RNA-seq of coding RNA from mouse tissues harvested from 8-week old male C57BL/6 mice (ENCODE/UW)
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
SUBMITTER: ENCODE DCC
PROVIDER: E-MTAB-2685 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Richard Sandstrom mailto:sull@u.washington.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track was produced as part of the mouse ENCODE Project. This track shows RNA-seq measured genome-wide in mouse tissues and cell lines (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?type=cellType). Poly-A selected mRNA was used as the source for transcriptome profiling of tissues and cell types that also had corresponding DNase I hypersensitive profiles. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols. Fresh tissues were harvested from mice and stored until used for preparing total RNA samples. The total RNA was used as starting material to select poly-A RNA and used for constructing SOLiD libraries according to the protocols supplied by the manufacturer. All RNA samples were spiked in with NIST standards before libraries were constructed. The RNA-seq libraries were sequenced on ABI SOLiD sequencing platform as 50-base reads according to the manufacturer's recommendations. Reads were aligned to the mm9 reference genome using ABI BioScope software version 1.2.1. Colorspace FASTQ format files were created using Heng Li's solid2fastq.pl script version 0.1.4 (Li et al., 2009a), representing 0, 1, 2, 3 color codes with the letters A, C, G, T respectively. Signal files were created from the BAM (Li et al., 2009b) alignments using BEDTools (Quinlan et al., 2010).
2012-07-20 | E-GEOD-39524 | biostudies-arrayexpress
Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Richard Sandstrom mailto:sull@u.washington.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track, produced as part of the mouse ENCODE Project, contains deep sequencing DNase data that will be used to identify sites where regulatory factors bind to the genome (footprints). Footprinting is a technique used to define the DNA sequences that interact with and bind DNA-binding proteins, such as transcription factors, zinc-finger proteins, hormone-receptor complexes, and other chromatin-modulating factors like CTCF. The technique depends upon the strength and tight nature of protein-DNA interactions. In their native chromatin state, DNA sequences that interact directly with DNA-binding proteins are relatively protected from DNA degrading endonucleases, while the exposed/unbound portions are readily degraded by such endonucleases. A massively parallel next-generation sequencing technique to define the DNase hypersensitive sites in the genome was adopted. The DNase samples were sequenced using next-generation sequencing machines to significantly higher depths of 300-fold or greater. This produces a base-pair level resolution of the DNase susceptibility maps of the native chromatin state. These base-pair resolution maps represent and are dependent upon the nature and the specificity of interaction of the DNA with the regulatory/modulatory proteins binding at specific loci in the genome; thus they represent the native chromatin state of the genome under investigation. The deep sequencing approach has been used to define the footprint landscape of the genome by identifying DNA motifs that interact with known or novel DNA binding proteins. Cells were grown according to the approved ENCODE cell culture protocols (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell/mouse). Digital DNaseI was performed by DNaseI digestion of intact nuclei, followed by isolating DNaseI "double-hit" fragments (Sabo et al., 2006), and direct sequencing of fragment ends (which correspond to in vivo DNaseI cleavage sites) using the Solexa platform (27 bp reads). High-quality reads were mapped to the NCBI37/mm9 mouse genome using Bowtie 0.12.5; only unique mappings were kept. DNaseI sensitivity is directly reflected in raw tag density (Raw Signal), which is shown in the track as density of tags mapping within a 150 bp sliding window (at a 20 bp step across the genome). DNaseI hypersensitive zones (HotSpots) were identified using the HotSpot algorithm (Sabo et al., 2004). False discovery rate thresholds of 1.0% (FDR 0.01) were computed for each cell type by applying the HotSpot algorithm to an equivalent number of random uniquely mapping 36-mers. DNaseI hypersensitive sites (DHSs or Peaks) were identified as signal peaks within 1.0% (FDR 0.01) hypersensitive zones using a peak-finding algorithm. Only DNase Solexa libraries from unique cell types producing the highest quality data, as defined by Percent Tags in Hotspots (PTIH ~40%), were designated for deep sequencing to a depth of over 200 million tags. Results were validated by conventional DNaseI hypersensitivity assays using end-labeling/Southern blotting methods.
2012-09-19 | E-GEOD-40869 | biostudies-arrayexpress
Project description:This track is produced as part of the mouse ENCODE Project. This track shows DNaseI sensitivity measured genome-wide in mouse tissues and cell lines using the Digital DNaseI methodology (see below), and DNaseI hypersensitive sites. DNaseI has long been used to map general chromatin accessibility and DNaseI hypersensitivity is a universal feature of active cis-regulatory sequences. The use of this method has led to the discovery of functional regulatory elements that include enhancers, insulators, promotors, locus control regions and novel elements. For each experiment (tissue/cell type) this track shows DNaseI sensitivity as a continuous function using sequencing tag density (Signal), and discrete loci of DNaseI sensitive zones (HotSpots) and hypersensitive sites (Peaks). For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell/mouse). Fresh tissues were harvested from mice and the nuclei prepared according to the tissue appropriate protocol (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell/mouse). Digital DNaseI was performed by DNaseI digestion of intact nuclei, isolating DNaseI 'double-hit' fragments as described in Sabo et al. (2006), and direct sequencing of fragment ends (which correspond to in vivo DNaseI cleavage sites) using the Illumina IIx (and Illumina HiSeq by early 2011) platform (36 bp reads). Uniquely mapping high-quality reads were mapped to the genome using the bowtie aligner. DNaseI sensitivity is directly reflected in raw tag density, which is shown in the track as density of tags mapping within a 150 bp sliding window (at a 20 bp step across the genome). DNaseI sensitive zones (HotSpots) were identified using the HotSpot algorithm described in Sabo et al. (2004). 1.0% false discovery rate thresholds (FDR 0.01) were computed for each cell type by applying the HotSpot algorithm to an equivalent number of random uniquely mapping 36mers. DNaseI hypersensitive sites (DHSs or Peaks) were identified as signal peaks within FDR 1.0% hypersensitive zones using a peak-finding algorithm (I-max).
2012-10-03 | E-GEOD-37074 | biostudies-arrayexpress
Project description:The basic body plan and major physiological axes have been highly conserved during mammalian evolution, yet only a small fraction of the human genome sequence appears to be subject to evolutionary constraint. To quantify cis- versus trans-acting contributions to mammalian regulatory evolution, we performed genomic DNase I footprinting of the mouse genome across 25 cell and tissue types, collectively defining ~8.6 million transcription factor (TF) occupancy sites at nucleotide resolution. Here we show that mouse TF footprints conjointly encode a regulatory lexicon that is ~95% similar with that derived from human TF footprints. However, only ~20% of mouse TF footprints have human orthologues. Despite substantial turnover of the cis-regulatory landscape, nearly half of all pairwise regulatory interactions connecting mouse TF genes have been maintained in orthologous human cell types through evolutionary innovation of TF recognition sequences. Furthermore, the higher-level organization of mouse TF-to-TF connections into cellular network architectures is nearly identical with human. Our results indicate that evolutionary selection on mammalian gene regulation is targeted chiefly at the level of trans-regulatory circuitry, enabling and potentiating cis-regulatory plasticity. We performed genomic DNase I footprinting of the mouse genome across 25 cell and tissue types, collectively defining ~8.6 million transcription factor (TF) occupancy sites at nucleotide resolution.
2014-11-19 | E-GEOD-51341 | biostudies-arrayexpress
Project description:This experiment combines four RNA-Seq datasets of soybean seeds at the following developmental stages: 1) seed globular stage, E-GEOD-57349 (https://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-57349/); 2) seed heart stage, E-GEOD-57350 (https://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-57350/); 3) seed cotyledon stage, E-GEOD-57606 (https://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-57606/) and 4) seed early maturation stage, E-GEOD-46096 (https://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-46096/). Authors investigated soybean seed development because (1) soybean seeds are a major source of food and fuel, (2) soybean seeds have been an excellent system for studying the basic processes controlling seed development for over three decades, and (3) new soybean genomic resources, including the sequence of the soybean genome and the gene expression profiles for all seed compartments, tissues, and cell types, can be used to gain new insights into the regulatory processes required for seed differentiation. Authors sequenced messenger RNA populations of specific soybean seed compartments to provide new insights into gene expression that are important for âmaking a soybean seed.â
2014-05-07 | E-MTAB-4045 | biostudies-arrayexpress
Project description:This is a total RNA-seq data set of two inbred lines of maize, B73 and Mo17, extracted from experiment E-GEOD-39232 (https://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-39232/). E-GEOD-39232 is a larger study which also studied the expression of small RNAs and genome-wide cytosine methylation pattern in the two cultivars using high-throughput sequencing methods. For total RNA-seq, three biological replicates were used per cultivar. E-GEOD-39232 was originally submitted to NCBI Gene Expression Omnibus under accession number GSE39232 (http://www.ncbi.nlm.nih.gov/projects/geo/query/acc.cgi?acc=GSE39232) and later imported to ArrayExpress as E-GEOD-39232.
2014-10-20 | E-MTAB-3028 | biostudies-arrayexpress
Project description:This experiment is contains cow organism part samples and strand-specific RNA-seq data from experiment E-GEOD-41637 (https://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-41637/), which aimed at assessing tissue-specific transcriptome variation across mammals, with chicken used as an outgroup in evolutionary analyses. Each organism part was sourced from three different animals as biological replicates. This data set was originally submitted to NCBI Gene Expression Omnibus under accession number GSE41637 (http://www.ncbi.nlm.nih.gov/projects/geo/query/acc.cgi?acc=GSE41637) and later imported to ArrayExpress as E-GEOD-41637.
2012-12-21 | E-MTAB-2798 | biostudies-arrayexpress
Project description:This experiment is contains rat organism part samples and strand-specific RNA-seq data from experiment E-GEOD-41637 (https://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-41637/), which aimed at assessing tissue-specific transcriptome variation across mammals, with chicken used as an outgroup in evolutionary analyses. Each organism part was sourced from animals of three different strains (Sprague-Dawley, BN/SsNHsd and F344/Cr1). This data set was originally submitted to NCBI Gene Expression Omnibus under accession number GSE41637 (http://www.ncbi.nlm.nih.gov/projects/geo/query/acc.cgi?acc=GSE41637) and later imported to ArrayExpress as E-GEOD-41637.
2012-12-21 | E-MTAB-2800 | biostudies-arrayexpress
Project description:This experiment is contains rhesus macaque organism part samples and strand-specific RNA-seq data from experiment E-GEOD-41637 (https://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-41637/), which aimed at assessing tissue-specific transcriptome variation across mammals, with chicken used as an outgroup in evolutionary analyses. Each organism part was sourced from three different animals as biological replicates. This data set was originally submitted to NCBI Gene Expression Omnibus under accession number GSE41637 (http://www.ncbi.nlm.nih.gov/projects/geo/query/acc.cgi?acc=GSE41637) and later imported to ArrayExpress as E-GEOD-41637.
2012-12-21 | E-MTAB-2799 | biostudies-arrayexpress
Project description:This experiment is contains chicken organism part samples and strand-specific RNA-seq data from experiment E-GEOD-41637 (https://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-41637/), which aimed at assessing tissue-specific transcriptome variation across mammals, with chicken used as an outgroup in evolutionary analyses. Each organism part was sourced from three different animals as biological replicates. This data set was originally submitted to NCBI Gene Expression Omnibus under accession number GSE41637 (http://www.ncbi.nlm.nih.gov/projects/geo/query/acc.cgi?acc=GSE41637) and later imported to ArrayExpress as E-GEOD-41637.
2012-12-21 | E-MTAB-2797 | biostudies-arrayexpress