Regulation of gene expression in the nervous system

2008 ◽  
Vol 414 (3) ◽  
pp. 327-341 ◽  
Author(s):  
Lezanne Ooi ◽  
Ian C. Wood
Keyword(s):  
Gene Expression ◽  
Nervous System ◽  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Regulation Of Gene Expression ◽  
Cell Types ◽  
Gene Regulatory

The nervous system contains a multitude of cell types which are specified during development by cascades of transcription factors acting combinatorially. Some of these transcription factors are only active during development, whereas others continue to function in the mature nervous system to maintain appropriate gene-expression patterns in differentiated cells. Underpinning the function of the nervous system is its plasticity in response to external stimuli, and many transcription factors are involved in regulating gene expression in response to neuronal activity, allowing us to learn, remember and make complex decisions. Here we review some of the recent findings that have uncovered the molecular mechanisms that underpin the control of gene regulatory networks within the nervous system. We highlight some recent insights into the gene-regulatory circuits in the development and differentiation of cells within the nervous system and discuss some of the mechanisms by which synaptic transmission influences transcription-factor activity in the mature nervous system. Mutations in genes that are important in epigenetic regulation (by influencing DNA methylation and post-translational histone modifications) have long been associated with neuronal disorders in humans such as Rett syndrome, Huntington's disease and some forms of mental retardation, and recent work has focused on unravelling their mechanisms of action. Finally, the discovery of microRNAs has produced a paradigm shift in gene expression, and we provide some examples and discuss the contribution of microRNAs to maintaining dynamic gene regulatory networks in the brain.

scholarly journals Identifying genetic modulators of the connectivity between transcription factors and their transcriptional targets

2016 ◽  
Vol 113 (13) ◽  
pp. E1835-E1843 ◽  
Author(s):  
Mina Fazlollahi ◽  
Ivor Muroff ◽  
Eunjee Lee ◽  
Helen C. Causton ◽  
Harmen J. Bussemaker
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Nonsynonymous Mutation ◽  
Gene Regulatory ◽  
Genetic Modulators

Regulation of gene expression by transcription factors (TFs) is highly dependent on genetic background and interactions with cofactors. Identifying specific context factors is a major challenge that requires new approaches. Here we show that exploiting natural variation is a potent strategy for probing functional interactions within gene regulatory networks. We developed an algorithm to identify genetic polymorphisms that modulate the regulatory connectivity between specific transcription factors and their target genes in vivo. As a proof of principle, we mapped connectivity quantitative trait loci (cQTLs) using parallel genotype and gene expression data for segregants from a cross between two strains of the yeast Saccharomyces cerevisiae. We identified a nonsynonymous mutation in the DIG2 gene as a cQTL for the transcription factor Ste12p and confirmed this prediction empirically. We also identified three polymorphisms in TAF13 as putative modulators of regulation by Gcn4p. Our method has potential for revealing how genetic differences among individuals influence gene regulatory networks in any organism for which gene expression and genotype data are available along with information on binding preferences for transcription factors.

scholarly journals Expression pattern determines regulatory logic

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244864
Author(s):  
Carlos Mora-Martinez
Keyword(s):  
Gene Expression ◽  
Gene Regulatory Networks ◽  
Dna Sequences ◽  
In Silico ◽  
Regulatory Networks ◽  
Expression Patterns ◽  
Cell Types ◽  
Evolutionary Strategy ◽  
Specific Gene ◽  
Gene Regulatory

Large amounts of effort have been invested in trying to understand how a single genome is able to specify the identity of hundreds of cell types. Inspired by some aspects of Caenorhabditis elegans biology, we implemented an in silico evolutionary strategy to produce gene regulatory networks (GRNs) that drive cell-specific gene expression patterns, mimicking the process of terminal cell differentiation. Dynamics of the gene regulatory networks are governed by a thermodynamic model of gene expression, which uses DNA sequences and transcription factor degenerate position weight matrixes as input. In a version of the model, we included chromatin accessibility. Experimentally, it has been determined that cell-specific and broadly expressed genes are regulated differently. In our in silico evolved GRNs, broadly expressed genes are regulated very redundantly and the architecture of their cis-regulatory modules is different, in accordance to what has been found in C. elegans and also in other systems. Finally, we found differences in topological positions in GRNs between these two classes of genes, which help to explain why broadly expressed genes are so resilient to mutations. Overall, our results offer an explanatory hypothesis on why broadly expressed genes are regulated so redundantly compared to cell-specific genes, which can be extrapolated to phenomena such as ChIP-seq HOT regions.

scholarly journals Automated generation of context-specific Gene Regulatory Networks with a weighted approach in D. melanogaster

2020 ◽  
Author(s):  
Leandro Murgas ◽  
Sebastian Contreras-Riquelme ◽  
J. Eduardo Martínez ◽  
Camilo Villaman ◽  
Rodrigo Santibáñez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Current Knowledge ◽  
Regulation Of Gene Expression ◽  
Chromatin Accessibility ◽  
Reference Network ◽  
Specific Gene ◽  
Gene Regulatory

AbstractMotivationThe regulation of gene expression is a key factor in the development and maintenance of life in all organisms. This process is carried out mainly through the action of transcription factors (TFs), although other actors such as ncRNAs are involved. In this work, we propose a new method to construct Gene Regulatory Networks (GRNs) depicting regulatory events in a certain context for Drosophila melanogaster. Our approach is based on known relationships between epigenetics and the activity of transcription factors.ResultsWe developed method, Tool for Weighted Epigenomic Networks in D. melanogaster (Fly T-WEoN), which generates GRNs starting from a reference network that contains all known gene regulations in the fly. Regulations that are unlikely taking place are removed by applying a series of knowledge-based filters. Each of these filters is implemented as an independent module that considers a type of experimental evidence, including DNA methylation, chromatin accessibility, histone modifications, and gene expression. Fly T-WEoN is based on heuristic rules that reflect current knowledge on gene regulation in D. melanogaster obtained from literature. Experimental data files can be generated with several standard procedures and used solely when and if available.Fly T-WEoN is available as a Cytoscape application that permits integration with other tools, and facilitates downstream network analysis. In this work, we first demonstrate the reliability of our method to then provide a relevant application case of our tool: early development of D. melanogaster.AvailabilityFly T-WEoN, together with its step-by-step guide is available at https://[email protected]

scholarly journals Chip-seq and gene expression data for the identification of functional sub-pathways: a proof of concept in lung cancer

2020 ◽  
Author(s):  
Xanthoula Atsalaki ◽  
Lefteris Koumakis ◽  
George Potamias ◽  
Manolis Tsiknakis
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Systems Biology ◽  
Gene Expression Data ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Integrative Approach ◽  
Expression Data ◽  
Gene Regulatory

AbstractHigh-throughput technologies, such as chromatin immunoprecipitation (ChIP) with massively parallel sequencing (ChIP-seq) have enabled cost and time efficient generation of immense amount of genome data. The advent of advanced sequencing techniques allowed biologists and bioinformaticians to investigate biological aspects of cell function and understand or reveal unexplored disease etiologies. Systems biology attempts to formulate the molecular mechanisms in mathematical models and one of the most important areas is the gene regulatory networks (GRNs), a collection of DNA segments that somehow interact with each other. GRNs incorporate valuable information about molecular targets that can be corellated to specific phenotype.In our study we highlight the need to develop new explorative tools and approaches for the integration of different types of -omics data such as ChIP-seq and GRNs using pathway analysis methodologies. We present an integrative approach for ChIP-seq and gene expression data on GRNs. Using public microarray expression samples for lung cancer and healthy subjects along with the KEGG human gene regulatory networks, we identified ways to disrupt functional sub-pathways on lung cancer with the aid of CTCF ChIP-seq data, as a proof of concept.We expect that such a systems biology pipeline could assist researchers to identify corellations and causality of transcription factors over functional or disrupted biological sub-pathways.

scholarly journals Upregulation and cell specificity of C4 genes are derived from ancestral C3 gene regulatory networks

2020 ◽  
Author(s):  
Pallavi Singh ◽  
Sean R. Stevenson ◽  
Ivan Reyna-Llorens ◽  
Gregory Reeves ◽  
Tina B. Schreier ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Transcript Accumulation ◽  
Specific Expression ◽  
Cell Specificity ◽  
Distinct Cell ◽  
Gene Regulatory

ABSTRACTThe efficient C4 pathway is based on strong up-regulation of genes found in C3 plants, but also compartmentation of their expression into distinct cell-types such as the mesophyll and bundle sheath. Transcription factors associated with these phenomena have not been identified. To address this, we undertook genome-wide analysis of transcript accumulation, chromatin accessibility and transcription factor binding in C4Gynandropsis gynandra. From these data, two models relating to the molecular evolution of C4 photosynthesis are proposed. First, increased expression of C4 genes is associated with increased binding by MYB-related transcription factors. Second, mesophyll specific expression is associated with binding of homeodomain transcription factors. Overall, we conclude that during evolution of the complex C4 trait, C4 cycle genes gain cis-elements that operate in the C3 leaf such that they become integrated into existing gene regulatory networks associated with cell specificity and photosynthesis.

scholarly journals Single cell and single nucleus RNA-Seq reveal cellular heterogeneity and homeostatic regulatory networks in adult mouse stria vascularis

2019 ◽  
Author(s):  
Soumya Korrapati ◽  
Ian Taukulis ◽  
Rafal Olszewski ◽  
Madeline Pyle ◽  
Shoujun Gu ◽  
...  
Keyword(s):  
Single Cell ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Stria Vascularis ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Genetic Mechanisms ◽  
Single Nucleus ◽  
Gene Regulatory

AbstractThe stria vascularis (SV) generates the endocochlear potential (EP) in the inner ear and is necessary for proper hair cell mechanotransduction and hearing. While channels belonging to SV cell types are known to play crucial roles in EP generation, relatively little is known about gene regulatory networks that underlie the ability of the SV to generate and maintain the EP. Using single cell and single nucleus RNA-sequencing, we identify and validate known and rare cell populations in the SV. Furthermore, we establish a basis for understanding molecular mechanisms underlying SV function by identifying potential gene regulatory networks as well as druggable gene targets. Finally, we associate known deafness genes with adult SV cell types. This work establishes a basis for dissecting the genetic mechanisms underlying the role of the SV in hearing and will serve as a basis for designing therapeutic approaches to hearing loss related to SV dysfunction.

scholarly journals Revealing the Key Regulators of Cell Identity in the Human Adult Pancreas

2020 ◽  
Author(s):  
Lotte Vanheer ◽  
Andrea Alex Schiavo ◽  
Matthias Van Haele ◽  
Tine Haesen ◽  
Adrian Janiszewski ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Cell Types ◽  
List Type ◽  
Cell Identity ◽  
Pancreatic Cell ◽  
Human Adult ◽  
Gene Regulatory ◽  
Cellular Identity

SUMMARYCellular identity during development is under the control of transcription factors that form gene regulatory networks. However, the transcription factors and gene regulatory networks underlying cellular identity in the human adult pancreas remain largely unexplored. Here, we integrate multiple single-cell RNA sequencing datasets of the human adult pancreas, totaling 7393 cells, and comprehensively reconstruct gene regulatory networks. We show that a network of 142 transcription factors forms distinct regulatory modules that characterize pancreatic cell types. We present evidence that our approach identifies key regulators of cell identity in the human adult pancreas. We predict that HEYL and JUND are active in acinar and alpha cells, respectively, and show that these proteins are present in the human adult pancreas as well as in human induced pluripotent stem cell-derived pancreatic cells. The comprehensive gene regulatory network atlas can be explored interactively online. We anticipate our analysis to be the starting point for a more sophisticated dissection of how transcription factors regulate cell identity in the human adult pancreas. Furthermore, given that transcription factors are major regulators of embryo development and are often perturbed in diseases, a comprehensive understanding of how transcription factors work will be relevant in development and disease biology.HIGHLIGHTS-Reconstruction of gene regulatory networks for human adult pancreatic cell types-An interactive resource to explore and visualize gene expression and regulatory states-Predicting putative transcription factors driving pancreatic cell identity-HEYL and JUND as candidate regulators of acinar and alpha cell identity, respectively

scholarly journals Comparative analyses of saprotrophy in Salisapilia sapeloensis and diverse plant pathogenic oomycetes reveal lifestyle-specific gene expression

2020 ◽  
Vol 96 (11) ◽  
Author(s):  
Sophie de Vries ◽  
Jan de Vries ◽  
John M Archibald ◽  
Claudio H Slamovits
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Plant Pathogens ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Reference Points ◽  
Global Perspective ◽  
Specific Gene ◽  
Gene Regulatory ◽  
Specific Array

ABSTRACT Oomycetes include many devastating plant pathogens. Across oomycete diversity, plant-infecting lineages are interspersed by non-pathogenic ones. Unfortunately, our understanding of the evolution of lifestyle switches is hampered by a scarcity of data on the molecular biology of saprotrophic oomycetes, ecologically important primary colonizers of dead tissue that can serve as informative reference points for understanding the evolution of pathogens. Here, we established Salisapilia sapeloensis as a tractable system for the study of saprotrophic oomycetes. We generated multiple transcriptomes from S. sapeloensis and compared them with (i) 22 oomycete genomes and (ii) the transcriptomes of eight pathogenic oomycetes grown under 13 conditions. We obtained a global perspective on gene expression signatures of oomycete lifestyles. Our data reveal that oomycete saprotrophs and pathogens use similar molecular mechanisms for colonization but exhibit distinct expression patterns. We identify a S. sapeloensis-specific array and expression of carbohydrate-active enzymes and putative regulatory differences, highlighted by distinct expression levels of transcription factors. Salisapilia sapeloensis expresses only a small repertoire of candidates for virulence-associated genes. Our analyses suggest lifestyle-specific gene regulatory signatures and that, in addition to variation in gene content, shifts in gene regulatory networks underpin the evolution of oomycete lifestyles.

scholarly journals Precision of Tissue Patterning is Controlled by Dynamical Properties of Gene Regulatory Networks

2019 ◽  
Author(s):  
Katherine Exelby ◽  
Edgar Herrera-Delgado ◽  
Lorena Garcia Perez ◽  
Ruben Perez-Carrasco ◽  
Andreas Sagner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Regulatory Networks ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Expression Patterns ◽  
Cell Fates ◽  
Gene Circuits ◽  
Stochastic Fluctuations ◽  
Network Properties ◽  
Gene Regulatory

AbstractDuring development, gene regulatory networks allocate cell fates by partitioning tissues into spatially organised domains of gene expression. How the sharp boundaries that delineate these gene expression patterns arise, despite the stochasticity associated with gene regulation, is poorly understood. We show, in the vertebrate neural tube, using perturbations of coding and regulatory regions, that the structure of the regulatory network contributes to boundary precision. This is achieved, not by reducing noise in individual genes, but by the configuration of the network modulating the ability of stochastic fluctuations to initiate gene expression changes. We use a computational screen to identify network properties that influence boundary precision, revealing two dynamical mechanisms by which small gene circuits attenuate the effect of noise in order to increase patterning precision. These results highlight design principles of gene regulatory networks that produce precise patterns of gene expression.

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