Systematic transcriptome wide analysis of lncRNA-miRNA interactions

Long noncoding RNAs (lncRNAs) are a recently discovered class of non-protein coding RNAs which have now increasingly been shown to be involved in a wide variety of biological processes as regulatory molecules. Little is known regarding the regulatory interactions between noncoding RNA classes. Recent reports have suggested that lncRNAs could potentially interact with other noncoding RNAs including miroRNAs (miRNAs) and modulate their regulatory role through interactions. We hypothesized that long noncoding RNAs could participate as a layer of regulatory interactions with miRNAs. The availability of genome-scale datasets for argonaute targets across human transcriptome has prompted us to reconstruct a genome-scale network of interactions between miRNAs and lncRNAs. We used well characterized experimental Photoactivatable-Ribonucleoside-Enhanced Crosslinking and Immunoprecipitation (PAR-CLIP) datasets and the recent genome-wide annotations for lncRNAs in public domain to construct a comprehensive transcriptome-wide map of miRNA regulatory elements. Comparative analysis revealed many of the miRNAs could target long noncoding RNAs, apart from the coding transcripts thus participating in a novel layer of regulatory interactions between noncoding RNA classes. We also find the miRNA regulatory elements have a positional preference, clustering towards the 3' and 5' ends of the long noncoding transcripts. We also further reconstruct a genome-wide map of miRNA interactions with lncRNAs as well as messenger RNAs. This analysis suggests widespread regulatory interactions between noncoding RNAs classes and suggests a novel functional role for lncRNAs. We also present the first transcriptome scale study on lncRNA-miRNA interactions and the first report of a genome-scale reconstruction of a noncoding RNA regulatory interactome involving lncRNAs

Differentially expressed microRNAs in experimental cerebral malaria and their involvement in endocytosis, adherens junctions, FoxO and TGF-β signalling pathways

Cerebral malaria (CM) is the most severe manifestation of infection with Plasmodium, however its pathogenesis is still not completely understood. microRNA (miRNA) have been an area of focus in infectious disease research, due to their ability to affect normal biological processes, and have been shown to play roles in various viral, bacterial and parasitic infections, including malaria. The expression of miRNA was studied following infection of CBA mice with either Plasmodium berghei ANKA (causing CM), or Plasmodium yoelii (causing severe but non-cerebral malaria (NCM)). Using microarray analysis, miRNA expression was compared in the brains of non-infected (NI), NCM and CM mice. Six miRNA were significantly dysregulated between NCM and CM mice, and four of these, miR-19a-3p, miR-19b-3p, miR-142-3p and miR-223-3p, were further validated by qPCR assays. These miRNA are significantly involved in several pathways relevant to CM, including the TGF-β and endocytosis pathways. Dysregulation of these miRNA during CM specifically compared with NCM suggests that these miRNA, through their regulation of downstream targets, may be vitally involved in the neurological syndrome. Our data implies that, at least in the mouse model, miRNA may play a regulatory role in CM pathogenesis.This work was funded by the National Health and Medical Research Council (#1099920 for GEG). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.S

Morphological effects of G-quadruplex stabilization using a small molecule in zebrafish.

Zebrafish (Danio rerio) embryos are transparent and advantageous for studying early developmental changes due to ex utero development, making them an appropriate model for studying gene expression changes as a result of molecular targeting. Zebrafish embryos were injected with a previously reported G-quadruplex selective ligand, and the phenotypic changes were recorded. We report marked discrepancies in the development of intersegmental vessels. In silico analysis determined that the putative G-quadruplex motif occur in the upstream promoter region of the Cdh5 (N-cadherin) gene. A real-time polymerase chain reaction-based investigation indicated that in zebrafish, CDH-2 (ZN-cad) was significantly downregulated in the ligand-treated embryos. Biophysical characterization of the interaction of the ligand with the G-quadruplex motif found in this promoter yielded strong binding and stabilization of the G-quadruplex with this ligand. Hence, we report for the first time the phenotypic impact of G-quadruplex targeting with a ligand in a vertebrate organism. This study has unveiled not only G-quadruplex targeting in non-human animal species but also the potential that G-quadruplexes can provide a ready tool for understanding the phenotypic effects of targeting certain important genes involved in differentiation and developmental processes in a living eukaryotic organism

Antagonism of microRNA function in zebrafish embryos by using locked nucleic acid enzymes (LNAzymes).

MicroRNAs (miRNAs) have crucial functions in many cellular processes, such as differentiation, proliferation and apoptosis; aberrant expression of miRNAs has been linked to human diseases, including cancer. Tools that allow specific and efficient knockdown of miRNAs would be of immense importance for exploring miRNA function. Zebrafish serves as an excellent vertebrate model system to understand the functions of miRNAs involved in a variety of biological processes. We designed and employed a strategy based on locked nucleic acid enzymes (LNAzymes) for in vivo knockdown of miRNA in zebrafish embryos. We demonstrate that LNAzyme can efficiently knockdown miRNAs with minimal toxicity to the zebrafish embryos

Antagonism of microRNA function in zebrafish embryos by using locked nucleic acid enzymes (LNAzymes).

MicroRNAs (miRNAs) have crucial functions in many cellular processes, such as differentiation, proliferation and apoptosis; aberrant expression of miRNAs has been linked to human diseases, including cancer. Tools that allow specific and efficient knockdown of miRNAs would be of immense importance for exploring miRNA function. Zebrafish serves as an excellent vertebrate model system to understand the functions of miRNAs involved in a variety of biological processes. We designed and employed a strategy based on locked nucleic acid enzymes (LNAzymes) for in vivo knockdown of miRNA in zebrafish embryos. We demonstrate that LNAzyme can efficiently knockdown miRNAs with minimal toxicity to the zebrafish embryos

3-D density kernel estimation for counting in microscopy image volumes using 3-D image filters and random decision trees

We describe a means through which cells can be accurately counted in 3-D microscopy image data, using only weakly annotated images as input training material. We update an existing 2-D density kernel estimation approach into 3-D and we introduce novel 3-D features which encapsulate the 3-D neighbourhood surrounding each voxel. The proposed 3-D density kernel estimation (DKE-3-D) method, which utilises an ensemble of random decision trees, is computationally efficient and achieves state-of-the-art performance. DKE-3-D avoids the problem of discrete object identification and segmentation, common to many existing 3-D counting techniques, and we show that it outperforms other methods when quantification of densely packed and heterogeneous objects is desired. In this article we successfully apply the technique to two simulated and to two experimentally derived datasets and show that DKE-3-D has great potential in the biomedical sciences and any field where volumetric datasets are used

Reverse genetics screen in zebrafish identifies a role of miR-142a-3p in vascular development and integrity.

MicroRNAs are a well-studied class of non-coding RNA and are known to regulate developmental processes in eukaryotes. Their role in key biological processes such as vasculature development has attracted interest. However, a comprehensive understanding of molecular regulation of angiogenesis and vascular integrity during development remains less explored. Here we identified miRNAs involved in the development and maintenance of vasculature in zebrafish embryos using a reverse genetics approach. Using a combination of bioinformatics predictions and literature based evidences we mined over 701 Human and 329 Zebrafish miRNAs to derive a list of 29 miRNAs targeting vascular specific genes in zebrafish. We shortlisted eight miRNAs and investigated their potential role in regulating vascular development in zebrafish transgenic model. In this screen we identified three miRNAs, namely miR-1, miR-144 and miR-142a-3p that have the potential to influence vascular development in zebrafish. We show that miR-142a-3p mediates vascular integrity and developmental angiogenesis in vivo. Overexpression of miR-142a-3p results in loss of vascular integrity, hemorrhage and vascular remodeling during zebrafish embryonic development, while loss of function of miR-142a-3p causes abnormal vascular remodeling. MiR-142a-3p functions in part by directly repressing cdh5 (VE-cadherin). The vascular abnormalities that results from modulation of miR-142a-3p are reminiscent of cdh5 perturbation in zebrafish embryos. We also demonstrate that the action of miR-142a on cdh5 is potentially regulated by Lmo2, an important transcription factor, known for its role in vasculature development. The miR142a-3p mediated control of cdh5 constitutes an additional layer of regulation for maintaining vascular integrity and developmental angiogenesis. These findings have implications in development, wound repair and tumor growth

3-D density kernel estimation for counting in microscopy image volumes using 3-D image filters and random decision trees

We describe a means through which cells can be accurately counted in 3-D microscopy image data, using only weakly annotated images as input training material. We update an existing 2-D density kernel estimation approach into 3-D and we introduce novel 3-D features which encapsulate the 3-D neighbourhood surrounding each voxel. The proposed 3-D density kernel estimation (DKE-3-D) method, which utilises an ensemble of random decision trees, is computationally efficient and achieves state-of-the-art performance. DKE-3-D avoids the problem of discrete object identification and segmentation, common to many existing 3-D counting techniques, and we show that it outperforms other methods when quantification of densely packed and heterogeneous objects is desired. In this article we successfully apply the technique to two simulated and to two experimentally derived datasets and show that DKE-3-D has great potential in the biomedical sciences and any field where volumetric datasets are used