The goal of this grant application is to develop the first commercially available library preparation kit for profiling small RNAs from single cells using NGS methods. Single cell analyses of mRNA have allowed the identification of crucial differences between cells that were otherwise considered identical. These findings have shown that there is intrinsic ?noise? in the regulation of gene expression that plays an important role in determining cell fates. Unfortunately, there is currently a lack of information about the cell-to-cell variability of levels of ?small RNAs, including microRNAs. Indeed, there is no commercially available library preparation kit for small RNAs that can profile single cells. We propose to further develop our library preparation technology, RealSeq-AC, to be able to quantify small RNAs from single cells. RealSeq-AC uses a scheme involving a single combo-adapter and circularization that accurately quantifies over 75% of all miRNAs detected, compared to ~35% from the best competitor kit. To adapt this technology for single-cell sequencing we will test three separate strategies to dramatically reduce the presence of adapter-dimers in the library, as well as possible use of miRNA pre-amplification to reduce the number of PCR cycles needed. We will develop a protocol that performs all steps from cell lysis to final purification of amplified libraries in a single tube. This technology will allow the accurate quantification of small RNAs from single cells.
Health relatedness narrative Transcriptomic analysis of single cells has shown that there is a high cell-to-cell variability in gene expression among apparently identical cells in a population. However, a similar analysis is not currently possible for levels of small RNAs, which play key roles in regulating gene expression. The goal of this grant application is to develop the first commercially available library preparation kit for profiling microRNAs from single cells using modern high-throughput sequencing methods. Understanding how individual cells vary in their small RNA profiles is of central importance to understanding cancer progression and the evolution of malignant tumor cells.
