Detecting significant features in modeling microRNA-target interactions

Risultato della ricerca: Article

Abstract

MicroRNAs (miRNAs) are small non-coding RNA molecules mediating the translational repression and degradation of target mRNAs in the cell. Mature miRNAs are used as a template by the RNA-induced silencing complex (RISC) to recognize the complementary mRNAs to be regulated. Up to 60% of human genes are putative targets of one or more miRNAs. Several prediction tools are available to suggest putative miRNA targets, however, only a small part of the interaction pairs has been validated by experimental approaches. The analysis of the expression profile of the RNA fraction immunoprecipitated (IP) with the RISC proteins is an established method to detect which genes are actually regulated by the RISC machinery. In fact, genes that result over-expressed in the IP sample with respect to the whole cell lysate RNA, are considered as involved in the RISC complex, then miRNA targets. Here, we aim to find the features useful to predict which genes are overexpressed in IP, i.e. miRNA targets, without actually performing the IP experiments. To this purpose, we compiled and analyzed a novel high throughput data set suitable to unravel the features involved in the miRNA regulatory activities. We analyzed IP samples obtained by the immunoprecipitation of two RISC proteins, AGO2 and GW182. The two proteins shows different behaviors, in terms of enriched genes and features characterizing the immunoprecipitated RNA fractio. Further analysis is needed to unravel the reason of such different behavior.
Lingua originaleEnglish
pagine (da-a)1-2
Numero di pagine2
RivistaPEERJ PREPRINTS
Stato di pubblicazionePublished - 2017

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RNA
Genes
Proteins
Machinery
Throughput
Degradation
Molecules

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title = "Detecting significant features in modeling microRNA-target interactions",
abstract = "MicroRNAs (miRNAs) are small non-coding RNA molecules mediating the translational repression and degradation of target mRNAs in the cell. Mature miRNAs are used as a template by the RNA-induced silencing complex (RISC) to recognize the complementary mRNAs to be regulated. Up to 60{\%} of human genes are putative targets of one or more miRNAs. Several prediction tools are available to suggest putative miRNA targets, however, only a small part of the interaction pairs has been validated by experimental approaches. The analysis of the expression profile of the RNA fraction immunoprecipitated (IP) with the RISC proteins is an established method to detect which genes are actually regulated by the RISC machinery. In fact, genes that result over-expressed in the IP sample with respect to the whole cell lysate RNA, are considered as involved in the RISC complex, then miRNA targets. Here, we aim to find the features useful to predict which genes are overexpressed in IP, i.e. miRNA targets, without actually performing the IP experiments. To this purpose, we compiled and analyzed a novel high throughput data set suitable to unravel the features involved in the miRNA regulatory activities. We analyzed IP samples obtained by the immunoprecipitation of two RISC proteins, AGO2 and GW182. The two proteins shows different behaviors, in terms of enriched genes and features characterizing the immunoprecipitated RNA fractio. Further analysis is needed to unravel the reason of such different behavior.",
author = "Giovanni Perconti and Flavia Contino and Serena Bivona and Salvatore Feo and Claudia Coronnello",
year = "2017",
language = "English",
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journal = "PEERJ PREPRINTS",
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TY - JOUR

T1 - Detecting significant features in modeling microRNA-target interactions

AU - Perconti, Giovanni

AU - Contino, Flavia

AU - Bivona, Serena

AU - Feo, Salvatore

AU - Coronnello, Claudia

PY - 2017

Y1 - 2017

N2 - MicroRNAs (miRNAs) are small non-coding RNA molecules mediating the translational repression and degradation of target mRNAs in the cell. Mature miRNAs are used as a template by the RNA-induced silencing complex (RISC) to recognize the complementary mRNAs to be regulated. Up to 60% of human genes are putative targets of one or more miRNAs. Several prediction tools are available to suggest putative miRNA targets, however, only a small part of the interaction pairs has been validated by experimental approaches. The analysis of the expression profile of the RNA fraction immunoprecipitated (IP) with the RISC proteins is an established method to detect which genes are actually regulated by the RISC machinery. In fact, genes that result over-expressed in the IP sample with respect to the whole cell lysate RNA, are considered as involved in the RISC complex, then miRNA targets. Here, we aim to find the features useful to predict which genes are overexpressed in IP, i.e. miRNA targets, without actually performing the IP experiments. To this purpose, we compiled and analyzed a novel high throughput data set suitable to unravel the features involved in the miRNA regulatory activities. We analyzed IP samples obtained by the immunoprecipitation of two RISC proteins, AGO2 and GW182. The two proteins shows different behaviors, in terms of enriched genes and features characterizing the immunoprecipitated RNA fractio. Further analysis is needed to unravel the reason of such different behavior.

AB - MicroRNAs (miRNAs) are small non-coding RNA molecules mediating the translational repression and degradation of target mRNAs in the cell. Mature miRNAs are used as a template by the RNA-induced silencing complex (RISC) to recognize the complementary mRNAs to be regulated. Up to 60% of human genes are putative targets of one or more miRNAs. Several prediction tools are available to suggest putative miRNA targets, however, only a small part of the interaction pairs has been validated by experimental approaches. The analysis of the expression profile of the RNA fraction immunoprecipitated (IP) with the RISC proteins is an established method to detect which genes are actually regulated by the RISC machinery. In fact, genes that result over-expressed in the IP sample with respect to the whole cell lysate RNA, are considered as involved in the RISC complex, then miRNA targets. Here, we aim to find the features useful to predict which genes are overexpressed in IP, i.e. miRNA targets, without actually performing the IP experiments. To this purpose, we compiled and analyzed a novel high throughput data set suitable to unravel the features involved in the miRNA regulatory activities. We analyzed IP samples obtained by the immunoprecipitation of two RISC proteins, AGO2 and GW182. The two proteins shows different behaviors, in terms of enriched genes and features characterizing the immunoprecipitated RNA fractio. Further analysis is needed to unravel the reason of such different behavior.

UR - http://hdl.handle.net/10447/252274

UR - https://peerj.com/preprints/3337v1/

M3 - Article

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EP - 2

JO - PEERJ PREPRINTS

JF - PEERJ PREPRINTS

SN - 2167-9843

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