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Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
Published on: June 24, 2021
A detailed transcript-level probe annotation reveals alternative splicing based microarray platform differences
Joseph C Lee1, David Stiles, Jun Lu
1Genomics Core Laboratory, National Institute of Diabetes & Digestive & Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA. jclee8@gmail.com
BMC Genomics
|August 22, 2007
Summary
Alternative splicing significantly impacts gene expression measurements across different microarray platforms. Understanding probe-transcript relationships is key to improving data reproducibility and comparability in gene expression studies.
Area of Science:
- Genomics
- Molecular Biology
- Bioinformatics
Background:
- Microarrays are widely used for measuring gene expression levels.
- Improving microarray reproducibility across different manufacturers is crucial for data integration.
- Alternative splicing is a potential, yet unquantified, source of cross-platform expression variability.
Purpose of the Study:
- To investigate the influence of alternative splicing on gene expression measurement differences across microarray platforms.
- To develop a method for categorizing genes based on their susceptibility to alternative splicing variations.
- To enhance the comparability and reproducibility of microarray data.
Main Methods:
- Created a novel microarray probe/transcript annotation using AceView Aug05 release.
- Categorized genes based on their expression susceptibility to alternative splicing.
- Analyzed gene expression data from multiple platforms using the new categorization.
- Developed a probe-level visualization method for transcript specificity.
Main Results:
- Genes less susceptible to alternative splicing showed greater signal agreement across platforms.
- Genes highly susceptible to alternative splicing exhibited more significant cross-platform differences.
- A new visualization method effectively highlighted probe differences based on transcript specificity.
Conclusions:
- Detailed probe annotation at the transcriptome level is essential for accurate gene expression analysis.
- Alternative splicing within samples contributes to technical variability in cross-platform microarray data.
- Addressing alternative splicing is critical for enhancing the reliability of gene expression studies.
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