Phylogenetic characteristics of selected European huchen (Hucho hucho L.) broodstocks – implication for broodstock management

Abstract European huchen (Hucho hucho) is a representative of large and rare migratory salmonid fish, which has become endangered due to extensive anthropogenic changes in freshwater ecosystems. Numerous broodstocks of the European huchen have therefore been established throughout the species’ range in recent years to supplement wild fisheries of this species. Unfortunately, this conservation management strategy entails a number of potential ecological and genetic risks associated with the release of farm-raised fish into wild populations. A comprehensive and feasible genetic monitoring protocol for broodstocks maintained for the production of restocking material is therefore essential in the sustainable management of critically endangered fish species. The current paper presents phylogenetic characteristics of four selected huchen broodstocks across Central and Eastern Europe. Genetic comparisons of the studied broodstocks were based on ten microsatellite DNA markers. The effective population size (Ne), the individual assignment test, the Principal Coordinates Analysis (PCoA), the allele sharing distance (DAS) and the Bayesian clustering analysis were applied in this study. Moreover, five selected fragments of mitochondrial DNA were used for molecular verification of species membership and genetic purity of examined specimens.

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Genotyping of Two Mediterranean Trout Populations in Central-Southern Italy for Conservation Purposes Using a Rainbow-Trout-Derived SNP Array

Animals ◽

10.3390/ani11061803 ◽

2021 ◽

Vol 11 (6) ◽

pp. 1803

Author(s):

Valentino Palombo ◽

Elena De Zio ◽

Giovanna Salvatore ◽

Stefano Esposito ◽

Nicolaia Iaffaldano ◽

...

Keyword(s):

Rainbow Trout ◽

Genetic Structure ◽

Fishery Management ◽

Snp Array ◽

Fine Scale ◽

Principal Coordinates Analysis ◽

Data Set ◽

Management Actions ◽

Principal Coordinates ◽

Mediterranean Trout

Mediterranean trout is a freshwater fish of particular interest with economic significance for fishery management, aquaculture and conservation biology. Unfortunately, native trout populations’ abundance is significantly threatened by anthropogenic disturbance. The introduction of commercial hatchery strains for recreation activities has compromised the genetic integrity status of native populations. This work assessed the fine-scale genetic structure of Mediterranean trout in the two main rivers of Molise region (Italy) to support conservation actions. In total, 288 specimens were caught in 28 different sites (14 per basins) and genotyped using the Affymetrix 57 K rainbow-trout-derived SNP array. Population differentiation was analyzed using pairwise weighted FST and overall F-statistic estimated by locus-by-locus analysis of molecular variance. Furthermore, an SNP data set was processed through principal coordinates analysis, discriminant analysis of principal components and admixture Bayesian clustering analysis. Firstly, our results demonstrated that rainbow trout SNP array can be successfully used for Mediterranean trout genotyping. In fact, despite an overwhelming number of loci that resulted as monomorphic in our populations, it must be emphasized that the resulted number of polymorphic loci (i.e., ~900 SNPs) has been sufficient to reveal a fine-scale genetic structure in the investigated populations, which is useful in supporting conservation and management actions. In particular, our findings allowed us to select candidate sites for the collection of adults, needed for the production of genetically pure juvenile trout, and sites to carry out the eradication of alien trout and successive re-introduction of native trout.

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Tree Species Diversity and Composition of Miombo Woodlands in South-Central Angola: A Chronosequence of Forest Recovery after Shifting Cultivation

International Journal of Forestry Research ◽

10.1155/2017/6202093 ◽

2017 ◽

Vol 2017 ◽

pp. 1-13 ◽

Cited By ~ 16

Author(s):

Francisco M. P. Gonçalves ◽

Rasmus Revermann ◽

Amândio L. Gomes ◽

Marcos P. M. Aidar ◽

Manfred Finckh ◽

...

Keyword(s):

Shifting Cultivation ◽

Stand Structure ◽

Woody Species ◽

Distinct Group ◽

Forest Recovery ◽

Miombo Woodlands ◽

Principal Coordinates Analysis ◽

South Central ◽

Principal Coordinates ◽

Management Plans

The study was carried out in the Cusseque area of the Municipality of Chitembo in south-central Angola. Our objectives were to assess the floristic diversity, the species composition, and stand structure of Miombo woodlands during regeneration after shifting cultivation. A total of 40 plots of 1000 m2were surveyed and analyzed, corresponding to mature forests/woodlands and three fallow types of different age. The analyses were based on plot inventories of all trees with DBH ≥ 5 cm. A total of 51 woody species, 38 genera, and 19 families were recorded. The dominant family was Fabaceae, with subfamily Caesalpinioideae being very abundant. Shannon Diversity and Evenness were highest in mature forests and young fallows, while the mature forest stands showed the highest species richness. A Principal Coordinates Analysis (PCoA) showed many species shared between the intermediate fallow types, but only few species were shared with young fallows. Mature forests formed a clearly distinct group. This study shows potential pathways of forest recovery in terms of faster regeneration after agricultural abandonment and, thus, the results presented here can be used in future conservation and management plans in order to reduce the pressure on mature forests.

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Unraveling city-specific signature and identifying sample origin locations for the data from CAMDA MetaSUB challenge

Biology Direct ◽

10.1186/s13062-020-00284-1 ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Runzhi Zhang ◽

Alejandro R. Walker ◽

Susmita Datta

Keyword(s):

Machine Learning ◽

Error Rates ◽

Average Error ◽

Importance Score ◽

Learning Methods ◽

Principal Coordinates Analysis ◽

Principal Coordinates ◽

Total Variability ◽

The Common ◽

Feature Selecting

Abstract Background Composition of microbial communities can be location-specific, and the different abundance of taxon within location could help us to unravel city-specific signature and predict the sample origin locations accurately. In this study, the whole genome shotgun (WGS) metagenomics data from samples across 16 cities around the world and samples from another 8 cities were provided as the main and mystery datasets respectively as the part of the CAMDA 2019 MetaSUB “Forensic Challenge”. The feature selecting, normalization, three methods of machine learning, PCoA (Principal Coordinates Analysis) and ANCOM (Analysis of composition of microbiomes) were conducted for both the main and mystery datasets. Results Features selecting, combined with the machines learning methods, revealed that the combination of the common features was effective for predicting the origin of the samples. The average error rates of 11.93 and 30.37% of three machine learning methods were obtained for main and mystery datasets respectively. Using the samples from main dataset to predict the labels of samples from mystery dataset, nearly 89.98% of the test samples could be correctly labeled as “mystery” samples. PCoA showed that nearly 60% of the total variability of the data could be explained by the first two PCoA axes. Although many cities overlapped, the separation of some cities was found in PCoA. The results of ANCOM, combined with importance score from the Random Forest, indicated that the common “family”, “order” of the main-dataset and the common “order” of the mystery dataset provided the most efficient information for prediction respectively. Conclusions The results of the classification suggested that the composition of the microbiomes was distinctive across the cities, which could be used to identify the sample origins. This was also supported by the results from ANCOM and importance score from the RF. In addition, the accuracy of the prediction could be improved by more samples and better sequencing depth.

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Genetic analysis of a heritage variety collection

Plant Genetic Resources ◽

10.1017/s1479262118000448 ◽

2018 ◽

Vol 17 (03) ◽

pp. 232-244 ◽

Cited By ~ 2

Author(s):

J. M. Preston ◽

B. V. Ford-Lloyd ◽

L. M. J. Smith ◽

R. Sherman ◽

N. Munro ◽

...

Keyword(s):

Genetic Analysis ◽

Group Method ◽

Niche Markets ◽

Principal Coordinates Analysis ◽

Pair Group ◽

Landrace Diversity ◽

Principal Coordinates ◽

Length Polymorphisms ◽

Seed Saving ◽

History Of

AbstractLandraces (including heritage varieties) are an important agrobiodiversity resource offering considerable value as a buffer against crop failures, as a crop for niche markets, and as a source of diversity for crop genetic improvement activities underpinning future food security. Home gardens are reservoirs of landrace diversity, but some of the accessions held in them are vulnerable or threatened with extinction. Those associated with seed saving networks have added security, for example, ca. 800 varieties are stored in the Heritage Seed Library (HSL) of Garden Organic, UK. In this study, Amplified Fragment Length Polymorphisms-based genetic analysis of accessions held in the HSL was used to (a) demonstrate the range of diversity in the collection, (b) characterize accessions to aid collection management and (c) promote broader use of the collection. In total, 171 accessions were included from six crops: Vicia faba L., Pisum sativum L., Daucus carota L., Cucumis sativus L., Lactuca sativa L. and Brassica oleracea L. var. acephala (DC.) Metzq. Average expected heterozygosity ranged from 0.18 to 0.28 in D. carota; 0.02–0.18 in P. sativum; 0.05–0.18 in L. sativa; 0.15–0.26 in B. oleracea var. acephala; 0.15–0.37 in C. sativus and 0.07–0.36 in V. faba. Genetic diversity and Fst values generally reflected the breeding system and cultivation history of the different crops. Comparisons of the diversity found in heritage varieties with that found in commercial varieties did not show a consistent pattern. Principal coordinates analysis and Unweighted Pair Group Method with Arithmetic Mean cluster analysis were used to identify four potential duplicate accession pairs.

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Conservation genetics of the endangered Spotted Turtle (Clemmys guttata) illustrate the risks of “bottleneck tests”

Canadian Journal of Zoology ◽

10.1139/cjz-2013-0188 ◽

2014 ◽

Vol 92 (2) ◽

pp. 149-162 ◽

Cited By ~ 9

Author(s):

Christina M. Davy ◽

Robert W. Murphy

Keyword(s):

Population Genetics ◽

Freshwater Turtles ◽

Population Declines ◽

Isolated Populations ◽

Principal Coordinates Analysis ◽

Turtle Species ◽

Principal Coordinates ◽

Clemmys Guttata ◽

Spotted Turtle ◽

Cast Doubt

Studies of population genetics in turtles have suggested that turtles do not experience genetic impacts of bottlenecks as strongly as expected. However, recent studies cast doubt on two commonly used tests implemented in the program BOTTLENECK, suggesting that these findings should be re-evaluated. The Spotted Turtle (Clemmys guttata (Schneider, 1792)) is endangered both globally and within Canada, but genetic data required to develop effective recovery strategies are unavailable. Here, we conducted the first study of population genetic structure in C. guttata. We then used multiple small populations of C. guttata as replicates to test whether the commonly used program BOTTLENECK could detect the genetic signature of bottlenecks in our study populations, which are all thought to have experienced significant declines in the past 2–3 generations (75 years). Turtles (n = 256) were genotyped at 11 microsatellite loci. A suite of Bayesian population genetics analyses and a principal coordinates analysis identified a minimum of 6 distinct genetic populations and a maximum of 10 differentiated subpopulations across the sampled Canadian range of C. guttata, which corresponded to demographically independent units. BOTTLENECK failed to detect population declines. A literature review found that bottleneck tests in 17 of 18 previous genetic studies of tortoises and freshwater turtles were based on suboptimal sampling, potentially confounding their results. High retention of genetic diversity (allelic richness and heterozygosity) in isolated populations of C. guttata and other turtle species is encouraging for species recovery, but conclusions about the prevalence of genetic bottlenecks in such populations should be re-examined.

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Use of multivariate methods in forest research site selection

Canadian Journal of Forest Research ◽

10.1139/x91-219 ◽

1991 ◽

Vol 21 (11) ◽

pp. 1573-1580 ◽

Cited By ~ 29

Author(s):

Andrew J. Burton ◽

Carl W. Ramm ◽

Kurt S. Pregitzer ◽

David D. Reed

Keyword(s):

Site Selection ◽

Large Scale ◽

Multivariate Methods ◽

Data Bases ◽

Principal Coordinates Analysis ◽

Research Site ◽

Principal Coordinates ◽

Alternative Sites ◽

Existing Data ◽

Selection Of

In large-scale gradient studies, selection of the best research sites is critical but time-consuming and costly. Multivariate methods can be used to quickly identify suitable sites from existing data bases. Based on a study of acid deposition in the Great Lakes region (the Michigan Gradient Study), we illustrate the use of multivariate methods in screening potential research sites for similarity. Sites were examined using cluster analysis, principal coordinates analysis, and correspondence analysis. The graphical displays generated by the multivariate methods were used to identify similar sites across the gradient. A list of 31 potential sites was reduced to 5 similar research sites and several alternative sites. The results of the multivariate methods compared well with more traditional methods of research site selection but allowed for multiple comparisons of many potential sites using a variety of data from existing data bases. By eliminating sites that are unacceptable with respect to available data, the multivariate methods reduce the number of sites that require field visitation prior to final site verification. This process represents a substantial savings in time and effort when dealing with a long list of potential research sites.

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Unraveling city-specific signature and identifying sample origin locations for the data from CAMDA MetaSUB challenge

10.21203/rs.2.20675/v1 ◽

2020 ◽

Author(s):

Runzhi Zhang ◽

Alejandro R. Walker ◽

Susmita Datta

Keyword(s):

Machine Learning ◽

Feature Selection ◽

Error Rates ◽

Average Error ◽

Importance Score ◽

Learning Methods ◽

Principal Coordinates Analysis ◽

Principal Coordinates ◽

Total Variability ◽

The Common

Abstract BackgroundComposition of microbial communities can be location specific, and the different abundance of taxon within location could help us to unravel city-specific signature and predict the sample origin locations accurately. In this study, the whole genome shotgun (WGS) metagenomics data from samples across 16 cities around the world and samples from another 8 cities were provided as the main and mystery datasets respectively as the part of the CAMDA 2019 MetaSUB “Forensic Challenge”. The feature selection, normalization, three methods of machine learning, PCoA (Principal Coordinates Analysis) and ANCOM (Analysis of composition of microbiomes) were conducted for both the main and mystery datasets.ResultsFeature selection, combined with the machines learning methods, revealed that the combination of the common features was effective for predicting the origin of the samples. The average error rates of 11.6% and 30.0% of three machine learning methods were obtained for main and mystery datasets respectively. Using the samples from main dataset to predict the labels of samples from mystery dataset, nearly 89.98% of the test samples could be correctly labeled as “mystery” samples. PCoA showed that nearly 60% of the total variability of the data could be explained by the first two PCoA axes. Although many cities overlapped, the separation of some cities was found in PCoA. The results of ANCOM, combined with importance score from the Random Forest, indicated that the common “family”, “order” of the main-dataset and the common “order” of the mystery dataset provided the most efficient information for prediction respectively.ConclusionsThe results of the classification suggested that the composition of the microbiomes was distinctive across the cities, which was also supported by the results from ANCOM and importance score from the RF. The analysis utilized in this study can be of great help in field of forensic science to efficiently predict the origin of the samples. And the accurate of the prediction could be improved by more samples and better sequencing depth.

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Principal coordinate analysis of genotype × environment interaction for grain yield of bread wheat in the semi-arid regions

Genetika ◽

10.2298/gensr1303691s ◽

2013 ◽

Vol 45 (3) ◽

pp. 691-701 ◽

Cited By ~ 3

Author(s):

Naser Sabaghnia ◽

Mohtasham Mohammadi ◽

Rahmatollah Karimizadeh

Keyword(s):

Grain Yield ◽

Spanning Tree ◽

Arid Regions ◽

Minimum Spanning Tree ◽

Principal Coordinate Analysis ◽

Ge Interaction ◽

Principal Coordinates Analysis ◽

Principal Coordinates ◽

Main Effects ◽

Semi Arid

Multi-environmental trials have significant main effects and significant multiplicative genotype ? environment (GE) interaction effect. Principal coordinate analysis (PCOA) offers a more appropriate statistical analysis to deal with such situations, compared to traditional statistical methods. Eighteen bread wheat genotypes were grown in four semi-arid regions over three year seasons to study the GE interaction and yield stability and obtained data on grain yield were analyzed using PCOA. Combined analysis of variance indicated that all of the studied effects including the main effects of genotype and environments as well as the GE interaction were highly significant. According to grand means and total mean yield, test environments were grouped to two main groups as high mean yield (H) and low mean yield (L). There were five H test environments and six L test environments which analyzed in the sequential cycles. For each cycle, both scatter point diagram and minimum spanning tree plot were drawn. The identified most stable genotypes with dynamic stability concept and based on the minimum spanning tree plots and centroid distances were G1 (3310.2 kg ha-1) and G5 (3065.6 kg ha-1), and therefore could be recommended for unfavorable or poor conditions. Also, genotypes G7 (3047.2 kg ha-1) and G16 (3132.3 kg ha-1) were located several times in the vertex positions of high cycles according to the principal coordinates analysis. The principal coordinates analysis provided useful and interesting ways of investigating GE interaction of barley genotypes. Finally, the results of principal coordinates analysis in general confirmed the breeding value of the genotypes, obtained on the basis of the yield stability evaluation.

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Morphological and genetic diversity of Senecio vulgaris L. (Asteraceae) in Iran

Acta Botanica Croatica ◽

10.37427/botcro-2021-012 ◽

2021 ◽

Vol 80 (2) ◽

Author(s):

Mostafa Ebadi ◽

Rosa Eftekharian

Keyword(s):

Genetic Diversity ◽

Principal Component ◽

Morphological Characters ◽

Mantel Test ◽

Morphological Data ◽

Principal Coordinates Analysis ◽

Cauline Leaf ◽

Senecio Vulgaris ◽

Molecular Features ◽

Principal Coordinates

Senecio vulgaris L., an annual herb belonging to the Asteraceae, is widely distributed in different regions of the world. There is no information on the intraspecific variations of the morphological and molecular features of this species. In the present investigation, we studied the morphological and genetic diversity of 81 accessions of S. vulgaris collected from 10 geographical populations. Eleven inter simple sequence repeat (ISSR) primers were used for the examination of genetic variations among the populations. Analysis of molecular variance (AMOVA) and GST analyses revealed significant differences among the investigated populations. A significant correlation between genetic distance and geographical distance was revealed by the Mantel test. However, reticulation analysis indicated the occurrence of gene flow among most of the populations studied. Principal component analysis (PCA) plot showed that the number of capitula, length of the cauline leaf and plant height were the most variable morphological characters. Principal coordinates analysis (PCoA) plot revealed two groups of populations, according to molecular and morphological data. The results suggested the existence of possible intraspecific taxonomic ranks within this species.

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Genetic diversity analysis of the Greek lentil (Lens culinaris) landrace ‘Eglouvis’ using morphological and molecular markers

Plant Genetic Resources ◽

10.1017/s1479262118000096 ◽

2018 ◽

Vol 16 (5) ◽

pp. 469-477 ◽

Cited By ~ 5

Author(s):

Georgios F. Tsanakas ◽

Photini V. Mylona ◽

Katerina Koura ◽

Anthoula Gleridou ◽

Alexios N. Polidoros

Keyword(s):

Genetic Diversity ◽

Molecular Markers ◽

Genetic Variability ◽

Morphological Analysis ◽

Phenotypic Variability ◽

Market Price ◽

Genetic Distances ◽

Reaction Products ◽

Principal Coordinates Analysis ◽

Principal Coordinates

AbstractThe Greek lentil landrace ‘Eglouvis’ is cultivated continuously at the Lefkada island for more than 400 years. It has great taste, high nutritional value and high market price. In the present study, we used morphological and molecular markers to estimate genetic diversity within the landrace. Morphological analysis was based on characteristics of the seed. Molecular analysis was performed using simple sequence repeat (SSR) molecular markers in a high-resolution melting (HRM) approach. ‘Samos’ and ‘Demetra’, two of the most widely cultivated commercial lentil varieties in Greece, were used for comparisons. Morphological analysis was performed with 584 seeds randomly selected from a lot. Analysis of seed dimensions and colour distributed the samples in different categories and highlighted the phenotypic variability in ‘Eglouvis’ lentil seeds. Genetic variability was estimated from 91 individual DNA samples with 11 SSR markers using HRM analysis. Genotyping was based upon the shape of the melting curves and the difference plots; all polymerase chain reaction products were also run on agarose gels. Genetic distances of individuals and principal coordinates analysis suggested that ‘Eglouvis’ landrace has a unique genetic background that significantly differs from ‘Samos’ and ‘Demetra’ and no overlapping could be detected. Genetic variability within the ‘Eglouvis’ landrace can be considered in targeted breeding programs as a significant phytogenetic resource of lentils in Greece.

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