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27 results for “phylogenetic and genetic diversity”
Fig.2. The phylogenetic tree for 72 in Genetic Diversity Of (Brassica Napus L.) Spring Oilseed Rape
Fig.2. The phylogenetic tree for 72 individual of Brassica napus constructed on the basis of RAPD data: M - 'Maskot, S - 'Sw Savan', H -'Heros', U -'Ural', L -'Landmark'
Fig. 4 in Marked genetic diversity within Blastocystis in Australian wildlife revealed using a next generation sequencing-phylogenetic approach
Fig. 4. Relative abundance of Blastocystis subtypes (STs) in marsupial and deer species. Marsupials are represented by eastern grey kangaroos and wallabies; deer are represented by red, fallow and sambar deer. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in Marked genetic diversity within Blastocystis in Australian wildlife revealed using a next generation sequencing-phylogenetic approach
Fig. 3. Phylogenetic analysis of SSU-rRNA sequence data (aligned over 2035 positions) to infer the relationships of recognised Blastocystis subtypes (STs) as well as new STs discovered in the present study. The tree was constructed using Bayesian Inference method (MrBayes) and used Proteromonas lacertae as an outgroup. Posterior probabilities less than 0.95% are not displayed. The two novel subtypes and additional ST13 and ST24 sequences are indicated in bold. After the present analysis was completed, Santín et al. (2023) reported a subdivision of "ST10" into four STs (i.e. ST10, ST42, ST43 and ST44).
Fig. 2 in Marked genetic diversity within Blastocystis in Australian wildlife revealed using a next generation sequencing-phylogenetic approach
Fig. 2. Diagram of the method used to obtain sequence for a SSU-rRNA gene region (~1750 bp) of Blastocystis. Two primer sets were used to obtain overlapping sequences for this region.
Fig. 2 Maximum likelihood phylogenetic tree constructed using the mitochondrial cox1 gene for 103 in Genetic diversity and population genetics of large lungworms (Dictyocaulus, Nematoda) in wild deer in Hungary
ƒFig. 2 Maximum likelihood phylogenetic tree constructed using the mitochondrial cox1 gene for 103 Dictyocaulus lungworms originating from Hungary and five lungworms from GenBank indicated by their accession numbers (one dictyocaulid worm of red deer in New Zealand and four sequences of D. viviparus). Lungworms were collected from hunted deer (fallow, red and roe deer), indicated by triangle, square and circle, respectively. Geographical collecting regions are indicated for each sample
Figure 2 in Phylogenetic status and genetic diversity of corsac fox (Vulpes corsac) in Golestan Province, Iran
Figure 2. Bayesian phylogenetic tree reconstructed from the genus Vulpes and the position of corsac fox.
Figure 3 in Phylogenetic status and genetic diversity of corsac fox (Vulpes corsac) in Golestan Province, Iran
Figure 3. Haplotype network of corsac fox samples. Haplotype A included samples existing in GenBank from northern China (KJ140137 and NC0239580); other haplotypes belong to Iranian samples.
Figure. Phylogram showing phylogenetic relationships estimated using maximum likelihood analysis of 16S rRNA and COXI gene revealed the grouping of Orthochirus iranus, O. farzanpay, O. stockwelli, O. zagrosensis, O. innesi (JQ514244.1 Morocco), and O. bicolor (KT716038.1 India), with the outgroup species Androctonus crassicauda (FJ217732). in A study of genetic diversity among different population of Orthochirus sp. based on cytochrome C oxidase subunit I and 16srRNA sequencing
Figure. Phylogram showing phylogenetic relationships estimated using maximum likelihood analysis of 16S rRNA and COXI gene revealed the grouping of Orthochirus iranus, O. farzanpay, O. stockwelli, O. zagrosensis, O. innesi (JQ514244.1 Morocco), and O. bicolor (KT716038.1 India), with the outgroup species Androctonus crassicauda (FJ217732).
Figure 4 in Genetic diversity, phylogenetic and phylogeographic analyses of Oncideres impluviata (Germar, 1823) (Coleoptera: Cerambycidae) in Rio Grande do Sul state, Brazil
Figure 4 Phylogenetic tree summarizing the results of Bayesian inference (BI) and Maximum likelihood (ML). Tree shows the relationships among species of Oncideres along with the haplotype network of five populations of Oncideres impluviata from Rio Grande do Sul, Brazil. A, B and C depicts clades within Oncideres impluviata. The circle areas in the haplotype network are proportional to the frequencies of each haplotype and hatch markers represent the number of differences among haplotypes.
Figure 2 in Genetic diversity, phylogenetic and phylogeographic analyses of Oncideres impluviata (Germar, 1823) (Coleoptera: Cerambycidae) in Rio Grande do Sul state, Brazil
Figure 2 Injuries caused by Oncideres impluviata to Acacia mearnsii in the State of Rio Grande do Sul, Brazil. Girdled fallen branches in a Acacia plantation in General Câmara.Red arrows show branches girdled by O. impluviata (a). Adults of O. impluviata copulating and girdling the main trunk of a young Acacia tree in Encruzilhada do Sul (b).
Fig. 1 in Marked genetic diversity within Blastocystis in Australian wildlife revealed using a next generation sequencing-phylogenetic approach
Fig. 1. Map showing Melbourne's water catchment areas where samples were collected (2009-2022).
Figure 1 in Phylogenetic status and genetic diversity of corsac fox (Vulpes corsac) in Golestan Province, Iran
Figure 1. Geographic location of collected samples.
Figure 1 in Genetic diversity, phylogenetic and phylogeographic analyses of Oncideres impluviata (Germar, 1823) (Coleoptera: Cerambycidae) in Rio Grande do Sul state, Brazil
Figure 1 Adult specimen of O. impluviata - Dorsal view.
Figure 3 in Genetic diversity, phylogenetic and phylogeographic analyses of Oncideres impluviata (Germar, 1823) (Coleoptera: Cerambycidae) in Rio Grande do Sul state, Brazil
Figure 3 Physiographic regions of Rio Grande do Sul state, Brazil.
Phylogenetically under‐dispersed gut microbiomes are not correlated with host genomic heterozygosity in a genetically diverse reptile community
<p>We are providing semi-processed datasets relevant to the paper "Phylogenetically under-dispersed gut microbiomes across a range of host genetic diversity in a reptile community point to structuring by conserved host genes." Specifically, we include VCF files of RADseq data from host individuals, which are processed versions of the raw reads available at NCBI's Short Read Archive under PRJA744273. These data were processed for heterozygosity calculation using an adapted of the pipeline presented in Singhal et al. 2017, "Genetic diversity is largely unpredictable but scales with museum occurrences in a species-rich clade of Australian lizards."</p> <p>In addition, we include a database of 16S sequences from gut microbiome amplicon sequencing from the same host animals. The raw reads are available at NCBI's Short Read Archive under PRJNA746253. The sequences accessioned here are a curated, cleaned set of reference reads to which we realigned reads from each individual host.</p>
Figure 2. Calibrated phylogenetic tree obtained with BEAST v.1.10.4 in Cryptic lineages, cryptic barriers: historical seascapes and oceanic fronts drive genetic diversity in supralittoral rockpool beetles (Coleoptera: Hydraenidae)
Figure 2. Calibrated phylogenetic tree obtained with BEAST v.1.10.4 of Ochthebius with focus on subgenus Cobalius (purple shade) and quadricollis species group (green shade) (former subgenus 'Calobius'). Numbers at nodes represent posterior probabilities, and 95% highest posterior density are given in blue horizontal rectangles. Calibrations points used in analysis are specified by grey dots.
Figure 4. Comparative phylogenetic relationship between the 11 in Well-known species, unexpected results: high genetic diversity in declining Vipera ursinii in central, eastern and southeastern Europe
Figure 4. Comparative phylogenetic relationship between the 11 regions with both mtDNA (left) and nDNA (right). left: Mitochondrial DNA tree based on the genetic distances of the different haplotypes (combining cytochrome b and ND4; 1920 bp) within each region. right: Nuclear tree based on Cavalli-Sforza and Edwards Dc distances (Cavalli-Sforza and Edwards, 1967) calculated with the software POPULATIONS 1.2.28 (Langella, 1999) based on 5 microsatellites markers. Dashed branches correspond to discrepancies between both phylogenetic reconstructions. Both trees were not rooted. The colours are different between subspecies: green: V. ursinii rakosiensis, yellow: V. u. moldavica, blue: V. u. macrops, grey: V. u. macrops from Bistra Mt., red: V. renardi.
Phylogenetically under‐dispersed gut microbiomes are not correlated with host genomic heterozygosity in a genetically diverse reptile community
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Net N mineralization:Dimensions of Biodiversity - Genetic, Phylogenetic, Functional, and Remotely Sensed Diversity
Novel remote sensing methods for monitoring the Earth's biodiversity will be applied to experimental manipulations of plant diversity - allowing scientists to examine the linkages between plant biodiversity, soil microbe diversity and ecosystem function at multiple scales of spatial resolution. Specifically, we propose to link remotely sensed optical diversity to plant functional, phylogenetic and genotypic diversity aboveground and to net primary production (NPP), and soil properties and microbial processes belowground, as a basis for predicting ecosystem processes with remote sensing. Our central hypothesis is that i) biodiversity (genotypic, functional and phylogenetic diversity) at one trophic level (plants) drives genetic and functional diversity in other trophic levels (soil microbes) with consequences for ecosystem function and ii) that such diversity can be detected remotely at multiple scales of spatial resolution. We propose to test this hypotheses within the long-term prairie biodiversity experiment (e120 Big Bio), the newly established Forest and Biodiversity (e271 FAB 1) experiment, and the Biodiversity of Willows and Poplars (e277 BiWaP) experiment. We will measure optical properties of these plots at the leaf level, 1 m above the plant canopy and from aircraft. Leaf level sampling and percent cover estimates will be non-destructive. Biomass sampling in Big Bio will follow standard protocol for the long-term experiment. Biomass estimates in FAB and BiWaP will use non-destructive methods. Below ground sampling in BigBio will be taken within the clip strip for biomass harvest. The proposed research involves researchers at the University of Minnesota, the University of Alberta, the University of Nebraska Lincoln, the University of Wisconsin, and Appalachian State University.
Root biomass:Dimensions of Biodiversity - Genetic, Phylogenetic, Functional, and Remotely Sensed Diversity
Novel remote sensing methods for monitoring the Earth's biodiversity will be applied to experimental manipulations of plant diversity - allowing scientists to examine the linkages between plant biodiversity, soil microbe diversity and ecosystem function at multiple scales of spatial resolution. Specifically, we propose to link remotely sensed optical diversity to plant functional, phylogenetic and genotypic diversity aboveground and to net primary production (NPP), and soil properties and microbial processes belowground, as a basis for predicting ecosystem processes with remote sensing. Our central hypothesis is that i) biodiversity (genotypic, functional and phylogenetic diversity) at one trophic level (plants) drives genetic and functional diversity in other trophic levels (soil microbes) with consequences for ecosystem function and ii) that such diversity can be detected remotely at multiple scales of spatial resolution. We propose to test this hypotheses within the long-term prairie biodiversity experiment (e120 Big Bio), the newly established Forest and Biodiversity (e271 FAB 1) experiment, and the Biodiversity of Willows and Poplars (e277 BiWaP) experiment. We will measure optical properties of these plots at the leaf level, 1 m above the plant canopy and from aircraft. Leaf level sampling and percent cover estimates will be non-destructive. Biomass sampling in Big Bio will follow standard protocol for the long-term experiment. Biomass estimates in FAB and BiWaP will use non-destructive methods. Below ground sampling in BigBio will be taken within the clip strip for biomass harvest. The proposed research involves researchers at the University of Minnesota, the University of Alberta, the University of Nebraska Lincoln, the University of Wisconsin, and Appalachian State University.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.