Integrated Functional Genomic Analysis Enables Annotation of Kidney Genome-Wide Association Study Loci

Abstract

Background Linking genetic risk loci identified by genome-wide association studies (GWAS) to their causal genes remains a major challenge. Disease-associated genetic variants are concentrated in regions containing regulatory DNA elements, such as promoters and enhancers. Although researchers have previously published DNA maps of these regulatory regions for kidney tubule cells and glomerular endothelial cells, maps for podocytes and mesangial cells have not been available.Methods We generated regulatory DNA maps (DNase-seq) and paired gene expression profiles (RNA-seq) from primary outgrowth cultures of human glomeruli that were composed mainly of podocytes and mesangial cells. We generated similar datasets from renal cortex cultures, to compare with those of the glomerular cultures. Because regulatory DNA elements can act on target genes across large genomic distances, we also generated a chromatin conformation map from freshly isolated human glomeruli. ResultsWe identified thousands of unique regulatory DNA elements, many located close to transcription factor genes, which the glomerular and cortex samples expressed at different levels. We found that genetic variants associated with kidney diseases (GWAS) and kidney expression quantitative trait loci were enriched in regulatory DNA regions. By combining GWAS, epigenomic, and chromatin conformation data, we functionally annotated 46 kidney disease genes. ConclusionsWe demonstrate a powerful approach to functionally connect kidney disease-/trait-associated loci to their target genes by leveraging unique regulatory DNA maps and integrated epigenomic and genetic analysis. This process can be applied to other kidney cell types and will enhance our understanding of genome regulation and its effects on gene expression in kidney disease. (C) Immunofluorescence staining for indicated proteins (green) in human glomerular cell outgrowth cultures. Nuclei are counterstained with DAPI (blue). (D) Unsupervised clustering and row-normalized expression heatmap of all differentially expressed genes in glomerular and cortex samples. (E) Heatmap of raw FPKM expression values of selected lineage-defining genes in RNA-seq datasets.the horizontal axis. Genes with greater expression in glomeruli tend to have greater numbers of DHS with higher accessibility in glomeruli (and vice versa for genes expressed at a higher level in cortex cultures). This enrichment is significant: Spearman correlation=0.45, P=4.2310 253 . (F) Enrichment of transcription factor DNA recognition motifs in constitutive (left column) and differentially accessible DHS (middle and right columns) between the two sample types. The Bonferroni-corrected P values of the enrichments using a hypergeometric distribution are shown. ChIP-seq, chromatin immunoprecipitation sequencing.

Single cell transcriptional and chromatin accessibility profiling redefine cellular heterogeneity in the adult human kidney

“…This approach can link putative regulatory regions with their target genes and has been applied to human pancreatic islets 73 , acute leukemia 74 , and multiple mouse tissues, including: hippocampus 75 , mammary gland 76 , T-cells 77 , and kidney among others 8,9 . In particular, genome wide association study (GWAS) risk loci can be linked to their target genes, which would complement the progress made using chromosome conformation capture (Hi-C) 33 . We generated cell-type-specific ciscoaccessibility networks (CCAN) that had significant overlap with a published database 40 .…”

“…We detected 214,890 accessible chromatin regions among 27,034 cells in the snATAC-seq library. We compared these regions to a previously-published dataset of DNase I-hypersensitive sites (DHS) in bulk glomeruli and tubulointerstitium 33 . DNase hypersensitivity is an alternative measure of chromatin accessibility and approximately 50% of all regions identified by our pipeline were overlapping with a DHS in the glomerulus or tubulointerstitium.…”

“…Glomerulus and tubulointerstitial DNase hypersensitive sites (DHS) were downloaded in bed format from Sieber et al 33 . Glomerulus and tubulointerstitial DHS master lists were composed by merging the tissuespecific bed files, converting to a GRanges object with the GenomicRanges package 87 , and collapsing the intervals with the reduce function.…”

Long-Range Chromatin Interactions in the Kidney

“…A lack of cell type-specific epigenomic maps or maps of open chromatin for whole kidney, kidney compartments, and kidney cell types has been a key limitation in understanding kidney-specific genetic regulation in both health and disease. In this issue of the Journal of the American Society of Nephrology, a study by Sieber et al 9 takes the first step to fill this critically important gap using DNase I hypersensitive sites sequencing to generate open chromatin information specific to kidney. Although DNA is normally wrapped around nucleosomes, regions of DNA in the genome that are transcriptionally active are not covered by nucleosomes, and they are sensitive to low-concentration DNase I, allowing the generation of a "fingerprint" to identify promoters and enhancers.…”

“…Although DNA is normally wrapped around nucleosomes, regions of DNA in the genome that are transcriptionally active are not covered by nucleosomes, and they are sensitive to low-concentration DNase I, allowing the generation of a "fingerprint" to identify promoters and enhancers. Using cells from human kidney glomeruli and tubuli after minimal culturing, Sieber et al 9 performed DNase I hypersensitive sites sequencing and identified regulatory regions in human glomeruli and tubuli. To further confirm the relationship between genetic variants and gene regulation, they generated chromatin conformation capture maps for those freshly isolated human glomeruli.…”