Massively parallel approaches for characterizing noncoding functional variation in human evolution.
Curr Opin Genet Dev
; 88: 102256, 2024 Oct.
Article
en En
| MEDLINE
| ID: mdl-39217658
ABSTRACT
The genetic differences underlying unique phenotypes in humans compared to our closest primate relatives have long remained a mystery. Similarly, the genetic basis of adaptations between human groups during our expansion across the globe is poorly characterized. Uncovering the downstream phenotypic consequences of these genetic variants has been difficult, as a substantial portion lies in noncoding regions, such as cis-regulatory elements (CREs). Here, we review recent high-throughput approaches to measure the functions of CREs and the impact of variation within them. CRISPR screens can directly perturb CREs in the genome to understand downstream impacts on gene expression and phenotypes, while massively parallel reporter assays can decipher the regulatory impact of sequence variants. Machine learning has begun to be able to predict regulatory function from sequence alone, further scaling our ability to characterize genome function. Applying these tools across diverse phenotypes, model systems, and ancestries is beginning to revolutionize our understanding of noncoding variation underlying human evolution.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Genoma Humano
/
Evolución Molecular
Límite:
Animals
/
Humans
Idioma:
En
Revista:
Curr Opin Genet Dev
Asunto de la revista:
GENETICA
Año:
2024
Tipo del documento:
Article
Pais de publicación:
Reino Unido