Microsatellite DNA Variation in the Siberian Sturgeon, &lt;I&gt;Acipenser Baeri&lt;/I&gt; (Actinopterygii, Acipenseriformes, Acipenseridae), Cultured in a Polish Fish Farm

Fopp‐Bayat, Dorota

doi:10.3750/aip2010.40.1.03

Cited by 8 publications

(5 citation statements)

References 21 publications

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“…This result, also confirmed by the average Ho, showed the historical fluctuation in BSs population size (foundation effect), which was expected because the conjunction of BSs genes compared to WPs is typically characterized by lower genetic variability (FOPP-BAYAT, 2010). However, the genetic variability of BSs remained high, which indicated good reproductive management.…”

Section: Genetic Variabilitysupporting

confidence: 63%

Genetic diversity of pacu for restocking programs in the Tietê and Grande rivers, Brazil

Ribeiro

Lopera-Barrero

Santos³

et al. 2015

Sem. Ci. Agr.

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Piaractus mesopotamicus is a tropical fish under threat because of declines in the number of wild populations. Restocking programs have been developed as a conservation method, and the genetic monitoring of populations and broodstocks is important to ensure the viability of such programs. The objective of the current unprecedented experiment was to evaluate the genetic diversity of P. mesopotamicus wild populations (WPs) and broodstocks (BSs) using microsatellites markers for supplying the restocking programs in the Tietê and Grande rivers. Six microsatellite loci were amplified using the DNA obtained from the caudal fin of 279 adult fish. The observed intrapopulation genetic variability was high with mean heterozygosity ranging from 0.203 to 0.833. The number of alleles per locus ranged from three (loci Pme28 and Pme32) to thirteen (loci Pme4, Pme5 and Pme14), and there were allele differences between WPsxWPs and WPsxBSs. This differentiation was confirmed by the dendrogram analysis that showed three specific clusters. Four alleles were shared in the WPs2012xBSs. Positive FIS values indicated the presence of endogamy in seven out of ten samples obtained from the WPs. The AMOVA analysis and FST values indicated moderate and high genetic differences in WPsxWPs and high genetic differences in WPsxBSs. The genetic distance and genetic identity values and number of migrants confirmed these results. Adequate intrapopulation genetic variability, similarity between BSsxBSs, and genetic differences between WPs2011xWPs2012 and WPsxBSs were observed. In the wild, individuals from the restocking program were partially observed. ResumoPiaractus mesopotamicus é um peixe tropical que nos últimos anos tem apresentado uma diminuição no número de populações naturais. Programas de repovoamento vêm sendo utilizados como método de conservação, entretanto, o monitoramento genético das populações e dos estoques de reprodutores é importante para conferir a viabilidade desse tipo de programas. O objetivo do presente estudo foi avaliar de forma inédita a diversidade genética de populações selvagens (WPs) e estoques de reprodutores (BSs) de P. mesopotamicus utilizados em programas de repovoamento dos rios Tietê e Grande, através de marcadores microssatélite. Seis loci microssatélite foram amplificados usando DNA extraído de nadadeira caudal de 279 indivíduos adultos. Foi observada alta variabilidade genética intrapopulacional, com medias de heterozigosidade observada entre 0.203 e 0.833. O número de alelos por locus foi de três (locus Pme28 e Pme32) a 13 (locus Pme4, Pme5 e Pme14) e houve diferenciação de alelos entre WPsxWPs e WPsxBSs. Essa diferenciação foi confirmada pela análise do dendrograma que mostrou a formação de três agrupamentos específicos. Observaram-se quatro alelos compartilhados entre WPs2012xBSs. Valores positivos de F IS mostraram a presença de endogamia em sete das 10 coletas realizadas nas WPs. A análise de AMOVA e do F ST indicou moderada e muito alta diferenciação genética entre WPsxWPs e diferenciação gen...

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Section: Genetic Variabilitysupporting

confidence: 63%

Genetic diversity of pacu for restocking programs in the Tietê and Grande rivers, Brazil

Ribeiro

Lopera-Barrero

Santos³

et al. 2015

Sem. Ci. Agr.

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“…Additionally, the global deviation observed of the studied fish group from H-WE seems to support this hypothesis. Similar observations are frequently reported for other fish stocks kept under controlled conditions, e.g., for Chinook salmon, Oncorhynchus tshawytscha (Walbaum); Arctic charr, Salvelinus alpinus (L.); brook trout, S. fontinalis; paddlefish, Polyodon spathula (Walbaum); European huchen, Hucho hucho (L.) (Kim et al 2004, Ditlecadet et al 2006, Fopp-Bayat et al 2010, Kaczmarczyk et al 2012, Kucinski et al 2015.…”

Section: Locussupporting

confidence: 73%

Example of the application the microsatellite DNA fragments in the study of farmed European catfish (Silurus glanis, L.) broodstock

Kuciński¹,

Liszewski²,

Krzyoeków³

et al. 2015

Archives of Polish Fisheries

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Acta Technologica Agriculturae 1/2016Dušan Páleš et al.The most effective way for determination of curves for practical use is to use a set of control points. These control points can be accompanied by other restriction for the curve, for example boundary conditions or conditions for curve continuity (Sederberg, 2012). When a smooth curve runs only through some control points, we refer to curve approximation. The B-spline curve is one of such approximation curves and is addressed in this contribution. A special case of the B-spline curve is the Bézier curve Rédl et al., 2014). The B-spline curve is applied to a set of control points in a space, which were obtained by measurement of real vehicle movement on a slope (Rédl, 2007(Rédl, , 2008. Data were processed into the resulting trajectory (Rédl, 2012;Rédl and Kučera, 2008). Except for this, the movement of the vehicle was simulated using motion equations (Rédl, 2003;Rédl and Kročko, 2007). B-spline basis functionsBézier basis functions known as Bernstein polynomials are used in a formula as a weighting function for parametric representation of the curve (Shene, 2014). B-spline basis functions are applied similarly, although they are more complicated. They have two different properties in comparison with Bézier basis functions and these are: 1) solitary curve is divided by knots, 2) basis functions are not nonzero on the whole area. Every B-spline basis function is nonzero only on several neighbouring subintervals and thereby it is changed only locally, so the change of one control point influences only the near region around it and not the whole curve.These numbers are called knots, the set U is called the knot vector, and the half-opened interval 〈u i , u i + 1 ) is the i-th knot span. Seeing that knots u i may be equal, some knot spans may not exist, thus they are zero. If the knot u i appears p times, hence u i = u i + 1 = ... = u i + p -1 , where p >1, u i is a multiple knot of multiplicity p, written as u i (p). If u i is only a solitary knot, it is also called a simple knot. If the knots are equally spaced, i.e. (u i + 1 -u i ) = constant, for every 0 ≤ i ≤ (m -1), the knot vector or knot sequence is said uniform, otherwise it is non-uniform.Knots can be considered as division points that subdivide the interval 〈u 0 , u m 〉 into knot spans. All B-spline basis functions are supposed to have their domain on 〈u 0 , u m 〉. We will use u 0 = 0 and u m = 1.To define B-spline basis functions, we need one more parameter k, which gives the degree of these basis functions. Recursive formula is defined as follows:This definition is usually referred to as the Cox-de Boor recursion formula. If the degree is zero, i.e. k = 0, these basis functions are all step functions that follows from Eq. (1). N i, 0 (u) = 1 is only in the i-th knot span 〈u i , u i + 1 ). For example, if we have four knots u 0 = 0, u 1 = 1, u 2 = 2 and u 3 = 3, knot spans 0, 1 and 2 are 〈0, 1), 〈1, 2) and 〈2, 3), and the basis functions of degree 0 are N 0, 0 (u) = 1 on interval 〈0, 1) Acta In this co...

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“…Although information on the genetic diversity and differentiation is urgently needed for the conservation management of European huchen these data are still unavailable for the Polish population of this fish species. Additionally, there are many studies that demonstrate the benefits of conservation management based on genetic data (Hansen 2002; Gum et al 2003, 2006; Fopp-Bayat 2010; Olsson et al 2012). Thus, studies on the genetic structure of stock or population are important during conservation management for endangered fish species being protected by a rehabilitation measure, such as European huchen.…”

Section: Introductionmentioning

confidence: 99%

Genetic analysis of four European huchen (Hucho hucho Linnaeus, 1758) broodstocks from Poland, Germany, Slovakia, and Ukraine: implication for conservation

et al. 2015

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Four broodstocks of European huchen (Hucho hucho) from: Poland, Germany, Slovakia, and Ukraine were investigated using ten microsatellite DNA loci. Microsatellite DNA analysis was successfully applied for the first time in the Polish broodstock of this fish species. The genetic variation and genetic distance between these broodstocks were evaluated. In addition, we examined the potential effects of a genetic bottleneck on the genetic variation of the broodstocks. The European huchen broodstocks exhibited moderate genetic diversity (PIC = 0.405–0.496 and I = 0.831–1.047) with the exception of German broodstock which presented higher genetic diversity (PIC = 0.590 and I = 1.254). Observed (Ho) and expected (He) heterozygosity across the investigated loci in all broodstocks ranged from 0.434 to 0.686 and from 0.452 to 0.650, respectively. Overall, the studied broodstocks were in Hardy-Weinberg equilibrium (HWE); however, from 8 to 42 % of the loci deviated from HWE in each stock. The Garza-Williamson index (M = 0.146–0.279) and values of the heterozygosity excess revealed a reduction of genetic variation in all studied broodstocks because of the founder or bottleneck effect. The analysis of genetic differentiation (Fst) and Nei’s genetic distance between pairs of broodstocks revealed that Polish and Ukrainian broodstocks of European huchen were characterized by the closest genetic distance. In contrast, the highest genetic divergence parameters (Fst and Nei’s distance) were observed among German, Slovak, and Ukrainian broodstocks.

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Microsatellite DNA Variation in the Siberian Sturgeon, <I>Acipenser Baeri</I> (Actinopterygii, Acipenseriformes, Acipenseridae), Cultured in a Polish Fish Farm

Cited by 8 publications

References 21 publications

Genetic diversity of pacu for restocking programs in the Tietê and Grande rivers, Brazil

Genetic diversity of pacu for restocking programs in the Tietê and Grande rivers, Brazil

Example of the application the microsatellite DNA fragments in the study of farmed European catfish (Silurus glanis, L.) broodstock

Genetic analysis of four European huchen (Hucho hucho Linnaeus, 1758) broodstocks from Poland, Germany, Slovakia, and Ukraine: implication for conservation

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