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242 results for “Genetic mapping”
Data from: Genetic mapping identifies a major locus spanning P450 clusters associated with pyrethroid resistance in kdr-free Anopheles arabiensis from Chad
Prevention of malaria transmission throughout much of Africa is dependent on bednets that are impregnated with pyrethroid insecticides. Anopheles arabiensis is the major malaria vector in Chad and efforts to control this vector are threatened by the emergence of pyrethroid resistance. WHO bioassays revealed that An. arabiensis from Ndjamena is resistant to pyrethroids and dichlorodiphenyltrichloroethane (DDT) but fully susceptible to carbamates and organophosphates. No 1014F or 1014S kdr alleles were detected in this population. To determine the mechanisms that are responsible for resistance, genetic crosses were established between the Ndja strain and an insecticide susceptible population from Mozambique. Resistance was inherited as an autosomal trait and quantitative trait locus (QTL) mapping identified a single major locus on chromosome 2R, which explained 24.4% of the variance in resistance. This QTL is enriched in P450 genes including 25 cytochrome P450s in total. One of these, Cyp6p4 is 22-fold upregulated in the Ndja strain compared with the susceptible. Piperonyl butoxide (PBO) synergist and biochemical assays further support a role for P450s in conferring pyrethroid resistance in this population.
Data from: Is evolution predictable? quantitative genetics under complex genotype-phenotype maps
<p>A fundamental aim of post-genomic 21st century biology is to understand the genotype-phenotype map (GPM) or how specific genetic variation relates to specific phenotypic variation. Quantitative genetics approximates such maps using linear models, and has developed methods to predict the response to selection in a population. The other major field of research concerned with the GPM, developmental evolutionary biology or evo-devo, has found the GPM to be highly nonlinear and complex. Here we quantify how the predictions of quantitative genetics are affected by the complex, nonlinear maps found in developmental biology. We found that the disagreements between predicted and observed responses to selection are common, roughly in a third of generations, systematic and due to nonlinear nature of the genotype-phenotype map. They occur at all time scales, even from one generation to the next. Our results are a step towards integrating the fields studying the GPM.</p>
Construction of genetic linkage map based on SNP markers, QTL mapping and detection of candidate genes of growth-related traits in Pacific abalone using genotyping-by-sequencing
<p><a name="_Hlk72585736"><span>Pacific abalone (<i>Haliotis discus hannai</i>) is a commercially important high valued molluscan species. Its wild population has decreased in recent years. Pacific abalone is widely cultured in Korea. Traditional breeding programs have been implemented for hatchery production of abalone seeds. To obtain more genetic information for the molecular breeding program, a high-density linkage map and quantitative trait locus (QTL) for three growth-related traits was constructed for Pacific abalone. F1 cross population with two parents were sampled to construct the linkage map using genotyping by sequencing (GBS). A total of 664,630,534 clean reads and 56,686 SNPs were generated. In sum, 3,345 segregating SNPs were used to construct a consensus linkage map. The map spanned 1,747.023 cM with 18 linkage groups and an average interval of 0.55 cM. QTL analysis revealed two significant QTL in LG10 on the consensus linkage map in each growth-related trait. Both the QTLs are located in the telomere region of the chromosome. Moreover, four potential candidate genes for growth-related traits were identified in the QTL region. Expression analysis revealed that identified genes are involved in growth regulation of abalone. The newly constructed genetic linkage map, growth-related QTLs and potential candidate genes identified in the present study can be used as valuable genetic resources and will be useful for marker-assisted selection (MAS) of Pacific abalone in molecular breeding program.</span></a></p>
Data from: Association mapping of genetic risk factors for chronic wasting disease in wild deer
Chronic wasting disease (CWD) is a fatal transmissible spongiform encephalopathy affecting North American cervids. We assessed the feasibility of association mapping CWD genetic risk factors in wild white-tailed deer (Odocoileus virginianus) and mule deer (Odocoileus hemionus) using a panel of bovine microsatellite markers from three homologous deer linkage groups predicted to contain candidate genes. These markers had a low cross-species amplification rate (27.9%) and showed weak linkage disequilibrium (<1 cM). Markers near the prion protein and the neurofibromin 1 (NF1) genes were suggestively associated with CWD status in white-tailed deer (P = 0.006) and mule deer (P = 0.02), respectively. This is the first time an association between the NF1 region and CWD has been reported.
Data from: A map-based approach to assessing genetic diversity, structure, and connectivity in the seagrass Halodule wrightii
Seagrass cover has declined in many areas of the world in a trend that has accelerated over the past several decades. This raises concern for both the impact the decline in cover has on coastal ecosystems and the effect it may have on seagrass evolutionary potential, as genotypic and genomic variation is lost. We used 8 microsatellite loci to investigate genetic diversity, structure, and connectivity in the seagrass Halodule wrightii from the Gulf of Mexico (Texas, USA) and western Atlantic (Bermuda). We examined how estimates correlated with changes in H. wrightii abundance and distribution on the Texas Gulf coast over the past 50 yr. Results show that, compared to other species, H. wrightii from this region exhibits variable clonal diversity (R = 0.02-0.81), moderate allelic diversity (mean AR = 4.09), and relatively high heterozygosity (mean He = 0.56). The patterns of genetic diversity and structure, however, do not entirely coincide with either geography or recent historical trends in seagrass distribution in this region. Results from a basin in which seagrasses have recently been expanding were consistent with expectations, as they were for an isolated site near the limit of H. wrightii's range. Results from basins in which seagrasses have been experiencing decline and/or fragmentation, however, were mixed. Genetic structure on the Texas coast was relatively weak and coincided more strongly with tidal range than with geographic barriers or distance. Rapid expansion and the discovery of identical multi-locus genotypes at several sites raises the possibility of migration via drifting vegetative fragments, as the geographic distance among certain multi-locus genotypes cannot be explained by rhizome growth models.
FIGURE 1. Map showing collection localities for L in Morphological diversity and genetic structure within Lerista kalumburu Storr, 1976 (Squamata: Scincomorpha: Sphenomorphidae) — taxonomic implications
FIGURE 1. Map showing collection localities for L. kalumburu. Type locality (Kalumburu) in red, collection locality for twotoed specimens (Theda Station) in yellow. Locality lacking tissue sample (Doongan Station) indicated with hollow symbol. (Google © 2010; Image NASA © 2012 Cnes/Spot Image Data S10, NOAA, U.S. Navy, NGA, CEBCO).
FIGURE 15. Schematic maps showing interpopulational genetic divergences within P in Taxonomic revision of Phascogale tapoatafa (Meyer, 1793) (Dasyuridae; Marsupialia), including descriptions of two new subspecies and confirmation of P. pirata Thomas, 1904 as a ' Top End' endemic
FIGURE 15. Schematic maps showing interpopulational genetic divergences within P. tapoatafa (sensu lato) for cytochrome b (ranges of pairwise raw sequence divergences): a) divergences between the 'Top End' population and each other regional population; and b) divergences among all populations of P. tapoatafa, excluding the 'Top End' population.
On the utility of Cas13d for genetic interaction mapping
<p>Scripts to calculate tau values and genetic interaction (GI) scores in knockdown experiments using Cas13d. </p>
Fig. 1. Maps displaying all 290 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 1. Maps displaying all 290 occurrence points used for Myosotis pygmy species group niche modelling (Supplementary Table S1). Maps, clockwise from top: World, New Zealand, Campbell Island, and southern South America. Colour represents a priori species: M. antarctica (pink circles); M. drucei (dark blue circles); M. pygmaea (green circles); M. brevis (yellow circles); M. glauca (light blue circles); M. "Volcanic Plateau" (grey triangles).
Evaluation of Cas13d as a tool for genetic interaction mapping
<p>This zenodo upload contains the scripts for the calculation of tau values and genetic interaction scores (GI) in knockdown experiments with Cas13d. In addition to the scripts for determining the tau values and GI scores (Calculate_tau_and_GI.zip), the script for creating the plots used and the reference files for the publication “On the utility of Cas13d for genetic interaction mapping” are also provided. Further information can be found in the README. </p>
Distribution. SE Guinea, E Liberia, S Ivory Coast, and W Ghana; populations ofeither this species, the Ivory Coast White-toothed Shrew (C. eburnea), or both species are found in S Sierra Leone and are included in the range map ofthis species but have not been investigated genetically and could represent either species. There are apparently records that represent this species from S Nigeria, although further research is needed to confirm thatthis speciesis truly found there. in Soricidae
Distribution. SE Guinea, E Liberia, S Ivory Coast, and W Ghana; populations ofeither this species, the Ivory Coast White-toothed Shrew (C. eburnea), or both species are found in S Sierra Leone and are included in the range map ofthis species but have not been investigated genetically and could represent either species. There are apparently records that represent this species from S Nigeria, although further research is needed to confirm thatthis speciesis truly found there.
Panicum hallii RIL population (HAL2 X FIL2 ) genetic map
<p>This project represents the method of constructing genetic map for the <em>Panicum hallii</em> Recombinant Inbreed Line (RIL) population. This population is a cross between one inland (HAL2) and one coastal (FIL2) natural accession of <em>P. hallii</em>. This map compromise of 441 RIL individuals genotyped for 901 markers. The raw sequences for RIL individuals are available in NCBI SRA archive Umbrella project PRJNA701489. </p>
Multi-omic Mapping of Human Pancreatic Islet Endoplasmic Reticulum and Cytokine Stress Responses Provide Type 2 Diabetes Genetic Insights
<p>The following data accompanying the manuscript can be found here:</p> <ul> <li>Expression (bulk RNA-seq & scRNA-seq) matrices</li> <li>Chromatin accessibility (bulk ATAC-seq) matrices</li> <li>TDF files for IGV browser visualization of cis-regulatory elements</li> </ul>
Simulation and empirical data for "Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations"
<p>Simulation data and empirical data used to generate figures from "Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations". Can be used with code provided on the associated github to regenerate the figures. </p>
Experimental data of genetic mapping, fine mapping or agronomic traits, related to Figures 1 and 3
<p>This dataset reports the experimental data of <span>g</span>enetic mapping<span>,</span> <span>f</span>ine mapping<span>, </span>agronomic, flowering time and yield-related traits for NIL<sup>DAN340</sup> and NIL<sup>K22</sup>, agronomic, flowering time and yield-related traits for knockout of <em>qKDR1</em>, agronomic, flowering time and yield-related traits for knockout of microRPG1<span>.</span></p>
Data from: Seeking signatures of reinforcement at the genetic level: a hitchhiking mapping and candidate gene approach in the house mouse
Reinforcement is the process by which prezygotic isolation is strengthened as a response to selection against hybridization. Most empirical support for reinforcement comes from the observation of its possible phenotypic signature: an accentuated degree of prezygotic isolation in the hybrid zone as compared to allopatry. Here, we implemented a novel approach to this question by seeking for the signature of reinforcement at the genetic level. In the house mouse, selection against hybrids and enhanced olfactory-based assortative mate preferences are observed in a hybrid zone between the two European subspecies Mus musculus musculus and M. m. domesticus, suggesting a possible recent reinforcement event. To test for the genetic signature of reinforcing selection and identify genes involved in sexual isolation, we adopted a hitchhiking mapping approach targeting genomic regions containing candidate genes for assortative mating in mice. We densely scanned these genomic regions in hybrid zone and allopatric samples using a large number of fast evolving microsatellite loci that allow the detection of recent selection events. We found a handful of loci showing the expected pattern of significant reduction in variability in populations close to the hybrid zone, showing assortative odour preference in mate choice experiments as compared to populations further away and displaying no such preference. These loci lie close to genes that we pinpoint as testable candidates for further investigation.
FIGURES 1–2 in High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis.
FIGURES 1–2. Helichus cordubensis: 1, male genitalia, ventral view; 2, lateral view of same. Locality of specimen used for the illustration: "Alta Gracia, La Granja. Sierra de Córdoba, Cordoba province, Argentina".
Data from: Chromosome-scale reference genome and RAD-based genetic map of yellow starthistle (Centaurea solstitialis) reveal putative structural variation and QTLs associated with invader traits
<p>The data directory here includes all of the data and scripts necessary to recreate the results and plots for the manuscript titled "Chromosome-scale reference genome and RAD-based genetic map of yellow starthistle (Centaurea solstitialis) reveal putative structural variation and QTLs associated with invader traits". These data include a genetic map, QTL analysis, paleolog analysis, gene synteny analysis, and assembly validation for yellow starthistle (Centaurea solstitialis).</p>
Fig. 1. Map showing the collection sites for 5 in Efficiency of RAPD, ISSR, iPBS, SCoT and phytochemical markers in the genetic relationship study of five native and economical important bamboos of North-East India
Fig. 1. Map showing the collection sites for 5 different native bamboos of North-East India. Number indicates the collection sites for the study, 1-Manipur hill; 2- Manipur Valley; 3-Mizoram; 4-Assam and 5-Sikkim. (Mapsource: https://eros.usgs.gov/).
Mapping of End Stage Renal Disease Genetic Susceptibility in African Americans by Admixture Linkage Disequilibrium
ClinicalTrials.gov study NCT00559767. IPD Sharing: Not stated. Countries: 1. Publications: 3.
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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)
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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.