A metrological foundation for absolute transcriptomics using International System of Units-anchored calibrators

Area of Science:

• Biotechnology
• Genomics
• Metrology

Background:

• RNA sequencing (RNA-seq) data exhibits inconsistencies due to systemic and sequence-dependent biases.
• These biases, including batch effects, limit analyses to relative fold-changes, hindering cross-experiment data comparability.
• Current quality control (QC) methods often fail to detect significant absolute quantification errors masked by fold-change metrics.

Purpose of the Study:

• To develop a method for converting RNA-seq reads into absolute quantities.
• To establish a metrological foundation for RNA-seq data, enabling universal benchmarks and interoperability.
• To empirically characterize and correct for systemic and sequence-dependent biases in RNA-seq.

Main Methods:

• Introduction of TranScale, utilizing 100 biomimetic standards with SI-traceable concentrations.
• Certification of standards by Isotope Dilution Mass Spectrometry (IDMS).
• Co-processing of standards within samples to generate library-specific calibration curves (R² > 0.97) for bias correction.

Main Results:

• TranScale successfully converts RNA-seq reads into absolute quantities, revealing hidden systemic biases.
• Median inter-laboratory coefficient of variation (CV) reduced from >85% to <25%.
• Biological signal-to-noise ratio increased from ~0 to >7.9, outperforming ComBat.

Conclusions:

• TranScale provides a robust method for accurate RNA-seq quantification by anchoring data to the International System of Units (SI).
• This approach enables reliable absolute comparisons of gene quantities across different experiments and laboratories.
• The study establishes a foundation for standardized, interoperable RNA-seq data analysis.