Literature DB >> 26412306

The Menu of Features that Define Primary MicroRNAs and Enable De Novo Design of MicroRNA Genes.

Wenwen Fang1, David P Bartel2.   

Abstract

MicroRNAs (miRNAs) are small regulatory RNAs processed from stem-loop regions of primary transcripts (pri-miRNAs), with the choice of stem loops for initial processing largely determining what becomes a miRNA. To identify sequence and structural features influencing this choice, we determined cleavage efficiencies of >50,000 variants of three human pri-miRNAs, focusing on the regions intractable to previous high-throughput analyses. Our analyses revealed a mismatched motif in the basal stem region, a preference for maintaining or improving base pairing throughout the remainder of the stem, and a narrow stem-length preference of 35 ± 1 base pairs. Incorporating these features with previously identified features, including three primary-sequence motifs, yielded a unifying model defining mammalian pri-miRNAs in which motifs help orient processing and increase efficiency, with the presence of more motifs compensating for structural defects. This model enables generation of artificial pri-miRNAs, designed de novo, without reference to any natural sequence yet processed more efficiently than natural pri-miRNAs.
Copyright © 2015 Elsevier Inc. All rights reserved.

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Year:  2015        PMID: 26412306      PMCID: PMC4613790          DOI: 10.1016/j.molcel.2015.08.015

Source DB:  PubMed          Journal:  Mol Cell        ISSN: 1097-2765            Impact factor:   17.970


  41 in total

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Authors:  G Hutvágner; J McLachlan; A E Pasquinelli; E Bálint; T Tuschl; P D Zamore
Journal:  Science       Date:  2001-07-12       Impact factor: 47.728

2.  Vertebrate microRNA genes.

Authors:  Lee P Lim; Margaret E Glasner; Soraya Yekta; Christopher B Burge; David P Bartel
Journal:  Science       Date:  2003-03-07       Impact factor: 47.728

3.  Both natural and designed micro RNAs can inhibit the expression of cognate mRNAs when expressed in human cells.

Authors:  Yan Zeng; Eric J Wagner; Bryan R Cullen
Journal:  Mol Cell       Date:  2002-06       Impact factor: 17.970

4.  Sequence requirements for micro RNA processing and function in human cells.

Authors:  Yan Zeng; Bryan R Cullen
Journal:  RNA       Date:  2003-01       Impact factor: 4.942

5.  Argonaute2 is the catalytic engine of mammalian RNAi.

Authors:  Jidong Liu; Michelle A Carmell; Fabiola V Rivas; Carolyn G Marsden; J Michael Thomson; Ji-Joon Song; Scott M Hammond; Leemor Joshua-Tor; Gregory J Hannon
Journal:  Science       Date:  2004-07-29       Impact factor: 47.728

6.  The Microprocessor complex mediates the genesis of microRNAs.

Authors:  Richard I Gregory; Kai-Ping Yan; Govindasamy Amuthan; Thimmaiah Chendrimada; Behzad Doratotaj; Neil Cooch; Ramin Shiekhattar
Journal:  Nature       Date:  2004-11-07       Impact factor: 49.962

7.  miRNPs: a novel class of ribonucleoproteins containing numerous microRNAs.

Authors:  Zissimos Mourelatos; Josée Dostie; Sergey Paushkin; Anup Sharma; Bernard Charroux; Linda Abel; Juri Rappsilber; Matthias Mann; Gideon Dreyfuss
Journal:  Genes Dev       Date:  2002-03-15       Impact factor: 11.361

8.  Genes and mechanisms related to RNA interference regulate expression of the small temporal RNAs that control C. elegans developmental timing.

Authors:  A Grishok; A E Pasquinelli; D Conte; N Li; S Parrish; I Ha; D L Baillie; A Fire; G Ruvkun; C C Mello
Journal:  Cell       Date:  2001-07-13       Impact factor: 41.582

9.  Next-generation libraries for robust RNA interference-based genome-wide screens.

Authors:  Martin Kampmann; Max A Horlbeck; Yuwen Chen; Jordan C Tsai; Michael C Bassik; Luke A Gilbert; Jacqueline E Villalta; S Chul Kwon; Hyeshik Chang; V Narry Kim; Jonathan S Weissman
Journal:  Proc Natl Acad Sci U S A       Date:  2015-06-15       Impact factor: 11.205

10.  A microRNA in a multiple-turnover RNAi enzyme complex.

Authors:  György Hutvágner; Phillip D Zamore
Journal:  Science       Date:  2002-08-01       Impact factor: 47.728

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  60 in total

1.  Microprocessor Recruitment to Elongating RNA Polymerase II Is Required for Differential Expression of MicroRNAs.

Authors:  Victoria A Church; Sigal Pressman; Mamiko Isaji; Mary Truscott; Nihal Terzi Cizmecioglu; Stephen Buratowski; Maxim V Frolov; Richard W Carthew
Journal:  Cell Rep       Date:  2017-09-26       Impact factor: 9.423

2.  The RNA-binding protein QKI5 regulates primary miR-124-1 processing via a distal RNA motif during erythropoiesis.

Authors:  Fang Wang; Wei Song; Hongmei Zhao; Yanni Ma; Yuxia Li; Di Zhai; Jingnan Pi; Yanmin Si; Jiayue Xu; Lei Dong; Rui Su; Mengmeng Zhang; Yong Zhu; Xiaoxia Ren; Fei Miao; Wenjie Liu; Feng Li; Junwu Zhang; Aibin He; Ge Shan; Jingyi Hui; Linfang Wang; Jia Yu
Journal:  Cell Res       Date:  2017-02-28       Impact factor: 25.617

3.  Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs.

Authors:  Tobias Fehlmann; Christina Backes; Mustafa Kahraman; Jan Haas; Nicole Ludwig; Andreas E Posch; Maximilian L Würstle; Matthias Hübenthal; Andre Franke; Benjamin Meder; Eckart Meese; Andreas Keller
Journal:  Nucleic Acids Res       Date:  2017-09-06       Impact factor: 16.971

4.  Effective and Accurate Gene Silencing by a Recombinant AAV-Compatible MicroRNA Scaffold.

Authors:  Jun Xie; Phillip W L Tai; Alexander Brown; Shoufang Gong; Sha Zhu; Yi Wang; Chengjian Li; Cansu Colpan; Qin Su; Ran He; Hong Ma; Jia Li; Hanqing Ye; Jihye Ko; Phillip D Zamore; Guangping Gao
Journal:  Mol Ther       Date:  2019-11-27       Impact factor: 11.454

Review 5.  The roles of structural dynamics in the cellular functions of RNAs.

Authors:  Laura R Ganser; Megan L Kelly; Daniel Herschlag; Hashim M Al-Hashimi
Journal:  Nat Rev Mol Cell Biol       Date:  2019-08       Impact factor: 94.444

6.  Emerging roles of DROSHA beyond primary microRNA processing.

Authors:  Dooyoung Lee; Chanseok Shin
Journal:  RNA Biol       Date:  2017-12-12       Impact factor: 4.652

Review 7.  Guidelines for the optimal design of miRNA-based shRNAs.

Authors:  Xavier Bofill-De Ros; Shuo Gu
Journal:  Methods       Date:  2016-04-12       Impact factor: 3.608

8.  Enhancement of gene knockdown efficiency by CNNC motifs in the intronic shRNA precursor.

Authors:  Seong Kyun Park; Yun Kee; Byung Joon Hwang
Journal:  Genes Genomics       Date:  2019-01-17       Impact factor: 1.839

9.  Drosha and Dicer: Slicers cut from the same cloth.

Authors:  Sisi Li; Dinshaw J Patel
Journal:  Cell Res       Date:  2016-04-29       Impact factor: 25.617

10.  MicroRNA Clustering Assists Processing of Suboptimal MicroRNA Hairpins through the Action of the ERH Protein.

Authors:  Wenwen Fang; David P Bartel
Journal:  Mol Cell       Date:  2020-04-16       Impact factor: 17.970

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