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An eQTL Landscape of Kidney Tissue in Human Nephrotic Syndrome.

Publication ,  Journal Article
Gillies, CE; Putler, R; Menon, R; Otto, E; Yasutake, K; Nair, V; Hoover, P; Lieb, D; Li, S; Eddy, S; Fermin, D; McNulty, MT; Hacohen, N ...
Published in: Am J Hum Genet
August 2, 2018

Expression quantitative trait loci (eQTL) studies illuminate the genetics of gene expression and, in disease research, can be particularly illuminating when using the tissues directly impacted by the condition. In nephrology, there is a paucity of eQTL studies of human kidney. Here, we used whole-genome sequencing (WGS) and microdissected glomerular (GLOM) and tubulointerstitial (TI) transcriptomes from 187 individuals with nephrotic syndrome (NS) to describe the eQTL landscape in these functionally distinct kidney structures. Using MatrixEQTL, we performed cis-eQTL analysis on GLOM (n = 136) and TI (n = 166). We used the Bayesian "Deterministic Approximation of Posteriors" (DAP) to fine-map these signals, eQTLBMA to discover GLOM- or TI-specific eQTLs, and single-cell RNA-seq data of control kidney tissue to identify the cell type specificity of significant eQTLs. We integrated eQTL data with an IgA Nephropathy (IgAN) GWAS to perform a transcriptome-wide association study (TWAS). We discovered 894 GLOM eQTLs and 1,767 TI eQTLs at FDR < 0.05. 14% and 19% of GLOM and TI eQTLs, respectively, had >1 independent signal associated with its expression. 12% and 26% of eQTLs were GLOM specific and TI specific, respectively. GLOM eQTLs were most significantly enriched in podocyte transcripts and TI eQTLs in proximal tubules. The IgAN TWAS identified significant GLOM and TI genes, primarily at the HLA region. In this study, we discovered GLOM and TI eQTLs, identified those that were tissue specific, deconvoluted them into cell-specific signals, and used them to characterize known GWAS alleles. These data are available for browsing and download via our eQTL browser, "nephQTL."

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Published In

Am J Hum Genet

DOI

EISSN

1537-6605

Publication Date

August 2, 2018

Volume

103

Issue

2

Start / End Page

232 / 244

Location

United States

Related Subject Headings

  • Young Adult
  • Transcriptome
  • Quantitative Trait Loci
  • Polymorphism, Single Nucleotide
  • Nephrotic Syndrome
  • Middle Aged
  • Male
  • Kidney
  • Humans
  • Genome-Wide Association Study
 

Citation

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Chicago
ICMJE
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Gillies, C. E., Putler, R., Menon, R., Otto, E., Yasutake, K., Nair, V., … Sampson, M. G. (2018). An eQTL Landscape of Kidney Tissue in Human Nephrotic Syndrome. Am J Hum Genet, 103(2), 232–244. https://doi.org/10.1016/j.ajhg.2018.07.004
Gillies, Christopher E., Rosemary Putler, Rajasree Menon, Edgar Otto, Kalyn Yasutake, Viji Nair, Paul Hoover, et al. “An eQTL Landscape of Kidney Tissue in Human Nephrotic Syndrome.Am J Hum Genet 103, no. 2 (August 2, 2018): 232–44. https://doi.org/10.1016/j.ajhg.2018.07.004.
Gillies CE, Putler R, Menon R, Otto E, Yasutake K, Nair V, et al. An eQTL Landscape of Kidney Tissue in Human Nephrotic Syndrome. Am J Hum Genet. 2018 Aug 2;103(2):232–44.
Gillies, Christopher E., et al. “An eQTL Landscape of Kidney Tissue in Human Nephrotic Syndrome.Am J Hum Genet, vol. 103, no. 2, Aug. 2018, pp. 232–44. Pubmed, doi:10.1016/j.ajhg.2018.07.004.
Gillies CE, Putler R, Menon R, Otto E, Yasutake K, Nair V, Hoover P, Lieb D, Li S, Eddy S, Fermin D, McNulty MT, Nephrotic Syndrome Study Network (NEPTUNE), Hacohen N, Kiryluk K, Kretzler M, Wen X, Sampson MG. An eQTL Landscape of Kidney Tissue in Human Nephrotic Syndrome. Am J Hum Genet. 2018 Aug 2;103(2):232–244.
Journal cover image

Published In

Am J Hum Genet

DOI

EISSN

1537-6605

Publication Date

August 2, 2018

Volume

103

Issue

2

Start / End Page

232 / 244

Location

United States

Related Subject Headings

  • Young Adult
  • Transcriptome
  • Quantitative Trait Loci
  • Polymorphism, Single Nucleotide
  • Nephrotic Syndrome
  • Middle Aged
  • Male
  • Kidney
  • Humans
  • Genome-Wide Association Study