Dataset Information

Apparent microRNA-Target-specific Histone Modification in Mammalian Spermatogenesis.

ABSTRACT: BACKGROUND:Epigenetics is an important mRNA expression regulator. However, how distinct epigenetic factors, such as microRNAs (miRNAs) and promoter methylation, cooperatively regulate mRNA expression is rarely discussed. Recently, apparent miRNA regulation of promoter methylation was identified by bioinformatic analysis; however, it has not yet been experimentally confirmed. If miRNA regulation of other epigenetic factors were identified, it would reveal another layer of epigenetic regulation. In this paper, histone modifications (H3K4me1, H3K4me3, H3K27me3, H3K27ac, H3K9ac, and H2AZ) during mammalian spermatogenesis were studied and the apparent miRNA-target-specific histone modification was investigated by bioinformatic analyses of publicly available datasets. RESULTS:We identified several miRNAs' target genes that are significantly associated with histone modification during mammalian spermatogenesis. MiRNAs that target genes associated with the most significant histone modifications are expressed before or during spermatogenesis; thus the results were convincing. CONCLUSIONS:In this paper, we identified apparent miRNA regulation of histone modifications using a bioinformatics approach. The biological mechanisms of this effect should be further experimentally investigated.

SUBMITTER: Taguchi YH

PROVIDER: S-EPMC4345942 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Apparent microRNA-Target-specific Histone Modification in Mammalian Spermatogenesis.

Taguchi Y-H YH

Evolutionary bioinformatics online 20150224 Suppl 1

<h4>Background</h4>Epigenetics is an important mRNA expression regulator. However, how distinct epigenetic factors, such as microRNAs (miRNAs) and promoter methylation, cooperatively regulate mRNA expression is rarely discussed. Recently, apparent miRNA regulation of promoter methylation was identified by bioinformatic analysis; however, it has not yet been experimentally confirmed. If miRNA regulation of other epigenetic factors were identified, it would reveal another layer of epigenetic regul ...[more]

PMID: 25780334

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Project description:MicroRNAs (miRNAs) are single-stranded non-coding RNAs known to regulate a wide range of cellular processes by silencing the gene expression at the protein and/or mRNA levels. Computational prediction of miRNA targets is essential for elucidating the detailed functions of miRNA. However, the prediction specificity and sensitivity of the existing algorithms are still poor to generate meaningful, workable hypotheses for subsequent experimental testing. Constructing a richer and more reliable training data set and developing an algorithm that properly exploits this data set would be the key to improve the performance current prediction algorithms.A comprehensive training data set is constructed for mammalian miRNAs with its positive targets obtained from the most up-to-date miRNA target depository called miRecords and its negative targets derived from 20 microarray data. A new algorithm SVMicrO is developed, which assumes a 2-stage structure including a site support vector machine (SVM) followed by a UTR-SVM. SVMicrO makes prediction based on 21 optimal site features and 18 optimal UTR features, selected by training from a comprehensive collection of 113 site and 30 UTR features. Comprehensive evaluation of SVMicrO performance has been carried out on the training data, proteomics data, and immunoprecipitation (IP) pull-down data. Comparisons with some popular algorithms demonstrate consistent improvements in prediction specificity, sensitivity and precision in all tested cases. All the related materials including source code and genome-wide prediction of human targets are available at http://compgenomics.utsa.edu/svmicro.html.A 2-stage SVM based new miRNA target prediction algorithm called SVMicrO is developed. SVMicrO is shown to be able to achieve robust performance. It holds the promise to achieve continuing improvement whenever better training data that contain additional verified or high confidence positive targets and properly selected negative targets are available.

Dataset Information

Apparent microRNA-Target-specific Histone Modification in Mammalian Spermatogenesis.

Publications

Apparent microRNA-Target-specific Histone Modification in Mammalian Spermatogenesis.

Similar Datasets

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