Epistatic interactions alter dynamics of multilocus gene-for-gene coevolution.
Ontology highlight
ABSTRACT:
SUBMITTER: Fenton A
PROVIDER: S-EPMC2065793 | biostudies-literature | 2007 Nov
REPOSITORIES: biostudies-literature
Publications
Epistatic interactions alter dynamics of multilocus gene-for-gene coevolution.
Fenton Andy A Brockhurst Michael A MA
PloS one 20071107 11
Fitness costs associated with resistance or virulence genes are thought to play a key role in determining the dynamics of gene-for-gene (GFG) host-parasite coevolution. However, the nature of interactions between fitness effects of multiple resistance or virulence genes (epistasis) has received less attention. To examine effects of the functional form of epistasis on the dynamics of GFG host-parasite coevolution we modified a classic multilocus GFG model framework. We show that the type of epist ...[more]
Similar Datasets
Project description:BACKGROUND: Epistasis, i.e., the interaction of alleles at different loci, is thought to play a central role in the formation and progression of complex diseases. The complexity of disease expression should arise from a complex network of epistatic interactions involving multiple genes. METHODOLOGY: We develop a general model for testing high-order epistatic interactions for a complex disease in a case-control study. We incorporate the quantitative genetic theory of high-order epistasis into the setting of cases and controls sampled from a natural population. The new model allows the identification and testing of epistasis and its various genetic components. CONCLUSIONS: Simulation studies were used to examine the power and false positive rates of the model under different sampling strategies. The model was used to detect epistasis in a case-control study of inflammatory bowel disease, in which five SNPs at a candidate gene were typed, leading to the identification of a significant three-locus epistasis.
| S-EPMC2909900 | biostudies-literature
Project description:The treatment of complex diseases often relies on combinatorial therapy, a strategy where drugs are used to target multiple genes simultaneously. Promising candidate genes for combinatorial perturbation often constitute epistatic genes, i.e., genes which contribute to a phenotype in a non-linear fashion. Experimental identification of the full landscape of genetic interactions by perturbing all gene combinations is prohibitive due to the exponential growth of testable hypotheses. Here we present a model for the inference of pairwise epistatic, including synthetic lethal, gene interactions from siRNA-based perturbation screens. The model exploits the combinatorial nature of siRNA-based screens resulting from the high numbers of sequence-dependent off-target effects, where each siRNA apart from its intended target knocks down hundreds of additional genes. We show that conditional and marginal epistasis can be estimated as interaction coefficients of regression models on perturbation data. We compare two methods, namely glinternet and xyz, for selecting non-zero effects in high dimensions as components of the model, and make recommendations for the appropriate use of each. For data simulated from real RNAi screening libraries, we show that glinternet successfully identifies epistatic gene pairs with high accuracy across a wide range of relevant parameters for the signal-to-noise ratio of observed phenotypes, the effect size of epistasis and the number of observations per double knockdown. xyz is also able to identify interactions from lower dimensional data sets (fewer genes), but is less accurate for many dimensions. Higher accuracy of glinternet, however, comes at the cost of longer running time compared to xyz. The general model is widely applicable and allows mining the wealth of publicly available RNAi screening data for the estimation of epistatic interactions between genes. As a proof of concept, we apply the model to search for interactions, and potential targets for treatment, among previously published sets of siRNA perturbation screens on various pathogens. The identified interactions include both known epistatic interactions as well as novel findings.
| S-EPMC8277066 | biostudies-literature
Project description:The fitness effect of mutations can be influenced by their interactions with the environment, other mutations, or both. Previously, we constructed 32 ( = 2⁵) genotypes that comprise all possible combinations of the first five beneficial mutations to fix in a laboratory-evolved population of Escherichia coli. We found that (i) all five mutations were beneficial for the background on which they occurred; (ii) interactions between mutations drove a diminishing returns type epistasis, whereby epistasis became increasingly antagonistic as the expected fitness of a genotype increased; and (iii) the adaptive landscape revealed by the mutation combinations was smooth, having a single global fitness peak. Here we examine how the environment influences epistasis by determining the interactions between the same mutations in two alternative environments, selected from among 1,920 screened environments, that produced the largest increase or decrease in fitness of the most derived genotype. Some general features of the interactions were consistent: mutations tended to remain beneficial and the overall pattern of epistasis was of diminishing returns. Other features depended on the environment; in particular, several mutations were deleterious when added to specific genotypes, indicating the presence of antagonistic interactions that were absent in the original selection environment. Antagonism was not caused by consistent pleiotropic effects of individual mutations but rather by changing interactions between mutations. Our results demonstrate that understanding adaptation in changing environments will require consideration of the combined effect of epistasis and pleiotropy across environments.
| S-EPMC3616912 | biostudies-literature
Project description:Reduced activity of two genes in combination often has a more detrimental effect than expected. Such epistatic interactions not only occur when genes are mutated but also due to variation in gene expression, including among isogenic individuals in a controlled environment. We hypothesized that these 'epigenetic' epistatic interactions could place important constraints on the evolution of gene expression. Consistent with this, we show here that yeast genes with many epistatic interaction partners typically show low expression variation among isogenic individuals and low variation across different conditions. In addition, their expression tends to remain stable in response to the accumulation of mutations and only diverges slowly between strains and species. Yeast promoter architectures, the retention of gene duplicates, and the divergence of expression between humans and chimps are also consistent with selective pressure to reduce the likelihood of harmful epigenetic epistatic interactions. Based on these and previous analyses, we propose that the tight regulation of epistatic interaction network hubs makes an important contribution to the maintenance of a robust, 'canalized' phenotype. Moreover, that epigenetic epistatic interactions may contribute substantially to fitness defects when single genes are deleted.
| S-EPMC3588906 | biostudies-other
Project description:Protein evolution depends on the adaptation of these molecules to different functional challenges. This occurs by tuning their biochemical, biophysical, and structural traits through the accumulation of mutations. While the role of protein dynamics in biochemistry is well recognized, there are limited examples providing experimental evidence of the optimization of protein dynamics during evolution. Here we report an NMR study of four variants of the CTX-M β-lactamases, in which the interplay of two mutations outside the active site enhances the activity against a cephalosporin substrate, ceftazidime. The crystal structures of these enzymes do not account for this activity enhancement. By using NMR, here we show that the combination of these two mutations increases the backbone dynamics in a slow timescale and the exposure to the solvent of an otherwise buried β-sheet. The two mutations located in this β-sheet trigger conformational changes in loops located at the opposite side of the active site. We postulate that the most active variant explores alternative conformations that enable binding of the more challenging substrate ceftazidime. The impact of the mutations in the dynamics is context-dependent, in line with the epistatic effect observed in the catalytic activity of the different variants. These results reveal the existence of a dynamic network in CTX-M β-lactamases that has been exploited in evolution to provide a net gain-of-function, highlighting the role of alternative conformations in protein evolution.
| S-EPMC9547502 | biostudies-literature
Project description:BackgroundCoevolution has been used to identify and predict interactions and functional relationships between proteins of many different organisms including humans. Current efforts in annotating the human genome increasingly show that non-coding DNA sequence has important functional and regulatory interactions. Furthermore, regulatory elements do not necessarily reside in close proximity of the coding region for their target genes.ResultsWe characterize coevolution as it appears in locus-gene interactions in the human genome, focusing on expression Quantitative Trait - Locus (eQTL) interactions. Our results show that in these interactions the conservation status of the loci is predictive of the conservation status of their target genes. Furthermore, comparing the phylogenetic histories of intra-chromosomal pairs of loci and transcription start sites, we find that pairs that appear coevolved are enriched for cis-eQTL interactions. Exploring this property we found that coevolution might be useful in prioritizing association tests in cis-eQTL detection.ConclusionsThe relationship between the conservation status of pairs of loci and protein coding transcription start sites reveal correlations with regulatory interactions. Pairs that appear coevolved are enriched for intra-chromosomal regulatory interactions, thus our results suggest that measures of coevolution can be useful for prediction and detection of new interactions. Measures of coevolution are genome-wide and could potentially be used to prioritize the detection of distant or inter-chromosomal interactions such as trans-eQTL interactions in the human genome.
| S-EPMC6419833 | biostudies-literature
Project description:The inability of native Saccharomyces cerevisiae to convert xylose from plant biomass into biofuels remains a major challenge for the production of renewable bioenergy. Despite extensive knowledge of the regulatory networks controlling carbon metabolism in yeast, little is known about how to reprogram S. cerevisiae to ferment xylose at rates comparable to glucose. Here we combined genome sequencing, proteomic profiling, and metabolomic analyses to identify and characterize the responsible mutations in a series of evolved strains capable of metabolizing xylose aerobically or anaerobically. We report that rapid xylose conversion by engineered and evolved S. cerevisiae strains depends upon epistatic interactions among genes encoding a xylose reductase (GRE3), a component of MAP Kinase (MAPK) signaling (HOG1), a regulator of Protein Kinase A (PKA) signaling (IRA2), and a scaffolding protein for mitochondrial iron-sulfur (Fe-S) cluster biogenesis (ISU1). Interestingly, the mutation in IRA2 only impacted anaerobic xylose consumption and required the loss of ISU1 function, indicating a previously unknown connection between PKA signaling, Fe-S cluster biogenesis, and anaerobiosis. Proteomic and metabolomic comparisons revealed that the xylose-metabolizing mutant strains exhibit altered metabolic pathways relative to the parental strain when grown in xylose. Further analyses revealed that interacting mutations in HOG1 and ISU1 unexpectedly elevated mitochondrial respiratory proteins and enabled rapid aerobic respiration of xylose and other non-fermentable carbon substrates. Our findings suggest a surprising connection between Fe-S cluster biogenesis and signaling that facilitates aerobic respiration and anaerobic fermentation of xylose, underscoring how much remains unknown about the eukaryotic signaling systems that regulate carbon metabolism.
| S-EPMC5065143 | biostudies-literature
Project description:OBJECTIVE:Several confirmed genetic susceptibility loci for lupus have been described. To date, no clear evidence for genetic epistasis in lupus has been established. The aim of this study was to test for gene-gene interactions in a number of known lupus susceptibility loci. METHODS:Eighteen single-nucleotide polymorphisms tagging independent and confirmed lupus susceptibility loci were genotyped in a set of 4,248 patients with lupus and 3,818 normal healthy control subjects of European descent. Epistasis was tested by a 2-step approach using both parametric and nonparametric methods. The false discovery rate (FDR) method was used to correct for multiple testing. RESULTS:We detected and confirmed gene-gene interactions between the HLA region and CTLA4, IRF5, and ITGAM and between PDCD1 and IL21 in patients with lupus. The most significant interaction detected by parametric analysis was between rs3131379 in the HLA region and rs231775 in CTLA4 (interaction odds ratio 1.19, Z = 3.95, P = 7.8 × 10(-5) [FDR ?0.05], P for multifactor dimensionality reduction = 5.9 × 10(-45)). Importantly, our data suggest that in patients with lupus, the presence of the HLA lupus risk alleles in rs1270942 and rs3131379 increases the odds of also carrying the lupus risk allele in IRF5 (rs2070197) by 17% and 16%, respectively (P = 0.0028 and P = 0.0047, respectively). CONCLUSION:We provide evidence for gene-gene epistasis in systemic lupus erythematosus. These findings support a role for genetic interaction contributing to the complexity of lupus heritability.
| S-EPMC3268866 | biostudies-literature
Project description:Breast cancer cells recruit surrounding stromal cells, such as cancer-associated fibroblasts (CAFs), to remodel their extracellular matrix (ECM) and promote invasive tumor growth. Two major ECM components, fibronectin (Fn) and collagen I (Col I), are known to interact with each other to regulate cellular behavior. In this study, we seek to understand how Fn and Col I interplay and promote a dysregulated signaling pathway to facilitate tumor progression. Specifically, we investigated the evolution of tumor-conditioned stromal ECM composition, structure, and relaxation. Furthermore, we assessed how evolving Fn-Col I interactions gradually affected pro-angiogenic signaling. Our data first indicate that CAFs initially assembled a strained, viscous, and unfolded Fn matrix. This early altered Fn matrix was later remodeled into a thick Col I-rich matrix that was characteristic of a dense tumor mass. Next, our results suggest that this ECM remodeling was primarily mediated by matrix metalloproteinases (MMPs). This MMP activity caused profound structural and mechanical changes in the developing ECM, which then modified vascular endothelial growth factor (VEGF) secretion by CAFs and matrix sequestration. Collectively, these findings enhance our understanding of the mechanisms by which Fn and Col I synergistically interplay in promoting a sustained altered signaling cascade to remodel the breast tumor stroma for invasive breast tumor growth.
| S-EPMC5293676 | biostudies-other
Project description:Microbes evolve within complex ecological communities where biotic interactions impact both individual cells and the environment as a whole. Here we examine how cellular regulation in the marine cyanobacterium Prochlorococcus is influenced by a heterotrophic bacterium, Alteromonas macleodii, under different light conditions. We monitored the transcriptome of Prochlorococcus, grown either alone or in coculture, across a diel light:dark cycle and under the stress of extended darkness-a condition that cells would experience when mixed below the ocean's euphotic zone. More Prochlorococcus transcripts exhibited 24-h periodic oscillations in coculture than in pure culture, both over the normal diel cycle and after the shift to extended darkness. This demonstrates that biotic interactions, and not just light, can affect timing mechanisms in Prochlorococcus, which lacks a self-sustaining circadian oscillator. The transcriptomes of replicate pure cultures of Prochlorococcus lost their synchrony within 5 h of extended darkness and reflected changes in stress responses and metabolic functions consistent with growth cessation. In contrast, when grown with Alteromonas, replicate Prochlorococcus transcriptomes tracked each other for at least 13 h in the dark and showed signs of continued biosynthetic and metabolic activity. The transcriptome patterns suggest that the heterotroph may be providing energy or essential biosynthetic substrates to Prochlorococcus in the form of organic compounds, sustaining this autotroph when it is deprived of solar energy. Our findings reveal conditions where mixotrophic metabolism may benefit marine cyanobacteria and highlight new impacts of community interactions on basic Prochlorococcus cellular processes. IMPORTANCEProchlorococcus is the most abundant photosynthetic organism on the planet. These cells play a central role in the physiology of surrounding heterotrophs by supplying them with fixed organic carbon. It is becoming increasingly clear, however, that interactions with heterotrophs can affect autotrophs as well. Here we show that such interactions have a marked impact on the response of Prochlorococcus to the stress of extended periods of darkness, as reflected in transcriptional dynamics. These data suggest that diel transcriptional rhythms within Prochlorococcus, which are generally considered to be strictly under the control of light quantity, quality, and timing, can also be influenced by biotic interactions. Together, these findings provide new insights into the importance of microbial interactions on Prochlorococcus physiology and reveal conditions where heterotroph-derived compounds may support autotrophs-contrary to the canonical autotroph-to-heterotroph trophic paradigm.
| S-EPMC5974335 | biostudies-literature