Spliced synthetic genes as internal controls in RNA sequencing experiments

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• RNA sequencing (RNA-seq) is vital for transcriptome analysis, but faces challenges due to transcriptome complexity, dynamic gene expression ranges, and technical biases.
• Accurate gene expression quantification and isoform assembly are crucial for understanding cellular function and disease.

Purpose of the Study:

• To develop a robust method for normalizing RNA-seq data and improving the accuracy of transcript assembly and quantification.
• To create artificial RNA standards that can serve as internal controls for RNA-seq experiments.
• To develop RNA standards for detecting fusion genes relevant to cancer diagnosis.

Main Methods:

• Development of 'sequins' (sequencing spike-ins): artificial, full-length spliced mRNA isoforms with no genomic homology.
• In silico chromosome integration of sequins for alignment to gene loci.
• Application of sequins across various concentrations to emulate alternative splicing and differential gene expression.
• Utilizing sequins for normalization and to assess sample-specific biases in human RNA samples.
• Designing fusion gene sequins for cancer-related rearrangement detection.

Main Results:

• Sequins provide scaling factors for accurate normalization between RNA-seq samples.
• Demonstrated the utility of sequins in measuring sample-specific biases.
• Established the limits of reliable transcript assembly and quantification using sequins.
• Developed fusion gene sequins to aid in cancer diagnosis.

Conclusions:

• RNA sequins offer a reliable qualitative and quantitative reference for navigating human transcriptome complexity.
• Sequins enhance the accuracy and reliability of RNA-seq analyses.
• This technology has significant implications for basic research and clinical diagnostics, particularly in oncology.