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Gene expression data is analyzed to identify biomarkers, e.g. relevant genes, which serve for diagnostic, predictive, or prognostic use. Traditional approaches for biomarker detection select distinctive features from the data based exclusively on the signals therein, facing multiple shortcomings in regards to overfitting, biomarker robustness, and actual biological relevance. Prior knowledge approaches are expected to address these issues by incorporating prior biological knowledge, e.g. on gene-disease associations, into the actual analysis. However, prior knowledge approaches are currently not widely applied in practice because they are often use-case specific and seldom applicable in a different scope. This leads to a lack of comparability of prior knowledge approaches, which in turn makes it currently impossible to assess their effectiveness in a broader context.
Our work addresses the aforementioned issues with three contributions. Our first contribution provides formal definitions for both prior knowledge and the flexible integration thereof into the feature selection process. Central to these concepts is the automatic retrieval of prior knowledge from online knowledge bases, which allows for streamlining the retrieval process and agreeing on a uniform definition for prior knowledge. We subsequently describe novel and generalized prior knowledge approaches that are flexible regarding the used prior knowledge and applicable to varying use case domains. Our second contribution is the benchmarking platform Comprior. Comprior applies the aforementioned concepts in practice and allows for flexibly setting up comprehensive benchmarking studies for examining the performance of existing and novel prior knowledge approaches. It streamlines the retrieval of prior knowledge and allows for combining it with prior knowledge approaches. Comprior demonstrates the practical applicability of our concepts and further fosters the overall development and comparability of prior knowledge approaches. Our third contribution is a comprehensive case study on the effectiveness of prior knowledge approaches. For that, we used Comprior and tested a broad range of both traditional and prior knowledge approaches in combination with multiple knowledge bases on data sets from multiple disease domains. Ultimately, our case study constitutes a thorough assessment of a) the suitability of selected knowledge bases for integration, b) the impact of prior knowledge being applied at different integration levels, and c) the improvements in terms of classification performance, biological relevance, and overall robustness.
In summary, our contributions demonstrate that generalized concepts for prior knowledge and a streamlined retrieval process improve the applicability of prior knowledge approaches. Results from our case study show that the integration of prior knowledge positively affects biomarker results, particularly regarding their robustness. Our findings provide the first in-depth insights on the effectiveness of prior knowledge approaches and build a valuable foundation for future research.
Background
The forelimb-specific gene tbx5 is highly conserved and essential for the development of forelimbs in zebrafish, mice, and humans. Amongst birds, a single order, Dinornithiformes, comprising the extinct wingless moa of New Zealand, are unique in having no skeletal evidence of forelimb-like structures.
Results
To determine the sequence of tbx5 in moa, we used a range of PCR-based techniques on ancient DNA to retrieve all nine tbx5 exons and splice sites from the giant moa, Dinornis. Moa Tbx5 is identical to chicken Tbx5 in being able to activate the downstream promotors of fgf10 and ANF. In addition we show that missexpression of moa tbx5 in the hindlimb of chicken embryos results in the formation of forelimb features, suggesting that Tbx5 was fully functional in wingless moa. An alternatively spliced exon 1 for tbx5 that is expressed specifically in the forelimb region was shown to be almost identical between moa and ostrich, suggesting that, as well as being fully functional, tbx5 is likely to have been expressed normally in moa since divergence from their flighted ancestors, approximately 60 mya.
Conclusions
The results suggests that, as in mice, moa tbx5 is necessary for the induction of forelimbs, but is not sufficient for their outgrowth. Moa Tbx5 may have played an important role in the development of moa’s remnant forelimb girdle, and may be required for the formation of this structure. Our results further show that genetic changes affecting genes other than tbx5 must be responsible for the complete loss of forelimbs in moa.
Polynucleobacter asymbioticus strain QLW-P1DMWA-1T represents a group of highly successful heterotrophic ultramicrobacteria that is frequently very abundant (up to 70% of total bacterioplankton) in freshwater habitats across all seven continents. This strain was originally isolated from a shallow Alpine pond characterized by rapid changes in water temperature and elevated UV radiation due to its location at an altitude of 1300 m. To elucidate the strain’s adjustment to fluctuating environmental conditions, we recorded changes occurring in its transcriptomic and proteomic profiles under contrasting experimental conditions by simulating thermal conditions in winter and summer as well as high UV irradiation. To analyze the potential connection between gene expression and regulation via methyl group modification of the genome, we also analyzed its methylome. The methylation pattern differed between the three treatments, pointing to its potential role in differential gene expression. An adaptive process due to evolutionary pressure in the genus was deduced by calculating the ratios of non-synonymous to synonymous substitution rates for 20 Polynucleobacter spp. genomes obtained from geographically diverse isolates. The results indicate purifying selection.
Orthogonal systems for heterologous protein expression as well as for the engineering of synthetic gene regulatory circuits in hosts like Saccharomyces cerevisiae depend on synthetic transcription factors (synTFs) and corresponding cis-regulatory binding sites. We have constructed and characterized a set of synTFs based on either transcription activator-like effectors or CRISPR/Cas9, and corresponding small synthetic promoters (synPs) with minimal sequence identity to the host’s endogenous promoters. The resulting collection of functional synTF/synP pairs confers very low background expression under uninduced conditions, while expression output upon induction of the various synTFs covers a wide range and reaches induction factors of up to 400. The broad spectrum of expression strengths that is achieved will be useful for various experimental setups, e.g., the transcriptional balancing of expression levels within heterologous pathways or the construction of artificial regulatory networks. Furthermore, our analyses reveal simple rules that enable the tuning of synTF expression output, thereby allowing easy modification of a given synTF/synP pair. This will make it easier for researchers to construct tailored transcriptional control systems.
The cell interior is a highly packed environment in which biological macromolecules evolve and function. This crowded media has effects in many biological processes such as protein-protein binding, gene regulation, and protein folding. Thus, biochemical reactions that take place in such crowded conditions differ from diluted test tube conditions, and a considerable effort has been invested in order to understand such differences.
In this work, we combine different computationally tools to disentangle the effects of molecular crowding on biochemical processes. First, we propose a lattice model to study the implications of molecular crowding on enzymatic reactions. We provide a detailed picture of how crowding affects binding and unbinding events and how the separate effects of crowding on binding equilibrium act together. Then, we implement a lattice model to study the effects of molecular crowding on facilitated diffusion. We find that obstacles on the DNA impair facilitated diffusion. However, the extent of this effect depends on how dynamic obstacles are on the DNA. For the scenario in which crowders are only present in the bulk solution, we find that at some conditions presence of crowding agents can enhance specific-DNA binding. Finally, we make use of structure-based techniques to look at the impact of the presence of crowders on the folding a protein. We find that polymeric crowders have stronger effects on protein stability than spherical crowders. The strength of this effect increases as the polymeric crowders become longer. The methods we propose here are general and can also be applied to more complicated systems.
Recent high-throughput technologies enable the acquisition of a variety of complementary data and imply regulatory networks on the systems biology level. A common approach to the reconstruction of such networks is the cluster analysis which is based on a similarity measure. We use the information theoretic concept of the mutual information, that has been originally defined for discrete data, as a measure of similarity and propose an extension to a commonly applied algorithm for its calculation from continuous biological data. We compare our approach to previously existing algorithms. We develop a performance optimised software package for the application of the mutual information to large-scale datasets. Furthermore, we design and implement a web-based service for the analysis of integrated data measured with different technologies. Application to biological data reveals biologically relevant groupings and reconstructed signalling networks show agreements with physiological findings.
Comparative study of gene expression during the differentiation of white and brown preadipocytes
(2002)
Introduction Mammals have two types of adipose tissue: the lipid storing white adipose tissue and the brown adipose tissue characterised by its capacity for non-shivering thermogenesis. White and brown adipocytes have the same origin in mesodermal stem cells. Yet nothing is known so far about the commitment of precursor cells to the white and brown adipose lineage. Several experimental approaches indicate that they originate from the differentiation of two distinct types of precursor cells, white and brown preadipocytes. Based on this hypothesis, the aim of this study was to analyse the gene expression of white and brown preadipocytes in a systematic approach. Experimental approach The white and brown preadipocytes to compare were obtained from primary cell cultures of preadipocytes from the Djungarian dwarf hamster. Representational difference analysis was used to isolate genes potentially differentially expressed between the two cell types. The thus obtained cDNA libraries were spotted on microarrays for a large scale gene expression analysis in cultured preadipocytes and adipocytes and in tissue samples. Results 4 genes with higher expression in white preadipocytes (3 members of the complement system and a fatty acid desaturase) and 8 with higher expression in brown preadipocytes were identified. From the latter 3 coded for structural proteins (fibronectin, metargidin and a actinin 4), 3 for proteins involved in transcriptional regulation (necdin, vigilin and the small nuclear ribonucleoprotein polypeptide A) and 2 are of unknown function. Cluster analysis was applied to the gene expression data in order to characterise them and led to the identification of four major typical expression profiles: genes up-regulated during differentiation, genes down-regulated during differentiation, genes higher expressed in white preadipocytes and genes higher expressed in brown preadipocytes. Conclusion This study shows that white and brown preadipocytes can be distinguished by different expression levels of several genes. These results draw attention to interesting candidate genes for the determination of white and brown preadipocytes (necdin, vigilin and others) and furthermore indicate that potential importance of several functional groups in the differentiation of white and brown preadipocytes, mainly the complement system and extracellular matrix.