Iva Sabolić1*, Radoslav Atanasoski2, Robert Šket3,4, Tine Tesovnik3,4, Barbara Slapnik3,4, Klemenitna Črepinšek3,4, Blaž Vrhovšek3,4, Tadej Avčin4,5, Mojca Zajc Avramovič5, Jernej Kovač3,4, Uršula Prosenc Zmrzljak2, Barbara Jenko Bizjan2,3,4
1 Bioinformatic department, Labena, Zagreb, Croatia
2 Bioinformatic department, BIA Separations CRO, Labena, Ljubljana, Slovenia
3 Clinical Institute of Special Laboratory diagnostics, University Children’s hospital, University Medical Centre Ljubljana, Slovenia
4 Faculty of Medicine, University of Ljubljana, Slovenia
5 Clinical Department of allergology, rheumatology, and clinical immunology, University Children’s hospital, University Medical Centre Ljubljana, Slovenia
iva.sabolic [at] labena.hr
Abstract
Multi systemic inflammatory syndrome in children (MIS-C) is a rare condition associated with SARS-CoV-2. To improve the understanding of underlying regulatory networks and potentially explain the mechanism behind MIS-C disease onset, we conducted a simultaneous profiling of transcriptome and epigenome from the same cell using the 10X Genomics Chromium Single Cell Multiome ATAC + Gene Expression protocol. Our study design consisted of 10 patients sampled at two time points: at the time of MIS-C disease flare before treatment was applied, and at the time of disease remission.
In order to facilitate an efficient way of processing the wealth of data generated by the employed protocol, we developed a bioinformatic workflow that enables users to systematically extract information crucial for understanding cellular function and regulation. The workflow is comprised of primary analysis performed using 10X Genomics Cell Ranger ARC software, and advanced analysis conducted utilizing a curated collection of various R packages. Through the proposed analyses, researchers can effectively identify and correct technical aberrations and batch effects in the data, unveil distinct cell types, detect differential gene expression between flare and remission states, reveal heterogeneity within cell populations, pinpoint enriched biological pathways and functions, and elucidate regulatory elements controlling gene activity.
The results of this project are expected to enlighten the underlying pathophysiology of MIS-C flare and support clinical decision on more targeted treatment. The identified disrupted networks during MIS-C flare could lead the way to establish an early diagnosis and improve long-term outcome, including prevention of myocardial and neuropsychological impairment.
Keywords: bioinformatic pipeline, multiome, COVID-19, MIS-C
Acknowledgement: Grants received form: ARIS: J3-50115, J3-3061, Interreg Italia-Slovenia: Concerto