31 resultados para gene flow, genetic structure, Lake Carpentaria, Ambassis macleayi, freshwater fish
em Aquatic Commons
Resumo:
Long-term sustainable management of wild populations should be based on management actions that account for the genetic structure among populations. Knowledge of genetic structure and of the degree of demographic exchange between discreet [sic] populations allows managers to better define management units. However, adequate gene loci for population assessments are not always available. In this study, variable co-dominant DNA loci in the heavily exploited marine genus Brevoortia were developed with a microsatellite-enriched DNA library for the Gulf Menhaden (Brevoortia patronus). Microsatellite marker discovery was followed by genetic characterization of 4 endemic North American Brevoortia species, by using 14 novel loci as well as 5 previously described loci. Power analysis of these loci for use in species identification and genetic stock structure was used to assess their potential to improve the stock definition in the menhaden fishery of the Gulf of Mexico. These loci could be used to reliably identify menhaden species in the Gulf of Mexico with an estimated error rate of α=0.0001. Similarly, a power analysis completed on the basis of observed allele frequencies in Gulf Menhaden indicated that these markers can be used to detect very small levels of genetic divergence (Fst≈0.004) among simulated populations, with sample sizes as small as n=50 individuals. A cursory analysis of genetic structure among Gulf Menhaden sampled throughout the Gulf of Mexico indicated limited genetic structure among sampling locations, although the available sampling did not reach the target number (n=50) necessary to detect minimal values of significant structure.
Resumo:
Genetic structure of hatchery population of Thai pangas (Pangasius hypophthalmus) of Jessore region, Bangladesh has been investigated from 1 January 2004 to 31 December 2004. Samples for this study were collected from five fish hatcheries viz. Asrom, Banchte Shekha, Chowdhury, Maola and Rezaul Haque. The enzymes were encoded by 15 gene loci: Adh-1*, Est-1*, G3pdh-2*, Gpi-1*, Gpi-2*, Idhp-1*, Idhp-2*, Ldh-1*, Ldh-2*, Mdh-1*, Mdh-2*, Pgm*, Sdh-1*, Sdh-2* and Sod*. Among them four (Est-1*, G3pdh-2*, Gpi-2*and Pgm*) were found to be polymorphic in different populations but only Gpi-2* was polymorphic in all the sampled populations. The mean proportion of polymorphic loci per population was the highest (26.7%) in Banchte Shekha hatchery while the mean proportion of heterozygous loci was 13.33% per individual in Banchte Shekha and Maola hatcheries. The UPGMA dendrogram of Nei's (1972) genetic distances indicated a relationship between the genetic distance and geographical difference. High genetic variability in stocks of Thai pangas was observed in the Banchte Shekha and Maola hatcheries and less variability was found in the other three hatcheries.
Resumo:
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.
Resumo:
Neogobius caspius is a small benthic fish that is native to the Caspian Sea. The importance of this fish is because of it is role as a main food resource of the sturgeon fish. The genetic diversity of N. caspius population in the Caspian Sea was studied using PCR- RFLP technique. A total of 135 samples of N. caspius were collected from coastal line in the north Caspian sea, including specimens from coasts of Anzali , Torkman Port and Chalus. Genomic DNA was extracted by phenol-chloroform method and then was amplified using a pair primer of cytochrom b gene, 2 tRNA gene and the control region sequences by a thermal cycler. D2 (5'-CCGGAGTATGTAGGGCATTCTCAC-3'), CY1 (5'-YYTAACCRRGACYAATGACTTGA-3') 12 restriction enzyme were used to digest the target gene region including: Alul HincII —Tas1 —Rsa1 -MboI -DraI -BSeNI(BSRI) Alw261(BsmAI). Bsul 51 Hin11 Bsh12851- BsuRI(HaeIII) digested PCR products were observed by silver staining method followed by Polyacrylamide gel electrophoresis (PAGE). The results were shown the same pattern among the species. There was no polymorphism and no differentiation in population in the Neogobius caspius fish and all individuals have shown homogenous genotype.
Resumo:
In order to carry out Biometric studies, 75 samples were caught from 3 locations ( Tajan river, Sefidrud and Shirud) using Salic and the length (±1 mm) and weights (± 5 gr) of samples were determined. Using One-way ANOVA by SPPSS software, there wasn’t significant difference between locations in length and fecondity (P ≥0.01(, but there was significant difference between Shirud and tajan samples with sefidrud in weight ) P≤0.01(. In order to carry out genetic variation studies, 210 fish were caught from 3 different regions of the Iranian coastline (Khoshkrud, Tonekabon, Gorganrud) and 1 region in Azerbaijan (Waters of the Caspian Sea close to Kura River mouth) during 2008-2009 . Genomic DNA was extracted of fin using the phenol-chloroform. The quantity and quality of DNA from samples were assessed by spectrophptometer and 1% agarose gel electro-phoresis. PCR was carried out using 15 paired microsatellite primers. PCR products were separated on 8% polyacrylamide gels that were stained using silver nitrate. Molecular weight calculate using UVTech software. The recorded microsatellite genotypes were used as input data for the GENALEX software version 6 package in order to calculate allele and genotype frequencies, observed (Ho) and (He) expected heterozygosities and to test for deviations from Hardy-Weinberg equilibrium. Genetic distance between two populations was estimated from Nei standard genetic distance and genetic similarity index (Nei, 1972). Genetic differentiation between populations was also evaluated by the calculation of pairwise estimates of Fst and Rst values. From 15 SSR markers were used in this investigation, 9 of them were polymorph. Average of expected and observed heterozygosity was 0.54 and 0.49 respectively. Significant deviations from Hardy-Weinberg expectations were observed in all of location except Anzali lagoon- autumn in AF277576 and EF144125, Khoshkrud in EF144125 and Gorganrud and Kura in AF277576. Using Fst and Rst there was significant difference between locations ) P≤0.01(. According to Fst , the highest population differentiation (Fst= 0.217) was between Gorganrud and Khoshkrud that have the lowest Nm and the lowest (Fst= 0.086) was between Gorganrud and Tonekabon that have the highest Nm. Using Rst the highest population differentiation (Rst= 0.271) was between Tonekabon and spring Anzali lagoon and the lowest (Rst= 0.026) was between Tonekabon and Autumn Anzali 159 lagoon. Also the difference between Spring Anzali lagoon and Autumn Anzali lagoon was noticeable (Fst=0.15). AMOVA analysis with consideration of 2 sampling regions (Iran and Azerbaijan) and 7 sampling locations (Iran: Khoshkrud, Tonekabon, Gorganrud, Spring Anzali lagoon and Autumn Anzali lagoon ; Azerbaijan: the Kura mouth) revealed that almost all of the variance in data namely 83% )P≤0.01( was within locations, Genetic variances among locations was 14% )P≤0.01( and among regions was 3% )P≤0.01(. The genetic distance was the highest (0.646) between Gorganrud and Autumn Anzali lagoon populations, whereas the lowest distance (0.237) was between Gorganrud and Tonekabon River. Result obtained from the present study show that at least 2 different population of Rutilus frissi kutum are found in the Caspian sea,which are including the kura river population and the southern Caspian sea samples and it appears that there is more than one population in southern Caspian sea that should be attantioned in artifical reproduction Center and stoke rebilding.
Resumo:
Many interconnected problems involved for the conservation of freshwater fish genetic resources of India are enumerated. Some possible solutions to the problems are also discussed.
Resumo:
The purpose of the study was to provide an in-depth understanding of information generation, flow and utilization within Uganda’s regional fish trade. The study was carried out at district headquarters, border points, landing sites and border markets, involving DFOs, Customs Officials, BMU executives and market managers.
Resumo:
We surveyed variation at 13 microsatellite loci in approximately 7400 chinook salmon sampled from 52 spawning sites in the Fraser River drainage during 1988–98 to examine the spatial and temporal basis of population structure in the watershed. Genetically discrete chinook salmon populations were associated with almost all spawning sites, although gene flow within some tributaries prevented or limited differentiation among spawning groups. The mean FST value over 52 samples and 13 loci surveyed was 0.039. Geographic structuring of populations was apparent: distinct groups were identified in the upper, middle, and lower Fraser River regions, and the north, south, and lower Thompson River regions. The geographically and temporally isolated Birkenhead River population of the lower Fraser region was sufficiently genetically distinctive to be treated as a separate region in a hierarchial analysis of gene diversity. Approximately 95% of genetic variation was contained within populations, and the remainder was accounted for by differentiation among regions (3.1%), among populations within regions (1.3%), and among years within populations (0.5%).Analysis of allelic diversity and private alleles did not support the suggestion that genetically distinctive populations of chinook salmon in the south Thompson were the result of postglacial hybridization of ocean-type and stream-type chinook in the Fraser River drainage. However, the relatively small amount of differentiation among Fraser River chinook salmon populations supports the suggestion that gene flow among genetically distinct groups of postglacial colonizing groups of chinook salmon has occurred, possibly prior to colonization of the Fraser River drainage.
Resumo:
A total of 1006 king mackerel (Scomberomorus cavalla) representing 20 discrete samples collected between 1996 and 1998 along the east (Atlantic) and west (Gulf) coasts of Florida and the Florida Keys were assayed for allelic variation at seven nuclear-encoded microsatellites. No significant deviations from Hardy-Weinberg equilibrium expectations were found for six of the microsatellites, and genotypes at all microsatellites were independent. Allele distributions at each microsatellite were independent of sex and age of individuals. Homogeneity tests of spatial distributions of alleles at the microsatellites revealed two weakly divergent “genetic” subpopulations or stocks of king mackerel in Florida waters—one along the Atlantic coast and one along the Gulf coast. Homogeneity tests of allele distributions when samples were pooled along seasonal (temporal) boundaries, consistent with the temporal boundaries used currently for stock assessment and allocation of the king mackerel resource, were nonsignificant. The degree of genetic divergence between the two “genetic” stocks was small: on average, only 0.19% of the total genetic variance across all samples assayed occurred between the two regions. Cluster analysis, assignment tests, and spatial autocorrelation analysis did not generate patterns that were consistent with either geographic or spatial-temporal boundaries. King mackerel sampled from the Florida Keys could not be assigned unequivocally to either “genetic” stock. The genetic data were not consistent with current spatial-temporal boundaries employed in stock assessment and allocation of the king mackerel resource. The genetic differences between king mackerel in the Atlantic versus those in the Gulf most likely stem from reduced gene flow (migration) between the Atlantic and Gulf in relation to gene flow (migration) along the Atlantic and Gulf coasts of peninsular Florida. This difference is consistent with findings for other marine fishes where data indicate that the southern Florida peninsula serves (or has served) as a biogeographic boundary.