Toward reliable biomarker signatures in the age of liquid biopsies - how to standardize the small RNA-Seq workflow. Issue 13 (17th June 2016)

• Record Type: Journal Article
• Authors: Buschmann, Dominik; Haberberger, Anna; Kirchner, Benedikt; Spornraft, Melanie; Riedmaier, Irmgard; Schelling, Gustav; Pfaffl, Michael W.
• Is Part Of: Nucleic acids research. Volume 44:Issue 13(2016)
• Page Start: 5995
• Page End: 6018
• Publication Date: 2016-06-17
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkw545
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: Small RNA-Seq has emerged as a powerful tool in transcriptomics, gene expression profiling and biomarker discovery. Sequencing cell-free nucleic acids, particularly microRNA (miRNA), from liquid biopsies additionally provides exciting possibilities for molecular diagnostics, and might help establish disease-specific biomarker signatures. The complexity of the small RNA-Seq workflow, however, bears challenges and biases that researchers need to be aware of in order to generate high-quality data. Rigorous standardization and extensive validation are required to guarantee reliability, reproducibility and comparability of research findings. Hypotheses based on flawed experimental conditions can be inconsistent and even misleading. Comparable to the well-established MIQE guidelines for qPCR experiments, this work aims at establishing guidelines for experimental design and pre-analytical sample processing, standardization of library preparation and sequencing reactions, as well as facilitating data analysis. We highlight bottlenecks in small RNA-Seq experiments, point out the importance of stringent quality control and validation, and provide a primer for differential expression analysis and biomarker discovery. Following our recommendations will encourage better sequencing practice, increase experimental transparency and lead to more reproducible small RNA-Seq results. This will ultimately enhance the validity of biomarker signatures, and allow reliable and robust clinical predictions.