Dataset Information

Variation in the expression of miRNAs and mRNAs in rice (Oryza sativa)

ABSTRACT: Changes in patterns of gene expression are believed to be responsible for the phenotypic differences within and between species. Although the evolutionary significance of functional mutations has been emphasized in rice domestication, little is known about the differences in gene regulation underlying the phenotypic diversification among rice varieties. MicroRNAs (miRNAs) are small regulatory RNAs that play crucial roles in regulating post-transcriptional gene expression. Here, we studied the variation in the expression of both miRNAs and mRNA transcripts in three indica and three japonica rice varieties using RNA sequencing (RNA-seq) to examine the miRNA regulatory effect on target gene expression in rice. In total, 71.0%, 9.2%, and 1.5% of the expressed mature miRNAs showed tissue, subspecies, and tissue-subspecies interaction-biased expression. Most of these differentially expressed miRNAs are evolutionarily weakly conserved. To examine the miRNA regulatory effect on global gene expression under endogenous conditions, we performed pair-wise correlation coefficient analyses on the expression levels of 240 mature miRNAs and 1178 messenger RNAs (mRNAs) both globally and for each specific miRNA-mRNA pair. We found that the deeply conserved miRNAs can significantly decrease the target mRNA abundance. In addition, a total of 109 miRNA-mRNA pairs were identified as significantly correlated pairs (Adjusted p<0.01). Of those, 41 pairs showed positive correlations, while 68 pairs showed negative correlations. Functional analysis elucidated that these mRNAs belonged to different biological pathways that could regulate the stress response, metabolic processes, and rice development. In conclusion, the joint interrogation of miRNA and mRNA expression profiles in this study proved useful for the study of the role of miRNA expression and regulation in the plant transcriptome.

ORGANISM(S): Oryza sativa Japonica Group Oryza sativa Indica Group

PROVIDER: GSE71925 | GEO | 2017/02/09

SECONDARY ACCESSION(S): PRJNA292458

REPOSITORIES: GEO

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Project description:Schmitz2014 - RNA triplex formation The model is parameterized using the parameters for gene CCDC3 from Supplementary Table S1. The two miRNAs which form the triplex together with CCDC3 are miR-551b and miR-138. This model is described in the article: Cooperative gene regulation by microRNA pairs and their identification using a computational workflow. Schmitz U, Lai X, Winter F, Wolkenhauer O, Vera J, Gupta SK. Nucleic Acids Res. 2014 Jul; 42(12): 7539-7552 Abstract: MicroRNAs (miRNAs) are an integral part of gene regulation at the post-transcriptional level. Recently, it has been shown that pairs of miRNAs can repress the translation of a target mRNA in a cooperative manner, which leads to an enhanced effectiveness and specificity in target repression. However, it remains unclear which miRNA pairs can synergize and which genes are target of cooperative miRNA regulation. In this paper, we present a computational workflow for the prediction and analysis of cooperating miRNAs and their mutual target genes, which we refer to as RNA triplexes. The workflow integrates methods of miRNA target prediction; triplex structure analysis; molecular dynamics simulations and mathematical modeling for a reliable prediction of functional RNA triplexes and target repression efficiency. In a case study we analyzed the human genome and identified several thousand targets of cooperative gene regulation. Our results suggest that miRNA cooperativity is a frequent mechanism for an enhanced target repression by pairs of miRNAs facilitating distinctive and fine-tuned target gene expression patterns. Human RNA triplexes predicted and characterized in this study are organized in a web resource at www.sbi.uni-rostock.de/triplexrna/. This model is hosted on BioModels Database and identified by: BIOMD0000000530. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Background: microRNAs (miRNAs) are approximately 21 nucleotide non-coding transcripts capable of regulating gene expression. The most widely studied mechanism of regulation involves binding of the miRNA to a target mRNA, usually in its 3’ untranslated region (UTR). As a result, translation of the target mRNA is inhibited and sometimes the mRNA itself can be de-stabilized. The inhibitory effects of miRNAs have been linked to many diverse cellular processes including malignant proliferation and apoptosis, development and differentiation, metabolic processes and neural plasticity. We asked whether endogenous fluctuations in a set of mRNA and miRNA profiles contain correlated changes that are statistically distinguishable from the many other fluctuations in the data set. Methodology/Principal Findings: Biopsies from 12 human primary brain tumors were used to extract RNA. These samples were used to determine genome-wide mRNA expression levels by microarray analysis and a miRNA profile by real-time reverse transcription PCR (RT-PCR). Correlation coefficients were determined for all possible mRNA-miRNA pairs and the distribution of these correlations compared to the random distribution. An excess of high positive and negative correlation pairs were observed at the tails of these distributions. Most of these highest correlation pairs do not contain sufficiently complementary sequences to predict a target relationship; nor do they lie in physical proximity to each other. However, by examining pairs in which the significance of the correlation coefficients is modestly relaxed, negative correlations do tend to predict targets and positive correlations do tend to predict physically proximate pairs. A subset of high correlation pairs were experimentally validated by over-expressing or suppressing a miRNA and measuring the correlated mRNAs. Conclusions/Significance: Sufficient information exists within a set of tumor samples to detect endogenous correlations between miRNA and mRNA levels. Based on the validations of the correlations the causal arrow for these correlations is likely to be directed from the miRNAs to the mRNAs. From these data sets, we inferred and validated a tumor suppression pathway linked to miR-181c. Keywords: cell type comparison

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Variation in the expression of miRNAs and mRNAs in rice (Oryza sativa)

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