Variational Markov Chain Monte Carlo for Bayesian smoothing of non-linear niffusions

In this paper we develop set of novel Markov chain Monte Carlo algorithms for Bayesian smoothing of partially observed non-linear diffusion processes. The sampling algorithms developed herein use a deterministic approximation to the posterior distribution over paths as the proposal distribution for a mixture of an independence and a random walk sampler. The approximating distribution is sampled by simulating an optimized time-dependent linear diffusion process derived from the recently developed variational Gaussian process approximation method. Flexible blocking strategies are introduced to further improve mixing, and thus the efficiency, of the sampling algorithms. The algorithms are tested on two diffusion processes: one with double-well potential drift and another with SINE drift. The new algorithm's accuracy and efficiency is compared with state-of-the-art hybrid Monte Carlo based path sampling. It is shown that in practical, finite sample, applications the algorithm is accurate except in the presence of large observation errors and low observation densities, which lead to a multi-modal structure in the posterior distribution over paths. More importantly, the variational approximation assisted sampling algorithm outperforms hybrid Monte Carlo in terms of computational efficiency, except when the diffusion process is densely observed with small errors in which case both algorithms are equally efficient.

Variational Markov chain Monte Carlo for Bayesian smoothing of non-linear diffusions

In this paper we develop set of novel Markov Chain Monte Carlo algorithms for Bayesian smoothing of partially observed non-linear diffusion processes. The sampling algorithms developed herein use a deterministic approximation to the posterior distribution over paths as the proposal distribution for a mixture of an independence and a random walk sampler. The approximating distribution is sampled by simulating an optimized time-dependent linear diffusion process derived from the recently developed variational Gaussian process approximation method. The novel diffusion bridge proposal derived from the variational approximation allows the use of a flexible blocking strategy that further improves mixing, and thus the efficiency, of the sampling algorithms. The algorithms are tested on two diffusion processes: one with double-well potential drift and another with SINE drift. The new algorithm's accuracy and efficiency is compared with state-of-the-art hybrid Monte Carlo based path sampling. It is shown that in practical, finite sample applications the algorithm is accurate except in the presence of large observation errors and low to a multi-modal structure in the posterior distribution over paths. More importantly, the variational approximation assisted sampling algorithm outperforms hybrid Monte Carlo in terms of computational efficiency, except when the diffusion process is densely observed with small errors in which case both algorithms are equally efficient. © 2011 Springer-Verlag.

Using non-homogeneous Poisson models with multiple change-points to estimate the number of ozone exceedances in Mexico City

In this paper, we consider some non-homogeneous Poisson models to estimate the probability that an air quality standard is exceeded a given number of times in a time interval of interest. We assume that the number of exceedances occurs according to a non-homogeneous Poisson process (NHPP). This Poisson process has rate function lambda(t), t >= 0, which depends on some parameters that must be estimated. We take into account two cases of rate functions: the Weibull and the Goel-Okumoto. We consider models with and without change-points. When the presence of change-points is assumed, we may have the presence of either one, two or three change-points, depending of the data set. The parameters of the rate functions are estimated using a Gibbs sampling algorithm. Results are applied to ozone data provided by the Mexico City monitoring network. In a first instance, we assume that there are no change-points present. Depending on the adjustment of the model, we assume the presence of either one, two or three change-points. Copyright (C) 2009 John Wiley & Sons, Ltd.

Non-coding RNAs in schistosomes: an unexplored world

Non-coding RNAs (ncRNAs) were recently given much higher attention due to technical advances in sequencing which expanded the characterization of transcriptomes in different organisms. ncRNAs have different lengths (22 nt to >1, 000 nt) and mechanisms of action that essentially comprise a sophisticated gene expression regulation network. Recent publication of schistosome genomes and transcriptomes has increased the description and characterization of a large number of parasite genes. Here we review the number of predicted genes and the coverage of genomic bases in face of the public ESTs dataset available, including a critical appraisal of the evidence and characterization of ncRNAs in schistosomes. We show expression data for ncRNAs in Schistosoma mansoni. We analyze three different microarray experiment datasets: (1) adult worms' large-scale expression measurements; (2) differentially expressed S. mansoni genes regulated by a human cytokine (TNF-α) in a parasite culture; and (3) a stage-specific expression of ncRNAs. All these data point to ncRNAs involved in different biological processes and physiological responses that suggest functionality of these new players in the parasite's biology. Exploring this world is a challenge for the scientists under a new molecular perspective of host-parasite interactions and parasite development.

Non-coding RNAs: the architects of eukaryotic complexity

Around 98% of all transcriptional output in humans is noncoding RNA. RNA-mediated gene regulation is widespread in higher eukaryotes and complex genetic phenomena like RNA interference, co-suppression, transgene silencing, imprinting, methylation, and possibly position-effect variegation and transvection, all involve intersecting pathways based on or connected to RNA signaling. I suggest that the central dogma is incomplete, and that intronic and other non-coding RNAs have evolved to comprise a second tier of gene expression in eukaryotes, which enables the integration and networking of complex suites of gene activity. Although proteins are the fundamental effectors of cellular function, the basis of eukaryotic complexity and phenotypic variation may lie primarily in a control architecture composed of a highly parallel system of trans-acting RNAs that relay state information required for the coordination and modulation of gene expression, via chromatin remodeling, RNA-DNA, RNA-RNA and RNA-protein interactions. This system has interesting and perhaps informative analogies with small world networks and dataflow computing.

Non-coding RNAs: multi-tasking molecules in the cell

In the last years it has become increasingly clear that the mammalian transcriptome is highly complex and includes a large number of small non-coding RNAs (sncRNAs) and long noncoding RNAs (lncRNAs). Here we review the biogenesis pathways of the three classes of sncRNAs, namely short interfering RNAs (siRNAs), microRNAs (miRNAs) and PIWI-interacting RNAs (piRNAs). These ncRNAs have been extensively studied and are involved in pathways leading to specific gene silencing and the protection of genomes against virus and transposons, for example. Also, lncRNAs have emerged as pivotal molecules for the transcriptional and post-transcriptional regulation of gene expression which is supported by their tissue-specific expression patterns, subcellular distribution, and developmental regulation. Therefore, we also focus our attention on their role in differentiation and development. SncRNAs and lncRNAs play critical roles in defining DNA methylation patterns, as well as chromatin remodeling thus having a substantial effect in epigenetics. The identification of some overlaps in their biogenesis pathways and functional roles raises the hypothesis that these molecules play concerted functions in vivo, creating complex regulatory networks where cooperation with regulatory proteins is necessary. We also highlighted the implications of biogenesis and gene expression deregulation of sncRNAs and lncRNAs in human diseases like cancer.

Emerging roles of non-coding RNAs in pancreatic β-cell function and dysfunction.

Pancreatic β-cells play a central role in glucose homeostasis by tightly regulating insulin release according to the organism's demand. Impairment of β-cell function due to hostile environment, such as hyperglycaemia and hyperlipidaemia, or due to autoimmune destruction of β-cells, results in diabetes onset. Both environmental factors and genetic predisposition are known to be involved in the development of the disease, but the exact mechanisms leading to β-cell dysfunction and death remain to be characterized. Non-coding RNA molecules, such as microRNAs (miRNAs), have been suggested to be necessary for proper β-cell development and function. The present review aims at summarizing the most recent findings about the role of non-coding RNAs in the control of β-cell functions and their involvement in diabetes. We will also provide a perspective view of the future research directions in the field of non-coding RNAs. In particular, we will discuss the implications for diabetes research of the discovery of a new communication mechanism based on cell-to-cell miRNA transfer. Moreover, we will highlight the emerging interconnections between miRNAs and epigenetics and the possible role of long non-coding RNAs in the control of β-cell activities.

BlastR--fast and accurate database searches for non-coding RNAs.

We present and validate BlastR, a method for efficiently and accurately searching non-coding RNAs. Our approach relies on the comparison of di-nucleotides using BlosumR, a new log-odd substitution matrix. In order to use BlosumR for comparison, we recoded RNA sequences into protein-like sequences. We then showed that BlosumR can be used along with the BlastP algorithm in order to search non-coding RNA sequences. Using Rfam as a gold standard, we benchmarked this approach and show BlastR to be more sensitive than BlastN. We also show that BlastR is both faster and more sensitive than BlastP used with a single nucleotide log-odd substitution matrix. BlastR, when used in combination with WU-BlastP, is about 5% more accurate than WU-BlastN and about 50 times slower. The approach shown here is equally effective when combined with the NCBI-Blast package. The software is an open source freeware available from www.tcoffee.org/blastr.html.

Small and long non-coding RNAs in cardiac homeostasis and regeneration

Cardiovascular diseases and in particular heart failure are major causes of morbidity and mortality in the Western world. Recently, the notion of promoting cardiac regeneration as a means to replace lost cardiomyocytes in the damaged heart has engendered considerable research interest. These studies envisage the utilization of both endogenous and exogenous cellular populations, which undergo highly specialized cell fate transitions to promote cardiomyocyte replenishment. Such transitions are under the control of regenerative gene regulatory networks, which are enacted by the integrated execution of specific transcriptional programs. In this context, it is emerging that the non-coding portion of the genome is dynamically transcribed generating thousands of regulatory small and long non-coding RNAs, which are central orchestrators of these networks. In this review, we discuss more particularly the biological roles of two classes of regulatory non-coding RNAs, i.e. microRNAs and long non-coding RNAs, with a particular emphasis on their known and putative roles in cardiac homeostasis and regeneration. Indeed, manipulating non-coding RNA-mediated regulatory networks could provide keys to unlock the dormant potential of the mammalian heart to regenerate. This should ultimately improve the effectiveness of current regenerative strategies and discover new avenues for repair. This article is part of a Special Issue entitled: Cardiomyocyte Biology: Cardiac Pathways of Differentiation, Metabolism and Contraction.

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 clinic.

Involvement of long non-coding RNAs in beta cell failure at the onset of type 1 diabetes in NOD mice.

AIMS/HYPOTHESIS: Exposure of pancreatic beta cells to cytokines released by islet-infiltrating immune cells induces alterations in gene expression, leading to impaired insulin secretion and apoptosis in the initial phases of type 1 diabetes. Long non-coding RNAs (lncRNAs) are a new class of transcripts participating in the development of many diseases. As little is known about their role in insulin-secreting cells, this study aimed to evaluate their contribution to beta cell dysfunction. METHODS: The expression of lncRNAs was determined by microarray in the MIN6 beta cell line exposed to proinflammatory cytokines. The changes induced by cytokines were further assessed by real-time PCR in islets of control and NOD mice. The involvement of selected lncRNAs modified by cytokines was assessed after their overexpression in MIN6 cells and primary islet cells. RESULTS: MIN6 cells were found to express a large number of lncRNAs, many of which were modified by cytokine treatment. The changes in the level of selected lncRNAs were confirmed in mouse islets and an increase in these lncRNAs was also seen in prediabetic NOD mice. Overexpression of these lncRNAs in MIN6 and mouse islet cells, either alone or in combination with cytokines, favoured beta cell apoptosis without affecting insulin production or secretion. Furthermore, overexpression of lncRNA-1 promoted nuclear translocation of nuclear factor of κ light polypeptide gene enhancer in B cells 1 (NF-κB). CONCLUSIONS/INTERPRETATION: Our study shows that lncRNAs are modulated during the development of type 1 diabetes in NOD mice, and that their overexpression sensitises beta cells to apoptosis, probably contributing to their failure during the initial phases of the disease.

Comprehensive Genomic Characterization of Long Non-coding RNAs across Human Cancers.

The discovery of long non-coding RNA (lncRNA) has dramatically altered our understanding of cancer. Here, we describe a comprehensive analysis of lncRNA alterations at transcriptional, genomic, and epigenetic levels in 5,037 human tumor specimens across 13 cancer types from The Cancer Genome Atlas. Our results suggest that the expression and dysregulation of lncRNAs are highly cancer type specific compared with protein-coding genes. Using the integrative data generated by this analysis, we present a clinically guided small interfering RNA screening strategy and a co-expression analysis approach to identify cancer driver lncRNAs and predict their functions. This provides a resource for investigating lncRNAs in cancer and lays the groundwork for the development of new diagnostics and treatments.

Dysregulation of REST-regulated coding and non-coding RNAs in a cellular model of Huntington's disease

Huntingtin (Htt) protein interacts with many transcriptional regulators, with widespread disruption to the transcriptome in Huntington's disease (HD) brought about by altered interactions with the mutant Htt (muHtt) protein. Repressor Element-1 Silencing Transcription Factor (REST) is a repressor whose association with Htt in the cytoplasm is disrupted in HD, leading to increased nuclear REST and concomitant repression of several neuronal-specific genes, including brain-derived neurotrophic factor (Bdnf). Here, we explored a wide set of HD dysregulated genes to identify direct REST targets whose expression is altered in a cellular model of HD but that can be rescued by knock-down of REST activity. We found many direct REST target genes encoding proteins important for nervous system development, including a cohort involved in synaptic transmission, at least two of which can be rescued at the protein level by REST knock-down. We also identified several microRNAs (miRNAs) whose aberrant repression is directly mediated by REST, including miR-137, which has not previously been shown to be a direct REST target in mouse. These data provide evidence of the contribution of inappropriate REST-mediated transcriptional repression to the widespread changes in coding and non-coding gene expression in a cellular model of HD that may affect normal neuronal function and survival.

Expression of Mitochondrial Non-coding RNAs (ncRNAs) Is Modulated by High Risk Human Papillomavirus (HPV) Oncogenes

The study of RNA and DNA oncogenic viruses has proved invaluable in the discovery of key cellular pathways that are rendered dysfunctional during cancer progression. An example is high risk human papillomavirus (HPV), the etiological agent of cervical cancer. The role of HPV oncogenes in cellular immortalization and transformation has been extensively investigated. We reported the differential expression of a family of human mitochondrial non-coding RNAs (ncRNAs) between normal and cancer cells. Normal cells express a sense mitochondrial ncRNA (SncmtRNA) that seems to be required for cell proliferation and two antisense transcripts (ASncmtRNAs). In contrast, the ASncmtRNAs are down-regulated in cancer cells. To shed some light on the mechanisms that trigger down-regulation of the ASncmtRNAs, we studied human keratinocytes (HFK) immortalized with HPV. Here we show that immortalization of HFK with HPV-16 or 18 causes down-regulation of the ASncmtRNAs and induces the expression of a new sense transcript named SncmtRNA-2. Transduction of HFK with both E6 and E7 is sufficient to induce expression of SncmtRNA-2. Moreover, E2 oncogene is involved in down-regulation of the ASncmtRNAs. Knockdown of E2 in immortalized cells reestablishes in a reversible manner the expression of the ASncmtRNAs, suggesting that endogenous cellular factors(s) could play functions analogous to E2 during non-HPV-induced oncogenesis.