Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Laser Capture Microdissection-based RNAseq for Profiling Mouse and Human Sebaceous Gland Transcriptomes

ABSTRACT: Laser Capture Microdissection-based RNAseq for Profiling Mouse and Human Sebaceous Gland Transcriptomes

PROVIDER: PRJNA962126 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR24314847_1.fastq.gz	Fastqsanger.gz
	SRR24314847_2.fastq.gz	Fastqsanger.gz
	SRR24314848_1.fastq.gz	Fastqsanger.gz
	SRR24314848_2.fastq.gz	Fastqsanger.gz
	SRR24314849_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 10

Similar Datasets

Laser Capture Microdissection-based RNAseq for Profiling Mouse and Human Sebaceous Gland Transcriptomes

Project description:We describe the use of laser capture microdissection (LCM) to isolate human and murine sebaceous glands (SGs) for transcriptomic analysis and publish this SG transcriptomic data for reference. We show that compared to whole skin RNA sequencing, LCM RNA sequencing allows for high resolution in identifying and describing SG genes at homeostasis. Lastly, we compare this LCM of sebaceous glands to published SG clusters from single cell RNA sequencing of skin, and show that we achieve greater resolution and depth with the LCM approach.

2024-01-26 | GSE230682 | GEO

Sebaceous gland progenitor cell RNAseq during morphogenesis and steady state homeostasis

Project description:Laser capture microdissection enriched for sebaceous gland basal cells at P4, P10, P30

2019-07-15 | GSE126491 | GEO

Identification of genes involved in sebaceous gland carcinoma of the eyelid

Project description:Sebaceous gland carcinoma is the frequent malignant tumor of the eyelid. However, there is limited understanding of how altered gene expression of sebaceous gland carcinoma of the eyelid related to the pathogenesis. In this study, to identify genes involved in sebaceous gland carcinoma of the eyelid, global-scale gene expression analysis was carried out using a GeneChip® system.

2019-01-25 | GSE125582 | GEO

Laser capture microdissection of endothelial and neuronal cells from human dorsolateral prefrontal cortex

Project description:We used laser capture microdissection to isolate both microvascular endothelial cells and neurons from post mortem brain tissue from patients with schizophrenia and bipolar disorder and healthy controls. RNA was isolated from these cell populations, amplified, and analysed using Affymetrix HG133plus2.0 GeneChips. In the first instance, we used the dataset to compare the neuronal and endothelial data, in order to demonstrate that the predicted differences between cell types could be detected using this methodology. Keywords: cell type comparison, laser capture microdissection

2008-12-18 | GSE12679 | GEO

Laser Capture Microdissection and RNA Sequencing Human Adamantinomatous Craniopharyngioma

Project description:Laser Capture Microdissection and RNA Sequencing Human Adamantinomatous Craniopharyngioma

| PRJEB18054 | ENA

Laser Capture Microdissection (LCM) analysis of mycorrhizal rice roots

Project description:Laser Capture Microdissection (LCM) analysis of mycorrhizal rice roots

| PRJNA492135 | ENA

Laser Capture Microdissection and RNA Sequencing Human Adamantinomatous Craniopharyngioma

Project description:Laser capture microdissection of cluster cells, palisading epithelium and glial tissue from 2 cases of human adamantinomatous craniopharyngioma. 1 case performed in duplicate.

2018-04-11 | E-MTAB-5266 | biostudies-arrayexpress

Lung cancer transcriptomes refined with laser capture microdissection.

Project description:We evaluated the importance of tumor cell selection for generating gene signatures in non-small cell lung cancer. Tumor and nontumor tissue from macroscopically dissected (Macro) surgical specimens (31 pairs from 32 subjects) was homogenized, extracted, amplified, and hybridized to microarrays. Adjacent scout sections were histologically mapped; sets of approximately 1000 tumor cells and nontumor cells (alveolar or bronchial) were procured by laser capture microdissection (LCM). Within histological strata, LCM and Macro specimens exhibited approximately 67% to 80% nonoverlap in differentially expressed (DE) genes. In a representative subset, LCM uniquely identified 300 DE genes in tumor versus nontumor specimens, largely attributable to cell selection; 382 DE genes were common to Macro, Macro with preamplification, and LCM platforms. RT-qPCR validation in a 33-gene subset was confirmatory (ρ = 0.789 to 0.964, P = 0.0013 to 0.0028). Pathway analysis of LCM data suggested alterations in known cancer pathways (cell growth, death, movement, cycle, and signaling components), among others (eg, immune, inflammatory). A unique nine-gene LCM signature had higher tumor-nontumor discriminatory accuracy (100%) than the corresponding Macro signature (87%). Comparison with Cancer Genome Atlas data sets (based on homogenized Macro tissue) revealed both substantial overlap and important differences from LCM specimen results. Thus, cell selection via LCM enhances expression profiling precision, and confirms both known and under-appreciated lung cancer genes and pathways.

| S-EPMC4215031 | biostudies-literature

Identification of Inner Mucus-Associated Bacteria by Laser Capture Microdissection

Project description:Identification of Inner Mucus-Associated Bacteria by Laser Capture Microdissection

| PRJEB28517 | ENA

Transcriptome of Ameloblastoma using Laser capture microdissection

Project description:The goal of the study was to characterize the whole genome transcriptome profiles of pure sample population of human ameloblastoma epithelial cells for examination of molecular pathways. Seventeen human ameloblastoma samples were obtained. Both fresh frozen and FFPE samples were used and placed in solution for 1-4 weeks to allow decalcification by EDTA. The tissue was sectioned at -35C at a thickness of 7 microns. These sections were used for laser capture microdissection (LCM) to isolate the neoplastic epithelial portion of the tumors, using static image settings. Total RNA was extracted from each sample and examined using the whole genome microarray against the Stratagene universal human reference RNA.

2016-09-01 | E-GEOD-68531 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data