Past dissertations |

Past dissertations

Past dissertations

Bram Burger at University of Bergen
Dissertation: June 10tht, 2021 10:15, Zoom
PhD thesis title: Statistical considerations for the design and interpretation of proteomics experiments
Ivana Mikocziova at University of Oslo
Trial lecture: May 21st, 2021 10:15, Zoom
Topic for trial lecture: Immune responses to acute viral infections
Dissertation:  May 21st, 2021 12:15
Title of thesis: “Characterisation of germline immunoglobulin variants from naïve B cell receptor repertoires


Summary of thesis:

Antibodies and B cell receptors are crucial components of the immune system.  However, immunoglobulin genes, which encode both antibodies and B cell receptors, are not well explored. This is partly due to high similarities among immunoglobulin genes, large structural variation of the immunoglobulin loci as well as the presence of somatic hypermutation in antigen-experienced B cells.

In this thesis, we used a dataset composed of naïve immunoglobulin repertoires from a cohort of 100 Norwegians. Since naïve B cells have not undergone somatic hypermutation, we were able to infer germline alleles from this dataset. We optimised existing software tools for germline inference and discovered a great amount of structural variation and a large number of previously unreported immunoglobulin V alleles in both heavy and light chain genes. On top of that, we developed an approach for filtering potential sequencing and PCR artefacts.

We also analysed the leader sequences and 5’ untranslated regions (5’UTR) of immunoglobulin genes and discovered even more polymorphisms in these regions. Surprisingly, we found several sequences with identical coding V region that had different 5’ UTRs and/or leader sequences. Our analysis also revealed alternatively spliced transcripts of genes with low usage levels, which raises questions about mechanisms that regulate the expression of immunoglobulin genes.

The results of our work provide a valuable contribution to the efforts to characterise germline immunoglobulin gene variants. This will enable further research into the functional effect of immunoglobulin polymorphisms as well as exploration of possible influence of coding and non-coding immunoglobulin polymorphisms on health and disease.

Ying Yao at University of Oslo
Trial lecture: March 24th 2021 at 09.15
Topic for trial lecture:
The role of gut microbiota in health and disease
Dissertation:  March 24th 2021 at 11.15
Title of thesis:“High-throughput sequencing of gluten-specific T cells in celiac disease

Summary of thesis:

Celiac disease is a chronic inflammatory disorder resulting from mis-appropriate immune response toward ingested gluten proteins. Gluten-specific CD4+ T cells, as the key drivers for the pathogenesis can be identified by staining with HLA-DQ:gluten tetramers.

In this project, we conducted single cell transcriptome sequencing on CD4+ T cells sampled from peripheral blood of untreated CD patients. The tetramer-specific T cells showed transcriptomic profiles consistent with activated effector memory T cells that share features with Th1 and follicular helper T cells. Compared to non-specific cells, gluten-specific T cells showed differential expression of several genes involved in metabolic processes, including fatty acid metabolism and redox potentials. In addition, we utilized the unique expression of immune receptor of each T and B cell to quantify the impact of index switching on single cell RNA-seq experiments.

We also demonstrated that the state of celiac disease could be inferred by unbiased direct TCR sequencing on lamina propria T cells, which is promising for the ultimate goal of inferring celiac disease state based on TCR sequencing of circulating T cells.


Bjørn Bredesen at University of Bergen

Trial lecture November 2nd at 10.15
Topic for trial lecture: “Spatial transcriptomics”
External link to the trial lecture is found here.


Dissertation: November 20th at 10.15-12.00

Title of thesis: “Modelling the structure, function and evolution of Polycomb/Trithorax Response Elements”

External link to dissertation here.


Sonja Lagström at University of Oslo

Trial lecture November 6th at 08.30
Topic for trial lecture:
“Tracking the COVID19 pandemics using next generation sequencing (NGS)  – sequence variants in the Nordic Countries.” External link to trial lecture here.
Dissertation: November 6th at 10.30
Title of thesis:“Characterisation of human papillomavirus genomic variation and chromosomal integration in cervical samples”

Persistent infection with a high-risk human papillomavirus (HPV) type is necessary for cervical cancer development, causing nearly 5% of all cancers worldwide. Nevertheless, only a small fraction of HPV infections progress to cancer, indicating that additional molecular factors contribute to the development of cervical cancer.

The thesis aimed to characterise and explore mutations in the HPV genome and viral integrations into the human genome contributing to HPV-induced carcinogenesis. This can reveal new insight into cervical cancer development.

A unique next-generation sequencing protocol, TaME-seq, was developed for analysis of HPV genomic variation and integration. The results show that the overall intra-host HPV genomic variability is higher than previously assumed, with a high number of HPV genome variants found in all samples from early infections to cancer. A noticeable part of the mutations in HPV16, which is the most carcinogenic HPV type, was associated with the APOBEC3-enzyme that is suggested to be involved in viral clearance. The findings revealed integration sites that located both in previously reported and novel genomic sites. A large number of integrations was observed in or close to human cancer-related genes, which could be an indication of a more aggressive infection.

The TaME-seq method could potentially be a valuable method for assessing the risk of developing cervical cancer. An additional HPV screening test would enable more personalised follow-up, improving detection of lesions with higher risk of progression and reducing unnecessary follow-up and treatment of women with minimal risk of developing high-grade lesions or cancer.


Yaxin Xue at University of Bergen

Trial lecture October 26th at 13.00
Topic for trial lecture: “Computational challenges and approaches linked to use of long-read sequencing in metagenomics”.
Dissertation: November 5th at 10:15-13:00
Title of thesis: “Development and application of computational methods for NGS-based microbiome research”
Xiaokang Zhang at University of Bergen
Trial lecture October 19th at 13.15-14.00
Topic for trial lecture: “Machine learning approaches in personalized medicine”.
External link to the trial lecture is found here.
Dissertation: October 30th at 10:15-13:00
Title of thesis: Biomarker Discovery Using Statistical and Machine Learning Approaches on Gene Expression Data
Cod is an important fish for Norway and is used as a model organism to learn about how environmental toxicants affect biological systems. In the dCod1.0 project, we have studied how fish react to toxicants at molecular level. Using sequencing technology, we have measured the expression of several thousand genes in liver samples from cods exposed in the laboratory or from contaminated environments. An interesting question is which genes are activated when the fish are exposed to environmental toxicants.
One technology for measuring gene expression is RNA sequencing. The data that is produced must go through a series of steps to obtain gene expression. There are many tools to automate this process. However, many of them are made for special applications and for data from model organisms such as humans or mice. Therefore, we have developed a workflow called RASflow that can be easily used without special programming skills and with different research interests.
When the gene expression profiles are clear, both traditional statistical hypothesis testing and machine learning methods can be applied to find out the individual genes or gene sets that show a reaction to the toxicants. The performance of the individual method is very dependent on the data. In addition, the methods are often unstable when the number of samples is low and the number of genes is high. Motivated by this, we developed a framework that makes it possible to combine different methods to identify relevant genes and that shows stable behavior across all the data sets we have analyzed.
External link to defense here.

Joseph Diab at University of Tromsø – The Arctic University

Time: October 9th 10:15-16:00

Thesis title: “The Metabolome and Lipidome of Ulcerative Colitis”

Summary of the thesis:

Inflammatory bowel disease (IBD) is a chronic, relapsing inflammatory disorder in the gastrointestinal tract affecting up to 0.5% of the population of the Western world. The two major forms of IBD, Ulcerative Colitis (UC) and Crohn’s Disease (CD), are characterized by a dysregulated immune response triggered by several genetic, microbial and environmental factors.

We preformed mass spectrometry-based metabolomic and lipidomic analysis on colon biopsies from UC patients to unravel the disease pathobiology and to identify markers for the disease outcome. We found that the alteration in lipid mediators correlates with the severity of UC. Moreover, we report potential prognostic and diagnostic markers for UC, such as very long chain ceramids and lipid mediators. Likewise, tryptophan metabolism is a key aspect of the impaired metabolism in active UC.

This work demonstrates the importance of metabolomics in IBD to identify key drivers of pathogenesis which prerequisite personalized treatment.

The trail lecture starts at 10.15, the defense starts at 12.15

Trial lecture:
Title:  “Proteomics in Inflammatory Bowel Disease – Integrated multi-omics to facilitate personalized medicine in IBD”

Link to the trial lecture and defense at UiT.


Zhi Zhao at University of Oslo
Time: October 9th 10:15-16:00
Thesis title: “Multivariate structured penalized and Bayesian regressions for pharmacogenomic screens”
Summary of the thesis:

Pharmacogenomic screens for personalized cancer therapy are the focused biomedical application in this thesis. Due to the complex relationships between targeted cancer drugs and high-dimensional genomic predictors, we have developed penalized likelihood methods and Bayesian hierarchical models to capture the complex structures in the pharmacogenomic data and to predict drug sensitivity.

The first part of the thesis proposed to address the correlations between drug sensitivity measures for multiple cancer drugs and the heterogeneity of multiple sources of genomic data in multivariate penalized likelihood methods with structured penalities. The proposed methods can improve the prediction performance of drug sensitivity. The second part of the thesis exploited Bayesian priors for the relationships between multiple drugs and relationships between drug sensitivity and the targeted pathways or genes of cancer drugs. Large pharmocogenomic screens may also include samples from multiple cancer tissue types. We employed random effects to address the sample heterogeneity in the proposed Bayesian model. The results have shown good structure recovery in the complex data and good prediction of responses by the new Bayesian models.

We congratulate NORBIS PhD member Zhi Zhao on his upcoming dissertation! Tomorrow (Friday October 9th) at 12.15 he will defend his thesis “Multivariate structured penalized and Bayesian regressions for pharmacogenomic screens” at the University of Oslo. The trial lecture starts at 10.15. Both trial lecture and thesis defense will be streamed online and all who like can join in. Thesis abstract and (external) links to trial lecture and defense are found here: