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doi:10.22028/D291-30340
Titel: | A high-resolution map of the human small non-coding transcriptome |
VerfasserIn: | Fehlmann, Tobias Backes, Christina Alles, Julia Fischer, Ulrike Hart, Martin Kern, Fabian Langseth, Hilde Rounge, Trine Umu, Sinan Ugur Kahraman, Mustafa Laufer, Thomas Haas, Jan Staehler, Cord Ludwig, Nicole Hübenthal, Matthias Meder, Benjamin Franke, Andre Lenhof, Hans-Peter Meese, Eckart Keller, Andreas |
Sprache: | Englisch |
Titel: | Bioinformatics |
Bandnummer: | 34 |
Heft: | 10 |
Startseite: | 1621 |
Endseite: | 1628 |
Verlag/Plattform: | Oxford University Press |
Erscheinungsjahr: | 2018 |
Dokumenttyp: | Journalartikel / Zeitschriftenartikel |
Abstract: | Motivation Although the amount of small non-coding RNA-sequencing data is continuously increasing, it is still unclear to which extent small RNAs are represented in the human genome. Results In this study we analyzed 303 billion sequencing reads from nearly 25 000 datasets to answer this question. We determined that 0.8% of the human genome are reliably covered by 874 123 regions with an average length of 31 nt. On the basis of these regions, we found that among the known small non-coding RNA classes, microRNAs were the most prevalent. In subsequent steps, we characterized variations of miRNAs and performed a staged validation of 11 877 candidate miRNAs. Of these, many were actually expressed and significantly dysregulated in lung cancer. Selected candidates were finally validated by northern blots. Although isolated miRNAs could still be present in the human genome, our presented set likely contains the largest fraction of human miRNAs. |
DOI der Erstveröffentlichung: | 10.1093/bioinformatics/btx814 |
URL der Erstveröffentlichung: | https://academic.oup.com/bioinformatics/article/34/10/1621/4769492 |
Link zu diesem Datensatz: | hdl:20.500.11880/28748 http://dx.doi.org/10.22028/D291-30340 |
ISSN: | 1460-2059 1367-4803 |
Datum des Eintrags: | 20-Feb-2020 |
Fakultät: | MI - Fakultät für Mathematik und Informatik |
Fachrichtung: | MI - Informatik |
Professur: | MI - Prof. Dr. Hans-Peter Lenhof |
Sammlung: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
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