The Vacc-SeqQC project: Benchmarking RNA-Seq for clinical vaccine studies.

Area of Science:

• Immunology
• Genomics
• Biotechnology

Background:

• Systems vaccinology integrates omics data to study immune responses to vaccines.
• Standardizing RNA sequencing (RNA-seq) technical and analytical parameters is crucial for multi-site clinical trials.

Purpose of the Study:

• To benchmark RNA sequencing (RNA-seq) parameters in a multi-site vaccine clinical trial.
• To provide guidelines for optimizing RNA-seq data analysis in systems vaccinology.

Main Methods:

• Collected longitudinal peripheral blood mononuclear cell (PBMC) samples from subjects vaccinated with *Francisella tularensis*.
• Performed RNA-Seq at two sites, evaluating gene filtering, RNA controls, fold change, read length, and sequencing depth.
• Used synthetic mRNA spike-ins to establish read-count thresholds and modeled statistical power.

Main Results:

• Filtering lowly expressed genes improves fold-change accuracy and inter-site agreement.
• Read length had minimal impact; fold-change cutoffs reduced agreement.
• Sequencing depth minimally affected statistical power but reduced transcriptome representation.

Conclusions:

• Recommends filtering lowly expressed genes and using caution with fold-change cutoffs for RNA-seq in vaccine studies.
• Effect size is a major driver of statistical power for detecting differential gene expression.
• Provides essential benchmarks for future systems vaccinology research.