1. INTRODUCTION
Bivalves are widespread mollusks distributed in freshwater and marine ecosystems. These mollusks are sedentary animals attached to the substratum or firmly cemented in lakes and rivers. Freshwater bivalves are able to feed on microorganisms such as diatoms, bacteria, and phytoplankton. They are also considering as a food source for many aquatic animals such as herons, fishes, and other invertebrates [1]. Freshwater bivalves are important for ecosystem services such as nutrient cycling, water filtration, and reduction of water turbidity [2]. Spathopsis rubens was common in the Nile and its main canals from upper to lower Egypt and inhabit all types of water bodies, swiftly and slowly running or stagnant water [3]. Threats to freshwater bivalves include pollution and climate changes, but human disturbance is the main factor affecting freshwater bivalves. These factors have resulted in a decrease in freshwater bivalve’s diversity and a change in their community structure [4–6].
The utility of simple sequence repeats (SSR) or microsatellites technique had been established for a wide range of applications, such as conservation biology, systematic and molecular ecology [7]. In research, the microsatellite DNA markers have been used to detect genetic variations and to estimate population structure in organisms [8]. Having such techniques to detect the differences in the levels of genetic variety among populations of organisms, especially the aquatic ones could shed the light on the evolutionary potential for dealing with effects of infection with pathogens and changes in habitat [9–12]. Applications of inter simple sequence repeats (ISSR) markers for population studies were reported for different species of mollusks including the amethyst gem clam Gemma gemma [13], the giant Mediterranean limpet Patella furruginea [14], the giant clam Tridacna gigas [15], Helix pomatia [16], and Cepaea vindobonensis [17]. The present work investigated the morphometric measurement and water quality of four different populations of freshwater clam S. rubens along Al-Mahmoudia irrigation canal at Damanhour, Egypt. In addition, the study was extended to address the genetic differentiation and phylogenetic relationship between the collected bivalves using ISSR markers.
2. MATERIALS AND METHODS
2.1. Study areas and samples collection
Al-Mahmoudia canal is found close to the northern edge of the western delta in Beheira Governorate, Egypt. The total length of the canal is 77 km from the Rosetta branch of the Nile down to the Mediterranean Sea at Alexandria [18]. It has economic importance of the people in Beheira and Alexandria Governorates. It has been exploited to support fisheries, agriculture, industry, public water supply, hydroelectric power, and recreation. Al-Mahmoudia canal possesses three different sources of water; two of them are freshwater sources which come from Rosetta branch via El-ATF pump stations at the head of the canal and Al-Khandaq Al-Sharqi canal, and the third one is drainage water from Zarkon drain via Edku irrigation pump station [18]. Due to the different water resources that poured in Al-Mahmoudia canal, the pollutants lead to a significant deterioration of the quality of the water in the canal [19]. Spathopsis rubens were collected during July 2018 from four sites on Al-Mahmoudia irrigation canal (Fig. 1). These sites are Zaweyt Ghazal (first location), Ezbet Siknidah (second location), Ezbet Qabil (third location), and Manshat Hamour (fourth location). The specimens collected from the four locations were taken to the laboratory and dead or damaged specimens were eliminated. The morphometric characteristics of the collected samples were determined by measuring the shell length (L), width (W), and height (H) to the nearest millimeter (mm) with Vernier calipers. Total wet weights (g) were also determined. The soft tissues were separated and preserved at −80°C until used.
2.2. Water quality determination
Physicochemical parameters such as dissolved oxygen, pH, temperature, and turbidity were detected in collected water samples by a water quality meter (AQUAREAD, AP-800). The data were assessed using the one-way analysis of variance Significant differences were indicated when p < 0.05. Tukey pairwise comparisons were used to compare the difference between group mean values.
2.3. Multivariate analysis
Canonical correspondence analysis (CCA, PAST, software V3.2) [20,21] was used as correspondence analysis of a site/species matrix where each location has given values for each one of the water quality factors (pH, dissolved oxygen, turbidity, and temperature). The ordination axes are linear combinations of the environmental variables. The ordinations given as site scores environmental variables are plotted as correlations with site scores. Scaling 2 emphasizes relationships between morphometric parameters.
2.4. DNA extraction and purification
The DNA was extracted from bivalves according to Attaran-Fariman and Javid [22] with slight modification using a standard phenol-chloroform extraction [23].
2.5. DNA Quantification and purity measurement
A NanoDrop ND-200 Spectrophotometer (AOSHENG) used to quantify the DNA in all extracts. The purity of the elution (protein contaminants) showed by the absorbance ratio at 260 nm/280 nm and humic acids showed by the absorbance ratio at 260 nm/230 nm.
 | Figure 1: Map showing the collection sites (Zawyet Ghazal: location 1, Ezbet Siknidah: location 2, Ezbet Qabil: location 3, and Manshaat Hamour location 4). [Click here to view] |
2.6. Inter-simple sequence repeat (ISSR)
The template quality of extracted genomic DNA was tested by ISSR by polymerase chain reaction (PCR). The sequence of the primer used for ISSR that was synthesized by Jena Bioscience Company; Germany (Table 1).
2.7. PCR amplification conditions of ISSR primers
The reaction mixture for ISSR amplification assay had a total volume of 18 μl, containing 50 ng genomic DNA, 1 μl of single primer ISSR (Table 1), 9 μl Taq DNA polymerase (Taq polymerase Fast Gene, Ready Mix PCR Kit), and 7 μl PCR-grade water (Jena Bioscience). Each amplification reaction was performed using a single primer and repeated twice to verify band autosimilarity. PCR reactions were performed using a thermocycler (TC-3000) (TECHNE), programmed for 1 cycle of denaturation at 94°C for 4 minutes, followed by 40 cycles of denaturation at 94°C for 1 minute, annealing at 49°C for 1.30 minutes, extension at 72°C for 3 minutes, and a final extension 1 cycle at 72°C for 5 minutes, a final hold at 20°C. The amplification products of each sample for each ISSR primer, along with 8 μl of a 100 bp DNA Ladder H3 RTU, were size fractionated on 2% agarose gel electrophoresis (Mupid–One, JAPAN) at 100 volts for 30 minutes. Gel documentation system was used for molecular data analysis (NIPPON GENETICS EUROPE). The sizes of DNA fragments of the amplified products were estimated by comparing the DNA bands with that of the DNA ladder
2.8. ISSR data analysis
Only the reproducible and consistent bands were recorded manually for further analysis. Amplified products scored for band presence (1) or absence (0) and a binary qualitative data matrix was constructed. Fragments which could not be unambiguously recognized were not scored for analysis. Analysis of molecular variance was performed to analyze genetic distance among samples using the PAST program. A cluster dendrogram based on similarity matrix obtained with unweighted pair group method using the arithmetic average (UPGMA) was constructed based on the Nei’s (1978) genetic distances for determining the genetic relationship among populations.
 | Table 1: Characteristics of ISSR markers used for the analysis of S. rubens populations. [Click here to view] |
 | Table 2: Length, height, width, and total weight of S. rubens collected from investigated locations. [Click here to view] |
3. RESULTS
The morphometric characters of S. rubens collected from Zaweyt Ghazal (first location), Ezbet Siknidah (second location), Ezbet Qabil (third location), and Manshat Hamour (fourth location) on Al-Mahmoudia canal are summarized in Table 2. The length and height of the collected samples from the different locations showed slight significant differences. The length of the samples ranged from 11.12 to 11.97 cm and the height ranged from 6.02 to 6.64 cm, while there are no statistical differences between the total weight and width of the samples.
The water quality parameters including temperature, dissolved oxygen, pH, and turbidity of the samples collected from the investigated locations are summarized in Table 3. The result showed that there was no variation in the water temperature among different locations, while the turbidity, dissolved oxygen, and pH of the water samples were changed according to locations. The water sample of the first location recorded the highest value of turbidity and dissolved oxygen and the lowest value of pH. Figures 2 and 3 showed that the high degree of similarity was reported between the second and fourth location and the samples collected from the first location were grouped in another cluster. High degree of correlation between temperature and total weight, as well as between height and length, was obtained in samples collected from the third location; however, there is no correlation between that parameters and pH, turbidity and dissolved oxygen. Statistical analysis also showed that the width of samples has a degree of positive correlation with pH and negative correlation with turbidity and dissolved oxygen.
ISSR analysis for 10 primers (ISSR M1, ISSR M2, ISSR M3, ISSR M8, ISSR M9, ISSR M12, ISSR M17, ISSR F2, ISSR F4, and ISSR F9) was used to detect the genetic diversity of S. rubens collected from four sites on Al-Mahmoudia irrigation canal. The range of bands number of monomorphic and polymorphic bands produced by different 10-ISSR primers is shown in Table 4. These results indicated that there were 49 polymorphic bands produced by the ten primers. The primers ISSR M1, ISSR M 3, ISSR M 17, and ISSR F2 showed 3-polymorphic bands, the primers ISSR M2, ISSR M8, and ISSR F4 showed 5-polymorphic band, while the primer ISSR M9 and ISSR F9 showed 7-polymorphic bands. The primer ISSRM12 recorded the highest number of polymorphic bands (8).
 | Table 3: Environmental factors of water samples collected from investigated locations. [Click here to view] |
 | Figure 2: Biplots of the canonical correspondence analysis models for the water quality factors matrix: Locations, location (1) Zawyet Ghazal, location (2) Ezbet Siknidah, location (3) Ezbet Qabil, and location (4) Monshaat Hamour. Water quality factors are: pH, dissolved oxygen (DO), turbidity (Tu), and temperature (Temp). [Click here to view] |
Cluster dendrogram based on the similarity matrix obtained with UPGMA and the relationships between samples collected from four locations were shown in Figure 4. The phylogenetic tree analysis revealed that the samples collected from location 1 were grouped in one cluster while the samples collected from locations 2, 3, and 4 were grouped in another one. The second cluster showed that samples collected from locations 2 and 3 were closely related to each other, followed by samples collected from locations 3 and 4.
The similarity and distance indices bands in samples collected from four locations were shown in Table 5. This table shows that cluster of samples collected from locations 2 and 3 recorded the highest similarity and distance indices at a distance of 0.60859, while samples collected from locations 1 and 3 recorded the lowest similarity and distance indices at a distance of 0.1716.
4. DISCUSSION
The current study was conducted to investigate the morphometric and genetic variations of different populations of freshwater clam S. rubens along Al-Mahmoudia irrigation canal at Damnhour, Egypt. Environmental factors, such as temperature, dissolved oxygen, and water turbidity, significantly affect the distribution of benthic community structure [24,25]. The obtained data showed that turbidity and dissolved oxygen of water samples collected from the first location were higher than the values of water samples collected from the other locations and the samples of S. rubens collected from the first location were grouped in one cluster while the samples collected from the other locations were grouped in another one. Cao et al. [26] reported that a positive correlation was found between the dissolved oxygen and macrozoobenthos diversity and also indicated that high turbidity of water could provide rich food sources for the reproduction of bivalves.
 | Figure 3: Dendrograms of cluster analysis based on the degree of similarity relationship between samples of S. rubens collected from different sites under investigation (location (1) Zawyet Ghazal, location (2) Ezbet Siknidah, location (3) Ezbet Qabil, and location (4) Monshaat Hamour. [Click here to view] |
 | Table 4: Number of amplified bands (monomorphic, polymorphic) and percentage of polymorphism) in S. rubens produced by each primer. [Click here to view] |
The present study shows that a high degree of correlation between temperature and total weight, height and length, in samples collected from the third location. This agrees with the previous finding of Saucedo et al. [27] who showed that temperature is considered as a major environmental factor influencing in the physiological process of oyster and suggested that high temperature within tolerance limits associated with reducing feeding and poor growth.
 | Figure 4: Dendrogram representing the genetic relationships of S. rubens from different sites under investigation using UPGMA cluster analysis of genetic similarity coefficients generated from studied 10 `ISSR primers. [Click here to view] |
 | Table 5: Similarity and distance indices bands in the 10 genotypes of S. rubens under test. |
Genetic variation is a proper approach used for determining the biological potential of organisms. It has shown that organisms with high levels of genetic variation were able to adapt better with changes in its surroundings environments [28]. In contrast, reduction of genetic variation could cause more sensitivity to environmental changes which in turn led to the extinction of a species [17]. Moreover, it may affect growth and reproduction [29]. Hence, the genetic variability maintenance is crucial for the conservation of a species [30]. ISSRs have become useful dominant markers for genetic investigations due to their high polymorphism, reproducibility, technical simplicity, and cost-effectiveness [31].
In the present study, the genetic structure by using ISSR analysis of S. rubens collected from four sites situated on Al-Mahmoudia irrigation canal, Egypt, showed that there were 49 polymorphic bands produced by the primers used in this study. The phylogenetic tree analysis revealed that the genotypes of samples collected from location 1 were grouped in one cluster while the genotypes of samples collected from locations 2, 3, and 4 grouped in another cluster. Along the coast of China, Hou et. al. [32] investigated seven different populations of Mactra veneriformes (210 individual) by ISSR fingerprinting [32]. Furthermore, Varela et al. [33] indicated that this technique could be useful to define parentage and relatedness in mussels.
A few investigations of bivalves inhabiting similar environments, such as the surf clams Donax serra and D. deltoides [34,35], the Arctic surf clam Mactromeris polynyma [36], and the soft-shell clam Mya arenaria [37], have revealed limited genetic differences among populations separated by thousands of kilometers. Other studies revealed some differences among populations but associated with a physical barrier (Coelomactra antiquate) [38], a biogeographic break (Merceneria merceneria), or isolation by distance (Mactra veneriformis) [39].
It was concluded that the correlation between environmental factors and morphometric analysis and the genetic variation observed in the ISSR markers will be useful for future studies on the population structure of S. rubens and for aquaculture of this species.
CONFLICT OF INTEREST
All authors declare that there was no conflict of interest.
REFERENCES
1. Katsallah GM, Rukayya M, Sambo D, Gaba T. Comparative metal analysis of the soft tissues of three species of Anodonta (Class: Bivalvia) from Kubanni Lake in Zaria Nigeria. J Environ Sci Toxicol Food 2013;6:18–23.
2. Hinzmann M, Lopes-Lima M, Teixeira A, Varandas S, Sousa R, Lopes A, et al. Reproductive cycle and strategy of Anodonta anatina (L.,1758): Notes on hermaphroditism. J Exp Zool A: Ecol Genet Physiol 2013;319(7):378–90.
3. Ibrahim AM, Bishai HM, Khalil MT. Freshwater molluscs of Egypt. Publication of National Biodiversity Unit, Egyptian Environmental Affairs Agency, EEAA, Cairo, Egypt, pp 1–145, 1999.
4. Wu XP. Studies on freshwater mollusca in mid-reaches of Changjiang River. PhD Thesis, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan, China, 1998.
5. Zhang MH, Xu L, Xie GL, Liu YB, Liu XM, Song SC, et al. The conservation, distribution and diversity of freshwater mussels in the Poyang Lake Basin. Mark Sci. 2013;37(8):114–24.
6. Zieritz A, Bogan AE, Froufe E, Klishko O, Kondo T, Kovitvadhi U, et al. Diversity, biogeography and conservation of freshwater mussels (Bivalvia: Unionida) in East and Southeast Asia. Hydrobiologia 2018;810(1):29–44.
7. Gharbawi WY. Molecular Genetics Characterization of Plectropomus areolatus Samples Collected from Jeddah Coast Using ISSR Analysis. World Appl Sci J. 2015;33(4):536–41.
8. An HS, Lee JW. Development of microsatellite markers for the Korean mussel, Mytilus coruscus (Mytilidae) using Next-Generation Sequencing. Int J Mol Sci 2012;13(8):10583–93.
9. Freeland JL, Petersen SD, Kirk H. Molecular ecology. 2nd edition, Wiley-Blackwell, Oxford, UK, 2011; doi:10.1002/9780470979365
10. Liu XH, Yao YG. Characterization of 12 polymorphic microsatellite markers in the Chinese tree shrew (Tupaia belangeri chinensis). Zool Res. 2013;34(2, E2): E62–8.
11. Wu SZ, Guan YY, Huang XD, He MX. Development of 25 novel microsatellite loci and genetic variation analysis in breeding populations of the pearl oyster, Pinctada fucata. J World Aquacult Soc 2013;44(4):600–9.
12. MacDonald HC, Ormerod SJ, Bruford SW. Enhancing capacity for freshwater conservation at the genetic level: A demonstration using three stream macro-invertebrates. Aquat Conserv 2017;27(2):452–61.
13. Casu M, Maltagliati F, Cossu P, Lai T, Curini-Galletti M, Castelli A, Commito J. Fine-grained spatial genetic structure in the bivalve Gemma gemma from Maine and Virginia (USA), as revealed by inter-simple sequence repeat markers. J Exp Mar Biol Ecol 2005;(325):46–54.
14. Casu M, Casu D, Lai T, Cossu P, Curini-Galletti M. Inter-simple sequence repeat markers reveal strong genetic differentiation among population of the endangered mollusk Patella furruginea (Gasteopoda: Patellidae) from two Sardinian marine protected areas. Mar Biol 2006;149(5):1163–74.
15. Evans BS, Jerry DR. Population genetic structure of giant clams, Tridacna gigas (Family: Tridacnidae), on the Great Barrier Reef. J Fish Aquat Sci 2006;1(3):235–43.
16. Snegin EA, Artemchuk O. Population genetic structure of Helix pomatia L.(Mollusca: Pulmonata) from the southeastern and eastern parts of the rang. Russ J Genet 2017;53(3):348–57.
17. Evans RD, Van Herwerden L, Russ GR, Frisch AJ. Strong genetic but not spatial subdivision of two reef fish species targeted by fishers on the Great Barrier Reef. Fish Res 2010;(102):16–25.
18. Hoevenaars J, Slootweg R. Natural resources perspective working paper. In IPTRID. Toward Integrated Planning of Irrigation and Drainage in Egypt. In Support of the Integrated Irrigation Improvement and Management Project (IIIMP). Final Report. Rome, Italy, FAO, 2005. Available via http://www.fao.org/docrep/008/a0021e/a0021e00.htm (Accessed 9 March 2007).
19. Abdullah A, Hussona E. Water quality assessment of Mahmoudia canal in northern west of Egypt. J Poll Eff Cont 2014;2(121):2.
20. Legendre P, Legendre L. Numerical ecology, 2nd English edition, Elsevier, Amsterdam, p 853, 1998.
21. Hammer Ø, Harper DT, Ryan PD. PAST: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontol Electron 2001;4(1):1–9.
22. Attaran-Fariman G, Javid P. The best DNA extraction method from sea anemone species with the mucosal tissue. Indian J Geo-Mar Sci 2015;44(7):1011–16.
23. Taggart JB, Hynes RA, Prodohl PA, Ferguson AA. simplified protocol for routine total DNA isolation from salmonid fishes. J Fish Biol 1992;40(6):963–65.
24. Zhao FB, Chen PP, Xu HT, Zhang W, Feng H, Wang LQ. The relationship between the environmental factors and community structure of benthos in Shanghai river channel. J Ecol Environ 2016;25(8):1361–68.
25. Negi RK, Mamgain S. Seasonal variation of benthic macro-invertebrates from Tons River of Garhwal Himalaya Uttarakhand. Pak J Biol Sci 2013;16(22):1510–16.
26. Cao YL, Liu XJ, Wu RW, Xue T, Li L, Zhou CH, et al. Conservation of the endangered freshwater mussel Solenaia carinata (Bivalvia, Unionidae) in China. Nat Conserv 2018;(26):33–53.
27. Saucedo PE, Ocampo L, Monteforte M, Bervera H. Effect of temperature on oxygen consumption and ammonia excretion in the Calafia mother of pearl oyster, Pinctata mazatlanica (Hanley, 1856). Aquaculture 2004(299):377–87.
28. 28. Alam S, Islam S, Alam S. DNA fingerprinting of the freshwater mud eel, Monopterus cuchia (Hamilton) by randomly amplified polymorphic DNA (RAPD) marker. Int J Biotech Biochem 2010;6(2):271–8.
29. Dixon TJ, Coman GJ, Arnold J, Sellars MJ, Lyons RE, Dierens L, Preston N P, Li Y. Shifts in genetic diversity during domestication of Black Tiger shrimp, Penaeus monodon, monitored using two multiplexed microsatellite systems. Aquaculture 2008;283:1–6.
30. Barroso R, Wheeler P, LaPatra S, Drew R, Thorgaard G. QTL for IHNV resistance and growth identified in a rainbow (Oncorhynchus mykiss) x Yellowstone cutthroat (Oncorhynchus clarki bouvieri) trout cross. Aquaculture 2008;(277):156–63.
31. Zietkiewicz E, Rafalski A, Labuda D. Genome fingerprinting by simple sequence repeat (SSR)-anchored polymerase chain reaction amplification. Genomics 1994;20(2):176–83.
32. Hou L, Lü H, Zou X, Bi X, Yan D, He C. Genetic characterizations of Mactra veneriformis (Bivalve) along the Chinese coast using ISSR-PCR markers. Aquaculture 2006;261(3):865–71.
33. Varela MA, Gonza´lez-Tizo´n A, Marin˜as L, Martı´nez-Lage A. Genetic Divergence Detected by ISSR Markers and Characterization of Microsatellite Regions in Mytilus Mussels. Biochem Genet 2007;45:565–78.
34. Murray-Jones SE, Ayre DJ. High levels of gene flow in the surf bivalve Donax deltoids (Bivalvia: Donacidae) on the east coast of Australia. Mar Biol 1997;1(128):83–9.
35. Laudien J, Bery T, Arntz WE. Population structure growth and production of the surf clam Donax serra (Bivalvia: Donacidae) on two Namibian sandy beaches. Estuar Coast Shelf Sci 2003;585:105–15.
36. Cassista MR, Hart MW. Spatial and temporal genetic homogeneity in the Arctic surf clam (Mactromeris polynyma). J Mar Biol 2007;152(3):569–79.
37. Strasser A, Barber H. Limited genetic variation and structure in soft shell clams (Mya arenaria) across their native and introduced range. Conserv Genet 2009;10(4):803–14.
38. Kong LF, Li Q, Qiu ZX. Genetic and morphological differentiation in the clam Coelomactra antiquate (Bivalvia : Veneroida) along the coast of china. J Exp Mar Biol Ecol 2007;343(1):110–17.
39. Baker P, Austin JD, Bowen BW, Baker SM. Range-Wide population structure and history of the northern quahog (Merceneria merceneria) inferred from mitochondrial DNA sequence data. J Mar Sci 2008;65(2):155–63.