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

Area of Science:

• Genetics
• Bioinformatics
• Genomics

Background:

• Transcriptome-wide association studies (TWAS) bridge the gap between genetic variants and phenotypic traits by examining gene expression.
• Understanding gene-trait associations is crucial for dissecting complex diseases and guiding functional genomics research.

Purpose of the Study:

• To provide a comprehensive overview of Transcriptome-wide association study (TWAS) methodologies.
• To discuss the advantages, limitations, and applications of various TWAS approaches.
• To highlight the utility of TWAS in post-Genome-wide association study (GWAS) analysis.

Main Methods:

• TWAS utilizes in silico models to predict gene expression based on genetic variants.
• These predictive models are then applied to Genome-wide association study (GWAS) data.
• The approach facilitates the identification of gene-trait associations with high interpretability.

Main Results:

• TWAS enables the identification of genes that mediate the relationship between genetic variation and observed phenotypes.
• The methodology offers interpretable gene-trait associations, facilitating downstream functional studies.
• TWAS supports the development of genetics-anchored resources for biological research.

Conclusions:

• TWAS is a powerful post-GWAS analytical framework for identifying genetically influenced traits.
• The approach enhances the interpretability of genetic association findings and supports functional genomics.
• TWAS methodologies are valuable tools for advancing our understanding of genetic contributions to human health and disease.