Abstract

Limitations and Challenges in MicroGenomics -- What we can Learn from Single-Cell and Exosome Expression Profiling

Michael Pfaffl, Professor, Technical University of Munich

So far quantitative real-time RT-PCR is the ‘Gold standard’ in molecular and clinical diagnostics, due to its high sensitivity, good reproducibility, and the wide dynamic quantification range. It is the most sensitive method for the quantification of mRNA/microRNA expression levels, in particular for extreme low abundant transcripts in tissue samples or liquid biopsies with limited RNA concentrations, e.g. single-cells, microvesicles or exosomes. Today the identification of novel and valid ‘biomarker signatures’ are in the focus. Therefore RNA Sequencing is increasingly used in experimental and clinical samples, to get the ‘holistic view’ on the mRNA and small RNA transcriptome. The high resolution down to single nucleotide changes afforded by small RNA Seq has revealed a new dimension of heterogeneity during microRNA biogenesis, resulting in multiple sequence and length isoforms, besides canonical microRNAs. These isomiRs have been shown to associate with RISC complex, impact the translational machinery and hence can be functional by regulating microRNA target genes. Similar to strand switching between -5p and -3p as the dominant microRNAs, recent studies have shown differential expression of isomiRs across tissues and developmental stages. Since microRNAs are transported at high concentration in exosomes we assessed holistic isomiR expression profiling in micro-vesicular isolates in two major biofluids, blood and milk. Goal was to elucidate a ‘novel group of biomarker signatures’ on the basis of isomiR expression profiles, and to investigate their potential in exosomal intercellular communication. While these approaches bear a tremendous potential for diagnostic applications, a comprehensive understanding of its underlying quantification strategies and data analysis is important. The interfacing and integration of different technologies for data collection and their analysis in various biological matrices are pivotal to novel biomarker identification and later the