Computational analysis of microRNAs in biomedicine

All genetic information necessary for creating and maintaining life is stored in DNA and RNA molecules. Gene expression is the process by which sets of DNA (i.e. genes) are encoded into functional gene products. Thus, the state and function of a single cell can be determined by the amount and type of genes expressed: tumour cells can be detected from normal cells, and one functional brain region can be differentiated from another. The discovery of non-coding RNAs like microRNAs (miRNAs) introduced a sophisticated level of gene regulation to our understanding of the flow of genetic information. Strong evidence suggest miRNAs have vital roles in mediating a wide range of biological pathways essential to cell maintenance and tissue-specific function. In complex diseases such as cancer, they show particular promise as candidate biomarkers in prognosis, diagnosis, and treatment. However, we are still uncertain about the precise mechanisms and contributions of miRNAs in regulating gene expression. High-throughput technologies generate molecular data of unprecedented size and depth, providing unique opportunities to study small RNA molecules and complex diseases. Despite exact regulatory mechanisms being uncertain, miRNAs are functionally characterized with high-throughput expression data and the biological pathways annotated to their putative target genes. However, the sheer size of the data generated and to be processed raises challenges in computational resources and in discovering clinically relevant information. This work addresses these challenges with the development and application of two computational tools to better facilitate miRNA research. SePIA is a high-throughput workflow to reliably process sequencing data and perform expression analysis to identify strongly-related miRNAs and their predicted target genes. Director is a visualization package to further the interpretation of molecular interactions and depict the co-regulatory behaviour of miRNAs. The usefulness of these tools is shown in the application of two biomedical studies: in differentiating brain tissue phenotypes, and in determining a role in the chemosensitivity of diffuse large B-cell lymphoma. Sufficient biological context is drawn from the computational results generated by the tools to hypothesize and experimentally validate the role of miRNAs, and propose a set as candidate biomarkers and targets for drug therapy. SePIA and Director are readily available tools developed to improve and make more convenient the computational analysis of miRNAs in biomedical research

SePIA: RNA and small RNA sequence processing, integration, and analysis

Abstract Background Large-scale sequencing experiments are complex and require a wide spectrum of computational tools to extract and interpret relevant biological information. This is especially true in projects where individual processing and integrated analysis of both small RNA and complementary RNA data is needed. Such studies would benefit from a computational workflow that is easy to implement and standardizes the processing and analysis of both sequenced data types. Results We developed SePIA (Sequence Processing, Integration, and Analysis), a comprehensive small RNA and RNA workflow. It provides ready execution for over 20 commonly known RNA-seq tools on top of an established workflow engine and provides dynamic pipeline architecture to manage, individually analyze, and integrate both small RNA and RNA data. Implementation with Docker makes SePIA portable and easy to run. We demonstrate the workflow’s extensive utility with two case studies involving three breast cancer datasets. SePIA is straightforward to configure and organizes results into a perusable HTML report. Furthermore, the underlying pipeline engine supports computational resource management for optimal performance. Conclusion SePIA is an open-source workflow introducing standardized processing and analysis of RNA and small RNA data. SePIA’s modular design enables robust customization to a given experiment while maintaining overall workflow structure. It is available at http://anduril.org/sepia

SePIA : RNA and small RNA sequence processing, integration, and analysis

Background: Large-scale sequencing experiments are complex and require a wide spectrum of computational tools to extract and interpret relevant biological information. This is especially true in projects where individual processing and integrated analysis of both small RNA and complementary RNA data is needed. Such studies would benefit from a computational workflow that is easy to implement and standardizes the processing and analysis of both sequenced data types. Results: We developed SePIA (Sequence Processing, Integration, and Analysis), a comprehensive small RNA and RNA workflow. It provides ready execution for over 20 commonly known RNA-seq tools on top of an established workflow engine and provides dynamic pipeline architecture to manage, individually analyze, and integrate both small RNA and RNA data. Implementation with Docker makes SePIA portable and easy to run. We demonstrate the workflow's extensive utility with two case studies involving three breast cancer datasets. SePIA is straightforward to configure and organizes results into a perusable HTML report. Furthermore, the underlying pipeline engine supports computational resource management for optimal performance. Conclusion: SePIA is an open-source workflow introducing standardized processing and analysis of RNA and small RNA data. SePIA's modular design enables robust customization to a given experiment while maintaining overall workflow structure.Peer reviewe

Reply to : Proofreading deficiency in mitochondrial DNA polymerase does not affect total dNTP pools in mouse embryos

Non peer reviewe

MicroRNA Expression Profiling Reveals MiRNA Families Regulating Specific Biological Pathways in Mouse Frontal Cortex and Hippocampus

Peer reviewe

MicroRNAs regulate key cell survival pathways and mediate chemosensitivity during progression of diffuse large B- cell lymphoma

Despite better therapeutic options and improved survival of diffuse large B-cell lymphoma (DLBCL), 30-40% of the patients experience relapse or have primary refractory disease with a dismal prognosis. To identify biological correlates for treatment resistance, we profiled microRNAs (miRNAs) of matched primary and relapsed DLBCL by next-generation sequencing. Altogether 492 miRNAs were expressed in the DLBCL samples. Thirteen miRNAs showed significant differential expression between primary and relapse specimen pairs. Integration of the differentially expressed miRNAs with matched mRNA expression profiles identified highly anti-correlated, putative targets, which were significantly enriched in cancer-associated pathways, including phosphatidylinositol (PI)), mitogen-activated protein kinase (MAPK), and B-cell receptor (BCR) signaling. Expression data suggested activation of these pathways during disease progression, and functional analyses validated that miR-370-3p, miR-381-3p, and miR-409-3p downregulate genes on the PI, MAPK, and BCR signaling pathways, and enhance chemosensitivity of DLBCL cells in vitro. High expression of selected target genes, that is, PIP5K1 and IMPA1, was found to be associated with poor survival in two independent cohorts of chemoimmunotherapy-treated patients (n = 92 and n = 233). Taken together, our results demonstrate that differentially expressed miRNAs contribute to disease progression by regulating key cell survival pathways and by mediating chemosensitivity, thus representing potential novel therapeutic targets.Peer reviewe

Lymphatic endothelium stimulates melanoma metastasis and invasion via MMP14-dependent Notch3 and beta 1-integrin activation

Lymphatic invasion and lymph node metastasis correlate with poor clinical outcome in melanoma. However, the mechanisms of lymphatic dissemination in distant metastasis remain incompletely understood. We show here that exposure of expansively growing human WM852 melanoma cells, but not singly invasive Bowes cells, to lymphatic endothelial cells (LEC) in 3D co-culture facilitates melanoma distant organ metastasis in mice. To dissect the underlying molecular mechanisms, we established LEC co-cultures with different melanoma cells originating from primary tumors or metastases. Notably, the expansively growing metastatic melanoma cells adopted an invasively sprouting phenotype in 3D matrix that was dependent on MMP14, Notch3 and beta 1-integrin. Unexpectedly, MMP14 was necessary for LEC-induced Notch3 induction and coincident beta 1-integrin activation. Moreover, MMP14 and Notch3 were required for LEC-mediated metastasis of zebrafish xenografts. This study uncovers a unique mechanism whereby LEC contact promotes melanoma metastasis by inducing a reversible switch from 3D growth to invasively sprouting cell phenotype.Peer reviewe

Selective MicroRNA-Offset RNA Expression in Human Embryonic Stem Cells

Small RNA molecules, including microRNAs (miRNAs), play critical roles in regulating pluri-potency, proliferation and differentiation of embryonic stem cells. miRNA-offset RNAs (moRNAs) are similar in length to miRNAs, align to miRNA precursor (pre-miRNA) loci and are therefore believed to derive from processing of the pre-miRNA hairpin sequence. Recent next generation sequencing (NGS) studies have reported the presence of moRNAs in human neurons and cancer cells and in several tissues in mouse, including pluripotent stem cells. In order to gain additional knowledge about human moRNAs and their putative development-related expression, we applied NGS of small RNAs in human embryonic stem cells (hESCs) and fibroblasts. We found that certain moRNA isoforms are notably expressed in hESCs from loci coding for stem cell-selective or cancer-related miRNA clusters. In contrast, we observed only sparse moRNAs in fibroblasts. Consistent with earlier findings, most of the observed moRNAs derived from conserved loci and their expression did not appear to correlate with the expression of the adjacent miRNAs. We provide here the first report of moRNAs in hESCs, and their expression profile in comparison to fibroblasts. Moreover, we expand the repertoire of hESC miRNAs. These findings provide an expansion on the known repertoire of small non-coding RNA contents in hESCs.Peer reviewe

Lymphatic endothelium stimulates melanoma metastasis and invasion via MMP14-dependent Notch3 and beta 1-integrin activation

Lymphatic invasion and lymph node metastasis correlate with poor clinical outcome in melanoma. However, the mechanisms of lymphatic dissemination in distant metastasis remain incompletely understood. We show here that exposure of expansively growing human WM852 melanoma cells, but not singly invasive Bowes cells, to lymphatic endothelial cells (LEC) in 3D co-culture facilitates melanoma distant organ metastasis in mice. To dissect the underlying molecular mechanisms, we established LEC co-cultures with different melanoma cells originating from primary tumors or metastases. Notably, the expansively growing metastatic melanoma cells adopted an invasively sprouting phenotype in 3D matrix that was dependent on MMP14, Notch3 and beta 1-integrin. Unexpectedly, MMP14 was necessary for LEC-induced Notch3 induction and coincident beta 1-integrin activation. Moreover, MMP14 and Notch3 were required for LEC-mediated metastasis of zebrafish xenografts. This study uncovers a unique mechanism whereby LEC contact promotes melanoma metastasis by inducing a reversible switch from 3D growth to invasively sprouting cell phenotype