GSE172446
MicroRNA-seq of cell lines expressing pri-miR-9 paralog constructs II
MicroRNA (miRNA) biogenesis begins with Drosha cleavage, the fidelity of which is critical for downstream processing and mature miRNA target specificity. To understand how pri-miRNA sequence and structure influence Drosha cleavage, we studied the processing of pri-miR-9-1 sequence variants, which encode the same mature miRNA but differ in the surrounding scaffold. We show that, in addition to previously known features, the overall structural flexibility of pri-miRNA impacts Drosha cleavage fidelity. Internal loops and nearby G·U wobble pairs on the pri-miRNA stem induce the use of non-canonical cleavage sites by Drosha, resulting in 5' isomiR production. Here, we report the the miRNA-seq data of HEK293T cell lines transfected with different pri-miR-9 constructs. Overall design: Briefly, HEK293 cells were transfected with several wild-type and chimeric pri-miR-9 constructs. Transfections were performed using PolyJet™ DNA Transfection Reagent (SignaGen) according to the manufacturer's instructions. 48 hours after transfection total RNA was obtained using a chloroform-isopropanol extraction. 5µg of total RNA was ligated with RNA 3' adaptor using T4 RNA Ligase 2 - truncated (NEB), in the presence of RNase Inhibitor (NEB). RNA 5' adaptor was ligated using T4 RNA Ligase 1 - high concentration (NEB) and 10 mM ATP. Ligated small RNAs were reverse transcribed using SuperScript® IV Reverse Transcriptase (Thermo-Fisher). Small RNA library cDNA was amplified and indexed using Phusion® High-Fidelity DNA polymerase (NEB). Constructs were purified in a 6% (w/v) native acrylamide gel based on the expected product size and purified by ethanol precipitation. Libraries quality was assessed by using Qubit dsDNA HS Assay Kit (ThermoFisher) and Agilent High Sensitivity DNA kit (Agilent). Libraries were pulled together, denaturalized and prepared at a final concentration of 12pM and run on MiSeq Reagent Kit v3 (Illumina) according to the manufacturer specifications.  Fastq files were analyzed using a Python-based custom software, QuagmiR (https://cgc.sbgenomics.com/public/apps#nikola_tesic/quagmir/quagmir-1-0/) designed for the optimal mapping and analysis of isomiRs.