Reexamining microRNA site accessibility in Drosophila: a population genomics study.
Kertesz et al. (Nature Genetics 2008) described PITA, a miRNA target prediction algorithm based on hybridization energy and site accessibility. In this note, we used a population genomics approach to reexamine their data and found that the PITA algorithm had lower specificity than methods based on e...
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doaj-4d7b49a43d274c3caa2620bf81e671902020-11-24T21:55:35ZengPublic Library of Science (PLoS)PLoS ONE1932-62032009-01-0145e568110.1371/journal.pone.0005681Reexamining microRNA site accessibility in Drosophila: a population genomics study.Kevin ChenJonas MaaskolaMark L SiegalNikolaus RajewskyKertesz et al. (Nature Genetics 2008) described PITA, a miRNA target prediction algorithm based on hybridization energy and site accessibility. In this note, we used a population genomics approach to reexamine their data and found that the PITA algorithm had lower specificity than methods based on evolutionary conservation at comparable levels of sensitivity.We also showed that deeply conserved miRNAs tend to have stronger hybridization energies to their targets than do other miRNAs. Although PITA had higher specificity in predicting targets than a naïve seed-match method, this signal was primarily due to the use of a single cutoff score for all miRNAs and to the observed correlation between conservation and hybridization energy. Overall, our results clarify the accuracy of different miRNA target prediction algorithms in Drosophila and the role of site accessibility in miRNA target prediction.http://europepmc.org/articles/PMC2682560?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kevin Chen Jonas Maaskola Mark L Siegal Nikolaus Rajewsky |
spellingShingle |
Kevin Chen Jonas Maaskola Mark L Siegal Nikolaus Rajewsky Reexamining microRNA site accessibility in Drosophila: a population genomics study. PLoS ONE |
author_facet |
Kevin Chen Jonas Maaskola Mark L Siegal Nikolaus Rajewsky |
author_sort |
Kevin Chen |
title |
Reexamining microRNA site accessibility in Drosophila: a population genomics study. |
title_short |
Reexamining microRNA site accessibility in Drosophila: a population genomics study. |
title_full |
Reexamining microRNA site accessibility in Drosophila: a population genomics study. |
title_fullStr |
Reexamining microRNA site accessibility in Drosophila: a population genomics study. |
title_full_unstemmed |
Reexamining microRNA site accessibility in Drosophila: a population genomics study. |
title_sort |
reexamining microrna site accessibility in drosophila: a population genomics study. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2009-01-01 |
description |
Kertesz et al. (Nature Genetics 2008) described PITA, a miRNA target prediction algorithm based on hybridization energy and site accessibility. In this note, we used a population genomics approach to reexamine their data and found that the PITA algorithm had lower specificity than methods based on evolutionary conservation at comparable levels of sensitivity.We also showed that deeply conserved miRNAs tend to have stronger hybridization energies to their targets than do other miRNAs. Although PITA had higher specificity in predicting targets than a naïve seed-match method, this signal was primarily due to the use of a single cutoff score for all miRNAs and to the observed correlation between conservation and hybridization energy. Overall, our results clarify the accuracy of different miRNA target prediction algorithms in Drosophila and the role of site accessibility in miRNA target prediction. |
url |
http://europepmc.org/articles/PMC2682560?pdf=render |
work_keys_str_mv |
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