Dataset Information

A model explaining mRNA level fluctuations based on activity demands and RNA age.

ABSTRACT: Cellular RNA levels typically fluctuate and are influenced by different transcription rates and RNA degradation rates. However, the understanding of the fundamental relationships between RNA abundance, environmental stimuli, RNA activities, and RNA age distributions is incomplete. Furthermore, the rates of RNA degradation and transcription are difficult to measure in transcriptomic experiments in living organisms, especially in studies involving humans. A model based on activity demands and RNA age was developed to explore the mechanisms of RNA level fluctuations. Using single-cell time-series gene expression experimental data, we assessed the transcription rates, RNA degradation rates, RNA life spans, RNA demand, accumulated transcription levels, and accumulated RNA degradation levels. This model could also predict RNA levels under simulation backgrounds, such as stimuli that induce regular oscillations in RNA abundance, stable RNA levels over time that result from long-term shortage of total RNA activity or from uncontrollable transcription, and relationships between RNA/protein levels and metabolic rates. This information contributes to existing knowledge.

SUBMITTER: Xu Z

PROVIDER: S-EPMC8336849 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A model explaining mRNA level fluctuations based on activity demands and RNA age.

Xu Zhongneng Z Asakawa Shuichi S

PLoS computational biology 20210723 7

Cellular RNA levels typically fluctuate and are influenced by different transcription rates and RNA degradation rates. However, the understanding of the fundamental relationships between RNA abundance, environmental stimuli, RNA activities, and RNA age distributions is incomplete. Furthermore, the rates of RNA degradation and transcription are difficult to measure in transcriptomic experiments in living organisms, especially in studies involving humans. A model based on activity demands and RNA ...[more]

PMID: 34297727

Similar Datasets

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

Project description:Bone histomorphometry is a well-established approach to assessing skeletal pathology, providing a standard evaluation of the cellular components, architecture, mineralization, and growth of bone tissue. However, it depends in part on the subjective interpretation of cellular morphology by an expert, which introduces bias. In addition, diseases like osteogenesis imperfecta (OI) and fibrous dysplasia are accompanied by changes in the morphology and function of skeletal tissue and cells, hindering consistent evaluation of some morphometric parameters and interpretation of the results. For instance, traditional histomorphometry combined with collagen turnover markers suggested that reduced bone formation in classical OI is accompanied by increased bone resorption. In contrast, the well-documented postpubertal reduction in fractures would be easier to explain by reduced bone resorption after puberty, highlighting the need for less ambiguous measurements. Here we propose an approach to histomorphometry based on in situ mRNA hybridization, which uses Col1a1 as osteoblast and Ctsk as osteoclast markers. This approach can be fully automated and eliminates subjective identification of bone surface cells. We validate these markers based on the expression of Bglap, Ibsp, and Acp5. Comparison with traditional histological and tartrate-resistant acid phosphatase staining of the same sections suggests that mRNA-based analysis is more reliable. Unlike inconclusive traditional histomorphometry of mice with α2(I)-Gly610 to Cys substitution in the collagen triple helix, mRNA-based measurements reveal reduced osteoclastogenesis in 11-wk-old animals consistent with the postpubertal catch-up osteogenesis observed by microCT. We optimize the technique for cryosections of mineralized bone and sections of paraffin-embedded decalcified tissue, simplifying and broadening its applications. We illustrate the application of the mRNA-based approach to human samples using the example of a McCune-Albright syndrome patient. By eliminating confounding effects of altered cellular morphology and the need for subjective morphological evaluation, this approach may provide a more reproducible and accessible evaluation of bone pathology.

Dataset Information

A model explaining mRNA level fluctuations based on activity demands and RNA age.

Publications

A model explaining mRNA level fluctuations based on activity demands and RNA age.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets