGTATTTC

Reverse: GAATGGGCACGTTCCTTGG

62 3 820-874 0.477 0.580 0.609

TUB78 Forward: TGCTCTGCCTTCCAACATGT

Reverse: GTACGTGAGGGACAATGGGG

59 3 558-642 0.388 0.414 0.458

TUB84 Forward: CACCTCCTACGTTACTGCCA

Reverse: TCAAACTGGATTCAGGCATGC

59 2 580-613 0.359 0.479 0.333

TUB93 Forward: AGCCTTTTTGAGTCACATGCA

Reverse: ACACTGATGGTACGTGAACAA

60 2 570-624 0.195 0.223 0.167

TUB94 Forward: TGTCTGAGGATCGAGACGAGA

Reverse: GCACGCGCTTACTTATGTTGG

60 3 689-767 0.522 0.600 0.542

TUB98 Forward: AGCGGAAAAGAATGATGAAGGC

Reverse: GTTGGCTTCTTTCTTGCGGC

60 4 647-683 0.474 0.554 0.667

TUB103 Forward: GGAGCAGTGAAACCCCTGAA

Reverse: GTCCAGGTCGCCGTAAAGAA

60 4 519-533 0.357 0.392

(°C): annealing temperature; NA: number of alleles; BS: band size; PIC: polymorphic information content; He: expected

heterozygosity; Ho: observed heterozygosity.

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accessions (BGU58, BGU59 and BGU62)

exclusive to the region of Januária, Minas

Gerais that is located in Brazil Southeastern

part of the semiarid region.

The Bayesian analysis indicated the exis-

tence of only two groups, the three accessions

from Januária, Minas Gerais in one group and

the remaining accessions from Uauá, Bahia;

Juazeiro, Bahia; and Petrolina, Pernambuco in

another group (Fig. 4).

The analysis of molecular variance of 24

individuals the umbu tree from four distinct

populations revealed that only 12 % of the

genetic variability is between populations and

Fig. 2. Dendrogram representing the SSR genetic divergence among the 24 accessions of S. tuberosa obtained from the

UPGMA method, using the complement of the Jaccard index as the average of dissimilarity. Cophenetic value = 1.0.

Fig. 3. Delta K, calculated with the second-order average rate of variation of the K probability divided by the standard

deviation of the K probability.

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88 % of the variability is within populations

(Table 2).

DISCUSSION

Microsatellite markers used to estimate the

genetic diversity and structure of S. tuberosa

accessions had good amplification patterns

and an average of 3.5 alleles per locus. This

is similar to the study of Balbino, Caetano,

and Almeida (2018) who found an average

of 2.7 alleles per locus for the same species

Cristóbal-Pérez, Fuchs, Harvey, and Quesada

(2019) evaluated the genetic variability of

another species of the genus (S. purpurea)

using 24 microsatellites and found an average

of 5.88 alleles. Silva et al. (2017) also found

high allelic diversity (6.97 alleles per locus)

using ISSR markers to characterize the genetic

diversity of S. mombin.

The polymorphic information content

(PIC) values were moderate (0.5 > PIC > 0.25)

to highly (PIC > 0.5) informative, according to

the classification by Botstein, White, Skolnick,

and Davis (1980), except for TUB93 that had

a less-informative PIC value of 0.195, and the

SPO4, SPO14 and TUB94 loci were the most

informative (Table 1; Silva et al., 2017) esti-

mated the genetic diversity of S. mombin using

ISSR markers and found PIC values above

0.250 for most of the markers used, similar to

our study.

For the SPO8, SPO14, TUB84, TUB93,

TUB94 and TUB103 markers, the expected

heterozygosity was higher than the observed

heterozygosity, meaning high genetic vari-

ability and mixing of populations. Cristóbal-

Pérez et al. (2019) also found higher expected

heterozygosity values when evaluating 139

individuals of S. purpurea, from three Mexican

localities, based on 10 polymorphic SSR loci.

The expected and observed heterozygosity

values were similar to those observed by Bal-

bino et al. (2018), who found values between

0.158 and 0.607, and 0.170 and 0.781, respec-

tively, in a study about the phylogeographic

pattern of S. tuberosa using accD-psaI plastid

sequences and SSR markers of individuals

from 20 localities of Brazil Northeastern.

In the cluster analysis, the cophenetic cor-

relation coefficient of 1.0 indicates the confi-

dence of the data and shows there is a good fit

between the genetic distances, original matrix,

and graphic representation. Dendrogram of the

24 individuals analyzed, based on the UPGMA

Fig. 4. Genetic structure of 24 umbu tree accessions from four semiarid regions, based on a Bayesian analysis, considering

K = 2, obtained by the ΔK method, from 20 independent simulations for each number of possible clusters (k).

TABLE 2

Analysis of molecular variance (AMOVA) among four umbu tree populations assessed with ten microsatellite loci

Source of variation d.f. SS MS p-value Total genetic variation (%) Φ

Among populations 3 27.833 9.278 < 0.001 12 Φ

= 0.12 1.865

Within population 20 102.833 5.142 < 0.001 88 1- Φ

= 0.88

Total 23 130.667

d.f.: Degree of freedom; SS: Sum of squares; MS: Mean squares; p-value based on 999 permutations; Φ

: Subpopulation

genetic variance (

)/total genetic variance (

); Nm: Number of migrants calculated using the method by Wright (1949) [(1-

ΦST)/(4 ΦST)].

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method, showed four groups. Reduced cluster

number was reported by Santana et al. (2011),

when analyzed the genetic diversity among 17

Spondias sp. accessions from Brazil Northeast,

with 25 ISSR markers, a king of universal SSR.

Based on ISSR, Silva et al. (2017) reported

nine groups with a sampling of 126 individuals

of S. mombin from three populations, collected

in the Mato Grosso State, Brazil.

The BGU56 accession comprised the first

group diverging from the other studied acces-

sions. The second group only contains the

accessions from Januária-MG, municipality

located in the Brazilian Southeast Region, geo-

graphically distant, around 2 000 Km, from the

other analyzed regions. The fourth group has

the most accessions and comprises individuals

from the Juazeiro, state of Bahia, Uauá, state

of Bahia, and Petrolina, state of Pernambuc

regions, which are relatively close to each

other, maximum of 150 km, in the same eco-

geographic region. Thus, we can infer that their

proximity justifies this cluster. Based on pheno-

typic characters, Santos (1997) concluded that

variability in umbu tree is uniformly distributed

in the semiarid region of Brazil. Differently,

Santos et al. (2008), based on AFLP markers,

concluded that the genetic variability of umbu

tree is not uniformly distributed in this region

and that geographic barriers or edaphoclimatic

conditions have limited the crossing and fre-

quency of the alleles among populations. The

present study also indicates that the variability

of umbu tree is not uniformly distributed in

the semiarid region, since individuals from

Januária form nearly exclusive group, while

individuals from Uauá, Juazeiro and Petrolina

are almost all in the same group.

Based on Bayesian statistics, two genet-

ic groups (K) were found in this study. Of

these two groups obtained for K, one includes

the three accessions (BGU58, BGU59 and

BGU62) from Januária-MG, in the southeast

part of the Brazilian semiarid region, and the

other contains the remaining accessions from

Uauá, Juazeiro, and Petrolina. Balbino et al.

(2018) also found K = 2 in a study of the

phylogeographic pattern of S. tuberosa using

sequences of the accD-psaI plastid region and

six SSR markers for individuals from 20 locali-

ties of the Brazil North-eastern. By Bayesian

analysis, the two groups found in the present

study can be seen at a cutoff point of 0.40 in

the UPGMA dendrogram (Fig. 1), in three

groups. Costa and Santos (2017) also reported

concordances between UPGMA and Bayesian

analyses when studying accessions of Psidium

(guava) with SNPs.

The analysis of molecular variance indi-

cated moderate genetic differentiation diversity

among population (12 % of the variability). A

similar result was found in the study of Bal-

bino et al. (2018), where the authors detected

13 % genetic variability among populations of

S. tuberosa from Brazil North-eastern regions.

These data go to what was reported by Paiva

(1998) who noted that in natural plant popula-

tions in tropical regions most genetic variabil-

ity is preserved within populations. Still about,

according to Wright (1965), F

(=Φ

) values

above 0.25 indicate high levels of genetic dif-

ferentiation and an F

value of 0.12 indicates

moderate differentiation.

Using the AFLP molecular marker, Santos

et al. (2008) studied the distribution of the

genetic variability of umbu tree in the semi-

arid region of Brazil and found high genetic

differentiation (F

= 0.3138), suggesting that

this species has restricted flow, with less than

one migrant per generation (Nm = 0.567), and

high variability between populations. Using

an isoenzymatic polymorphism analysis Silva,

Martins, and Oliveira (2009) estimated the

genetic diversity and structure of S. lutea popu-

lations in the forest zone in Pernambuco State,

in Northeastern Brazil, and found an Nm value

of 5.27, which differs from that found in the

present study.

The cluster analysis, AMOVA and Bayes-

ian analysis of the present study indicate that the

genetic diversity of S. tuberosa is not uniformly

distributed in the Januária-MG, Juazeiro-BA,

Uauá-BA and Petrolina-PE regions. Thus,

germplasm from a greater number of popula-

tions should be collected in other Brazilian

regions to increase the genetic diversity of the

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germplasm collection maintained at Embrapa

Semiárido, Brazil.

The F

value of 0.12 indicates moderate

genetic differentiation among the S. tuberosa

populations from Januária-MG, Juazeiro-BA,

Uauá-BA and Petrolina-PE, suggesting that

the genetic variability of the accessions of the

Embrapa germplasm collection is moderately

structured in function of origin. The genetic

diversity of S. tuberosa is not uniformly dis-

tributed in the four studied Brazilian semiarid

regions and germplasm expedition should con-

sider sampling in other regions to increase the

collection variability.

Ethical statement: authors declare that

they all agree with this publication and made

significant contributions; that there is no con-

flict of interest of any kind; and that we fol-

lowed all pertinent ethical and legal procedures

and requirements. All financial sources are

fully and clearly stated in the acknowledge-

ments section. A signed document has been

filed in the journal archives.

ACKNOWLEDGMENTS

The authors would like to thank Embrapa

(Brazilian Agricultural Research Corporation)

for the infrastructure and financial support for

carrying out the experiments; CAPES (Coordi-

nation for the Improvement of Higher Educa-

tion Personnel) and CNPq (National Council

for Scientific and Technological Development)

for the grant of the postgraduate scholarship.

We also thank Mr. Geraldo Freire dos Santos

for his support in the field and Ms. Tatiana

Ayako Taura for the support on the map.

RESUMEN

Diversidad y estructura genética de “accesiones”

de Spondias tuberosa (Anacardiaceae) basadas

en loci de microsatélites

Introducción: Spondias tuberosa es un árbol endé-

mico de la región semiárida de Brasil con potencial fru-

tícola. Objetivo: Estimar la diversidad y caracterizar la

estructura genética de accesiones de S. tuberosa en cuatro

áreas del semiárido brasileño, para así facilitar estudios

de conservación de recursos genéticos de esta especie.

Metodología: El ADN fue extraído utilizando el método

CTAB 2x a partir de muestras de hojas de 24 accesiones

de S. tuberosa disponibles en el banco de germoplasma

de Embrapa Semiárido, Brasil. Diez loci de microsatélites

fueron usados en este estudio. Resultados: El dendro-

grama UPGMA generado con una matriz de similitud de

coeficientes de Jaccard, formó cuatro grupos con punto de

corte en 0.44. El coeficiente de similitud osciló entre 0.30 y

0.84, indicando una gran divergencia entre las accesiones.

El análisis Bayesiano realizado en el software Structure

sugiere la existencia de dos subpoblaciones, una formada

por las accesiones de la región de Januária y otra derivada

de las regiones de Juazeiro, Uauá y Petrolina. El valor de

de 0.12 derivado del análisis molecular de la varianza

indica moderada variación genética entre las cuatro pobla-

ciones, sugiriendo que la variabilidad genética se estructura

moderadamente en función de la región. Conclusiones:

Los análisis en conjunto indican que la diversidad genética

de S. tuberosa no se encuentra distribuida uniformemente

en las regiones estudiadas. Por lo tanto, se debe recolectar

germoplasma de un mayor número de poblaciones para

aumentar la diversidad genética del banco actual de la

especie.

Palabras clave: árbol de Umbú; AMOVA; SSR.

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