| 1. |
|
|
| 2. |
- Fernandez Navarro, Jose, 1982-
(författare)
-
Computational methods for analysis and visualization of spatially resolved transcriptomes
- 2019
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Characterizing the expression level of genes (transcriptome) in cells and tis- sues is essential for understanding the biological processes of multicellular or- ganisms. RNA sequencing (RNA-seq) has gained traction in the last decade as a powerful tool that provides an accurate quantitative representation of the transcriptome in tissues. RNA-seq methods are, however, limited by the fact that they provide an average representation of the transcriptome across the tissue. Single cell RNA sequencing (scRNA-seq) provides quantitative gene expression levels of individual cells. This enables the molecular characteri- zation of cell types in health, disease and developmental tissues. However, scRNA-seq lacks the spatial context needed to understand how cells interact and their microenvironment. Current methods that provide spatially resolved gene expression levels are limited by a low throughput and the fact that the target genes must be known in advance.Spatial Transcriptomics (ST) is a novel method that combines high-resolution imaging with high-throughput sequencing. ST provides spatially resolved gene expression levels in tissue sections. The first part of the work presented in this thesis (Papers I, II, III and IV) revolves around the ST method and the development of the computational tools required to process, analyse and visualize ST data.Furthermore, the ST method was utilized to construct a three-dimensional (3D) molecular atlas of the adult mouse brain using 75 consecutive coronal sections (Paper V). We show that the molecular clusters obtained by unsu- pervised clustering of the atlas highly correlates with the Allen Brain Atlas. The molecular clusters provide new insights in the organization of regions like the hippocampus or the amygdala. We show that the molecular atlas can be used to spatially map single cells (scRNA-seq) onto the clusters and that only a handful of genes is required to define the brain regions at a molecular level.Finally, the hippocampus and the olfactory bulb of transgenic mice mim- icking the Alzheimer’s disease (AD) were spatially characterized using the ST method (Paper VI). Dierential expression analysis revealed genes central in areas highly cited as important in AD including lipid metabolism, cellular bioenergetics, mitochondrial function, stress response and neurotransmission.
|
|
| 3. |
- Friedrich, Stefanie, 1973-
(författare)
-
Computational Analysis of Tumour Heterogeneity
- 2020
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Every tumour is unique and characterised by its genetic, epigenetic, phenotypic, and morphological signature. The diversity observed between and within tumours, and over time, is termed tumour heterogeneity. An increased heterogeneity within a tumour correlates with cancer progression, higher resistance rates, and poorer outcome. Heterogeneity between tumours explains aspects of a treatment’s ineffectiveness. Depending on a tumour’s unique signature, common processes like unhindered cell proliferation, invasiveness, or treatment resistance characterise tumour progression. Studying tumour heterogeneity aims to understand cancer causes and evolution, and eventually to improve cancer treatment outcomes. This thesis presents application and development of computational methods to study tumour heterogeneity. Papers I and II concern the in-depth investigation of clinical tissue samples taken from prostate cancer patients. The findings range from spatial expansion of gene expression patterns based on high-resolution data to a gene expression signature of non-responding cancer cells revealed by spatio-temporal analysis. These cells underwent a transition from an epithelial to a mesenchymal phenotype pre-treatment. Papers III and IV present tools to detect fusion transcripts and copy number variations, respectively. Both tools, applicable to high-resolution data, enable the in-depth study of mutations, which are the driving force behind tumour heterogeneity.The results in this thesis demonstrate how the beneficial combination of high-resolution data and computational methods leads to novel insights of tumour heterogeneity.
|
|
| 4. |
- Georgakopoulos-Soares, Ilias, et al.
(författare)
-
Alternative splicing modulation by G-quadruplexes
- 2022
-
Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 13:1
-
Tidskriftsartikel (refereegranskat)abstract
- Alternative splicing is central to metazoan gene regulation, but the regulatory mechanisms are incompletely understood. Here, we show that G-quadruplex (G4) motifs are enriched ~3-fold near splice junctions. The importance of G4s in RNA is emphasised by a higher enrichment for the non-template strand. RNA-seq data from mouse and human neurons reveals an enrichment of G4s at exons that were skipped following depolarisation induced by potassium chloride. We validate the formation of stable RNA G4s for three candidate splice sites by circular dichroism spectroscopy, UV-melting and fluorescence measurements. Moreover, we find that sQTLs are enriched at G4s, and a minigene experiment provides further support for their role in promoting exon inclusion. Analysis of >1,800 high-throughput experiments reveals multiple RNA binding proteins associated with G4s. Finally, exploration of G4 motifs across eleven species shows strong enrichment at splice sites in mammals and birds, suggesting an evolutionary conserved splice regulatory mechanism.
|
|
| 5. |
- Howick, Virginia M., et al.
(författare)
-
The Malaria Cell Atlas : Single parasite transcriptomes across the complete Plasmodium life cycle
- 2019
-
Ingår i: Science. - : American Association for the Advancement of Science. - 0036-8075 .- 1095-9203. ; 365:6455
-
Tidskriftsartikel (refereegranskat)abstract
- Malaria parasites adopt a remarkable variety of morphological life stages as they transition through multiple mammalian host and mosquito vector environments. We profiled the single-cell transcriptomes of thousands of individual parasites, deriving the first high-resolution transcriptional atlas of the entire Plasmodium berghei life cycle. We then used our atlas to precisely define developmental stages of single cells from three different human malaria parasite species, including parasites isolated directly from infected individuals. The Malaria Cell Atlas provides both a comprehensive view of gene usage in a eukaryotic parasite and an open-access reference dataset for the study of malaria parasites.
|
|
