Single cell RNA sequencing to dissect the molecular heterogeneity in lupus nephritis
Evan Der ... Thomas Tuschl, Chaim Putterman
Evan Der ... Thomas Tuschl, Chaim Putterman
Published May 4, 2017
Citation Information: JCI Insight. 2017;2(9):e93009. doi:10.1172/jci.insight.93009.
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Categories: Research Article Nephrology

Single cell RNA sequencing to dissect the molecular heterogeneity in lupus nephritis

Abstract

Lupus nephritis is a leading cause of mortality among systemic lupus erythematosus (SLE) patients, and its heterogeneous nature poses a significant challenge to the development of effective diagnostics and treatments. Single cell RNA sequencing (scRNA-seq) offers a potential solution to dissect the heterogeneity of the disease and enables the study of similar cell types distant from the site of renal injury to identify novel biomarkers. We applied scRNA-seq to human renal and skin biopsy tissues and demonstrated that scRNA-seq can be performed on samples obtained during routine care. Chronicity index, IgG deposition, and quantity of proteinuria correlated with a transcriptomic-based score composed of IFN-inducible genes in renal tubular cells. Furthermore, analysis of cumulative expression profiles of single cell keratinocytes dissociated from nonlesional, non–sun-exposed skin of patients with lupus nephritis also revealed upregulation of IFN-inducible genes compared with keratinocytes isolated from healthy controls. This indicates the possible use of scRNA-seq analysis of skin biopsies as a biomarker of renal disease. These data support the potential utility of scRNA-seq to provide new insights into the pathogenesis of lupus nephritis and pave the way for exploiting a readily accessible tissue to reflect injury in the kidney.

Authors

Evan Der, Saritha Ranabothu, Hemant Suryawanshi, Kemal M. Akat, Robert Clancy, Pavel Morozov, Manjunath Kustagi, Mareike Czuppa, Peter Izmirly, H. Michael Belmont, Tao Wang, Nicole Jordan, Nicole Bornkamp, Janet Nwaukoni, July Martinez, Beatrice Goilav, Jill P. Buyon, Thomas Tuschl, Chaim Putterman

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Simulated average number of detected genes by the number of mRNA transcr...

Figure 1

Simulated average number of detected genes by the number of mRNA transcripts sampled from simulated single cell transcriptomes.

Three sizes of a single cell transcriptome were simulated: 50,000 (blue); 250,000 (green); and 500,000 (red) mRNA transcripts. The simulation was based on gene frequencies from bulk HEK293 polyA RNA-seq data with 18,101 distinctive genes with 100 iterations for each point. (A) Complete graph for sampled simulated single cell transcriptome sizes from 1–500,000. Because simulated single cell transcriptomes almost never have all 18,101 genes detected in bulk RNA-seq, the average number of detected genes is asymptotically approaching the maximal number of genes with an increase of the size of simulated single cell transcriptome. (B) Enlarged fragment of near-linear part of A corresponding to the approximate number of genes detected in individual cells (700 genes). The gray dotted diagonal (y = x) represents a hypothetical linear relationship between number of transcripts sampled and number of genes detected.