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Updated: Jun 26, 2025
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Engineering Artificial Factors to Specifically Manipulate Alternative Splicing in Human Cells
Published on: April 26, 2017
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A multi-tissue, splicing-based joint transcriptome-wide association study identifies susceptibility genes for breast
Guimin Gao1, Julian McClellan1, Alvaro N Barbeira2
1Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA.
American Journal of Human Genetics
|May 11, 2024
Summary
This study introduces a multi-tissue joint splicing transcriptome-wide association study (splicing-TWAS) to identify breast cancer susceptibility genes. The novel approach significantly enhances gene discovery compared to traditional methods, highlighting the importance of splicing quantitative trait loci (sQTLs).
Area of Science:
- Genetics and Genomics
- Cancer Research
- Bioinformatics
Background:
- Splicing-based transcriptome-wide association studies (splicing-TWASs) are valuable for identifying breast cancer susceptibility genes.
- Existing splicing-TWASs are limited by focusing solely on breast tissue and individual excised introns, reducing their detection power.
- Genome-wide association studies (GWAS) have identified numerous genetic loci associated with breast cancer risk.
Purpose of the Study:
- To develop and apply a multi-tissue joint splicing-TWAS to increase the power of identifying breast cancer susceptibility genes.
- To integrate splicing signals from multiple excised introns across various relevant tissues.
- To compare the findings with traditional gene-expression-based TWAS and identify novel associations.
Main Methods:
- Conducted a multi-tissue joint splicing-TWAS integrating signals from 11 potentially relevant tissues.
- Utilized summary statistics from a large meta-analysis of GWAS data from 424,650 women of European ancestry.
- Trained splicing-level prediction models using GTEx (v.8) data and compared results with gene-expression TWAS.
Main Results:
- Identified 240 genes using the multi-tissue joint splicing-TWAS and nine additional genes via tissue-specific analysis.
- Discovered 88 novel genes in 62 loci not previously reported by TWAS, and 17 genes in seven loci distant from known GWAS variants.
- Found 110 genes identified exclusively by splicing-TWAS, indicating that splicing quantitative trait loci (sQTLs) have a stronger impact than expression quantitative trait loci (eQTLs) for many genes.
Conclusions:
- The multi-tissue joint splicing-TWAS significantly enhances the discovery of breast cancer susceptibility genes.
- Splicing variations, particularly intron excision events, play a crucial role in breast cancer risk for many genes.
- This approach provides a more comprehensive understanding of genetic contributions to breast cancer beyond traditional gene expression.
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