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92 results for “genomics and gene mapping”
Identification of novel genes involved in phosphate accumulation in Lotus japonicus through Genome Wide Association mapping of root system architecture and anion content
<p>130 Lotus japonicus accessions were used. The names and accession numbers are<br> listed in S6 Table. Seeds were scarified with sandpaper and then sterilized 14 minutes in 0.05%<br> sodium hypochlorite. Subsequently, seeds were rinsed and washed 5 times in sterile distilled<br> water. For the germination, seeds were positioned in imbibed filter paper, in sterile Petri dishes,<br> and wrapped in aluminium foil. After 3 days at 21°C, young seedling were transferred to square<br> plates (12 x 12 cm) containing growth medium. Both media used in this<br> study were based on Long-Ashton solution (with two levels of phosphate concentration -20 or<br> 750 μM, LP or HP, respectively) with 0.8% MES buffer (Duchefa Biochemie,<br> Haarlem, The Netherlands), 0.8% agarose (to minimize phosphate contamination), and adjusted<br> to pH 5.7 with 1M KOH. After adding the medium, plates were dried, closed, overnight in a<br> sterile laminar flow hood. Two accessions, with four replicates per each accession, were placed<br> on each plate. Each plate was replicated, with mirrored position of each accession to minimize<br> any positional growth effects. Plates were placed vertically, and plants grown under long-day<br> conditions (21°C, 16 h light/8 h dark cycle) with white light bulbs emitting 50 μmol/m 2 /s and<br> roots were exposed to light. Every day at the same time, the racks were transported to the image<br> acquisition room where images of each plate were acquired with eight Epson V600 CCD flatbed<br> color image scanners (Seiko Epson) and then immediately returned to the growth chamber.</p>
Supplemental material for: Genome-wide association study and fine-mapping using imputed sequences to prioritize candidate genes for 30 complex traits in 50,309 Holstein bulls
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Data from: Localizing FST outliers on a QTL map reveals evidence for large genomic regions of reduced gene exchange during speciation-with-gene-flow
Populations that maintain phenotypic divergence in sympatry typically show a mosaic pattern of genomic divergence, requiring a corresponding mosaic of genomic isolation (reduced gene flow). However, mechanisms that could produce the genomic isolation required for divergence-with-gene-flow have barely been explored, apart from the traditional localized effects of selection and reduced recombination near centromeres or inversions. By localizing FST outliers from a genome scan of wild pea aphid host races on a Quantitative Trait Locus (QTL) map of key traits, we test the hypothesis that between-population recombination and gene exchange are reduced over large 'divergence hitchhiking' (DH) regions. As expected under divergence hitchhiking, our map confirms that QTL and divergent markers cluster together in multiple large genomic regions. Under divergence hitchhiking, the nonoutlier markers within these regions should show signs of reduced gene exchange relative to nonoutlier markers in genomic regions where ongoing gene flow is expected. We use this predicted difference among nonoutliers to perform a critical test of divergence hitchhiking. Results show that nonoutlier markers within clusters of FST outliers and QTL resolve the genetic population structure of the two host races nearly as well as the outliers themselves, while nonoutliers outside DH regions reveal no population structure, as expected if they experience more gene flow. These results provide clear evidence for divergence hitchhiking, a mechanism that may dramatically facilitate the process of speciation-with-gene-flow. They also show the power of integrating genome scans with genetic analyses of the phenotypic traits involved in local adaptation and population divergence.
Data from: Deciphering the genomic architecture of the stickleback brain with a novel multi-locus gene-mapping approach
Quantitative traits important to organismal function and fitness, such as brain size, are presumably controlled by many small-effect loci. Deciphering the genetic architecture of such traits with traditional quantitative trait locus (QTL) mapping methods is challenging. Here, we investigated the genetic architecture of brain size (and the size of five different brain parts) in nine-spined sticklebacks (Pungitius pungitius) with the aid of novel multi-locus QTL mapping approaches based on a de-biased LASSO method. Apart from having more statistical power to detect QTL and reduced rate of false positives than conventional QTL mapping approaches, the developed methods can handle large marker panels and provide estimates of genomic heritability. Single-locus analyses of an F2-interpopulation cross with 239 individuals and 15 198 fully informative single nucleotide polymorphisms (SNPs) uncovered 79 QTL associated with variation in stickleback brain size traits. Many of these loci were in strong linkage disequilibrium (LD) with each other, and consequently, a multi-locus mapping of individual SNPs, accounting for LD structure in the data, recovered only four significant QTL. However, a multi-locus mapping of SNPs grouped by linkage group (LG) identified 14 LGs (1-6 depending on the trait) that influence variation in brain traits. For instance, 17.6% of the variation in relative brain size was explainable by cumulative effects of SNPs distributed over six LGs, whereas 42% of the variation was accounted for by all 21 LGs. Hence, the results suggest that variation in stickleback brain traits is influenced by many small-effect loci. Apart from suggesting moderately heritable (h2 ≈ 0.15-0.42) multifactorial genetic architecture of brain traits, the results highlight the challenges in identifying the loci contributing to variation in quantitative traits. Nevertheless, the results demonstrate that the novel QTL mapping approach developed here has distinctive advantages over the traditional QTL mapping methods in analyses of dense marker panels.
Supplementary data "Broad genomic workup including Optical Genome Mapping uncovers a DDX3X::MLLT10 gene fusion in Acute Myeloid Leukemia"
<pre>Supplementary data "Broad genomic workup including Optical Genome Mapping uncovers a DDX3X::MLLT10 gene fusion in Acute Myeloid Leukemia" - OGM Rare Variant Analysis for both time points extracted from Bionano Access RVP Analysis output folder: -> unfiltered annotated SV output -> unfiltered CNV output - Whole Exome Sequencing Gene Panel results as output by Varvis (Limbus) (CSV file) -> WES SNVs -> WES CNVs - Quality metrics + selected results: -> OGM; both time points -> Whole Exome Sequencing; time point 1</pre>
Optical genome mapping reveals and characterizes recurrent aberrations and new fusion genes in adult ALL
<p>Optical genome mapping results files on single patient level:</p> <p>SV (Structural Variants)</p> <p>CNV (Copy number Variants)</p> <p>Aneuploidies </p> <p>OGM raw data sets a are available from the corresponding author upon request.</p>
Data from: Localizing FST outliers on a QTL map reveals evidence for large genomic regions of reduced gene exchange during speciation-with-gene-flow
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Data from: Deciphering the genomic architecture of the stickleback brain with a novel multi-locus gene-mapping approach
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Data from: The coupling hypothesis: why genome scans may fail to map local adaptation genes
Genomic scans of multiple populations often reveal marker loci with greatly increased differentiation between populations. Often this differentiation coincides in space with contrasts in ecological factors, forming a genetic–environment association (GEA). GEAs imply a role for local adaptation, and so it is tempting to conclude that the strongly differentiated markers are themselves under ecologically based divergent selection, or are closely linked to loci under such selection. Here, we highlight an alternative and neglected explanation: intrinsic (i.e. environment-independent) pre- or post-zygotic genetic incompatibilities rather than local adaptation can be responsible for increased differentiation. Intrinsic genetic incompatibilities create endogenous barriers to gene flow, also known as tension zones, whose location can shift over time. However, tension zones have a tendency to become trapped by, and therefore to coincide with, exogenous barriers due to ecological selection. This coupling of endogenous and exogenous barriers can occur easily in spatially subdivided populations, even if the loci involved are unlinked. The result is that local adaptation explains where genetic breaks are positioned, but not necessarily their existence, which can be best explained by endogenous incompatibilities. More precisely, we show that (i) the coupling of endogenous and exogenous barriers can easily occur even when ecological selection is weak; (ii) when environmental heterogeneity is fine-grained, GEAs can emerge at incompatibility loci, but only locally, in places where habitats and gene pools are sufficiently intermingled to maintain linkage disequilibria between genetic incompatibilities, local-adaptation genes and neutral loci. Furthermore, the association between the locally adapted and intrinsically incompatible alleles (i.e. the sign of linkage disequilibrium between endogenous and exogenous loci) is arbitrary and can form in either direction. Reviewing results from the literature, we find that many predictions of our model are supported, including endogenous genetic barriers that coincide with environmental boundaries, local GEA in mosaic hybrid zones, and inverted or modified GEAs at distant locations. We argue that endogenous genetic barriers are often more likely than local adaptation to explain the majority of Fst-outlying loci observed in genome scan approaches – even when these are correlated to environmental variables.
Data from: The coupling hypothesis: why genome scans may fail to map local adaptation genes
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Data from: Interpreting the genomic landscape of speciation: a road map for finding barriers to gene flow
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KSHV chromatin looping facilitates effective gene expression: high-resolution mapping of K-Rta binding sites in the KSHV genome
GEO Series GSE99950. Homo sapiens. 6 samples. Type: Other; Genome binding/occupancy profiling by high throughput sequencing.
Large-scale East-Asian eQTL mapping reveals novel candidate genes for LD mapping and the genomic landscape of transcriptional effects of sequence variants
GEO Series GSE53351. Homo sapiens. 301 samples. Type: Expression profiling by array.
Genome-wide maps of gene expression in alkaline sphingomyelinase knockout mice
GEO Series GSE114608. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Genome-wide maps of chromatin state(ATAC-seq) and gene expression(RNA-seq) of cold exposed Dot1L-ablated mouse brown adipose tissue
GEO Series GSE159645. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Genome-wide maps of factors and gene expression in pre-B leukemic 697 line
GEO Series GSE138031. Homo sapiens. 19 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Effect of genomic and cellular environments on gene expression noise [bulk-mapping]
GEO Series GSE223369. Homo sapiens. 3 samples. Type: Other.
Genome-wide maps of enhancer regulation connect risk variants to disease genes
GEO Series GSE285157. Homo sapiens. 16 samples. Type: Expression profiling by high throughput sequencing.
Genome-wide DNA accessibility maps and differential gene expression using ChIP-seq, ATAC-seq and RNA-seq for the human secondary fibroblast cell line hiF-T and whole worms with and without knockdown o
GEO Series GSE98758. Caenorhabditis elegans; Homo sapiens. 58 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
KSHV chromatin looping facilitates effective gene expression: high-resolution mapping of long-range chromatin interactions in the KSHV genome [Hi-C]
GEO Series GSE99946. Homo sapiens. 4 samples. Type: Other.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.