Project description:A diversity of RNA molecule 5' ends are generated during transcriptional and post-transcriptional processes. Different RNA ends can confer or represent different functional activities and thus the identification of RNA end usage dynamics contributes to the functional characterization of RNA molecules. Here we present a method that enables the accurate identification of RNA 5' ends from samples with low amounts of total RNAs, and thus allow characterization of RNA regulatory mechanisms in specific cell-types.
Project description:Single-cell RNA -seq can precisely resolve cellular states, but applying this method to low-input samples is challenging. Here, we present Seq-Well, a portable, low-cost platform for massively parallel single-cell RNA -seq. Barcoded mRNA capture beads and single cells are sealed in an array of subnanoliter wells using a semipermeable membrane, enabling efficient cell lysis and transcript capture. We characterize Seq-Well extensively and use it to profile thousands of primary human macrophages exposed to tuberculosis.
Project description:We developed a new method on sequencing low-input RNA. This method shows much low-bias with the advantage of semiconductor while competing with smart-seq2. In order to analyze the low-input RNA datasets sensitively, we also develop FANSe2splice with high experimental verification rate as the analysis tool in our method.