RNA exome capture sequencing

Focus on RNA coding regions to maximize RNA-Seq discovery power

Introduction to RNA exome capture sequencing

Achieve cost-effective, accurate, and sensitive RNA exome analysis of even difficult samples without sacrificing gene fusion discovery power. Many RNA exome sequencing methods focus on a defined number of known transcripts or require expensive deep sequencing. RNA exome capture sequencing overcomes these challenges by combining RNA-Seq with exome enrichment.

This method captures only the coding regions of the transcriptome, allowing higher throughput and requiring lower sequencing depth than non-exome capture methods. Sequence-specific capture of the RNA exome does not rely on the presence of a poly-A tail. This makes RNA exome capture sequencing ideal for RNA-Seq with low-quality samples or limited starting material.

Advantages of RNA exome capture sequencing

Isolating transcriptome coding regions maximizes discovery power at a fraction of the read depth of total RNA sequencing.

Enables high sample throughput and cost efficiency

Focuses on high-value content for affordability

Achieves high-quality data from degraded samples, including formalin-fixed, paraffin-embedded (FFPE) tissues

Requires low sample input (as little as 10 ng total RNA) while maintaining high sensitivity

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Transcriptome analysis with NGS

Illumina Distinguished Scientist Gary P. Schroth, PhD demonstrates advances in RNA-Seq technology. Learn how these RNA library prep methods allow transcriptome analysis from challenging samples, like single cells or FFPE tissues.

RNA exome capture sequencing workflow

Illumina offers RNA exome capture workflows that simplify the entire process, from library preparation to data analysis and biological interpretation.

Featured products

Illumina RNA Prep with Enrichment

A fast, integrated workflow for producing enriched and indexed sequencing libraries from a broad range of sample types and RNA input quantities.

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RNA sequencing considerations

Each RNA-Seq experiment type—whether it’s gene expression profiling, targeted RNA expression, or small RNA analysis—has unique requirements for read length and depth. This article reviews experimental considerations and offers resources to help with study design.

Additional resources

RNA-Seq data analysis

User-friendly software tools simplify mRNA-Seq data analysis for biologists, regardless of bioinformatics experience.

Single-cell RNA sequencing

Study cellular differences often masked by bulk sampling and explore highly sensitive single-cell sequencing methods.

Speak to a specialist

Talk to an expert to learn more about RNA exome capture sequencing.