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Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease
Lei Hou1,2, Xushen Xiong1,2,3, Yongjin Park1,2
1Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA.
Nature Genetics
|September 28, 2023
Summary
This study maps gene regulatory elements (AREs) and their genetic influences across human tissues. It provides insights into how genetic variants impact complex traits and diseases like schizophrenia.
Area of Science:
- Genomics
- Epigenetics
- Systems Biology
Background:
- Noncoding genetic variants significantly influence complex traits but their regulatory roles are poorly understood.
- Understanding gene regulation is crucial for deciphering the genetic basis of human diseases.
Purpose of the Study:
- To profile epigenomic variation and identify active regulatory elements (AREs) across multiple human tissues.
- To investigate genetic influences on AREs and their association with complex traits and diseases.
- To develop methods for prioritizing genetic variants, regulatory elements, and genes implicated in disease.
Main Methods:
- Epigenomic profiling of H3K27ac in 387 brain, heart, muscle, and lung samples from the Genotype-Tissue Expression (GTEx) project.
- Annotation of 282,000 active regulatory elements (AREs) and identification of sex-biased and genetically influenced AREs.
- Integration of genetic and epigenomic data to identify disease-associated loci, driver single nucleotide polymorphisms (SNPs), and impacted AREs.
- Development of genetics-based ARE-gene linking scores (gLink scores) for prioritizing SNP-ARE-gene circuits.
Main Results:
- Characterization of 282,000 AREs with tissue-specific activity patterns.
- Identification of 2,436 sex-biased AREs and 5,397 genetically influenced AREs linked to 130,000 genetic variants (haQTLs).
- Mechanistic insights for 55 genome-wide association studies (GWAS) loci, pinpointing candidate tissues, driver SNPs, and affected AREs.
- Demonstration of gLink scores' efficacy in prioritizing SNP-ARE-gene regulatory circuits.
Conclusions:
- The study provides valuable epigenomic datasets and computational integration for understanding the molecular basis of human diseases.
- The findings offer insights into the regulatory mechanisms underlying complex traits and diseases, exemplified by schizophrenia.
- The developed gLink scores serve as a powerful tool for prioritizing genetic variants and regulatory elements in disease-associated pathways.
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