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Identifications of conserved 7-mers in 3'-UTRs and microRNAs in Drosophila
BACKGROUND: MicroRNAs (miRNAs) are a class of endogenous regulatory small RNAs which play an important role in posttranscriptional regulations by targeting mRNAs for cleavage or translational repression. The base-pairing between the 5'-end of miRNA and the target mRNA 3'-UTRs is essential...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2007
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2241842/ https://www.ncbi.nlm.nih.gov/pubmed/17996040 http://dx.doi.org/10.1186/1471-2105-8-432 |
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author | Gu, Jin Fu, Hu Zhang, Xuegong Li, Yanda |
author_facet | Gu, Jin Fu, Hu Zhang, Xuegong Li, Yanda |
author_sort | Gu, Jin |
collection | PubMed |
description | BACKGROUND: MicroRNAs (miRNAs) are a class of endogenous regulatory small RNAs which play an important role in posttranscriptional regulations by targeting mRNAs for cleavage or translational repression. The base-pairing between the 5'-end of miRNA and the target mRNA 3'-UTRs is essential for the miRNA:mRNA recognition. Recent studies show that many seed matches in 3'-UTRs, which are fully complementary to miRNA 5'-ends, are highly conserved. Based on these features, a two-stage strategy can be implemented to achieve the de novo identification of miRNAs by requiring the complete base-pairing between the 5'-end of miRNA candidates and the potential seed matches in 3'-UTRs. RESULTS: We presented a new method, which combined multiple pairwise conservation information, to identify the frequently-occurred and conserved 7-mers in 3'-UTRs. A pairwise conservation score (PCS) was introduced to describe the conservation of all 7-mers in 3'-UTRs between any two Drosophila species. Using PCSs computed from 6 pairs of flies, we developed a support vector machine (SVM) classifier ensemble, named Cons-SVM and identified 689 conserved 7-mers including 63 seed matches covering 32 out of 38 known miRNA families in the reference dataset. In the second stage, we searched for 90 nt conserved stem-loop regions containing the complementary sequences to the identified 7-mers and used the previously published miRNA prediction software to analyze these stem-loops. We predicted 47 miRNA candidates in the genome-wide screen. CONCLUSION: Cons-SVM takes advantage of the independent evolutionary information from the 6 pairs of flies and shows high sensitivity in identifying seed matches in 3'-UTRs. Combining the multiple pairwise conservation information by the machine learning approach, we finally identified 47 miRNA candidates in D. melanogaster. |
format | Text |
id | pubmed-2241842 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-22418422008-02-14 Identifications of conserved 7-mers in 3'-UTRs and microRNAs in Drosophila Gu, Jin Fu, Hu Zhang, Xuegong Li, Yanda BMC Bioinformatics Research Article BACKGROUND: MicroRNAs (miRNAs) are a class of endogenous regulatory small RNAs which play an important role in posttranscriptional regulations by targeting mRNAs for cleavage or translational repression. The base-pairing between the 5'-end of miRNA and the target mRNA 3'-UTRs is essential for the miRNA:mRNA recognition. Recent studies show that many seed matches in 3'-UTRs, which are fully complementary to miRNA 5'-ends, are highly conserved. Based on these features, a two-stage strategy can be implemented to achieve the de novo identification of miRNAs by requiring the complete base-pairing between the 5'-end of miRNA candidates and the potential seed matches in 3'-UTRs. RESULTS: We presented a new method, which combined multiple pairwise conservation information, to identify the frequently-occurred and conserved 7-mers in 3'-UTRs. A pairwise conservation score (PCS) was introduced to describe the conservation of all 7-mers in 3'-UTRs between any two Drosophila species. Using PCSs computed from 6 pairs of flies, we developed a support vector machine (SVM) classifier ensemble, named Cons-SVM and identified 689 conserved 7-mers including 63 seed matches covering 32 out of 38 known miRNA families in the reference dataset. In the second stage, we searched for 90 nt conserved stem-loop regions containing the complementary sequences to the identified 7-mers and used the previously published miRNA prediction software to analyze these stem-loops. We predicted 47 miRNA candidates in the genome-wide screen. CONCLUSION: Cons-SVM takes advantage of the independent evolutionary information from the 6 pairs of flies and shows high sensitivity in identifying seed matches in 3'-UTRs. Combining the multiple pairwise conservation information by the machine learning approach, we finally identified 47 miRNA candidates in D. melanogaster. BioMed Central 2007-11-08 /pmc/articles/PMC2241842/ /pubmed/17996040 http://dx.doi.org/10.1186/1471-2105-8-432 Text en Copyright © 2007 Gu et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Gu, Jin Fu, Hu Zhang, Xuegong Li, Yanda Identifications of conserved 7-mers in 3'-UTRs and microRNAs in Drosophila |
title | Identifications of conserved 7-mers in 3'-UTRs and microRNAs in Drosophila |
title_full | Identifications of conserved 7-mers in 3'-UTRs and microRNAs in Drosophila |
title_fullStr | Identifications of conserved 7-mers in 3'-UTRs and microRNAs in Drosophila |
title_full_unstemmed | Identifications of conserved 7-mers in 3'-UTRs and microRNAs in Drosophila |
title_short | Identifications of conserved 7-mers in 3'-UTRs and microRNAs in Drosophila |
title_sort | identifications of conserved 7-mers in 3'-utrs and micrornas in drosophila |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2241842/ https://www.ncbi.nlm.nih.gov/pubmed/17996040 http://dx.doi.org/10.1186/1471-2105-8-432 |
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