RNAome sequencing delineates the complete RNA landscape

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Standard RNA profiling methods often use enrichment, excluding certain RNA types like small and large RNAs in a single analysis.
• This limitation prevents comprehensive analysis of the entire transcriptome and the relationships between different RNA classes.

Purpose of the Study:

• To introduce and detail RNAome sequencing, a novel strand-specific method for simultaneous expression profiling of small and large RNAs.
• To provide the R code for the Total RNA Analysis Pipeline (TRAP) for analyzing RNAome sequencing data.

Main Methods:

• RNAome sequencing involves ribosomal RNA-depleted total RNA, enabling strand-specific detection of both small and large RNAs in a single sequencing run.
• The Total RNA Analysis Pipeline (TRAP) is an R-based algorithm developed for analyzing RNAome sequencing datasets.

Main Results:

• RNAome sequencing quantitatively preserves all RNA classes, allowing for direct comparisons between them.
• The method facilitates the study of relationships between different RNA classes, offering a more holistic view of gene expression.

Conclusions:

• RNAome sequencing offers a comprehensive approach to RNA expression profiling, overcoming limitations of traditional methods.
• The described methodology and analysis pipeline enable deeper insights into the complex landscape of RNA expression and regulation.