From SNPs to pathways: integration of functional effect of sequence variations on models of cell signalling pathways

Background: Single nucleotide polymorphisms (SNPs) are the most frequent type of sequence variation between individuals, and represent a promising tool for finding genetic determinants of complex diseases and understanding the differences in drug response. In this regard, it is of particular interest to study the effect of non-synonymous SNPs in the context of biological networks such as cell signalling pathways. UniProt provides curated information about the functional and phenotypic effects of sequence variation, including SNPs, as well as on mutations of protein sequences. However, no strategy has been developed to integrate this information with biological networks, with the ultimate goal of studying the impact of the functional effect of SNPs in the structure and dynamics of biological networks. Results: First, we identified the different challenges posed by the integration of the phenotypic effect of sequence variants and mutations with biological networks. Second, we developed a strategy for the combination of data extracted from public resources, such as UniProt, NCBI dbSNP, Reactome and BioModels. We generated attribute files containing phenotypic and genotypic annotations to the nodes of biological networks, which can be imported into network visualization tools such as Cytoscape. These resources allow the mapping and visualization of mutations and natural variations of human proteins and their phenotypic effect on biological networks (e.g. signalling pathways, protein-protein interaction networks, dynamic models). Finally, an example on the use of the sequence variation data in the dynamics of a network model is presented. Conclusion: In this paper we present a general strategy for the integration of pathway and sequence variation data for visualization, analysis and modelling purposes, including the study of the functional impact of protein sequence variations on the dynamics of signalling pathways. This is of particular interest when the SNP or mutation is known to be associated to disease. We expect that this approach will help in the study of the functional impact of disease-associated SNPs on the behaviour of cell signalling pathways, which ultimately will lead to a better understanding of the mechanisms underlying complex diseases.

Structural and functional properties of genes involved in human cancer

Background: One of the main goals of cancer genetics is to identify the causative elements at the molecular level leading to cancer.Results: We have conducted an analysis of a set of genes known to be involved in cancer in order to unveil their unique features that can assist towards the identification of new candidate cancer genes. Conclusion: We have detected key patterns in this group of genes in terms of the molecular function or the biological process in which they are involved as well as sequence properties. Based on these features we have developed an accurate Bayesian classification model with which human genes have been scored for their likelihood of involvement in cancer.

Optimum power allocation for parallel Gaussian channels with arbitrary input distributions

The mutual information of independent parallel Gaussian-noise channels is maximized, under an average power constraint, by independent Gaussian inputs whose power is allocated according to the waterfilling policy. In practice, discrete signalling constellations with limited peak-to-average ratios (m-PSK, m-QAM, etc) are used in lieu of the ideal Gaussian signals. This paper gives the power allocation policy that maximizes the mutual information over parallel channels with arbitrary input distributions. Such policy admits a graphical interpretation, referred to as mercury/waterfilling, which generalizes the waterfilling solution and allows retaining some of its intuition. The relationship between mutual information of Gaussian channels and nonlinear minimum mean-square error proves key to solving the power allocation problem.

Capacity-achieving input covariance for single-user multi-antenna channels

We characterize the capacity-achieving input covariance for multi-antenna channels known instantaneously at the receiver and in distribution at the transmitter. Our characterization, valid for arbitrary numbers of antennas, encompasses both the eigenvectors and the eigenvalues. The eigenvectors are found for zero-mean channels with arbitrary fading profiles and a wide range of correlation and keyhole structures. For the eigenvalues, in turn, we present necessary and sufficient conditions as well as an iterative algorithm that exhibits remarkable properties: universal applicability, robustness and rapid convergence. In addition, we identify channel structures for which an isotropic input achieves capacity.

Asymmetry of Functional Connectivity in Schizophrenia at Different Spatial Scales

Introduction: The interhemispheric asymmetries that originate from connectivity-related structuring of the cerebral cortex are compromised in schizophrenia (SZ). Recently, we have revealed the whole-head topography of EEG synchronization in SZ (Jalili et al. 2007; Knyazeva et al. 2008). Here we extended the analysis to assess the abnormality in the asymmetry of synchronization, which is further motivated by the evidence that the interhemispheric asymmetries suspected to be abnormal in SZ originate from the connectivity-related structuring of the cortex. Methods: Thirteen right-handed SZ patients and thirteen matched controls, participated in this study and the multichannel (128) EEGs were recorded for 3-5 minutes at rest. Then, Laplacian EEG (LEEG) were calculated using a 2-D spline. The LEEGs were analysis through calculating the power spectral density using Welch's average periodogram method. Furthermore, using a state-space based multivariate synchronization measure, S-estimator, we analyzed the correlate of the functional cortico-cortical connectivity in SZ patients compared to the controls. The values of S-estimator were obtained at three different special scales: first-order neighbors for each sensor location, second-order neighbors, and the whole hemisphere. The synchronization measures based on LEEG of alpha and beta bands were applied and tuned to various spatial scales including local, intraregional, and long-distance levels. To assess the between-group differences, we used a permutation version of Hotelling's T2 test. For correlation analysis, Spearman Rank Correlation was calculated. Results: Compared to the controls, who had rightward asymmetry at a local level (LEEG power), rightward anterior and leftward posterior asymmetries at an intraregional level (first- and second-order S-estimator), and rightward global asymmetry (hemispheric S-estimator), SZ patients showed generally attenuated asymmetry, the effect being strongest for intraregional synchronization. This deviation in asymmetry across the anterior-to-posterior axis is consistent with the cerebral form of the so-called Yakovlevian or anticlockwise cerebral torque. Moreover, the negative occipital and positive frontal asymmetry values suggest higher regional synchronization among the left occipital and the right frontal locations relative to their symmetrical counterparts. Correlation analysis linked the posterior intraregional and hemispheric abnormalities to the negative SZ symptoms, whereas the asymmetry of LEEG power appeared to be weakly coupled to clinical ratings. The posterior intraregional abnormalities of asymmetry were shown to increase with the duration of the disease. The tentative links between these findings and gross anatomical asymmetries, including the cerebral torque and gyrification pattern in normal subjects and SZ patients, are discussed. Conclusions: Overall, our findings reveal the abnormalities in the synchronization asymmetry in SZ patients and heavy involvement of the right hemisphere in these abnormalities. These results indicate that anomalous asymmetry of cortico-cortical connections in schizophrenia is amenable to electrophysiological analysis.

Sequential estimation of time-varying multipath channel for MIMO-OFDM systems

In this paper, we introduce a pilot-aided multipath channel estimator for Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems. Typical estimation algorithms assume the number of multipath components and delays to be known and constant, while theiramplitudes may vary in time. In this work, we focus on the more realistic assumption that also the number of channel taps is unknown and time-varying. The estimation problem arising from this assumption is solved using Random Set Theory (RST), which is a probability theory of finite sets. Due to the lack of a closed form of the optimal filter, a Rao-Blackwellized Particle Filter (RBPF) implementation of the channel estimator is derived. Simulation results demonstrate the estimator effectiveness.

Large-system analysis of a CDMA dynamic channel under a Markovian input process

We study the minimum mean square error (MMSE) and the multiuser efficiency η of large dynamic multiple access communication systems in which optimal multiuser detection is performed at the receiver as the number and the identities of active users is allowed to change at each transmission time. The system dynamics are ruled by a Markov model describing the evolution of the channel occupancy and a large-system analysis is performed when the number of observations grow large. Starting on the equivalent scalar channel and the fixed-point equation tying multiuser efficiency and MMSE, we extend it to the case of a dynamic channel, and derive lower and upper bounds for the MMSE (and, thus, for η as well) holding true in the limit of large signal–to–noise ratios and increasingly large observation time T.

Multiuser detection with an unknown number of active users: receiver design

In multiuser detection, the set of users active at any time may be unknown to the receiver. In these conditions, optimum reception consists of detecting simultaneously the set of activeusers and their data, problem that can be solved exactly by applying random-set theory (RST) and Bayesian recursions (BR). However, implementation of optimum receivers may be limited by their complexity, which grows exponentially with the number of potential users. In this paper we examine three strategies leading to reduced-complexity receivers.In particular, we show how a simple approximation of BRs enables the use of Sphere Detection (SD) algorithm, whichexhibits satisfactory performance with limited complexity.

Asymptotic capacity of static multiuser channels with an unknown number of users

We examine a multiple-access communication system in which multiuser detection is performed without knowledge of the number of active interferers. Using a statistical-physics approach, we compute the single-user channel capacity and spectral efficiency in the large-system limit.

Functional chromatin features are associated with structural mutations in cancer.

BACKGROUND: Structural mutations (SMs) play a major role in cancer development. In some cancers, such as breast and ovarian, DNA double-strand breaks (DSBs) occur more frequently in transcribed regions, while in other cancer types such as prostate, there is a consistent depletion of breakpoints in transcribed regions. Despite such regularity, little is understood about the mechanisms driving these effects. A few works have suggested that protein binding may be relevant, e.g. in studies of androgen receptor binding and active chromatin in specific cell types. We hypothesized that this behavior might be general, i.e. that correlation between protein-DNA binding (and open chromatin) and breakpoint locations is common across divergent cancers. RESULTS: We investigated this hypothesis by comprehensively analyzing the relationship among 457 ENCODE protein binding ChIP-seq experiments, 125 DnaseI and 24 FAIRE experiments, and 14,600 SMs from 8 diverse cancer datasets covering 147 samples. In most cancers, including breast and ovarian, we found enrichment of protein binding and open chromatin in the vicinity of SM breakpoints at distances up to 200 kb. Furthermore, for all cancer types we observed an enhanced enrichment in regions distant from genes when compared to regions proximal to genes, suggesting that the SM-induction mechanism is independent from the bias of DSBs to occur near transcribed regions. We also observed a stronger effect for sites with more than one protein bound. CONCLUSIONS: Protein binding and open chromatin state are associated with nearby SM breakpoints in many cancer datasets. These observations suggest a consistent mechanism underlying SM locations across different cancers.

Functional architecture of olfactory ionotropic glutamate receptors.

Ionotropic glutamate receptors (iGluRs) are ligand-gated ion channels that mediate chemical communication between neurons at synapses. A variant iGluR subfamily, the Ionotropic Receptors (IRs), was recently proposed to detect environmental volatile chemicals in olfactory cilia. Here, we elucidate how these peripheral chemosensors have evolved mechanistically from their iGluR ancestors. Using a Drosophila model, we demonstrate that IRs act in combinations of up to three subunits, comprising individual odor-specific receptors and one or two broadly expressed coreceptors. Heteromeric IR complex formation is necessary and sufficient for trafficking to cilia and mediating odor-evoked electrophysiological responses in vivo and in vitro. IRs display heterogeneous ion conduction specificities related to their variable pore sequences, and divergent ligand-binding domains function in odor recognition and cilia localization. Our results provide insights into the conserved and distinct architecture of these olfactory and synaptic ion channels and offer perspectives into the use of IRs as genetically encoded chemical sensors. VIDEO ABSTRACT:

Transcriptional and functional profiles of voltage-gated Na(+) channels in injured and non-injured DRG neurons in the SNI model of neuropathic pain.

Changes in expression and function of voltage-gated sodium channels (VGSC) in dorsal root ganglion (DRG) neurons may play a major role in the genesis of peripheral hyperexcitability that occurs in neuropathic pain. We present here the first description of changes induced by spared nerve injury (SNI) to Na(v)1 mRNA levels and tetrodotoxin-sensitive and -resistant (TTX-S/TTX-R) Na(+) currents in injured and adjacent non-injured small DRG neurons. VGSC transcripts were down-regulated in injured neurons except for Na(v)1.3, which increased, while they were either unchanged or increased in non-injured neurons. TTX-R current densities were reduced in injured neurons and the voltage dependence of steady-state inactivation for TTX-R was positively shifted in injured and non-injured neurons. TTX-S current densities were not affected by SNI, while the rate of recovery from inactivation was accelerated in injured neurons. Our results describe altered neuronal electrogenesis following SNI that is likely induced by a complex regulation of VGSCs.

Diagnosis of muscular dystrophies at the nanometer scale

The diagnosis of muscular dystrophies or the assessment of the functional benefit of gene or cell therapies can be difficult, especially for poorly accessible muscles, and it often lacks a singlefiber resolution. In the present study, we evaluated whether muscle diseases can be diagnosed from small biopsies using atomic force microscopy (AFM). AFM was shown to provide a sensitive and quantitative description of the resistance of normal and dystrophic myofibers within live muscle tissues explanted from Duchenne mdx mice. The rescue of dystrophin expression by gene therapy approaches led to the functional recovery of treated dystrophic muscle fibers, as probed using AFM and by in situ wholemuscle strength measurements. Comparison of muscles treated with viral or non-viral vectors indicated that the efficacy of the gene transfer approaches could be distinguished with a single myofiber resolution. This indicated full correction of the resistance to deformation in nearly all of the muscle fibers treated with an adeno-associated viral vector that mediates exon-skipping on the dystrophin mRNA. Having shown that AFM can provide a quantitative assessment of the expression of muscle proteins and of the muscular function in animal models, we assessed myofiber resistance in the context of human muscular dystrophies and myopathies. Thus, various forms of human Becker syndrome can also be detected using AFM in blind studies of small frozen biopsies from human patients. Interestingly, it also allowed the detection of anomalies in a fraction of the muscle fibers from patients showing a muscle weakness that could not be attributed to a known molecular or genetic defect. Overall, we conclude that AFM may provide a useful method to complement current diagnosis tools of known and unknown muscular diseases, in research and in a clinical context.

Interaction of GAG trinucleotide repeat and C-129T polymorphisms impairs expression of the glutamate-cysteine ligase catalytic subunit gene.

Glutamate cysteine ligase (GCL) catalyzes the rate-limiting step in the de novo synthesis of glutathione (GSH). The catalytic subunit (GCLC) of GCL contains a GAG trinucleotide-repeat (TNR) polymorphism within the 5'-untranslated region (5'-UTR) that has been associated with various human disorders. Although several studies suggest that this variation influences GSH content, its implication for GCLC expression remains unknown. To better characterize its functional significance, we performed reporter gene assays with constructs containing the complete GCLC 5'-UTR upstream of a luciferase gene. Transfection of these vectors into various human cell lines did not reveal any significant differences between 7, 8, 9, or 10 GAG repeats, under either basal or oxidative stress conditions. To correlate these results with the previously described down-regulation induced by the C-129T GCLC promoter polymorphism, combinations of both variations were tested. Interestingly, the -129T allele down-regulates gene expression when combined with 7 GAG but not with 8, 9, or 10 GAG TNRs. This observation was confirmed in primary fibroblast cells, in which the combination of GAG TNR 7/7 and -129C/T genotypes decreased the GCLC protein level. These results provide evidence that interaction of the two variations can efficiently impair GCLC expression and thus suggest its involvement in the pathogenesis of diseases related to GSH metabolism.