Transcriptome-Wide Association Studies (TWAS): Methodologies, Applications, and Challenges

Curr Protoc. 2024 Feb;4(2):e981. doi: 10.1002/cpz1.981.

Abstract

Transcriptome-wide association study (TWAS) methodologies aim to identify genetic effects on phenotypes through the mediation of gene transcription. In TWAS, in silico models of gene expression are trained as functions of genetic variants and then applied to genome-wide association study (GWAS) data. This post-GWAS analysis identifies gene-trait associations with high interpretability, enabling follow-up functional genomics studies and the development of genetics-anchored resources. We provide an overview of commonly used TWAS approaches, their advantages and limitations, and some widely used applications. © 2024 Wiley Periodicals LLC.

Keywords: PrediXcan; complex traits; electronic health records; joint-tissue imputation (JTI); single-cell transcriptomics; transcriptome-wide association studies (TWAS).

MeSH terms

  • Computer Simulation
  • Genome-Wide Association Study* / methods
  • Phenotype
  • Quantitative Trait Loci
  • Transcriptome* / genetics