Genetic diversity of Lippia origanoides Kunth. in natural populations using ISSR markers

Diversidade genética por marcadores ISSR em populações naturais de Lippia origanoides Kunth.

ABSTRACT

Lippia origanoides Kunth. is a medicinal plant that is widely available in the Northeast region of Brazil and is known as “alecrim-d’angola”. However, there is no information available on the genetic variability of this species in the region. Thus, the current study was aimed to analyze the genetic diversity and structuring of L. origanoides populations occurring in the states of Bahia and Pernambuco, Brazil, using Inter-Simple Sequence Repeat (ISSR) molecular markers. The evaluated Nei’s diversity index of the populations varied from 0.162 to 0.237, and the Shannon diversity index varied from 0.247 to 0.350. In molecular variance (AMOVA) analysis, a variation of 31% was observed among the populations, which denotes a high interpopulation structuring. The structure analysis and dendrogram indicated the possibility of classifying the 18 populations into four groups. As their genetic structure is extremely high, it is important to collect L. origanoides germplasm, including as many populations as possible. Since the region of Chapada Diamantina holds the most diverse populations of L. origanoides germplasm, it is a priority area to obtain the germplasm.

Keywords:
Genetic variability; medicinal plant; Verbenaceae; germplasm conservation.

RESUMO

A espécie medicinal Lippia origanoides Kunth. tem ampla ocorrência no Nordeste brasileiro, sendo conhecida como alecrim-d’angola. Porém, dados sobre a variabilidade genética da espécie na região são inexistentes. O objetivo dessa pesquisa foi analisar os níveis de diversidade e estruturação genética das populações de L. origanoides ocorrentes no Estado da Bahia e Pernambuco, por meio de marcadores moleculares ISSR. Nas populações avaliadas o Índice de diversidade de Nei oscilou entre 0,162 e 0,237, o Índice de Shannon variou entre 0,247 e 0,350. A AMOVA identificou variação entre populações de 31%, sugerindo alta estruturação interpopulacional. A análise no Structure e o dendrograma gerado indicaram a possibilidade de separação das 18 populações em quatro grupos distintos. A coleta de germoplasma da espécie deve ser feita no maior número de populações possível, devido à alta estruturação genética encontrada. A região da Chapada Diamantina é uma área prioritária para obtenção de germoplasma de L. origanoides, pois detém as populações mais diversas.

Palavras-chave:
Variabilidade genética; planta medicinal; Verbenaceae; conservação de germoplasma.

INTRODUCTION

The genus Lippia Linn. comprises many species that are known for their therapeutic applications (Stashenko et al., 2010; Trindade et al., 2021), including Lippia origanoides Kunth., popularly known as “alecrim-d’angola” and “salva-de-marajó”. Due to the production of several essential oils, plants of this species have various confirmed medicinal applications, such as acaricidal, insecticidal, antioxidant, trypanocidal, anticancer, and antibacterial actions (Betancourt et al., 2019, Damasceno et al., 2018; Leal et al., 2019; Mar et al., 2018; Melo et al., 2020; Raman et al., 2018; Ribeiro et al., 2021; Stashenko et al., 2010).

The extractivism of medicinal plants results in a high risk of genetic variability loss because of fragmentation and anthropogenic intervention in their natural habitats and non-controlled extraction, making it necessary to adopt measures for quantification and conservation of these genetic resources (Costa et al., 2020). Therefore, the genetic diversity analyses of native species are important to define conservation strategies (Gois et al., 2018; Silva et al., 2017), through the selection of plants or populations for germplasm collections, as well as indicating the locations for in situ conservation and minimizing the occurrence of genetic erosions (Melo et al., 2018).

Although L. origanoides has medicinal importance, there is no information available on the genetic variability of this plant in Brazil. The species of plants grow naturally in arid and semiarid regions, and its populations cover a large area of the Northeast region of Brazil (O’Leary et al., 2012), including the state of Bahia, which is a favorable place to conduct the initial research on genetic diversity, to obtain data relevant for the conservation of the species (Silva et al., 2017).

Inter-Simple Sequence Repeat (ISSR) are molecular markers that have been useful for diversity genetic analysis of several medicinal plant species (Costa et al., 2020; Hadipour et al., 2020; White et al., 2018), including L. origanoides (Martínez-Natarén et al., 2014; Suarez et al., 2008; Vega-Vela; Delgado-Ávila; Chacón-Sánchez, 2013). Therefore, the present study was aimed to evaluate the interpopulation genetic diversity levels and distribution of L. origanoides populations occurring in the state of Bahia and Pernambuco, Brazil, using ISSR molecular markers, as well as generating data to assist the species germplasm conservation in the region.

MATERIAL AND METHODS

Plant material

A total of 18 natural populations of L. origanoides occurring in the states of Bahia and Pernambuco, Northeast region of Brazil, were collected from areas of Caatinga, Atlantic Forest, and in transition areas between these biomes (Table 1) in highly anthropized environments. The samples of young leaves were collected from 270 plants (15 of each population). The sampled plants were at least 5 meters (m) apart from each other to avoid collecting the plant material from clones originating from the vegetative propagation of species.

Table 1:
Population abbreviation, municipality, geographical coordinates, and altitude (m) of the locations of 18 L. origanoides Kunth. populations from the states of Bahia (BA) and Pernambuco (PE), Brazil.

Abbreviation	Municipality-State	Latitude and Longitude	Altitude
JEQ	Jequié-BA	13°45’54.0”S. 40°03’28.6”W	346
NIT	Nova Itarana-BA	12°58’22.0”S. 39°56’05.6”W	526
STE	Santa Terezinha-BA	12°35’46.8”S. 39°32’14.8”W	140
UTI	Utinga-BA	12°04’54”S. 41°05’40”W	863
PAL	Palmeiras-BA	12°26’47.7”S. 41°29’12.6”W	809
MCH	Morro do Chapéu-BA	11°36’19.5”S. 40°59’38.3”W	941
MUC	Mucugê-BA	12°59’42.3”S. 41°23’08.6”W	975
RCO	Rio de Contas-BA	13°28’53.8”S. 41°51’47.3”W	1065
JAG	Jaguarari-BA	10°05’20.4”S. 40°13’58”W	543
SSE	Sento Sé-BA	09°44’45”S. 41°53’06”W	400
SBA	Santa Bárbara-BA	12°01’04.5”S. 38°58’15.5”W	270
CNO	Casa Nova-BA	09°09’43”S. 40°58’15”W	417
FLO	Floresta-PE	08°41’0.6”S. 38°09’09.1”W	437
TUC	Tucano-BA	11°01’25.5”S. 38°49’23.7”W	354
JER	Jeremoabo-BA	10°13’35.7”S. 38°17’54.4”W	227
QUI	Quixabeira-BA	11°20’03.9”S. 40°07’39.1”W	396
SBR	Santa Brígida-BA	09°50’16.4”S. 38°15’43.9”W	397
SLU	Santaluz-BA	11°12’30.4”S. 39°24’50.0”W	348

The fertile branches were also collected from each population for taxonomic identification, and exsiccates were housed in the Herbarium of the State University of Feira de Santana. The shortest distance between populations was 44.22 km (Jeremoabo and Santa Brígida), whereas the longest distance was 608.41 km (Jequié and Floresta).

DNA extraction and amplification

The leaf samples for genetic analysis were kept in cetyltrimethylammonium bromide (CTAB) gel (35% NaCl₂ and 3% CTAB) (Doyle; Doyle, 1987) at the time of collection and were stored in it till the DNA extraction process.

The genomic DNA was extracted according to Doyle and Doyle protocol (1987) and rescaled for 1-mL tubes for the stored samples. The tests were performed to verify polymorphisms using 13 primers. Among them, 9 primers showed good electrophoretic standards and polymorphism for the species and were selected for further analyses (Table 2). The DNA was amplified through Polymerase Chain Reaction (PCR), according to Wolfe et al. (1998) modified protocol, and using the TopTaq Master Mix Kit (Qiagen, Hilden, Germany). The reaction was performed employing the Esco Swift Max Pro thermal cycler (Esco Global, Portland, USA), and the same protocol was used for all primers.

Table 2:
Name, sequence, annealing temperature (°C), and the number of polymorphic bands of primers selected for the analysis.

Name	Sequence	Annealing temperature (°C)	Number of polymorphic bands
Manny	(CAC)4-RC	51.7	14
Jhon	(AG)7-YC	46.9	15
ISSR6	(AG)8-YT	50.2	18
ISSR7	(AG)8-YC	50.2	16
Goofy	(GT)7-YG	49.0	14
Chris	(CA)7-YG	49.6	16
ISSR899	(CA)6-RG	48.6	15
MAO	(CTC)4-RC	50.9	14
OMAR	(GAG)4-RC	49.9	13

The amplified PCR products were resolved on 2.0% agarose gels in Sodium Borate buffer (SB 1X) along with 100 base-pair markers. The gels were stained with 10% ethidium bromide solution for approximately one hour, followed by documentation in the Spectroline UV transilluminator (Fisher Scientific, Waltham, USA).

Data analysis

The GelCompar II 5.0 (Applied Maths NV, Sint-Martens-Latem, Belgium) was used to analyze the gels and generate a binary matrix with values of zero (absence), one (presence) for the data obtained for each locus, and -1 (or -9, depending on the program used for the analyses) for missing data.

The binary matrix was used to estimate the parameters of genetic diversity, including the number and percentage of polymorphic loci, Nei’s diversity index, Shannon diversity index, and genetic distance between populations. The analysis of molecular variance (AMOVA) and analysis of the correlation between matrices of genetic and geographical distances was used to evaluate the genetic structuring of populations through the Mantel test. In addition, Popgene 1.32 (Yeh; Yang; Boyle, 1997) and GenAlEx 6.5 (Peakall; Smouse, 2011) were also used.

To estimate the genetic pool through the correlation of allelic frequencies within populations, Structure 2.3.3 (Printchard; Stephens; Donnelly, 2000) was used for the genetic data analysis using the Bayesian method. Furthermore, Evanno’s (2005) correction method was used to establish the best attribution peak (K), and for each attribution peak, 1000 runs were performed. AFLPsurv 1.0 (Vekemans, 2002) and Phylip 3.69 (Felsenstein, 2011) were used for the analyses using Nei’s non-biased matrix of genetic distance, and the Neighbor-Joining grouping method with bootstrap support (Saitou; Nei, 1987). A dendrogram was developed and analyzed using the FigTree 1.2.2 (Rambaut, 2009).

RESULTS AND DISCUSSION

Genetic diversity

A total of 135 loci were obtained, with an average of 15 bands per primer. According to Colombo et al. (1998), an average quantity of 50 to 100 polymorphic loci is required for a secure evaluation using dominant markers such as ISSR. Several studies on L. origanoides using ISSR markers have shown similar numbers of polymorphic loci (Vargas-Mendonça et al., 2016; Vega-Vela et al., 2013). Thus, considering the individual populations, the average percentage of polymorphic bands was 60.08% (Table 3), and similar results (60.9%) were found for L. origanoides by Martínez-Natarén et al. (2014).

Table 3:
Number of polymorphic loci (NL _p ), percentage of polymorphic loci (% L _p ), Nei’s diversity index (NDI), Shannon diversity index (SDI), exclusive locus (EL), and genetic group (GG) in 18 populations of L. origanoides Kunth.

Population	NLp	% Lp	NDI	SDI	EL	GG
JEQ	84	57.78	0.182	0.281	0	1
NIT	90	64.44	0.185	0.290	0	1
STE	90	63.70	0.170	0.269	0	1
SBA	79	54.07	0.169	0.260	0	1
QUI	88	61.48	0.199	0.304	0	1
SLU	82	58.52	0.185	0.284	0	1
UTI	99	68.89	0.226	0.343	0	2
PAL	94	65.19	0.211	0.322	0	2
MCH	86	59.26	0.188	0.288	0	2
MUC	96	65.93	0.207	0.317	1	2
RCO	99	71.11	0.237	0.359	0	2
JAG	96	65.19	0.214	0.325	1	3
SSE	89	58.52	0.207	0.309	0	3
CNO	81	54.07	0.180	0.272	0	3
FLO	78	51.11	0.162	0.247	0	4
TUC	81	54.07	0.175	0.266	0	4
JER	80	53.33	0.163	0.251	0	4
SBR	80	54.81	0.186	0.280	1	4
Mean	87.33	60.08	0.191	0.292	-	-

Regarding genetic diversity variables, Nei’s diversity index in each population ranged from 0.162 (FLO) to 0.237 (RCO), with a mean of 0.191 (Table 3). The lowest Shannon diversity index (I) was found for FLO (0.247) and the highest for RCO (0.359), with a mean of 0.292 (Table 3). Thus, FLO showed the lowest genetic diversity, and RCO presented the highest.

The studies on the diversity of L. origanoides demonstrated different results. Suarez et al. (2008) and Vega-Vela et al. (2013) used the same molecular marker and found higher genetic diversity for the species with high Nei’s diversity index, 0.453 and 0.367, respectively. However, similar studies presented a lower Nei’s diversity index. For instance, Vargas-Mendoza et al. (2016) found a mean of 0.110 for 22 populations of L. origanoides, as well as Martínez-Natarén et al. (2014) found Nei’s diversity index of 0.170 for 14 populations.

The genetic diversity found within populations can be correlated to environmental factors, such as relief and vegetation. The mountainous areas with diverse phytophysiognomies, such as Chapada Diamantina, have populations with higher genetic diversity (UTI, PAL, MCH, MUC, and RCO). According to Salimena et al. (2002), Chapada Diamantina is one of the diverse centers of Lippia L. in Brazil. The flatter reliefs and more uniform vegetation are found as the distance from this region increases; therefore, populations outside this region presented lower genetic diversity. The differences in relief and vegetation affecting the genetic diversity of L. origanoides were also found in Colombia (Vega-Vela; Sanchez, 2012).

According to Yang et al. (2012) and Gois et al. (2018), the occurrence of exclusive loci or private alleles indicates different populations. However, in the current study, the occurrence of private alleles was low; only the populations MUC, JAG, and SBR presented them (one each) (Table 2). Moreover, according to the distance between populations based on Nei’s matrix of genetic identity (1978), the highest genetic similarity was found between the populations CNO and JAG (0.933), which were 112.44 km from each other. The lowest genetic similarity was found between JEQ and FLO (0.797), which were 608.41 km distant from each other. However, the results of the Mantel test showed no significant correlation between geographical and genetic distance matrices (r = 0.0005, p = 0.384). The report of Fajardo et al. (2018) demonstrated that these results indicate the fragmentation and spatial isolation of the analyzed populations are relatively new events and did not form standards of genetic geographical isolation.

Population genetic structure

Since above 25% of the variability between populations denotes strong structuring, the Analysis of Molecular Variance (AMOVA) showed 69% of the genetic variability within populations and 31% between them, indicating the high genetic structuring. The genetic distance between populations indicates the genetic difference between populations, which can be classified as low (0.05 to 0.15), moderate (0.15 to 0.25), or high (>0.25) (Wright, 1978). The mean genetic distance between populations was obtained at 0.19, denoting a moderate difference between populations. Moreover, various studies on L. origanoides found moderate structuring between populations (Vega-Vela; Sanchéz, 2012; Vega-Vela et al., 2013).

Organization of genetic structure

The analysis of genetic structure by the Bayesian method pointed out the formation of four genetic groups (K = 4) based on the highest ᴧK value (Figure 1).

Figure 1:
Values of Delta K according to the correction of Evanno (2005), showing participation peaks (K) for 18 populations of L. origanoides Kunth. (Highest K value = 4; and the other peaks: K = 2, K = 8, and K = 12).

According to the highest peak (K = 4), the populations were organized into four groups (Figure 2). The populations JEQ, NIT, STE, SBA, QUI, and SLU formed the first group (yellow); UTI, PAL, MCH, MUC, and RCO formed the second group (green); JAG, SSE, and CNO formed the third group (blue); and FLO, TUC, JER, and SBR formed the fourth group (red) (Figure 2). The analysis indicated that the highest mixing level occurred for the populations JEQ, TUC, and SBR.

Figure 2:
Proportions of Bayesian mixture, generated from the Structure program data for 18 populations of L. origanoides Kunth. collected in the states of Bahia and Pernambuco, Brazil. 1 = JEQ; 2 = NIT; 3 = STE; 4 = UTI; 5 = PAL; 6 = MCH; 7 = MUC; 8 = RCO; 9 = JAG; 10 = SSE; 11 = SBA; 12 = CNO; 13 = FLO; 14 = TUC; 15 = JER; 16 = QUI; 17 = SBR; 18 = SLU.

The Neighbor-Joining dendrogram (Figure 3) also showed the formation of four clades, with similar arrangements to the one resulting from the Structure analysis. Among the four groups formed in the dendrogram, three (group 1, group 3, and group 4) presented low support values (less than 500). In genetic diversity studies, the occurrence of low support values is common in dendrograms originated by clustering methods, especially in the innermost nodes, as a consequence of instabilities in the chosen algorithm. However, the congruence with the result obtained in the Structure analysis indicates the plausibility of separating evaluated populations into four groups.

Figure 3:
Neighbor-Joining dendrogram based on the Nei’s matrix of genetic distance for 18 populations of L. origanoides Kunth., denoting the formation of four groups. Group 1: POP04 = UTI; POP05 = PAL; POP06 = MCH; POP07 = MUC; POP08 = RCO. Group 2: POP09 = JAG; POP010 = SSE; POP012 = CNO. Group 3: POP01 = JEQ; POP02 = NIT; POP03 = STE; POP011 = SBA; POP016 = QUI; POP018 = SLU. Group 4: POP013 = FLO; POP014 = TUC; POP015 = JER; POP017 = SBR.

The MUC, UTI, MCH, PAL, and RCO populations formed the first clade, and these populations are from the Chapada Diamantina region, presenting the highest genetic diversity indexes. The SSE, JAG, and CNO populations were clustered as the second clade, and these populations are from the northern state of Bahia, and the two latter are in a subgroup (Figure 2). The third clade was formed by three subgroups; first by SBA and QUI (Figure 3); second by JEQ and NIT; and third by SLU and STE. Moreover, these populations are within and nearby the ecotone between the Caatinga and Atlantic Forest biomes. SBR, FLO, TUC, and JER, populations from the northeastern state of Bahia and near the Pernambuco border, composed the fourth clade, and these populations presented the lowest genetic diversity, and the latter two populations formed a subgroup (Figure 2).

Although some populations close to each other remained in the same group, the geographical distance did not affect the formation of these groups, according to the Mantel test. Therefore, these groups represent the genetic diversity of L. origanoides created by various environmental factors, such as relief, climate, and vegetation, indicating adaptive genetic differentiations (Coop et al., 2010). The obtained genetic structuring level in this study suggests the need for adequate planning for L. origanoides germplasm collections, considering the genetic diversity distribution between the studied populations for better conservation of the genetic variability (Dardengo, et al., 2021).

CONCLUSIONS

The application of ISSR molecular markers facilitated the understanding of genetic diversity as well the genetic structuring level of species populations. The populations of L. origanoides had a mean value of 0.292 for the Shannon diversity index and 0.191 for the Nei’s diversity index, with populations located in Chapada Diamantina showing the highest values. There was a high genetic structure among populations (31%). Moreover, the cluster analysis indicated the separation of populations into four genetic groups. The collection of L. origanoides samples should comprise germplasm from populations belonging to different genetic groups. The priority area to collect L. origanoides germplasm is the Chapada Diamantina region.

AUTHOR CONTRIBUTION

Conceptual idea: Feijó, E.V.R.S.; Berg, C.V.D.; Oliveira, L.M.; Methodology design: Feijó, E.V.R.S.; Berg, C.V.D.; Oliveira, L.M.; Data collection: Feijó, E.V.R.S.; Barbosa, B.L.; Oliveira, L.M.; Data analysis and interpretation: Feijó, E.V.R.S.; Barbosa, B.L.; Berg, C.V.D.; Writing and editing: Feijó, E.V.R.S.; Barbosa, B.L.; Berg, C.V.D.; Oliveira, L.M.

REFERENCES

• BETANCOURT, L. et al. Effects of Colombian oregano essential oil (Lippia origanoides Kunth) and Eimeria species on broiler production and cecal microbiota. Poultry Science, 98(10):4777-4786, 2019.
• COLOMBO, C. et al Genetic diversity characterization of cassava cultivars (Manihot esculenta Crantz).: I) RAPD markers. Genetics and Molecular Biology, 21(1):105-113, 1998.
• COSTA, R. B. et al. Diversidade genética e estrutura populacional deCroton urucuranaBaill. (Euphorbiaceae) no Brasil central por marcadores ISSR. Genetics and Evolutionary Biology, 43:831-838, 2020.
• COOP, G. et al. Using environmental correlations to identify loci underlying local adaptation. Genetics, 185(4):1411-1423, 2010.
• DAMASCENO, E. T. S. et al. Lippia origanoideskunth. essential oil loaded in nanogel based on the chitosan and ρ-coumaric acid: Encapsulation efficiency and antioxidant activity. Industrial Crops and Products, 125:85-94, 2018.
• DARDENGO, J. F. E. et al. Structure and genetic diversity of Theobroma speciosum(Malvaceae) and implications for Brazilian Amazon conservation. Rodriguésia, 72:e02022018, 2021.
• DOYLE, J. J.; DOYLE, J. L. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochemical Bulletin, 19(1):11-15, 1987.
• EVANNO, G. et al. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Molecular Ecology, 14:2611-2620, 2005.
• FAJARDO, C. G. et al. Genetic diversity in natural populations of Hancornia speciosaGomes: Implications for conservation of genetic resources. Ciência e Agrotecnologia, 42(6):623-630, 2018.
• FELSENSTEIN, J. Phylip: Phylogeny inference package version 3.69. Distributed by the author. Department of Genome Sciences, University of Washington, Seattle available from, 2011. Available in: <Available in: https://evolution.genetics.washington.edu/phylip.html >. Access in: May, 12, 2022.
  » https://evolution.genetics.washington.edu/phylip.html
• GOIS, I. B. et al. Variabilidade genética em populações naturais de Cassia grandis L. f. Floresta e Ambiente, 25(4):1-10, 2018.
• HADIPOUR, M. et al. Genetic diversity and species differentiation of the medicinal plant Persian poppy (Papaver bracteatum L.) using AFLP and ISSR markers. Ecological Genetics and Genomics, 16:100058, 2020.
• LEAL, A. L. A. B. et al. Antimicrobial action of essential oil of Lippia origanoides H.B.K. Journal of Clinical Microbiology Biochemical Technology, 5(1):7-12, 2019.
• MAR, J. M. Lippia origanoidesessential oil: An efficient alternative to controlAedes aegypti, Tetranychus urticaeandCerataphis lataniae Industrial Crops and Products , 111:292-297, 2018.
• MARTÍNEZ-NATARÉN, D. A. et al. Genetic diversity and genetic structure in wild populations of Mexican oregano (Lippia graveolens H.B.K.) and its relationship with the chemical composition of the essential oil. Plant Systematics and Evolution, 300:535-547, 2014.
• MELO, M. F. V. et al. Forest inventory and the genetic diversity of the remaining fragment ofHymenaea courbarilL. Ciência e Agrotecnologia , 42(5):491-500, 2018.
• MELO, A. R. B. et al. Lippia sidoides, andLippia origanoidesessential oils affect the viability, motility, and ultrastructure ofTrypanosoma cruzi Micron, 129:102781, 2020.
• O’LEARY, N. et al. Species delimitation in Lippia section Goniostachyum (Verbenaceae) using the phylogenetic species concept. Botanical Journal of the Linnean Society, 170(2):197-219, 2012.
• PEAKALL, R.; SMOUSE P. E. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics, 28(19):2537-2539, 2012.
• PRITCHARD, J.; STEPHENS, M.; DONNELLY, P. Inference of population structure using multilocus genotype data. Genetics , 155(2):945-959, 2000.
• RAMBAUT, A. Tree figure drawing tool, version 1.3.1. Edinburgh: Institute o Evolutionary Biology, 2009. Available in: <Available in: http://tree.bio.ed.ac.uk/software/figtree/ >. Access in: May, 12, 2022.
  » http://tree.bio.ed.ac.uk/software/figtree/
• RAMAN, V. et al. Proteomic analysis reveals that an extract of the plantLippia origanoidessuppresses mitochondrial metabolism in triple-negative breast cancer cells. Journal of Proteome Research, 17 (10):3370-3383, 2018.
• RIBEIRO, F. P. et al. Composição química e atividade antibacteriana do óleo essencial deLippia origanoideskunth da floresta nacional de carajás, Brasil. Medicina Complementar e Alternativa Baseada em Evidências, 2021:1-8, 2021.
• SAITOU, N.; NEI, M. The neighbor-joining method: A new method for reconstructing phylogenetics trees. Molecular Biology and Evolution, 4(4):406-425, 1987.
• SALIMENA, F. R. G. Novos sinônimos e tipificação em Lippiasect. rhodolippia (Verbenaceae). Darwiniana, 40(1-4):121-125, 2002.
• SILVA, A. V. C. et al. Caracterização de árvores, frutos e diversidade genética em populações naturais de mangaba. Ciência e Agrotecnologia , 41(3):255-262, 2017.
• SUAREZ, A. G.; CASTILLO, G.; CHACON, M. I. Genetic diversity and spatial genetic structure within a population of an aromatic shrub, Lippia origanoides (Verbenaceae), in the Chicamocha Canyon, northeastern Colombia. Genetics Reserch, 90:455-465, 2008.
• STASHENKO, E. E. et al. Lippia origanoides chemotype differentiation based on essential oil GC-MS and principal component analysis. Journal of Separation Science, 33(1):93-103, 2010.
• TRINDADE, S. C. et al. Atividade antimicrobiana dos extratos metanólicos de diferentes espécies do gênero Lippia Research, Society and Development, 10(9):e22610918051, 2021.
• VARGAS-MENDOZA, C. F. et al. Natural selection under contrasting ecological conditions in the aromatic plant Lippia graveolens (H.B.K., Verbenaceae). Plant Systematics and Evolution , 302:275-289, 2016.
• VEGA-VELA, N. E.; CHACÓN-SÁNCHEZ, M. I. Genetic structure along an altitudinal gradient in Lippia origanoides, a promising aromatic plant species restricted to semiarid areas in northern South America. Ecology and Evolution, 2(11):2669-2681, 2012.
• VEGA-VELA, N. E. et al. Genetic structure and essential oil diversity of the aromatic shrub Lippia origanoides Kunth. (Verbenaceae) in two populations from northern Colombia. Agronomía Colombiana, 31(1):7-17, 2013.
• VEKEMANS, X. AFLP-surv version 1.0. Belgium: Laboratoire de génétique et ecologie végétale. Université Libre de Bruxelles, 2002. Available in: <Available in: https://www2.ulb.ac.be/sciences/lagev/aflp-surv.html >. Access in: May, 12, 2022.
  » https://www2.ulb.ac.be/sciences/lagev/aflp-surv.html
• WHITE, L. A. S. et al. Genetic diversity of a native population of Myrcia ovata (Myrtaceae) using ISSR molecular markers. Genetics and Molecular Research, 17(3):1-11, 2018.
• WRIGHT, S. Evolution and the genetics of populations. Chicago, Illinois, United States: University of Chicago Press, 1978. 590p.
• WOLFE, A. D. et al. Assessing hybridization in natural populations of Penstemon (Scrophulariaceae) using hypervariable Inter simple sequence repeat (ISSR) bands. Molecular Ecology , 7(9):1107-1125, 1998.
• YANG, H. Q. et al. Genetic diversity and differentiation of Dendrocalamus membranaceus (Poaceae: Bambusoideae), a declining bamboo species in Yunnan, China, as based on Inter simple sequence repeat (ISSR) analysis. International Journal of Molecular Sciences, 13(4):4446-4457, 2012.
• YEH, F. C.; YANG, R.; BOYLE, T. POPGENE 1.32: Population genetic analysis. Free computer program distributed by the authors. 1999. Available in: <Available in: https://download.cnet.com/Popgene/3000-2054_4-75328340.html >. Access in: May, 12, 2022.
  » https://download.cnet.com/Popgene/3000-2054_4-75328340.html

Publication Dates

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

History

• Received
  16 Jan 2022
• Accepted
  11 May 2022