Genetic diversity and differentiation of sea trout (Salmo trutta) populations in Lithuanian rivers assessed by microsatellite DNA variation

Samuilovienė, Aurelija; Kontautas, Antanas; Gross, Riho

doi:10.1007/s10695-009-9310-1

Cited by 15 publications

(16 citation statements)

References 43 publications

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“…This is congruent with other studies of sea trout where IBD has been observed (Moran et al 1995;Hansen & Mensberg 1998;Samuiloviene et al 2009) and also the nonexistence of IBD among samples of resident brown trout (Ryman 1983;Carlsson & Nilsson 2001). This is congruent with other studies of sea trout where IBD has been observed (Moran et al 1995;Hansen & Mensberg 1998;Samuiloviene et al 2009) and also the nonexistence of IBD among samples of resident brown trout (Ryman 1983;Carlsson & Nilsson 2001).…”

Section: Genetic Structuresupporting

confidence: 91%

“…The structuring is similar to other studies of brown trout genetic structure on similar geographical scales (Hansen et al 2002;Lehtonen et al 2009;Massa-Gallucci et al 2010;Samuiloviene et al 2009). The structuring is similar to other studies of brown trout genetic structure on similar geographical scales (Hansen et al 2002;Lehtonen et al 2009;Massa-Gallucci et al 2010;Samuiloviene et al 2009).…”

Section: Genetic Structuresupporting

confidence: 89%

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Importance of life‐history and landscape characteristics for genetic structure and genetic diversity of brown trout (Salmo truttaL.)

Nilsson

2011

Ecology of Freshwater Fish

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Investigating the influence of evolutionary forces on the genetic structure and genetic diversity remains a major challenge. Yet, it is of considerable interest for conservation and management of a species. This study investigates the influence of life-history and landscape features, such as altitude, connectivity and habitat size, on genetic diversity and genetic structure of brown trout (Salmo trutta L.) with stream-resident, lake-dwelling and seamigrating life-history in two river systems in northern Sweden. Using regression tree analysis including ecological and landscape characteristics, we show that life history is the most important variable explaining genetic diversity and population differentiation. Sea-migrating populations show high diversity and low differentiation, and lake-and stream-resident populations show low diversity and high population differentiation, among all samples. No overall genetic correlation with geographical distance was noted; however, among sea-migrating populations within the River Vindelälven drainage, this pattern was observed. This study illustrates that life-history and landscape features help to explain genetic structure and genetic variation. The information is important for conservation and management actions, such as fisheries regulations, habitat restorations, stocking of hatchery fish, defining management units and introducing genetic monitoring programmes.

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Section: Genetic Structuresupporting

confidence: 91%

Section: Genetic Structuresupporting

confidence: 89%

Importance of life‐history and landscape characteristics for genetic structure and genetic diversity of brown trout (Salmo truttaL.)

Nilsson

2011

Ecology of Freshwater Fish

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“…European, and especially Baltic, sea trout populations have been frequently studied mainly of Danish and Swedish stocks (i.e. Hansen & Mensberg 1998;Laikre et al 2002;Fraser et al 2007;€ Ostergren et al 2011), but also Polish (Was & Wenne 2002Drywa et al 2013), Lithuanian (Samuiloviene et al 2009) and Russian (Lehtonen et al 2009) stocks. However, works focused on population structure from a single basin are rarer and absent in southern Baltic rivers.…”

Section: Introductionmentioning

confidence: 99%

Genetic diversity within sea trout population from an intensively stocked southern Baltic river, based on microsatellite DNA analysis

Bernaś

Burzyński

Dębowski

et al. 2014

Fisheries Management Eco

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Sea trout, Salmo trutta L., populations in the Slupia River basin have been affected by mass stocking with smolts and fry. This work is focused on a small-scale differentiation in sea trout populations from one basin with a strong emphasis on the relationship between wild and hatchery origin fish. A total of 216 sea trout were genotyped at 10 microsatellite loci. Global F ST obtained by AMOVA was low at 0.0165. Pairwise F ST were significant for all tests except wild and stocked adults. The highest pairwise difference was found between the hatchery sample and Kwacza (F ST = 0.038). Analysis of the genetic structure revealed micro-geographical differentiation with four subpopulations. The quality of the artificial spawning was found not to be adequate with a high risk of adverse effects to the whole population. All future stocking actions in the basin should consider the existing population structures.

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“…Also, according to the expected and observed heterozygoty values, it is clearly seen from the graph that the interpopulation genetic distance is the farthest in FRT population. Samuiloviene et al (2009) reported that significant population differentiation was found both between river systems and between population pairs within the same river system in sea trout (Salmo trutta) populations in Lithuanian rivers. They suggested that even geographically adjacent tributaries exhibited significant genetic differences.…”

Section: Resultsmentioning

confidence: 99%

Untitled

Ceyhun¹,

Çiltaş²

2013

Turk. J. Fish. Aquat. Sci.

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In this study, the genotypic differences of five different trout populations were compared using microsatellite markers. Fish analyzed were; Balıklı Lake (BLK) and Abant Lake (ABN) found in lakes, and Fırat Basin (FRT), Aras Basin (ARS), Çoruh Basin (CRH) found in rivers. Allele numbers in each locus were determined by application of Single Strand Conformation Polymorphism (SSCP) to the microsatellite sections. Totally 62 alleles were observed from 10 microsatellite loci. According to the results from factorial correspondence analysis, it was determined that all of the populations formed different groups from each other. Considering all loci, observed heterozygosity (Ho) and expected heterozygosity (He), values changed from 0.602-0.668 and 0.570-0.670, respectively. Ho value was significantly (P<0.01) higher than He value of populations of FRT. Fixation index for subpopulations (FIS) values were ranged from 0.069 to -0.173 (BLK to FRT) in populations, and the overall average diversity between populations (FST) value of the all loci was calculated as 0.0790. According to FST values calculated among populations, genetic distance was found to be significant (P<0.05) among four populations. It was determined that four of five populations were at the Hardy-Weinberg equilibrium (HWE). Considering genetic distance in populations, it was observed that the distance was shorter in lake forms compared to River forms.Keywords: Salmo trutta, microsatellite, SSCP, genetic variation. Türkiye'deki Beş Farklı Yerli Alabalık Türünün Genetik Varyasyonunun Mikrosatelit Markırlar ile Belirlenmesi Özet

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Genetic diversity and differentiation of sea trout (Salmo trutta) populations in Lithuanian rivers assessed by microsatellite DNA variation

Cited by 15 publications

References 43 publications

Importance of life‐history and landscape characteristics for genetic structure and genetic diversity of brown trout (Salmo truttaL.)

Importance of life‐history and landscape characteristics for genetic structure and genetic diversity of brown trout (Salmo truttaL.)

Genetic diversity within sea trout population from an intensively stocked southern Baltic river, based on microsatellite DNA analysis

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