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Towards understanding of complex disease etiology using sequence Capture Hi-C (HiCap) and associated high throughput functional assays

Time: Fri 2020-12-18 10.00

Location: https://kth-se.zoom.us/j/68351334868?pwd=MDBORVRFbnBEOWd6N3RmeGJWNXJ3QT09, Solna, Sweden (English)

Subject area: Biotechnology

Doctoral student: Sailendra Pradhananga , Genteknologi, Science for Life Laboratory, SciLifeLab

Opponent: Professor Benedicte Alexandra Lie, Department of Medical Genetics, University of Oslo

Supervisor: Assoc. Prof. Pelin Sahlén, Science for Life Laboratory, SciLifeLab, Genteknologi; Professor Joakim Lundeberg, Science for Life Laboratory, SciLifeLab, Genteknologi

Abstract

A human genome laid out in a straight line would measure 2m from end to end, but in living cells it is folded into a compact structure contained in a nuclear space with a diameter of 2µm. This compact genome is hierarchically organized and spatiotemporally regulates distinct cellular gene expression mechanisms via promoter - enhancer chromatin loops. Additionally, large scale genomic studies have identified enhancer regions enriched with complex disease risk variants but uncovering their contribution to disease pathology remains challenging. 

This thesis reports the genome-wide generation and analysis of regulatory and functional regions in complex disease relevant cell types. High throughput sequencing methods including whole genome/exome sequencing, capture Hi-C (HiCap), RNA sequencing, and ChIP sequencing were used to create a snapshot of the functional and genomic landscape of cell types relevant to complex diseases.

 Paper I present a technical comparison of variant calls generated using two genotyping technologies: whole exome and whole genome sequencing (WGS and WES). This comparison unequivocally shows that variant quality from moderately sequenced WGS variant calls is stable and concordant with deeply sequenced WES calls. Papers II and III report the assignment of target genes to cardiovascular risk SNPs using capture Hi-C (HiCap) and other functional assays and identify both known and novel biological processes related to cardiovascular pathology. Finally, paper IV reports the use of whole genome sequencing and capture Hi-C data to identify rare variants in putative enhancer regions in a patient with a congenital heart defect and reveals a number of processes and genes relevant to the pathology. 

In conclusion, this thesis demonstrates that combining capture Hi-C with functional high throughput sequencing methods can improve our understanding of the etiology of complex diseases. We believe that the resulting mechanistic understanding of complex disease pathologies will enable effective intervention using drugs targeting regulatory processes.

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Last changed: Nov 25, 2020