a catalog of biological databases
|Description:||The main product of this work is an extensive database of gene expression along the nephron provided as publicly accessible. The data also provide genome-wide maps of alternative exon usage and polyadenylation sites in the kidney.|
|University/Institution:||National Institutes of Health|
|Address:||Dr. Mark A. Knepper, National Institutes of Health, Building 10, Room 6N307, 10 Center Drive, MSC-1603, Bethesda, MD 20892-1603.|
|Contact name (PI/Team):||Mark A. Knepper|
|Contact email (PI/Helpdesk):||email@example.com|
Deep Sequencing in Microdissected Renal Tubules Identifies Nephron Segment-Specific Transcriptomes. [PMID: 25817355]
The function of each renal tubule segment depends on the genes expressed therein. High-throughput methods used for global profiling of gene expression in unique cell types have shown low sensitivity and high false positivity, thereby limiting the usefulness of these methods in transcriptomic research. However, deep sequencing of RNA species (RNA-seq) achieves highly sensitive and quantitative transcriptomic profiling by sequencing RNAs in a massive, parallel manner. Here, we used RNA-seq coupled with classic renal tubule microdissection to comprehensively profile gene expression in each of 14 renal tubule segments from the proximal tubule through the inner medullary collecting duct of rat kidneys. Polyadenylated mRNAs were captured by oligo-dT primers and processed into adapter-ligated cDNA libraries that were sequenced using an Illumina platform. Transcriptomes were identified to a median depth of 8261 genes in microdissected renal tubule samples (105 replicates in total) and glomeruli (5 replicates). Manual microdissection allowed a high degree of sample purity, which was evidenced by the observed distributions of well established cell-specific markers. The main product of this work is an extensive database of gene expression along the nephron provided as a publicly accessible webpage (https://helixweb.nih.gov/ESBL/Database/NephronRNAseq/index.html). The data also provide genome-wide maps of alternative exon usage and polyadenylation sites in the kidney. We illustrate the use of the data by profiling transcription factor expression along the renal tubule and mapping metabolic pathways.