Identifying enhancer properties associated with genetic risk for complex traits using regulome-wide association studies.
PLoS Comput Biol
; 18(9): e1010430, 2022 09.
Article
em En
| MEDLINE
| ID: mdl-36070311
ABSTRACT
Genetic risk for complex traits is strongly enriched in non-coding genomic regions involved in gene regulation, especially enhancers. However, we lack adequate tools to connect the characteristics of these disruptions to genetic risk. Here, we propose RWAS (Regulome Wide Association Study), a new application of the MAGMA software package to identify the characteristics of enhancers that contribute to genetic risk for disease. RWAS involves three steps:
(i) assign genotyped SNPs to cell type- or tissue-specific regulatory features (e.g., enhancers); (ii) test associations of each regulatory feature with a trait of interest for which genome-wide association study (GWAS) summary statistics are available; (iii) perform enhancer-set enrichment analyses to identify quantitative or categorical features of regulatory elements that are associated with the trait. These steps are implemented as a novel application of MAGMA, a tool originally developed for gene-based GWAS analyses. Applying RWAS to interrogate genetic risk for schizophrenia, we discovered a class of risk-associated AT-rich enhancers that are active in the developing brain and harbor binding sites for multiple transcription factors with neurodevelopmental functions. RWAS utilizes open-source software, and we provide a comprehensive collection of annotations for tissue-specific enhancer locations and features, including their evolutionary conservation, AT content, and co-localization with binding sites for hundreds of TFs. RWAS will enable researchers to characterize properties of regulatory elements associated with any trait of interest for which GWAS summary statistics are available.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Herança Multifatorial
/
Estudo de Associação Genômica Ampla
Tipo de estudo:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
PLoS Comput Biol
Assunto da revista:
BIOLOGIA
/
INFORMATICA MEDICA
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Estados Unidos