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40 results for “GC content”
Data from: Study of regional differences in GC content values in chromosomes of the guppy and related fish species
<p><span><span><span><span><span><span><span><span><span><span><span>Genetic and physical mapping of the guppy (<i>P. reticulata</i>) have shown that recombination patterns differ greatly between males and females. Crossover events occur evenly across the chromosomes in females, but in male meiosis they are restricted to the tip furthest from the centromere of each chromosome, creating very high recombination rates per megabase, similar to the high rates in of pseudo-autosomal regions (PARs) of mammalian sex chromosomes. We here used the intronic GC content to indirectly infer the recombination patterns on guppy chromosomes. This is based on evidence that recombination is associated with GC-biased gene conversion, so that genome regions with high recombination rates should be detectable by high GC content. We used intron sequences and 3<sup>rd</sup> positions of codons, in order to make comparisons between sequences that are matched, as far as possible, with respect to selective constraints. Both these types of sites are likely to be under weak selection. Almost all guppy chromosomes, including the sex chromosome (LG12), prove to have very high GC values near their assembly ends, suggesting high recombination rates due to strong crossover localisation in male meiosis. Our test does not suggest that the guppy XY pair has stronger crossover localisation than the autosomes, or than the homologous chromosome in a closely related fish, the platyfish (<i>Xiphophorus maculatus</i>). We therefore conclude that the guppy XY pair has not recently undergone an evolutionary change to a different recombination pattern, or reduced its crossover rate, but that the guppy evolved Y-linkage due to acquiring a male-determining factor that also conferred the male crossover pattern. The results also identify the centromere ends of guppy chromosomes, which were not determined in the guppy genome assembly. </span></span></span></span></span></span></span></span></span></span></span></p>
Data from: MicroRNA stability in FFPE tissue samples: dependence on GC content
MicroRNAs (miRNAs) are small non-coding RNAs responsible for fine-tuning of gene expression at post-transcriptional level. The alterations in miRNA expression levels profoundly affect human health and often lead to the development of severe diseases. Currently, high throughput analyses, such as microarray and deep sequencing, are performed in order to identify miRNA biomarkers, using archival patient tissue samples. MiRNAs are more robust than longer RNAs, and resistant to extreme temperatures, pH, and formalin-fixed paraffin-embedding (FFPE) process. Here, we have compared the stability of miRNAs in FFPE cardiac tissues using next-generation sequencing. The mode read length in FFPE samples was 11 nucleotides (nt), while that in the matched frozen samples was 22 nt. Although the read counts were increased 1.7-fold in FFPE samples, compared with those in the frozen samples, the average miRNA mapping rate decreased from 32.0% to 9.4%. These results indicate that, in addition to the fragmentation of longer RNAs, miRNAs are to some extent degraded in FFPE tissues as well. The expression profiles of total miRNAs in two groups were highly correlated (0.88
Processed data for Jowhar et al, "A ubiquitous GC content signature underlies multimodal mRNA regulation by DDX3X"
<p>Processed data for Jowhar et al, "A ubiquitous GC content signature underlies multimodal mRNA regulation by DDX3X".</p> <p>It contains the data objects to reproduce all figures of the paper.</p> <p>More info here: <strong><a href="https://github.com/calviellolab/DDX3X_GC_paper">https://github.com/calviellolab/DDX3X_GC_paper</a></strong></p>
Addiitional Files: The diagrams of population structure, highly divergent regions, GC content and Nanopore reads depth, SNP number and Nanopore reads depth, and analyses of co-linearity against Nipponbare reference genome in 251 accessions.
<p>Additional Files for " <strong>A Super Pan-Genomic Landscape of Rice".</strong></p> <p>Addtional File1: Supplementary File1.Population structure of 251 rice accessions inferred by ADMIXTURE from K=6 to K=15.</p> <p>Additional File2: Supplementary File2.The diagram of co-linearity for assembled genome against Nipponbare refercne genome in 251 rice accessions.</p> <p>Additional File3: Supplementary File3. Highly divergent regions based on SV.</p> <p>Additional File4: Supplementary File4. The diagram of SNP number and Nanopore reads depth per 100kb windows in 251 rice accessions.</p> <p>Additonal File5:Supplementary File5. The diagram of GC content and the Nanopore reads depth per 10kb windows in 251 rice accessions.</p> <p> </p>
Data from: A modified GC-specific MAKER gene annotation method reveals improved and novel gene predictions of high and low GC content in Oryza sativa
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Data from: MicroRNA stability in FFPE tissue samples: dependence on GC content
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Data from: Study of regional differences in GC content values in chromosomes of the guppy and related fish species
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The amount of RNA editing sites in liverwort organellar genes is correlated with GC content and nuclear PPR protein diversity
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Raw data associated with the article: "Single-molecule DNA sequencing of widely varying GC-content using nucleotide release, capture and detection in microdroplets.", NAR, Puchtler et.al.
<p>All data taken in the production of the corresponding paper: "Single-molecule DNA sequencing of widely varying GC-content using nucleotide release, capture and detection in microdroplets."</p> <p>The associated manuscript describes a method for DNA sequencing which involves the sequential release of nucleotides from a single, immobilised strand of DNA via pyrophosphorolysis (PPL). Released nucleotides, in the form of dNTPs, are captured in microdroplets which are manipulated using an optical-EWOD platform. A detection chemistry within each droplet releases a specific dye depending on which dNTPs are present, allowing the optical read-out of bases within each droplet. Hence, by capturing bases sequentially within droplets as they are cleaved from the strand of DNA, the sequence can be optically identified.</p>
The GC-content at the 5'ends of human protein-coding genes is undergoing mutational decay
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Raw data associated with the article: "Single-molecule DNA sequencing of widely varying GC-content using nucleotide release, capture and detection in microdroplets.", NAR, Puchtler et.al.
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Evolutionary consequences of DNA methylation on the GC content in vertebrate genomes
GEO Series GSE56639. Gallus gallus. 1 samples. Type: Methylation profiling by high throughput sequencing; Third-party reanalysis.
Figure 8 from: Savych A, Marchyshyn S, Mosula L, Bilyk O, Humeniuk I, Davidenko A (2022) Analysis of amino acids content in the plant components of the antidiabetic herbal mixture by GC-MS. Pharmacia 69(1): 69-76. https://doi.org/10.3897/pharmacia.69.e77251
Figure 8 GC-MS chromatogram of derivatives of amino acids after hydrolysis in Taraxaci radices.
Figure 5 from: Savych A, Marchyshyn S, Mosula L, Bilyk O, Humeniuk I, Davidenko A (2022) Analysis of amino acids content in the plant components of the antidiabetic herbal mixture by GC-MS. Pharmacia 69(1): 69-76. https://doi.org/10.3897/pharmacia.69.e77251
Figure 5 GC-MS chromatogram of derivatives of free amino acids in Rosae fructus.
Figure 2 from: Savych A, Marchyshyn S, Mosula L, Bilyk O, Humeniuk I, Davidenko A (2022) Analysis of amino acids content in the plant components of the antidiabetic herbal mixture by GC-MS. Pharmacia 69(1): 69-76. https://doi.org/10.3897/pharmacia.69.e77251
Figure 2 GC-MS chromatogram of derivatives of amino acids after hydrolysis in Urticae folia.
Figure 3 from: Savych A, Marchyshyn S, Mosula L, Bilyk O, Humeniuk I, Davidenko A (2022) Analysis of amino acids content in the plant components of the antidiabetic herbal mixture by GC-MS. Pharmacia 69(1): 69-76. https://doi.org/10.3897/pharmacia.69.e77251
Figure 3 GC-MS chromatogram of derivatives of free amino acids in Myrtilli folia.
Figure 7 from: Savych A, Marchyshyn S, Mosula L, Bilyk O, Humeniuk I, Davidenko A (2022) Analysis of amino acids content in the plant components of the antidiabetic herbal mixture by GC-MS. Pharmacia 69(1): 69-76. https://doi.org/10.3897/pharmacia.69.e77251
Figure 7 GC-MS chromatogram of derivatives of free amino acids in Taraxaci radices.
Figure 10 from: Savych A, Marchyshyn S, Mosula L, Bilyk O, Humeniuk I, Davidenko A (2022) Analysis of amino acids content in the plant components of the antidiabetic herbal mixture by GC-MS. Pharmacia 69(1): 69-76. https://doi.org/10.3897/pharmacia.69.e77251
Figure 10 GC-MS chromatogram of derivatives of amino acids after hydrolysis in Menthae folia.
Figure 1 from: Savych A, Marchyshyn S, Mosula L, Bilyk O, Humeniuk I, Davidenko A (2022) Analysis of amino acids content in the plant components of the antidiabetic herbal mixture by GC-MS. Pharmacia 69(1): 69-76. https://doi.org/10.3897/pharmacia.69.e77251
Figure 1 GC-MS chromatogram of derivatives of free amino acids in Urticae folia.
Figure 4 from: Savych A, Marchyshyn S, Mosula L, Bilyk O, Humeniuk I, Davidenko A (2022) Analysis of amino acids content in the plant components of the antidiabetic herbal mixture by GC-MS. Pharmacia 69(1): 69-76. https://doi.org/10.3897/pharmacia.69.e77251
Figure 4 GC-MS chromatogram of derivatives of amino acids after hydrolysis in Myrtilli folia.
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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.