|
|
|
Courtesy of Janez Plavec
|
The paper:
A. Grimson, et al., "MicroRNA targeting specificity in mammals: determinants
beyond seed pairing," Mol Cell, 27:91-105, 2007. (Cited in 109 papers)
The bottom line:
Massachusetts Institute of Technology biologist David Bartel and colleagues
constructed an algorithm to predict miRNA target sites on untranslated regions
(UTRs) of mRNAs, which affects posttranscriptional repression. In addition to seed
pairing, which is the alignment of complimentary sequences between mRNAs and miRNAs,
and central to microRNA's function, factors that predict where miRNA binds include
adenine and urasil-rich sequences, as well as the distance of target sites away from
the center of long UTR's.
The detail:
Prior to this Hot Paper, researchers knew that factors besides seed pairing
influenced binding, but Bartel's group considered these other factors in
unprecedented detail, according to John Rossi, a molecular geneticist at City of
Hope.
The rub:
Oliver Hobert at Columbia University cautions that there are key
experimentally-proven, in vivo exceptions to each of the handful of prediction
algorithms out there. "I don't trust any one more than the others," he says. Bartel
concedes the controversy, but "a lot of people are using our target predictions," he
says.
The applications:
Rossi, for example, says that his group has used the "Bartelian method" to
indentify several SNPs in seed regions or in sequences that precede miRNA genes that
are linked to schizophrenia or autism. Furthermore, Bartel's group recently used the
algorithms to successfully predict the target sites and show the affect of miRNA
miR-223 on protein output in the cell (Nature, 455:64-71, 2008).
| Algorithm |
Avg. protein repression of top 29 genes predicted to be miR-223 targets |
| miRanda |
13.1% |
| PicTar |
17.0% |
| TargetScan (based on this Hot Paper) |
26.4% |