scholarly journals Evolution of gene regulatory networks by means of selection and random genetic drift

2018 ◽  
Author(s):  
Antonios Kioukis ◽  
Pavlos Pavlidis
Keyword(s):  
Natural Selection ◽  
Positive Selection ◽  
Genetic Drift ◽  
Regulatory Networks ◽  
Fitness Landscape ◽  
Random Genetic Drift ◽  
Maturation Period ◽  
Evolutionary Forces ◽  
Gene Regulatory

The evolution of a population by means of genetic drift and natural selection operating on a gene regulatory network (GRN) of an individual has not been scrutinized in depth. Thus, the relative importance of various evolutionary forces and processes on shaping genetic variability in GRNs is understudied. Furthermore, it is not known if existing tools that identify recent and strong positive selection from genomic sequences, in simple models of evolution, can detect recent positive selection when it operates on GRNs. Here, we propose a simulation framework, called EvoNET, that simulates forward-in-time the evolution of GRNs in a population. Since the population size is finite, random genetic drift is explicitly applied. The fitness of a mutation is not constant, but we evaluate the fitness of each individual by measuring its genetic distance from an optimal genotype. Mutations and recombination may take place from generation to generation, modifying the genotypic composition of the population. Each individual goes through a maturation period, where its GRN reaches equilibrium. At the next step, individuals compete to produce the next generation. As time progresses, the beneficial genotypes push the population higher in the fitness landscape. We examine properties of the GRN evolution such as robustness against the deleterious effect of mutations and the role of genetic drift. We confirm classical results from Andreas Wagner’s work that GRNs show robustness against mutations and we provide new results regarding the interplay between random genetic drift and natural selection.

scholarly journals Reproductive barriers as a byproduct of gene network evolution

2020 ◽  
Author(s):  
Chia-Hung Yang ◽  
Samuel V. Scarpino
Keyword(s):  
Natural Selection ◽  
Reproductive Isolation ◽  
Gene Networks ◽  
Regulatory Networks ◽  
Network Evolution ◽  
Genetic Interactions ◽  
Reproductive Barriers ◽  
Evolutionary Forces ◽  
Functional Representation

AbstractMolecular analyses of closely related taxa have increasingly revealed the importance of higher-order genetic interactions in explaining the observed pattern of reproductive isolation between populations. Indeed, both empirical and theoretical studies have linked the process of speciation to complex genetic interactions. Gene Regulatory Networks (GRNs) capture the inter-dependencies of gene expression and encode information about an individual’s phenotype and development at the molecular level. As a result, GRNs can–in principle–evolve via natural selection and play a role in non-selective, evolutionary forces. Here, we develop a network-based model, termed the pathway framework, that considers GRNs as a functional representation of coding sequences. We then simulated the dynamics of GRNs using a simple model that included natural selection, genetic drift, and sexual reproduction and found that reproductive barriers can develop rapidly between allopatric populations experiencing identical selection pressure. Further, we show that alleles involved in reproductive isolation can predate the allopatric separation of populations and that the number of interacting loci involved in genetic incompatibilities, i.e., the order, is often high simply as a by-product of the networked structure of GRNs. Finally, we discuss how results from the pathway framework are consistent with observed empirical patterns for genes putatively involved in post-zygotic isolation. Taken together, this study adds support for the central role of gene networks in speciation and in evolution more broadly.

scholarly journals Identification of cancer biomarkers of prognostic value using specific gene regulatory networks (GRN): a novel role of RAD51AP1 for ovarian and lung cancers

2017 ◽  
Vol 39 (3) ◽  
pp. 407-417 ◽  
Author(s):  
Dimple Chudasama ◽  
Valeria Bo ◽  
Marcia Hall ◽  
Vladimir Anikin ◽  
Jeyarooban Jeyaneethi ◽  
...  
Keyword(s):  
Gene Regulatory Networks ◽  
Prognostic Value ◽  
Regulatory Networks ◽  
Cancer Biomarkers ◽  
Specific Gene ◽  
Lung Cancers ◽  
Gene Regulatory

scholarly journals Emergent properties of HNF4α-PPARγ network may drive consequent phenotypic plasticity in NAFLD

2020 ◽  
Author(s):  
Sarthak Sahoo ◽  
Divyoj Singh ◽  
Priyanka Chakraborty ◽  
Mohit Kumar Jolly
Keyword(s):  
Liver Disease ◽  
Phenotypic Plasticity ◽  
Regulatory Networks ◽  
Emergent Properties ◽  
Alcoholic Fatty Liver ◽  
Global Presence ◽  
Adults And Children ◽  
Gene Regulatory ◽  
Emergent Dynamics

ABSTRACTNon-Alcoholic Fatty Liver Disease (NAFLD) is the most common form of chronic liver disease in adults and children. It is characterized by excessive accumulation of lipids in the hepatocytes of patients without any excess alcohol intake. With a global presence of 24% and limited therapeutic options, the disease burden of NAFLD is increasing. Thus, it becomes imperative to attempt to understand the dynamics of disease progression at a systems-level. Here, we decode the emergent dynamics of underlying gene regulatory networks that have been identified to drive the initiation and progression of NAFLD. We have developed a mathematical model to elucidate the dynamics of the HNF4α-PPARγ gene regulatory network. Our simulations reveal that this network can enable multiple co-existing phenotypes under certain biological conditions: an adipocyte, a hepatocyte, and a “hybrid” adipocyte-like state of the hepatocyte. These phenotypes may also switch among each other, thus enabling phenotypic plasticity and consequently leading to simultaneous deregulation of the levels of molecules that maintain a hepatic identity and/or facilitate a partial or complete acquisition of adipocytic traits. These predicted trends are supported by the analysis of clinical data, further substantiating the putative role of phenotypic plasticity in driving NAFLD. Our results unravel how the emergent dynamics of underlying regulatory networks can promote phenotypic plasticity, thereby propelling the clinically observed changes in gene expression often associated with NAFLD.

scholarly journals From epigenetic landscape to phenotypic fitness landscape: evolutionary effect of pathogens on host traits

2016 ◽  
Author(s):  
Mark Jayson V. Cortez ◽  
Jomar F. Rabajante ◽  
Jerrold M. Tubay ◽  
Ariel L. Babierra
Keyword(s):  
Regulatory Networks ◽  
Fitness Landscape ◽  
Phenotypic Diversity ◽  
Oscillatory Behavior ◽  
Epigenetic Landscape ◽  
Negative Frequency Dependent Selection ◽  
Gene Regulatory ◽  
Epigenetic Gene Regulation ◽  
Phenotypic Fitness ◽  
The Red Queen

AbstractThe epigenetic landscape illustrates how cells differentiate into different types through the control of gene regulatory networks. Numerous studies have investigated epigenetic gene regulation but there are limited studies on how the epigenetic landscape and the presence of pathogens influence the evolution of host traits. Here we formulate a multistable decision-switch model involving many possible phenotypes with the antagonistic influence of parasitism. As expected, pathogens can drive dominant (common) phenotypes to become inferior, such as through negative frequency-dependent selection. Furthermore, novel predictions of our model show that parasitism can steer the dynamics of phenotype specification from multistable equilibrium convergence to oscillations. This oscillatory behavior could explain pathogen-mediated epimutations and excessive phenotypic plasticity. The Red Queen dynamics also occur in certain parameter space of the model, which demonstrates winnerless cyclic phenotype-switching in hosts and in pathogens. The results of our simulations elucidate how epigenetic landscape is associated with the phenotypic fitness landscape and how parasitism facilitates non-genetic phenotypic diversity.

scholarly journals The Contribution of Autophagy and LncRNAs to MYC-Driven Gene Regulatory Networks in Cancers

2021 ◽  
Vol 22 (16) ◽  
pp. 8527
Author(s):  
Leila Jahangiri ◽  
Perla Pucci ◽  
Tala Ishola ◽  
Ricky M. Trigg ◽  
John A. Williams ◽  
...  
Keyword(s):  
Gene Networks ◽  
Regulatory Networks ◽  
Metabolic Reprogramming ◽  
Cellular Processes ◽  
Cancer Genomes ◽  
Mutual Regulation ◽  
Myc Gene ◽  
Gene Regulatory ◽  
Non Coding Rnas

MYC is a target of the Wnt signalling pathway and governs numerous cellular and developmental programmes hijacked in cancers. The amplification of MYC is a frequently occurring genetic alteration in cancer genomes, and this transcription factor is implicated in metabolic reprogramming, cell death, and angiogenesis in cancers. In this review, we analyse MYC gene networks in solid cancers. We investigate the interaction of MYC with long non-coding RNAs (lncRNAs). Furthermore, we investigate the role of MYC regulatory networks in inducing changes to cellular processes, including autophagy and mitophagy. Finally, we review the interaction and mutual regulation between MYC and lncRNAs, and autophagic processes and analyse these networks as unexplored areas of targeting and manipulation for therapeutic gain in MYC-driven malignancies.

scholarly journals The Role of Gene Conversion between Transposable Elements in Rewiring Regulatory Networks

2019 ◽  
Vol 11 (7) ◽  
pp. 1723-1729
Author(s):  
Jeffrey A Fawcett ◽  
Hideki Innan
Keyword(s):  
Transposable Elements ◽  
Gene Conversion ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Alternative Mechanism ◽  
Beneficial Mutations ◽  
Future Studies ◽  
Cellular Processes ◽  
Gene Regulatory

Abstract Nature has found many ways to utilize transposable elements (TEs) throughout evolution. Many molecular and cellular processes depend on DNA-binding proteins recognizing hundreds or thousands of similar DNA motifs dispersed throughout the genome that are often provided by TEs. It has been suggested that TEs play an important role in the evolution of such systems, in particular, the rewiring of gene regulatory networks. One mechanism that can further enhance the rewiring of regulatory networks is nonallelic gene conversion between copies of TEs. Here, we will first review evidence for nonallelic gene conversion in TEs. Then, we will illustrate the benefits nonallelic gene conversion provides in rewiring regulatory networks. For instance, nonallelic gene conversion between TE copies offers an alternative mechanism to spread beneficial mutations that improve the network, it allows multiple mutations to be combined and transferred together, and it allows natural selection to work efficiently in spreading beneficial mutations and removing disadvantageous mutations. Future studies examining the role of nonallelic gene conversion in the evolution of TEs should help us to better understand how TEs have contributed to evolution.

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