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Transcriptome Analysis of Single Cells
Published on: April 25, 2011
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Transcriptomic variation of pharmacogenes in multiple human tissues and lymphoblastoid cell lines
A Chhibber1, C E French2, S W Yee1
1Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA.
The Pharmacogenomics Journal
|February 10, 2016
Summary
This study used RNA-sequencing to analyze pharmacogenes across multiple human tissues, revealing significant variations in gene expression and splicing. These findings offer a valuable resource for drug discovery and personalized medicine.
Area of Science:
- Genomics
- Pharmacogenomics
- Molecular Biology
Background:
- Genetic variations in pharmacogenes influence drug response and toxicity.
- Previous studies were limited by microarray technology, single-tissue focus, or small sample sizes.
- Understanding pharmacogene expression across diverse tissues is crucial for drug development.
Purpose of the Study:
- To comprehensively analyze expression levels and alternative splicing of 389 Pharmacogenomics Research Network genes.
- To investigate these genes across five distinct human tissues: liver, kidney, heart, adipose, and lymphoblastoid cell lines.
- To establish a rich resource for pharmacogenomics research.
Main Methods:
- RNA-sequencing (RNA-seq) was employed to profile gene expression and splicing.
- Data was analyzed from 139 individuals across five tissue types.
- Results were compared with existing GTEx data for validation.
Main Results:
- Substantial inter-individual and inter-tissue variation in expression levels and splicing of pharmacogenes was observed.
- 183 novel splicing events in pharmacogenes were identified.
- RNA-seq data provided a consistent picture compared to GTEx data.
Conclusions:
- This study provides an in-depth resource on pharmacogene expression and splicing across multiple human tissues.
- The findings can inform biomarker discovery and the development of targeted therapeutics.
- The identified variations highlight the complexity of pharmacogene regulation and its clinical implications.
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