The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Deep Sequencing in Microdissected Renal Tubules Identifies Nephron Segment–Specific Transcriptomes
Open accessAbstract
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.
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STAR: ultrafast universal RNA-seq aligner
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Mapping and quantifying mammalian transcriptomes by RNA-Seq
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RNA-Seq: a revolutionary tool for transcriptomics
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Single-cell RNA-seq: advances and future challenges
Saliba, A.-E., Westermann, A. J., Gorski, S. A., & Vogel, J. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku555 · Cited by 847
Lactate dehydrogenase. Biochemistry and function of lactate dehydrogenase
Markert, C. L. (1984) · Cell Biochemistry and Function · doi:10.1002/cbf.290020302 · Cited by 115
Cited by
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Young, M. D., & Behjati, S. (2020) · GigaScience · doi:10.1093/gigascience/giaa151 · Cited by 1,619
“These markers were then manually inspected and each cluster was assigned a cell type based on the comparison of these markers to the literature (particularly Chabardès-Garonne et al., 2003; Habuka et al., 2014; Lee, Chou, and Knepper, 2015).”
MethodSingle-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease
Park, J., Shrestha, R., Qiu, C., Kondo, A., Huang, S., Werth, M., Li, M., Barasch, J., & Suszták, K. (2018) · Science · doi:10.1126/science.aar2131 · Cited by 1,065
Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors
Young, M. D., Mitchell, T. J., Vieira Braga, F. A., Tran, M. G. B., Stewart, B. J., Ferdinand, J. R., Collord, G., Botting, R. A., Popescu, D.-M., Loudon, K. W., et al. (2018) · Science · doi:10.1126/science.aat1699 · Cited by 762
Wu, H., Kirita, Y., Donnelly, E. L., & Humphreys, B. D. (2019) · Journal of the American Society of Nephrology · doi:10.1681/asn.2018090912 · Cited by 752
Metadata
- Authors
- Lee, J. W., Chou, C.-L., & Knepper, M. A.
- Venue
- Journal of the American Society of Nephrology
- Published
- 2015-11
- Volume
- 26
- Issue
- 11
- Pages
- 2669-2677
- ISSN
- 1046-6673 (ISSN-L)
- OpenAlex
- W2111410841
- Cited by
- 540
- References
- 5
- FWCI
- 21.23
- Type
- journal article
- Language
- en
- Open access
- green
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