A large-scale comparative study of isoform expressions measured on four platforms

Area of Science:

• Genomics
• Molecular Biology
• Cancer Research

Background:

• Eukaryotic gene expression involves multiple isoforms with diverse functions.
• Accurate measurement of gene and isoform expression is crucial for understanding cancer.
• Previous comparisons exist for gene expression platforms, but not extensively for isoform quantification, especially for newer platforms like NanoString.

Purpose of the Study:

• To conduct a large-scale comparison of gene and isoform expression quantification platforms.
• To evaluate the performance of RNA-sequencing (RNA-seq), NanoString, array-based methods (Microarray, Exon-array), and RT-qPCR.
• To assess platform consistency in cancer cell line studies.

Main Methods:

• Comparative analysis of RNA-seq, NanoString, Exon-array, and Microarray data.
• NanoString experiments on 59 cancer cell lines measuring 478 isoforms in 155 genes.
• RT-qPCR experiments on a subset of isoforms in 13 cell lines.
• Integration of data from 46 cancer cell lines for comprehensive comparison.

Main Results:

• Agreement on isoform expression quantification is lower than for gene expression across platforms.
• NanoString and Exon-array showed inconsistency in isoform quantification.
• RT-qPCR demonstrated better consistency with RNA-seq and Exon-array than NanoString for isoforms.
• RNA-seq exhibited the highest overall consistency for gene expression quantification.

Conclusions:

• RNA-sequencing (RNA-seq) is the most consistent platform for gene expression measurement.
• Isoform quantification remains challenging, with varying consistency across different platforms.
• Specific RNA-seq quantification methods (Net-RSTQ, eXpress) showed better cross-platform agreement for isoforms.