Quantitative Prediction of miRNA-mRNA Interaction Based on Equilibrium Concentrations

MicroRNAs (miRNAs) suppress gene expression by forming a duplex with a target messenger RNA (mRNA), blocking translation or initiating cleavage. Computational approaches have proven valuable for predicting which mRNAs can be targeted by a given miRNA, but currently available prediction methods do not address the extent of duplex formation under physiological conditions. Some miRNAs can at low concentrations bind to target mRNAs, whereas others are unlikely to bind within a physiologically relevant concentration range. Here we present a novel approach in which we find potential target sites on mRNA that minimize the calculated free energy of duplex formation, compute the free energy change involved in unfolding these sites, and use these energies to estimate the extent of duplex formation at specified initial concentrations of both species. We compare our predictions to experimentally confirmed miRNA-mRNA interactions (and non-interactions) in Drosophila melanogaster and in human. Although our method does not predict whether the targeted mRNA is degraded and/or its translation to protein inhibited, our quantitative estimates generally track experimentally supported results, indicating that this approach can be used to predict whether an interaction occurs at specified concentrations. Our approach offers a more-quantitative understanding of post-translational regulation in different cell types, tissues, and developmental condition

Quantitative Prediction of miRNA-mRNA Interaction Based on Equilibrium Concentrations

MicroRNAs (miRNAs) suppress gene expression by forming a duplex with a target messenger RNA (mRNA), blocking translation or initiating cleavage. Computational approaches have proven valuable for predicting which mRNAs can be targeted by a given miRNA, but currently available prediction methods do not address the extent of duplex formation under physiological conditions. Some miRNAs can at low concentrations bind to target mRNAs, whereas others are unlikely to bind within a physiologically relevant concentration range. Here we present a novel approach in which we find potential target sites on mRNA that minimize the calculated free energy of duplex formation, compute the free energy change involved in unfolding these sites, and use these energies to estimate the extent of duplex formation at specified initial concentrations of both species. We compare our predictions to experimentally confirmed miRNA-mRNA interactions (and non-interactions) in Drosophila melanogaster and in human. Although our method does not predict whether the targeted mRNA is degraded and/or its translation to protein inhibited, our quantitative estimates generally track experimentally supported results, indicating that this approach can be used to predict whether an interaction occurs at specified concentrations. Our approach offers a more-quantitative understanding of post-translational regulation in different cell types, tissues, and developmental conditions

Transcriptome-Wide Prediction of miRNA Targets in Human and Mouse Using FASTH

Transcriptional regulation by microRNAs (miRNAs) involves complementary base-pairing at target sites on mRNAs, yielding complex secondary structures. Here we introduce an efficient computational approach and software (FASTH) for genome-scale prediction of miRNA target sites based on minimizing the free energy of duplex structure. We apply our approach to identify miRNA target sites in the human and mouse transcriptomes. Our results show that short sequence motifs in the 5′ end of miRNAs frequently match mRNAs perfectly, not only at validated target sites but additionally at many other, energetically favourable sites. High-quality matching regions are abundant and occur at similar frequencies in all mRNA regions, not only the 3′UTR. About one-third of potential miRNA target sites are reassigned to different mRNA regions, or gained or lost altogether, among different transcript isoforms from the same gene. Many potential miRNA target sites predicted in human are not found in mouse, and vice-versa, but among those that do occur in orthologous human and mouse mRNAs most are situated in corresponding mRNA regions, i.e. these sites are themselves orthologous. Using a luciferase assay in HEK293 cells, we validate four of six predicted miRNA-mRNA interactions, with the mRNA level reduced by an average of 73%. We demonstrate that a thermodynamically based computational approach to prediction of miRNA binding sites on mRNAs can be scaled to analyse complete mammalian transcriptome datasets. These results confirm and extend the scope of miRNA-mediated species- and transcript-specific regulation in different cell types, tissues and developmental conditions

Long Noncoding RNA-Directed Epigenetic Regulation of Gene Expression Is Associated With Anxiety-like Behavior in Mice

Background RNA-directed regulation of epigenetic processes has recently emerged as an important feature of mammalian differentiation and development. Perturbation of this regulatory system in the brain may contribute to the development of neuropsychiatric disorders. Methods RNA sequencing was used to identify changes in the experience-dependent expression of long noncoding RNAs (lncRNAs) within the medial prefrontal cortex of adult mice. Transcripts were validated by real-time quantitative polymerase chain reaction and a candidate lncRNA, Gomafu, was selected for further investigation. The functional role of this schizophrenia-related lncRNA was explored in vivo by antisense oligonucleotide-mediated gene knockdown in the medial prefrontal cortex, followed by behavioral training and assessment of fear-related anxiety. Long noncoding RNA-directed epigenetic regulation of gene expression was investigated by chromatin and RNA immunoprecipitation assays. Results RNA sequencing analysis revealed changes in the expression of a significant number of genes related to neural plasticity and stress, as well as the dynamic regulation of lncRNAs. In particular, we detected a significant downregulation of Gomafu lncRNA. Our results revealed that Gomafu plays a role in mediating anxiety-like behavior and suggest that this may occur through an interaction with a key member of the polycomb repressive complex 1, BMI1, which regulates the expression of the schizophrenia-related gene beta crystallin (Crybb1). We also demonstrated a novel role for Crybb1 in mediating fear-induced anxiety-like behavior. Conclusions Experience-dependent expression of lncRNAs plays an important role in the epigenetic regulation of adaptive behavior, and the perturbation of Gomafu may be related to anxiety and the development of neuropsychiatric disorders

Small non-coding RNA expression from anterior cingulate cortex in schizophrenia shows sex specific regulation

MicroRNAs (miRNAs) are known to regulate the expression of genes that are important for brain development and function, but the roles of other classes of small non-coding RNAs (sncRNAs) are less well understood. Additionally, although miRNA expression studies have been conducted in post-mortem brain samples from schizophrenia (SCZ) patients, other classes of sncRNAs are yet to be investigated in SCZ. We profiled the expression of miRNAs, piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs) and small nuclear RNAs (snRNAs) in SCZ by applying small RNA sequencing (RNA-Seq) to sncRNA isolated from post-mortem anterior cingulate cortex (ACC) of SCZ-affected individuals (n = 22) and matched controls (n = 22). We identified about onethird of annotated miRNAs, one-quarter of snoRNAs and a small proportion of piRNAs and snRNAs. No sncRNAs were significantly differentially expressed between SCZ and controls, but there was evidence for an interaction between disease status and sex on the expression level of a number of miRNAs and snoRNAs. Many of these transcripts exhibited differential expression between male and female cases, and/or between female cases and controls, suggesting sex based dysregulation in ACC of SCZ. These findings require replication in an independent sample, but our study provides further insights into the potential involvement of sncRNAs in brain function and SCZ

Small non-coding RNA expression from anterior cingulate cortex in schizophrenia shows sex specific regulation

This work was supported by The Zaccari Scholarship in Mental Health Research, University of Queensland (to CR) and by Queensland Health (Grant number: 201300025).This work was supported by The Zaccari Scholarship in Mental Health Research, University of Queensland (to CR) and by Queensland Health (Grant number: 201300025). The number of known sncRNAs identified in each condition: A) miRNAs, B) piRNAs, C) snoRNAs and D) snRNAs

Optimization of signal-to-noise ratio for efficient microarray probe design

Motivation: Target-specific hybridization depends on oligo-probe characteristics that improve hybridization specificity and minimize genome-wide cross-hybridization. Interplay between specific hybridization and genome-wide cross-hybridization has been insufficiently studied, despite its crucial role in efficient probe design and in data analysis. Results: In this study, we defined hybridization specificity as a ratio between oligo target-specific hybridization and oligo genome-wide cross-hybridization. A microarray database, derived from the Genomic Comparison Hybridization (GCH) experiment and performed using the Affymetrix platform, contains two different types of probes. The first type of oligo-probes does not have a specific target on the genome and their hybridization signals are derived from genome-wide cross-hybridization alone. The second type includes oligonucleotides that have a specific target on the genomic DNA and their signals are derived from specific and cross-hybridization components combined together in a total signal. A comparative analysis of hybridization specificity of oligo-probes, as well as their nucleotide sequences and thermodynamic features was performed on the database. The comparison has revealed that hybridization specificity was negatively affected by low stability of the fully-paired oligo-target duplex, stable probe self-folding, G-rich content, including GGG motifs, low sequence complexity and nucleotide composition symmetry. Conclusion: Filtering out the probes with defined 'negative' characteristics significantly increases specific hybridization and dramatically decreasing genome-wide cross-hybridization. Selected oligo-probes have two times higher hybridization specificity on average, compared to the probes that were filtered from the analysis by applying suggested cutoff thresholds to the described parameters. A new approach for efficient oligo-probe design is described in our study

In Planta Determination of the mRNA-Binding Proteome of Arabidopsis Etiolated Seedlings

RNA binding proteins (RBPs) control the fate and expression of a transcriptome. Despite this fundamental importance, our understanding of plant RBPs is rudimentary, being mainly derived via bioinformatic extrapolation from other kingdoms. Here, we adapted the mRNA-protein interactome capture method to investigate the RNA binding proteome in planta. From Arabidopsis thaliana etiolated seedlings, we captured more than 700 proteins, including 300 with high confidence that we have defined as the At-RBP set. Approximately 75% of these At-RBPs are bioinformatically linked with RNA biology, containing a diversity of canonical RNA binding domains (RBDs). As no prior experimental RNA binding evidence exists for the majority of these proteins, their capture now authenticates them as RBPs. Moreover, we identified protein families harboring emerging and potentially novel RBDs, including WHIRLY, LIM, ALBA, DUF1296, and YTH domain-containing proteins, the latter being homologous to animal RNA methylation readers. Other At-RBP set proteins include major signaling proteins, cytoskeleton-associated proteins, membrane transporters, and enzymes, suggesting the scope and function of RNA-protein interactions within a plant cell is much broader than previously appreciated. Therefore, our foundation data set has provided an unbiased insight into the RNA binding proteome of plants, on which future investigations into plant RBPs can be based