Microbial community analysis of Acropora palamata mucus swabs, water and sediment samples from Hawksnest Bay, St. John, U.S. Virgin Islands

Colonies of the scleractinian coral Acropora palmata, listed as threatened under the US Endangered Species Act in 2006, have been monitored in Hawksnest Bay, within Virgin Islands National Park, St. John, from 2004 through 2010 by scientists with the US Geological Survey, National Park Service, and the University of the Virgin Islands. The focus has been on documenting the prevalence of disease, including white band, white pox (also called patchy necrosis and white patches), and unidentified diseases (Rogers et al., 2008; Muller et al., 2008). In an effort to learn more about the pathologies that might be involved with the diseases that were observed, samples were collected from apparently healthy and diseased colonies in July 2009 for analysis. Two different microbial assays were performed on Epicentre Biotechnologies DNA swabs containing A. palmata coral mucus, and on water and sediment samples collected in Hawksnest Bay. Both assays are based on polymerase chain reaction (PCR) amplification of portions of the small rRNA gene (16S). The objectives were to determine 1) if known coral bacterial pathogens Serratia marcescens (Acroporid Serratiosis), Vibrio coralliilyticus (temperature-dependent bleaching, White Syndrome), Vibrio shiloi (bleaching, necrosis), and Aurantimonas coralicida (White Plague Type II) were present in any samples, and 2) if there were any differences in microbial community profiles of each healthy, unaffected or diseased coral mucus swab. In addition to coral mucus, water and sediment samples were included to show ambient microbial populations. In the first test, PCR was used to separately amplify the unique and diagnostic region of the 16S rRNA gene for each of the coral pathogens being screened. Each pathogen test was designed so that an amplified DNA fragment could be seen only if the specific pathogen was present in a sample. A positive result was indicated by bands of DNA of the appropriate size on an agarose gel, which separates DNA fragments based on the size of the molecule. DNA from pure cultures of each of the pathogens was used as a positive control for each assay.

Nuclear and mitochondrial DNA markers for specific identification of istiophorid and xiphiid billfishes

Independent molecular markers based on mitochondrial and nuclear DNA were developed to provide positive identification of istiophorid and xiphiid billfishes (marlins, spearfishes, sailfish, and swordfish). Both classes of markers were based on amplification of short segments (<1.7 kb) of DNA by the polymerase chain reaction and subsequent digestion with informative restriction endonucleases. Candidate markers were evaluated for their ability to discriminate among the different species and the level of intraspecific variation they exhibited. The selected markers require no more than two restriction digestions to allow unambiguous identification, although it was not possible to distinguish between white marlin and striped marlin with any of the genetic characters screened in our study. Individuals collected from throughout each species’ range were surveyed with the selected markers demonstrating low levels of intraspecific character variation within species. The resulting keys provide two independent means for the forensic identification of fillets and for specific identification of early life history stages.

Genetic diversity study of Caspian brown trout (Salmo trutta caspius Kessler, 1877) population in five rivers in the southern part of Caspian Sea, Iran

For study the genetic diversity of Caspian brown trout population in five rivers in the southern part of Caspian Sea in Iran 182 number generators in the fall and winter of 1390 were collected in Chalus, Sardab Rud, Cheshmeh Kileh, Kargan Rud and Astara rivers. Then about 3-5 g of soft and fresh tissue from the bottom fin fish removed and were fixed in ethanol 96°. Genomic DNA was extracted by using ammonium acetate, then quantity and quality of the extracted DNA were determined by using spectrophotometry and horizontal electrophoresis in 1% agarose gel. The polymerase chain reaction was performed by using 16 SSR primers and sequencing primers (D-Loop) and the quality of PCR products amplified by SSR method were performed by using horizontal electrophoresis in 2% agarose gel. Alleles and their sizes were determined by using vertical electrophoresis in 6% polyacrylamide gel and silver nitrate staining method. Gel images were recorded by gel documentarian, the bands were scored by using Photo- Capt software and statistical analysis was performed by using Gene Alex and Pop Gene software. Also the PCR sequencing products after quality assessment by usinghorizontal electrophoresis in 1.5% agarose gel were purified and sent to South Korea Bioneer Corporation for sequencing. Sequencing was performed by chain termination method and the statistical analysis was performed by using Bio- Edit, Mega, Arlequin and DNA SP software. The SSR method, 5 pairs of primers produced polymorphic bands and the average real and effective number of alleles were calculated 5.60±1.83 and 3.87±1.46 in the Cheshmeh Kileh river and 7.60±1.75 and 5.48±1.32 in the Karganrud river and the mean observed and expected heterozygosity were calculated 0.44 ±0.15 and 0.52 ±0.16 in the Cheshmeh Kileh river and 0.50 ±0.11 and 0.70±0.13 in the Karganrud river. Analysis of Molecular Variance results showed that significant differences in genetic diversity between and within populations and between and within individuals in the studied rivers (P<0.01). The sequencing method identified 35 different haplotype, the highest number of polymorphic position (251) and haplotype (14) were observed in the Chalus river. The highest mean observed number of alleles (2.24±0.48) was calculated in the Sardabrud river, the highest mean observed heterozygosity (1.00±0.03) was calculated in the Chalus river and the highest mean nucleotide diversity (0.13±0.07) was observed in the Sardabrud river and mean haplotype diversity was obtained (1) in three studied rivers. The overall results show that there are no same population of this fish in the studied rivers and Karganrud and Chalus rivers in the SSR and sequencing methods had the highest levels of genetic diversity.

Molecular identification of symbiotic dinoflagellates (Zooxanthellae) of dominant reef-building corals off Kish Island

Scleractinian coral species harbour communities of photosynthetic taxa of the genus Symbiodinium. As many as eight genetic clades (A, B, C, D, E, F, G and H) of Symbiodinium have been discovered using molecular biology. These clades may differ from each other in their physiology, and thus influence the ecological distribution and resilience of their host corals to environmental stresses. Corals of the Persian Gulf are normally subject to extreme environmental conditions including high salinity and seasonal variation in temperature. This study is the first to use molecular techniques to identify the Symbiodinium of the Iranian coral reefs to the level of phylogenetic clades. Samples of eight coral species were collected at two different depths from the eastern part of Kish Island in the northern Persian Gulf. Partial 28S nuclear ribosomal (nr) DNA of Symbiodinium (D1/D2 domains) were amplified by Polymerase Chain Reaction (PCR). PCR products were analyzed using Single Stranded Conformational Polymorphism (SSCP) and phylogenetic analyses of the LSU DNA sequences from a subset of the samples. The results showed that Symbiodinium populations were generally uniform among and within the populations of 8 coral species studied, and there are at least two clades of Symbiodinium from Kish Island. Clade D was detected from 8 of the coral species while clade C90 was found in 2 of species only (one species hosted two clades simultaneously). The dominance of clade D might be explained by high temperatures or the extreme temperature variation, typical of the Persian Gulf.

The genetic diversity of Acipenser stellatus populations in the Caspian Sea was studied using microsatellite technique

A total of 361 caudal fin samples were collected from adult A. stellatus specimens caught in the north Caspian Sea, including specimens from Kazakhstan (Ural River), Russia (Volga River), Azerbaijan (Kura River), specimens caught in the south Caspian Sea including specimens from Fishery Zone 1 (from Astara to Anzali), Fishery Zone 2 (from Anzali to Ramsar), Fishery Zone 3 (from Nowshahr to Babolsar), Fishery Zone 4 (from Miyankaleh to Gomishan) as well as from specimens caught in Turkmenistan (all specimens were collected during the sturgeon stock assessment survey). About 2 g of fin tissue was removed from each caudal fin sample, stored in 96% ethyl alcohol and transferred to the genetic laboratory of the International Sturgeon Research Institute. Genomic DNA was extracted using phenol-chloroform method. The quality and quantity of DNA was assessed using 1% Agarose gel electrophoresis and Polymerase Chain Reaction (PCR) was conducted on the target DNA using 15 paired microsatellite primer. PCR products were electrophoresed on polyacrylamide gels (6%) that were stained using silver nitrate. Electrophoretic patterns and DNA bands were analyzed with BioCapt software. Allele count and frequency, genetic diversity, expected heterozygosity and observed heterozygosity allele number, and the effective allele number, genetic similarity and genetic distance, FST and RST were calculated. The Hardy Wienberg Equilibrium based on X2 and Analysis of Molecular Variance (AMOVA) at 10% confidence level was calculated using the Gene Alex software. Dendrogram for genetic distances and identities were calculated using TFPGA program for any level of the hierarchy. It is evident from the results obtained that the 15 paired primers studied, polymorphism was observed in 10 pairs in 12 loci, while one locus did not produce DNA bands. Mean allele number was 13.6. Mean observed and expected heterozygosity was 0.86 and 0.642, respectively. It was also seen that specimens from all regions were not in Hardy Wienberg Equilibrium in most of the loci (P≤0.001). Highest Fst (0.063) was observed when comparing specimens from Fishery Zone 2 and Fishery Zone 4 (Nm=3.7) and lowest FST (0.028) was observed when comparing specimens from the Volga River and those from the Ural River (8.7). Significant differences (P<0.01) were observed between RST recorded in the specimens studied. Highest genetic distance (0.604) and lowest genetic resemblance (0.547) were observed between specimens from Fishery zones 2 and 4. Lowest genetic distance (0.311) and highest genetic resemblance (0.733) was observed between specimens from Turkmenistan and specimens from Fishery zone 1. Based on the genetic dendrogeram tree derived by applying UPGMA algorithm, A. stellatus specimens from Fishery zone 2 or in other words specimens from the Sepidrud River belong to one cluster which divides into two clusters, one of which includes specimens from Fishery zones 1, 3 and 4 and specimens from Turkmenistan while the other cluster includes specimens from Ural, Volga and Kura Rivers. It is thus evident that the main population of this species belongs to the Sepidrud River. Results obtained from the present study show that at least eight different populations of A. stellatus are found in the north and south Caspian Sea, four of which are known populations including the Ural River population, the Volga River population, the Kura River population and the Sepidrud River populations. The four other populations identified belonging to Fishery zones 1, 3, and 4 and to Turkmenistan are most probably late or early spawners of the spring run and autumn run of each of the major rivers mentioned. Specific markers were also identified for each of the populations identified. The Ural River population can be identified using primers Spl-68, 54b and Spl-104, 163 170, 173, the Volga River population can be identified using primers LS-54b and Spl-104, 170, 173 113a and similarly the population from the Kura River can be identified using primers LS-34, 54b and Spl-163, 173 and that from the Sepidrud River can be identified using primers LS-19, 34, 54b and Spl-105, 113b. This study gives evidence of the presence of different populations of this species and calls for serious measures to be taken to protect the genetic stocks of these populations. Considering that the population of A. stellatus in Fishery zone 2 is an independent population of the Sepidrud River in the Gilan Province, the catch of these fishes in the region needs to be controlled and regulated in order to restore the declining stocks of this species.

The genetic structure and phylogenetics of pikeperch (Sander lucioperca) Anzali and Amirkolaye wetlands and perch (Perca fluviatilis) populations in Aras Dam and south-west of the Caspian Sea

The genetic structure of pikeperch (Sander lucioperca) and perch (Perca fluviatilis) populations was studied using microsatellite technique. A total of 207 specimens of adult pikeperch were collected from Aras dam (57 specimens), Anzali wetland (50 specimens), Talesh (50 specimens) and Chaboksar (50 specimens) coasts. Also a total of 158 specimens of adult perch were collected from Anzali (Abkenar (50 specimens)and Hendekhale(48 specimens)) and Amirkolaye(60 specimens) wetlands. About 2 g of each specimen's dorsal fin was removed, stored in 96% ethyl alcohol and transferred to the genetic laboratory of the International Sturgeon Research Institute. Genomic DNA was extracted using ammonium-acetate method. The quality and quantity of DNA was assessed using 1% agarose gel electrophoresis. Polymerase Chain Reaction (PCR) was conducted on the target DNA using 15 pairs of microsatellite primers. PCR products were electrophoresed on poly acryl amide gels (6%) that were stained that were stained using silver nitrate. DNA bands were analyzed with BioCapt software. Allele count and frequency, genetic diversity, expected and observed heterozygosity , allele number and the effective allele number, genetic similarity and genetic distance, Fst, Rst, Hardy Weinberg Equilibrium based on X2 and Analysis of Molecular Variance (AMOVA) at 10% confidence level was calculated using the Gene Alex software. Dendogram for genetic distances and identities were calculated using TFPGA program for any level of hierarchy. The results for P. fluviatilis showed that from 15 pair of primers that were examined 6 polymorphic and 7 monomorphic loci were produced, while 2 loci didn't produce any DNA bands. Mean allele number was 4.1±1.1 and mean observed and expected heterozygosity was 0.56±0.12 and 0.58±0.14 respectively. It was also seen that specimens from all regions were not in Hardy Weinberg Equilibrium in some of loci (P<0.001). Highest Fst (0.095) with Nm=2.37 was observed between Hendekhale and Amirkolaye and the lowest Fst (0.004) with Nm=59.31 was observed between Abkenar and Hendekhale. According to AMOVA Significant difference (P<0.05) was observed between recorded Rst in the studied regions in Anzali and Amirkolaye lagoons. In another words there are two distinct populations of this species in Anzali and Amirkolaye lagoons. The highest genetic distance (0.181) and lowest genetic resemblance (0.834) were observed between specimens from Hendekhale and Amirkolaye and the lowest genetic distance (0.099) and highest genetic 176 resemblance (0.981) were observed between specimens from Abkenar and Hendekhale. Based on the genetic dendogram tree derived by applying UPGMA algorithm, specimens from Anzali and Amirkolaye wetlands have the same ancestor. On the other hand there is no noticeable genetic distance between the specimens of these two regions. Also the results for S. lucioperca showed that from 15 pair of primers that were examined 6 polymorphic and 7 monomorphic loci were produced, while 2 loci didn't produce any DNA bands. Mean allele number was 3.0±0.6 and mean observed and expected heterozygosity was 0.52±0.21 and 0.50±0.14 respectively. It was also seen that specimens from all regions were not in Hardy Weinberg Equilibrium in some of loci (P<0.001). Highest Fst (0.093) with Nm=2.43 was observed between Aras dam and Anzali wetland and the lowest Fst (0.022) with Nm=11.27 was observed between Talesh and Chaboksar coasts. Significant differences (P<0.05) were observed between recorded Rst in the studied regions exept for Talesh and Chaboksar Coasts. In another words there are three distinct populations of this species in Caspian sea, Anzali wetland and Aras dam. Highest genetic distance (0.110) and lowest genetic resemblance (0.896) were observed between specimens from Aras dam and Anzali wetland and the lowest genetic distance (0.034) and highest genetic resemblance (0.966) were observed between specimens from Talesh and Chaboksar coasts. Based on the genetic dendogram tree derived by applying UPGMA algorithm, specimens from Talesh and Chaboksar coasts have the lowest genetic distance. On the other hand the main population of this species belongs to Anzali wetland. Phylogenetic relationship of these two species was inferred using mitochondrial cytochrome b gene sequencing. For this purpose 2 specimens of P. fluviatilis from Anzali wetland, 2 specimens of S. lucioperca from Aras dam and 2 specimens of S. lucioperca from Anzali wetland were sequenced and submitted in Gene Bank. These sequences were aligned with Clustal W. The phylogenic relationships were assessed with Mega 4. The results of evolutionary history studies of these species using Neighbor-Joining and Maximum Parsimony methods showed that the evolutionary origin of pikeperch in Aras Dam and Anzali wetland is common. On the other hand these two species had common ancestor in about 4 million years ago. Also different sequences of any region specimens are supposed as different haplotypes. 177 As a conclusion the results of this study showed that microsatellite and mtDNA sequencing methods respectively are effective in genetic structure and phylogenic studies of P. fluviatilis and S. lucioperca.

Report of the NBFGR-BOBLME Indian mackerel genetics harmonisation training workshop, Kochi, India, 20-27 August, 2013

This workshop was held at the National Bureau of Fish Genetic Resources and followed on from the Indian mackerel Working group meeting in Colombo (28-29 May, 2012). Activities included; DNA extraction; PCR (Polymerase Chain Reaction) for microsatellites; genotyping microsatellites; data analysis; emerging technologies; and an action plan