Toward transcriptomics as a primary tool for rare disease investigation.

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• RNA-sequencing (RNA-seq) has become a valuable tool for rare disease diagnosis and discovery over the last five years.
• It analyzes expressed RNA transcripts from accessible patient samples like blood, skin, or muscle.

Purpose of the Study:

• To summarize recent developments and challenges in applying RNA-seq to rare disease investigation.
• To highlight RNA-seq's capability in identifying aberrant gene expression and splicing for functional evidence.
• To discuss the potential of RNA-seq in profiling noncoding and structural variant effects.

Main Methods:

• Analysis of RNA-seq data to identify outlier gene expression and alternative splicing.
• Profiling of variant effects, including noncoding and structural variants.
• Assessment of canonical and deep intronic splicing events.

Main Results:

• RNA-seq can detect functional evidence for rare diseases by revealing aberrant gene expression and splicing.
• It offers insights into the impact of noncoding and structural variants on gene expression.
• RNA-seq can identify both canonical and deep intronic splicing alterations.

Conclusions:

• RNA-seq is a powerful approach for rare disease research, offering insights beyond coding variants.
• Developmental and cell type specificity of gene expression presents a key limitation.
• Future advances in computational methods and experimental techniques will expand the use of RNA-seq and multiomics in rare disease diagnosis and precision health.