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Epigenome-augmented eQTL-hotspots reveal genome-wide transcriptional programs in 36 human tissues.
- Source :
- Briefings in Bioinformatics; May2024, Vol. 25 Issue 3, p1-11, 11p
- Publication Year :
- 2024
-
Abstract
- Expression quantitative trait loci (eQTLs) are used to inform the mechanisms of transcriptional regulation in eukaryotic cells. However, the specificity of genome-wide eQTL identification is limited by stringent control for false discoveries. Here, we described a method based on the non-homogeneous Poisson process to identify 125 489 regions with highly frequent, multiple eQTL associations, or 'eQTL-hotspots', from the public database of 59 human tissues or cell types. We stratified the eQTL-hotspots into two classes with their distinct sequence and epigenomic characteristics. Based on these classifications, we developed a machine-learning model, E-SpotFinder, for augmented discovery of tissue- or cell-type-specific eQTL-hotspots. We applied this model to 36 tissues or cell types. Using augmented eQTL-hotspots, we recovered 655 402 eSNPs and reconstructed a comprehensive regulatory network of 2 725 380 cis -interactions among eQTL-hotspots. We further identified 52 012 modules representing transcriptional programs with unique functional backgrounds. In summary, our study provided a framework of epigenome-augmented eQTL analysis and thereby constructed comprehensive genome-wide networks of cis -regulations across diverse human tissues or cell types. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14675463
- Volume :
- 25
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Briefings in Bioinformatics
- Publication Type :
- Academic Journal
- Accession number :
- 177375740
- Full Text :
- https://doi.org/10.1093/bib/bbae109