Identification of long non-coding RNAs involved in neuronal development and intellectual disability

Recently, exome sequencing led to the identification of causal mutations in 16–31% of patients with intellectual disability (ID), leaving the underlying cause for many patients unidentified. In this context, the noncoding part of the human genome remains largely unexplored. For many long non-coding RNAs (lncRNAs) a crucial role in neurodevelopment and hence the human brain is anticipated. Here we aimed at identifying lncRNAs associated with neuronal development and ID. Therefore, we applied an integrated genomics approach, harnessing several public epigenetic datasets. We found that the presence of neuron-specific H3K4me3 confers the highest specificity for genes involved in neurodevelopment and ID. Based on the presence of this feature and GWAS hits for CNS disorders, we identified 53 candidate lncRNA genes. Extensive expression profiling on human brain samples and other tissues, followed by Gene Set Enrichment Analysis indicates that at least 24 of these lncRNAs are indeed implicated in processes such as synaptic transmission, nervous system development and neurogenesis. The bidirectional or antisense overlapping orientation relative to multiple coding genes involved in neuronal processes supports these results. In conclusion, we identified several lncRNA genes putatively involved in neurodevelopment and CNS disorders, providing a resource for functional studies

Network-based approaches to explore complex biological systems towards network medicine

Network medicine relies on different types of networks: from the molecular level of protein–protein interactions to gene regulatory network and correlation studies of gene expression. Among network approaches based on the analysis of the topological properties of protein–protein interaction (PPI) networks, we discuss the widespread DIAMOnD (disease module detection) algorithm. Starting from the assumption that PPI networks can be viewed as maps where diseases can be identified with localized perturbation within a specific neighborhood (i.e., disease modules), DIAMOnD performs a systematic analysis of the human PPI network to uncover new disease-associated genes by exploiting the connectivity significance instead of connection density. The past few years have witnessed the increasing interest in understanding the molecular mechanism of post-transcriptional regulation with a special emphasis on non-coding RNAs since they are emerging as key regulators of many cellular processes in both physiological and pathological states. Recent findings show that coding genes are not the only targets that microRNAs interact with. In fact, there is a pool of different RNAs—including long non-coding RNAs (lncRNAs) —competing with each other to attract microRNAs for interactions, thus acting as competing endogenous RNAs (ceRNAs). The framework of regulatory networks provides a powerful tool to gather new insights into ceRNA regulatory mechanisms. Here, we describe a data-driven model recently developed to explore the lncRNA-associated ceRNA activity in breast invasive carcinoma. On the other hand, a very promising example of the co-expression network is the one implemented by the software SWIM (switch miner), which combines topological properties of correlation networks with gene expression data in order to identify a small pool of genes—called switch genes—critically associated with drastic changes in cell phenotype. Here, we describe SWIM tool along with its applications to cancer research and compare its predictions with DIAMOnD disease genes

Systems biology in inflammatory bowel diseases

Purpose of review: Ulcerative colitis (UC) and Crohn’s Disease (CD) are the two predominant types of inflammatory bowel disease (IBD), affecting over 1.4 million individuals in the US. IBD results from complex interactions between pathogenic components, including genetic and epigenetic factors, the immune response and the microbiome through an unknown sequence of events. The purpose of this review is to describe a system biology approach to IBD as a novel and exciting methodology aiming at developing novel IBD therapeutics based on the integration of molecular and cellular "omics" data. Recent Findings: Recent evidence suggested the presence of genetic, epigenetic, transcriptomic, proteomic and metabolomic alterations in IBD patients. Furthermore, several studies have shown that different cell types, including fibroblasts, epithelial, immune and endothelial cells together with the intestinal microbiota are involved in IBD pathogenesis. Novel computational methodologies have been developed aiming to integrate high - throughput molecular data. Summary: A systems biology approach could potentially identify the central regulators (hubs) in the IBD interactome and improve our understanding of the molecular mechanisms involved in IBD pathogenesis. The future IBD therapeutics should be developed on the basis of targeting the central hubs in the IBD network

Bio-Communication of Bacteria and its Evolutionary Interrelations to Natural Genome Editing Competences of Viruses

Communicative competences enable bacteria to develop, organise and coordinate rich social life with a great variety of behavioral patterns even in which they organise themselves like multicellular organisms. They have existed for almost four billion years and still survive, being part of the most dramatic changes in evolutionary history such as DNA invention, cellular life, invention of nearly all protein types, partial constitution of eukaryotic cells, vertical colonisation of all eukaryotes, high adaptability through horizontal gene transfer and co-operative multispecies colonisation of all ecological niches. Recent research demonstrates that these bacterial competences derive from the aptitude of viruses for natural genome editing. 
	In contrast to a book which would be the appropriate space to outline in depth all communicative pathways inherent in bacterial life in this current article I want to give an overview for a broader readership over the great variety of bacterial bio-communication: In a first step I describe how they interpret and coordinate, what semiochemical vocabulary they share and which goals they try to reach. In a second stage I describe the main categories of sign-mediated interactions between bacterial and non-bacterial organisms, and between bacteria of the same or related species. In a third stage I will focus on the relationship between bacteria and their obligate settlers, i.e. viruses. We will see that bacteria are important hosts for multiviral colonisation and virally-determined order of nucleic acid sequences.

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What is Life?

In searching for life in extraterrestrial space, it is essential to act based on an unequivocal definition of life. In the twentieth century, life was defined as cells that self-replicate, metabolize, and are open for mutations, without which genetic information would remain unchangeable, and evolution would be impossible. Current definitions of life derive from statistical mechanics, physics, and chemistry of the twentieth century in which life is considered to function machine like, ignoring a central role of communication. Recent observations show that context-dependent meaningful communication and network formation (and control) are central to all life forms. Evolutionary relevant new nucleotide sequences now appear to have originated from social agents such as viruses, their parasitic relatives, and related RNA networks, not from errors. By applying the known features of natural languages and communication, a new twenty-first century definition of life can be reached in which communicative interactions are central to all processes of life. A new definition of life must integrate the current empirical knowledge about interactions between cells, viruses, and RNA networks to provide a better explanatory power than the twentieth century narrative

Genome-wide profiling of the cardiac transcriptome after myocardial infarction identifies novel heart-specific long non-coding RNAs

Aim Heart disease is recognized as a consequence of dysregulation of cardiac gene regulatory networks. Previously, unappreciated components of such networks are the long non-coding RNAs (lncRNAs). Their roles in the heart remain to be elucidated. Thus, this study aimed to systematically characterize the cardiac long non-coding transcriptome post-myocardial infarction and to elucidate their potential roles in cardiac homoeostasis. Methods and results We annotated the mouse transcriptome after myocardial infarction via RNA sequencing and ab initio transcript reconstruction, and integrated genome-wide approaches to associate specific lncRNAs with developmental processes and physiological parameters. Expression of specific lncRNAs strongly correlated with defined parameters of cardiac dimensions and function. Using chromatin maps to infer lncRNA function, we identified many with potential roles in cardiogenesis and pathological remodelling. The vast majority was associated with active cardiac-specific enhancers. Importantly, oligonucleotide-mediated knockdown implicated novel lncRNAs in controlling expression of key regulatory proteins involved in cardiogenesis. Finally, we identified hundreds of human orthologues and demonstrate that particular candidates were differentially modulated in human heart disease. Conclusion These findings reveal hundreds of novel heart-specific lncRNAs with unique regulatory and functional characteristics relevant to maladaptive remodelling, cardiac function and possibly cardiac regeneration. This new class of molecules represents potential therapeutic targets for cardiac disease. Furthermore, their exquisite correlation with cardiac physiology renders them attractive candidate biomarkers to be used in the clini

RNA-based regulation: dynamics and response to perturbations of competing RNAs

The observation that, through a titration mechanism, microRNAs (miRNAs) can act as mediators of effective interactions among their common targets (competing endogenous RNAs or ceRNAs) has brought forward the idea ('ceRNA hypothesis') that RNAs can regulate each other in extended 'cross-talk' networks. Such an ability might play a major role in post-transcriptional regulation (PTR) in shaping a cell's protein repertoire. Recent work focusing on the emergent properties of the cross-talk networks has emphasized the high flexibility and selectivity that may be achieved at stationarity. On the other hand, dynamical aspects, possibly crucial on the relevant time scales, are far less clear. We have carried out a dynamical study of the ceRNA hypothesis on a model of PTR. Sensitivity analysis shows that ceRNA cross-talk is dynamically extended, i.e. it may take place on time scales shorter than those required to achieve stationairity even in cases where no cross-talk occurs in the steady state, and is possibly amplified. Besides, in case of large, transfection-like perturbations the system may develop strongly non-linear, threshold response. Finally, we show that the ceRNA effect provides a very efficient way for a cell to achieve fast positive shifts in the level of a ceRNA when necessary. These results indicate that competition for miRNAs may indeed provide an elementary mechanism to achieve system-level regulatory effects on the transcriptome over physiologically relevant time scales.Comment: Main text: 10 pages, 13 figures. Supporting Text: 3 pages, 6 figure

A Path to Implement Precision Child Health Cardiovascular Medicine.

Congenital heart defects (CHDs) affect approximately 1% of live births and are a major source of childhood morbidity and mortality even in countries with advanced healthcare systems. Along with phenotypic heterogeneity, the underlying etiology of CHDs is multifactorial, involving genetic, epigenetic, and/or environmental contributors. Clear dissection of the underlying mechanism is a powerful step to establish individualized therapies. However, the majority of CHDs are yet to be clearly diagnosed for the underlying genetic and environmental factors, and even less with effective therapies. Although the survival rate for CHDs is steadily improving, there is still a significant unmet need for refining diagnostic precision and establishing targeted therapies to optimize life quality and to minimize future complications. In particular, proper identification of disease associated genetic variants in humans has been challenging, and this greatly impedes our ability to delineate gene-environment interactions that contribute to the pathogenesis of CHDs. Implementing a systematic multileveled approach can establish a continuum from phenotypic characterization in the clinic to molecular dissection using combined next-generation sequencing platforms and validation studies in suitable models at the bench. Key elements necessary to advance the field are: first, proper delineation of the phenotypic spectrum of CHDs; second, defining the molecular genotype/phenotype by combining whole-exome sequencing and transcriptome analysis; third, integration of phenotypic, genotypic, and molecular datasets to identify molecular network contributing to CHDs; fourth, generation of relevant disease models and multileveled experimental investigations. In order to achieve all these goals, access to high-quality biological specimens from well-defined patient cohorts is a crucial step. Therefore, establishing a CHD BioCore is an essential infrastructure and a critical step on the path toward precision child health cardiovascular medicine

Artificial and Natural Genetic Information Processing

Conventional methods of genetic engineering and more recent genome editing techniques focus on identifying genetic target sequences for manipulation. This is a result of historical concept of the gene which was also the main assumption of the ENCODE project designed to identify all functional elements in the human genome sequence. However, the theoretical core concept changed dramatically. The old concept of genetic sequences which can be assembled and manipulated like molecular bricks has problems in explaining the natural genome-editing competences of viruses and RNA consortia that are able to insert or delete, combine and recombine genetic sequences more precisely than random-like into cellular host organisms according to adaptational needs or even generate sequences de novo. Increasing knowledge about natural genome editing questions the traditional narrative of mutations (error replications) as essential for generating genetic diversity and genetic content arrangements in biological systems. This may have far-reaching consequences for our understanding of artificial genome editing