Using ISSR Genomic Fingerprinting to Study the Genetic Differentiation of Artemia Leach, 1819 (Crustacea: Anostraca) from Iran and Neighbor Regions with the Focus on the Invasive American Artemia franciscana
1
Institute of Pharmacy and Molecular Biotechnology (IPMB), Heidelberg University, Im Neuenheimer Feld 364, 69120 Heidelberg, Germany
2
College of Fisheries and Life Science, Hainan Tropical Ocean University, Sanya 572000, China
3
College of Ecology and Environment, Hainan Tropical Ocean University, Sanya 572000, China
4
College of Ecology and Environment, Hainan University, Haikou 570228, China
*
Authors to whom correspondence should be addressed.
Diversity 2020, 12(4), 132; https://doi.org/10.3390/d12040132
Submission received: 4 March 2020
/
Revised: 23 March 2020
/
Accepted: 26 March 2020
/
Published: 31 March 2020
/
Corrected: 4 June 2025
(This article belongs to the Section Biodiversity Conservation)
Abstract
:Due to the rapid developments in the aquaculture industry, Artemia franciscana, originally an American species, has been introduced to Eurasia, Africa and Australia. In the present study, we used a partial sequence of the mitochondrial DNA Cytochrome Oxidase subunit I (mt-DNA COI) gene and genomic fingerprinting by Inter-Simple Sequence Repeats (ISSRs) to determine the genetic variability and population structure of Artemia populations (indigenous and introduced) from 14 different geographical locations in Western Asia. Based on the haplotype spanning network, Artemia urmiana has exhibited higher genetic variation than native parthenogenetic populations. Although A. urmiana represented a completely private haplotype distribution, no apparent genetic structure was recognized among the native parthenogenetic and invasive A. franciscana populations. Our ISSR findings have documented that despite that invasive populations have lower variation than the source population in Great Salt Lake (Utah, USA), they have significantly revealed higher genetic variability compared to the native populations in Western Asia. According to the ISSR results, the native populations were not fully differentiated by the PCoA analysis, but the exotic A. franciscana populations were geographically divided into four genetic groups. We believe that during the colonization, invasive populations have experienced substantial genetic divergences, under new ecological conditions in the non-indigenous regions.
1. Introduction
The brine shrimp Artemia is a unique zooplankton that has a limited number of species, distributed globally, except in Antarctica [1]. This tiny crustacean has potentially adapted to live in extreme environmental conditions, such as hypersaline environments [2,3].
Artemia has been mainly used as live food in larviculture and fishery industries, especially in Asia [4]. Artemia has been used to improve the quality of sodium chloride production in solar salt-fields [5,6]. It was also introduced as a model organism in many bioscience studies, including cellular and molecular biology [7], phylogeography and asexual evolution [8], bioencapsulation [9] and toxicity assessment [10].
The genus Artemia consists of seven bisexual species and a large number of parthenogenetic populations with different ploidy levels [3,11]. It has been assumed that Asia is the origin of Artemia urmiana Günther, 1899 (Lake Urmia, Iran), Artemia sinica Cai, 1989 (China), Artemia tibetiana Abatzopoulos, Zhang and Sorgeloos, 1998 (Qinghai-Tibetan Plateau, China), and corresponding parthenogenetic populations [3,12]. Recently, two new species, Artemia frameshifta and Artemia murae have been described from Mongolia [13]. These species have been described using a single mitochondrial DNA protein-coding Cytochrome Oxidase subunit I (COI) gene sequence without confirmation by any morphometric and population genetic analyses [11]. A main problem in the submitted COI sequence of A. frameshifta (LC195588) was detected in the protein sequence with several stop codon(s). In a protein coding gene, this is an indication for a nuclear copy of this mtDNA gene. Sometimes, the COI marker provides a sharp PCR amplified band on the agarose gel, but the sequence information presents heterogeneities [14]. These kinds of results could mislead the interpretation of downstream phylogenetic analyses. Therefore, the population would need more biosystematic evidences to determine its taxonomical status. In A. frameshifta, neither the existence of males nor the reproductive mode has been revealed [13]. Based on the current information, we assume that A. frameshifta is a parthenogenetic population, which needs more investigations to confirm the biological status of the species.
Generally, the long-distance translocations of the American species Artemia franciscana to other non-indigenous regions have occurred as a result of commercial activities, which have been fully documented previously [2,15,16,17,18]. Artemia franciscana is a successful invader in saltwater ecosystems due to its faster filter-feeding rate, a high potential of reproduction [15,19], and a better physiological immune system, which is associated with nutritional behavior against cestode parasites [15] than the native species. Asem et al. [17] have suggested that these biological characteristics could afford a high level of adaptive potential of A. franciscana in the new non-indigenous habitats, which would eventually result in the replacement with native species.
Lee [20] has documented that the genetic structure of introduced populations to the non-indigenous habitats is one of the most determinative parameters in their successful establishment. Generally, genetic diversity of the species could determine the potential of an exotic species to acclimatize in the new environmental conditions [21].
Previous studies on A. franciscana have documented that invasive populations demonstrated genetic variations relative to the native American source populations [2,17,18,22,23,24]. The low genetic diversity in the non-indigenous populations has been attributed to the founder effect [22] or population bottleneck due to the decreasing of population size in introduced populations during the process of establishment [17]. Moreover, high genetic variation could be a result of adaptive capacity and physiological flexibility as a special biological trait observed in invasive populations [2,6,24,25,26].
Eimanifar et al. [2] have reported the existence of invasive A. franciscana in four sites from Iran (three sites) and Iraq (one site) using the mitochondrial COI sequence marker. The aim of the present study was to further perform an analysis based on population genetic approaches to determine the intra- and inter-specific genetic variations of native and invasive Artemia populations from Iran and neighboring regions (14 sites) using Inter-Simple Sequence Repeats (ISSRs) genomic fingerprinting. Genomic fingerprinting by ISSR has been demonstrated to be a useful molecular tool to recognize DNA polymorphisms among Artemia taxa [27,28,29,30]. We hypothesize that the establishment of an exotic species in the new geographical habitats should be accompanied by intra-species genetic divergence to better adapt to the new environmental conditions. Here, we utilized high-resolution ISSR genomic fingerprinting to compare the genetic differentiation in native and colonizing populations of American A. franciscana in the indigenous environments.
2. Material and Methods
2.1. Sample Collection and DNA Extraction
Artemia cyst specimens were collected from 14 geographical localities across Iran and neighbor countries (Figure 1). All studied populations had been confirmed to be bisexual or parthenogenetic according to Asem et al. [3]. The sample localities with their geographical coordinates, abbreviations and IPMB voucher are summarized in Table 1. Total genomic DNA was extracted from part of the antenna of adult males and females using the Chelex® 100 Resin method (6%, Bio-Rad Laboratories, Hercules, CA, USA) [16]. All extracted DNA was stored at −80 °C for subsequent genetic characterization.
2.2. Population Identification and Phylogenetic Analyses
A partial sequence of the mitochondrial marker cytochrome c oxidase subunit I (COI) was utilized to identify the taxonomical status of the studied populations using phylogenetic analyses as implemented in the MEGA X program (Temple University, Philadelphia, USA) [2,17,18]. To identify the taxonomical status of the studied populations, the COI reference sequences from the recognized bisexual species and parthenogenetic populations were downloaded from GenBank (Table 2). Sequences were aligned using MEGA X with default settings [31]. Phylogenetic trees were reconstructed based on the Maximum Likelihood approach included in the MEGA X program. To reveal the genealogical and geographical relationships, a median haplotype network was established, following the median-joining algorithm in the Network program ver. 5.0.1.1 (Universität Hamburg, Hamburg, Germany) [32].
2.3. Genomic Fingerprinting by ISSR-PCR
Genomic variability was examined by inter simple sequence repeat ISSR-PCR using the same DNA template used for phylogenetic analyses. Initially, 15 ISSR primers were analyzed to distinguish the intra- and inter-specific genetic variability within and among 83 randomly selected individuals, belonging to 14 geographically different localities of Artemia. Out of 15 tested ISSR primers, five were selected because of unambiguous banding patterns of the PCR products (Table 3).
PCR was carried out in a 25 μl volume consisting of 40 ng template DNA, 2.5 μl 10× PCR buffer (160 mM (NH4)2SO4, 670 mM Tris-HCl pH 8.8, 0.1% Tween-20, 25 mM MgCl2), 10 pmol primer, 2 μg/μl bovine serum albumin (BSA), 0.5 units Taq DNA polymerase (Bioron), 0.1 mM dGTP, dCTP, and dTTP, 0.045 mM dATP, 1 μCi [α-33P]-dATP (Perkin Elmer, LAS, Rodgau, Germany). PCR amplifications were executed in a thermal cycler based on the following conditions: 94 °C denaturation for 1 min, 35 cycles of 46–54 °C annealing for 50 s and 72 °C extension for 2 min. The final cycle was continued for 7-min at 72 °C. Final PCR products were mixed with 8 μl bromophenol blue and run on high-resolution denaturing polyacrylamide gels 6% (0.2 mm) for 3 h at 65 W (size 45 × 30 cm) including 1× TBE buffer. The gels were dried and exposed for 2 days to X-ray hyperfilm (Kodak, Taufkirchen, Germany) and subsequently developed. Finally, the autoradiograms were scanned to identify the polymorphic bands [25].
2.4. ISSR Statistics
The quality and quantity of ISSR bands were inspected visually. Ambiguous and smeared bands were excluded from the analysis, and only unequivocally reproducible bands were scored for each individual as present (1) or absent (0). The binary data matrix (presence = 1; absence = 0) was formulated in MS Excel v.2016 and used for subsequent genetic analyses.
ISSR data were analyzed via the Bayesian model-based clustering algorithm as implemented in the STRUCTURE v. 2.3 program (University of Oxford, Oxford, United Kingdom) [34,35]. We analyzed the genetic structure among populations by assigning individuals into potential numbers of clusters (K = 1 − 10). ISSR genotypes were processed with a period of burn-in 50,000 and 100,000 MCMC repetitions [34]. The CLUMPAK online program was employed to identify the pattern of clustering modes and packaging population structure [35]. The online programs, CLUMPAK [36] and STRUCTURE HARVESTER [37] were implemented to assess and visualize the most appropriate number of K by calculating the likelihood of the posterior probability [38].
The binary data matrix was employed to calculate the genetic diversity parameters of each population using GenAlex ver. 6.5 (Australian National University, Acton, Australia) [39]. The population genetic parameters were as follows: Na (number of different alleles), Ne (number of effective alleles), I (Shannon’s information index), He (expected heterozygosity), uHe (unbiased expected heterozygosity), PPL (percentage of polymorphic loci), NB (number of bands) and NPB (number of private bands) and pairwise population matrix of Nei genetic distance [28,29].
Intra- and inter-specific molecular variations and genetic relationships among populations were implemented by Principal Coordinate Analysis (PCoA) and Analysis of Molecular Variance (AMOVA) as utilized by GenAlex ver. 6.5, respectively [39].
To better understand the population genetic variations, ISSR analyses were performed on three platforms separately, as follows: whole populations, native populations and invasive American A. franciscana.
3. Results
3.1. Phylogenetic Analyses and Haplotype Distribution
Our phylogenetic analyses provide evidence that the studied bisexual specimens from three localities of Iran, Nough Catchment (NOG), Mahshar port (MSH) and Maharlu Lake (MAHR), and a locality from Iraq, Garmat Ali (GAA), clustered in the clade of A. franciscana (Figure 2). In addition, all parthenogenetic populations clustered in two separated clades that shared a common ancestor with urmiana. Although most of the parthenogenetic populations were located in clade P1, the majority of CAM specimens (eight out of nine). The clade P1 contained two sub-clades, consisting of diploids and triploid populations.
Figure 3 represents the haplotype spanning network of COI among native A. urmiana and parthenogenetic populations. Results demonstrated that A. urmiana has wider genetic variation compared to parthenogenetic ones. Genetic differentiation and a close relationship of Camalti Lake (CAM) population (Turkey) with A. urmiana was clearly revealed in the tree. While COI sequences of nine parthenogenetic populations were distributed in five Haplotypes (H2–6), A. urmiana showed private haplotypes without a shared haplotype in other populations. The COI sequences of invasive A. franciscana were grouped into six distinct haplotypes. No population with private haplotypes was observed (Figure 4). The numbers of individuals and population composition were calculated for each haplotype (Appendix A, Table A1 and Table A2).
3.2. ISSR Profiling
We have shown previously that ISSR can detect substantial genetic variation in the genus Artemia [28,29]. ISSR fingerprints can differ within and among populations. Altogether, 152 observed and unambiguously identified ISSR bands were analyzed. The total number of polymorphic loci showed a mean value of 25.42 ± 2.28%; the lowest number was seen in Camalti Lake (CAM) (7.24%) and the highest in Nough Catchment (NOG) (38.82%). Generally, the lowest values of genetic indices belonged to the parthenogenetic CAM, while the highest values were shared between the native parthenogenetic population from Eastern lagoon around Urmia Lake (LAGE) (Ne = 1.256 ± 0.031, I= 0.208 ± 0.024, He = 0.143 ± 0.017, uHe = 0.171 ± 0.020) and invasive A. franciscana from NOG (Na = 1.013 ± 0.071, I = 0.208 ± 0.023) (Table 4). In summary, 134 and 126 distinguished ISSR bands were examined for ten native and four American A. franciscana populations, respectively (Table 5 and Table 6). According to the results of the Nei genetic matrix, parthenogenetic CAM from Turkey and invasive GAA from Iraq showed the high genetic distance with parthenogenetic and invasive populations, respectively (Table 7 and Table 8).
Based on the total results of ISSR, the AMOVA analysis documented that most of the genetic variations were attributed among native and invasive populations more than within populations (69% vs. 31%). There was no indicative genetic variability observed in the midst of among- and within variation (55% vs. 45%) in native populations. In contrast, the high differentiation was represented within populations (71% vs. 29%) of non-indigenous A. franciscana in Asia (Table 9, Figure 5A–C).
Bayesian clustering analysis using STRUCTURE was performed to investigate the genetic patterns of the studied populations. The optimum K was obtained at K = 2 for the whole 14 populations and ten native populations, and K = 9 for four invasive A. franciscana, respectively. Figure 6 showed the clustering of genetic structures, where the first highest posterior probability (K) was represented by different colors for each population. With regard to the genetic patterns of ISSR, native and exotic populations could be completely divided into two groups (Figure 6A). The results of the analysis for native populations documented that parthenogenetic CAM is a distinct population with a differing clustering pattern. The STRUCTURE analysis could not fully distinguish A. urmiana and parthenogenetic populations (Figure 6B). The high value of optimum K (K = 9) was prominent in the clustering analysis for A. franciscana populations, which generally revealed a complex pattern (Figure 6C). Proportions of genetic clusters (percentage) for each locality were summarized in Figure 7 (see also Table A3, Table A4 and Table A5).
The first and second PCoA coordinates explained 64.66% and 7.00% of the variance, respectively (overall, 71.66% of total variation). The results showed all populations clustered into three groups, where invasive A. franciscana has been significantly separated from the native populations based on the first coordinate. Ten native populations (including A. urmiana and parthenogenetics) were divided into two distinct groups, G2 and G3. G2 included all of the CAM population and a single individual of Eastern lagoon around Urmia Lake (LAGE). Bisexual A. urmiana and other parthenogenetics were placed in G3 (Figure 8). The results of the separate analyses of PCoA for native and invasive populations are shown in Figure 9 and Figure 10, which include overall 42.55% and 41.55% of the total variation, respectively. Although native populations produced almost the same result with the “whole populations” analysis (Figure 9), the separated analyses of PCoA for invasive A. franciscana could separate all four populations in isolated groups (Figure 10).
Similar to the phylogeny based on COI sequences, clustering analysis of ISSR sequences by STRUCTURE has revealed a distinguished structure for non-indigenous A. franciscana populations. In this analysis, all native populations (bisexual A. urmiana and parthenogenetic ones) have displayed almost similar patterns, but a separated analysis for native populations has revealed a non-identical structure for the CAM population. Additionally, an inconsistent pattern of the Eastern lagoon around Urmia Lake (LAGE) was also observed. A separated analysis for invasive populations could not reveal different patterns among examined populations by STRUCTURE (Figure 6A–C). On the other hand, PCoA has divided A. franciscana from native populations. Although PCoAs could not branch off natives by localities, the separated PCoA has divided invasive populations based on localities in the four groups. Contrary to COI haplotype distribution, the ISSR marker was unable to reveal a private pattern for bisexual A. urmiana in comparison to native parthenogenetic populations.
4. Discussion
The present study was performed to compare the population structure and genetic differentiation of native and invasive Artemia populations. The mitochondrial COI gene has been established as a useful molecular marker to determine the intra- and inter-specific evolutionary associations [2,3,17,18]. Asem et al. [2] have documented that di- and triploid parthenogenetic brine shrimps are maternally related to A. urmiana, while tetra- and pentaploid lineages shared a common maternal ancestor with A. sinica. Based on the mitochondrial COI dataset, all examined parthenogenetic individuals have grouped in a close evolutionary relationship with A. urmiana (Figure 2). Our results have demonstrated that they should include di- and/or triploids. This observation has also been confirmed by the phylogenetic tree. Although individuals of eight Artemia populations have been exactly located in sub-clades of di- and/or triploid, eight out of nine specimens of CAM from Turkey have been placed in a particular clade (P2), in a close connection with A. urmiana (Figure 2). This finding has also been confirmed by haplotype distribution (Figure 3). Previously, Sayg [40] has confirmed that triploid and pentaploid parthenogenetic populations coexisted in Camalti Lake (CAM). Our observation has confirmed that Camalti Lake (CAM) populations had a parthenogenetic reproductive mode and those examined specimens should be considered as a diploid and/or triploid population (see [3]). Despite the fact that A. urmiana shared a common ancestor with di- and triploids, it has presented an unexpectedly high level of haplotype diversity of the COI marker. These results have also been documented by Eimanifar and Wink [28]. The high level of haplotype variation might be attributed to the evolutionary life history of A. urmiana [30] and/or its large population size [28]. Urmia Lake has undergone considerable changes in environmental conditions, such as salinity and temperature [41,42], which could have influenced genetic variation and population size during evolution.
Although COI sequences should reveal a phylogeographic structure in the closely related species [43], our results could not determine a level of geographical differentiation among native as well as among invasive populations. Contrary to the results of the mitochondrial marker, genomic fingerprinting ISSR could not reveal a significant high level of genetic variation in A. urmiana. This result might be due to differences in the rate of variation of mitochondrial and nuclear genes and potential hybridization events in the past.
The ISSR method had been utilized to study ten diploid parthenogenetic Artemia populations from China by Hou et al. [27]. Their genetic variation was significantly higher than our examined parthenogenetic populations. For example, the percentage of polymorphic loci ranged from 54.12–87.06% vs. 8.21–39.55%. Western Asia is the origin of di- and triploid parthenogenetic populations [3], so high genetic diversity of Chinese populations could be the result of their adaptation during colonization through biological dispersal to the new environments in East Asia under historical evolutionary progress.
In general, it was reported that the invasive populations have lower genetic variation in the new environments as compared with their origin populations [44]. The colonized population of A. franciscana in Vietnam has a lower genetic diversity than its native source population from San Francisco Bay (SFB) [22]. In contrast, Eimanifar et al. [2] have documented that Asian invasive A. franciscana populations had higher genetic variation than the American Great Salt Lake (GSL) population and native Asian species. Similar results have been reported for some invasive populations from Mediterranean regions [23,24]. A recent study assumed that invasive populations of A. franciscana show a wide degree of genetic differentiation in Australia [17].
Overall, our ISSR results have documented that invasive A. franciscana populations had distinctly higher genetic variation than Western Asian native parthenogenetic populations. On the other hand, native A. franciscana from Great Salt Lake (GSL) have represented higher variation than examined invasive populations in this study, as the percentage of polymorphic loci differed from 67–81% vs. 30.95–46.83% (see [29]). Additionally, all four invasive A. franciscana populations clearly revealed a different genetic structure. Observation of low genetic diversity in native populations might be attributed to the effect of asexual reproduction in parthenogenetic populations and/or critical climatic conditions in West Asia, especially Urmia Lake in the last two decades (see [3,30]). We believe that interactions between different ecological conditions in the new environments and the high potential of physiological plasticity and genetic adaptation of A. franciscana could exert different evolutionary pathways during the introduction of exotic populations, which would have ultimately caused intra-specific variations and genetic divergence in the examined invasive populations.
In conclusion, it is expected that the non-indigenous species should have a lower genetic variation than their source populations [25,44,45]. However, non-indigenous A. franciscana populations gave opposite results in comparison with native populations from GSL and SFB. Since there is neither a taxonomical identification key nor morphological identifications to distinguish bisexual species and parthenogenetic populations [11,46], it would not be possible to identify the exotic population at the earliest time of invasion. Therefore, there is a lack of information to regularly determine the colonization progress and evolutionary development of A. franciscana in the new habitats. We assume that differences in the genetic variation of non-indigenous populations could be due to the study on different invasion periods consisting of i) introduced, ii) establishing/colonizing, iii) established/colonized populations.
Author Contributions
Research design, material preparation, and data collection were performed by A.E. Data analysis was carried out by A.A. The first draft of the manuscript was written by A.A. and A.E. P.-Z.W., W.L. and M.W. reviewed the draft. All authors have read and agreed to the published version of the manuscript.
Funding
This study was carried out at IPMB, Department of Biology, University Heidelberg and A/10/97179. Amin Eimanifar was supported by a Ph.D. fellowship from the Deutscher Akademischer Austauschdienst (DAAD, German Academic Exchange Service).
Acknowledgments
We would like to express our appreciations to the Dr. Razia Sultana from the Food and Marine Resources Research Center, PCSIR Laboratories Complex, Pakistan and Prof. Gilbert Van Stappen from the Artemia Reference Center, Belgium for providing Artemia samples to this research project.
Conflicts of Interest
The authors declare no conflict of interest. M.W. is Editor-in-Chief of Diversity.
Appendix A
Table A1.
Information of network haplotype composition of native populations.
| Haplotype | Ind. | Pop. (Ind.) | Haplotype | Ind. | Pop. (Ind.) |
|---|---|---|---|---|---|
| H1 | 18 | URM (18) | H24 | 1 | URM (1) |
| H2 | 7 | CAM (7) | H25 | 1 | URM (1) |
| H3 | 16 | KOC (6), LAGW (5)ABG (3), LAGE (1), KBG (1) | H26 | 1 | URM (1) |
| H4 | 15 | ING (5), MIG (4), KBG (3), LAGE (2) | H27 | 1 | URM (1) |
| H5 | 7 | QOM (6), MIG (1) | H28 | 1 | URM (1) |
| H6 | 1 | CAM (1) | H29 | 1 | URM (1) |
| H7 | 1 | URM (1) | H30 | 1 | URM (1) |
| H8 | 1 | URM (1) | H31 | 2 | URM (2) |
| H9 | 2 | URM (2) | H32 | 1 | URM (1) |
| H10 | 1 | URM (1) | H33 | 1 | URM (1) |
| H11 | 1 | URM (1) | H34 | 1 | URM (1) |
| H12 | 3 | URM (3) | H35 | 1 | URM (1) |
| H13 | 1 | URM (1) | H36 | 1 | URM (1) |
| H14 | 1 | URM (1) | H37 | 1 | URM (1) |
| H15 | 1 | URM (1) | H38 | 1 | URM (1) |
| H16 | 1 | URM (1) | H39 | 1 | URM (1) |
| H17 | 1 | URM (1) | H40 | 1 | URM (1) |
| H18 | 1 | URM (1) | H41 | 1 | URM (1) |
| H19 | 1 | URM (1) | H42 | 1 | URM (1) |
| H20 | 1 | URM (1) | H43 | 1 | URM (1) |
| H21 | 1 | URM (1) | H44 | 1 | URM (1) |
| H22 | 1 | URM (1) | H45 | 1 | URM (1) |
| H23 | 1 | URM (1) | - | - | - |
Ind. = Individual, Pop. = Population.
Table A2.
Information of network haplotype composition of invasive A. franciscana populations.
| Haplotype | Ind. | Pop. (Ind.) |
|---|---|---|
| H1 | 8 | GAA (4), MAH (2), MSH (2) |
| H2 | 7 | NOG (4), MSH (3) |
| H3 | 4 | GAA (4) |
| H4 | 1 | NOG (1) |
| H5 | 1 | MAH (1) |
| H6 | 1 | MSH (1) |
Ind. = Individual, Pop. = Population.
Table A3.
Proportion of genetic clusters for each locality in STRUCTURE analysis among whole examined populations.
Table A3.
Proportion of genetic clusters for each locality in STRUCTURE analysis among whole examined populations.
| Population | K1 (%) | K2 (%) |
|---|---|---|
| KOC | 0.1 | 99.9 |
| ABG | 0.2 | 99.8 |
| LAGE | 0.7 | 99.3 |
| LAGW | 0.3 | 99.7 |
| KBG | 0.1 | 99.9 |
| QOM | 0.1 | 99.9 |
| MIG | 1.9 | 98.1 |
| CAM | 0.1 | 99.9 |
| INC | 0.2 | 99.8 |
| URM | 3.6 | 96.4 |
| MAH | 98.7 | 1.3 |
| NOG | 99.9 | 0.1 |
| MSH | 99.9 | 0.1 |
| GAA | 99.9 | 0.1 |
Table A4.
Proportion of genetic clusters for each locality in STRUCTURE analysis among native populations.
Table A4.
Proportion of genetic clusters for each locality in STRUCTURE analysis among native populations.
| Population | K1 (%) | K2 (%) |
|---|---|---|
| KOC | 000099.7 | 0.3 |
| ABG | 99.8 | 0.2 |
| LAGE | 72.1 | 27.9 |
| LAGW | 99.6 | 0.4 |
| KBG | 99.5 | 0.5 |
| QOM | 99.8 | 0.2 |
| MIG | 99.6 | 0.4 |
| CAM | 0.2 | 99.8 |
| INC | 99.7 | 0.3 |
| URM | 93.1 | 6.9 |
Table A5.
Proportion of genetic clusters for each locality in STRUCTURE analysis among invasive A. franciscana populations.
Table A5.
Proportion of genetic clusters for each locality in STRUCTURE analysis among invasive A. franciscana populations.
| Population | K1 (%) | K2 (%) | K3 (%) | K4 (%) | K5 (%) | K6 (%) | K7 (%) | K8 (%) | K9 (%) |
|---|---|---|---|---|---|---|---|---|---|
| MAH | 1.1 | 0.4 | 0.3 | 1.7 | 0.4 | 1.1 | 46 | 1.8 | 47.1 |
| NOG | 0.6 | 0.5 | 0.4 | 57 | 0.6 | 33.6 | 3.6 | 0.3 | 3.4 |
| MSH | 0.5 | 28.6 | 0.3 | 0.4 | 27.9 | 0.4 | 3.4 | 33.9 | 4.6 |
| GAA | 38.8 | 0.2 | 42.3 | 0.3 | 0.4 | 0.2 | 7 | 1.1 | 9.7 |
References
- Van Stappen, G. Zoogeography. In Artemia: Basic and Applied Biology; Abatzopoulos, T.J., Beardmore, J.A., Clegg, J.S., Sorgeloos., P., Eds.; Kluwer Academic Publishers: Dordrecht, The Netherlands, 2002; pp. 171–224. [Google Scholar]
- Eimanifar, A.; Van Stappen, G.; Marden, B.; Wink, M. Artemia biodiversity in Asia with the focus on the phylogeography of the introduced American species Artemia franciscana Kellogg, 1906. Mol. Phylogenetics Evol. 2014, 79, 392–403. [Google Scholar] [CrossRef] [PubMed]
- Asem, A.; Eimanifar, A.; Sun, S.C. Genetic variation and evolutionary origins of parthenogenetic Artemia (Crustacea: Anostraca) with different ploidies. Zool. Scr. 2016, 45, 421–436. [Google Scholar] [CrossRef]
- Van Stappen, G. Artemia biodiversity in Central and Eastern Asia. Ph.D. Thesis, Ghent University, Ghent, Belgium, 2008. [Google Scholar]
- Jones, A.G.; Ewing, C.M.; Melvin, M.V. Biotechnology of solar saltfields. Hydrobiologia 1981, 81, 391–406. [Google Scholar] [CrossRef]
- Ruebhart, D.R.; Cock, I.E.; Shaw, G.R. Invasive character of the brine shrimp Artemia franciscana Kellogg 1906 (Branchiopoda: Anostraca) and its potential impact on Australian inland hypersalinewaters. Mar. Freshw. Res. 2008, 59, 587–595. [Google Scholar] [CrossRef]
- Li, D.R.; Ye, H.L.; Yang, J.S.; Yang, F.; Wang, M.R.; De Vos, S.; Vuylsteke, M.; Sorgeloos, P.; Van Stappen, G.; Bossier, P.; et al. Identification and characterization of a Masculinizer (Masc) gene involved in sex differentiation in Artemia. Gene 2017, 614, 56–64. [Google Scholar] [CrossRef]
- Kappas, I.; Baxevanis, D.; Abatzopoulos, T.J. Phylogeographic patterns in Artemia: A model organism for hypersaline crustaceans. In Phylogeography and Population Genetics in Crustacea; Koenemann, S., Schubart, C., Held, C., Eds.; CRC Press: Boca Raton, FL, USA, 2011; pp. 233–255. [Google Scholar]
- Vazquez-Silva, G.; Aguirre-Garrido, J.F.; Ramirez-Saad, H.C.; Mayorga-Reyes, L.; Azaola-Espinosa, A.; Morales-Jiménez, J. Effect of bacterial probiotics bioencapsulated in Artemia franciscana on weight and length of the short fin silverside (Chirostoma humboldtianum) and the characterization of its intestinal bacterial community by DGGE. Lat. Am. J. Aquat. Res. 2018, 45, 1031–1043. [Google Scholar]
- Rajabi, S.; Ramazani, A.; Hamidi, M.; Naji, T. Artemia salina as a model organism in toxicity assessment of nanoparticles. J. Pharm. Sci. 2015, 23, 20. [Google Scholar] [CrossRef]
- Asem, A.; Rastegar-Pouyani, N.; De los Rios, P. The genus Artemia Leach, 1819 (Crustacea: Branchiopoda): True and false taxonomical descriptions. Lat. Am. J. Aquat. Res. 2010, 38, 501–506. [Google Scholar]
- Asem, A.; Eimanifar, A.; Rastegar-Pouyani, N.; Hontoria, F.; De Vos, S.; Van Stappen, G.; Sun, S.C. An overview on the nomenclatural and phylogenetic problems of native Asian brine shrimps of the genus Artemia Leach, 1819 (Crustacea: Anostraca). Zookeys 2020, 902, 1. [Google Scholar] [CrossRef]
- Naganawa, H.; Mura, G. Two new cryptic species of Artemia (Branchiopoda, Anostraca) from Mongolia and the possibility of invasion and disturbance by the aquaculture industry in East Asia. Crustaceana 2017, 90, 1679–1698. [Google Scholar] [CrossRef]
- Wang, W.; Luo, Q.; Guo, H.; Bossier, P.; Van Stappen, G.; Sorgeloos, P.; Xin, N.; Sun, Q.; Hu, S.; Yu, J. Phylogenetic analysis of brine shrimp (Artemia) in China using DNA barcoding. Genom. Proteom. Bioinform. 2008, 6, 155–162. [Google Scholar] [CrossRef]
- Sanchez, M.I.; Paredes, I.; Lebouvier, M.; Green, A.J. Functional role of native and invasive filter-feeders, and the effect of parasites: Learning from hypersaline ecosystems. PLoS ONE 2016, 11, e0161478. [Google Scholar] [CrossRef] [PubMed]
- Horvath, Z.; Lejeusne, C.; Amat, F.; Sanchez-Fontenla, J.; Vad, C.F.; Green, A.J. Eastern spread of the invasive Artemia franciscana in the Mediterranean Basin, with the first record from the Balkan Peninsula. Hydrobiologia 2018, 822, 229–235. [Google Scholar] [CrossRef]
- Asem, A.; Eimanifar, A.; Li, W.; Wang, P.; Brooks, S.A.; Wink, M. Phylogeography and population genetic structure of an exotic invasive brine shrimp Artemia Leach, 1819 (Crustacea: Anostraca) in Australia. Aust. J. Zool. 2018, 66, 307–316. [Google Scholar] [CrossRef]
- Saji, A.; Eimanifar, A.; Soorae, P.S.; Al Dhaheri, S.H.; Asem, A. Phylogenetic Analysis of exotic invasive species of Brine Shrimp Artemia Leach, 1819 (Branchiopoda, Anostraca) in Al Wathba Wetland Reserve (UAE.; Abu Dhabi). Crustacean 2019, 92, 495–503. [Google Scholar] [CrossRef]
- Amat, F.; Hontoria, F.; Navarro, J.C.; Vieira, N.; Mura, G. Biodiversity loss in the genus Artemia in the Western Mediterranean region. Limnetica 2007, 26, 387–404. [Google Scholar]
- Lee, C.E. Evolutionary genetics of invasive species. Trends Ecol. Evol. 2002, 17, 386–391. [Google Scholar] [CrossRef]
- Lavergne, S.; Molofsky, J. Increased genetic variation and evolutionary potential drive the success of an invasive grass. Proc. Natl. Acad. Sci. USA 2007, 104, 3883–3888. [Google Scholar] [CrossRef]
- Kappas, I.; Abatzopoulos, T.J.; Van Hoa, N.; Sorgeloos, P.; Beardmore, J.A. Genetic and reproductive differentiation of Artemia franciscana in a new environment. Mar. Biol. 2004, 146, 103–117. [Google Scholar] [CrossRef]
- Hontoria, F.; Redón, S.; Maccari, M.; Varó, I.; Vavarro, C.J.; Ballell, L.; Amat, F. A revision of Artemia biodiversity in Macaronesia. Aquat. Biosyst. 2012, 8, 25. [Google Scholar] [CrossRef]
- Muñoz, J.; Gómez, A.; Figuerola, J.; Amat, F.; Rico, C.; Green, A.J. Colonization and dispersal patterns of the invasive American brine shrimp Artemia franciscana (Branchiopoda: Anostraca) in the Mediterranean region. Hydrobiologia 2014, 726, 25–41. [Google Scholar] [CrossRef]
- Dlugosch, M.K.; Parker, M.I. Founding events in species invasions: Genetic variation, adaptive evolution, and the role of multiple introductions. Mol. Ecol. 2008, 17, 431–449. [Google Scholar] [CrossRef] [PubMed]
- Vikas, P.A.; Sajeshkumar, N.K.; Thomas, P.C.; Chakraborty, K.; Vijayan, K.K. Aquaculture related invasion of the exotic Artemia franciscana and displacement of the autochthonous Artemia populations from the hypersaline habitats of India. Hydrobiologia 2012, 684, 129–142. [Google Scholar] [CrossRef]
- Hou, L.; Li, H.; Zou, X.; Yao, F.; Bi, X.; He, C. Population genetic structure and genetic differentiation of Artemia parthenogenetica in China. J. Shellfish Res. 2006, 25, 999–1005. [Google Scholar]
- Eimanifar, A.; Wink, M. Fine-scale population genetic structure in Artemia urmiana (Günther, 1890) based on mtDNA sequences and ISSR genomic fingerprinting. Org. Divers. Evol. 2013, 13, 531–543. [Google Scholar] [CrossRef]
- Eimanifar, A.; Marden, B.; Braun, M.S.; Wink, M. Analysis of the genetic variability of Artemia franciscana Kellogg, 1906 from the Great Salt Lake (USA) based on mtDNA sequences, ISSR genomic fingerprinting and biometry. Mar. Biodivers. 2015, 45, 311–319. [Google Scholar] [CrossRef]
- Asem, A.; Eimanifar, A.; Van Stappen, G.; Sun, S.C. The impact of one-decade ecological disturbance on genetic changes: A study on the brine shrimp Artemia urmiana from Urmia Lake, Iran. PeerJ 2019, 7, e7190. [Google Scholar] [CrossRef]
- Kumar, S.; Stecher, G.; Li, M.; Knyaz, C.; Tamura, K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 2018, 35, 1547–1549. [Google Scholar] [CrossRef]
- Bandelt, H.J.; Forster, P.; Rohl, A. Median-joining networks for inferring intraspecific phylogenies. Mol. Biol. Evol. 1999, 16, 37–48. [Google Scholar] [CrossRef]
- Maniatsi, S.; Baxevanis, A.D.; Kappas, I.; Deligiannidis, P.; Triantafyllidis, A.; Papakostas, S.; Bougiouklis, D.; Abatzopoulos, T.J. Is polyploidy a persevering accident or an adaptive evolutionary pattern? The case of the brine shrimp Artemia. Mol. Phylogenetics Evol. 2011, 58, 353–364. [Google Scholar] [CrossRef]
- Pritchard, J.K.; Stephens, M.; Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 2000, 155, 945–959. [Google Scholar] [PubMed]
- Falush, D.; Stephens, M.; Pritchard, J.K. Inference of population structure using multilocus genotype data: Dominant markers and null alleles. Mol. Ecol. Notes 2007, 7, 574–578. [Google Scholar] [CrossRef] [PubMed]
- Kopelman, N.M.; Mayzel, J.; Jakobsson, M.; Rosenberg, N.A.; Mayrose, I. Clumpak: A program for identifying clustering modes and packaging population structure inferences across K. Mol. Ecol. Resour. 2015, 15, 1179–1191. [Google Scholar] [CrossRef]
- Earl, D.A.; von Holdt, B.M. Structure Harvester: A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 2012, 4, 359–361. [Google Scholar] [CrossRef]
- Evanno, G.; Regnaut, S.; Goudet, J. Detecting the number of clusters of individuals using the software Structure: A simulation study. Mol. Ecol. 2005, 14, 2611–2620. [Google Scholar] [CrossRef]
- Peakall, R.; Smouse, P.E. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research—An update. Bioinformatics 2012, 28, 2537–2539. [Google Scholar] [CrossRef]
- Sayg, Y. Characterization of parthenogenetic Artemia populations from Camalti (Izmir, Turkey) and Kalloni (Lesbos, Greece): Survival, growth, maturation, biometrics, fatty acid profiles and hatching characteristics. Hydrobiologia 2004, 527, 227–239. [Google Scholar] [CrossRef]
- Kelts, K.; Shahrabi, M. Holocene sedimentalogy of hypersaline Lake Urmia, northwestern Iran. Paleogeography. Paleoclimatol. Paleoecol. 1986, 54, 105–130. [Google Scholar] [CrossRef]
- Djamali, M.; Kürschner, H.; Akhani, H.; De Beaulieu, J.L.; Amini, A.; Andrieu-Ponel, V.; Ponel, P.; Stevens, L. Palaeoecological significance of the spores of the liverwort Riella (Riellaceae) in a late Pleistocene long pollen record from the hypersaline Lake Urmia, NW Iran. Rev. Palaeobot. Palynol. 2008, 152, 66–73. [Google Scholar] [CrossRef]
- Hebert, P.D.N.; Ratnasingham, S.; Waard, J.R. Barcoding animal life: Cytochrome c oxidase subunit 1 divergences among closely related species. Proceedings of the Royal Society of London. Ser. B Biol. Sci. 2003, 270, 96–99. [Google Scholar] [CrossRef]
- Golani, D.G.; Azzurro, E.; Corsini-Foka, M.; Falautana, M.; Andaloro, F.; Bernardi, G. Genetic bottlenecks and successful biological invasions: The case of a recent Lessepsian migrant. Biol. Lett. 2007, 3, 541–545. [Google Scholar] [CrossRef] [PubMed]
- Rattanawannee, A.; Duangphakdee, O.; Chanchao, C.; Teerapakpinyo, C.; Warrit, N.; Wongsiri, S.; Oldroyd, B.P. Genetic Characterization of Exotic Commercial Honey Bee (Hymenoptera: Apidae) Populations in Thailand Reveals High Genetic Diversity and Low Population Substructure. J. Econ. Entomol. 2020, 113, 34–42. [Google Scholar] [CrossRef] [PubMed]
- Asem, A.; Sun, S.C. Morphological differentiation of seven parthenogenetic Artemia (Crustacea: Branchiopoda) populations from China, with special emphasis on ploidy degrees. Microsc. Res. Tech. 2016, 79, 258–266. [Google Scholar] [CrossRef] [PubMed]
Figure 1.
Map of Artemia sampling sites (1 = URM, 2 = LAGW, 3 = LAGE, 4 = QOM, 5 = MIG, 6 = MSH, 7 = MAH, 8 = NOG, 9 = INC, 10 = CAM, 11 = ABG, 12 = GAA, 13 = KBG, 14 = KOC; Abbreviations are listed in Table 1).
Figure 1.
Map of Artemia sampling sites (1 = URM, 2 = LAGW, 3 = LAGE, 4 = QOM, 5 = MIG, 6 = MSH, 7 = MAH, 8 = NOG, 9 = INC, 10 = CAM, 11 = ABG, 12 = GAA, 13 = KBG, 14 = KOC; Abbreviations are listed in Table 1).
Figure 2.
Phylogenetic tree of Artemia using COI sequences based on the ML approach. The number behind major nodes denotes bootstrap confidential values. Daphnia tenebrosa (HQ972028) was used as an outgroup. (URM: Artemia urmiana, TIB: Artemia tibetiana, SIN: Artemia sinica, FRA: Artemia franciscana, PER: Artemia prersimilis, SAL: Artemia salina, DI: Diploid parthenogenetic population, TRI: Triploid parthenogenetic population, TETRA: Tetraploid parthenogenetic population, PENTA: Pentaploid parthenogenetic population; abbreviations listed in Table 1).
Figure 2.
Phylogenetic tree of Artemia using COI sequences based on the ML approach. The number behind major nodes denotes bootstrap confidential values. Daphnia tenebrosa (HQ972028) was used as an outgroup. (URM: Artemia urmiana, TIB: Artemia tibetiana, SIN: Artemia sinica, FRA: Artemia franciscana, PER: Artemia prersimilis, SAL: Artemia salina, DI: Diploid parthenogenetic population, TRI: Triploid parthenogenetic population, TETRA: Tetraploid parthenogenetic population, PENTA: Pentaploid parthenogenetic population; abbreviations listed in Table 1).
Figure 3.
The relationship of COI haplotypes distribution among native populations (abbreviations listed in Table 1).
Figure 3.
The relationship of COI haplotypes distribution among native populations (abbreviations listed in Table 1).
Figure 4.
The relationship of COI haplotypes distribution among invasive A. franciscana populations (Abbreviations listed in Table 1).
Figure 4.
The relationship of COI haplotypes distribution among invasive A. franciscana populations (Abbreviations listed in Table 1).
Figure 5.
Contribution of genetic variation within and among populations for the examined populations by AMOVA, based on ISSR markers (A = whole examined populations, B = native populations, C = invasive A. franciscana).
Figure 5.
Contribution of genetic variation within and among populations for the examined populations by AMOVA, based on ISSR markers (A = whole examined populations, B = native populations, C = invasive A. franciscana).
Figure 6.
Clustering of genetic structures based on ISSR markers (A = whole examined populations, B = native populations, C = invasive A. franciscana; abbreviations listed in Table 1).
Figure 6.
Clustering of genetic structures based on ISSR markers (A = whole examined populations, B = native populations, C = invasive A. franciscana; abbreviations listed in Table 1).
Figure 7.
Proportion of genetic clusters for each locality in the STRUCTURE analysis (A = whole examined populations, B = native populations, C = invasive A. franciscana; abbreviations listed in Table 1).
Figure 7.
Proportion of genetic clusters for each locality in the STRUCTURE analysis (A = whole examined populations, B = native populations, C = invasive A. franciscana; abbreviations listed in Table 1).
Figure 8.
Principal Coordinates Analysis (PCoA) showing differentiation patterns among whole examined populations based on ISSR markers (abbreviations listed in Table 1).
Figure 8.
Principal Coordinates Analysis (PCoA) showing differentiation patterns among whole examined populations based on ISSR markers (abbreviations listed in Table 1).
Figure 9.
Principal Coordinates Analysis (PCoA) showing differentiation patterns among native populations based on ISSR markers (abbreviations listed in Table 1).
Figure 9.
Principal Coordinates Analysis (PCoA) showing differentiation patterns among native populations based on ISSR markers (abbreviations listed in Table 1).
Figure 10.
Principal Coordinates Analysis (PCoA) showing differentiation patterns among invasive A. franciscana populations based on ISSR markers (abbreviations listed in Table 1).
Figure 10.
Principal Coordinates Analysis (PCoA) showing differentiation patterns among invasive A. franciscana populations based on ISSR markers (abbreviations listed in Table 1).
Table 1.
Origin of Artemia samples from Iran and neighbor regions. (IPMB = Institute of Pharmacy and Molecular Biotechnology, Heidelberg University, Abb. = Abbreviation).
Table 1.
Origin of Artemia samples from Iran and neighbor regions. (IPMB = Institute of Pharmacy and Molecular Biotechnology, Heidelberg University, Abb. = Abbreviation).
| No. | Voucher Number (IPMB) | Abb. | Species/Population | Locality | Country | Geographic Coordinates | COI Accession Numbers |
|---|---|---|---|---|---|---|---|
| 1 | 57211 | URM | A. urmiana | Urmia Lake | Iran | 37°20′ E–45°40′ N | JX512748-808 [28] |
| 2 | 57223 | LAGW | Parthenogenetic | Western Lagoon around Urmia Lake | Iran | 37°15′ E–45°85′ N | KF691338-342 [2] |
| 3 | 57224 | LAGE | Parthenogenetic | Eastern Lagoon around Urmia Lake | Iran | 37°50′ E–46°40′ N | KF691343-345 [2] |
| 4 | 57225 | QOM | Parthenogenetic | Qom Salt Lake | Iran | 34°40′ E–51°80′ N | KF691367-372 [2] |
| 5 | 57226 | MIG | Parthenogenetic | Mighan Salt Lake | Iran | 34°20′ E–49°80′ N | KF691357-361 [2] |
| 6 | 57230 | MSH | A. franciscana | Mahshar port | Iran | 49°11′ E–30°33′ N | KF691351-356 [2] |
| 7 | 57228 | MAHR | A. franciscana | Maharlu Lake | Iran | 29°57′ E–52°14′ N | KF691347, 349-350 [2] |
| 8 | 57229 | NOG | A. franciscana | Nough Catchment | Iran | 30°60′ E–56°50′ N | KF691362-366 [2] |
| 9 | 57227 | INC | Parthenogenetic | Incheh Lake | Iran | 37°24′ E–54°36′ N | KF691333-337 [2] |
| 10 | 57292 | CAM | Parthenogenetic | Camalti Lake | Turkey | 27°08′ E–38°25′ N | KF691520-525; 527-529 [2] |
| 11 | 57255 | ABG | Parthenogenetic | Abu-Ghraib | Iraq | 44°30′ E–33°20′ N | KF691373-375 [2] |
| 12 | 57256 | GAA | A. franciscana | Garmat Ali | Iraq | 47°49′ E–30°30′ N | KF691376-383 [2] |
| 13 | 57258 | KBG | Parthenogenetic | Kara Bogaz Gol | Turkmenistan | 53°33′ E–41°17′ N | KF691530-532,534 [2] |
| 14 | 57257 | KOC | Parthenogenetic | Korangi Creek (Karachi coast) | Pakistan | 67°10′ E–24°48′ N | KF691442-445; 447-448 JX512748 [2] |
Table 2.
Species information and GenBank accession numbers for COI reference sequences.
| Species/Population | Abbreviation | Individual | Accession Numbers | Ref. |
|---|---|---|---|---|
| A. urmiana | URM | 4 | JX512748-751 | [28] |
| A. sinica | SIN | 4 | KF691298-301 | [2] |
| A. tibetiana | TIB | 4 | KF691215-218 | [2] |
| A. salina | SAL | 4 | KF691512-515 | [2] |
| A. persimilis | PER | 4 | DQ119647 HM998992 EF615594 EF615593 | [27] [33] [14] [14] |
| A. franciscana | FRA | 4 | KJ863440-443 | [2] |
| Diploid Pop. | DI | 4 | KU183949-952 | [3] |
| Triploid Pop. | TRE | 3 | HM998997-999 | [33] |
| Tetraploid Pop. | TETR | 4 | KU183954-957 | [3] |
| Pentaploid Pop. | PEN | 4 | KU183968-971 | [3] |
Table 3.
List of primers screened for Inter-Simple Sequence Repeats (ISSR) analysis.
| Primer | Sequence | GC (%) | Annealing Temperature (°C) | Amplification Pattern |
|---|---|---|---|---|
| ISSR1 | (AC)8T | 47.1 | 48–54 | Smear |
| ISSR2 | (CAC)5 | 66.7 | 48–54 | Smear |
| ISSR3 | (GACA)4 | 50 | 48–54 | Smear |
| ISSR4 | (AG)12 | 50 | 48–54 | Poor |
| ISSR5 | (TC)9 | 50 | 48–54 | Poor |
| ISSR6 | (GT)10 | 50 | 48–54 | Smear |
| ISSR7 | (CA)10A | 47.6 | 48–54 | Poor |
| ISSR8 | (GAA)5 | 33.3 | 48–54 | No amplification |
| ISSR9 | (CAG)6 | 66.7 | 48–54 | No amplification |
| ISSR10 | (GCCG)4 | 100 | 48–54 | No amplification |
| ISSR11 | (AG)8C | 52.9 | 48 | Good and sharp |
| ISSR12 | (AG)8YTa | 50 | 48 | Good and sharp |
| ISSR13 | (GA)9T | 47.4 | 50 | Good and sharp |
| ISSR14 | (TG)8G | 52.9 | 50 | Good and sharp |
| ISSR15 | (AC)8C | 52.9 | 49 | Good and sharp |
Table 4.
Genetic indices among examined populations according to ISSR markers.
| Pop. | N | Na | Ne | I | He | uHe | PPL | NB | NPB |
|---|---|---|---|---|---|---|---|---|---|
| KOC | 7 | 0.645 (0.062) | 1.102 (0.021) | 0.090 (0.017) | 0.059 (0.012) | 0.064 (0.012) | 17.76 | 71 | 0 |
| ABG | 7 | 0.743 (0.066) | 1.149 (0.024) | 0.131 (0.020) | 0.088 (0.013) | 0.095 (0.014) | 23.68 | 77 | 0 |
| LAGE | 3 | 0.914 (0.072) | 1.256 (0.031) | 0.208 (0.024) | 0.143 (0.017) | 0.171 (0.020) | 34.87 | 86 | 0 |
| LAGW | 7 | 0.829 (0.066) | 1.157 (0.024) | 0.140 (0.020) | 0.093 (0.014) | 0.100 (0.015) | 25.66 | 87 | 0 |
| KBG | 7 | 0.743 (0.068) | 1.161 (0.025) | 0.139 (0.020) | 0.094 (0.014) | 0.101 (0.015) | 25.00 | 75 | 0 |
| QOM | 7 | 0.638 (0.062) | 1.097 (0.020) | 0.087 (0.016) | 0.058 (0.011) | 0.062 (0.012) | 17.11 | 71 | 0 |
| MIG | 5 | 0.678 (0.067) | 1.150 (0.025) | 0.128 (0.020) | 0.087 (0.014) | 0.096 (0.015) | 23.03 | 68 | 0 |
| CAM | 7 | 0.559 (0.051) | 1.041 (0.014) | 0.036 (0.011) | 0.024 (0.008) | 0.026 (0.008) | 7.24 | 74 | 0 |
| INC | 7 | 0.658 (0.064) | 1.125 (0.022) | 0.110 (0.018) | 0.074 (0.013) | 0.080 (0.014) | 19.74 | 70 | 0 |
| URM | 5 | 0.783 (0.072) | 1.200 (0.027) | 0.173 (0.022) | 0.117 (0.015) | 0.130 (0.017) | 30.26 | 73 | 0 |
| MAH | 2 | 0.822 (0.066) | 1.181 (0.025) | 0.155 (0.021) | 0.106 (0.015) | 0.142 (0.020) | 25.66 | 86 | 1 |
| NOG | 7 | 1.013 (0.071) | 1.244 (0.030) | 0.208 (0.023) | 0.140 (0.016) | 0.151 (0.017) | 38.82 | 95 | 0 |
| MSH | 7 | 1.066 (0.066) | 1.223 (0.028) | 0.193 (0.022) | 0.129 (0.015) | 0.139 (0.016) | 36.84 | 106 | 0 |
| GAA | 5 | 0.921 (0.067) | 1.206 (0.028) | 0.172 (0.022) | 0.117 (0.015) | 0.130 (0.017) | 30.26 | 94 | 0 |
| Mean | 5.9 (0.035) | 0.787 (0.018) | 1.164 (0.007) | 0.141 (0.005) | 0.095 (0.004) | 0.106 (0.004) | 25.42 (2.28%) | - | - |
Pop. = Population, N = number of individuals, Na = number of Different Alleles, Ne = number of Effective Alleles, I = Shannon’s Information Index, He = Expected Heterozygosity, uHe = Unbiased Expected Heterozygosity, PPL = Percentage of Polymorphic Loci, NB = number of bands, NPB = number of private bands.
Table 5.
Genetic indices among native populations according to ISSR markers.
| Population | N | Na | Ne | I | He | uHe | PPL | NB | NPB |
|---|---|---|---|---|---|---|---|---|---|
| KOC | 7.000 | 0.731 (0.067) | 1.115 (0.023) | 0.102 (0.019) | 0.067 (0.013) | 0.073 (0.014) | 20.15 | 71 | 2 |
| ABG | 7.000 | 0.843 (0.071) | 1.169 (0.027) | 0.148 (0.022) | 0.100 (0.015) | 0.107 (0.016) | 26.87 | 77 | 4 |
| LAGE | 3.000 | 1.037 (0.075) | 1.291 (0.034) | 0.236 (0.026) | 0.162 (0.018) | 0.195 (0.022) | 39.55 | 86 | 1 |
| LAGW | 7.000 | 0.940 (0.069) | 1.178 (0.027) | 0.158 (0.022) | 0.106 (0.015) | 0.114 (0.016) | 29.10 | 87 | 4 |
| KBG | 7.000 | 0.843 (0.073) | 1.183 (0.028) | 0.158 (0.023) | 0.107 (0.015) | 0.115 (0.017) | 28.36 | 75 | 0 |
| QOM | 7.000 | 0.724 (0.066) | 1.110 (0.023) | 0.099 (0.018) | 0.065 (0.013) | 0.070 (0.014) | 19.40 | 71 | 0 |
| MIG | 5.000 | 0.769 (0.073) | 1.170 (0.027) | 0.145 (0.022) | 0.098 (0.015) | 0.109 (0.017) | 26.12 | 68 | 3 |
| CAM | 7.000 | 0.634 (0.055) | 1.046 (0.016) | 0.041 (0.013) | 0.027 (0.009) | 0.029 (0.009) | 8.21 | 74 | 0 |
| INC | 7.000 | 0.746 (0.069) | 1.142 (0.025) | 0.125 (0.021) | 0.084 (0.014) | 0.091 (0.015) | 22.39 | 70 | 1 |
| URM | 5.000 | 0.888 (0.077) | 1.227 (0.029) | 0.196 (0.024) | 0.133 (0.017) | 0.148 (0.018) | 34.33 | 73 | 3 |
| Mean | 6.200 (0.036) | 0.816 (0.022) | 1.163 (0.008) | 0.141 (0.007) | 0.095 (0.005) | 0.105 (0.005) | 25.45 (2.74) | - | - |
Pop. = Population, N = number of individuals, Na = number of Different Alleles, Ne = number of Effective Alleles, I = Shannon’s Information Index, He = Expected Heterozygosity, uHe = Unbiased Expected Heterozygosity, PPL = Percentage of Polymorphic Loci, NB = number of bands, NPB = number of private bands.
Table 6.
Genetic indices among invasive A. franciscana populations according to ISSR markers.
| Population | N | Na | Ne | I | He | uHe | PPL | NB | NPB |
|---|---|---|---|---|---|---|---|---|---|
| MAH | 2.000 | 0.992 (0.071) | 1.219 (0.029) | 0.187 (0.025) | 0.128 (0.017) | 0.171 (0.023) | 30.95 | 86 | 3 |
| NOG | 7.000 | 1.222 (0.073) | 1.295 (0.034) | 0.251 (0.026) | 0.169 (0.018) | 0.182 (0.019) | 46.83 | 95 | 6 |
| MSH | 7.000 | 1.286 (0.065) | 1.269 (0.033) | 0.233 (0.025) | 0.156 (0.018) | 0.168 (0.019) | 44.44 | 106 | 8 |
| GAA | 5.000 | 1.111 (0.070) | 1.249 (0.033) | 0.207 (0.025) | 0.141 (0.018) | 0.157 (0.020) | 36.51 | 94 | 5 |
| Mean | 5.250 (0.091) | 1.153 (0.035) | 1.258 (0.016) | 0.220 (0.013) | 0.149 (0.009) | 0.169 (0.010) | 39.68 (3.65) | - | - |
Pop. = Population, N = number of individuals, Na = number of Different Alleles, Ne = number of Effective Alleles, I = Shannon’s Information Index, He = Expected Heterozygosity, uHe = Unbiased Expected Heterozygosity, PPL = Percentage of Polymorphic Loci, NB = number of bands, NPB = number of private bands.
Table 7.
Pairwise Population Matrix of Nei Genetic Distance among invasive A. franciscana populations.
Table 7.
Pairwise Population Matrix of Nei Genetic Distance among invasive A. franciscana populations.
| Population | KOC | ABG | LAGE | LAGW | KBG | QOM | MIG | CAM | INC |
|---|---|---|---|---|---|---|---|---|---|
| ABG | 0.162 | - | - | - | - | - | - | - | - |
| LAGE | 0.167 | 0.175 | - | - | - | - | - | - | - |
| LAGW | 0.193 | 0.127 | 0.190 | - | - | - | - | - | - |
| KBG1 | 0.156 | 0.117 | 0.142 | 0.111 | - | - | - | - | - |
| QOM | 0.182 | 0.131 | 0.171 | 0.135 | 0.099 | - | - | - | - |
| MIG | 0.217 | 0.185 | 0.171 | 0.212 | 0.124 | 0.148 | - | - | - |
| CAM | 0.362 | 0.346 | 0.249 | 0.358 | 0.279 | 0.354 | 0.331 | - | - |
| INC | 0.233 | 0.165 | 0.184 | 0.223 | 0.149 | 0.176 | 0.091 | 0.351 | - |
| URM | 0.219 | 0.194 | 0.165 | 0.190 | 0.141 | 0.174 | 0.194 | 0.351 | 0.211 |
Table 8.
Pairwise Population Matrix of Nei Genetic Distance among native populations.
| Population | MAH | NOG | MAH |
|---|---|---|---|
| NOG | 0.143 | - | - |
| MSH | 0.145 | 0.144 | - |
| GAA | 0.198 | 0.170 | 0.152 |
Table 9.
Molecular variation (within and among populations) for examined populations by AMOVA based on ISSR markers.
Table 9.
Molecular variation (within and among populations) for examined populations by AMOVA based on ISSR markers.
| Whole Populations | |||||
|---|---|---|---|---|---|
| Source | df | SS | MS | Est. Var. | % |
| Among Pops | 13 | 1673.318 | 128.717 | 20.265 | 69% |
| Within Pops | 69 | 639.405 | 9.267 | 9.267 | 31% |
| Total | 82 | 2312.723 | - | 29.532 | 100% |
| Source | df | SS | MS | Est. Var. | % |
| Native Populations | |||||
| Among Pops | 9 | 627.912 | 69.768 | 10.006 | 55% |
| Within Pops | 52 | 418.362 | 8.045 | 8.045 | 45% |
| Total | 61 | 1046.274 | - | 18.052 | 100% |
| A. franciscana | |||||
| Source | df | SS | MS | Est. Var. | % |
| Among Pops | 3 | 117.338 | 39.113 | 5.239 | 29% |
| Within Pops | 17 | 221.043 | 13.003 | 13.003 | 71% |
| Total | 20 | 338.381 | - | 18.241 | 100% |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Eimanifar, A.; Asem, A.; Wang, P.-Z.; Li, W.; Wink, M. Using ISSR Genomic Fingerprinting to Study the Genetic Differentiation of Artemia Leach, 1819 (Crustacea: Anostraca) from Iran and Neighbor Regions with the Focus on the Invasive American Artemia franciscana. Diversity 2020, 12, 132. https://doi.org/10.3390/d12040132
AMA Style
Eimanifar A, Asem A, Wang P-Z, Li W, Wink M. Using ISSR Genomic Fingerprinting to Study the Genetic Differentiation of Artemia Leach, 1819 (Crustacea: Anostraca) from Iran and Neighbor Regions with the Focus on the Invasive American Artemia franciscana. Diversity. 2020; 12(4):132. https://doi.org/10.3390/d12040132
Chicago/Turabian StyleEimanifar, Amin, Alireza Asem, Pei-Zheng Wang, Weidong Li, and Michael Wink. 2020. "Using ISSR Genomic Fingerprinting to Study the Genetic Differentiation of Artemia Leach, 1819 (Crustacea: Anostraca) from Iran and Neighbor Regions with the Focus on the Invasive American Artemia franciscana" Diversity 12, no. 4: 132. https://doi.org/10.3390/d12040132
APA StyleEimanifar, A., Asem, A., Wang, P.-Z., Li, W., & Wink, M. (2020). Using ISSR Genomic Fingerprinting to Study the Genetic Differentiation of Artemia Leach, 1819 (Crustacea: Anostraca) from Iran and Neighbor Regions with the Focus on the Invasive American Artemia franciscana. Diversity, 12(4), 132. https://doi.org/10.3390/d12040132
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
