Expression attenuation as a mechanism of robustness against gene duplication.
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ABSTRACT:
SUBMITTER: Ascencio D
PROVIDER: S-EPMC7970654 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We study the effects of non-determinism and gene duplication on the structure of genotype-phenotype (GP) maps by introducing a non-deterministic version of the Polyomino self-assembly model. This model has previously been used in a variety of contexts to model the assembly and evolution of protein quaternary structure. Firstly, we show the limit of the current deterministic paradigm which leads to built-in anti-correlation between evolvability and robustness at the genotypic level. We develop a set of metrics to measure structural properties of GP maps in a non-deterministic setting and use them to evaluate the effects of gene duplication and subsequent diversification. Our generalized versions of evolvability and robustness exhibit positive correlation for a subset of genotypes. This positive correlation is only possible because non-deterministic phenotypes can contribute to both robustness and evolvability. Secondly, we show that duplication increases robustness and reduces evolvability initially, but that the subsequent diversification that duplication enables has a stronger, inverse effect, greatly increasing evolvability and reducing robustness relative to their original values.
| S-EPMC8220273 | biostudies-literature
Project description:RNA-sequencing (RNA-seq) is a relatively new technology that lacks standardisation. RNA-seq can be used for Differential Gene Expression (DGE) analysis, however, no consensus exists as to which methodology ensures robust and reproducible results. Indeed, it is broadly acknowledged that DGE methods provide disparate results. Despite obstacles, RNA-seq assays are in advanced development for clinical use but further optimisation will be needed. Herein, five DGE models (DESeq2, voom + limma, edgeR, EBSeq, NOISeq) for gene-level detection were investigated for robustness to sequencing alterations using a controlled analysis of fixed count matrices. Two breast cancer datasets were analysed with full and reduced sample sizes. DGE model robustness was compared between filtering regimes and for different expression levels (high, low) using unbiased metrics. Test sensitivity estimated as relative False Discovery Rate (FDR), concordance between model outputs and comparisons of a 'population' of slopes of relative FDRs across different library sizes, generated using linear regressions, were examined. Patterns of relative DGE model robustness proved dataset-agnostic and reliable for drawing conclusions when sample sizes were sufficiently large. Overall, the non-parametric method NOISeq was the most robust followed by edgeR, voom, EBSeq and DESeq2. Our rigorous appraisal provides information for method selection for molecular diagnostics. Metrics may prove useful towards improving the standardisation of RNA-seq for precision medicine.
| S-EPMC8214188 | biostudies-literature
Project description:BackgroundMost genes are not affected when any transcription factor (TF) is knocked out, indicating that they have robust transcriptional regulatory program. Yet the mechanism underlying robust transcriptional regulatory program is less clear.ResultsHere, we studied the cause and effect of robust transcriptional regulatory program. We found that cooperative TFs in the robust transcriptional regulatory program regulate their common target genes in an activity-redundant fashion, and they are able to compensate for each other's loss. As a result, their target genes are insensitive to their single perturbation. We next revealed that the degree of robustness of transcriptional regulatory program influences gene expression variability. Genes with fragile (unrobust) transcriptional regulatory program under normal growth condition could be readily reprogrammed to significantly modulate gene expression upon changing conditions. They also have high evolutionary rates of gene expression. We further showed that the fragile transcriptional regulatory program is a major source of expression variability.ConclusionWe showed that activity-redundant TFs guarantee the robustness of transcriptional regulatory programs, and the fragility of transcriptional regulatory program plays a major role in gene expression variability. These findings reveal the mechanisms underlying robust transcription and expression variability.
| S-EPMC2792230 | biostudies-literature
Project description:Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for the ubiquity of nonlinear dynamics in gene expression networks, and generate useful guidelines for the design of synthetic gene circuits.
| S-EPMC4833316 | biostudies-literature
Project description:Many biological networks can maintain their function against single gene loss. However, the evolutionary mechanisms responsible for such robustness remain unclear. Here, we demonstrate that antagonistic host-parasite interactions can act as a selective pressure driving the emergence of robustness against gene loss. Using a model of host signaling networks and simulating their coevolution with parasites that interfere with network function, we find that networks evolve both redundancy and specific architectures that allow them to maintain their response despite removal of proteins. We show that when the parasite pressure is removed, subsequent evolution can lead to loss of redundancy while architecture-based robustness is retained. Contrary to intuition, increased parasite virulence hampers evolution of robustness by limiting the generation of population level diversity in the host. However, when robustness emerges under high virulence, it tends to be stronger. These findings predict an increased presence of robustness mechanisms in biological networks operating under parasite interference. Conversely, the presence of such mechanisms could indicate current or past parasite interference.
| S-EPMC2516366 | biostudies-literature
Project description:Phenotype of biological systems needs to be robust against mutation in order to sustain themselves between generations. On the other hand, phenotype of an individual also needs to be robust against fluctuations of both internal and external origins that are encountered during growth and development. Is there a relationship between these two types of robustness, one during a single generation and the other during evolution? Could stochasticity in gene expression have any relevance to the evolution of these types of robustness? Robustness can be defined by the sharpness of the distribution of phenotype; the variance of phenotype distribution due to genetic variation gives a measure of 'genetic robustness', while that of isogenic individuals gives a measure of 'developmental robustness'. Through simulations of a simple stochastic gene expression network that undergoes mutation and selection, we show that in order for the network to acquire both types of robustness, the phenotypic variance induced by mutations must be smaller than that observed in an isogenic population. As the latter originates from noise in gene expression, this signifies that the genetic robustness evolves only when the noise strength in gene expression is larger than some threshold. In such a case, the two variances decrease throughout the evolutionary time course, indicating increase in robustness. The results reveal how noise that cells encounter during growth and development shapes networks' robustness to stochasticity in gene expression, which in turn shapes networks' robustness to mutation. The necessary condition for evolution of robustness, as well as the relationship between genetic and developmental robustness, is derived quantitatively through the variance of phenotypic fluctuations, which are directly measurable experimentally.
| S-EPMC1855988 | biostudies-literature
Project description:BackgroundWith the exponential growth of high-throughput technologies, multiple pathway analysis methods have been proposed to estimate pathway activities from gene expression profiles. These pathway activity inference methods can be divided into two main categories: non-Topology-Based (non-TB) and Pathway Topology-Based (PTB) methods. Although some review and survey articles discussed the topic from different aspects, there is a lack of systematic assessment and comparisons on the robustness of these approaches.ResultsThus, this study presents comprehensive robustness evaluations of seven widely used pathway activity inference methods using six cancer datasets based on two assessments. The first assessment seeks to investigate the robustness of pathway activity in pathway activity inference methods, while the second assessment aims to assess the robustness of risk-active pathways and genes predicted by these methods. The mean reproducibility power and total number of identified informative pathways and genes were evaluated. Based on the first assessment, the mean reproducibility power of pathway activity inference methods generally decreased as the number of pathway selections increased. Entropy-based Directed Random Walk (e-DRW) distinctly outperformed other methods in exhibiting the greatest reproducibility power across all cancer datasets. On the other hand, the second assessment shows that no methods provide satisfactory results across datasets.ConclusionHowever, PTB methods generally appear to perform better in producing greater reproducibility power and identifying potential cancer markers compared to non-TB methods.
| S-EPMC10785356 | biostudies-literature
Project description:BackgroundMendelian inheritance is a fundamental law of genetics. When we consider two genomes in a diploid cell, a heterozygote's phenotype is dominated by a particular homozygote according to the law of dominance. Classical Mendelian dominance is concerned with which proteins are dominant, and is usually based on simple genotype-phenotype relationship in which one gene regulates one phenotype. However, in reality, some interactions between genes can exist, resulting in deviations from Mendelian dominance. Whether and how Mendelian dominance is generalized to the phenotypes of gene expression determined by gene regulatory networks (GRNs) remains elusive.ResultsHere, by using the numerical evolution of diploid GRNs, we discuss whether the dominance of phenotype evolves beyond the classical Mendelian case of one-to-one genotype-phenotype relationship. We examine whether complex genotype-phenotype relationship can achieve Mendelian dominance at the expression level by a pair of haplotypes through the evolution of the GRN with interacting genes. This dominance is defined via a pair of haplotypes that differ from each other but have a common phenotype given by the expression of target genes. We numerically evolve the GRN model for a diploid case, in which two GRN matrices are added to give gene expression dynamics and simulate evolution with meiosis and recombination. Our results reveal that group Mendelian dominance evolves even under complex genotype-phenotype relationship. Calculating the degree of dominance shows that it increases through the evolution, correlating closely with the decrease in phenotypic fluctuations and the increase in robustness to initial noise. We also demonstrate that the dominance of gene expression patterns evolves concurrently. This evolution of group Mendelian dominance and pattern dominance is associated with phenotypic robustness against meiosis-induced genome mixing, whereas sexual recombination arising from the mixing of genomes from the parents further enhances dominance and robustness. Due to this dominance, the robustness to genetic differences increases, while optimal fitness is sustained to a significant difference between the two genomes.ConclusionGroup Mendelian dominance and gene-expression pattern dominance are achieved associated with the increase in phenotypic robustness to noise.
| S-EPMC8182915 | biostudies-literature
Project description:Ehrlichia ruminantium is a tick-borne intracellular pathogen of ruminants that causes heartwater, a disease present in Sub-saharan Africa, islands in the Indian Ocean and the Caribbean, inducing significant economic losses. At present, three avirulent strains of E. ruminantium (Gardel, Welgevonden and Senegal isolates) have been produced by a process of serial passaging in mammalian cells in vitro, but unfortunately their use as vaccines do not offer a large range of protection against other strains, possibly due to the genetic diversity present within the species. So far no genetic basis for virulence attenuation has been identified in any E. ruminantium strain that could offer targets to facilitate vaccine production. Virulence attenuated Senegal strains have been produced twice independently, and require many fewer passages to attenuate than the other strains. We compared the genomes of a virulent and attenuated Senegal strain and identified a likely attenuator gene, ntrX, a global transcription regulator and member of a two-component system that is linked to environmental sensing. This gene has an inverted partial duplicate close to the parental gene that shows evidence of gene conversion in different E. ruminantium strains. The pseudogenisation of the gene in the avirulent Senegal strain occurred by gene conversion from the duplicate to the parent, transferring a 4 bp deletion which is unique to the Senegal strain partial duplicate amongst the wild isolates. We confirmed that the ntrX gene is not expressed in the avirulent Senegal strain by RT-PCR. The inverted duplicate structure combined with the 4 bp deletion in the Senegal strain can explain both the attenuation and the faster speed of attenuation in the Senegal strain relative to other strains of E. ruminantium. Our results identify nrtX as a promising target for the generation of attenuated strains of E. ruminantium by random or directed mutagenesis that could be used for vaccine production.
| S-EPMC9937504 | biostudies-literature
Project description:The molecular pathogenesis of pediatric astrocytomas is still poorly understood. To further understand the genetic abnormalities associated with these tumors, we performed a genome-wide analysis of DNA copy number aberrations in pediatric low-grade astrocytomas by using array-based comparative genomic hybridization. Duplication of the BRAF protooncogene was the most frequent genomic aberration, and tumors with BRAF duplication showed significantly increased mRNA levels of BRAF and a downstream target, CCND1, as compared with tumors without duplication. Furthermore, denaturing HPLC showed that activating BRAF mutations were detected in some of the tumors without BRAF duplication. Similarly, a marked proportion of low-grade astrocytomas from adult patients also had BRAF duplication. Both the stable silencing of BRAF through shRNA lentiviral transduction and pharmacological inhibition of MEK1/2, the immediate downstream phosphorylation target of BRAF, blocked the proliferation and arrested the growth of cultured tumor cells derived from low-grade gliomas. Our findings implicate aberrant activation of the MAPK pathway due to gene duplication or mutation of BRAF as a molecular mechanism of pathogenesis in low-grade astrocytomas and suggest inhibition of the MAPK pathway as a potential treatment.
| S-EPMC2289793 | biostudies-literature