Local genetic context shapes the function of a gene regulatory network

Gene expression levels are influenced by multiple coexisting molecular mechanisms. Some of these interactions such as those of transcription factors and promoters have been studied extensively. However, predicting phenotypes of gene regulatory networks (GRNs) remains a major challenge. Here, we use a well-defined synthetic GRN to study in Escherichia coli how network phenotypes depend on local genetic context, i.e. the genetic neighborhood of a transcription factor and its relative position. We show that one GRN with fixed topology can display not only quantitatively but also qualitatively different phenotypes, depending solely on the local genetic context of its components. Transcriptional read-through is the main molecular mechanism that places one transcriptional unit (TU) within two separate regulons without the need for complex regulatory sequences. We propose that relative order of individual TUs, with its potential for combinatorial complexity, plays an important role in shaping phenotypes of GRNs.

Download Full-text

Local genetic context shapes the function of a gene regulatory network

10.1101/2021.01.10.426121 ◽

2021 ◽

Author(s):

Anna Nagy-Staroń ◽

Kathrin Tomasek ◽

Caroline Caruso Carter ◽

Elisabeth Sonnleitner ◽

Bor Kavčič ◽

...

Keyword(s):

Gene Regulatory Network ◽

Gene Regulatory Networks ◽

Regulatory Network ◽

Regulatory Networks ◽

Molecular Mechanisms ◽

Transcriptional Unit ◽

Regulatory Sequences ◽

Gene Regulatory ◽

Context Shapes ◽

Genetic Context

Gene expression levels are influenced by multiple coexisting molecular mechanisms. Some of these interactions, such as those of transcription factors and promoters have been studied extensively. However, predicting phenotypes of gene regulatory networks remains a major challenge. Here, we use a well-defined synthetic gene regulatory network to study how network phenotypes depend on local genetic context, i.e. the genetic neighborhood of a transcription factor and its relative position. We show that one gene regulatory network with fixed topology can display not only quantitatively but also qualitatively different phenotypes, depending solely on the local genetic context of its components. Our results demonstrate that changes in local genetic context can place a single transcriptional unit within two separate regulons without the need for complex regulatory sequences. We propose that relative order of individual transcriptional units, with its potential for combinatorial complexity, plays an important role in shaping phenotypes of gene regulatory networks.

Download Full-text

Comprehensive Assessment and Network Analysis of the Emerging Genetic Susceptibility Landscape of Prostate Cancer

Cancer Informatics ◽

10.4137/cin.s12128 ◽

2013 ◽

Vol 12 ◽

pp. CIN.S12128 ◽

Cited By ~ 5

Author(s):

Chindo Hicks ◽

Lucio Miele ◽

Tejaswi Koganti ◽

Srinivasan Vijayakumar

Keyword(s):

Prostate Cancer ◽

Genetic Susceptibility ◽

Pathway Analysis ◽

Gene Regulatory Networks ◽

Genetic Variants ◽

Regulatory Networks ◽

Molecular Mechanisms ◽

Comprehensive Assessment ◽

Increased Risk ◽

Gene Regulatory

Background Recent advances in high-throughput genotyping have made possible identification of genetic variants associated with increased risk of developing prostate cancer using genome-wide associations studies (GWAS). However, the broader context in which the identified genetic variants operate is poorly understood. Here we present a comprehensive assessment, network, and pathway analysis of the emerging genetic susceptibility landscape of prostate cancer. Methods We created a comprehensive catalog of genetic variants and associated genes by mining published reports and accompanying websites hosting supplementary data on GWAS. We then performed network and pathway analysis using single nucleotide polymorphism (SNP)-containing genes to identify gene regulatory networks and pathways enriched for genetic variants. Results We identified multiple gene networks and pathways enriched for genetic variants including IGF-1, androgen biosynthesis and androgen signaling pathways, and the molecular mechanisms of cancer. The results provide putative functional bridges between GWAS findings and gene regulatory networks and biological pathways.

Download Full-text

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

10.1101/2020.06.15.151712 ◽

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.

Download Full-text

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

10.1101/756635 ◽

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.

Download Full-text

Unexpected links reflect the noise in networks

10.1101/000497 ◽

2013 ◽

Author(s):

Anatoly Yambartsev ◽

Michael Perlin ◽

Yevgeniy Kovchegov ◽

Natalia Shulzhenko ◽

Karina Mine ◽

...

Keyword(s):

Gene Regulatory Networks ◽

Regulatory Networks ◽

Molecular Mechanisms ◽

Simulation Analysis ◽

Biological Processes ◽

Special Relationship ◽

False Discovery ◽

Precise Estimation ◽

Gene Regulatory ◽

The Mathematical Model

Gene regulatory networks are commonly used for modeling biological processes and revealing underlying molecular mechanisms. The reconstruction of gene regulatory networks from observational data is a challenging task, especially, considering the large number of involved players (e.g. genes) and much fewer biological replicates available for analysis. Herein, we proposed a new statistical method of estimating the number of erroneous edges that strongly enhances the commonly used inference approaches. This method is based on special relationship between correlation and causality, and allows to identify and to remove approximately half of erroneous edges. Using the mathematical model of Bayesian networks and positive correlation inequalities we established a mathematical foundation for our method. Analyzing real biological datasets, we found a strong correlation between the results of our method and the commonly used false discovery rate (FDR) technique. Furthermore, the simulation analysis demonstrates that in large networks, our new method provides a more precise estimation of the proportion of erroneous links than FDR.

Download Full-text

The mechanisms of gene regulatory networks constrain evolution: A lesson from synthetic circuits

10.1101/184325 ◽

2017 ◽

Author(s):

Yolanda Schaerli ◽

Alba Jiménez ◽

José M. Duarte ◽

Ljiljana Mihajlovic ◽

Julien Renggli ◽

...

Keyword(s):

Gene Expression ◽

Gene Regulatory Networks ◽

Phenotypic Variation ◽

Regulatory Networks ◽

Molecular Mechanisms ◽

Raw Material ◽

Darwinian Evolution ◽

Regulatory Mechanisms ◽

Gene Regulatory ◽

Organismal Development

AbstractPhenotypic variation is the raw material of adaptive Darwinian evolution. The phenotypic variation found in organismal development is biased towards certain phenotypes, but the molecular mechanisms behind such restrictions are still poorly understood. Gene regulatory networks have been proposed as one cause of constrained phenotypic variation. However, most of the evidence for this is theoretical rather than experimental. Here, we study evolutionary biases in two synthetic gene regulatory circuits expressed inE. colithat produce a gene expression stripe - a pivotal pattern in embryonic development. The two parental circuits produce the same phenotype, but create it through different regulatory mechanisms. We show that mutations cause distinct novel phenotypes in the two networks and use a combination of experimental measurements, mathematical modelling and DNA sequencing to understand why mutations bring forth only some but not other novel gene expression phenotypes. Our results reveal that the regulatory mechanisms of networks restrict the possible phenotypic variation upon mutation. Consequently, seemingly equivalent networks can indeed be distinct in how they constrain the outcome of further evolution.

Download Full-text

Gene Regulatory Networks Generating the Phenomena of Additivity, Dominance and Epistasis

Genetics ◽

10.1093/genetics/155.2.969 ◽

2000 ◽

Vol 155 (2) ◽

pp. 969-980 ◽

Cited By ~ 2

Author(s):

Stig W Omholt ◽

Erik Plahte ◽

Leiv Øyehaug ◽

Kefang Xiang

Keyword(s):

Gene Regulatory Networks ◽

Regulatory Networks ◽

Feedback Loop ◽

Molecular Mechanisms ◽

Gene Action ◽

Gene Dosage ◽

Dominant Negative ◽

Protein Activity ◽

Genetic Dominance ◽

Gene Regulatory

Abstract We show how the phenomena of genetic dominance, overdominance, additivity, and epistasis are generic features of simple diploid gene regulatory networks. These regulatory network models are together sufficiently complex to catch most of the suggested molecular mechanisms responsible for generating dominant mutations. These include reduced gene dosage, expression or protein activity (haploinsufficiency), increased gene dosage, ectopic or temporarily altered mRNA expression, increased or constitutive protein activity, and dominant negative effects. As classical genetics regards the phenomenon of dominance to be generated by intralocus interactions, we have studied two one-locus models, one with a negative autoregulatory feedback loop, and one with a positive autoregulatory feedback loop. To include the phenomena of epistasis and downstream regulatory effects, a model of a three-locus signal transduction network is also analyzed. It is found that genetic dominance as well as overdominance may be an intra- as well as interlocus interaction phenomenon. In the latter case the dominance phenomenon is intimately connected to either feedback-mediated epistasis or downstream-mediated epistasis. It appears that in the intra- as well as the interlocus case there is considerable room for additive gene action, which may explain to some degree the predictive power of quantitative genetic theory, with its emphasis on this type of gene action. Furthermore, the results illuminate and reconcile the prevailing explanations of heterosis, and they support the old conjecture that the phenomenon of dominance may have an evolutionary explanation related to life history strategy.

Download Full-text

Regulation of gene expression in the nervous system

Biochemical Journal ◽

10.1042/bj20080963 ◽

2008 ◽

Vol 414 (3) ◽

pp. 327-341 ◽

Cited By ~ 42

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.

Download Full-text