A single workflow for multi-species blood transcriptomics

Area of Science:

• Genomics
• Immunology
• Pharmacology

Background:

• Blood transcriptomic analysis offers insights into physiological states and immune responses to vaccines.
• Current multi-species transcriptomic analysis faces technological challenges and lacks standardized workflows for inter-species comparison.

Purpose of the Study:

• To develop a single, comprehensive total RNA sequencing (RNA-Seq) workflow for generating reliable blood transcriptomic data from humans and preclinical animal models.
• To establish standardized criteria and thresholds for validating transcriptomic workflows across species.

Main Methods:

• A complete RNA-Seq workflow was applied to blood samples from humans, rabbits, non-human primates, and mice.
• Workflow performance was rigorously evaluated using multiple wet-lab and dry-lab metrics.
• An automated data analysis pipeline was developed to streamline dataset validation.

Main Results:

• The proposed workflow successfully generated reliable transcriptomic data across four species.
• Key validation criteria and thresholds were identified for assessing workflow performance.
• Automated analysis facilitated efficient validation of generated transcriptomic datasets.

Conclusions:

• An end-to-end workflow was developed to enhance standardization and inter-species comparison in blood transcriptomics.
• This standardized approach allows direct comparison of preclinical and clinical RNA sequencing data for vaccine and drug development.
• The workflow facilitates the identification of biomarkers for monitoring drug safety and vaccine efficacy.