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Stochastic gene

Liliana Ironi, Ettore Lanzarone
Computational and mathematical models have significantly contributed to the rapid progress in the study of gene regulatory networks (GRN), but researchers still lack a reliable model-based framework for computer-aided analysis and design. Such tool should both reveal the relation between network structure and dynamics and find parameter values and/or constraints that enable the simulated dynamics to reproduce specific behaviors. This paper addresses these issues and proposes a computational framework that facilitates network analysis or design...
June 19, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Liang He, Ilya Zhbannikov, Konstantin G Arbeev, Anatoliy I Yashin, Alexander M Kulminski
Unraveling the underlying biological mechanisms or pathways behind the effects of genetic variations on complex diseases remains one of the major challenges in the post-GWAS (where GWAS is genome-wide association study) era. To further explore the relationship between genetic variations, biomarkers, and diseases for elucidating underlying pathological mechanism, a huge effort has been placed on examining pleiotropic and gene-environmental interaction effects. We propose a novel genetic stochastic process model (GSPM) that can be applied to GWAS and jointly investigate the genetic effects on longitudinally measured biomarkers and risks of diseases...
June 21, 2017: Genetic Epidemiology
Zuzanna Szymańska, Maciej Cytowski, Elaine Mitchell, Cicely K Macnamara, Mark A J Chaplain
In this paper, we present two mathematical models related to different aspects and scales of cancer growth. The first model is a stochastic spatiotemporal model of both a synthetic gene regulatory network (the example of a three-gene repressilator is given) and an actual gene regulatory network, the NF-[Formula: see text]B pathway. The second model is a force-based individual-based model of the development of a solid avascular tumour with specific application to tumour cords, i.e. a mass of cancer cells growing around a central blood vessel...
June 20, 2017: Bulletin of Mathematical Biology
Timothy J Straub, Olga Zhaxybayeva
Whether prokaryotes (Bacteria and Archaea) are naturally organized into phenotypically and genetically cohesive units comparable to animal or plant species remains contested, frustrating attempts to estimate how many such units there might be, or to identify the ecological roles they play. Analyses of gene sequences in various closely related prokaryotic groups reveal that sequence diversity is typically organized into distinct clusters, and processes such as periodic selection and extensive recombination are understood to be drivers of cluster formation ("speciation")...
June 19, 2017: Proceedings of the National Academy of Sciences of the United States of America
Joris Paijmans, David K Lubensky, Pieter Rein Ten Wolde
Synthetic biology sets out to implement new functions in cells, and to develop a deeper understanding of biological design principles. Elowitz and Leibler [Nature (London) 403, 335 (2000)NATUAS0028-083610.1038/35002125] showed that by rational design of the reaction network, and using existing biological components, they could create a network that exhibits periodic gene expression, dubbed the repressilator. More recently, Stricker et al. [Nature (London) 456, 516 (2008)NATUAS0028-083610.1038/nature07389] presented another synthetic oscillator, called the dual-feedback oscillator, which is more stable...
May 2017: Physical Review. E
Robson Rodrigues da Silva, Daniel Gustavo Goroso, Donald M Bers, José Luis Puglisi
Mathematical models of the cardiac cell have started to include markovian representations of the ionic channels instead of the traditional Hodgkin & Huxley formulations. There are many reasons for this: Markov models are not restricted to the idea of independent gates defining the channel, they allow more complex description with specific transitions between open, closed or inactivated states, and more importantly those states can be closely related to the underlying channel structure and conformational changes...
June 12, 2017: Computers in Biology and Medicine
Alexandra Pavlova, Luciano B Beheregaray, Rhys Coleman, Dean Gilligan, Katherine A Harrisson, Brett A Ingram, Joanne Kearns, Annika M Lamb, Mark Lintermans, Jarod Lyon, Thuy T T Nguyen, Minami Sasaki, Zeb Tonkin, Jian D L Yen, Paul Sunnucks
Genetic diversity underpins the ability of populations to persist and adapt to environmental changes. Substantial empirical data show that genetic diversity rapidly deteriorates in small and isolated populations due to genetic drift, leading to reduction in adaptive potential and fitness and increase in inbreeding. Assisted gene flow (e.g. via translocations) can reverse these trends, but lack of data on fitness loss and fear of impairing population "uniqueness" often prevents managers from acting. Here, we use population genetic and riverscape genetic analyses and simulations to explore the consequences of extensive habitat loss and fragmentation on population genetic diversity and future population trajectories of an endangered Australian freshwater fish, Macquarie perch Macquaria australasica...
July 2017: Evolutionary Applications
Huijing Wang, Christian Ray
Single cells can stochastically switch across thresholds imposed by regulatory networks. Such thresholds can act as a tipping point, drastically changing global phenotypic states. In ecology and economics, imminent transitions across such tipping points can be predicted using dynamical early warning indicators. A typical example is "flickering" of a fast variable, predicting a longer-lasting switch from a low to a high state or vice versa. Considering the different timescales between metabolite and protein fluctuations in bacteria, we hypothesized that metabolic early warning indicators predict imminent transitions across a network threshold caused by enzyme saturation...
June 9, 2017: Physical Biology
Teruyoshi Hirayama, Takeshi Yagi
Individual neurons are basic functional units in the complex system of the brain. One aspect of neuronal individuality is generated by stochastic and combinatorial expression of diverse clustered protocadherins (Pcdhs), encoded by the Pcdha, Pcdhb, and Pcdhg gene clusters, that are critical for several aspects of neural circuit formation. Each clustered Pcdh gene has its own promoter containing conserved sequences and is transcribed by a promoter choice mechanism involving interaction between the promoter and enhancers...
June 4, 2017: Seminars in Cell & Developmental Biology
Christopher Schneider, Leo Bronstein, Jascha Diemer, Heinz Koeppl, Beatrix Suess
RNA-engineered systems offer simple and versatile control over gene expression in many organisms. In particular, the design and implementation of riboswitches presents a unique opportunity to manipulate any reporter device in cis, executing tight temporal and spatial control at low metabolic costs. Assembled to higher order genetic circuits, such riboswitch-regulated devices may efficiently process logical operations. Here, we propose a hierarchical stochastic modeling approach to characterize an in silico repressor gate based on neomycin- and tetracycline-sensitive riboswitches...
June 7, 2017: ACS Synthetic Biology
Alessandra Dal Molin, Giacomo Baruzzo, Barbara Di Camillo
The sequencing of the transcriptomes of single-cells, or single-cell RNA-sequencing, has now become the dominant technology for the identification of novel cell types and for the study of stochastic gene expression. In recent years, various tools for analyzing single-cell RNA-sequencing data have been proposed, many of them with the purpose of performing differentially expression analysis. In this work, we compare four different tools for single-cell RNA-sequencing differential expression, together with two popular methods originally developed for the analysis of bulk RNA-sequencing data, but largely applied to single-cell data...
2017: Frontiers in Genetics
A B M Shamim Ul Hasan, Hiroyuki Kurata
Biological memory is a ubiquitous function that can generate a sustained response to a transient inductive stimulus. To better understand this function, we must consider the mechanisms by which different structures of genetic networks achieve memory. Here, we investigated two competitive gene regulatory network models: the regulated mutual activation network (MAN) and the regulated mutual repression network (MRN). Stochasticity deteriorated the persistence of memory of both the MAN and the MRN. Mathematical comparison by simulation and theoretical analysis identified functional differences in the stochastic memory between the competitive models: specifically, the MAN provided much more robust, persistent memory than the MRN...
June 3, 2017: Journal of Theoretical Biology
Petr V Nazarov, Arnaud Muller, Tony Kaoma, Nathalie Nicot, Cristina Maximo, Philippe Birembaut, Nhan L Tran, Gunnar Dittmar, Laurent Vallar
BACKGROUND: RNA sequencing (RNA-seq) and microarrays are two transcriptomics techniques aimed at the quantification of transcribed genes and their isoforms. Here we compare the latest Affymetrix HTA 2.0 microarray with Illumina 2000 RNA-seq for the analysis of patient samples - normal lung epithelium tissue and squamous cell carcinoma lung tumours. Protein coding mRNAs and long non-coding RNAs (lncRNAs) were included in the study. RESULTS: Both platforms performed equally well for protein-coding RNAs, however the stochastic variability was higher for the sequencing data than for microarrays...
June 6, 2017: BMC Genomics
Jae Kyoung Kim, Eduardo D Sontag
Biochemical reaction networks (BRNs) in a cell frequently consist of reactions with disparate timescales. The stochastic simulations of such multiscale BRNs are prohibitively slow due to high computational cost for the simulations of fast reactions. One way to resolve this problem uses the fact that fast species regulated by fast reactions quickly equilibrate to their stationary distribution while slow species are unlikely to be changed. Thus, on a slow timescale, fast species can be replaced by their quasi-steady state (QSS): their stationary conditional expectation values for given slow species...
June 5, 2017: PLoS Computational Biology
Yadira Boada, Alejandro Vignoni, Jesus Pico
Stochastic fluctuations in gene expression trigger both beneficial and harmful consequences for cell behavior. Therefore, achieving a desired mean protein expression level while minimizing noise is of interest in many applications, including robust protein production systems in industrial biotechnology. Here we consider a synthetic gene circuit combining intracellular negative feedback and cell-to-cell communication based on quorum sensing. Accounting for both intrinsic and extrinsic noise, stochastic simulations allow us to analyze the capability of the circuit to reduce noise strength as a function of its parameters...
June 5, 2017: ACS Synthetic Biology
Jian-Rong Yang, Calum J Maclean, Chungoo Park, Huabin Zhao, Jianzhi Zhang
It is commonly, although not universally, accepted that most intra- and inter-specific genome sequence variations are more or less neutral, whereas a large fraction of organism-level phenotypic variations are adaptive. Gene expression levels are molecular phenotypes that bridge the gap between genotypes and corresponding organism-level phenotypes. Yet, it is unknown whether natural variations in gene expression levels are mostly neutral or adaptive. Here we address this fundamental question by genome-wide profiling and comparison of gene expression levels in nine yeast strains belonging to three closely related Saccharomyces species and originating from five different ecological environments...
May 29, 2017: Molecular Biology and Evolution
Andreas Piehler, Navid Ghorashian, Ce Zhang, Savaş Tay
Dynamic cell stimulation is a powerful technique for probing gene networks and for applications in stem cell differentiation, immunomodulation and signaling. We developed a robust and flexible method and associated microfluidic devices to generate a wide-range of precisely formulated dynamic chemical signals to stimulate live cells and measure their dynamic response. This signal generator is capable of digital to analog conversion (DAC) through combinatoric selection of discrete input concentrations, and outperforms existing methods by both achievable resolution, dynamic range and simplicity in design...
June 2, 2017: Lab on a Chip
Damien Nicolas, Nick E Phillips, Felix Naef
Isogenic cells in a common environment present a large degree of heterogeneity in gene expression. Part of this variability is attributed to transcriptional bursting: the stochastic activation and inactivation of promoters that leads to the discontinuous production of mRNA. The diversity in bursting patterns displayed by different genes suggests the existence of a connection between bursting and gene regulation. Experimental strategies such as single-molecule RNA FISH, MS2-GFP or short-lived protein reporters allow the quantification of transcriptional bursting and the comparison of bursting kinetics between conditions, allowing therefore the identification of molecular mechanisms modulating transcriptional bursting...
June 2, 2017: Molecular BioSystems
Jason H Moore, Peter C Andrews, Randal S Olson, Sarah E Carlson, Curt R Larock, Mario J Bulhoes, James P O'Connor, Ellen M Greytak, Steven L Armentrout
BACKGROUND: Large-scale genetic studies of common human diseases have focused almost exclusively on the independent main effects of single-nucleotide polymorphisms (SNPs) on disease susceptibility. These studies have had some success, but much of the genetic architecture of common disease remains unexplained. Attention is now turning to detecting SNPs that impact disease susceptibility in the context of other genetic factors and environmental exposures. These context-dependent genetic effects can manifest themselves as non-additive interactions, which are more challenging to model using parametric statistical approaches...
2017: BioData Mining
Abdulrakeeb M Al-Ssulami, Aqil M Azmi, Hassan Mathkour
Identification of transcription factor binding sites or biological motifs is an important step in deciphering the mechanisms of gene regulation. It is a classic problem that has eluded a satisfactory and efficient solution. In this paper, we devise a three-phase algorithm to mine for biologically significant motifs. In the first phase, we generate all the possible string motifs, this phase is followed by a filtering process where we discard all motifs that do not meet the constraints. And in the final phase, motifs are scored and ranked using a combination of stochastic techniques and [Formula: see text]-value...
May 11, 2017: Journal of Bioinformatics and Computational Biology
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