Population genetic structure of Rutilus frisii kutum in Caspian Sea using biometry and microsatellite molecular technique

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.

Caribbean connectivity: implications for Marine Protected Area Management. Proceedings of a Special Symposium, 9-11 November 2006, 59th Annual Meeting of the Gulf and Caribbean Fisheries Institute, Belize City, Belize

Executive Summary: Tropical marine ecosystems in the Caribbean region are inextricably linked through the movement of pollutants, nutrients, diseases, and other stressors, which threaten to further degrade coral reef communities. The magnitude of change that is occurring within the region is considerable, and solutions will require investigating pros and cons of networks of marine protected areas (MPAs), cooperation of neighboring countries, improved understanding of how external stressors degrade local marine resources, and ameliorating those stressors. Connectivity can be broadly defined as the exchange of materials (e.g., nutrients and pollutants), organisms, and genes and can be divided into: 1) genetic or evolutionary connectivity that concerns the exchange of organisms and genes, 2) demographic connectivity, which is the exchange of individuals among local groups, and 3) oceanographic connectivity, which includes flow of materials and circulation patterns and variability that underpin much of all these exchanges. Presently, we understand little about connectivity at specific locations beyond model outputs, and yet we must manage MPAs with connectivity in mind. A key to successful MPA management is how to most effectively work with scientists to acquire the information managers need. Oceanography connectivity is poorly understood, and even less is known about the shape of the dispersal curve for most species. Dispersal kernels differ for various systems, species, and life histories and are likely highly variable in space and time. Furthermore, the implications of different dispersal kernels on population dynamics and management of species is unknown. However, small dispersal kernels are the norm - not the exception. Linking patterns of dispersal to management options is difficult given the present state of knowledge. The behavioral component of larval dispersal has a major impact on where larvae settle. Individual larval behavior and life history details are required to produce meaningful simulations of population connectivity. Biological inputs are critical determinants of dispersal outcomes beyond what can be gleaned from models of passive dispersal. There is considerable temporal and spatial variation to connectivity patterns. New models are increasingly being developed, but these must be validated to understand upstream-downstream neighborhoods, dispersal corridors, stepping stones, and source/sink dynamics. At present, models are mainly useful for providing generalities and generating hypotheses. Low-technology approaches such as drifter vials and oceanographic drogues are useful, affordable options for understanding local connectivity. The “silver bullet” approach to MPA design may not be possible for several reasons. Genetic connectivity studies reveal divergent population genetic structures despite similar larval life histories. Historical stochasticity in reproduction and/or recruitment likely has important, longlasting consequences on present day genetic structure. (PDF has 200 pages.)

Report of the Indian Mackerel Working Group Meeting, Colombo, Sri Lanka, 28-29 May, 2012

Stock structure approaches and consequences of management in the eight member countries. Indian mackerel (Rastrelliger kanagurta) genetic stock studies and workplan

Morphometric studies in Penaeus merguiensis from Ratnagiri waters for selection of the brood stock in genetic improvement programmes

Studies on genetic improvement of penaeid prawns for the character higher tail weight using methods of selective breeding were undertaken. Prior to the actual breeding experiments it was necessary to find out the quantum of available variability in the character tail weight amongst the natural populations of Penaeus merguiensis from the Indian waters. Thirteen morphometric variables were measured and various statistical analyses were carried out. The tail weight showed almost double values of coefficient of variation in the females than the males (C.V. 20.37 and 11.08 respectively). The combination of the characters viz. sixth segment length (SSL), sixth segment depth (SSD) and posterior abdominal circumference (PAC) gave the highest R super(2) values. These variables were easy to measure and gave maximum variation in the character tail weight without sacrificing the breeders in the brood stock. The quantitative character tail weight was influenced by both genetic and environmental factors was statistically ascertained by applying 2-Factor analysis.

Microsatellite multiplex panels for genetic studies of gray snapper (Lutjanus griseus) and lane snapper (Lutjanus synagris)

Microsatellites are codominantly inherited nuclear-DNA markers (Wright and Bentzen, 1994) that are now commonly used to assess both stock structure and the effective population size of exploited fishes (Turner et al., 2002; Chistiakov et al., 2006; Saillant and Gold, 2006). Multiplexing is the combination of polymerase chain reaction (PCR) amplification products from multiple loci into a single lane of an electrophoretic gel (Olsen et al., 1996; Neff et al., 2000) and is accomplished either by coamplification of multiple loci in a single reaction (Chamberlain et al., 1988) or by combination of products from multiple single-locus PCR amplifications (Olsen et al., 1996). The advantage of multiplexing micro-satellites lies in the significant reduction in both personnel time (labor) and consumable supplies generally required for large genotyping projects (Neff et al., 2000; Renshaw et al., 2006).