Please use this identifier to cite or link to this item: doi:10.22028/D291-35567
Title: An estimate of the total number of true human miRNAs
Author(s): Alles, Julia
Fehlmann, Tobias
Fischer, Ulrike
Backes, Christina
Galata, Valentina
Minet, Marie
Hart, Martin
Abu-Halima, Masood
Grässer, Friedrich A.
Lenhof, Hans-Peter
Keller, Andreas
Meese, Eckart
Language: English
Title: Nucleic Acids Research
Volume: 47
Issue: 7
Pages: 3353–3364
Publisher/Platform: Oxford University Press
Year of Publication: 2019
DDC notations: 610 Medicine and health
Publikation type: Journal Article
Abstract: While the number of human miRNA candidates continuously increases, only a few of them are completely characterized and experimentally validated. Toward determining the total number of true miRNAs, we employed a combined in silico high- and experimental low-throughput validation strategy. We collected 28 866 human small RNA sequencing data sets containing 363.7 billion sequencing reads and excluded falsely annotated and low quality data. Our high-throughput analysis identified 65% of 24 127 mature miRNA candidates as likely false-positives. Using northern blotting, we experimentally validated miRBase entries and novel miRNA candidates. By exogenous overexpression of 108 precursors that encode 205 mature miRNAs, we confirmed 68.5% of the miRBase entries with the confirmation rate going up to 94.4% for the high-confidence entries and 18.3% of the novel miRNA candidates. Analyzing endogenous miRNAs, we verified the expression of 8 miRNAs in 12 different human cell lines. In total, we extrapolated 2300 true human mature miRNAs, 1115 of which are currently annotated in miRBase V22. The experimentally validated miRNAs will contribute to revising targetomes hypothesized by utilizing falsely annotated miRNAs.
DOI of the first publication: 10.1093/nar/gkz097
Link to this record: urn:nbn:de:bsz:291--ds-355674
hdl:20.500.11880/32443
http://dx.doi.org/10.22028/D291-35567
ISSN: 1362-4962
0305-1048
Date of registration: 24-Feb-2022
Description of the related object: Supplementary data
Related object: https://oup.silverchair-cdn.com/oup/backfile/Content_public/Journal/nar/47/7/10.1093_nar_gkz097/1/gkz097_supplemental_files.zip?Expires=1652182694&Signature=JbV5Dms~O99gjUpZztl8KH3mTRjNz~WR4~YAs3Fo5Yg6JNi9nGtiQsaQKhD399j4-V1urafPsTBKyjiusk60N7S-Vdrci83PlX2~8aeKYMzrWsS95QJHi54A7er15X2eWV1rCR4y~zTLH9dXpGP0nn8ZXZOL4M-OOQCbkI2fAxISHw05cCJTUvGmXsm0iTmwtMR4d6aapEbki3nBAjSEsh~UFEhrVwBdhHXyCWguCJSk3NcC-Qh5LbieJGtLe9n1lV-liHhgMRZU9kv28PM0OGJk7xRh-hY7tyjTDk8EoDaVPVhFaIC6qUAqRT6c605~BlxPG0mlEPj73BtyqnRWrA__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA
Faculty: M - Medizinische Fakultät
MI - Fakultät für Mathematik und Informatik
Department: M - Humangenetik
M - Infektionsmedizin
M - Medizinische Biometrie, Epidemiologie und medizinische Informatik
MI - Informatik
Professorship: M - Univ.-Prof. Dr. Andreas Keller
M - Prof. Dr. Eckhart Meese
M - Keiner Professur zugeordnet
MI - Prof. Dr. Hans-Peter Lenhof
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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