1. Functional characterization of human genomic variation linked to polygenic diseases.
- Author
-
Fabo, Tania and Khavari, Paul
- Subjects
- *
GENOME editing , *GENETIC variation , *GENOME-wide association studies , *GENE expression , *MONOGENIC & polygenic inheritance (Genetics) , *HIGH throughput screening (Drug development) , *LINCRNA - Abstract
Genome-wide association studies (GWAS) have localized variants to diverse classes of genomic elements, including coding sequences, introns, promoters, enhancers, 5′ and 3′-untranslated regions (UTRs), long noncoding RNA (lncRNA), and miRNAs. Annotation of diverse GWAS-identified loci from precise variant to biologic function to pathogenic impact requires understanding how different classes of genomic elements are affected by genetic variants and appropriately adapting a wide range of genomic tools to uncover variant function and effect. A variety of high-throughput screening methods and informatics tools have been adapted to capture the specific ways in which different variant classes affect gene expression and/or function. Precision gene-editing approaches that produce isogenic cells and tissues that differ only at the variant of interest comprise the gold standard for characterizing the effects of a GWAS variant in its native context. The burden of human disease lies predominantly in polygenic diseases. Since the early 2000s, genome-wide association studies (GWAS) have identified genetic variants and loci associated with complex traits. These have ranged from variants in coding sequences to mutations in regulatory regions, such as promoters and enhancers, as well as mutations affecting mediators of mRNA stability and other downstream regulators, such as 5′ and 3′-untranslated regions (UTRs), long noncoding RNA (lncRNA), and miRNA. Recent research advances in genetics have utilized a combination of computational techniques, high-throughput in vitro and in vivo screening modalities, and precise genome editing to impute the function of diverse classes of genetic variants identified through GWAS. In this review, we highlight the vastness of genomic variants associated with polygenic disease risk and address recent advances in how genetic tools can be used to functionally characterize them. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF