5 results on '"Katrin Sameith"'
Search Results
2. A central role for TFIID in the pluripotent transcription circuitry
- Author
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Hans R. Schöler, Daniel Esch, Erik van der Wal, Phillip Lijnzaad, H. T. Marc Timmers, Hermann vom Bruch, Katrin Sameith, Dong Wook Han, Guangming Wu, Sören Moritz, Nikolai Mischerikow, Atze J. Bergsma, Frank C. P. Holstege, A. F. Maarten Altelaar, Holm Zaehres, Albert J. R. Heck, W.W.M. Pim Pijnappel, Marijke P. Baltissen, Biomolecular Mass Spectrometry and Proteomics, Sub Biomol.Mass Spect. and Proteomics, Pediatrics, and Clinical Genetics
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Male ,Pluripotent Stem Cells ,Homeobox protein NANOG ,Transcription, Genetic ,Induced Pluripotent Stem Cells ,Biology ,Kruppel-Like Factor 4 ,Mice ,SOX2 ,Animals ,Humans ,Tissue engineering and pathology Renal disorder [NCMLS 3] ,Promoter Regions, Genetic ,Induced pluripotent stem cell ,Transcription factor ,Embryonic Stem Cells ,Genetics ,TATA-Binding Protein Associated Factors ,Multidisciplinary ,General transcription factor ,fungi ,Promoter ,Fibroblasts ,Cellular Reprogramming ,TATA-Box Binding Protein ,Chromatin ,Cell biology ,Female ,Transcription Factor TFIID ,RNA Polymerase II ,Transcription factor II D ,Reprogramming ,Transcription Factors - Abstract
Item does not contain fulltext Embryonic stem (ES) cells are pluripotent and characterized by open chromatin and high transcription levels, achieved through auto-regulatory and feed-forward transcription factor loops. ES-cell identity is maintained by a core of factors including Oct4 (also known as Pou5f1), Sox2, Klf4, c-Myc (OSKM) and Nanog, and forced expression of the OSKM factors can reprogram somatic cells into induced pluripotent stem cells (iPSCs) resembling ES cells. These gene-specific factors for RNA-polymerase-II-mediated transcription recruit transcriptional cofactors and chromatin regulators that control access to and activity of the basal transcription machinery on gene promoters. How the basal transcription machinery is involved in setting and maintaining the pluripotent state is unclear. Here we show that knockdown of the transcription factor IID (TFIID) complex affects the pluripotent circuitry in mouse ES cells and inhibits reprogramming of fibroblasts. TFIID subunits and the OSKM factors form a feed-forward loop to induce and maintain a stable transcription state. Notably, transient expression of TFIID subunits greatly enhanced reprogramming. These results show that TFIID is critical for transcription-factor-mediated reprogramming. We anticipate that, by creating plasticity in gene expression programs, transcription complexes such as TFIID assist reprogramming into different cellular states.
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- 2013
3. Fragrep: An Efficient Search Tool for Fragmented Patterns in Genomic Sequences
- Author
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Axel Mosig, Katrin Sameith, and Peter F. Stadler
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Biochemistry, Evolutionary biology, RNA, Non-coding RNA detection, Dictyostelium discoideum ,RNA, Untranslated ,RNase P ,Base Pair Mismatch ,Method ,Computational biology ,Biochemistry ,Dictyostelium discoideum ,Fragment (logic) ,Genetics ,ddc:572.8 ,Animals ,Dictyostelium ,Molecular Biology ,Vault (organelle) ,Sequence (medicine) ,Smith–Waterman algorithm ,Genome ,biology ,Efficient algorithm ,fungi ,Computational Biology ,non-coding RNA detection ,Sequence Analysis, DNA ,biology.organism_classification ,Computational Mathematics ,Order (biology) ,Fragrep ,fragmented pattern ,Algorithms ,Software - Abstract
Many classes of non-coding RNAs (ncRNAs; including Y RNAs, vault RNAs, RNase P RNAs, and MRP RNAs, as well as a novel class recently discovered in Dictyostelium discoideum) can be characterized by a pattern of short but well-conserved sequence elements that are separated by poorly conserved regions of sometimes highly variable lengths. Local alignment algorithms such as BLAST are therefore ill-suited for the discovery of new homologs of such ncRNAs in genomic sequences. The Fragrep tool instead implements an efficient algorithm for detecting the pattern fragments that occur in a given order. For each pattern fragment, the mismatch tolerance and bounds on the length of the intervening sequences can be specified separately. Furthermore, matches can be ranked by a statistically well-motivated scoring scheme.
- Published
- 2006
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4. Yeast glucose pathways converge on the transcriptional regulation of trehalose biosynthesis
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Linda V. Bakker, Nathalie Brabers, Thanasis Margaritis, Patrick Kemmeren, Katrin Sameith, Loes A.L. van de Pasch, Eva Apweiler, Dik van Leenen, and Frank C. P. Holstege
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Saccharomyces cerevisiae ,Saccharomyces cerevisiae Proteins ,lcsh:QH426-470 ,Transcription, Genetic ,lcsh:Biotechnology ,ved/biology.organism_classification_rank.species ,Epistasis and functional genomics ,03 medical and health sciences ,chemistry.chemical_compound ,Glucosyltransferases ,lcsh:TP248.13-248.65 ,Transcriptional regulation ,Genetics ,Model organism ,030304 developmental biology ,Oligonucleotide Array Sequence Analysis ,Regulation of gene expression ,0303 health sciences ,Trehalose biosynthesis ,biology ,ved/biology ,030302 biochemistry & molecular biology ,Trehalose ,Glucose signalling ,biology.organism_classification ,Regulatory networks ,Gene expression profiling ,Metabolic pathway ,lcsh:Genetics ,Glucose ,chemistry ,Biochemistry ,Gene Expression Regulation ,Biotechnology ,Research Article - Abstract
Background Cellular glucose availability is crucial for the functioning of most biological processes. Our understanding of the glucose regulatory system has been greatly advanced by studying the model organism Saccharomyces cerevisiae, but many aspects of this system remain elusive. To understand the organisation of the glucose regulatory system, we analysed 91 deletion mutants of the different glucose signalling and metabolic pathways in Saccharomyces cerevisiae using DNA microarrays. Results In general, the mutations do not induce pathway-specific transcriptional responses. Instead, one main transcriptional response is discerned, which varies in direction to mimic either a high or a low glucose response. Detailed analysis uncovers established and new relationships within and between individual pathways and their members. In contrast to signalling components, metabolic components of the glucose regulatory system are transcriptionally more frequently affected. A new network approach is applied that exposes the hierarchical organisation of the glucose regulatory system. Conclusions The tight interconnection between the different pathways of the glucose regulatory system is reflected by the main transcriptional response observed. Tps2 and Tsl1, two enzymes involved in the biosynthesis of the storage carbohydrate trehalose, are predicted to be the most downstream transcriptional components. Epistasis analysis of tps2 Δ double mutants supports this prediction. Although based on transcriptional changes only, these results suggest that all changes in perceived glucose levels ultimately lead to a shift in trehalose biosynthesis.
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- 2012
5. Functional Overlap and Regulatory Links Shape Genetic Interactions between Signaling Pathways
- Author
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Frank C. P. Holstege, Nevan J. Krogan, Ines J de Castro, Cheuk W. Ko, Patrick Kemmeren, Philip Lijnzaad, Thanasis Margaritis, Rodrigo Aldecoa, Tineke L. Lenstra, Joris J. Benschop, Mariel O. Brok, Like Fokkens, Berend Snel, Marian J. A. Groot Koerkamp, Virginia Taliadouros, Eva Apweiler, Loes A.L. van de Pasch, Linda V. Bakker, Nathalie Brabers, Sake van Wageningen, Dorothea Fiedler, Katrin Sameith, Antony J. Miles, Dik van Leenen, and Sander R. van Hooff
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Mutant ,Epistasis and functional genomics ,Context (language use) ,Saccharomyces cerevisiae ,Biology ,Article ,General Biochemistry, Genetics and Molecular Biology ,03 medical and health sciences ,0302 clinical medicine ,Redundancy (engineering) ,Phosphorylation ,030304 developmental biology ,Genetics ,0303 health sciences ,Biochemistry, Genetics and Molecular Biology(all) ,Gene Expression Profiling ,Phosphotransferases ,Epistasis, Genetic ,Phosphoric Monoester Hydrolases ,Gene expression profiling ,SIGNALING ,Epistasis ,CELLBIO ,DNA microarray ,030217 neurology & neurosurgery ,Function (biology) ,Signal Transduction - Abstract
SummaryTo understand relationships between phosphorylation-based signaling pathways, we analyzed 150 deletion mutants of protein kinases and phosphatases in S. cerevisiae using DNA microarrays. Downstream changes in gene expression were treated as a phenotypic readout. Double mutants with synthetic genetic interactions were included to investigate genetic buffering relationships such as redundancy. Three types of genetic buffering relationships are identified: mixed epistasis, complete redundancy, and quantitative redundancy. In mixed epistasis, the most common buffering relationship, different gene sets respond in different epistatic ways. Mixed epistasis arises from pairs of regulators that have only partial overlap in function and that are coupled by additional regulatory links such as repression of one by the other. Such regulatory modules confer the ability to control different combinations of processes depending on condition or context. These properties likely contribute to the evolutionary maintenance of paralogs and indicate a way in which signaling pathways connect for multiprocess control.
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