Fluidigm today announced it has added microRNA (miRNA) Expression Profiling to its C 1TM Single-Cell Auto Prep System, providing the ability to unlock the secrets of miRNA in single cells. The new protocol equips researchers with the simplest, fastest and most flexible workflow available to co-amplify hundreds of miRNAs in an individual cell while processing up to 96 cells in parallel. “Fluidigm is committed to expanding our single-cell applications menu so researchers can explore cellular networks at the system level,” said Candia Brown, Director, Single-Cell Genomics, Fluidigm. “Our customers need an expanded toolkit to explore both gene expression and gene regulation in biological pathways. By adding single-cell miRNA expression to our application menu, we are providing simplicity, speed and scale to answer these complex questions.” This is the third single-cell genomic application enabled on the C 1 system. The C 1 system portfolio also includes single-cell messenger RNA (mRNA) sequencing for whole transcriptome analysis and targeted gene expression analysis. The C 1 system is the only instrument on the market today that can automatically and reliably isolate, verify and process live single cells. In combination with the BioMark TM HD System, the C 1 system can generate more than 9,200 data points per run. MicroRNAs are small noncoding RNA molecules that regulate mRNA expression. It is widely known that miRNAs regulate thousands of human protein-coding genes that are involved in all biological processes, such as differentiation, development, and cell cycle management. miRNAs have also been shown to be associated with many common diseases, such as cancer and cardiovascular disease. Using Fluidigm’s C 1 Single-Cell Auto Prep System with Fluidigm’s BioMark HD System, geneticists and clinical researchers have a complete solution that enables them to examine the differences in gene regulation among single cells. Investigators can now correlate mRNA and miRNA expression to predict biological pathway regulation. Researchers want to understand the role miRNAs play in regulating biological pathways but miRNA expression profiling has proven challenging for two reasons. First, a single miRNA can target multiple mRNA targets and therefore can regulate several biological systems. This biological phenomenon is a contributing factor in cell-to-cell variability and can make it difficult to interpret miRNA targets. Studying miRNA expression at the single-cell level allows researchers to measure the rapid and dynamic changes that occur in some cells within the same population. Second, traditional methods have significant workflow challenges. Microarrays are labor intensive, lack sensitivity, have inflexible content, and require days to process a sample. Although real-time PCR offers greater sensitivity than microarrays, non-microfluidic-based technologies can be too cost prohibitive and time consuming to run large scale studies.