Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
622
datasets available to search
ShareScore release 0.9.0
Dataset results
622 results for “Genomic integrity”
Supplemental data for: Classification of the Celastrales based on integration of genomic, morphological, and Sanger-sequence characters
Open the record for dataset details and reuse information.
Integrative genomic phylogeography reveals signs of mitonuclear incompatibility in a natural hybrid goby population
Open the record for dataset details and reuse information.
Data from: Integration of Random Forest with population-based outlier analyses provides insight on the genomic basis and evolution of run timing in Chinook salmon (Oncorhynchus tshawytscha)
Open the record for dataset details and reuse information.
Data from: Contrasting patterns of population connectivity between regions in a commercially important mollusc Haliotis rubra: integrating population genetics, genomics and marine LiDAR data
Open the record for dataset details and reuse information.
Data from: Chromosome-level genome assembly of a cyprinid fish Onychostoma macrolepis by integration of Nanopore Sequencing, Bionano and Hi-C technology
Open the record for dataset details and reuse information.
An integrated genomic approach identifies HOXC8 as an upstream regulator in ovarian endometrioma
Open the record for dataset details and reuse information.
Data from: Which species, how many, and from where: Integrating habitat suitability, population genomics, and abundance estimates into species reintroduction planning
Open the record for dataset details and reuse information.
Data from: Maintenance of high genome integrity over vegetative growth in the fairy-ring mushroom Marasmius oreades
Open the record for dataset details and reuse information.
Data from: Integration of genomics and transcriptomics predicts diabetic retinopathy susceptibility genes
<p class="Normal1">We determined differential gene expression in response to high glucose in lymphoblastoid cell lines derived from matched individuals with type 1 diabetes with and without retinopathy. Those genes exhibiting the largest difference in glucose response were assessed for association to diabetic retinopathy in a genome-wide association study meta-analysis. Expression Quantitative Trait Loci (eQTLs) of the glucose response genes were tested for association with diabetic retinopathy. We detected an enrichment of the eQTLs from the glucose response genes among small association p-values and identified <i>FLCN</i> as a susceptibility gene for diabetic retinopathy. Expression of <i>FLCN </i>in response to glucose was greater in individuals with diabetic retinopathy. Independent cohorts of individuals with diabetes revealed an association of <i>FLCN</i> eQTLs to diabetic retinopathy. Mendelian randomization confirmed a direct positive effect of increased <i>FLCN</i> expression on retinopathy. Integrating genetic association with gene expression implicated <i>FLCN </i>as a disease gene for diabetic retinopathy.</p>
Data from: Causes and consequences of genetic background effects illuminated by integrative genomic analysis
The phenotypic consequences of individual mutations are modulated by the wild-type genetic background in which they occur. Although such background dependence is widely observed, we do not know whether general patterns across species and traits exist, nor about the mechanisms underlying it. We also lack knowledge on how mutations interact with genetic background to influence gene expression, and how this in turn mediates mutant phenotypes. Furthermore, how genetic background influences patterns of epistasis remains unclear. To investigate the genetic basis and genomic consequences of genetic background dependence of the scallopedE3 allele on the Drosophila melanogaster wing, we generated multiple novel genome-level datasets from a mapping-by-introgression experiment and a tagged RNA gene expression dataset. In addition we used whole genome re-sequencing of the parental lines—two commonly used laboratory strains—to predict polymorphic transcription factor binding sites for SD. We integrated these data with previously published genomic datasets from expression microarrays and a modifier mutation screen. By searching for genes showing a congruent signal across multiple datasets, we were able to identify a robust set of candidate loci contributing to the background-dependent effects of mutations in sd. We also show that the majority of background-dependent modifiers previously reported are caused by higher-order epistasis, not quantitative non-complementation. These findings provide a useful foundation for more detailed investigations of genetic background dependence in this system, and this approach is likely to prove useful in exploring the genetic basis of other traits as well.
Data from: The effects of male social environment on sperm phenotype and genome integrity
Sperm function and quality are primary determinants of male reproductive performance and hence fitness. The presence of rival males has been shown to affect ejaculate and sperm traits in a wide range of taxa. However, male physiological conditions may not only affect sperm phenotypic traits but also their genetic and epigenetic signatures, affecting the fitness of the resulting offspring. We investigated the effects of male-male competition on sperm quality using TUNEL assays and geometric morphometrics in the zebrafish, Danio rerio. We found that the sperm produced by males exposed to high male-male competition had smaller heads but larger midpiece and flagellum than sperm produced by males under low competition. Head and flagella also appeared less sensitive to the osmotic stress induced by activation with water. In addition, more sperm showed signals of DNA damage in ejaculates of males under high competition. These findings suggest that the presence of a rival male may have positive effects on phenotypic traits but negative effects on DNA integrity. Overall, males facing the presence of rival males may produce faster swimming and more competitive sperm but this may come at a cost for the next generation.
Data from: Integrating nonadditive genomic relationship matrices into the study of genetic architecture of complex traits
The study of genetic architecture of complex traits has been dramatically influenced by implementing genome-wide analytical approaches during recent years. Of particular interest are genomic prediction strategies which make use of genomic information for predicting phenotypic responses instead of detecting trait-associated loci. In this work, we present the results of a simulation study to improve our understanding of the statistical properties of estimation of genetic variance components of complex traits, and of additive, dominance, and genetic effects through best linear unbiased prediction methodology. Simulated dense marker information was used to construct genomic additive and dominance matrices, and multiple alternative pedigree- and marker-based models were compared to determine if including a dominance term into the analysis may improve the genetic analysis of complex traits. Our results showed that a model containing a pedigree- or marker-based additive relationship matrix along with a pedigree-based dominance matrix provided the best partitioning of genetic variance into its components, especially when some degree of true dominance effects was expected to exist. Also, we noted that the use of a marker-based additive relationship matrix along with a pedigree-based dominance matrix had the best performance in terms of accuracy of correlations between true and estimated additive, dominance, and genetic effects.
Data from: An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice
Evolutionary studies are often limited by missing data that are critical to understanding the history of selection. Selection experiments, which reproduce rapid evolution under controlled conditions, are excellent tools to study how genomes evolve under selection. Here we present a genomic dissection of the Longshanks selection experiment, in which mice were selectively bred over 20 generations for longer tibiae relative to body mass, resulting in 13% longer tibiae in two replicates. We synthesized evolutionary theory, genome sequences and molecular genetics to understand the selection response and found that it involved both polygenic adaptation and discrete loci of major effect, with the strongest loci tending to be selected in parallel between replicates. We show that selection may favor de-repression of bone growth through inactivating two limb enhancers of an inhibitor, Nkx3-2. Our integrative genomic analyses thus show that it is possible to connect individual base-pair changes to the overall selection response.
Multimodal Features Integration: Genomics and Histopathological images for colon cancer stage prediction and survival stratification
<p>File Description</p> <p>clinical_patient_coad.xls - Clinical data for colon cancer patients<br>COAD__geneExp.xls - RNA data for colon cancer patients<br>COAD__methylation_450__TSS200-TSS1500.xls - DNA methylation data for colon cancer patients<br>COAD__miRNAExp__ReadCount.xls - miRNA data for colon cancer patients<br>COAD_DX_STG1.tar.gz - Image tiles for stage 1 colon cancer patients<br>COAD_DX_STG2.tar.gz - Image tiles for stage 2 colon cancer patients<br>COAD_DX_STG3.tar.gz - Image tiles for stage 3 colon cancer patients<br>COAD_DX_STG4.tar.gz - Image tiles for stage 4 colon cancer patients</p>
Lipofection of non-integrative CRISPR/Cas9 ribonucleoproteins in male germline stem cells: a simple, safe and effective knockout tool for germline genome engineering
<p>individual data on flow cytometry</p>
Complete genomes of Asgard archaea reveal diverse integrated and mobile genetic elements
Open the record for dataset details and reuse information.
Data from: Integrating genomic and phenotypic data to evaluate alternative phylogenetic and species delimitation hypotheses in a recent evolutionary radiation of grasshoppers
Although resolving phylogenetic relationships and establishing species limits is a primary goal of systematics, these tasks remain challenging at both conceptual and analytical levels. Here, we integrated genomic and phenotypic data and employed a comprehensive suite of coalescent-based analyses to develop and evaluate competing phylogenetic and species delimitation hypotheses in a recent evolutionary radiation of grasshoppers (Chorthippus binotatus group) composed of two species and eight putative subspecies. To resolve the evolutionary relationships within this complex, we first evaluated alternative phylogenetic hypotheses arising from multiple schemes of genomic data processing and contrasted genetic-based inferences with different sources of phenotypic information. Second, we examined the importance of number of loci, demographic priors, number and kind of phenotypic characters, and sex-based trait variation for developing alternative species delimitation hypotheses. The best-supported topology was largely compatible with phenotypic data and showed the presence of two clades corresponding to the nominative species groups, one including three well-resolved lineages and the other comprising a four-lineage polytomy and a well-differentiated sister taxon. Integrative species delimitation analyses indicated that the number of employed loci had little impact on the obtained inferences but revealed the higher power provided by an increasing number of phenotypic characters and the usefulness of assessing their phylogenetic information-content and differences between sexes in among-taxa trait variation. Overall, our study highlights the importance of integrating multiple sources of information to test competing phylogenetic hypotheses and elucidate the evolutionary history of species complexes representing early-stages of divergence where conflicting inferences are more prone to appear.
Rice genome-scale network integration reveals transcriptional regulators of grass cell wall synthesis
<p><span><span><span><span><span><span><span><span><span><span><span>Grasses have evolved distinct cell wall composition and patterning relative to dicotyledonous plants. However, despite the importance of this plant family, transcriptional regulation of its cell wall biosynthesis is poorly understood. To identify grass cell wall-associated transcription factors, we constructed the Rice Combined mutual Ranked Network (RCRN). The RCRN covers >90% of annotated rice (<i>Oryza sativa</i>) genes, is high quality, and includes most grass-specific cell wall genes, such as mixed-linkage glucan synthases and hydroxycinnamoyl acyltransferases. Comparing the RCRN and an equivalent <i>Arabidopsis </i>network suggests that grass orthologs of most genetically verified eudicot cell wall regulators also control this process in grasses, but some vary significantly in network connectivity between these divergent species. Reverse genetics, yeast-one-hybrid, and protoplast-based assays reveal that OsMYB61a activates a grass-specific acyltransferase promoter, which confirms network predictions and supports grass-specific cell wall synthesis genes being incorporated into conserved regulatory circuits. In addition, 10 of 15 tested transcription factors, including six novel <u>w</u>all-<u>a</u>ssociated regulators (WAP1, WACH1, WAHL1, WADH1, OsMYB13a, and OsMYB13b), alter abundance of cell wall-related transcripts when transiently expressed. The results highlight the quality of the RCRN for examining rice biology, provide insight into the evolution of cell wall regulation, and identify network nodes and edges that are possible leads for improving cell wall composition.</span></span></span></span></span></span></span></span></span></span></span></p>
Existential Genomics: Effects of Multimodal Rehabilitation and Integrative Care on Patients With Chronic Pain
ClinicalTrials.gov study NCT02459639. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Data from: An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice
Open the record for dataset details and reuse information.
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.