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172 results for “Genetic Network”
Data from: Evaluating otter reintroduction outcomes using genetic spatial capture-recapture modified for dendritic networks
<p>River otters (Lontra canadensis) were extirpated from New Mexico by the 1950s. A limited reintroduction occurred during 2008–2010 in which 33 otters sourced from Washington (WA) were translocated to the Upper Rio Grande Basin (URG) of New Mexico. We conducted a noninvasive genetic capture-recapture survey during the winter of 2018 by collecting fecal DNA samples from river otter scats found at latrines in the URG dendritic network of perennial waterways. Our objectives were to: 1) estimate genetic diversity and effective population size; 2) genetic divergence from the WA source population and potential connectivity with regionally proximal populations; 3) spatially explicit population density and size; and 4) population growth rate since the founder event. Between February and April 2018, we collected 1,184 fecal DNA samples from 622 individual scats at 20 latrines; genotyping was attempted at 10 otter-specific microsatellite loci for a subsample of 543 samples. A bottlenecking founder effect was strongly supported, which, combined with genetic drift, reduced genetic diversity and effective population size by 20–26% and 106–170%, respectively, compared with the WA source population. Estimated population density from spatial capture-recapture models was 0.23–0.28 otter/km of waterway, or 1 otter/3.57–4.35 km of waterway, corresponding to a total population size of 83–100 otters across 359 km of the perennial dendritic network from La Mesilla, New Mexico to Alamosa National Wildlife Refuge, Colorado. Estimated average annual population growth rate since the founder event was 1.12–1.15/year. Despite successful population establishment, the URG river otter population remains small, is genetically degraded, and does not yet meet the criteria for long-term reintroduction success. Projections suggested that the population could reach the recommended minimum viable population size of ≥400 otters by the years 2030–2033, though sufficient habitat may not exist in the URG Basin to support that many otters. </p>
FIGURE 2. Median joining network genes showing 95 in Taxonomic status of the black fly Prosimulium italicum Rivosecchi (Diptera: Simuliidae) based on genetic evidence
FIGURE 2. Median joining network genes showing 95% probability linkages among 28 haplotypes of COI and COII genes obtained from 29 individuals of P. hirtipes and P. italicum. Mutational changes are represented by ticks across network connections. The area of each circle is proportional to the number of individuals sharing the haplotype.
FIGURE 2. Haplotype network calculated from a 360 in A new species of Uroplatus (Gekkonidae) from Ankarana National Park Madagascar, of remarkably high genetic divergence
FIGURE 2. Haplotype network calculated from a 360 bp segment of the nuclear gene CMOS for the species in the Uroplatus ebenaui group.
Fig. 2 Mitochondrial haplotype network using the 590 in Differentiation of North African foxes and population genetic dynamics in the desert-insights into the evolutionary history of two sister taxa, Vulpes rueppellii and Vulpes vulpes
Fig. 2 Mitochondrial haplotype network using the 590-bp concatenated sequences from Cyt-b and D-loop and a total of 46 sequences (same as in Fig. 1, except for C. lupus not being used as an outgroup in the TCS network). a Neighbour-Net network based on uncorrected patristic distances as implemented in SPLITSTREE. Canis lupus (DQ480504) was used as an outgroup. Numbers indicate bootstrap values. Scale bar represents 0.01 sequence divergence. Highlighoed are the four species, the three V. vulpes clades and the location within the network of the V. vulpes sample from Egypt. Colour patterns are concordant with Fig. 1 and b. b Statistical parsimony network assuming a 95 % parsimony threshold, as constructed by TCS. Symbol size and branch lengths are proportional to the number of shared individuals per haplotype and the number of mutational steps amongst haplotypes, respectively. Numbers in black background also refer to the number of mutation steps between species and V. vulpes clades. Symbols and colours are concordant with Fig. 1 and a. Haplotype codes, sample origin and corresponding accession numbers are available in Online Resource Table S1
Fig. 2 Minimum-spanning network among 44 in Mitochondrial evidence for genetic diversity and low phylogeographic differentiation in the Marsh Warbler Acrocephalus palustris (Aves: Acrocephalidae)
Fig. 2 Minimum-spanning network among 44 COI haplotypes of Marsh Warbler (see Table S2). Size of circles represents the relative frequency of given haplotypes and each line between black nodes indicates a single mutational step
Data from: Replicated landscape genetic and network analyses reveal wide variation in functional connectivity for American pikas
Landscape connectivity is essential for maintaining viable populations, particularly for species restricted to fragmented habitats or naturally arrayed in metapopulations and facing rapid climate change. The importance of assessing both structural connectivity (the physical distribution of favorable habitat patches) and functional connectivity (how species move among habitat patches) for managing such species is well understood. However, the degree to which functional connectivity for a species varies among landscapes, and the resulting implications for conservation, have rarely been assessed. We used a landscape genetics approach to evaluate resistance to gene flow and, thus, to determine how landscape and climate-related variables influence gene flow for American pikas (Ochotona princeps) in eight federally managed sites in the western United States. We used those empirically-derived, individual-based landscape resistance models in conjunction with predictive occupancy models to generate patch-based network models describing functional landscape connectivity. Metareplication across landscapes enabled identification of limiting factors for dispersal that would not otherwise have been apparent. Despite the cool microclimates characteristic of pika habitat, south-facing aspects consistently represented higher resistance to movement, supporting the previous hypothesis that exposure to relatively high temperatures may limit dispersal in American pikas. We found that other barriers to dispersal included areas with a high degree of topographic relief, such as cliffs and ravines, as well as streams and distances greater than one to four kilometers depending on the site. Using the empirically-derived network models of habitat patch connectivity, we identified habitat patches that were likely disproportionately important for maintaining functional connectivity, areas in which habitat appeared fragmented, and locations that could be targeted for management actions to improve functional connectivity. We concluded that climate change, besides influencing patch occupancy as predicted by other studies, may alter landscape resistance for pikas, thereby influencing functional connectivity through multiple pathways simultaneously. Spatial autocorrelation among genotypes varied across study sites and was largest where habitat was most dispersed, suggesting that dispersal distances increased with habitat fragmentation, up to a point. This study demonstrates how landscape features linked to climate can affect functional connectivity for species with naturally fragmented distributions, and reinforces the importance of replicating studies across landscapes.
Figure 1. Haplotype network derived from 704 in Repeated sampling adds to the genetic diversity of Lepidochelys olivacea (Eschscholtz 1829) olive ridley sea turtle
Figure 1. Haplotype network derived from 704 bp mitochondrial D-loop fragment. Circle sizes are proportional to the frequency of each haplotype. The black circles are hypothetical haplotypes not sampled. Each colour represents the ocean basin where the sample was taken: blue is Pacific Ocean, yellow is Indian Ocean, red is Atlantic Ocean, and green is Indo-Pacific Ocean.
Figure 5. Minimum spanning haplotype network derived from a 658 base-pair cytochrome c oxidase subunit I in Six degrees of separation in barnacles? Assessing genetic variability in the sea-turtle epibiont Stomatolepas elegans (Costa) among turtles, beaches and oceans
Figure 5. Minimum spanning haplotype network derived from a 658 base-pair cytochrome c oxidase subunit I (COI) fragment from 57 Stomatolepas elegans collected from nine different Lepidochelys olivacea nesting on Playa Teopa, Jalisco, Mexico, six S. elegans from Caretta caretta from the western Atlantic, and six S. praegustator from C. caretta from the western Atlantic. Circle sizes are proportional to the frequency of each haplotype, with haplotype 1 being most common. Coloured pie slices are also proportional, and represent the number of S. elegans from each turtle characterized by the respective haplotype. Colours represent the nine Mexican turtles randomly sampled for S. elegans populations. Open circles with numbers indicate Atlantic haplotypes. Solid black circles designate hypothetical missing haplotypes. The network includes S. elegans haplotypes 1–21, and S. praegustator haplotypes 19, 26–30. Haplotypes 1–17, shown in colour, represent Jalisco, Mexico specimens collected from nine different turtles in the Pacific, and haplotypes 18–21 and 26–30, shown as unshaded circles, represent southeastern United States Atlantic specimens collected from six different C. caretta (see Table 1).
Figure 3. Ninety-five per cent maximum parsimony networks obtained for the 12 in Mitochondrial DNA genetic variation and phylogeography of the recently described vole species Proedromys liangshanensis Liu, Sun, Zeng and Zhao, 2007 (Rodentia: Arvicolinae)
Figure 3. Ninety-five per cent maximum parsimony networks obtained for the 12 haplotypes in Proedromys liangshanensis. Circle sizes are proportional to haplotype frequencies.
FIGURE 3. Haplotype network for the 800 in Genetic evaluation of the Baja California rock squirrel Otospermophilus atricapillus (Rodentia: Sciuridae)
FIGURE 3. Haplotype network for the 800-bp Cyt b data set includes populations from California and the Baja California Peninsula. Each perpendicular hash mark across the line between adjacent haplotypes in the network represents a single-base substitution. The circle size is directly proportional to the number of specimens per haplotype; the key to the haplotype (Table 1) is adjacent to each circle; some haplotypes are present in more than one population. The clades are in boxes; Clade A (Southern Clade, lowlands across California and Baja California Peninsula); Clade B (Northern Clade, El Dorado Natural Forest); and Clade C (Central Clade, California highlands in Yosemite). Color for the haplotype circles are based on subspecies designation (see material and methods from subspecies allocation. Solid circle = O. b. atricapillus, dark gray circle O. b. beecheyi, light gray circle O. b. douglasii, open circle = O. b. fisheri, solid ellipse = O. b. nudipes, dark gray ellipse = O. b. parvulus, light gray ellipse = O. b. rupinarum, and open ellipse = O. b. sierrae.
Stan code from: Branching networks can have opposing influences on genetic variation in riverine metapopulations
Aim: Fractal networks, represented by branching complexity in rivers, are ubiquitous in nature. In rivers, the number of either distal (e.g., in headwater streams) or confluent (e.g., in mainstems) locations can be increased along with their branching complexity. Distal- or confluent-spatial locations can result in fewer or greater corridor linkages that can alter genetic divergence at the metapopulation scale. These mechanisms underlying the resulting genetic structuring remain poorly understood at the metapopulation scale, particularly in terms of the roles of species-specific dispersal traits. The objective of this study is to mechanistically understand how branching complexity can simultaneously influence genetic divergence in opposite directions. Location: Northeastern Japan Methods: To evaluate the integrated influences of network complexity and species dispersal on genetic divergence among populations at the catchment scale, we modelled metapopulation genetic dynamics under a Bayesian inference framework by adapting empirical genetic data from four macroinvertebrate species. Simulations were then performed using empirical and virtual species-characteristics on virtual river networks. Results: Our simulation experiments showed that both greater landscape connectivity (resulting from shorter watercourse distance) and greater isolation of distal locations occurred in the more-branched river networks. These two spatial features have negative and positive influences on genetic divergence, with their relative importance varying among different species and dispersal characteristics. Specifically, genetic divergence at the metapopulation scale increased for species having higher downstream-biased dispersal but decreased for species having higher upstream-biased dispersal. Distal populations (e.g., in headwaters) have higher genetic independence when downstream-biased asymmetry is higher. Main conclusions: We found a strong association between species dispersal and evolutionary processes such as gene flow and genetic drift. This association mediates the pervasive influences of branching complexity on genetic-divergence in the metapopulation. It also highlights the importance of considering species dispersal-patterns when developing management strategies in the face of rapid environmental-change scenarios.
Figure 5. The haplotype minimum spanning network using 612 in Phylogeny of the order Phoenicopteriformes and population genetics of the Caribbean flamingo (Phoenicopterus ruber: Aves)
Figure 5. The haplotype minimum spanning network using 612 bp of the cytochrome b gene to compare colonies of Caribbean flamingos from Cuba (N = 49), Bonaire (N = 38) and Galápagos (N = 35).
Geomagnetic datasets of BJI station reconstructed through Artificial Neural Network improved by Genetic Algorithm in 2021
<p>Beijing station established in 1954 is one of the oldest geomagnetic observatories in China, which plays an important role in data exchange, and further provide data or standardization for satellite observation and geomagnetic model construction. With the development of urbanization, the observed data are greatly disturbed by subways, and data disturbed are almost unavailable. The dataset was reconstructed through Artificial Neural Network improved by Genetic Algorithm, including minutely data of three components (<em>D</em>, <em>H</em> and <em>Z</em>) in 2021. This reconstruction method has been proved to be effective.</p>
(raw dataset) "Spatial biology of Ising-like synthetic genetic networks"
<p>This is the raw data for the manuscript Simpson et al "Spatial biology of Ising-like synthetic genetic<br> networks"</p>
Congenital Heart Disease GEnetic NEtwork Study (CHD GENES)
ClinicalTrials.gov study NCT01196182. IPD Sharing: Not stated. Countries: 2. Publications: 6.
Clinical and Genetic Evaluation of Individuals With Undiagnosed Disorders Through the Undiagnosed Diseases Network
ClinicalTrials.gov study NCT02450851. IPD Sharing: Not stated. Countries: 1. Publications: 253.
Family Blood Pressure Program - GENOA (Genetic Epidemiology Network of Atherosclerosis)
ClinicalTrials.gov study NCT00234260. IPD Sharing: Not stated. Countries: 1. Publications: 12.
The Establishment of Multiple Point Prediction Model About Tacrolimus Metabolic Differences Based on Genetic Network After Liver Transplantation and the Application of Multicenter
ClinicalTrials.gov study NCT02752529. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Data from: Approaches to integrating genetic data into ecological networks
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Data from: Scale-dependent genetic structure of the Idaho giant salamander (Dicamptodon aterrimus) in stream networks
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