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Abstract: SA-PO293

A Comprehensive Transcriptome Database for Mouse Renal Tubule Segments

Session Information

Category: Fluid and Electrolytes

  • 901 Fluid and Electrolytes: Basic

Authors

  • Chen, Lihe, National Heart Lung and Blood Institute, Kensington, Maryland, United States
  • Chou, Chung-Lin, National Heart Lung and Blood Institute, Kensington, Maryland, United States
  • Knepper, Mark A., National Heart Lung and Blood Institute, Kensington, Maryland, United States
Background

The mammalian renal tubule is comprised of at least 14 segments, each with distinct cell types and unique sets of transcriptomes. Recent advances in RNA-seq techniques offer the ability to profile the transcripts at the level of single-microdissected tubules and single-cells. To better understand the mouse renal physiology and pathophysiology, a comprehensive transcriptome database for all the mouse renal segments/cells is needed.

Methods

Here, we microdissected all 14 mouse renal tubule segments and carried out single-tubule RNA-seq in each of them. These data were used to create an online database that allows for: 1) easy exploration of transcript expression; and 2) visualization of isoform distribution along the renal tubule through a genome browser, JBrowse. We also developed a flow-sorting procedure to enrich Slc12a3+ distal convoluted tubule (DCT) cells and carried out single-cell RNA-seq (10X Chromium) to study their heterogeneity.

Results

We profiled at least 3 biological samples per segment and were able to detect more than 11,000 transcripts for each mouse renal tubule segment (mean TPM >1). We identified unique patterns of protein distribution along the renal tubule, including transcription factors, metabolic enzymes, and G protein-coupled receptors. Also, we incorporated JBrowse into the database, which allows for easy and intuitive visualization of exon usage for transcripts. Our data revealed distinct segment-specific isoforms of many genes including known isoforms of ROMK (Kcnj1), Wnk1, and SPAK (Stk39). This database allowed us to identify embigin (Emb) as a negative surface marker for proximal tubule cells, which was used to enrich non-proximal cell types by FACS sorting. We profiled ~2000 embigin+ cells at a median depth of ~1000 genes. Single-cell RNA-seq analysis of Emb+CD45-DAPI-LTL-PNA-Kit- cells indicated an enrichment of DCT cells (~1000 Slc12a3+ cells). Initial results show evidence of heterogeneity of Slc12a3+ cells separating into at least two independent clusters. Both clusters lacked AQP2 and 11β-hydroxysteroid dehydrogenase signals but a high percentage expressed ENaC subunits.

Conclusion

These data allowed us to create a resource in the form of a publicly accessible web page. They also expand our knowledge of the cell types that make up the DCT.

Funding

  • Government Support - Non-U.S.