Dataset Information

Introns targeted by plant microRNAs: a possible novel mechanism of gene regulation.

ABSTRACT:

Background

In plant cells, most microRNAs (miRNAs) perform cleavages of target mature mRNAs in the cytoplasm. A recent report of a miRNA pathway involved in DNA methylation in the rice nucleus raises the possibility that plant miRNAs could cleave intron-containing pre-mRNAs (the precursor of messenger RNAs) located in the nucleus.

Results

In this study, we searched for the miRNA binding sites present within the introns of Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) genes. All miRNA-intron interactions predicted to result in cleavages were validated by using the public degradome sequencing data. As a result, 40 miRNA-intron pairs involving 25 miRNAs in Arabidopsis and 1912 pairs involving 91 miRNAs in rice were identified. For several rice genes, not all transcription forms (alternative splicing variants) were under similar regulation by specific miRNAs. Certain transcripts could escape cleavages due to the absence of intronic miRNA binding sites within these sequences. In some instances, specific cleaved intron remnants could be converted to double-stranded RNAs (dsRNAs) by RNA-dependent RNA polymerase 2. These dsRNAs could then be processed into 21- and 24-nt phased sRNAs by the activity of Dicer-like 1 and 3, respectively. The resultant siRNAs have the potential to be incorporated into Argonaute (AGO)-associated silencing complexes and result in cleavages of target pre-mRNA sequences.

Conclusions

A regulatory model, miRNA-targeting of intron-containing pre-mRNAs-phased sRNAs-targeting of mature mRNAs is proposed, which further expands the potential modes of action of plant miRNAs.

SUBMITTER: Meng Y

PROVIDER: S-EPMC4883735 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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Publications

Introns targeted by plant microRNAs: a possible novel mechanism of gene regulation.

Meng Yijun Y Shao Chaogang C Ma Xiaoxia X Wang Huizhong H

Rice (New York, N.Y.) 20130415 1

<h4>Background</h4>In plant cells, most microRNAs (miRNAs) perform cleavages of target mature mRNAs in the cytoplasm. A recent report of a miRNA pathway involved in DNA methylation in the rice nucleus raises the possibility that plant miRNAs could cleave intron-containing pre-mRNAs (the precursor of messenger RNAs) located in the nucleus.<h4>Results</h4>In this study, we searched for the miRNA binding sites present within the introns of Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) ...[more]

PMID: 24280590

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Project description:BackgroundMicroRNAs (miRNAs) are a set of short (19∼24 nt) non-coding RNAs that play significant roles as posttranscriptional regulators in animals and plants. The ab initio prediction methods show excellent performance for discovering new pre-miRNAs. While most of these methods can distinguish real pre-miRNAs from pseudo pre-miRNAs, few can predict the positions of miRNAs. Among the existing methods that can also predict the miRNA positions, most of them are designed for mammalian miRNAs, including human and mouse. Minority of methods can predict the positions of plant miRNAs. Accurate prediction of the miRNA positions remains a challenge, especially for plant miRNAs. This motivates us to develop MaturePred, a machine learning method based on support vector machine, to predict the positions of plant miRNAs for the new plant pre-miRNA candidates.Methodology/principal findingsA miRNA:miRNA* duplex is regarded as a whole to capture the binding characteristics of miRNAs. We extract the position-specific features, the energy related features, the structure related features, and stability related features from real/pseudo miRNA:miRNA* duplexes. A set of informative features are selected to improve the prediction accuracy. Two-stage sample selection algorithm is proposed to combat the serious imbalance problem between real and pseudo miRNA:miRNA* duplexes. The prediction method, MaturePred, can accurately predict plant miRNAs and achieve higher prediction accuracy compared with the existing methods. Further, we trained a prediction model with animal data to predict animal miRNAs. The model also achieves higher prediction performance. It further confirms the efficiency of our miRNA prediction method.ConclusionsThe superior performance of the proposed prediction model can be attributed to the extracted features of plant miRNAs and miRNA*s, the selected training dataset, and the carefully selected features. The web service of MaturePred, the training datasets, the testing datasets, and the selected features are freely available at http://nclab.hit.edu.cn/maturepred/.

Dataset Information

Introns targeted by plant microRNAs: a possible novel mechanism of gene regulation.

Background

Results

Conclusions

Publications

Introns targeted by plant microRNAs: a possible novel mechanism of gene regulation.

Similar Datasets

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