Mus musculus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA97575 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Comparison of sense (forward probes) and antisense (reverse probes on U74 v1 gene arrays) transcripts in mouse kidney and brain. Positive calls related to antisense transcripts were compared to the cognate signals on the 430 version of mouse genome arrays to obtain genes that co expressed sense and antisense transcripts. This had to be done manually because divergent probe IDs on the two chip generations. Experiment Overall Design: The first Affymetrix U74 mouse gene chips contains reversely oriented probe sets. These probes will hybridize to natural antisense transcripts that overlap with the sense transcript in the cognate area. Affymetrix provided a mask to identify the reverse probes. Positive calls with these reverse probes will give an estimate of the antisense transcriptome in that particular tissue. Comparison of the reversely oriented probes with correctly annotated probes will reveal the expression ratio of sense and antisense transcripts.
2008-06-14 | E-GEOD-6106 | biostudies-arrayexpress
Project description:Comparison of sense (forward probes) and antisense (reverse probes on U74 v1 gene arrays) transcripts in mouse kidney and brain. Positive calls related to antisense transcripts were compared to the cognate signals on the 430 version of mouse genome arrays to obtain genes that co expressed sense and antisense transcripts. This had to be done manually because divergent probe IDs on the two chip generations. Keywords: Qualitative comparison of expression
2006-11-07 | GSE6106 | GEO
Project description:A transcriptome study in mouse hematopoietic stem cells was performed using a sensitive SAGE method, in an attempt to detect medium and low abundant transcripts expressed in these cells. Among a total of 31,380 unique transcript, 17,326 (55%) known genes were detected, 14,054 (45%) low-copy transcripts that have no matches to currently known genes. 3,899 (23%) were alternatively spliced transcripts of the known genes and 3,754 (22%) represent anti-sense transcripts from known genes.
2009-05-20 | GSE16139 | GEO
Project description:SILAC based protein correlation profiling using size exclusion of protein complexes derived from seven Mus musculus tissues (Heart, Brain, Liver, Lung, Kidney, Skeletal Muscle, Thymus)
2018-04-24 | PXD007288 | Pride
Project description:Expression of Mouse and Human Sense-Antisense Transcript
| PRJNA103413 | ENA
Project description:A transcriptome study in mouse hematopoietic stem cells was performed using a sensitive SAGE method, in an attempt to detect medium and low abundant transcripts expressed in these cells. Among a total of 31,380 unique transcript, 17,326 (55%) known genes were detected, 14,054 (45%) low-copy transcripts that have no matches to currently known genes. 3,899 (23%) were alternatively spliced transcripts of the known genes and 3,754 (22%) represent anti-sense transcripts from known genes. Mouse hematopoietic stem cells were purified from bone marrow cells using negative and positive selection with a Magnetic-Activated Cell Sorter (MACS). total RNA and mRNA were purified from the purified cells using Trizol reagent and magnetic oligo dT beads. Double strand cDNAs were synthesized using a cDNA synthesis kit and anchored oligo dT primers. After NlaIII digestion, 3’ cDNAs were isolated and amplified through 16-cycle PCR. SAGE tags were released from the 3’ cDNA after linker ligation. Ditags were formed, concatemerized and cloned into a pZERO vector. Sequencing reactions were performed with the ET sequencing terminator kit. Sequences were collected using a Megabase 1000 sequencer. SAGE tag sequences were extracted using SAGE 2000 software.
2009-05-20 | E-GEOD-16139 | biostudies-arrayexpress
Project description:Genome-wide analysis of expression and DNA methylation at CpG-island-associated sense-antisense transcript loci in mouse
| PRJNA111365 | ENA
Project description:<p>High throughput RNA Sequencing has revealed that the human genome is widely transcribed. However, the extent of natural antisense transcription, the molecular mechanisms by which natural antisense transcripts (NATs) might affect their cognate sense genes, and the role of NATs in cancer are less well understood. Here, we use strand-specific paired-end RNA sequencing (ssRNASeq) on a cohort of 376 cancer patients covering 9 tissue types to comprehensively characterize the landscape of antisense expression. Our results reveal that greater than 60% of annotated transcripts have measureable antisense expression and the expression of sense and antisense transcript pairs is in general positively correlated. Furthermore, by studying the expression of sense/antisense pairs across tissues we identify lineage-specific, ubiquitous and cancer-specific antisense loci. Our results raise the possibility that NATs participate in the regulation of well-known tumor suppressors and oncogenes. Finally, this study provides a catalogue of cancer related genes with significant antisense transcription (oncoNAT). This resource will allow researchers to investigate the molecular mechanisms of sense/antisense regulation and further advance our understanding of their role in cancer.</p>
| phs000937 | dbGaP
Project description:SILAC based protein correlation profiling using size exclusion of protein complexes derived from Mus musculus tissues (Heart, Liver, Lung, Kidney, Skeletal Muscle, Thymus)
2021-05-05 | PXD022309 | Pride
Project description:SILAC based protein correlation profiling using size exclusion of protein complexes derived from seven Mus musculus tissues (Heart, Brain, Liver, Lung, Kidney, Skeletal Muscle, Thymus)
2024-11-07 | MSV000096331 | MassIVE