scholarly journals Populations of genetic circuits are unable to find the fittest solution in a multilevel genotype-phenotype map

2019 ◽  
Author(s):  
Pablo Catalán ◽  
Susanna Manrubia ◽  
José A. Cuesta
Keyword(s):  
Regulatory Networks ◽  
Expression Patterns ◽  
Genetic Circuits ◽  
Target Pattern ◽  
Selective Pressures ◽  
Spatiotemporal Expression ◽  
Genotype Space ◽  
Great Relevance ◽  
Gene Regulatory ◽  
The Relationship

AbstractThe evolution of gene regulatory networks (GRNs) is of great relevance for both evolutionary and synthetic biology. Understanding the relationship between GRN structure and its function can allow us to understand the selective pressures that have shaped a given circuit. This is especially relevant when considering spatiotemporal expression patterns, where GRN models have been shown to be extremely robust and evolvable. However, previous models that studied GRN evolution did not include the evolution of protein and genetic elements that underlie GRN architecture. Here we use toyLIFE, a multilevel genotype-phenotype map, to show that not all GRNs are equally likely in genotype space and that evolution is biased to find the most common GRNs. toyLIFE rules create Boolean GRNs that, embedded in a one-dimensional tissue, develop a variety of spatiotemporal gene expression patterns. Populations of toyLIFE organisms choose the most common GRN out of a set of equally fit alternatives and, most importantly, fail to find a target pattern when it is very rare in genotype space. Indeed, we show that the probability of finding the fittest phenotype increases dramatically with its abundance in genotype space. This phenotypic bias represents a mechanism that can prevent the fixation in the population of the fittest phenotype, one that is inherent to the structure of genotype space and the genotype-phenotype map.

scholarly journals Populations of genetic circuits are unable to find the fittest solution in a multilevel genotype–phenotype map

2020 ◽  
Vol 17 (167) ◽  
pp. 20190843 ◽  
Author(s):  
Pablo Catalán ◽  
Susanna Manrubia ◽  
José A. Cuesta
Keyword(s):  
Regulatory Networks ◽  
Expression Patterns ◽  
Genetic Circuits ◽  
Temporal Expression ◽  
Target Pattern ◽  
Temporal Gene Expression ◽  
Genotype Space ◽  
Great Relevance ◽  
Spatio Temporal ◽  
The Relationship

The evolution of gene regulatory networks (GRNs) is of great relevance for both evolutionary and synthetic biology. Understanding the relationship between GRN structure and its function can allow us to understand the selective pressures that have shaped a given circuit. This is especially relevant when considering spatio-temporal expression patterns, where GRN models have been shown to be extremely robust and evolvable. However, previous models that studied GRN evolution did not include the evolution of protein and genetic elements that underlie GRN architecture. Here we use toy LIFE, a multilevel genotype–phenotype map, to show that not all GRNs are equally likely in genotype space and that evolution is biased to find the most common GRNs. toy LIFE rules create Boolean GRNs that, embedded in a one-dimensional tissue, develop a variety of spatio-temporal gene expression patterns. Populations of toy LIFE organisms choose the most common GRN out of a set of equally fit alternatives and, most importantly, fail to find a target pattern when it is very rare in genotype space. Indeed, we show that the probability of finding the fittest phenotype increases dramatically with its abundance in genotype space. This phenotypic bias represents a mechanism that can prevent the fixation in the population of the fittest phenotype, one that is inherent to the structure of genotype space and the genotype–phenotype map.

scholarly journals Comparative transcriptomics identifies differences in the regulation of the floral transition between Arabidopsis and Brassica rapa cultivars

2020 ◽  
Author(s):  
Alexander Calderwood ◽  
Jo Hepworth ◽  
Shannon Woodhouse ◽  
Lorelei Bilham ◽  
D. Marc Jones ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brassica Rapa ◽  
Regulatory Networks ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Detailed Comparison ◽  
Developmental Time ◽  
Floral Transition ◽  
Gene Regulatory

AbstractThe timing of the floral transition affects reproduction and yield, however its regulation in crops remains poorly understood. Here, we use RNA-Seq to determine and compare gene expression dynamics through the floral transition in the model species Arabidopsis thaliana and the closely related crop Brassica rapa. A direct comparison of gene expression over time between species shows little similarity, which could lead to the inference that different gene regulatory networks are at play. However, these differences can be largely resolved by synchronisation, through curve registration, of gene expression profiles. We find that different registration functions are required for different genes, indicating that there is no common ‘developmental time’ to which Arabidopsis and B. rapa can be mapped through gene expression. Instead, the expression patterns of different genes progress at different rates. We find that co-regulated genes show similar changes in synchronisation between species, suggesting that similar gene regulatory sub-network structures may be active with different wiring between them. A detailed comparison of the regulation of the floral transition between Arabidopsis and B. rapa, and between two B. rapa accessions reveals different modes of regulation of the key floral integrator SOC1, and that the floral transition in the B. rapa accessions is triggered by different pathways, even when grown under the same environmental conditions. Our study adds to the mechanistic understanding of the regulatory network of flowering time in rapid cycling B. rapa under long days and highlights the importance of registration methods for the comparison of developmental gene expression data.

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 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 The Hypoxia–Long Noncoding RNA Interaction in Solid Cancers

2021 ◽  
Vol 22 (14) ◽  
pp. 7261
Author(s):  
Seung Wan Son ◽  
Ba Da Yun ◽  
Mun Gyu Song ◽  
Jin Kyeong Lee ◽  
Soo Young Choi ◽  
...  
Keyword(s):  
Gene Regulatory Networks ◽  
Noncoding Rna ◽  
Regulatory Networks ◽  
Apoptotic Cell ◽  
Hallmarks Of Cancer ◽  
Dismal Prognosis ◽  
Gene Regulatory ◽  
Cellular Pathways ◽  
Rna Interaction ◽  
The Relationship

Hypoxia is one of the representative microenvironment features in cancer and is considered to be associated with the dismal prognosis of patients. Hypoxia-driven cellular pathways are largely regulated by hypoxia-inducible factors (HIFs) and notably exert influence on the hallmarks of cancer, such as stemness, angiogenesis, invasion, metastasis, and the resistance towards apoptotic cell death and therapeutic resistance; therefore, hypoxia has been considered as a potential hurdle for cancer therapy. Growing evidence has demonstrated that long noncoding RNAs (lncRNAs) are dysregulated in cancer and take part in gene regulatory networks owing to their various modes of action through interacting with proteins and microRNAs. In this review, we focus attention on the relationship between hypoxia/HIFs and lncRNAs, in company with the possibility of lncRNAs as candidate molecules for controlling cancer.

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.

scholarly journals How Criticality of Gene Regulatory Networks Affects the Resulting Morphogenesis under Genetic Perturbations

2018 ◽  
Vol 24 (2) ◽  
pp. 85-105 ◽  
Author(s):  
Hyobin Kim ◽  
Hiroki Sayama
Keyword(s):  
Single Cell ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Single Cell Level ◽  
Cell Level ◽  
Genetic Perturbations ◽  
Gene Regulatory ◽  
Seed Cell ◽  
Complex Features ◽  
The Relationship

Whereas the relationship between criticality of gene regulatory networks (GRNs) and dynamics of GRNs at a single-cell level has been vigorously studied, the relationship between the criticality of GRNs and system properties at a higher level has not been fully explored. Here we aim at revealing a potential role of criticality of GRNs in morphogenesis, which is hard to uncover through the single-cell-level studies, especially from an evolutionary viewpoint. Our model simulated the growth of a cell population from a single seed cell. All the cells were assumed to have identical intracellular GRNs. We induced genetic perturbations to the GRN of the seed cell by adding, deleting, or switching a regulatory link between a pair of genes. From numerical simulations, we found that the criticality of GRNs facilitated the formation of nontrivial morphologies when the GRNs were critical in the presence of the evolutionary perturbations. Moreover, the criticality of GRNs produced topologically homogeneous cell clusters by adjusting the spatial arrangements of cells, which led to the formation of nontrivial morphogenetic patterns. Our findings correspond to an epigenetic viewpoint that heterogeneous and complex features emerge from homogeneous and less complex components through the interactions among them. Thus, our results imply that highly structured tissues or organs in morphogenesis of multicellular organisms might stem from the criticality of GRNs.

scholarly journals Embryonic expression patterns of panarthropod Teneurin-m/odd Oz genes suggest a possible function in segmentation

2019 ◽  
Author(s):  
Ralf Janssen
Keyword(s):  
Regulatory Networks ◽  
Transmembrane Protein ◽  
Expression Patterns ◽  
Expression Data ◽  
Segmentation Gene ◽  
Protein Encoding ◽  
Related Group ◽  
Gene Regulatory ◽  
Encoding Gene ◽  
Pair Rule

AbstractBackgroundA hallmark of arthropods is their segmented body, and the so-called Drosophila segmentation gene cascade that controls this process serves as one of the best-studied gene regulatory networks. An important group of segmentation genes is represented by the pair-rule genes (PRGs). One of these genes was thought to be the type-II transmembrane protein encoding gene Tenascin-m (Ten-m (aka odd Oz)). Ten-m, however, does not have a pair-rule function in Drosophila, despite its characteristic PRG-like expression pattern. A recent study in the beetle Tribolium castaneum showed that its Ten-m gene is not expressed like a segmentation gene, and hence is very unlikely to have a function in segmentation.ResultsIn this study, I present data from a range of arthropods covering the arthropod tree of life, and an onychophoran, representing a closely related group of segmented animals. At least one ortholog of Ten-m/odz in each of these species is expressed in the form of transverse segmental stripes in the ectoderm of forming and newly formed segments – a characteristic of genes involved in segmentation.ConclusionsThe new expression data support the idea that Ten-m orthologs after all may be involved in panarthropod segmentation.

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