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Crop Science • Sci. agric. (Piracicaba, Braz.) 79 (3) • 2022 • https://doi.org/10.1590/1678-992X-2020-0308 linkcopy

Open-access Molecular diversity and ecogeographic distribution of Algerian wild olives (Olea europaea subsp. europaea var. sylvestris)

AuthorshipSCIMAGO INSTITUTIONS RANKINGS

    ABSTRACT:

    Olive is one of the most important crops in the Mediterranean Basin, because of the olive oil economic value and its role in characterization of the rural landscape. The strong influence of climatic changes on the modern agriculture and the availability of a large source of genetic variability pose as crucial future challenges. Therefore, safeguarding olive genetic resources becomes fundamental, not only in cultivated forms in ex situ collections, but also in terms of wild trees in their natural habitat. In this study, 174 samples of oleaster collected in different parts of Algeria were analyzed by 16 nuclear Simple Sequence Repeats (SSRs). The analysis showed a huge genetic variability in the oleaster, and the STRUCTURE and Principal Coordinate Analyses (PCoA) highlighted clusterization of genotypes according to their geographic origin and bioclimatic conditions. Genotypes adapted to harsh climatic conditions were identified, which could be useful to enrich the panel of olive genotypes for breeding purposes and preserve genetic diversity of this species from erosion risks.

    Keywords: SSR; Algeria; Oleaster; biodiversity; bioclimate

    Introduction

    Olive (Olea europaea L.) is one of the most ancient and socio–economically important trees of the Mediterranean Basin. The subspecies europaea has two botanical varieties: var. europaea, which corresponds to cultivated olive, and var. sylvestris, the wild form, also known as Oleaster (Green, 2002). Olive domestication dates back to approximately 6000 years ago in the Middle East of the Mediterranean Basin (Zohary and Hopf, 1994; Vossen, 2007; Besnard et al., 2018), where genetic studies support a major domestication event followed by the spread and secondary diversification of the crop in westernmost regions of the Mediterranean Basin (Díez et al., 2015; Besnard et al., 2001; D’Agostino et al., 2018). Even if selection of cultivars were associated to limited erosion of genetic diversity due to admixture between different genepools, wild forms can still be considered an important reserve of genes for adaptability and favorable agronomic traits (Hannachi et al., 2009; Besnard et al., 2013; Miazzi et al., 2020). Due to the great resistance to wind, drought, and salinity, wild forms play an important role in the preservation of Mediterranean ecosystems (Belaj et al., 2007). In addition, although they have low weight and low oil content fruit, some favorable features could be introduced into the cultivated varieties (Díaz–Rueda et al., 2020; León et al., 2018). For instance, wild olive can represent an interesting source of genes for resistance to diseases, such as the Olive Quick Decline Syndrome (OQDS) (Saponari et al., 2019), for which resistant or molecular targets and tolerant genotypes have been identified (Novelli et al., 2019). Nowadays, most olive wild–looking trees are actually feral forms from hybridization events between oleaster and cultivars, while the populations of genuine wild olives remain limited to isolated areas, such as remote areas of North Africa (Lumaret et al., 2004). In Algeria, olive is an important crop cultivated mainly in the northern part of the country, where it is represented by old cultivars poorly characterized (Boucheffa et al., 2017). Studies on Algerian olive genetic diversity focused on the evaluation of the variability distribution in cultivated and wild olives (Abdessemed et al., 2015; Boucheffa et al., 2017) or on the establishment of relationships between O. europaea subspecies (Rubio de Casas et al., 2006). Collected in undisturbed areas of Algeria, the genetic variability of wild olive germplasm has been analyzed using SSR markers to preserve it from the erosion risk and identify enhanced traits for the improvements of cultivated olive.

    Materials and Methods

    Plants material

    We collected 174 wild olive types from their undisturbed natural habitat in 33 provinces of northern Algeria. The sampling sites were selected to represent different microclimatic and soil conditions where the olive tree can grow, from the coastal area to the inner regions of northeastern Algeria. In each sampling site, individual plants were collected and geo–referenced using a Global Positioning System Tracker (Figure 1; Table 1).

    Figure 1
    Map of wild olive sampling sites in 33 provinces of northern Algeria in North Africa. The geographic coordinates of the sampling sites are reported in Table 1. Source:https://www.scribblemaps.com/create/#/lat=36.87962061&lng=40.78125&z=3&t=hybrid).
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    Table 1
    Estimation of ecogeographic parameters. For each sample coordinates, altitude, annual rainfall (Pmm) expressed in millimeter, average of maximum temperature of the hottest month (M °C), average of minimum temperature of the coldest month (m °C), Emberger coefficient (Q2) and the group clustering based on the Structure and dendrogram analysis are indicated.

    For each sample, the following climatic parameters of the collection sites were gathered: altitude, annual rainfall expressed in millimeter (P mm), average of the maximum temperature of the hottest month (M °C), average of the minimum temperature of the coldest month (m °C), Emberger coefficient (Q2) (Emberger, 1930) (National Office of Meteorology, Algeria http://www.aps.dz/en/; http://fr.climate–data.org/). Precipitation and temperature data were corrected according to different altitudes and the pluvio–thermic Emberger coefficient (Q2) was determined according to Bechkri and Khelifi (2017) (Table 1).

    Molecular characterization

    We collected 20 young leaves from different parts of the canopy of 174 olive trees and the leaves were immediately frozen after collection. For genomic DNA extraction, 150 mg of leaves were used following the protocol described by Spadoni et al. (2019). DNA quality and quantity were assessed spectrophotometrically and normalized to 50 ng μL–1.

    Genotypes were analyzed by 16 microsatellite markers (Carriero et al., 2002; Cipriani et al., 2002; De La Rosa et al., 2002; Sefc et al., 2000), considered informative and effective to discriminate olive cultivar (Baldoni et al., 2009). Amplifications were conducted according to Spadoni et al. (2019).

    The amplification of products was detected using the automatic sequencer ABI PRISM 3100 Avant Genetic Analyzer and data were collected with Gene Mapper genotyping software v.5.0, using a size standard.

    Genetic analysis

    The genetic diversity of genotypes was estimated through the following indices: number of alleles (Na), effective number of alleles (Ne), Shannon information index (I), observed (Ho) and expected (He) heterozygosity, and fixation index (F) using the GenAlex software v.6.5. The polymorphic information content (PIC) was calculated by using Cervus v 3.0 to describe the informativeness of each marker. Moreover, Cervus v 3.0 software was used to evaluate the significance of estimates per locus tested by permutations (9,999 replicates). The frequency of null alleles F (null) and departure from Hardy–Weinberg equilibrium (HWE) were tested, applying sequential Bonferroni correction.

    GenAlex v.6.5 was also used to perform the principal coordinate analysis (PCoA) using the Nei's unbiased genetic distance pairwise population matrix. The inter–individual relationship was calculated for the partition of olive samples into specific groupings. The Bayesian clustering algorithm implemented in the STRUCTURE software version 2.3.4 was used to infer the structure of the studied germplasm, assuming 10 genetic clusters (K) and performing 10 independent runs with 100,000 Markov Chain Monte Carlo (MCMC) iterations for each K following a burn–in of 10,000 iterations. The optimal value of K was determined based on the δK test (Evanno et al., 2005) using the STRUCTURE HARVESTER software. Accessions were assigned to defined populations if the value of the corresponding membership coefficient (qi) was higher than 0.6, otherwise, they were considered admixed ancestry. An Unweighted Neighbor–Joining dendrogram was generated in the DARWIN software version 6.0.010 with 1000 bootstraps value for tree construction and the tree was viewed using FigTree 2016–10–04–v1.4.4. Finally, the XLSTAT 2020.5.1 software was used to calculate the Spearman correlation coefficient to assess the correlation between clusterization, obtained by the software STRUCTURE, and ecogeographic parameters.

    Results

    Genetic diversity

    Each of the 174 samples was successfully amplified at 16 SSR loci. We obtained 173 alleles (Na) (average 10.81 alleles per locus), ranging from three for DCA15 to 18 for UDO43. The number of effective alleles (Ne) varied between 1.79 (GAPU45) and 12.74 (DCA16) with a mean value of 6.15. The Shannon information Index (I) ranged from 0.86 (GAPU45) to 2.78 (DCA16). Observed heterozygosity (Ho) ranged from 0.32 (EMOL) to 0.89 (DCA05) while expected heterozygosity (He) ranged from 0.44 (GAPU45) to 0.92 (DCA16), with a mean Fixation Index (F) of 0.11. All microsatellite markers were confirmed as highly polymorphic, with PIC values higher than 0.50 except for DCA15 and GAPU45. Null alleles were detected at a frequency higher than 0.2 only in EMOL and DCA17 loci. The departure from Hardy–Weinberg equilibrium was significant for five of the 16 loci analyzed (Table 2).

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    Table 2
    Genetic diversity indices of 16 SSR markers detected in 174 wild olive samples.

    Genetic relationships

    The PCoA explained 13.47 % and 9.13 % of the total variance for the first (PCo1) and the second (PCo2) principal coordinates, respectively. The PCo1 separated genotypes collected in western Algeria, from the eastern genotypes collected in the provinces of Jijel, Mila and Batna, near the border with Tunisia. The PCo2 divided, further, the Eastern samples collected in the temperate north–eastern provinces of Skikda, Guelma, Constantine, Souk Ahras and Jijel, from genotypes collected in the inner arid provinces of Batna, Biskra, Khenchela, Oum El Bouaghi and Tebessa (Figure 2).

    Figure 2
    Principal coordinates analysis (PCoA). Differentiation between 174 Algerian wild olive genotypes based on 16 polymorphic microsatellite markers.

    Population structure

    The population structure indicated two populations (K = 2) as the best model that fits genotype distributions, followed by K = 3 (Figure 3). At K = 2, two genetic clusters are distinguished. The first gene pool (Gp1) consisted of 78 genotypes, while the second (Gp2) included 86 samples. The Gp1 cluster included samples collected in the Northwest of the country, in particular in a region between Tizi Ouzou and Mascara provinces, although it also included several genotypes from the eastern provinces of Annaba and Mila. However, the Gp2 cluster contained genotypes mainly collected in northeastern Algeria with the exception of few genotypes from Oran, Sidi Bel Abbes, Ain Témouchent, and Tlemcen provinces located near the border with Morocco.

    Figure 3
    Analysis of the genetic structure of 174 wild olive accessions. Bar plot showing clusters inferred by STRUCTURE at K = 2 and K = 3. Each vertical line stands for a single accession assigned to defined populations if the value of the corresponding membership coefficient (qi) was higher than 0.6. The samples were sorted according to their geographic origin from West to East.

    At K = 3, the genetic cluster Gp1 had approximately the same composition as at K = 2, while the Gp2 cluster splits up into two sub–groups: Gp2.1, which included mainly genotypes from the northeastern provinces of Skikda, Guelma, Souk Ahras, and Jijel (except for the samples MILA–DB_2, BEJAIA–OG, AIN TÉMOUCHENT–AET and RELIZANE–Z); Gp2.2, which encompassed the genotypes collected in the inner mountainous provinces of Batna, Biskra and Khenchela (except for the samples M’SILA–HD, BORDJBOURARRERIDJ–DEZ and ORAN–S).

    The admixed group included 25 genotypes collected in the inner provinces of the northern belt of the country (RELIZANE–EK_1, M’SILA–D, BEJAIA–K, SETIF–BO BATNA–SDES, OUMELBOUAGHI–DL, CONSTANTINE–BH_1, etc.) (Table 1).

    The Unweighted Neighbor–Joining dendrogram showed four clusters. Three were compatible with clusters obtained by the population structure analysis and the fourth group included only nine samples (Figure 4). In particular, Cluster I contained 76 genotypes and reflected cluster Gp1 composition obtained from Structure. This group included main samples collected in the central and northwestern provinces with the exception of Annaba (Far East). Cluster II contained 34 samples, matching Gp2.1 (Northeast) except for six genotypes (AINTEMOUCHENT–CE, RELIZANE–Z, TIPAZA–PM, TIPAZA–PC, LAGHOUAT–DUAD_1 and TLEMCEN–R). Cluster III (55 genotypes) included the samples collected in the southeastern provinces of Batna, Biskra and Khenchela, matching Gp2.2. Finally, Cluster IV contained nine samples, all from the northeastern part of Algeria (Table 1).

    Figure 4
    Unweighted Neighbor–Joining dendrogram generated in DARWIN software version 6.0.010 showing clusterization of the samples analyzed.

    To analyze the possible correlation between the genetic structure of 174 wild olive genotypes and bioclimatic conditions, five ecogeographic parameters were used as described in the Materials and Methods section (Table 1).

    The results revealed high heterogeneity of samples within the subpopulation Gp1, while the subpopulation Gp2.1 included mostly samples growing at altitude < 600 m, and subject to abundant rains (p > 600 mm), with a temperature range between 4 °C and 30 °C, and an Emberger coefficient > 100 for 66 % of the samples. Conversely, the subpopulation Gp2.2 included genotypes mostly collected at altitude > 600 m, p < 600 mm, M > 30 °C, m < 4 °C. Moreover, the Q2 value was < 100 for all the samples (Figure 5A). The Spearman correlation coefficient was calculated to statistically support the correlation between the ecogeographic parameters and clusterization obtained by the software STRUCTURE. The results showed a significant correlation (p < 0.001) with all the variables considered. The highest positive correlation was observed between the values that support the membership to the Gp2.1 group in the software STRUCTURE and the Q2 values (0.519), while the highest negative correlation was observed between the Gp2.1 group and the Altitude values (–0.383) (Figure 5B).

    Figure 5
    A Stacked bar–plots illustrating, for each of the three clusters identified by STRUCTURE for K = 3, the percentages of genotypes collected in areas characterized by different ecogeographic parameters (altitude, annual rainfall (P), Minimum (m) –maximum (M) temperature, and Emberger coefficient (Q2). B Spearman correlation coefficient, significant at p < 0.001, indicating the correlation between the ecogeographic parameters and the cluster obtained by STRUCTURE software.

    Discussion

    Biological diversity is a crucial factor to increase and improve productivity in agriculture. Algeria is characterized by low population density and the presence of olive cultivations restricted to the northern coastal region. In Algeria, wild–looking forms of olive trees are preserved in natural areas where they can survive in small grove or scattered plants, due to the isolation from cultivated orchards. Prospections were conducted in 33 provinces in the northern region of Algeria, allowing the collection of 174 samples. The genetic analysis was carried out with 16 microsatellite markers, which were highly informative (Pasqualone et al., 2015; Sabetta et al., 2017; Saddoud et al., 2020). Other authors have reported that the results confirmed a high genetic diversity of the Algerian wild olive (Baldoni et al., 2006; Besnard and Bervillé, 2002; Lumaret et al., 2004; Mousavi et al., 2017; Mulas et al., 2004). Deviations from HW equilibrium and positive values of the inbreeding coefficient in some locus were observed, despite the width of the sampling in the analyzed loci. As already observed in cultivated olive (Di Rienzo et al., 2018; Muzzalupo and Perri, 2009), a certain degree of inbreeding can be favored by the geographic isolation of plants, which promote self–cross reproduction instead of open–pollinated reproduction, as reported in previous works on isolated olive trees (Besnard et al., 2007; Diaz et al., 2006). Indeed, the PCoA underlined the separation of the genotypes analyzed in three groups, according to their growing geographic areas: northwestern coastal area, northeastern coastal area, and northeastern mountainous areas. These three Regions are well separated by physical barriers, such as the Atlas Mountains in the West and the Aurès Massif, in the East (Figure 1).

    The STRUCTURE Bayesian–based analysis detected two main populations: Gp1 and Gp2. One cluster could be composed of genuine wild olives while the other one could include feral olives. However, a further subdivision was revealed within the Gp2 cluster. Many hypotheses about the origin of this clusterization may be raised. Based on previous studies, three principal gene pools were identified for domesticated olive, corresponding to three main geographical areas: western (Q1), central Mediterranean (Q2) and eastern Mediterranean (Q3) (Díez et al., 2015; Besnard et al., 2013). Therefore, the distinction of two subgroups within Gp2 could result from a further differentiation within the local oleaster or from the presence of feral forms derived from different cultivated gene pools.

    The clusterization obtained by structure seems also to be related to the growing climatic conditions of samples. Indeed, Gp1 collects the genotypes from the large coastal planes of Algeria, from the border with Morocco through the central Bejaia province, toward the plains of Oran and Annaba, characterized by intensive cultivation of olive. The Gp2.1 mostly included genotypes collected in northeastern Algeria, in the provinces of Skikda, Guelma, Souk Ahras, and Jijel, where the coast is predominantly mountainous with small plains characterized by mild temperature, high rainfall and moderate altitude. The Gp2.2 group included the genotypes collected in the inner eastern part of the country, in the regions of Batna, Biskra and Khenchela, characterized mainly by extreme temperature changes, lack of rain and high altitudes (Figure 5A). In regions near the desert, higher temperature and low precipitations hinder olive cultivation; thus, the genotypes belonging to this group could be particularly adapted to the harsh climatic conditions, such as aridity and thermic excursions. These genotypes could be useful in breeding programs for tolerance to drought, as well as resources for the introduction of olive populations in habitats where adverse conditions endanger this species.

    Many samples fall into the admixed group and were mostly collected in the plains of Sétif, Constantine. and Oum El Bouaghi provinces, main centers of grain cultivation during the French colonial period. This area, characterized by fertile soils and Mediterranean climate, is traditionally devoted to agriculture where olive cultivation and human selection could have contributed to an admixture between cultivars and wild populations, as previously reported in other countries (Belaj et al., 2007; Boucheffa et al., 2019; García–Verdugo et al., 2009).

    The Unweighted Neighbor–Joining dendrogram confirmed the three main groups outlined by STRUCTURE; nevertheless, it also revealed a fourth group that included nine samples collected in the area between the North and South East, probably the result of mixed pollination between wild and domesticated. Olive is generally considered a wind–pollinated species and its pollen spreads in a range of about 100 m; however, evidences have been found that it can move across kilometers, at low concentrations (Pinillos and Cuevas, 2009). Pollen dispersion and geographical barriers are probably the basis of the complex genetic structure observed in the Algerian wild germplasm and of the different gene pools found in the different geo–climatic conditions. The detection of three main gene pools shows how the geographical barriers can determine partial genetic isolation even on local scale, according to other studies (Belaj et al., 2007; Boucheffa et al., 2019; Breton et al., 2006; Sion et al., 2019). This wide genetic variability deserves further investigation to better understand the relationship between wild and feral forms spread in these areas. Indeed, wild genotypes constitute a priceless resource of genes that need to be preserved and conserved. On the other hand, feral forms represent a variability source useful for olive breeding programs. Future studies should compare the large genetic variability of wild olive with the variability in varieties cultivated in Algeria to investigate their relationships.

    Conclusion

    Our study provides a genetic characterization of 174 samples of oleaster collected in different regions of northern Algeria. The accessions were clustered according to geographic origin and consequently to their characteristic climatic conditions, which allows the identification of samples from an area characterized by higher temperatures and low precipitation, making them a good source of genes for tolerance to harsh climatic conditions, which is crucial to face challenges posed by climate change.

    Acknowledgments

    This research was funded by the Exceptional National program 2019/2020. W.F. acknowledges the financial support of Ecole Nationale Supérieure de Biotechnologie Constantine, Algeria. Experiments were also supported by statutory funds of the Department of Soil, Plant and Food Sciences (DISSPA), University of Bari, Italy. The 6th. author has been supported by MIUR – PON Ricerca e Innovazione 2014 – 2020 (project AIM1809249 – attività 2, linea 1). The 2nd. and 5th. authors were supported by PhD program of University of Bari Aldo Moro “Biodiversity, agriculture and environment” curriculum of “Genetics and plant biotechnology”. The 7th. author was supported by ADISU and University of Bari Aldo Moro with post–graduate fellowship.

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    Edited by

    • Edited by: Leonardo Oliveira Medici

    Publication Dates

    • Publication in this collection
      14 June 2021
    • Date of issue
      2022

    History

    • Received
      25 Sept 2020
    • Accepted
      08 Jan 2021
    Creative Common - by 4.0
    This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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