Genetic diversity of long-established populations of <i>Elaeis guineensis</i> jacquin (Arecaceae)

This study aimed to estimate the genetic diversity of three Elaeis guineensis populations in Rio Grande do Norte state, as well as to verify the decreases in effective population size. The population with the highest polymorphism was MAT (Mata) with+ 57 loci (72%), followed by RIA (Riacho) with 54 loci (68%) and HOR (Horta) with 34 loci (43.03%). The RIA population was shown to be the most genetically diverse, with Nei (h = 0.28) and Shannon (I = 0.41) diversity indices. There was high genetic differentiation among populations (AMOVA, analysis of molecular variance = 42%), which was separated into three distinct genetic groups according to a Bayesian analysis. There was a significant population decrease (P < 0.05) for the HOR population in the IAM (infinite allele model) and SMM (stepwise mutation model), and for the RIA population in the IAM. The data obtained in this study may support ex-situ conservation projects for Elaeis guineensis, contributing to the selection of genotypes and their sustainable use.

Index terms
Molecular Marker; Bottleneck; ISSR; Conservation

Authorship

Kyvia Pontes Teixeira das Chagas

MSc in Forestry Sciences, Federal University of Rio Grande do Norte, Macaíba, Rio Grande do Norte, Brazil. E-mail: kyviapontes@gmail.com Federal University of Rio Grande do NorteBrasilMacaíba, RN, Brasil MSc in Forestry Sciences, Federal University of Rio Grande do Norte, Macaíba, Rio Grande do Norte, Brazil. E-mail: kyviapontes@gmail.com

http://orcid.org/0000-0003-1361-3204

Ageu da Silva Monteiro Freire

Forest Engineer, Federal University of Rio Grande do Norte, Macaíba, Rio Grande do Norte, Brazil. E-mail: ageufreire@hotmail.com Federal University of Rio Grande do NorteBrasilMacaíba, RN, Brasil Forest Engineer, Federal University of Rio Grande do Norte, Macaíba, Rio Grande do Norte, Brazil. E-mail: ageufreire@hotmail.com

http://orcid.org/0000-0002-5364-0859

Luciana Gomes Pinheiro

MSc in Forestry Sciences, Federal University of Rio Grande do Norte, Macaíba, Rio Grande do Norte, Brazil. E-mail: luciana.gpinheiro@yahoo.com.br Federal University of Rio Grande do NorteBrasilMacaíba, RN, Brasil MSc in Forestry Sciences, Federal University of Rio Grande do Norte, Macaíba, Rio Grande do Norte, Brazil. E-mail: luciana.gpinheiro@yahoo.com.br

http://orcid.org/0000-0002-9115-4210

Cristiane Gouvêa Fajardo

DSc of Ecology, Federal University of Rio Grande do Norte, Macaíba, Rio Grande do Norte, Brazil. E-mail:genegoista00@gmail.com Federal University of Rio Grande do NorteBrasilMacaíba, RN, Brasil DSc of Ecology, Federal University of Rio Grande do Norte, Macaíba, Rio Grande do Norte, Brazil. E-mail:genegoista00@gmail.com

http://orcid.org/0000-0001-6202-7143

Fábio de Almeida Vieira

DSc of Forestry Engineering, Federal University of Rio Grande do Norte, Macaíba, Rio Grande do Norte, Brazil. E-mail: vieirafa@gmail.com Federal University of Rio Grande do NorteBrasilMacaíba, RN, Brasil DSc of Forestry Engineering, Federal University of Rio Grande do Norte, Macaíba, Rio Grande do Norte, Brazil. E-mail: vieirafa@gmail.com

http://orcid.org/0000-0003-3347-255X

SCIMAGO INSTITUTIONS RANKINGS

Figures | Tables | Formulas

Figures (2)
Tables (6)
Formulas (1)

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Figure 1
UPGMA dendrogram based on Nei’s genetic identity between three Elaeis guineensis populations

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Figure 2
The genotypic proportion between the three Elaeis guineensis populations showing K = 3. The populations are bounded by the vertical bars. The three different colours indicate the three distinct groups.

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Table 1
Population references, geographic coordinates, sample size (n) and anthropogenic pressure scale of the three Elaeis guineensis populations.

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Table 2
Summary of ISSR primers used, the nucleotide sequence, number of loci, and PIC value.

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Table 3
Measures of genetic diversity in Elaeis guineensis populations.

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Table 4
Estimates of the genetic distances of Nei (1978) below the diagonal, and geographic distance (Km) above the diagonal between the Elaeis guineensis populations.

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Table 5
Analysis of molecular variance (AMOVA) among populations and between individuals within of the Elaeis guineensis populations.

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Table 6
Bottleneck tests between mutation and genetic drift for the Elaeis guineensis populations in the IAM and SMM models.

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Figure 1 UPGMA dendrogram based on Nei’s genetic identity between three Elaeis guineensis populations

Figure 2 The genotypic proportion between the three Elaeis guineensis populations showing K = 3. The populations are bounded by the vertical bars. The three different colours indicate the three distinct groups.

Table 1 Population references, geographic coordinates, sample size (n) and anthropogenic pressure scale of the three Elaeis guineensis populations.

Population	Lat. /Long.	n	Vegetation	Soil use	Environment	Anthropogenic pressure
HOR (Horta)	5°52'58'' S / 35°21'47'' O	13	Riparian forest and open vegetation	Growing vegetables and logging	Declivity and high humidity	4
MAT (Mata)	5°53'28'' S / 35°21'10'' O	15	Atlantic forest fragment edge	Agricultural use and trails	High humidity and organic matter content	3
RIA (Riacho)	5°53'06'' S / 35°21'42'' O	15	Closed vegetation and ciliary forest	Roads	River course, rocks and declivities	2

Table 2 Summary of ISSR primers used, the nucleotide sequence, number of loci, and PIC value.

ISSR primers	Sequence (5' - 3')	Loci	PIC
UBC 807 (AG)8-T	AGA GAG AGA GAG AGA GT	15	0.49
UBC 822 (TC)8-A	TCT CTC TCT CTC TCT CA	10	0.50
UBC 825 (AC)8-T	ACA CAC ACA CAC ACA CT	11	0.50
UBC 826 (AC)8C	ACA CAC ACA CAC ACA CC	15	0.50
UBC 827 (AC)8G	ACA CAC ACA CAC ACA CG	14	0.48
UBC 857 (AC)8-YG	ACA CAC ACA CAC ACA CYG	14	0.49
Average		13	0.49

^{R =}
purine (A ou G)
^{Y =}
pyrimidine (C ou T)

Table 3 Measures of genetic diversity in Elaeis guineensis populations.

Populations	polymorphic loci / %	Na	Ne	h	I
HOR	34 / 43%	1.43±0.01	1.29±0.06	0.17±0.04 b	0.25±0.05 b
MAT	57 / 72%	1.72±0.06	1.45±0.05	0.27±0.03 a	0.40±0.04 a
RIA	54 / 68%	1.68±0.06	1.45±0.05	0.28±0.03 a	0.41±0.04 a
Average	48 / 61%	1.61	1.40	0.24	0.35
Total	78 / 99%	1.99±0.01	1.66±0.03	0.38±0.02	0.552±0.02

^*
Polymorphic loci, percentage of polymorphic loci (%), number of alleles (Na), effective number of alleles (Ne), Nei’s index (h), and Shannon index (I). The values represent the mean ± standard error. The averages followed by the same letter in the column do not differ significantly from each other by the Tukey Test at 5% probability.

Table 4 Estimates of the genetic distances of Nei (1978) below the diagonal, and geographic distance (Km) above the diagonal between the Elaeis guineensis populations.

Populations	HOR	MAT	RIA
HOR	0	1.45	0.39
MAT	0.40	0	1.06
RIA	0.25	0.24	0

Table 5 Analysis of molecular variance (AMOVA) among populations and between individuals within of the Elaeis guineensis populations.

Source of variation	df	SS	Variance component	Percentage of variation	P
Among populations	2	203.784	6.51	42%	< 0.00*
Within populations	40	354.123	8.85	58%
Total	42	557.91	15.36	100%
Genetic differentiation Fst:	0.42

^*
df: degrees of freedom; SS: sum of squared deviations; Fst: Genetic differentiation. P: probability.

Table 6 Bottleneck tests between mutation and genetic drift for the Elaeis guineensis populations in the IAM and SMM models.

Populations		IAM				SMM
Populations	n	He		P	n	He	P
HOR	34.75	27	0.05*		43.50	27	0.00*
MAT	37.26	44	0.08		44.14	42	0.35
RIA	37.43	50	0.00*		44.52	47	0.33

^*
n = expected number of loci with excess heterozygosity under the respective model; He = number of loci with excess heterozygosity; P = probability; * = signi?cant at 5% probability; IAM = infinite allele model and SMM = stepwise mutation model.

{PIC}_{i} =1- \sum_{j=1}^{n} P_{ij}^{2}

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Métricas

Genetic diversity of long-established populations of <i>Elaeis guineensis</i> jacquin (Arecaceae)

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Mensagem

[TFN0201] ^{R =}
purine (A ou G)

[TFN0202] ^{Y =}
pyrimidine (C ou T)