Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Short-read RNA sequencing (RNA-seq) has become the predominant method for transcriptome analysis, largely replacing microarrays.
• Despite its widespread adoption, RNA-seq analysis often relies on models of the known transcriptome, and its limitations are becoming apparent.
• Microarray technology has matured in both design and analysis strategies, prompting a re-evaluation of its utility.

Purpose of the Study:

• To provide an equitable comparison between modern microarray technology and RNA sequencing for transcriptome analysis.
• To highlight the advantages that modern arrays offer over RNA-seq, particularly in specific applications.
• To discuss the implications of these findings for current transcriptomic atlases and future research.

Main Methods:

• Comparative analysis of data generated by modern high-density arrays and RNA sequencing.
• Evaluation of quantification accuracy for constitutively expressed genes and lower expressed genes across tissue replicates.
• Assessment of the reliability of both technologies for studying long noncoding RNAs (lncRNAs).

Main Results:

• Array protocols provide more accurate quantification of constitutively expressed protein-coding genes across tissue replicates compared to RNA-seq.
• Arrays are more reliable for studying genes with lower expression levels.
• Arrays demonstrate that long noncoding RNAs (lncRNAs) are expressed at levels comparable to protein-coding genes, contrary to some RNA-seq interpretations.
• RNA-seq exhibits heterogeneous coverage of constitutively expressed genes, potentially undermining the validity and reproducibility of pathway analyses.

Conclusions:

• Modern arrays possess distinct advantages over RNA-seq for specific transcriptomic analyses, including accurate quantification of constitutive and low-expressed genes.
• The limitations of RNA-seq, such as heterogeneous gene coverage, necessitate a reappreciation of bulk transcriptomic methods like microarrays.
• Wider adoption of modern array data is crucial for revising existing RNA reference atlases and improving the study of lncRNAs.