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Updated: Nov 16, 2025

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
Published on: January 9, 2020
Chromatin architecture reveals cell type-specific target genes for kidney disease risk variants
Aiping Duan1,2, Hong Wang2, Yan Zhu1,2
1National Clinical Research Center for Kidney Disease, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, Jiangsu, China.
Background:
Cell type-specific transcriptional programming results from the combinatorial interplay between the repertoire of active regulatory elements. Disease-associated variants disrupt such programming, leading to altered expression of downstream regulated genes and the onset of pathological states. However, due to the non-linear regulatory properties of non-coding elements such as enhancers, which can activate transcription at long distances and in a non-directional way, the identification of causal variants and their target genes remains challenging. Here, we provide a multi-omics analysis to identify regulatory elements associated with functional kidney disease variants, and downstream regulated genes.
Results:
In order to understand the genetic risk of kidney diseases, we generated a comprehensive dataset of the chromatin landscape of human kidney tubule cells, including transcription-centered 3D chromatin organization, histone modifications distribution and transcriptome with HiChIP, ChIP-seq and RNA-seq. We identified genome-wide functional elements and thousands of interactions between the distal elements and target genes. The results revealed that risk variants for renal tumor and chronic kidney disease were enriched in kidney tubule cells. We further pinpointed the target genes for the variants and validated two target genes by CRISPR/Cas9 genome editing techniques in zebrafish, demonstrating that SLC34A1 and MTX1 were indispensable genes to maintain kidney function.
Conclusions:
Our results provide a valuable multi-omics resource on the chromatin landscape of human kidney tubule cells and establish a bioinformatic pipeline in dissecting functions of kidney disease-associated variants based on cell type-specific epigenome.
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