Evaluation of the External RNA Controls Consortium (ERCC) reference material using a modified Latin square design

Area of Science:

• Molecular Biology
• Genomics
• Biotechnology

Background:

• Highly multiplexed assays are crucial for RNA transcript quantitation in biology and medicine.
• Accurate data from transcriptomic assays necessitates robust measurement assurance using appropriate controls.
• The External RNA Controls Consortium (ERCC) developed methods to prototype and evaluate multiple RNA controls.

Purpose of the Study:

• To develop and evaluate methods for prototyping and assessing multiple RNA controls for transcriptomic assays.
• To utilize a modified Latin square design for broad dynamic range assessment of RNA controls.
• To assess the suitability of ERCC pools as surrogates for endogenous transcripts.

Main Methods:

• A modified Latin square design was employed to test four complex pools of ERCC RNA transcripts spiked into a human liver total RNA background.
• ERCC pools were analyzed across four microarray platforms (Agilent 1- and 2-color, Illumina bead, NIAID spotted) and two next-generation sequencing platforms (Life Technologies 5500xl, Illumina HiSeq 2500).
• Individual ERCC controls were assessed for reproducible performance, signal response, and linear behavior across platforms.

Main Results:

• Most ERCC controls demonstrated linear signal response to concentration within the dynamic range of the assays.
• Performance issues were attributed to detection limits, platform-specific probe interactions, or potential mixing errors.
• ERCC pools effectively established assay dynamic range and delineated usable regions for accurate differential expression measurements.

Conclusions:

• The modified Latin square design offers an economical and efficient method for evaluating multiple external RNA controls within a single experiment.
• This composite testing scheme assesses linear performance, signal response, and ratio detection.
• Well-designed pools of spiked-in RNA controls provide essential measurement assurance for endogenous gene expression studies.