BMC GeneticsSystems BiologyPeer-reviewed journal article
Integrative analyses of multi-tissue Hi-C and eQTL data demonstrate close spatial proximity between eQTLs and their target genes
Abstract
Gene regulation is important for cells and tissues to function. At the genomic level, it has been studied from two aspects, the identification of expression quantitative trait loci (eQTLs) and identification of long-range chromatin interactions. It is important to understand their relationship, such as whether eQTLs regulate their target genes through physical chromatin interaction. Although previous studies have suggested enrichment of eQTLs in regions with a high chromatin interaction frequency, it is unclear whether this relationship is consistent across different tissues and cell lines and whether there would be any tissue-specific patterns. Here, we performed integrative analyses of eQTL and high-throughput chromatin conformation capture (Hi-C) data from 11 human primary tissue types and 2 human cell lines. We found that chromatin interaction frequency is positively correlated with the number of genes having eQTLs, and eQTLs and their target genes are more likely to fall in the same topologically associating domains than that expected from randomly generated control datasets. These results are consistent across all tissues and cell lines we evaluated. Moreover, in dorsolateral prefrontal cortex, spleen, hippocampus, pancreas and aorta, tissue-specific eQTLs are enriched in tissue-specific frequently interacting regions. These results reveal a more detailed picture of the complicated relationship between different mechanisms of gene regulation.\n\nAuthor summaryWhole-genome gene regulation has been studied in tissues and cell lines from multiple perspectives, including identification of expression quantitative trait loci (eQTLs) and identification of long-range chromatin interactions. These two complementary approaches focus on different aspects of gene regulation, one being statistical across individuals while the other being physical within a sample. Integrating results from these two approaches will help us understand their relationships, such as whether eQTLs regulate their target genes through physical chromatin interaction. We performed comprehensive analyses using data from multiple human tissues and cell lines, and showed that chromatin interaction frequency is positively associated with eQTL results in all evaluated tissues and cell lines. The observed relationships also displayed tissue-specific pattern in some tissues. Our results revealed a more detailed picture of the complicated relationship between the different mechanisms of gene regulation.
- organism: human
- assay: Hi-C
- assay: DNA methylation
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: benchmarking
- approach: statistical model
- Citations
- 21
- FWCI
- 0.99
- Field percentile
- top 28%
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