Transcriptome analysis of basal and stimulated von Willebrand factor release from endothelial colony forming cells derived from Type 1 von Willebrand disease patients

Published: 20 September 2022| Version 1 | DOI: 10.17632/jc2vnrsccw.1
Charles Hindmarch, Neil Renwick, Kathrin Tyryshkin, Matteo Zago, Julie Grabell, Lisa Thibeault, Patricia Lima, Mackenzie Bowman, Robert Kloosterman, Paul James


All participants provided informed consent and this study was approved by the Queen’s University Health Sciences Ethics Review Board. Type 1 VWD patients ≥18 years of age were recruited through Inherited Bleeding Disorders Clinic of Southeastern Ontario in Kingston, Canada. Inclusion criteria for Type 1 VWD patients included a VWF antigen (VWF:Ag) and/or VWF activity (VWF:GPIbM or VWF:RCo) levels between 0.05 and 0.50 IU/mL, a VWF:GPIbM/VWF:Ag ratio >0.6, and normal VWF multimers. Illumina compatible libraries were constructed using the QuantSeq 3’ mRNA-Seq Library Prep Kit (Lexogen, Austria) using 350ng of total RNA as input. The library size and concentration were determined using the Labchip GX (Perkin Elmer) and Qubit (Thermo Fisher) platforms, respectively. Independently indexed and purified libraries were combined at an equimolar concentration and the library pool was subject to bead purification, denaturation, and dilution. This pooled library was loaded onto a MidOutput v2 reagent cartridge at a concentration of 2.2pM and subject to 75 cycles of single-ended sequencing to a depth exceeding 5 million clusters per sample on a NextSeq550 sequencer (Illumina, California). Raw data in the form of .fastq files were transferred to the Queen’s Center for Advanced Computing, Frontenac cluster, and assessed for quality and trimmed using an established pipeline. Briefly, sequencing reads were aligned to the Ensembl_GRCh38 human genome using STAR aligner and counts were generated using HTSEQ-COUNT. miRNA profiling was conducted according to an established barcoded small RNA sequencing platform. Briefly, 100ng of purified RNA was spiked with a set of synthetic calibration markers prior to ligation to a sample-specific 3’ oligonucleotide adaption specific for small RNA species. Following sequencing, .fastq files were uploaded through a web-accessible RNA sequencing pipeline ( hosted in the Tuschl Laboratory at The Rockefeller University. To report miRNA abundance independent of sequencing depth, read counts were normalized against total sequence reads annotated as miRNAs. mRNA sequencing raw counts: File Name New name MZ01N_pos_S12.counts.txt 1C pos MZ01P_neg_S1.counts.txt 1P neg MZ01P_pos_S2.counts.txt 1P pos MZ02P_neg_S3.counts.txt 2P neg MZ02P_pos_S4.counts.txt 2P pos MZ04N_neg_S13.counts.txt 2C neg MZ04N_pos_S14.counts.txt 2C pos MZ05P_neg_S5.counts.txt 3P neg MZ05P_pos_S6.counts.txt 3P pos MZ06N_neg_S15.counts.txt 3C neg MZ06N_pos_S16.counts.txt 3C pos MZ06P_neg_S7.counts.txt 4P neg MZ06P_pos_S8.counts.txt 4P pos MZ08P_neg_S9.counts.txt 5P neg MZ08P_pos_S10.counts.txt 5P pos MZ10N_neg_S17.counts.txt 4C neg MZ10N_pos_S18.counts.txt 4C pos P053_neg_S19.counts.txt 6P neg P053_pos_S20.counts.txt 6P pos V447_neg_S21.counts.txt 7P neg V447_pos_S22.counts.txt 7P pos V449_neg_S23.counts.txt 8P neg V449_pos_S24.counts.txt 8P pos miRNA data miRNA_processed_data.xlsx



Queen's University


RNA Sequencing, Bleeding Disorder, Transcriptomics, Von Willebrand Factor