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15,277 results for “GENETICS”
Fig. 3 in Pattern Of Genetic And Morphometric Differentiation In Maculinea Nausithous (Lepidoptera: Lycaenidae) In The Carpathian Basin
Fig. 3. UPGMA dendrogram constructed using CAVALLI-SFORSA & EDWARDS chord distances (A) and UPGMA phenogram built on the basis of the Euclidean distances among the average canonical
Fig. 1 in Pattern Of Genetic And Morphometric Differentiation In Maculinea Nausithous (Lepidoptera: Lycaenidae) In The Carpathian Basin
Fig. 1. Sample sites. Őrség region (West Hungary): Kétvölgy (Kv) and Magyarszombatfa (Mfa). Transylvania (Romania): Răscruci (Ras) and Fânatele Clujului (Fan)
Fig. 7 in Pattern Of Genetic And Morphometric Differentiation In Maculinea Nausithous (Lepidoptera: Lycaenidae) In The Carpathian Basin
Fig. 7. Results of the classification of individuals. A: Bar plot of the individuals as a result of the Bayesian clustering analysis. B: Distribution of the two genetic clusters in the two regions. 1: genetic cluster 1; 2: genetic cluster 2. C: Allocation of the individuals at the regional level on the basis of their
Fig. 1 in First record of a presumed wild common genet (Genetta genetta) in Switzerland
Fig. 1. Screen capture of the video recording a common genet (Genetta genetta) walking away from a camera trap set in the Châtillon forest, near Bernex, Geneva. This video was trigged by the genet on the 15th June 2019 at 09:58 p.m and is the second time that supposedly the same animal triggered the same camera six days earlier. The video recordings are available at https://doi.org/10.5281/zenodo.3617966.
Genetic background and thermal regime influence adaptation to novel environment in the seed beetle, Callosobruchus maculatus
<p>Climate change is associated with the increase in both mean and variability of thermal conditions. Therefore, the use of more realistic fluctuating thermal regimes is the most appropriate laboratory method for predicting population responses to thermal heterogeneity. However, the long- and short-term implications of evolving under such conditions are not well understood. Here, we examined differences in key life history traits among populations of seed beetles (<em>Callosobruchus</em> <em>maculatus</em>) that evolved under either constant control conditions or in an environment with fluctuating daily temperatures. Specifically, individuals from two distinct genetic backgrounds were kept for 19 generations at one of two temperatures, a constant temperature (T=29°C) or a fluctuating daily cycle (T<sub>mean</sub>=33°C, T<sub>max</sub>=40°C, and T<sub>min</sub>=26°C), and were assayed either in their evolved environment or in the other environment. We found that beetles that evolved in fluctuating environments but were then switched to constant 29°C conditions had far greater lifetime reproductive success compared to beetles that were kept in their evolved environments. This increase in reproductive success suggests that beetles raised in fluctuating environments may have evolved greater thermal breadth than control condition beetles. In addition, the degree of sexual dimorphism in body size and development varied as a function of genetic background, evolved thermal environment, and current temperature conditions. These results highlight not only the value of incorporating diel fluctuations into climate research but also suggest that populations that experience variability in temperature may be better able to respond to both short- and long-term changes in environmental conditions.</p>
blaPEC genetic environment
<p>Annotations of the region that sometimes carries <em>bla</em>PEC in <em>Pectobacterium</em>. For untruncated genome, DNA sequence between <em>btsS</em> and <em>glpT</em> was extracted and annotated using Prokka (v1.14.5) with standard parameters. The genomes are designated by their original accession number (GenBank assembly accession).</p> <p>HTML color code used in the main phylogenetic tree from the related paper is specified.</p>
Data from: Context matters: the landscape matrix determines the population genetic structure of temperate forest herbs across Europe
<p>Context. Plant populations in agricultural landscapes are mostly fragmented and their functional connectivity often depends on seed and pollen dispersal by animals. However, little is known about how the interactions of seed and pollen dispersers with the agricultural matrix translate into gene flow among plant populations.</p> <p>Objectives. We aimed to identify effects of the landscape structure on the genetic diversity within, and the genetic differentiation among, spatially isolated populations of three temperate forest herbs. We asked, whether different arable crops have different effects, and whether the orientation of linear landscape elements relative to the gene dispersal direction matters.</p> <p>Methods. We analysed the species' population genetic structures in seven agricultural landscapes across temperate Europe using microsatellite markers. These were modelled as a function of landscape composition and configuration, which we quantified in buffer zones around, and in rectangular landscape strips between, plant populations.</p> <p>Results. Landscape effects were diverse and often contrasting between species, reflecting their association with different pollen- or seed dispersal vectors. Differentiating crop types rather than lumping them together yielded higher proportions of explained variation. Some linear landscape elements had both a channelling and hampering effect on gene flow, depending on their orientation.</p> <p>Conclusions. Landscape structure is a more important determinant of the species' population genetic structure than habitat loss and fragmentation <i>per se</i>. Landscape planning with the aim to enhance the functional connectivity among spatially isolated plant populations should consider that even species of the same ecological guild might show distinct responses to the landscape structure.</p>
Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities: discovery cohort meta data and parsed TCR repertoire data
<p>Meta data corresponding the the discovery cohort for the paper, "Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities" by Magdalena L Russell, Aisha Souquette, David M Levine, Stefan A Schattgen, E Kaitlynn Allen, Guillermina Kuan, Noah Simon, Angel Balmaseda, Aubree Gordon, Paul G Thomas, Frederick A Matsen IV, and Philip Bradley. These meta data include: </p> <p>(1) a file mapping the SNP data subject IDs to the TCR repertoire data subject IDs (gwas_id_mapping.tsv)<br> (2) a file including the PCAir PCs, self-reported ancestry, and genomic ancestry for each subject (all_pc_air.txt)<br> (3) a file including the PCAir variance explained by each PC (all_pc_air_variance.txt)<br> (3) a file including the SNP ID, chromosome, hg19 position, allele, rsid, and quality control metrics for each SNP in the SNP array (emerson_snp_rs_data.tsv)<br> (4) a file including IMGT genes and sequences used for parsing TCRB repertoire data (human_vj_allele_cdr3_nucseqs.tsv)<br> (5) a file including predicted TRBD2 allele genotypes for each subject (emerson_trbd2_alleles.tsv)<br> (6) Parsed TCRB repertoire data. These raw data were first published in Emerson et. al, <em>Nature Genetics </em>2017. (emerson_parsed_tcrb.tgz)</p> <p><strong>Corresponding discovery cohort raw TCR repertoire data is available here: </strong>https: //doi.org/10.21417/B7001Z (ImmuneACCESS database)<br> <strong>Corresponding discovery cohort SNP data is available here:</strong> https: //www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001918.v1.p1 (The database of Genotypes and Phenotypes, accession number: phs001918)<br> <br> <strong>Software tools designed to work with these data are available here:</strong> https://github.com/phbradley/tcr-gwas</p>
Genetic diversity of wild and cultivated Coffea canephora in northeastern DR Congo and the implications for conservation - Additional Data
<p>List of wild and cultivated <em>Coffea canephora </em>accessions from northeastern Democratic Republic of the Congo included in Vanden Abeele et al. 2021 - American Journal of Botany, and the corresponding alleles for each of the 18 microsatellite markers (0 indicates missing alleles).</p>
[Data from:] Genetic Analysis Reveals Three Novel QTLs Underpinning a Butterfly Egg-Induced Hypersensitive Response-Like Cell Death in Brassica Rapa
<p><strong>Background</strong></p> <p>Cabbage white butterflies (<em>Pieris</em> spp.) can be severe pests of <em>Brassica</em> crops such as Chinese cabbage, Pak choi (<em>Brassica rapa</em>) or cabbages (<em>B. oleracea</em>). Eggs of <em>Pieris</em> spp. can induce a hypersensitive response-like (HR-like) cell death which reduces egg survival in the wild black mustard (<em>B. nigra</em>). Unravelling the genetic basis of this egg-killing trait in <em>Brassica</em> crops could improve crop resistance to herbivory, reducing major crop losses and pesticides use. Here we investigated the genetic architecture of a HR-like cell death induced by <em>P. brassicae</em> eggs in <em>B. rapa.</em></p> <p><strong>Results</strong></p> <p>A germplasm screening of <em>B. rapa</em> 56 accessions, representing the genetic and geographical diversity of a <em>B. rapa</em> core collection, showed phenotypic variation for cell death. An image-based phenotyping protocol was developed to accurately measure size of HR-like cell death and was then used to identify two accessions that consistently showed weak (R-o-18) or strong cell death response (L58). Screening of 160 RILs derived from these two accessions resulted in three novel QTLs for P<em>ieris</em> b<em>rassicae-</em>induced cell death on chromosomes A02 (<em>Pbc1</em>), A03 (<em>Pbc2</em>), and A06 (<em>Pbc3</em>). The three QTLs <em>Pbc1-3</em> contain cell surface receptors, intracellular receptors and other genes involved in plant immunity processes, such as ROS accumulation and cell death formation. Synteny analysis with <em>A. thaliana</em> suggested that <em>Pbc1</em> and <em>Pbc2</em> are novel QTLs associated with this trait, while <em>Pbc3</em> contains also LecRK-I.1, a gene of <em>A. thaliana</em> previously associated with cell death induced by a <em>P. brassicae</em> egg extract.</p> <p><strong>Conclusions</strong></p> <p>This study provides the first genomic regions associated with the <em>Pieris</em> egg-induced HR-like cell death in a <em>Brassica</em> crop species. It is a step closer towards unravelling the genetic basis of an egg-killing crop resistance trait, paving the way for breeders to further fine-map and validate candidate genes.</p>
Data from: Chrysolaena obovata, A SPECIES NATIVE OF BRAZILIAN CERRADO: GENETIC DIVERSITY AND STRUCTURE OF NATURAL POPULATIONS AND POTENTIAL FOR INULIN PRODUCTION
<p><em>Chrysolaena obovata</em> (Less.) M. Dematteis, an herbaceous Asteraceae species widely distributed across different Brazilian Cerrado physiognomies, has underground organs, named rhizophores, that accumulate high concentrations of inulin-type fructans. These carbohydrates are recognized as beneficial soluble fibers for human health and are currently used in the food and pharmaceutical industries. Considering that fructans, in addition to their economic potential, provide plants with greater tolerance to drought, heat and cold, it is important to understand whether their metabolism is conserved in natural populations. In this work, we aimed to investigate if the levels of genetic diversity in the populations studied allow the selection of localities with a high genetic base and higher fructan content for future programs of <em>in</em> <em>situ</em> conservation and genetic improvement for inulin production. Therefore, we characterized the diversity, structure, and gene flow of seven natural populations from Brazilian Cerrado, using nine microsatellite loci (SSR). In addition, we compared whether the fructan composition varied between populations of different Cerrado phytophysiognomies. Overall, we found that <em>C. obovata</em> populations exhibited moderate levels of genetic diversity, low genetic differentiation, and high gene flow. This study identified two populations with less genetic diversity and therefore, greater attention should be given to conservation programs including these populations. Fructan metabolism is conserved in all populations, indicating that <em>C. obovata</em> is an important genetic resource with high potential for inulin production.</p> <p><strong>File descriptions</strong></p> <p>Population_code.txt - Contains a matrix that indicates the population_code, Population_name, Brazilian-state, Phytophysiognomy, Collection coordinates and Altitudes (m).</p> <p>Date_ Diaz et al.xlsx – Contains Genotypes crude of the individuals analyzed. Primer used for nine microsatellite loci (Camacho <em>et al</em> 2017). </p> <p>Carbohydrates_Diaz et al - Contains data for carbohydrates in <em>C. obovata</em> plant rhizophores in each population (BRA, UB, SD, SP).</p> <p><strong>Location: Brazilian Cerrado</strong></p>
Summary Statistics from "Genetically regulated gene expression and proteins revealed discordant effects" (LWAS of biomarker)
<p>Summary statistics of 92 blood protein levels. The corresponding publication is currently under revision.</p> <p> The zipped txt file is tab-delimited and contains the following columns:</p> <ul> <li>protein: protein name abbreviation</li> <li>cytoband: genomic region</li> <li>gene: gene name abbreviation</li> <li>setting: either "combined" (adj. for sex & age) or sex-stratified ("males", "females"; adj. for age)</li> <li>variant_id_hg19: SNP ID according to hg19</li> <li>variant_id_hg38: SNP ID according to hg19</li> <li>chr: chromosome</li> <li>pos_hg19: base position according to hg19</li> <li>pos_hg38: base position according to hg19</li> <li>effect_allele: also known as counted allele in additive model</li> <li>other_allele: not-counted allele</li> <li>eaf: effect allele frequency</li> <li>maf: minor allele frequency</li> <li>info: imputation info score</li> <li>n_samples: number of samples</li> <li>beta: effect estimate</li> <li>se: standard error</li> <li>zscore: Z-statistic</li> <li>pvalue: p-value</li> <li>FDR: FDR by gene and setting</li> <li>BBFDR: hierarchical FDR by setting</li> <li>hierFDR: TRUE if SNP is significant after hierarchical FDR</li> </ul>
Data and scripts for: Genetic dissection of seasonal vegetation index dynamics in maize through aerial based high-throughput phenotyping
<p>Plant phenotyping under field conditions plays an important role in agricultural research. Efficient and accurate high-throughput phenotyping strategies enable a better connection between genotype and phenotype. Unmanned aerial vehicle-based high-throughput phenotyping platforms (UAV-HTPPs) provide novel opportunities for large-scale proximal measurement of plant traits with high efficiency, high resolution, and low cost. The objective of this study was to use time series normalized difference vegetation index (NDVI) extracted from UAV-based multispectral imagery to characterize its pattern across development and conduct genetic dissection of NDVI in a large maize population. The time series NDVI data from the multispectral sensor were obtained at 5 time points across the growing season for 1,752 diverse maize accessions with a UAV-HTPP. Cluster analysis of the acquired measurements classified 1,752 maize accessions into 2 groups with distinct NDVI developmental trends. To capture the dynamics underlying these static observations, penalized-splines (P-splines) model was used to obtain genotype-specific curve parameters. Genome-wide association study (GWAS) using static NDVI values and curve parameters as phenotypic traits detected signals significantly associated with the traits. Additionally, GWAS using the projected NDVI values from the P-splines models revealed the dynamic change of genetic effects, indicating the role of gene-environment interplay in controlling NDVI across the growing season. Our results demonstrated the utility of ultra-high spatial resolution multispectral imagery, as that acquired using a UAV-based remote sensing, for genetic dissection of NDVI.</p>
Data from: Seeing the Forest for the trees: Assessing genetic offset predictions from Gradient Forest
<p><span>Gradient Forest (GF) is a machine learning algorithm designed to analyze spatial patterns of biodiversity as a function of environmental gradients. An offset measure between the GF predicted environmental association of adapted alleles and a new environment (GF Offset), is increasingly being used to predict the loss of environmentally adapted alleles under rapid environmental change, but remains mostly untested for this purpose. Here we explore the robustness of GF Offset to assumption violations, and its relationship to measures of fitness, using SLiM simulations with explicit genome architecture and a spatial metapopulation. We evaluate measures of GF Offset in: (1) a neutral model with no environmental adaptation; (2) a monogenic "population genetic" model with a single environmentally adapted locus; and (3) a polygenic "quantitative genetic" model with two adaptive traits, each adapting to a different environment. We found GF Offset to be broadly correlated with fitness offsets under both single locus and polygenic architectures. However, neutral demography, genomic architecture, and the nature of the adaptive environment can all confound relationships between GF Offset and fitness. GF Offset is a promising tool, but it is important to understand its limitations and underlying assumptions, especially when used in the context of predicting maladaptation.</span></p>
FIG. 4 in Genetic diversity of Malagasy baobabs: implications for conservation
FIG. 4. — Observed nucleotide diversity PI (π) for the six Adansonia L. species endemic to Madagascar. Northern and southern populations of A. za Baill. are combined here. When distinguishing between geographic populations of A. za, nucleotide diversity was the same as combined for southern populations (π = 0.0029), but less for northern populations (π = 0.0026).
FIG. 3 in Genetic diversity of Malagasy baobabs: implications for conservation
FIG. 3. — Principal components analysis (PCA) of Malagasy Adansonia L. colored by species. Panels represent different PCA axes from: A, 2089 SNPs for all Malagasy Adansonia for axis 1 vs axis 2; B, axis 3 vs axis 4; C, 1873 SNPs for Longitubae taxa only for axis 1 vs axis 2; and D), axis 3 vs axis 4. Northern and southern populations of A. za Baill. labeled.
FIG. 2 in Genetic diversity of Malagasy baobabs: implications for conservation
FIG. 2. — SNP-based tree from 2089 biallelic SNPs as inferred by IQ-TREE. Values on the branches represent bootstrap support for the primary clades: A, broad scale relationships with monophyletic taxa collapsed and number of samples per clade indicated in parentheses; B, detailed phylogeny for the core Longitubae clade (A. perrieri Capuron, A. madagascariensis Baill., and A. za Baill.), with individual accessions mapped to their respective geographic localities in Madagascar (B). Adansonia za (Aza) accessions are listed in red; A. madagascariensis (Ama), in blue; and A. perrieri (Ape) accessions in yellow.
FIG. 1 in Genetic diversity of Malagasy baobabs: implications for conservation
FIG. 1. — Flowers of the six species of baobabs endemic to Madagascar: A, Adansonia grandidieri Baill.; B, A. madagascariensis Baill.; C, A. perrieri Capuron; D, A. rubrostipa Jum. & H. Perrier; E, A. suarezensis H. Perrier; F, A. za Baill. Photographs by David A. Baum and Nisa Karimi.
On the genetic architecture of rapidly adapting and convergent life history traits in guppies
<p>The genetic basis of traits shapes and constrains how adaptation proceeds in nature; rapid adaptation can be facilitated by polygenic traits, which subsequently provide multiple, redundant, genetic routes to adaptive phenotypes, reducing re-use of the same genes (genetic convergence). Guppy life history traits evolve rapidly and convergently among natural high- (HP) and low-predation (LP) environments in northern Trinidad. This system has been studied extensively at the phenotypic level, but little is known about the underlying genetic architecture. Here, we use an F2 QTL design to examine the genetic basis of seven (five female, two male) guppy life history phenotypes to assess whether the genetic architecture of these traits reflects theoretical predictions. We use RAD-sequencing data (16,539 SNPs) from 370 male and 267 female F2 individuals. We perform linkage mapping, estimates of genome-wide and per-chromosome heritability (multi-locus associations), and QTL ma pping (single-locus associations). Our results are consistent with architectures of many-loci of small effect for male age and size at maturity and female interbrood period. Male trait associations are clustered on specific chromosomes, but female interbrood period exhibits a weak genome-wide signal suggesting a potentially highly polygenic component. Offspring weight and female size at maturity are also associated with a single significant QTL each. These results suggest rapid phenotypic evolution of guppies may be facilitated by polygenic trait architectures, but these could fuel redundancy and limit gene re-use across populations, in agreement with an absence of strong signatures of genetic convergence from recent population genomic analyses of wild HP-LP guppies.</p>
Genetic structure in patchy populations of a candidate foundation plant: a case study of Leymus chinensis using genetic and clonal diversity
<p><strong>PREMISE</strong>: The distribution of genetic diversity on the landscape has critical ecological and evolutionary implications. This may be especially the case on a local scale for foundation plant species since they create and define ecological communities, contributing disproportionately to ecosystem function.</p> <p><strong>METHODS</strong>: We examined the distribution of genetic diversity and clones, which we defined first as unique multilocus genotypes (MLG), and then by grouping similar MLGs into multilocus lineages (MLL). We used 186 markers from inter-simple sequence repeats (ISSR) across 358 ramets from 13 patches of the foundation grass <em>Leymus chinensis</em>. We examined the relationship between genetic and clonal diversities, their variation with patch-size, and the effect of the number of markers used to evaluate genetic diversity and structure in this species.</p> <p><strong>RESULTS</strong>: Every ramet had a unique MLG. Almost all patches consisted of individuals belonging to a single MLL. We confirmed this with a clustering algorithm to group related genotypes. The predominance of a single lineage within each patch could be the result of the accumulation of somatic mutations, limited dispersal, some sexual reproduction with partners mainly restricted to the same patch, or a combination of all three.</p> <p><strong>CONCLUSIONS</strong>: We found strong genetic structure among patches of <em>L. chinensis</em>. Consistent with previous work on the species, the clustering of similar genotypes within patches suggests that clonal reproduction combined with somatic mutation, limited dispersal, and some degree of sexual reproduction among neighbors causes individuals within a patch to be more closely related than among patches.</p>
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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.