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Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis represents one of the most consistent pathophysiological findings in depressive disorders. Cortisol signaling is affected by proteins that mediate its cellular responses or alters its availability to mineralocorticoid and glucocorticoid receptors. In our study, we evaluated candidate genes that may influence the risk for depression and suicide due to its involvement in cortisol signaling. The aim of the study was to assess whether the genotypes of these genes are associated with the risk for depression, severity of depressive symptoms, suicidal ideation, and suicide attempts. And whether there is interaction between genes and early-life stress. In this study, 100 healthy controls and 140 individuals with depression were included. The subjects were clinically assessed using the 21-item GRID-Hamilton questionnaires (GRID-HAMD-21), Beck Scale for Suicidal Ideation (BSI), and the Childhood Trauma Questionnaire (CTQ). A robust multifactorial dimensionality reduction analysis was used to characterize the interactions between the genes HSD11B1 , NR3C1, NR3C2 , and MDR1 and early-life stress. It was found a significant association of the heterozygous genotype of the MDR1 gene rs1128503 polymorphism with reduced risk of at least one suicide attempt (OR: 0.08, p = 0.003*) and a reduction in the number of suicide attempts (β = −0.79, p = 0.006*). Furthermore, it was found that the MDR1 rs1228503 and NR3C2 rs2070951 genes interact with early-life stress resulting in a strong association with depression (p = 0.001). Our findings suggest that polymorphisms in the MDR1 and NR3C2 genes and their interaction with childhood trauma may be important biomarkers for depression and suicidal behaviors. [ABSTRACT FROM AUTHOR]

A simple agent‐based model is presented that produces results matching the experimental data found by Lenski's group for ≤50,000 generations of Escherichia coli bacteria under continuous selective pressure. Although various mathematical models have been devised previously to model the Lenski data, the present model has advantages in terms of overall simplicity and conceptual accessibility. The model also clearly illustrates a number of features of the evolutionary process that are otherwise not obvious, such as the roles of epistasis and historical contingency in adaptation and why evolution is time irreversible ('Dollo's law'). The reason for this irreversibility is that genomes become increasingly integrated or organized, and this organization becomes a novel selective factor itself, against which future generations must compete. Selection for integrated or synergistic networks, systems or sets of mutations or traits, not for individual mutations, confers the main adaptive advantage. The result is a punctuated form of evolution that follows a logarithmic occurrence probability, in which evolution proceeds very quickly when interactomes begin to form but which slows as interactomes become more robust and the difficulty of integrating new mutations increases. Sufficient parameters exist in the game to suggest not only how equilibrium or stasis is reached but also the conditions in which it will be punctuated, the factors governing the rate at which genomic organization occurs and novel traits appear, and how population size, genome size and gene variability affect these. [ABSTRACT FROM AUTHOR]

The expression of Neuritin-1 (NRN1), a neurotrophic factor crucial for neurodevelopment and synaptic plasticity, is enhanced by the Brain Derived Neurotrophic Factor (BDNF). Although the receptor of NRN1 remains unclear, it is suggested that NRN1's activation of the insulin receptor (IR) pathway promotes the transcription of the calcium voltage-gated channel subunit alpha1 C (CACNA1C). These three genes have been independently associated with schizophrenia (SZ) risk, symptomatology, and brain differences. However, research on how they synergistically modulate these phenotypes is scarce. We aimed to study whether the genetic epistasis between these genes affects the risk and clinical presentation of the disorder via its effect on brain structure. First, we tested the epistatic effect of NRN1 and BDNF or CACNA1C on (i) the risk for SZ, (ii) clinical symptoms severity and functionality (onset, PANSS, CGI and GAF), and (iii) brain cortical structure (thickness, surface area and volume measures estimated using FreeSurfer) in a sample of 86 SZ patients and 89 healthy subjects. Second, we explored whether those brain clusters influenced by epistatic effects mediate the clinical profiles. Although we did not find a direct epistatic impact on the risk, our data unveiled significant effects on the disorder's clinical presentation. Specifically, the NRN1-rs10484320 x BDNF-rs6265 interplay influenced PANSS general psychopathology, and the NRN1-rs4960155 x CACNA1C-rs1006737 interaction affected GAF scores. Moreover, several interactions between NRN1 SNPs and BDNF-rs6265 significantly influenced the surface area and cortical volume of the frontal, parietal, and temporal brain regions within patients. The NRN1-rs10484320 x BDNF-rs6265 epistasis in the left lateral orbitofrontal cortex fully mediated the effect on PANSS general psychopathology. Our study not only adds clinical significance to the well-described molecular relationship between NRN1 and BDNF but also underscores the utility of deconstructing SZ into biologically validated brain-imaging markers to explore their mediation role in the path from genetics to complex clinical manifestation. [ABSTRACT FROM AUTHOR]

Epistasis is a ubiquitous phenomenon in genetics, and is considered to be one of main factors in current efforts to unveil missing heritability of complex diseases. Simulation data is crucial for evaluating epistasis detection tools in genome‐wide association studies (GWAS). Existing simulators normally suffer from two limitations: absence of support for high‐order epistasis models containing multiple single nucleotide polymorphisms (SNPs), and inability to generate simulation SNP data independently. In this study, we proposed a simulator SimHOEPI, which is capable of calculating penetrance tables of high‐order epistasis models depending on either prevalence or heritability, and uses a resampling strategy to generate simulation data independently. Highlights of SimHOEPI are the preservation of realistic minor allele frequencies in sampling data, the accurate calculation and embedding of high‐order epistasis models, and acceptable simulation time. A series of experiments were carried out to verify these properties from different aspects. Experimental results show that SimHOEPI can generate simulation SNP data independently with high‐order epistasis models, implying that it might be an alternative simulator for GWAS. [ABSTRACT FROM AUTHOR]

Accurate models describing the relationship between genotype and phenotype are necessary in order to understand and predict how mutations to biological sequences affect the fitness and evolution of living organisms. The apparent abundance of epistasis (genetic interactions), both between and within genes, complicates this task and how to build mechanistic models that incorporate epistatic coefficients (genetic interaction terms) is an open question. The Walsh-Hadamard transform represents a rigorous computational framework for calculating and modeling epistatic interactions at the level of individual genotypic values (known as genetical, biological or physiological epistasis), and can therefore be used to address fundamental questions related to sequence-to-function encodings. However, one of its main limitations is that it can only accommodate two alleles (amino acid or nucleotide states) per sequence position. In this paper we provide an extension of the Walsh-Hadamard transform that allows the calculation and modeling of background-averaged epistasis (also known as ensemble epistasis) in genetic landscapes with an arbitrary number of states per position (20 for amino acids, 4 for nucleotides, etc.). We also provide a recursive formula for the inverse matrix and then derive formulae to directly extract any element of either matrix without having to rely on the computationally intensive task of constructing or inverting large matrices. Finally, we demonstrate the utility of our theory by using it to model epistasis within both simulated and empirical multiallelic fitness landscapes, revealing that both pairwise and higher-order genetic interactions are enriched between physically interacting positions. Author summary: An important question in genetics is how the effects of mutations combine to alter phenotypes. Genetic interactions (epistasis) describe non-additive effects of pairs of mutations, but can also involve higher-order (three- and four-way etc.) combinations. Quantifying higher-order interactions is experimentally very challenging requiring a large number of measurements. Techniques based on deep mutational scanning (DMS) represent valuable sources of data to study epistasis. However, the best way to extract the relevant pairwise and higher-order epistatic coefficients (genetic interaction terms) from this data for the task of phenotypic prediction remains an unresolved problem. The Walsh-Hadamard transform represents a rigorous computational framework for calculating and modeling epistatic interactions at the level of individual genotypic values. Critically, this formalism currently only allows for two alleles (amino acid or nucleotide states) per sequence position, hampering applications in more biologically realistic scenarios. Here we present an extension of the Walsh-Hadamard transform that overcomes this limitation and demonstrate the utility of our theory by using it to model epistasis within both simulated and empirical multiallelic genetic landscapes. [ABSTRACT FROM AUTHOR]

Much of evolutionary theory is predicated on assumptions about the relative importance of simple additive versus complex epistatic genetic architectures. Previous work suggests traits strongly associated with fitness will lack additive genetic variation, whereas traits less strongly associated with fitness are expected to exhibit more additive genetic variation. We use a quantitative genetics method, line cross analysis, to infer genetic architectures that contribute to trait divergence. By parsing over 1,600 datasets by trait type, clade, and cross divergence, we estimated the relative importance of epistasis across the tree of life. In our comparison between life-history traits and morphological traits, we found greater epistatic contributions to life-history traits. Our comparison between plants and animals showed that animals have more epistatic contribution to trait divergence than plants. In our comparison of within-species versus between-species crosses, we found that only animals exhibit a greater epistatic contribution to trait divergence as divergence increases. While many scientists have argued that epistasis is ultimately of little importance, our results show that epistasis underlies much of trait divergence and must be accounted for in theory and practical applications like domestication, conservation breeding design, and understanding complex diseases. [ABSTRACT FROM AUTHOR]

Although genome-wide association studies have identified multiple Alzheimer's disease (AD)-associated loci by selecting the main effects of individual single-nucleotide polymorphisms (SNPs), the interpretation of genetic variance in AD is limited. Based on the linear regression method, we performed genome-wide SNP-SNP interaction on cerebrospinal fluid Aβ 42 to identify potential genetic epistasis implicated in AD, with age, gender, and diagnosis as covariates. A GPU-based method was used to address the computational challenges posed by the analysis of epistasis. We found 368 SNP pairs to be statistically significant, and highly significant SNP-SNP interactions were identified between the marginal main effects of SNP pairs, which explained a relatively high variance at the Aβ 42 level. Our results replicated 100 previously reported AD-related genes and 5 gene-gene interaction pairs of the protein-protein interaction network. Our bioinformatics analyses provided preliminary evidence that the 5-overlapping gene-gene interaction pairs play critical roles in inducing synaptic loss and dysfunction, thereby leading to memory decline and cognitive impairment in AD-affected brains. [ABSTRACT FROM AUTHOR]

miR-137 is a highly conserved brain-enriched microRNA (miRNA) that has been associated with neuronal function and proliferation. Here, we show that Drosophila miR-137 null mutants display increased body weight with enhanced triglyceride content and decreased locomotor activity. In addition, when challenged by nutrient deprivation, miR-137 mutants exhibit reduced motivation to feed and prolonged survival. We show through genetic epistasis and rescue experiments that this starvation resistance is due to a disruption in insulin signaling. Our studies further show that miR-137 null mutants exhibit a drastic reduction in levels of the phosphorylated/activated insulin receptor, InR (InR-P). We investigated if this is due to the predicted miR-137 target, Protein Tyrosine Phosphatase 61F (PTP61F), ortholog of mammalian TC-PTP/PTP1B, which are known to dephosphorylate InR-P. Indeed, levels of an endogenously tagged GFP-PTP61F are significantly elevated in miR-137 null mutants, and we show that overexpression of PTP61F alone is sufficient to mimic many of the metabolic phenotypes of miR-137 mutants. Finally, we knocked-down elevated levels of PTP61F in the miR-137 null mutant background and show that this rescues levels of InR-P, restores normal body weight and triglyceride content, starvation sensitivity, as well as attenuates locomotor and starvation-induced feeding defects. Our study supports a model in which miR-137 is critical for dampening levels of PTP61F, thereby maintaining normal insulin signaling and energy homeostasis. [ABSTRACT FROM AUTHOR]

A fundamental problem in tissue morphogenesis is identifying how subcellular signaling regulates mesoscale organization of tissues. The primary cilium is a paradigmatic organelle for compartmentalized subcellular signaling. How signaling emanating from cilia orchestrates tissue organization—especially, the role of cilia-generated effectors in mediating diverse morpho-phenotypic outcomes—is not well understood. In the hedgehog pathway, bifunctional GLI transcription factors generate both GLI-activators (GLI-A) and GLI-repressors (GLI-R). The formation of GLI-A/GLI-R requires cilia. However, how these counterregulatory effectors coordinate cilia-regulated morphogenetic pathways is unclear. Here we determined GLI-A/GLI-R requirements in phenotypes arising from lack of hedgehog pathway repression (derepression) during mouse neural tube and skeletal development. We studied hedgehog pathway repression by the GPCR GPR161, and the ankyrin repeat protein ANKMY2 that direct cAMP/protein kinase-A signaling by cilia in GLI-R generation. We performed genetic epistasis between Gpr161 or Ankmy2 mutants, and Gli2/Gli3 knockouts, Gli3R knock-in and knockout of Smoothened, the hedgehog pathway transducer. We also tested the role of cilia-generated signaling using a Gpr161 ciliary localization knock-in mutant that is cAMP signaling competent. We found that the cilia-dependent derepression phenotypes arose in three modes: lack of GLI-R only, excess GLI-A formation only, or dual regulation of either lack of GLI-R or excess GLI-A formation. These modes were mostly independent of Smoothened. The cAMP signaling-competent non-ciliary Gpr161 knock-in recapitulated Gpr161 loss-of-function tissue phenotypes solely from lack of GLI-R only. Our results show complex tissue-specific GLI-effector requirements in morphogenesis and point to tissue-specific GLI-R thresholds generated by cilia in hedgehog pathway repression. Broadly, our study sets up a conceptual framework for rationalization of different modes of signaling generated by the primary cilium in mediating morphogenesis in diverse tissues. Author summary: The primary cilium is a minute cellular compartment that functions like an antenna in regulating cellular signaling. Defects in cilia and ciliary signaling disrupts tissue organization. However, how signaling generated by the cilia orchestrates tissue organization is not well understood. The hedgehog pathway is a developmental pathway that is dependent on cilia. In the hedgehog pathway, the GLI transcription factors generate mutually exclusive activators or repressors. The formation of both activators and repressors requires cilia. However, how cilia coordinate these factors in regulating tissue organization is unclear. Here, we studied defects in neural tube and skeletal development in the mouse that we described to result from lack of the ciliary repression of the hedgehog pathway. By studying whether the cilia generated activators or repressors regulated the tissue outcomes, we uncovered distinct modes by which ciliary outputs finally coordinated tissue organization. These modes showed to be from lack of the repressor only, excess activator only, or from dual regulation by lack of the repressor or activator. Lack of cilium specific trafficking also predominantly regulated tissue outcomes from lack of repressor only. Overall, our study uncovers general principles by which primary cilia organize tissue architecture. [ABSTRACT FROM AUTHOR]

Within biology, there have been long-standing goals to understand how traits impact fitness, determine the degree of adaptation, and predict responses to selection. One key step in answering these questions is to study the mode of gene action or genetic architecture of traits. The genetic architecture underlying a trait will ultimately determine whether selection can lead to a change in the phenotype. Theoretical and empirical research have shown that additive architectures are most responsive to selection. The genus Solanum offers a unique system to quantify the genetic architecture of traits. Crosses between Solanum pennellii and S. lycopersicum, which have evolved unique adaptive traits for very different environments, offer an opportunity to investigate the genetic architecture of a variety of morphological traits that often are not variable within species. We generated cohorts between strains of these two Solanum species and collected phenotypic data for eight morphological traits. The genetic architectures underlying these traits were estimated using an information-theoretic approach to line cross analysis. By estimating the genetic architectures of these traits, we were able to show a key role for maternal and epistatic effects and infer the accessibility of these traits to selection. [ABSTRACT FROM AUTHOR]

Coxsackievirus A24 (CV-A24) is a human enterovirus that causes acute flaccid paralysis. However, a Coxsackievirus A24 variant (CV-A24v) is the most common cause of eye infections. The causes of these variable pathogenicity and tissue tropism remain unclear. To elucidate the phylodynamics of CV-A24 and CV-A24v, we analyzed a dataset of 66 strains using Bayesian phylodynamic approach, along with detailed sequence variation and epistatic analyses. Six CV-A24 strains available in GenBank and 60 CV-A24v strains, including 11 Taiwanese strains, were included in this study. The results revealed striking differences between CV-A24 and CV-A24v exhibiting long terminal branches in the phylogenetic tree, respectively. CV-A24v presented distinct ladder-like clustering, indicating immune escape mechanisms. Notably, 10 genetic recombination events in the 3D regions were identified. Furthermore, 11 missense mutation signatures were detected to differentiate CV-A24 and CV-A24v; among these mutations, the F810Y substitution may significantly affect the secondary structure of the GH loop of VP1 and subsequently affect the epitopes of the capsid proteins. In conclusion, this study provides critical insights into the evolutionary dynamics and epidemiological characteristics of CV-A24 and CV-A24v, and highlights the differences in viral evolution and tissue tropism. [ABSTRACT FROM AUTHOR]

The evolvability of proteins stems from their underlying biochemical, biophysical, and genetic properties. Initial states appear to drive the adaptability of proteins. There is mounting evidence, from evolutionary trajectories, that the availability of adaptive mutations is greatly influenced by epistasis. The underlying molecular mechanisms remain largely unexplored, however. Emerging techniques in single-molecule studies are revolutionizing the exploration of molecular heterogeneity in protein ensembles, a cryptic determinant of evolvability, providing a better understanding of this phenomenon. The plethora of biological functions that sustain life is rooted in the remarkable evolvability of proteins. An emerging view highlights the importance of a protein's initial state in dictating evolutionary success. A deeper comprehension of the mechanisms that govern the evolvability of these initial states can provide invaluable insights into protein evolution. In this review, we describe several molecular determinants of protein evolvability, unveiled by experimental evolution and ancestral sequence reconstruction studies. We further discuss how genetic variation and epistasis can promote or constrain functional innovation and suggest putative underlying mechanisms. By establishing a clear framework for these determinants, we provide potential indicators enabling the forecast of suitable evolutionary starting points and delineate molecular mechanisms in need of deeper exploration. [ABSTRACT FROM AUTHOR]

A half-diallel cross study of seven melon inbred lines was carried out. The seven parents and their 21 F1 hybrids were evaluated for precocity of maturity, average weight per fruit, and fruit quality (fruit size, rind thickness, and soluble solids). The Diallel analysis was investigated for breeding values of these melon genotypes via general and specific combining ability, relationships between general and specific combining ability, and heterosis for the evaluated traits. The analysis of variance of the traits evaluated indicated highly significant differences among genotypes, suggesting the presence of adequate genetic variation for breeding. Additive genetic effects were most important with respect to fruit weight, while genetic dominance and epistasis effects mainly controlled fruit quality traits (fruit size, rind thickness, and TSS). Parent 1 (P1) and parent 3 (P3) had significant positive general combining ability effects for fruit weight. Also, P3 had positive general combining ability effects for fruit length and diameter, and cavity diameter. P3 was found to show maximum significant GCA in the desirable direction for all the traits except for TSS. Evaluation of heterosis (%) revealed that hybrid P1 × P3 can be considered as the best-performing hybrid for average fruit weight, TSS, and precocity, which also exhibited the highest positive and significant SCA effect for these traits. These results suggested that, among the melon genotypes studied, there is the potential to generate superior new varieties in hybrid production. [ABSTRACT FROM AUTHOR]

Mapping genetic variations to phenotypic variations poses a significant challenge, as mutations often combine unexpectedly, diverging from assumed additive effects even in the same environment. These interactions are known as epistasis or genetic interactions. Sign epistasis, as a specific type of epistasis, involves a complete reversal of mutation effects within altered genetic backgrounds, presenting a substantial hurdle to phenotype prediction. Despite its importance, there is a limited systematic overview of the mechanistic causes of sign epistasis. This review explores the mechanistic causes, highlighting its occurrence in signalling cascades, peaked fitness landscapes, and physical interactions. Moving beyond theoretical discussions, we delve into the practical applications of sign epistasis in agriculture, evolution, and antibiotic resistance. In conclusion, this review aims to enhance the comprehension of sign epistasis and molecular dynamics, anticipating future endeavours in systematic biology engineering that leverage the knowledge of sign epistasis. [ABSTRACT FROM AUTHOR]

Oriented cell divisions balance self-renewal and differentiation in stratified epithelia such as the skin epidermis. During peak epidermal stratification, the distribution of division angles among basal keratinocyte progenitors is bimodal, with planar and perpendicular divisions driving symmetric and asymmetric daughter cell fates, respectively. An apically restricted, evolutionarily conserved spindle orientation complex that includes the scaffolding protein LGN/Pins/Gpsm2 plays a central role in promoting perpendicular divisions and stratification, but why only a subset of cell polarize LGN is not known. Here, we demonstrate that the LGN paralog, AGS3/Gpsm1, is a novel negative regulator of LGN and inhibits perpendicular divisions. Static and ex vivo live imaging reveal that AGS3 overexpression displaces LGN from the apical cortex and increases planar orientations, while AGS3 loss prolongs cortical LGN localization and leads to a perpendicular orientation bias. Genetic epistasis experiments in double mutants confirm that AGS3 operates through LGN. Finally, clonal lineage tracing shows that LGN and AGS3 promote asymmetric and symmetric fates, respectively, while also influencing differentiation through delamination. Collectively, these studies shed new light on how spindle orientation influences epidermal stratification. [ABSTRACT FROM AUTHOR]

Leveraging linkage disequilibrium (LD) patterns as representative of population substructure enables the discovery of additive association signals in genome-wide association studies (GWASs). Standard GWASs are well-powered to interrogate additive models; however, new approaches are required for invesigating other modes of inheritance such as dominance and epistasis. Epistasis, or non-additive interaction between genes, exists across the genome but often goes undetected because of a lack of statistical power. Furthermore, the adoption of LD pruning as customary in standard GWASs excludes detection of sites that are in LD but might underlie the genetic architecture of complex traits. We hypothesize that uncovering long-range interactions between loci with strong LD due to epistatic selection can elucidate genetic mechanisms underlying common diseases. To investigate this hypothesis, we tested for associations between 23 common diseases and 5,625,845 epistatic SNP-SNP pairs (determined by Ohta's D statistics) in long-range LD (>0.25 cM). Across five disease phenotypes, we identified one significant and four near-significant associations that replicated in two large genotype-phenotype datasets (UK Biobank and eMERGE). The genes that were most likely involved in the replicated associations were (1) members of highly conserved gene families with complex roles in multiple pathways, (2) essential genes, and/or (3) genes that were associated in the literature with complex traits that display variable expressivity. These results support the highly pleiotropic and conserved nature of variants in long-range LD under epistatic selection. Our work supports the hypothesis that epistatic interactions regulate diverse clinical mechanisms and might especially be driving factors in conditions with a wide range of phenotypic outcomes. This study investigates epistasis in the genetic architecture of common diseases by using long-range linkage disequilibrium patterns. One significant and four near-significant associations across five disease phenotypes were identified, highlighting the pleiotropic and conserved nature of variants under epistatic selection. These findings provide insights into the genetic mechanisms underlying complex diseases. [ABSTRACT FROM AUTHOR]

Motivation The interaction between genetic variables is one of the major barriers to characterizing the genetic architecture of complex traits. To consider epistasis, network science approaches are increasingly being used in research to elucidate the genetic architecture of complex diseases. Network science approaches associate genetic variables' disease susceptibility to their topological importance in the network. However, this network only represents genetic interactions and does not describe how these interactions attribute to disease association at the subject-scale. We propose the Network-based Subject Portrait Approach (NSPA) and an accompanying feature transformation method to determine the collective risk impact of multiple genetic interactions for each subject. Results The feature transformation method converts genetic variants of subjects into new values that capture how genetic variables interact with others to attribute to a subject's disease association. We apply this approach to synthetic and genetic datasets and learn that (1) the disease association can be captured using multiple disjoint sets of genetic interactions and (2) the feature transformation method based on NSPA improves predictive performance comparing with using the original genetic variables. Our findings confirm the role of genetic interaction in complex disease and provide a novel approach for gene–disease association studies to identify genetic architecture in the context of epistasis. Availability and implementation The codes of NSPA are now available in: https://github.com/MIB-Lab/Network-based-Subject-Portrait-Approach Contact ting.hu@queensu.ca Supplementary information Supplementary data are available at Bioinformatics Advances online. [ABSTRACT FROM AUTHOR]

Temperature is a vital environmental factor affecting organisms' survival as they determine the mechanisms to tolerate rapid temperature changes. We demonstrate an experimental system for screening chemicals that affect cold tolerance in Caenorhabditis elegans. The anticancer drugs leptomycin B and camptothecin were among the 4000 chemicals that were screened as those affecting cold tolerance. Genes whose expression was affected by leptomycin B or camptothecin under cold stimuli were investigated by transcriptome analysis. Abnormal cold tolerance was detected in several mutants possessing genes that were rendered defective and whose expression altered after exposure to either leptomycin B or camptothecin. The genetic epistasis analysis revealed that leptomycin B or camptothecin may increase cold tolerance by affecting a pathway upstream of the insulin receptor DAF-2 that regulates cold tolerance in the intestine. Our experimental system combining drug and cold tolerance could be used for a comprehensive screening of genes that control cold tolerance at a low cost and in a short time period. [ABSTRACT FROM AUTHOR]

Mammalian genomes have multiple enhancers spanning an ultralong distance (>megabases) to modulate important genes, but it is unclear how these enhancers coordinate to achieve this task. We combine multiplexed CRISPRi screening with machine learning to define quantitative enhancer-enhancer interactions. We find that the ultralong distance enhancer network has a nested multilayer architecture that confers functional robustness of gene expression. Experimental characterization reveals that enhancer epistasis is maintained by three-dimensional chromosomal interactions and BRD4 condensation. Machine learning prediction of synergistic enhancers provides an effective strategy to identify noncoding variant pairs associated with pathogenic genes in diseases beyond genome-wide association studies analysis. Our work unveils nested epistasis enhancer networks, which can better explain enhancer functions within cells and in diseases. [ABSTRACT FROM AUTHOR]

A paradoxical finding from genome-wide association studies (GWAS) in plants is that variation in metabolite profiles typically maps to a small number of loci, despite the complexity of underlying biosynthetic pathways. This discrepancy may partially arise from limitations presented by geographically diverse mapping panels. Properties of metabolic pathways that impede GWAS by diluting the additive effect of a causal variant, such as allelic and genetic heterogeneity and epistasis, would be expected to increase in severity with the geographical range of the mapping panel. We hypothesized that a population from a single locality would reveal an expanded set of associated loci. We tested this in a French Arabidopsis thaliana population (less than 1 km transect) by profiling and conducting GWAS for glucosinolates, a suite of defensive metabolites that have been studied in depth through functional and genetic mapping approaches. For two distinct classes of glucosinolates, we discovered more associations at biosynthetic loci than the previous GWAS with continental-scale mapping panels. Candidate genes underlying novel associations were supported by concordance between their observed effects in the TOU-A population and previous functional genetic and biochemical characterization. Local populations complement geographically diverse mapping panels to reveal a more complete genetic architecture for metabolic traits. This article is part of the theme issue 'Genetic basis of adaptation and speciation: from loci to causative mutations'. [ABSTRACT FROM AUTHOR]

Countering prior beliefs that epistasis is rare, genomics advancements suggest the other way. Current practice often filters out genomic loci with low variant counts before detecting epistasis. We argue that this practice is far from optimal because it can throw away strong epistatic patterns. Instead, we present the compensated Sharma–Song test to infer genetic epistasis in genome-wide association studies by differential departure from independence. The test does not require a minimum number of replicates for each variant. We also introduce algorithms to simulate epistatic patterns that differentially depart from independence. Using two simulators, the test performed comparably to the original Sharma–Song test when variant frequencies at a locus are marginally uniform; encouragingly, it has a marked advantage over alternatives when variant frequencies are marginally nonuniform. The test further revealed uniquely clean epistatic variants associated with chicken abdominal fat content that are not prioritized by other methods. Genes involved in most numbers of inferred epistasis between single nucleotide polymorphisms (SNPs) belong to pathways known for obesity regulation; many top SNPs are located on chromosome 20 and in intergenic regions. Measuring differential departure from independence, the compensated Sharma–Song test offers a practical choice for studying epistasis robust to nonuniform genetic variant frequencies. [ABSTRACT FROM AUTHOR]

Fitness effects of mutation in natural populations of I Arabidopsis thaliana i reveal a complex influence of local adaptation. REFERENCES 1 Abrams, P.A., Matsuda, H., & Harada, Y. (1993) Evolutionarily unstable fitness maxima and stable fitness minima of continuous traits. The "Fitness landscape" metaphor is central to our ability to conceptualize how mutations generate new phenotypes and, in turn, variation in fitness. - Fisher's geometric model of mutational impact in high-dimensional continuous phenotype spaces, and its uses for predicting the distribution of fitness effects of new mutations, the joint fitness effects of mutations across environments, and so on. [Extracted from the article]

The many functions of microbial communities emerge from a complex web of interactions between organisms and their environment. This poses a significant obstacle to engineering microbial consortia, hindering our ability to harness the potential of microorganisms for biotechnological applications. In this study, we demonstrate that the collective effect of ecological interactions between microbes in a community can be captured by simple statistical models that predict how adding a new species to a community will affect its function. These predictive models mirror the patterns of global epistasis reported in genetics, and they can be quantitatively interpreted in terms of pairwise interactions between community members. Our results illuminate an unexplored path to quantitatively predicting the function of microbial consortia from their composition, paving the way to optimizing desirable community properties and bringing the tasks of predicting biological function at the genetic, organismal, and ecological scales under the same quantitative formalism. [Display omitted] • Simple statistical models predict the effect of a species on a community-level function • These models mirror the patterns of global epistasis reported in genetics • Ecological global epistasis emerges from widespread species-by-species interactions • This phenomenon can be leveraged to optimize the functions of microbial consortia Global epistasis, traditionally applied in genetics research, can be used to model complex microbial communities and predict the effects of a species on community-level functions. [ABSTRACT FROM AUTHOR]

Background: The influence of linkage disequilibrium (LD), epistasis, and inbreeding on genotypic variance continues to be an important area of investigation in genetics and evolution. Although the current knowledge about biological pathways and gene networks indicates that epistasis is important in determining quantitative traits, the empirical evidence for a range of species and traits is that the genotypic variance is most additive. This has been confirmed by some recent theoretical studies. However, because these investigations assumed linkage equilibrium, considered only additive effects, or used simplified assumptions for two- and higher-order epistatic effects, the objective of this investigation was to provide additional information about the impact of LD and epistasis on genetic variances in noninbred and inbred populations, using a simulated dataset. Results: In general, the most important component of the genotypic variance was additive variance. Because of positive LD values, after 10 generations of random crosses there was generally a decrease in all genetic variances and covariances, especially the nonepistatic variances. Thus, the epistatic variance/genotypic variance ratio is inversely proportional to the LD level. Increasing inbreeding increased the magnitude of the additive, additive x additive, additive x dominance, and dominance x additive variances, and decreased the dominance and dominance x dominance variances. Except for duplicate epistasis with 100% interacting genes, the epistatic variance/genotypic variance ratio was proportional to the inbreeding level. In general, the additive x additive variance was the most important component of the epistatic variance. Concerning the genetic covariances, in general, they showed lower magnitudes relative to the genetic variances and positive and negative signs. The epistatic variance/genotypic variance ratio was maximized under duplicate and dominant epistasis and minimized assuming recessive and complementary epistasis. Increasing the percentage of epistatic genes from 30 to 100% increased the epistatic variance/genotypic variance ratio by a rate of 1.3 to 12.6, especially in inbred populations. The epistatic variance/genotypic variance ratio was maximized in the noninbred and inbred populations with intermediate LD and an average allelic frequency of the dominant genes of 0.3 and in the noninbred and inbred populations with low LD and an average allelic frequency of 0.5. Conclusions: Additive variance is in general the most important component of genotypic variance. LD and inbreeding have a significant effect on the magnitude of the genetic variances and covariances. In general, the additive x additive variance is the most important component of epistatic variance. The maximization of the epistatic variance/genotypic variance ratio depends on the LD level, degree of inbreeding, epistasis type, percentage of interacting genes, and average allelic frequency. [ABSTRACT FROM AUTHOR]

Background: The c-Jun N-terminal kinase (JNK) pathway is an evolutionarily conserved regulator of cell death, which is essential for coordinating tissue homeostasis. In this study, we have characterized the Drosophila Ste20-like kinase Slik as a novel modulator of JNK pathway-mediated apoptotic cell death. Results: First, ectopic JNK signaling-triggered cell death is enhanced by slik depletion whereas suppressed by Slik overexpression. Second, loss of slik activates JNK signaling, which results in enhanced apoptosis and impaired tissue homeostasis. In addition, genetic epistasis analysis suggests that Slik acts upstream of or in parallel to Hep to regulate JNK-mediated apoptotic cell death. Moreover, Slik is necessary and sufficient for preventing physiologic JNK signaling-mediated cell death in development. Furthermore, introduction of STK10, the human ortholog of Slik, into Drosophila restores slik depletion-induced cell death and compromised tissue homeostasis. Lastly, knockdown of STK10 in human cancer cells also leads to JNK activation, which is cancelled by expression of Slik. Conclusions: This study has uncovered an evolutionarily conserved role of Slik/STK10 in blocking JNK signaling, which is required for cell death inhibition and tissue homeostasis maintenance in development. [ABSTRACT FROM AUTHOR]

Genetic analysis for quality attributes in chilli (Capsicum annuum L.) was studied in four selected crosses (F1) viz. LCA 710 x HC-28, LCA 712 x HC-28, LCA 712 x LCA 710 and LCA 764 x LCA 315 involving five diverse parents at HRS, Lam, Guntur, A.P. during Kharif, 2012-13 and their F2 (Selfing of F1), B1 (F1 x P1), B2 (F1 x P2) were developed during kharif, 2013-14. All the six generations (P1, P2, F1, F2, B1 and B2) of respective four crosses were evaluated in compact family block design with three replications during kharif, 2014-15 for ascorbic acid, oleoresin, capsaicin, red carotenoids, yellow carotenoids, total carotenoids and total colour value. The data generated was subjected to six generation mean analysis and the results revealed that all the types of gene actions i.e. additive, dominance and interaction components were played an important role in the inheritance of all studied parameters in all four crosses except cross 1 for yellow carotenoids in which interaction components were absent. Maximum number of crosses were exhibited duplicate epistasis while some crosses showed complimentary epistasis which indicating that all the quality attributes can be improved either by pedigree selection, recurrent selection, delayed selection, reciprocal recurrent selection, heterosis breeding, diallel selective mating scheme or bi-parental mating system. [ABSTRACT FROM AUTHOR]

The mature mammalian cortex is composed of 6 architecturally and functionally distinct layers. Two key steps in the assembly of this layered structure are the initial establishment of the glial scaffold and the subsequent migration of postmitotic neurons to their final position. These processes involve the precise and timely regulation of adhesion and detachment of neural cells from their substrates. Although much is known about the roles of adhesive substrates during neuronal migration and the formation of the glial scaffold, less is understood about how these signals are interpreted and integrated within these neural cells. Here, we provide in vivo evidence that Cas proteins, a family of cytoplasmic adaptors, serve a functional and redundant role during cortical lamination. Cas triple conditional knock-out (Cas TcKO) mice display severe cortical phenotypes that feature cobblestone malformations. Molecular epistasis and genetic experiments suggest that Cas proteins act downstream of transmembrane Dystroglycan and β1-Integrin in a radial glial cell-autonomous manner. Overall, these data establish a new and essential role for Cas adaptor proteins during the formation of cortical circuits and reveal a signaling axis controlling cortical scaffold formation. The assembly of a radial glial scaffold is a key step during cortical migration; this study demonstrates that Cas adaptor proteins act downstream of Dystroglycan and b1-Integrin during the establishment of this glial scaffold to regulate cortical lamination. [ABSTRACT FROM AUTHOR]

Plasticity in multicellular organisms involves signaling pathways converting contexts--either natural environmental challenges or laboratory perturbations--into context-specific changes in gene expression. Congruently, the interactions between the signaling molecules and transcription factors (TF) regulating these responses are also context specific. However, when a target gene responds across contexts, the upstream TF identified in one context is often inferred to regulate it across contexts. Reconciling these stable TF-target gene pair inferences with the context-specific nature of homeostatic responses is therefore needed. The induction of the Caenorhabditis elegans genes lipl-3 and lipl-4 is observed in many genetic contexts and is essential to survival during fasting. We find DAF-16/FOXO mediating lipl-4 induction in all contexts tested; hence, lipl-4 regulation seems context independent and compatible with across-context inferences. In contrast, DAF-16-mediated regulation of lipl-3 is context specific. DAF-16 reduces the induction of lipl-3 during fasting, yet it promotes it during oxidative stress. Through discrete dynamic modeling and genetic epistasis, we define that DAF-16 represses HLH-30/TFEB--the main TF activating lipl-3 during fasting. Contrastingly, DAF-16 activates the stress-responsive TF HSF-1 during oxidative stress, which promotes C. elegans survival through induction of lipl-3. Furthermore, the TF MXL-3 contributes to the dominance of HSF-1 at the expense of HLH-30 during oxidative stress but not during fasting. This study shows how context-specific diverting of functional interactions within a molecular network allows cells to specifically respond to a large number of contexts with a limited number of molecular players, a mode of transcriptional regulation we name "contextualized transcription." [ABSTRACT FROM AUTHOR]

Complex genetic diseases may be modulated by a large number of epistatic interactions affecting a polygenic phenotype. Identifying these interactions is difficult due to computational complexity, especially in the case of higher-order interactions where more than two genomic variants are involved. In this paper, we present BitEpi, a fast and accurate method to test all possible combinations of up to four bi-allelic variants (i.e. Single Nucleotide Variant or SNV for short). BitEpi introduces a novel bitwise algorithm that is 1.7 and 56 times faster for 3-SNV and 4-SNV search, than established software. The novel entropy statistic used in BitEpi is 44% more accurate to identify interactive SNVs, incorporating a p-value-based significance testing. We demonstrate BitEpi on real world data of 4900 samples and 87,000 SNPs. We also present EpiExplorer to visualize the potentially large number of individual and interacting SNVs in an interactive Cytoscape graph. EpiExplorer uses various visual elements to facilitate the discovery of true biological events in a complex polygenic environment. [ABSTRACT FROM AUTHOR]

Susceptibility to autoimmune diabetes is a complex genetic trait. Linkage analyses exploiting the NOD mouse, which spontaneously develops autoimmune diabetes, have proved to be a useful tool for the characterization of some of these traits. In a linkage analysis using 3A9 TCR transgenic mice on both B10.BR and NOD.H2k backgrounds, we previously determined that both the Idd2 and Idd13 loci were linked to the proportion of immunoregulatory CD4-CD8- double negative (DN) T cells. In addition to Idd2 and Idd13, five other loci showed weak linkage to the proportion of DN T cells. Of interest, in an interim analysis, a locus on chromosome 12 is linked to DN T cell proportion in both the spleen and the lymph nodes. To determine the impact of this locus on DN T cells, we generated two congenic sublines, which we named Chr12P and Chr12D for proximal and distal, respectively. While 3A9 TCR:insHEL NOD.H2k-Chr12D mice were protected from diabetes, 3A9 TCR:insHEL NOD.H2k-Chr12P showed an increase in diabetes incidence. Yet, the proportion of DN T cells was similar to the parental 3A9 TCR NOD.H2k strain for both of these congenic sublines. A genome-wide two dimensional LOD score analysis reveals genetic epistasis between chromosome 12 and the Idd13 locus. Altogether, this study identified further complex genetic interactions in defining the proportion of DN T cells, along with evidence of genetic epistasis within a locus on chromosome 12 influencing autoimmune susceptibility. [ABSTRACT FROM AUTHOR]

The endoplasmic reticulum (ER) is a membrane-bound organelle responsible for protein folding, lipid synthesis, and calcium homeostasis. Maintenance of ER structural integrity is crucial for proper function, but much remains to be learned about the molecular players involved. To identify proteins that support the structure of the ER, we performed a proteomic screen and identified nodal modulator (NOMO), a widely conserved type I transmembrane protein of unknown function, with three nearly identical orthologs specified in the human genome. We found that overexpression of NOMO1 imposes a sheet morphology on the ER, whereas depletion of NOMO1 and its orthologs causes a collapse of ER morphology concomitant with the formation of membrane-delineated holes in the ER network positive for the lysosomal marker lysosomal-associated protein 1. In addition, the levels of key players of autophagy including microtubule-associated protein light chain 3 and autophagy cargo receptor p62/sequestosome 1 strongly increase upon NOMO depletion. In vitro reconstitution of NOMO1 revealed a "beads on a string" structure likely representing consecutive immunoglobulin-like domains. Extending NOMO1 by insertion of additional immunoglobulin folds results in a correlative increase in the ER intermembrane distance. Based on these observations and a genetic epistasis analysis including the known ER-shaping proteins Atlastin2 and Climp63, we propose a role for NOMO1 in the functional network of ER-shaping proteins. [ABSTRACT FROM AUTHOR]

Introduction: Saline-alkali stress is one of the main abiotic factors limiting rice production worldwide. With the widespread use of rice direct seeding technology, it has become increasingly important to improve rice saline-alkali tolerance at the germination stage. Methods: To understand the genetic basis of saline-alkali tolerance and facilitate breeding efforts for developing saline-alkali tolerant rice varieties, the genetic basis of rice saline-alkali tolerance was dissected by phenotyping seven germination-related traits of 736 diverse rice accessions under the saline-alkali stress and control conditions using genome-wide association and epistasis analysis (GWAES). Results: Totally, 165 main-effect quantitative trait nucleotides (QTNs) and 124 additional epistatic QTNs were identified as significantly associated with saline-alkali tolerance, which explained a significant portion of the total phenotypic variation of the saline-alkali tolerance traits in the 736 rice accessions. Most of these QTNs were located in genomic regions either harboring saline-alkali tolerance QTNs or known genes for saline-alkali tolerance reported previously. Epistasis as an important genetic basis of rice saline-alkali tolerance was validated by genomic best linear unbiased prediction in which inclusion of both main-effect and epistatic QTNs showed a consistently better prediction accuracy than either main-effect or epistatic QTNs alone. Candidate genes for two pairs of important epistatic QTNs were suggested based on combined evidence from the high-resolution mapping plus their reported molecular functions. The first pair included a glycosyltransferase gene LOC_Os02g51900 (UGT85E1) and an E3 ligase gene LOC_Os04g01490 (OsSIRP4), while the second pair comprised an ethylene-responsive transcriptional factor, AP59 (LOC_Os02g43790), and a Bcl-2-associated athanogene gene, OsBAG1 (LOC_Os09g35630) for salt tolerance. Detailed haplotype analyses at both gene promoter and CDS regions of these candidate genes for important QTNs identified favorable haplotype combinations with large effects on saline-alkali tolerance, which can be used to improve rice saline-alkali tolerance by selective introgression. Discussion: Our findings provided saline-alkali tolerant germplasm resources and valuable genetic information to be used in future functional genomic and breeding efforts of rice saline-alkali tolerance at the germination stage. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) provide clear insight into understanding genetic variations and environmental influences responsible for various human diseases. Cancer identification through genetic interactions (epistasis) is one of the significant ongoing researches in GWAS. The growth of the cancer cell emerges from multi-locus as well as complex genetic interaction. It is impractical for the physician to detect cancer via manual examination of SNPs interaction. Due to its importance, several computational approaches have been modeled to infer epistasis effects. This article includes a comprehensive and multifaceted review of all relevant genetic studies published between 2001 and 2020. In this contemporary review, various computational methods are as follows: multifactor dimensionality reduction-based approaches, statistical strategies, machine learning, and optimization-based techniques are carefully reviewed and presented with their evaluation results. Moreover, these computational approaches' strengths and limitations are described. The issues behind the computational methods for identifying the cancer disease through genetic interactions and the various evaluation parameters used by researchers have been analyzed. This review is highly beneficial for researchers and medical professionals to learn techniques adapted to discover the epistasis and aids to design novel automatic epistasis detection systems with strong robustness and maximum efficiency to address the different research problems in finding practical solutions effectively. [ABSTRACT FROM AUTHOR]

Sex determination and differentiation is a complex process regulated by multiple factors, including factors from the germline or surrounding somatic tissue. In zebrafish, sex-determination involves establishment of a bipotential ovary that undergoes sex-specific differentiation and maintenance to form the functional adult gonad. However, the relationships among these factors are not fully understood. Here, we identify potential Rbpms2 targets and apply genetic epistasis experiments to decipher the genetic hierarchy of regulators of sexspecific differentiation. We provide genetic evidence that the crucial female factor rbpms2 is epistatic to the male factor dmrt1 in terms of adult sex. Moreover, the role of Rbpms2 in promoting female fates extends beyond repression of Dmrt1, asRbpms2 is essential for female differentiation even in the absence of Dmrt1. In contrast, female fates can be restored in mutants lacking both cyp19a1a and dmrt1, and prolonged in bmp15 mutants in the absence of dmrt1. Taken together, this work indicates that cyp19a1a-mediated suppression of dmrt1 establishes a bipotential ovary and initiates female fate acquisition. Then, after female fate specification, Cyp19a1a regulates subsequent oocyte maturation and sustains female fates independently of Dmrt1 repression. [ABSTRACT FROM AUTHOR]

Genome-wide association studies have identified many loci associated with Alzheimer's dementia. However, these variants only explain part of the heritability of Alzheimer's disease (AD). As genetic epistasis can be a major contributor to the "missing heritability" of AD, we conducted genome-wide epistasis screening for AD pathologies in 2 independent cohorts. First, we performed a genome-wide epistasis study of AD-related brain pathologies (N max = 1318) in ROS/MAP. Candidate interactions were validated using cerebrospinal fluid biomarkers of AD in ADNI (N max = 1128). Further functional analysis tested the association of candidate interactions with neuroimaging phenotypes. For tau and amyloid-β pathology, we identified 2803 and 464 candidate SNP-SNP interactions, respectively. Associations of candidate SNP-SNP interactions with brain volume and white matter changes from neuroimages provides additional insights into their molecular functions. Transcriptional analysis supported possible gene-gene interactions identified by statistical screening through their co-expression in the brain. In summary, we outlined an exhaustive epistasis analysis to identify novel genetic interactions with potential roles in AD pathologies. We further delved into the functional relevance of candidate interactions by association with neuroimaging phenotypes and analysis of co-expression between corresponding gene pairs. • Genetic interactions help explain the "missing heritability" in Alzheimer's disease. • We conducted a genome-wide epistasis analysis for Alzheimer's disease pathologies. • The epistasis signals were replicated in independent data. • Transcriptome analysis supported the interactions (such as INPP4B / RBFOX1 interaction). • Association with neuroimages provides insights into molecular functions of interactions. [ABSTRACT FROM AUTHOR]

To reveal the impacts of smoking on genetic architecture of human body weight, we conducted a genome-wide association study on 5,336 subjects in four ethnic populations from MESA (The Multi-Ethnic Study of Atherosclerosis) data. A full genetic model was applied to association mapping for analyzing genetic effects of additive, dominance, epistasis, and their ethnicity-specific effects. Both the unconditional model (base) and conditional model including smoking as a cofactor were investigated. There were 10 SNPs involved in 96 significant genetic effects detected by the base model, which accounted for a high heritability (61.78%). Gene ontology analysis revealed that a number of genetic factors are related to the metabolic pathway of benzopyrene, a main compound in cigarettes. Smoking may play important roles in genetic effects of dominance, dominance-related epistasis, and gene-ethnicity interactions on human body weight. Gene effect prediction shows that the genetic effects of smoking cessation on body weight vary from different populations. [ABSTRACT FROM AUTHOR]

When handling a structured population in association mapping, group-specific allele effects may be observed at quantitative trait loci (QTLs) for several reasons: (i) a different linkage disequilibrium (LD) between SNPs and QTLs across groups, (ii) group-specific genetic mutations in QTL regions, and/or (iii) epistatic interactions between QTLs and other loci that have differentiated allele frequencies between groups. We present here a new genome-wide association (GWAS) approach to identify QTLs exhibiting such group-specific allele effects. We developed genetic materials including admixed progeny from different genetic groups with known genome-wide ancestries (local admixture). A dedicated statistical methodology was developed to analyze pure and admixed individuals jointly, allowing one to disentangle the factors causing the heterogeneity of allele effects across groups. This approach was applied to maize by developing an inbred "Flint-Dent" panel including admixed individuals that was evaluated for flowering time. Several associations were detected revealing a wide range of configurations of allele effects, both at known flowering QTLs (Vgt1, Vgt2 and Vgt3) and new loci. We found several QTLs whose effect depended on the group ancestry of alleles while others interacted with the genetic background. Our GWAS approach provides useful information on the stability of QTL effects across genetic groups and can be applied to a wide range of species. Author summary: Identification of genomic regions involved in genetic architecture of traits has become commonplace in quantitative genetics studies. Genetic structure is a common feature in human, animal and plant species and most current methods target genomic regions whose effects on traits are conserved between genetic groups. However, a heterogeneity of allele effects may be observed due to different factors: a group-specific correlation between the alleles of the tagged marker and those of the causal variant, a group-specific mutation at the causal variant or an epistatic interaction between the causal variant and the genetic background. We propose a new method adapted to structured populations including admixed individuals, which aims to identify these genomic regions and to unravel the previous factors. The method was applied to a maize inbred diversity panel including lines from the dent and the flint genetic groups, as well as admixed lines, evaluated for flowering time. Several genomic regions were detected with various configurations of allele effects, with evidence of epistatic interactions between some of the loci and the genetic background. [ABSTRACT FROM AUTHOR]

Background: With the increasing amount of high-throughput genomic sequencing data, there is a growing demand for a robust and flexible tool to perform interaction analysis. The identification of SNP-SNP, SNP-CpG, and higher order interactions helps explain the genetic etiology of human diseases, yet genome-wide analysis for interactions has been very challenging, due to the computational burden and a lack of statistical power in most datasets. Results: The wtest R package performs association testing for main effects, pairwise and high order interactions in genome-wide association study data, and cis-regulation of SNP and CpG sites in genome-wide and epigenome-wide data. The software includes a number of post-test diagnostic and analysis functions and offers an integrated toolset for genetic epistasis testing. Conclusions: The wtest is an efficient and powerful statistical tool for integrated genetic epistasis testing. The package is available in CRAN: https://CRAN.R-project.org/package=wtest. [ABSTRACT FROM AUTHOR]

Post-traumatic stress disorder (PTSD) is a psychiatric syndrome that occurs after trauma exposure. Neurotransmitters such as dopamine and oxytocin have been reported to be involved in neuropathology of PTSD. Previous studies indicated that the dopamine–oxytocin interaction may contribute to behavioral disorders. Thus, exploring the epistasis (gene–gene interaction) between oxytocinergic and dopaminergic systems might be useful to reveal the genetic basis of PTSD. In this study, we analyzed two functional single nucleotide polymorphisms (SNPs), rs2268498 for oxytocinergic gene OXTR and rs1801028 for dopaminergic gene DRD2 based on putative oxytocin receptor–dopamine receptor D2 (OTR–DR2) heterocomplex in a Chinese cohort exposed to the 2008 Wenchuan earthquake (156 PTSD cases and 978 controls). Statistical analyses did not find any single variant or gene–environment interaction (SNP × earthquake-related trauma exposure) associated with provisional PTSD diagnosis or symptoms. An OXTR–DRD2 interaction (rs2268498 × rs1801028) was identified to confer risk of provisional PTSD diagnosis (OR = 9.18, 95% CI = 3.07–27.46 and P = 7.37e-05) and further subset analysis indicated that rs2268498 genotypes controlled the association directions of rs1801028 and rs1801028 genotypes also controlled the association directions of rs2268498. Rs2268498 × rs1801028 is also associated with PTSD symptoms (P = 0.043). Our study uncovered a genetic and putative function-based contribution of dopaminergic–oxytocinergic system interaction to PTSD. [ABSTRACT FROM AUTHOR]

Melanoma is a heterogenous malignancy with an unpredictable clinical course. Most patients who present in the clinic are diagnosed with primary melanoma, yet large‐scale sequencing efforts have focused primarily on metastatic disease. In this study we sequence‐profiled 524 American Joint Committee on Cancer Stage I–III primary tumours. Our analysis of these data reveals recurrent driver mutations, mutually exclusive genetic interactions, where two genes were never or rarely co‐mutated, and an absence of co‐occurring genetic events. Further, we intersected copy number calls from our primary melanoma data with whole‐genome CRISPR screening data to identify the transcription factor interferon regulatory factor 4 (IRF4) as a melanoma‐associated dependency. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]

Objectives/aims: Prolonged infections of immunocompromised individuals have been proposed as a crucial source of new variants of SARS-CoV-2 during the COVID-19 pandemic. In principle, sustained within-host antigenic evolution in immunocompromised hosts could allow novel immune escape variants to emerge more rapidly, but little is known about how and when immunocompromised hosts play a critical role in pathogen evolution. Materials and methods: Here, we use a simple mathematical model to understand the effects of immunocompromised hosts on the emergence of immune escape variants in the presence and absence of epistasis. Conclusions: We show that when the pathogen does not have to cross a fitness valley for immune escape to occur (no epistasis), immunocompromised individuals have no qualitative effect on antigenic evolution (although they may accelerate immune escape if within-host evolutionary dynamics are faster in immunocompromised individuals). But if a fitness valley exists between immune escape variants at the between-host level (epistasis), then persistent infections of immunocompromised individuals allow mutations to accumulate, therefore, facilitating rather than simply speeding up antigenic evolution. Our results suggest that better genomic surveillance of infected immunocompromised individuals and better global health equality, including improving access to vaccines and treatments for individuals who are immunocompromised (especially in lower- and middle-income countries), may be crucial to preventing the emergence of future immune escape variants of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Moving forward, the inclusion of a larger number of microtia/OAVS-related genes or the use of whole-exome sequencing should identify new variants that can be considered in future gene-gene interaction studies [[62]]. One significant gene-gene interaction related to the presentation of microtia/OAVS was identified: that between the non-synonymous p.(Pro1099Arg) I TCOF1 i variant and the synonymous p.(Leu858=) I SALL1 i variant (Figure 1). Keywords: gene-gene interactions; microtia; Mexican population; Multifactor Dimensionality Reduction (MDR); next-generation sequencing; OAVS EN gene-gene interactions microtia Mexican population Multifactor Dimensionality Reduction (MDR) next-generation sequencing OAVS 1723 11 11/17/22 20221101 NES 221101 1. Conclusions Although gene-gene interactions are known to play an important role in the etiology of many complex diseases, no previous study has addressed gene interactions in patients with microtia/OAVS. [Extracted from the article]

Epistasis refers to fitness or functional effects of mutations that depend on the sequence background in which these mutations arise. Epistasis is prevalent in nature, including populations of viruses, bacteria, and cancers, and can contribute to the evolution of drug resistance and immune escape. However, it is difficult to directly estimate epistatic effects from sampled observations of a population. At present, there are very few methods that can disentangle the effects of selection (including epistasis), mutation, recombination, genetic drift, and genetic linkage in evolving populations. Here we develop a method to infer epistasis, along with the fitness effects of individual mutations, from observed evolutionary histories. Simulations show that we can accurately infer pairwise epistatic interactions provided that there is sufficient genetic diversity in the data. Our method also allows us to identify which fitness parameters can be reliably inferred from a particular data set and which ones are unidentifiable. Our approach therefore allows for the inference of more complex models of selection from time-series genetic data, while also quantifying uncertainty in the inferred parameters. [ABSTRACT FROM AUTHOR]

Heterotrimeric (αβγ) G protein signaling pathways are critical environmental sensing systems found in eukaryotic cells. Exchange of GDP for GTP on the Gα subunit leads to its activation. In contrast, GTP hydrolysis on the Gα is accelerated by Regulator of G protein Signaling (RGS) proteins, resulting in a return to the GDP-bound, inactive state. Here, we analyzed growth, development and extracellular cellulase production in strains with knockout mutations in the seven identified RGS genes (rgs-1 to rgs-7) in the filamentous fungus, Neurospora crassa. We compared phenotypes to those of strains with either knockout mutations or expressing predicted constitutively activated, GTPase-deficient alleles for each of the three Gα subunit genes (gna-1Q204L, gna-2Q205L or gna-3Q208L). Our data revealed that six RGS mutants have taller aerial hyphae than wild type and all seven mutants exhibit reduced asexual sporulation, phenotypes shared with strains expressing the gna-1Q204L or gna-3Q208L allele. In contrast, Δrgs-1 and Δrgs-3 were the only RGS mutants with a slower growth rate phenotype, a defect in common with gna-1Q204L strains. With respect to female sexual development, Δrgs-1 possessed defects most similar to gna-3Q208L strains, while those of Δrgs-2 mutants resembled strains expressing the gna-1Q204L allele. Finally, we observed that four of the seven RGS mutants had significantly different extracellular cellulase levels relative to wild type. Of interest, the Δrgs-2 mutant had no detectable activity, similar to the gna-3Q208L strain. In contrast, the Δrgs-1 and Δrgs-4 mutants and gna-1Q204L and gna-2Q205L strains exhibited significantly higher cellulase activity than wild type. With the exception of sexual development, our results demonstrate the greatest number of genetic interactions between rgs-1 and gna-1 and rgs-2 and gna-3 in N. crassa. [ABSTRACT FROM AUTHOR]

The concept of genetic epistasis defines an interaction between two genetic loci as the degree of non-additivity in their phenotypes. A fitness landscape describes the phenotypes over many genetic loci, and the shape of this landscape can be used to predict evolutionary trajectories. Epistasis in a fitness landscape makes prediction of evolutionary trajectories more complex because the interactions between loci can produce local fitness peaks or troughs, which changes the likelihood of different paths. While various mathematical frameworks have been proposed to investigate properties of fitness landscapes, Beerenwinkel et al. (Stat Sin 17(4):1317–1342, 2007a) suggested studying regular subdivisions of convex polytopes. In this sense, each locus provides one dimension, so that the genotypes form a cube with the number of dimensions equal to the number of genetic loci considered. The fitness landscape is a height function on the coordinates of the cube. Here, we propose cluster partitions and cluster filtrations of fitness landscapes as a new mathematical tool, which provides a concise combinatorial way of processing metric information from epistatic interactions. Furthermore, we extend the calculation of genetic interactions to consider interactions between microbial taxa in the gut microbiome of Drosophila fruit flies. We demonstrate similarities with and differences to the previous approach. As one outcome we locate interesting epistatic information on the fitness landscape where the previous approach is less conclusive. [ABSTRACT FROM AUTHOR]

The six C. elegans vulval precursor cells (VPCs) are induced to form the 3°-3°-2°-1°-2°-3° pattern of cell fates with high fidelity. In response to EGF signal, the LET-60/Ras-LIN-45/Raf-MEK-2/MEK-MPK-1/ERK canonical MAP kinase cascade is necessary to induce 1° fate and synthesis of DSL ligands for the lateral Notch signal. In turn, LIN-12/Notch receptor is necessary to induce neighboring cells to become 2°. We previously showed that, in response to graded EGF signal, the modulatory LET-60/Ras-RGL-1/RalGEF-RAL-1/Ral signal promotes 2° fate in support of LIN-12. In this study, we identify two key differences between RGL-1 and RAL-1. First, deletion of RGL-1 confers no overt developmental defects, while previous studies showed RAL-1 to be essential for viability and fertility. From this observation, we hypothesize that the essential functions of RAL-1 are independent of upstream activation. Second, RGL-1 plays opposing and genetically separable roles in VPC fate patterning. RGL-1 promotes 2° fate via canonical GEF-dependent activation of RAL-1. Conversely, RGL-1 promotes 1° fate via a non-canonical GEF-independent activity. Our genetic epistasis experiments are consistent with RGL-1 functioning in the modulatory 1°-promoting AGE-1/PI3-Kinase-PDK-1-AKT-1 cascade. Additionally, animals lacking RGL-1 experience 15-fold higher rates of VPC patterning errors compared to the wild type. Yet VPC patterning in RGL-1 deletion mutants is not more sensitive to environmental perturbations. We propose that RGL-1 functions to orchestrate opposing 1°- and 2°-promoting modulatory cascades to decrease developmental stochasticity. We speculate that such switches are broadly conserved but mostly masked by paralog redundancy or essential functions. [ABSTRACT FROM AUTHOR]

Characterizing the fitness landscape, a representation of fitness for a large set of genotypes, is key to understanding how genetic information is interpreted to create functional organisms. Here we determined the evolutionarily-relevant segment of the fitness landscape of His3, a gene coding for an enzyme in the histidine synthesis pathway, focusing on combinations of amino acid states found at orthologous sites of extant species. Just 15% of amino acids found in yeast His3 orthologues were always neutral while the impact on fitness of the remaining 85% depended on the genetic background. Furthermore, at 67% of sites, amino acid replacements were under sign epistasis, having both strongly positive and negative effect in different genetic backgrounds. 46% of sites were under reciprocal sign epistasis. The fitness impact of amino acid replacements was influenced by only a few genetic backgrounds but involved interaction of multiple sites, shaping a rugged fitness landscape in which many of the shortest paths between highly fit genotypes are inaccessible. [ABSTRACT FROM AUTHOR]