A real-world multi-center RNA-seq benchmarking study using the Quartet and MAQC reference materials.

Area of Science:

• Genomics
• Molecular Biology
• Clinical Diagnostics

Background:

• Translating RNA-sequencing (RNA-seq) into clinical diagnostics necessitates reliable and consistent detection of subtle differential gene expression.
• Variability across laboratories poses a significant challenge for clinical RNA-seq applications, particularly for distinguishing disease subtypes or stages.

Purpose of the Study:

• To benchmark RNA-seq performance across multiple laboratories using reference samples.
• To systematically assess real-world RNA-seq performance and identify factors influencing gene expression detection.
• To provide recommendations for improving RNA-seq reliability in clinical settings.

Main Methods:

• Conducted a multi-laboratory RNA-seq benchmarking study involving 45 laboratories.
• Utilized Quartet and MAQC reference samples spiked with External RNA Controls Consortium (ERCC) controls.
• Investigated the impact of 26 experimental processes and 140 bioinformatics pipelines on gene expression analysis.

Main Results:

• Observed significant inter-laboratory variations in detecting subtle differential gene expressions.
• Identified mRNA enrichment methods, strandedness, and specific bioinformatics steps as primary sources of variation.
• Demonstrated the substantial influence of experimental execution on RNA-seq data consistency.

Conclusions:

• Standardization of experimental protocols and bioinformatics pipelines is essential for clinical RNA-seq.
• Best practice recommendations are provided for experimental design, gene filtering, annotation, and analysis.
• This study establishes a foundation for developing and quality controlling RNA-seq-based clinical diagnostics.