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Hypoxia is a condition in which cells are deprived of adequate oxygen supply and represents a main feature of solid tumours. Cells under hypoxic stress activate transcriptional responses driven by hypoxia-inducible factors (HIFs), which affect multiple cellular pathways, including angiogenesis, metabolic adaptation and cell proliferation. While the transcriptional changes induced in hypoxic tumours are well characterised, it is still poorly understood how hypoxia contributes to the aberrant post-transcriptional regulation observed in tumours. In this PhD thesis, I studied the RNA response to hypoxia in cancer, to provide novel insights into its regulation.
Using deep RNA-Sequencing (RNA-Seq), I investigated transcriptome changes of three human cell lines from lung, cervical and breast cancer under hypoxia, advancing our knowledge of post-transcriptional gene regulation in hypoxic cancer. I show that hypoxia induced consistent changes in transcript abundance in the three cancer types. This was coupled to divergent splicing responses, highlighting the cell type specificity of alternative splicing programs. While the mRNA levels of RNA-binding proteins were mainly reduced, hypoxia upregulated muscleblind-like protein 2 (MBNL2) in all three cell lines. Hypoxia control was specific for MBNL2, since it did not affect its paralogs MBNL1 and MBNL3. Via knockdown experiments of MBNL2 in hypoxic cells, I could show that MBNL2 induction promotes adaptation of cancer cells to low oxygen by regulating both transcript abundance and alternative splicing of hypoxia response genes. In addition, depletion of MBNL2 reduced the proliferation and migration of cancer cells, corroborating a function of MBNL2 as cancer driver.
In the last few years, a novel class of RNAs has gained attention, namely circular RNAs (circRNAs), which are produced by a particular splicing mechanism, known as back-splicing. CircRNAs have been reported to change their abundance in cancer and their high stability makes them promising candidates as diagnostic biomarkers. In this study, I took advantage of deep rRNA-depleted RNA-Seq data to comprehensively investigate the expression of circRNAs in human cancer cells and their changes in response to hypoxia. To reliably identify circRNAs, I established a pipeline that integrates two available tools. for circRNA detection with custom approaches for quantification and statistical analysis. Using this pipeline, I identified 12006 circRNAs in the three cancer cell lines. Their molecular features suggest an involvement of complementary RNA sequences as well as trans-acting factors in circRNA biogenesis, including the splicing factor HNRNPC. Remarkably, I detected 210 circRNAs that are more abundant than their linear counterparts. Upon hypoxic stress, 64 circRNAs were differentially expressed in cancer cells, in most cases in a cell type-specific manner. In summary, in this PhD thesis, I present a comparative transcriptome profiling in human cancer cell lines. It reveals MBNL2 as an important player in hypoxic cancer progression and provides novel insights into the biogenesis and regulation of circRNAs under hypoxic stress.
Transposable elements (TEs) are replicating genetic elementst hat comprise up to 50% of mammalian genomes. A specific class of TEs are retrotransposons that proliferate by transcription into a RNA intermediate, followed by genomic reintegration into another locus (so called “copy & paste” mechanism). Due to the lack of removal mechanisms and very rare parallel insertions, the presence of TE insertions at ortholgous genomic loci in multiple taxa provides a virtually homoplasy free phylogenetic marker. So far, developing phylogenetically informative markers from TE insertions has been a tedious work of testing hundreds of putative candidate loci in a trial-and error approach with low success rate. Hence, phylogenetic studies using TE insertions were often limited to a few dozen markers.
Recently, genome sequencing of multiple species using reference-mapping allowed the identification of genome-scale datasets of TE insertions. and made the ad-hoc development of phylogenetic informative markers possible. However, genome scale TE detection methods have rarely been applied to non model organisms in which data availability and quality is comparably limited. In this thesis, I developed the TeddyPi pipeline (TE detection and discovery for phylogenetic inference), a software tool that made it possible to obtain reliable genome-scale TE insertion data from low-coverage genomes. This was achieved by integrating the data from multiple TE and structural variation callers as well as applying a stringent filtering pipeline to exclude low-quality insertion calls. Whole-genome sequencing datasets of bears (Ursidae) and baleen whales (Mysticeti) were used to apply TE based phylogenetic inference and evaluate the method in comparison to sequence-based phylogenomic analyses.
In the bear genomes, TeddyPi identified 150,513 high-quality transposable element (TE) insertions, which allowed me to reconstruct the evolutionary history of bears despite extensive phylogenetic conflict (Lammers et al., 2017). The large number of detected TE insertions made also detailed network analyses possible that visualize the phylogenetic conflict. Experimental polymerase chain reaction (PCR) assays validated up to 93 % of the computationally identified TE loci and demonstrated the high accuracy of the dataset underlying the phylogenetic analyses.
Second, I present the initial genome sequencing of six baleen whales and a detailed investigation of their evolutionary history using TE insertions and established sequence-based phylogenomic methods. The taxon sampling of baleen whales included iconic species like the blue whale (Balaneoptera musculus) or the humpback whale (Megaptera novaengliae) (Árnason et al., 2018). A sequence-based reconstruction of the baleen whale species tree solved the long-debated phylogenetic position of the gray whale (Echrichtius robustus) within rorquals (Balaneopteridae) for the first time with high statistical support. Furthermore, the genome data made it possible to identify large extent of phylogenetic conflict for divergences during the radiation of rorquals that occurred 7-10 million years ago (Ma).
The phylogenomic analyses of 91,589 TE insertions in the whale genomes confirmed the sequence-based topology (Lammers et al., 2019). The quantification of phylogenetic signals obtained from the TE insertions revealed a high degree of discordance for the divergence of the gray whale and rorquals. Despite the large genome-scale dataset, statistical tests showed only marginal support for a bifurcating divergence of gray whales and the rorqual species. The limited statistical support for a strictly bifurcating tree obtained from genome-scale datasets of thousands of markers demonstrates the importance for including phylogenetic networks for displaying evolutionary divergences.
In conclusion, this thesis shows that identification of TE insertions from whole-genome resequencing provides plentiful and accurate phylogenomic markers. For the application in non model organisms, I provide a easy-to-use software to integrate multiple datasets from TE and structural variation callers in order to obtain reliable and ascertainment-bias free datasets. Detecting genome-scale datasets of TE insertions in two case studies demonstrates the applicability of this marker system for phylogenetic reconstruction and inferring phylogenetic conflict.