MicroRNA targeting specificity in mammals: determinants beyond seed pairing.

By Andrew Grimson, Kyle Kai-How Farh, W. K. Johnston, P. Garrett-engele, Lee P. Lim, David P. Bartel. Molecules and Cells, 2007

4,010 citations recorded by the source corpus.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/cf2011180602877ba7690e813a9a8568868cbed9

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Citations in the corpus

Connecting microRNA genes to the core transcriptional regulatory circuitry of embryonic stem cells (2008, background): “Targetscan prediction (Grimson et al., 2007) of Lin28 by mature Let-7g is noted (purple dashed line, right).”
Reversion of advanced Ebola virus disease in nonhuman primates with ZMapp™ (2014, methodology): “Then, we analyzed the relationship between the derepression of predicted targets and their site number, site type (6, 7, and 8 nt sites), site position, and other determinants used by TargetScan to calculate total context+ scores of predicted miRNA targets (Lewis et al., 2005; Grimson et al., 2007; ”
The microRNA.org resource: targets and expression (2007, methodology): “This approach, as designed into the original miRanda algorithm (14,15), is congruent with experimentally validated targets that do not contain perfect seed matches (17,18) and includes what other approaches have subsequently introduced as 30-compensatory matches (19) or combinations of seed and 30 m”
MicroRNAs in development and disease. (2011, methodology): “TargetScan prediction software applies the following parameters (186, 220, 353): 1) an alignment score for W-C base-pairing of nucleotides 2–7 (seed sequence) of the miRNA to its target, in addition to base-pairings beyond the seed sequence that can compensate for mismatches in the seed; 2) it also ”
A Pleiotropically Acting microRNA, miR-31, Inhibits Breast Cancer Metastasis (2009, positive): “To identify effectors of miR-31, we used two algorithms that predict the mRNA targets of a miRNA—PicTar (Krek et al., 2005) and TargetScan (Grimson et al., 2007).”
Getting to the root of miRNA-mediated gene silencing. (2008, background): “Studies comparing natural full-length 3′ UTRs suggest that the final outcome of miRNA regulation depends on the features and sequence of the target’s 3′ UTR (Behm-Ansmant et al., 2006; Eulalio et al., 2007a; Grimson et al., 2007).”
Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells. (2008, background): “Common target prediction algorithms assess complementarity of miRNAs to their targets (John et al. 2004), many enforcing strong pairing within the seed region of the miRNA (positions 2–8) (Lewis et al. 2005; Grimson et al. 2007).”
Reprogramming of mouse and human cells to pluripotency using mature microRNAs. (2011, background): “TargetScan prediction for mir-369 s also indicates that it inhibits ZEB2-related TGFb signaling (Grimson et al., 2007) (data not shown).”
MicroRNA-208a is a regulator of cardiac hypertrophy and conduction in mice. (2009, background): “org/), we selected several predicted miR-208a target genes for experimental scrutiny (32, 33).”
A search for conserved sequences in coding regions reveals that the let-7 microRNA targets Dicer within its coding sequence (2008, background): “We also found computational evidence to suggest that miRNA target sites in coding regions and 3 UTRs may differ in mechanism.”
miR-21: a small multi-faceted RNA (2008, background): “Several computational algorithms predict hundreds of mRNAs as possible targets for miR-21 [55–57]; however, relatively few have been experimentally validated.”