Kidney Week

Abstract: SA-PO192

Whole Glomerular Transcriptome Analysis from CKD Biopsies Predicts Cell Lineage-Specific Transcripts

Session Information

• Glomerular: Cell Biology
  November 04, 2017 | Location: Hall H, Morial Convention Center
  Abstract Time: 10:00 AM - 10:00 AM

Category: Glomerular

• 1003 Glomerular: Cell Biology

Authors

• Eddy, Sean, University of Michigan, Ann Arbor, Michigan, United States

Sean Eddy,

• Nair, Viji, University of Michigan, Ann Arbor, Michigan, United States

Viji Nair,

• Wei, Tao, Eli Lilly and Company, Indianapolis, Indiana, United States

Tao Wei,

• Reznichenko, Anna, AstraZeneca, Mölndal, Sweden

Anna Reznichenko,

• Menon, Rajasree, University of Michigan, Ann Arbor, Michigan, United States

Rajasree Menon,

• Hartman, John R, University of Michigan, Ann Arbor, Michigan, United States

John R Hartman,

• Otto, Edgar A., University of Michigan, Ann Arbor, Michigan, United States

Edgar A. Otto,

• Tomilo, Mark, University of Michigan, Ann Arbor, Michigan, United States

Mark Tomilo,

• Ju, Wenjun, University of Michigan, Ann Arbor, Michigan, United States

Wenjun Ju,

• Eichinger, Felix H., University of Michigan, Ann Arbor, Michigan, United States

Felix H. Eichinger,

• Godfrey, Brad A., University of Michigan, Ann Arbor, Michigan, United States

Brad A. Godfrey,

• Chen, Yu, Eli Lilly and Company, Indianapolis, Indiana, United States

Yu Chen,

• Conway, James, MedImmune, Gaithersburg, New Jersey, United States

James Conway,

• Lindenmeyer, Maja, Ludwig-Maximilians-Universität München, München, Germany

Maja Lindenmeyer,

• Cohen, Clemens D., Ludwig-Maximilians-Universität München, München, Germany

Clemens D. Cohen,

• Badal, Shawn S., Gilead Sciences, Inc., Foster City, California, United States

Shawn S. Badal,

• Wesley, Johnna D, Novo Nordisk Research Center, Seattle, Seattle, Washington, United States

Johnna D Wesley,

• Patel, Uptal D., Gilead Sciences, Inc., Foster City, California, United States

Uptal D. Patel,

• Breyer, Matthew D., Eli Lilly and Company, Indianapolis, Indiana, United States

Matthew D. Breyer,

• Duffin, Kevin L., Eli Lilly and Company, Indianapolis, Indiana, United States

Kevin L. Duffin,

• Magnone, Maria chiara, AstraZeneca, Mölndal, Sweden

Maria chiara Magnone,

• Moreno Quinn, Carol Patricia, MedImmune, Gaithersburg, New Jersey, United States

Carol Patricia Moreno Quinn,

• Kretzler, Matthias, University of Michigan, Ann Arbor, Michigan, United States

Matthias Kretzler,

Background

Single cell transcriptome analysis yields a wealth of information on cell type specific transcripts but is not feasible on a large scale, while tissue-level transcriptomic analysis yields a wealth of information on gene regulation but lacks cell type specificity. Coupling whole tissue transcriptome analysis with single cell transcriptome analysis can yield insights into cell type markers and expression profiles.

Methods

Transcriptomic profiles of microdissected glomeruli from clinically indicated renal biopsies were generated from 170 CKD patients in the European Renal cDNA Bank cohort. Gene expression modules were generated using weighted gene co-expression network analysis. Cell lineage signatures curated from published literature were used to compare with modules.

Results

Across the glomerular transcriptome, 22 co-expression modules were identified ranging in size from 76 to 2012 genes. Limiting the analysis to the most variant transcripts yielded 16 co-expression modules ranging in size from 99 to 1046 genes. Re-sampling analysis indicated that modules were stable. From the most variant transcript analysis, eigengenes were compared to cell type specific signatures and two modules (698 genes) were strongly correlated (r>0.75, p<10E-30) with a podocyte signature generated from podocyte gene set (Ju et al., 2013). Functional enrichment of these modules identified biology associated with podocyte dysfunction, fibrosis, and glomerular toxicity. These two modules contained 62% (21/34) of the podocyte genes expressed in the variant filtered dataset including NPHS1 and WT1, and 69% (93/134) of previously predicted podocyte genes; 11-33% of the remaining genes in the podocyte signature-associated modules were expressed in podocytes from single cell RNA-seq analysis of human kidney tissue (based on different thresholding criteria for defining single cell expression).

Conclusion

This approach allows for the identification of cell-lineage specific transcripts in whole tissue transcriptome datasets and offers the opportunity to identify novel cell lineage transcripts.

Funding

• NIDDK Support –