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Most phenotypes are determined by molecular systems composed of specifically interacting molecules. However, unlike for individual components, little is known about the distributions of mutational effects of molecular systems as a whole. We ask how the distribution of mutational effects of a transcriptional regulatory system differs from the distributions of its components, by first independently, and then simultaneously, mutating a transcription factor and the associated promoter it represses. We find that the system distribution exhibits increased phenotypic variation compared to individual component distributions - an effect arising from intermolecular epistasis between the transcription factor and its DNA-binding site. In large part, this epistasis can be qualitatively attributed to the structure of the transcriptional regulatory system and could therefore be a common feature in prokaryotes. Counter-intuitively, intermolecular epistasis can alleviate the constraints of individual components, thereby increasing phenotypic variation that selection could act on and facilitating adaptive evolution. [ABSTRACT FROM AUTHOR]

A mutation-accumulation (MA) experiment with Caenorhabditis elegans nematodes was conducted in which replicate, independently evolving lines were initiated from a low-fitness mitochondrial electron transport chain mutant, gas-1. The original intent of the study was to assess the effect of electron transport chain dysfunction involving elevated reactive oxygen species production on patterns of spontaneous germline mutation. In contrast to results of standard MA experiments, gas-1 MA lines evolved slightly higher mean fitness alongside reduced among-line genetic variance compared with their ancestor. Likewise, the gas-1 MA lines experienced partial recovery to wildtype reactive oxygen species levels. Whole-genome sequencing and analysis revealed that the molecular spectrum but not the overall rate of nuclearDNAmutation differed from wildtype patterns. Further analysis revealed an enrichment of mutations in loci that occur in a gas-1-centric region of the C. elegans interactome, and could be classified into a small number of functional-genomic categories. Characterization of a backcrossed four-mutation set isolated from one gas-1 MA line revealed this combination to be beneficial on both gas-1 mutant and wildtype genetic backgrounds. Our combined results suggest that selection favoring beneficial mutations can be powerful even under unfavorable population genetic conditions, and agree with fitness landscape theory predicting an inverse relationship between population fitness and the likelihood of adaptation. [ABSTRACT FROM AUTHOR]

Lesch-Nyhan disease (LND) is a rare X-linked inherited neurogenetic disorder of purine metabolism in which the enzyme, hypoxanthine-guanine phosphoribosyltransferase (HGprt) is defective. The authors report a novel point mutation that led to HGprt-related neurological dysfunction (HND) in a family in which there was a missense mutation in exon 6 of the coding region of theHPRT1gene: g.34938G>T, c.403G>T, p.D135Y. Molecular diagnosis is consistent with the genetic heterogeneity of theHPRT1gene responsible for HGprt deficiency. It allows fast, accurate carrier detection and genetic counseling. [ABSTRACT FROM AUTHOR]

Interferon-γ-induced aminopeptidase ERAP1 trims peptides within the endoplasmic reticulum so that they can be loaded onto MHC class I and presented to the CD8 + T-cells. ERAP1 association and its interaction with HLA-C∗06 is controversial across different populations. We have investigated the association and possible functional role of non-synonymous SNPs at different exons of ERAP1 (rs26653: Arg127Pro, rs30187: Lys528Arg and rs27044: Gln730Glu) and their interactions with HLA-C∗06 in psoriasis. Significant associations of HLA-C∗06 (OR = 5.47, P < 2.2 × 10 −16 ), rs30187 (OR 1.35, P = 7.4 × 10 −4 ) and rs27044 (OR = 1.24, P = 5.8 × 10 −3 ) were observed. All three ERAP1 SNPs showed significant association only for HLA-C∗06 positive patients, while rs30187 and rs27044 showed significant association only for early onset patients (rs30187: OR = 1.47, P = 9.6 × 10 −5 ; rs27044: OR = 1.36, P = 3.3 × 10 −4 ). No differential expression of ERAP1 was observed either between paired uninvolved and involved skin tissues of psoriasis patients or between non-risk and risk variants in the involved skin. Significant epistatic interaction was observed between HLA-C∗06 and the SNP (rs27044) located at the peptide-binding cavity of ERAP1. Evolutionary conservation analysis among mammals showed confinement of Lys528 and Gln730 within highly conserved regions of ERAP1 and suggested the possible detrimental effect of this allele in ERAP1 regulation. [ABSTRACT FROM AUTHOR]

Background: Colon cancer is a leading cause of worldwide cancer death. It has become clear that microRNAs (miRNAs) play a role in the progress of colon cancer and understanding the effect of miRNAs on tumorigenesis could lead to better prognosis and improved treatment. However, most studies have focused on studying differentially expressed miRNAs between tumor and non-tumor samples or between stages in tumor tissue. Limited work has conducted to study the interactions or epistasis between miRNAs and how the epistasis brings about effect on tumor progression. In this study, we investigate the main and pair-wise epistatic effects of miRNAs on the pathological stages of colon cancer using datasets from The Cancer Genome Atlas. Results: We develop a workflow composed of multiple steps for feature selection based on the Empirical Bayesian Elastic Net (EBEN) method. First, we identify the main effects using a model with only main effect on the phenotype. Second, a corrected phenotype is calculated by removing the significant main effect from the original phenotype. Third, we select features with epistatic effect on the corrected phenotype. Finally, we run the full model with main and epistatic effects on the previously selected main and epistatic features. Using the multi-step workflow, we identify a set of miRNAs with main and epistatic effect on the pathological stages of colon cancer. Many of miRNAs with main effect on colon cancer have been previously reported to be associated with colon cancer, and the majority of the epistatic miRNAs share common target genes that could explain their epistasis effect on the pathological stages of colon cancer. We also find many of the target genes of detected miRNAs are associated with colon cancer. Go Ontology Enrichment Analysis of the experimentally validates targets of main and epistatic miRNAs, shows that these target genes are enriched for biological processes associated with cancer progression. Conclusion: Our results provide a set of candidate miRNAs associated with colon cancer progression that could have potential translational and therapeutic utility. Our analysis workflow offers a new opportunity to efficiently explore epistatic interactions among genetic and epigenetic factors that could be associated with human diseases. Furthermore, our workflow is flexible and can be applied to analyze the main and epistatic effect of various genetic and epigenetic factors on a wide range of phenotypes. [ABSTRACT FROM AUTHOR]

Systems biology presents an integrated view of biological systems, focusing on the relations between elements, whether functional or evolutionary, and providing a rich framework for the comprehension of life. At the same time, many low-throughput experimental studies are performed without influence from this integrated view, whilst high-throughput experiments use low-throughput results in their validation and interpretation. We propose an inversion in this logic, and ask which benefits could be obtained from a holistic view coming from high-throughput studies--and systems biology in particular--in interpreting and designing low-throughput experiments. By exploring some key examples from the renal and adrenal physiology, we try to show that network and modularity theory, along with observed patterns of association between elements in a biological system, can have profound effects on our ability to draw meaningful conclusions from experiments. [ABSTRACT FROM AUTHOR]

The resistance of soybean ( Glycine max L. Merr.) cultivars varies with the different races of the soybean cyst nematode ( SCN), Heterodera glycines, referred to as HG types (biotypes). Resistant cultivars with durable resistance are emphasized in recent years. The aim here was to identify quantitative trait loci ( QTLs) for resistance to two SCN HG types ( HG type 2.5.7, race 1; and HG type 1.2.3.5.7, race 4) in resistant cultivar 'L-10' and to analyse the additive and epistatic effects of the identified QTLs. A total of 140 F5-derived F10 recombinant inbred lines (F5:10 RILs) were advanced via single-seed-descent from the cross between 'L-10' (broadly resistant to SCN) and 'Heinong 37' ( SCN-susceptible). For SCN HG type 2.5.7 and HG type 1.2.3.5.7 resistance, three and six QTLs for resistance to SCN HG type 2.5.7 and HG type 1.2.3.5.7 were identified, respectively, most of which could explain <10% of the phenotypic variation. Among these QTLs, five were identified over 2 years, while the other QTLs were detected in either 2009 or 2010. QSCN1-2, located near the SSR marker Sat_069 of linkage group D1b (Chromosome, 2), was responsible for the largest proportion of phenotypic variation (16.01% in 2009 and 18.94% in 2010), suggested that it could effectively be used as a candidate QTL for the marker-assisted selection ( MAS) of soybean lines resistant to SCN. Additionally, for SCN HG type 2.5.7 and HG type 1.2.3.5.7 resistance, two and four QTLs showed an additive effect ( a), respectively. One epistatic pair of QTLs ( QSCN1-1- QSCN1-3) for SCN HG type 2.5.7 resistance and eight epistatic pairs of QTLs for SCN HG type 1.2.3.5.7 resistance were found to have significant aa effects, among which one pair of QTLs ( QSCN4-4 and QSCN4-5) contributed a large proportion of aa effects (3%). The results indicated that additive and epistatic effects could significantly affect SCN resistance. Therefore, both of a and aa effects should be considered in MAS programmes. [ABSTRACT FROM AUTHOR]

The number one goal of most rice improvement programmes around the world is breeding for high potential to take care of the increasing consumption of rice. The objective of this experiment was to study the inheritance of yield and yield components and to estimate the heritabilities of important quantitative traits in rice (Oryza sativa L.). Six generations viz., P1, P2, F1, F2, BCP1 and BCP2 of a cross between IET6279 and IR70445-146-3-3 were used for the study. Generation mean analysis suggested that additive effects had a major role for the expression of plant height, number of panicles, number of spikelets per panicle, percentage spikelets fertility per plant and grain yield per plant, which further suggested that phenotypic selection was possible at an early stage. Both additive and non-additive gene actions were important for the expression of number of fertile spikelets per panicle and 100-grain weight. Therefore, selection for these characters would be fruitful, if delayed till epistasis effects are reduced to a minimum. High broad sense heritability estimates were observed for characters viz. plant height and 100-grain weight, suggesting that the characters under study are less influenced by environment in their expression. Thus, selection based on phenotypic value of these characters would be reliable and effective. Low estimates of broad sense heritability were observed for number of panicles per plant, number of spikelets per panicle, number of fertile spikelets per panicle, percentage spikelets fertility per plant and grain yield per plant, indicating that influence of the environment was high for these characters. Therefore, superior genotypes selection based on phenotypic performance for these characters may not effective. [ABSTRACT FROM AUTHOR]

Frequency-independent selection is generally considered as a force that acts to reduce the genetic variation in evolving populations, yet rigorous arguments for this idea are scarce. When selection fluctuates in time, it is unclear whether frequencyindependent selection may maintain genetic polymorphism without invoking additional mechanisms. We show that constant frequency-independent selection with arbitrary epistasis on a well-mixed haploid population eliminates genetic variation if we assume linkage equilibrium between alleles. To this end, we introduce the notion of frequency-independent selection at the level of alleles, which is sufficient to prove our claim and contains the notion of frequency-independent selection on haploids. When selection and recombination are weak but of the same order, there may be strong linkage disequilibrium; numerical calculations show that stable equilibria are highly unlikely. Using the example of a diallelic two-locus model, we then demonstrate that frequency-independent selection that fluctuates in time can maintain stable polymorphism if linkage disequilibrium changes its sign periodically. We put our findings in the context of results from the existing literature and point out those scenarios in which the possible role of frequencyindependent selection in maintaining genetic variation remains unclear. [ABSTRACT FROM AUTHOR]

The relative contributions of additive versus non-additive interactions in the regulation of complex traits remains controversial. This may be in part because large-scale epistasis has traditionally been difficult to detect in complex, multi-cellular organisms. We hypothesized that it would be easier to detect interactions using mouse chromosome substitution strains that simultaneously incorporate allelic variation in many genes on a controlled genetic background. Analyzing metabolic traits and gene expression levels in the offspring of a series of crosses between mouse chromosome substitution strains demonstrated that inter-chromosomal epistasis was a dominant feature of these complex traits. Epistasis typically accounted for a larger proportion of the heritable effects than those due solely to additive effects. These epistatic interactions typically resulted in trait values returning to the levels of the parental CSS host strain. Due to the large epistatic effects, analyses that did not account for interactions consistently underestimated the true effect sizes due to allelic variation or failed to detect the loci controlling trait variation. These studies demonstrate that epistatic interactions are a common feature of complex traits and thus identifying these interactions is key to understanding their genetic regulation. [ABSTRACT FROM AUTHOR]

Motivation: The existing epistasis analysis approaches have been criticized mainly for their: (i) ignoring heterogeneity during epistasis analysis; (ii) high computational costs; and (iii) volatility of performances and results. Therefore, they will not perform well in general, leading to lack of reproducibility and low power in complex disease association studies. In this work, a fast scheme is proposed to accelerate exhaustive searching based on multi-objective optimization named ESMO for concurrently analyzing heterogeneity and epistasis phenomena. In ESMO, mutual entropy and Bayesian network approaches are combined for evaluating epistatic SNP combinations. In order to be compatible with heterogeneity of complex diseases, we designed an adaptive framework based on non-dominant sort and top k selection algorithm with improved time complexity O(k*M*N). Moreover, ESMO is accelerated by strategies such as trading space for time, calculation sharing and parallel computing. Finally, ESMO is nonparametric and model-free. Results:We compared ESMO with other recent or classic methods using different evaluating measures. The experimental results show that our method not only can quickly handle epistasis, but also can effectively detect heterogeneity of complex population structures. [ABSTRACT FROM AUTHOR]

Epistasis and genetic variance heterogeneity are two non-additive genetic inheritance patterns that are often, but not always, related. Here we use theoretical examples and empirical results from earlier analyses of experimental data to illustrate the connection between the two. This includes an introduction to the relationship between epistatic gene action, statistical epistasis, and genetic variance heterogeneity, and a brief discussion about how genetic processes other than epistasis can also give rise to genetic variance heterogeneity. [ABSTRACT FROM AUTHOR]

Evo-devo is a theory proposed to study how phenotypes evolve by comparing the developmental processes of different organisms or the same organism experiencing changing environments. It has been recognized that nonallelic interactions at different genes or quantitative trait loci, known as epistasis, may play a pivotal role in the evolution of development, but it has proven difficult to quantify and elucidate this role into a coherent picture. We implement a high-dimensional genomewide association study model into the evo-devo paradigm and pack it into the R-based Evo-Devo-EpiR, aimed at facilitating the genome-wide landscaping of epistasis for the diversification of phenotypic development. By analyzing a highthroughput assay of DNA markers and their pairs simultaneously, Evo-Devo-EpiR is equipped with a capacity to systematically characterize various epistatic interactions that impact on the pattern and timing of development and its evolution. Enabling a global search for all possible genetic interactions for developmental processes throughout the whole genome, Evo-Devo-EpiR provides a computational tool to illustrate a precise genotype-phenotype map at interface between epistasis, development and evolution. [ABSTRACT FROM AUTHOR]

Key message : Complementing genomic data with other 'omics' predictors can increase the probability of success for predicting the best hybrid combinations using complex agronomic traits. Abstract: Accurate prediction of traits with complex genetic architecture is crucial for selecting superior candidates in animal and plant breeding and for guiding decisions in personalized medicine. Whole-genome prediction has revolutionized these areas but has inherent limitations in incorporating intricate epistatic interactions. Downstream 'omics' data are expected to integrate interactions within and between different biological strata and provide the opportunity to improve trait prediction. Yet, predicting traits from parents to progeny has not been addressed by a combination of 'omics' data. Here, we evaluate several 'omics' predictors-genomic, transcriptomic and metabolic data-measured on parent lines at early developmental stages and demonstrate that the integration of transcriptomic with genomic data leads to higher success rates in the correct prediction of untested hybrid combinations in maize. Despite the high predictive ability of genomic data, transcriptomic data alone outperformed them and other predictors for the most complex heterotic trait, dry matter yield. An eQTL analysis revealed that transcriptomic data integrate genomic information from both, adjacent and distant sites relative to the expressed genes. Together, these findings suggest that downstream predictors capture physiological epistasis that is transmitted from parents to their hybrid offspring. We conclude that the use of downstream 'omics' data in prediction can exploit important information beyond structural genomics for leveraging the efficiency of hybrid breeding. [ABSTRACT FROM AUTHOR]

The discovery of higher-order epistatic interactions is an important task in the field of genome wide association studies which allows for the identification of complex interaction patterns between multiple genetic markers. Some existing bruteforce approaches explore the whole space of k-interactions in an exhaustive manner resulting in almost intractable execution times. Computational cost can be reduced drastically by restricting the search space with suitable preprocessing filters which prune unpromising candidates. Other approaches mitigate the execution time by employing massively parallel accelerators in order to benefit from the vast computational resources of these architectures. In this paper, we combine a novel preprocessing filter, namely SingleMI, with massively parallel computation on modern GPUs to further accelerate epistasis discovery. Our implementation improves both the runtime and accuracy when compared to a previous GPU counterpart that employs mutual information clustering for prefiltering. SingleMI is open source software and publicly available at: . [ABSTRACT FROM AUTHOR]

The genetics of yield and its contributing traits was studied through generation mean analysis by using ten inbreds, their 45 F1 crosses by following diallel mating design, their corresponding F2, BC1 and BC2 progenies. The scaling test of A, B, C were significant indicating role of epistatic effects. In general, the magnitude of dominance effect was higher than additive effect indicating that yield and its components are largely governed by dominance effect. A breeding procedure which exploit both additive and dominance components, such as family selection with intermating, will be suitable for improvement of yield and its traits. The epistasis was complementary and duplicate type in the crosses for grain yield and its contributing traits. [ABSTRACT FROM AUTHOR]

Understanding genome and gene function in a whole organism requires us to fully comprehend the life cycle and the physiology of the organism in question. Caenorhabditis elegans XX animals are hermaphrodites that exhaust their sperm after 3 d of egg-laying. Even though C. elegans can live for many days after cessation of egg-laying, the molecular physiology of this state has not been as intensely studied as other parts of the life cycle, despite documented changes in behavior and metabolism. To study the effects of sperm depletion and aging of C. elegans during the first 6 d of adulthood, we measured the transcriptomes of first-day adult hermaphrodites and sixth-day sperm-depleted adults, and, at the same time points, mutant fog-2(lf) worms that have a feminized germline phenotype. We found that we could separate the effects of biological aging from sperm depletion. For a large subset of genes, young adult fog-2(lf) animals had the same gene expression changes as sperm-depleted sixth-day wild-type hermaphrodites, and these genes did not change expression when fog-2(lf) females reached the sixth day of adulthood. Taken together, this indicates that changing sperm status causes a change in the internal state of the worm, which we call the female-like state. Our data provide a high-quality picture of the changes that happen in global gene expression throughout the period of early aging in the worm. [ABSTRACT FROM AUTHOR]

Beneficial mutations are the driving force of adaptive evolution. In asexual populations, the identification of beneficial alleles is confounded by the presence of genetically linked hitchhiker mutations. Parallel evolution experiments enable the recognition of common targets of selection; yet these targets are inherently enriched for genes of large target size and mutations of large effect. A comprehensive study of individual mutations is necessary to create a realistic picture of the evolutionarily significant spectrum of beneficial mutations. Here we use a bulk-segregant approach to identify the beneficial mutations across 11 lineages of experimentally evolved yeast populations. We report that nearly 80% of detected mutations have no discernible effects on fitness and less than 1% are deleterious. We determine the distribution of driver and hitchhiker mutations in 31 mutational cohorts, groups of mutations that arise synchronously from low frequency and track tightly with one another. Surprisingly, we find that one-third of cohorts lack identifiable driver mutations. In addition, we identify intracohort synergistic epistasis between alleles of hsl7 and kel1, which arose together in a low-frequency lineage. [ABSTRACT FROM AUTHOR]

Despite the growing number of studies showing that genotype × environment and epistatic interactions control fitness, the influences of epistasis × environment interactions on adaptive trait evolution remain largely uncharacterized., Across three field trials, we quantified aliphatic glucosinolate ( GSL) defense chemistry, leaf damage, and relative fitness using mutant lines of Arabidopsis thaliana varying at pairs of causal aliphatic GSL defense genes to test the impact of epistatic and epistasis × environment interactions on adaptive trait variation., We found that aliphatic GSL accumulation was primarily influenced by additive and epistatic genetic variation, leaf damage was primarily influenced by environmental variation and relative fitness was primarily influenced by epistasis and epistasis × environment interactions. Epistasis × environment interactions accounted for up to 48% of the relative fitness variation in the field. At a single field site, the impact of epistasis on relative fitness varied significantly over 2 yr, showing that epistasis × environment interactions within a location can be temporally dynamic., These results suggest that the environmental dependency of epistasis can profoundly influence the response to selection, shaping the adaptive trajectories of natural populations in complex ways, and deserves further consideration in future evolutionary studies. [ABSTRACT FROM AUTHOR]

Adaptive diversification is an essential evolutionary process, one that produces phenotypic innovations including the colonization of available ecological niches. Bacteria can diverge in sympatry when ecological opportunities allow, but the underlying genetic mechanisms are often unknown. Perhaps, the longest-lasting adaptive diversification seen in the laboratory occurred during the long-term evolution experiment, in which 12 populations of Escherichia coli have been evolving independently for more than 65,000 generations from a common ancestor. In one population, two lineages, S and L, emerged at ~6500 generations and have dynamically coexisted ever since by negative frequency-dependent interactions mediated, in part, by acetate secretion by L. Mutations in spoT, arcA, and gntR promoted the emergence of the S lineage, although they reproduced only partially its phenotypic traits. Here, we characterize the evolved mechanism of acetate consumption by the S lineage that enabled invasion and coexistence with the L lineage. We identified an additional mutation in acs that, together with the arcA mutation, drove an early restructuring of the transcriptional control of central metabolism in S, leading to improved acetate consumption. Pervasive epistatic interactions within the S genome contributed to the exploitation of this new ecological opportunity. The emergence and maintenance of this long-term polymorphism is a complex multi-step process. [ABSTRACT FROM AUTHOR]

Motivation: Detecting epistatic interactions in genome-wide association studies (GWAS) is a computational challenge. Such huge numbers of single-nucleotide polymorphism (SNP) combinations limit the some of the powerful algorithms to be applied to detect the potential epistasis in largescale SNP datasets. Approach: We propose a new algorithm which combines the differential evolution (DE) algorithm with a classification based multifactor-dimensionality reduction (CMDR), termed DECMDR. DECMDR uses the CMDR as a fitness measure to evaluate values of solutions in DE process for scanning the potential statistical epistasis in GWAS. Results: The results indicated that DECMDR outperforms the existing algorithms in terms of detection success rate by the large simulation and real data obtained from the Wellcome Trust Case Control Consortium. For running time comparison, DECMDR can efficient to apply the CMDR to detect the significant association between cases and controls amongst all possible SNP combinations in GWAS. [ABSTRACT FROM AUTHOR]

Epistasis, commonly defined as the interaction between multiple genes, is an important genetic component underlying phenotypic variation. Many statistical methods have been developed to model and identify epistatic interactions between genetic variants. However, because of the large combinatorial search space of interactions, most epistasis mapping methods face enormous computational challenges and often suffer from low statistical power due to multiple test correction. Here, we present a novel, alternative strategy for mapping epistasis: instead of directly identifying individual pairwise or higher-order interactions, we focus on mapping variants that have non-zero marginal epistatic effects—the combined pairwise interaction effects between a given variant and all other variants. By testing marginal epistatic effects, we can identify candidate variants that are involved in epistasis without the need to identify the exact partners with which the variants interact, thus potentially alleviating much of the statistical and computational burden associated with standard epistatic mapping procedures. Our method is based on a variance component model, and relies on a recently developed variance component estimation method for efficient parameter inference and p-value computation. We refer to our method as the “MArginal ePIstasis Test”, or MAPIT. With simulations, we show how MAPIT can be used to estimate and test marginal epistatic effects, produce calibrated test statistics under the null, and facilitate the detection of pairwise epistatic interactions. We further illustrate the benefits of MAPIT in a QTL mapping study by analyzing the gene expression data of over 400 individuals from the GEUVADIS consortium. [ABSTRACT FROM AUTHOR]

Background: Identifying epistasis or epistatic interactions, which refer to nonlinear interaction effects of single nucleotide polymorphisms (SNPs), is essential to understand disease susceptibility and to detect genetic architectures underlying complex diseases. Though many works have been done for identifying epistatic interactions, due to their methodological and computational challenges, the algorithmic development is still ongoing. Results: In this study, a method epiACO is proposed to identify epistatic interactions, which based on ant colony optimization algorithm. Highlights of epiACO are the introduced fitness function Svalue, path selection strategies and a memory based strategy. The Svalue leverages the advantages of both mutual information and Bayesian network to effectively and efficiently measure associations between SNP combinations and the phenotype. Two path selection strategies, i.e., probabilistic path selection strategy and stochastic path selection strategy, are provided to adaptively guide ant behaviors of exploration and exploitation. The memory based strategy is designed to retain candidate solutions found in the previous iterations and compare them to solutions of the current iteration to generate new candidate solutions, yielding a more accurate way for identifying epistasis. Conclusions: Experiments of epiACO and its comparison with other recent methods epiMODE, TEAM, BOOST, SNPRuler, AntEpiSeeker, AntMiner, MACOED and IACO are performed on both simulation data sets and a real data set of age-related macular degeneration. Results show that epiACO is promising in identifying epistasis and might be an alternative to existing methods. [ABSTRACT FROM AUTHOR]

Cancer aggressiveness and its effect on patient survival depends on mutations in the tumor genome. Epistatic interactions between the mutated genes may guide the choice of anticancer therapy and set predictive factors of its success. Inhibitors targeting synthetic lethal partners of genes mutated in tumors are already utilized for efficient and specific treatment in the clinic. The space of possible epistatic interactions, however, is overwhelming, and computational methods are needed to limit the experimental effort of validating the interactions for therapy and characterizing their biomarkers. Here, we introduce SurvLRT, a statistical likelihood ratio test for identifying epistatic gene pairs and triplets from cancer patient genomic and survival data. Compared to established approaches, SurvLRT performed favorable in predicting known, experimentally verified synthetic lethal partners of PARP1 from TCGA data. Our approach is the first to test for epistasis between triplets of genes to identify biomarkers of synthetic lethality-based therapy. SurvLRT proved successful in identifying the known gene TP53BP1 as the biomarker of success of the therapy targeting PARP in BRCA1 deficient tumors. Search for other biomarkers for the same interaction revealed a region whose deletion was a more significant biomarker than deletion of TP53BP1. With the ability to detect not only pairwise but twelve different types of triple epistasis, applicability of SurvLRT goes beyond cancer therapy, to the level of characterization of shapes of fitness landscapes. [ABSTRACT FROM AUTHOR]

For over a decade functional gene-to-gene interaction (epistasis) has been suspected to be a determinant in the "missing heritability" of complex traits. However, searching for epistasis on the genome-wide scale has been challenging due to the prohibitively large number of tests which result in a serious loss of statistical power as well as computational challenges. In this article, we propose a two-stage method applicable to existing case-control data sets, which aims to lessen both of these problems by pre-assessing whether a candidate pair of genetic loci is involved in epistasis before it is actually tested for interaction with respect to a complex phenotype. The pre-assessment is based on a two-locus genotype independence test performed in the sample of cases. Only the pairs of loci that exhibit non-equilibrium frequencies are analyzed via a logistic regression score test, thereby reducing the multiple testing burden. Since only the computationally simple independence tests are performed for all pairs of loci while the more demanding score tests are restricted to the most promising pairs, genome-wide association study (GWAS) for epistasis becomes feasible. By design our method provides strong control of the type I error. Its favourable power properties especially under the practically relevant misspecification of the interaction model are illustrated. Ready-to-use software is available. Using the method we analyzed Parkinson's disease in four cohorts and identified possible interactions within several SNP pairs in multiple cohorts. [ABSTRACT FROM AUTHOR]

Gupta et al., in their article in this issue ('Niche construction in evolutionary theory: the construction of an academic niche?'. doi:), lament 'serious problems with the way science is being done' and suggest that 'niche construction theory exemplifies this state of affairs.' However, their aggressively confrontational but superficial critique of niche construction theory (NCT) only contributes to these problems by attacking claims that NCT does not make. This is unfortunate, as their poor scholarship has done a disservice to the evolutionary biology community through propagating misinformation. We correct Gupta et al.'s misunderstandings, stressing that NCT does not suggest that the fact that organisms engage in niche construction is neglected, nor does it make strong claims on the basis of its formal theory. Moreover, the treatment of niche construction as an evolutionary process has been highly productive, and is both theoretically and empirically well-validated. We end by reflecting on the potentially deleterious implications of their publication for evolutionary science. [ABSTRACT FROM AUTHOR]

Many mutations have deleterious phenotypic effects that can be alleviated by suppressor mutations elsewhere in the genome. High-throughput approaches have facilitated the large-scale identification of these suppressors and have helped shed light on core functional mechanisms that give rise to suppression. Following reports that suppression occurs naturally within species, it is important to determine how our understanding of this phenomenon based on lab experiments extends to genetically diverse natural populations. Although suppression is typically mediated by individual genetic changes in lab experiments, recent studies have shown that suppression in natural populations can involve combinations of genetic variants. This difference in complexity suggests that sets of variants can exhibit similar functional effects to individual suppressors found in lab experiments. In this review, we discuss how characterizing the way in which these variants jointly lead to suppression could provide important insights into the genotype-phenotype map that are relevant to evolution and health. [ABSTRACT FROM AUTHOR]

The experiment comprised of six F1's, which were selected based on the combinations of low yield × high yield and low ASI × high ASI. The selected six F1's were crossed in full diallel mating design to synthesise 16 double crosses was estimated and validated on the basis of performance of their constituent single crosses. Out of 16 hybrids, DCH 15 recorded lower tasseling and silking days and hence it can be used further in breeding programme. While, DCH 13 recorded narrow mean for ASI are suggested for use in deriving superior inbred lines with a combination of narrow ASI and higher ear circumference and kernel rows ear-1.The expected yield performance of DCH 5 (125.88), DCH 8 (124.23), DCH 10 (123.96), DCH 15 (123.73), DCH 6 (122.77) and DCH 12 (120.76) out yielded best check, Hema (119.00) for grain yield plant-1respectively. DCH 12 predicted better for most of the characters viz., ASI, ear length, ear circumference, kernel rows-1 and 100 grain weight. While, DCH 15 predicted better for characters viz., days to tasseling, days to silking, plant height (cm), ear height (cm), kernels row-1 and shelling percentage. Therefore, these two crosses may be used as double cross hybrids for breeding programme. In both prediction methods, nearly 14 out of 16 double cross hybrids manifested significant differences between realised and predicted performance suggesting involvement of epistasis in genetic control of grain yield plant-1. [ABSTRACT FROM AUTHOR]

Recognition and rejection of heterospecific male gametes occurs in a broad range of taxa, although the complexity of mechanisms underlying these components of postmating cryptic female choice is poorly understood. In plants, the arena for postmating interactions is the female reproductive tract (pistil), within which heterospecific pollen tube growth can be arrested via active molecular recognition and rejection. Unilateral incompatibility (UI) is one such postmating barrier in which pollen arrest occurs in only one direction of an interspecific cross. We investigated the genetic basis of pistil-side UI between Solanum species, with the specific goal of understanding the role and magnitude of epistasis between UI QTL. Using heterospecific introgression lines (ILs) between Solanum pennellii and S. lycopersicum, we assessed the individual and pairwise effects of three chromosomal regions (ui1.1, ui3.1, and ui12.1) previously associated with interspecific UI among Solanum species. Specifically, we generated double introgression ('pyramided') genotypes that combined ui12.1 with each of ui1.1 and ui3.1, and assessed the strength of UI pollen rejection in the pyramided lines, compared to single introgression genotypes. We found that none of the three QTL individually showed UI rejection phenotypes, but lines combining ui3.1 and ui12.1 showed significant pistil-side pollen rejection. Furthermore, double ILs (DILs) that combined different chromosomal regions overlapping ui3.1 differed significantly in their rate of UI, consistent with at least two genetic factors on chromosome three contributing quantitatively to interspecific pollen rejection. Together, our data indicate that loci on both chromosomes 3 and 12 are jointly required for the expression of UI between S. pennellii and S. lycopersicum, suggesting that coordinated molecular interactions among a relatively few loci underlie the expression of this postmating prezygotic barrier. In addition, in conjunction with previous data, at least one of these loci appears to also contribute to conspecific self-incompatibility (SI), consistent with a partially shared genetic basis between inter- and intraspecific mechanisms of postmating prezygotic female choice. [ABSTRACT FROM AUTHOR]

A low-activity variant of endoplasmic reticulum aminopeptidase 1 (ERAP1), Hap10, is associated with the autoinflammatory disorder Behçet's disease (BD) in epistasis with HLA-B*51, which is the main risk factor for this disorder. The role of Hap10 in BD pathogenesis is unknown. We sought to define the effects of Hap10 on the HLA-B*51 peptidome and to distinguish these effects from those due to HLA-B*51 polymorphisms unrelated to disease. The peptidome of the BD-associated HLA-B*51:08 subtype expressed in a Hap10-positive cell line was isolated, characterized by mass spectrometry, and compared with the HLA-B*51:01 peptidome from cells expressing more active ERAP1 allotypes. We additionally performed synthetic peptide digestions with recombinant ERAP1 variants and estimated peptide-binding affinity with standard algorithms. In the BD-associated ERAP1 context of B*51:08, longer peptides were generated; of the two major HLA-B*51 subpeptidomes with Pro-2 and Ala-2, the former one was significantly reduced, and the latter was increased and showed more ERAP1-susceptible N-terminal residues. These effects were readily explained by the low activity of Hap10 and the differential susceptibility of X-Pro and X-Ala bonds to ERAP1 trimming and together resulted in a significantly altered peptidome with lower affinity. The differences due to ERAP1 were clearly distinguished from those due to HLA-B*51 subtype polymorphism, which affected residue frequencies at internal positions of the peptide ligands. The alterations in the nature and affinity of HLA-B*51·peptide complexes probably affect T-cell and natural killer cell recognition, providing a sound basis for the joint association of ERAP1 and HLA-B*51 with BD. [ABSTRACT FROM AUTHOR]

Exploration of multi-locus evolution is critically important for understanding evolutionary dynamics. Recombination and epistasis lead to complex evolutionary dynamics. Quantifying the stability and function of such multi-locus evolutionary systems globally is a long-standing challenge for evolutionary biologists. The conventional Wright, Fisher and quasi-linkage equilibrium (QLE) theories can only be applied to highly restricted, simplified and special evolutionary scenarios. In this study, we developed a non-equilibrium potential and flux landscape theory to explore the multi-locus evolution beyond Wright, Fisher and the QLE. We found that the intrinsic potential landscape as a Lyapunov function under the zero noise limit can be used to describe the global stability of a deterministic multi-locus system. We identified and quantified two driving forces responsible for multi-locus evolution: the underlying landscape and the curl flux. We studied the evolution of different cases under recombination, epistasis and mutation. Recombination, frequency-dependent selection and mutation can give rise to non-zero curl flux. In particular, we investigated the dynamics of a simple example of a two-locus system. We explored the underlying potential landscape which shows stable basins attracting the system down to valleys and rotating curl flux, which aids the global communication under recombination, epistasis and mutation. Discontinuities in the first derivative of the non-equilibrium free energy functional shows the non-equilibrium phase transition as the recombination rate increases. We also explored the effect of epistasis on mono-stability and bi-stability evolution. Mutation may drive the system far from equilibrium and be another source of non-zero probability flux. Entropy production rate can quantify energy consumption or dissipation. We explained the origin of the Red Queen hypothesis for endless evolution using the curl flux. Our landscape and flux framework can be applied more generally to multi-locus evolutionary systems experiencing recombination and epistasis. [ABSTRACT FROM AUTHOR]

The role of epistasis in understanding the genetic architecture and variation of quantitative traits and its role, if any, in artificial selection and livestock improvement more generally has a long and sometimes controversial history. Its presence has been clearly demonstrated in, for example, laboratory experiments, but the amount of variation it contributes is likely to be small in outbred populations. In a finite population, although additive x additive epistatic variance is lost by genetic drift, it also contributes by conversion to additive variance through drift sampling and therefore has a potential indirect role in medium and long-term selection response, with superficial similarity to and hard to distinguish from mutation. Whilst predictions of response require knowledge of genetic parameters, an infinitesimal model provides some analytic results. Otherwise there is little quantitative information relevant to animal populations on which to judge this potential role of epistasis and reach firm conclusions. [ABSTRACT FROM AUTHOR]

Mycobacterium tuberculosis Beijing genotype strains increasingly circulate in different world regions, either as historical endemic, e.g. in East Asia, or recently imported, e.g. in South America, and this family is regarded as the most successful lineage of the global tuberculosis (TB) epidemic. Here we analysed the transmission capacity of these strains in the context of their phylogenetic background and drug resistance mutations. The study collection included all multidrug resistant (MDR) strains of Beijing genotype isolated in Beijing Chest Hospital, the largest tertiary TB facility in North China, in 2011–2013 ( n  = 278). Strains were subjected to NTF/IS 6110 and 24-loci MIRU-VNTR analysis. Drug resistance mutations were detected in rpoB , katG , inhA and oxyR–ahpC . A total of 58 and 220 strains were assigned to the ancient and modern Beijing sublineages, respectively. 24-MIRU-VNTR clustering was higher in modern versus ancient Beijing strains (35.9% vs. 12.1%; P  <   0.001). After taking into consideration the presence of rpoB and katG mutations, clustering decreased to 15.9% in modern and 0% in ancient strains. The most frequent combination of mutations ( rpoB 531-TTG and katG 315-ACC) was more prevalent in clustered versus non-clustered isolates in the modern sublineage (23/35 vs. 47/185; P  <   0.0001). To conclude, a combination of the known low-fitness-cost rpoB 531-TTG and katG 315-ACC mutations likely facilitates the increased transmission ability of MDR strains of the modern but not ancient Beijing sublineage. Accordingly, positive epistasis of major low-cost drug resistance-conferring mutations is influenced by the phylogenetic background of M. tuberculosis strains. [ABSTRACT FROM AUTHOR]

The article focuses on the challenges regarding the use of genetic mapping to detect epistasis. It is noted that multiple testing is a common challenge in genome-wide scans for epistasis while statistical power is a related difficulty that genome-wide scans for epistasis face. It is mentioned that as inbred lines allows unambiguous cataloging of the variants, using them as the founders of crosses is desirable.

Background: Aspirin Exacerbated Respiratory Disease (AERD) is a chronic medical condition that encompasses asthma, nasal polyposis, and hypersensitivity to aspirin and other non-steroidal anti-inflammatory drugs. Several previous studies have shown that part of the genetic effects of the disease may be induced by the interaction of multiple genetic variants. However, heavy computational cost as well as the complexity of the underlying biological mechanism has prevented a thorough investigation of epistatic interactions and thus most previous studies have typically considered only a small number of genetic variants at a time. Methods: In this study, we propose a gene network based analysis framework to identify genetic risk factors from a genome-wide association study dataset. We first derive multiple single nucleotide polymorphisms (SNP)-based epistasis networks that consider marginal and epistatic effects by using different information theoretic measures. Each SNP epistasis network is converted into a gene-gene interaction network, and the resulting gene networks are combined as one for downstream analysis. The integrated network is validated on existing knowledgebase of DisGeNET for known gene-disease associations and GeneMANIA for biological function prediction. Results: We demonstrated our proposed method on a Korean GWAS dataset, which has genotype information of 440,094 SNPs for 188 cases and 247 controls. The topological properties of the generated networks are examined for scale-freeness, and we further performed various statistical analyses in the Allergy and Asthma Portal (AAP) using the selected genes from our integrated network. Conclusions: Our result reveals that there are several gene modules in the network that are of biological significance and have evidence for controlling susceptibility and being related to the treatment of AERD. [ABSTRACT FROM AUTHOR]

Background: Epistasis plays an essential rule in understanding the regulation mechanisms and is an essential component of the genetic architecture of the gene expressions. However, interaction analysis of gene expressions remains fundamentally unexplored due to great computational challenges and data availability. Due to variation in splicing, transcription start sites, polyadenylation sites, post-transcriptional RNA editing across the entire gene, and transcription rates of the cells, RNA-seq measurements generate large expression variability and collectively create the observed position level read count curves. A single number for measuring gene expression which is widely used for microarray measured gene expression analysis is highly unlikely to sufficiently account for large expression variation across the gene. Simultaneously analyzing epistatic architecture using the RNA-seq and whole genome sequencing (WGS) data poses enormous challenges. Methods: We develop a nonlinear functional regression model (FRGM) with functional responses where the position-level read counts within a gene are taken as a function of genomic position, and functional predictors where genotype profiles are viewed as a function of genomic position, for epistasis analysis with RNA-seq data. Instead of testing the interaction of all possible pair-wises SNPs, the FRGM takes a gene as a basic unit for epistasis analysis, which tests for the interaction of all possible pairs of genes and use all the information that can be accessed to collectively test interaction between all possible pairs of SNPs within two genome regions. Results: By large-scale simulations, we demonstrate that the proposed FRGM for epistasis analysis can achieve the correct type 1 error and has higher power to detect the interactions between genes than the existing methods. The proposed methods are applied to the RNA-seq and WGS data from the 1000 Genome Project. The numbers of pairs of significantly interacting genes after Bonferroni correction identified using FRGM, RPKM and DESeq were 16,2361, 260 and 51, respectively, from the 350 European samples. Conclusions: The proposed FRGM for epistasis analysis of RNA-seq can capture isoform and position-level information and will have a broad application. Both simulations and real data analysis highlight the potential for the FRGM to be a good choice of the epistatic analysis with sequencing data. [ABSTRACT FROM AUTHOR]

Background: Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. Methods: In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Results: Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. Conclusions: We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes. [ABSTRACT FROM AUTHOR]

High-order epistasis—where the effect of a mutation is determined by interactions with two or more other mutations—makes small, but detectable, contributions to genotype-fitness maps. While epistasis between pairs of mutations is known to be an important determinant of evolutionary trajectories, the evolutionary consequences of high-order epistasis remain poorly understood. To determine the effect of high-order epistasis on evolutionary trajectories, we computationally removed high-order epistasis from experimental genotype-fitness maps containing all binary combinations of five mutations. We then compared trajectories through maps both with and without high-order epistasis. We found that high-order epistasis strongly shapes the accessibility and probability of evolutionary trajectories. A closer analysis revealed that the magnitude of epistasis, not its order, predicts is effects on evolutionary trajectories. We further find that high-order epistasis makes it impossible to predict evolutionary trajectories from the individual and paired effects of mutations. We therefore conclude that high-order epistasis profoundly shapes evolutionary trajectories through genotype-fitness maps. [ABSTRACT FROM AUTHOR]

Microbes often engage in cooperation through releasing biosynthetic compounds required by other species to grow. Given that production of costly biosynthetic metabolites is generally subjected to multiple layers of negative feedback, single mutations may frequently be insufficient to generate cooperative phenotypes. Synergistic epistatic interactions between multiple coordinated changes may thus often underlie the evolution of cooperation through overproduction of metabolites. To test the importance of synergistic mutations in cooperation we used an engineered bacterial consortium of an Escherichia coli methionine auxotroph and Salmonella enterica. S. enterica relies on carbon by-products from E. coli if lactose is the only carbon source. Directly selecting wild-type S. enterica in an environment that favored cooperation through secretion of methionine only once led to a methionine producer, and this producer both took a long time to emerge and was not very effective at cooperating. On the other hand, when an initial selection for resistance of S. enterica to a toxic methionine analog, ethionine, was used, subsequent selection for cooperation with E. coli was rapid, and the resulting double mutants were much more effective at cooperation. We found that potentiating mutations in metJ increase expression of metA, which encodes the first step of methionine biosynthesis. This increase in expression is required for the previously identified actualizing mutations in metA to generate cooperation. This work highlights that where biosynthesis of metabolites involves multiple layers of regulation, significant secretion of those metabolites may require multiple mutations, thereby constraining the evolution of cooperation. [ABSTRACT FROM AUTHOR]

Negative selection against deleterious alleles produced by mutation influences within-population variation as the most pervasive form of natural selection. However, it is not known whether deleterious alleles affect fitness independently, so that cumulative fitness loss depends exponentially on the number of deleterious alleles, or synergistically, so that each additional deleterious allele results in a larger decrease in relative fitness. Negative selection with synergistic epistasis should produce negative linkage disequilibrium between deleterious alleles and, therefore, an underdispersed distribution of the number of deleterious alleles in the genome. Indeed, we detected underdispersion of the number of rare loss-of-function alleles in eight independent data sets from human and fly populations. Thus, selection against rare protein-disrupting alleles is characterized by synergistic epistasis, which may explain how human and fly populations persist despite high genomic mutation rates. [ABSTRACT FROM AUTHOR]

Ankylosing spondylitis (AS) is an inflammatory disease strongly associated with the Major Histocompatibility Complex class I (MHC-I) allotype HLA-B*27. The endoplasmic reticulum aminopeptidases (ERAP)1 and 2, which trim peptides to their optimal length for MHC-I binding, are also susceptibility factors for this disease. Both highly active ERAP1 variants and ERAP2 expression favor AS, whereas loss-of-function ERAP1 and loss-of-expression ERAP2 variants are protective. Yet, only ERAP1 is in epistasis with HLA-B*27. We addressed two issues concerning the functional interaction of ERAP1 and ERAP2 with the HLA-B*27 peptidome in human cells: 1) distinguishing the effects of ERAP1 from those of ERAP2, and 2) determining the influence of ERAP2 in distinct ERAP1 contexts. Quantitative comparisons of the HLA-B*27:05 peptidomes from cells with various ERAP1/ERAP2 phenotypes were carried out. When cells expressing ERAP2 and either high or low activity ERAP1 variants were compared, increased amounts of nonamers, relative to longer ligands, and decreased amounts of peptides with Ala1, were observed in the more active ERAP1 context. When cells expressing ERAP2 in a low activity ERAP1 context or lacking ERAP2 but expressing a highly active ERAP1 variant were compared, the same effects on peptide length and Ala1, but also significantly lower amounts of peptides with N-terminal basic residues and lower affinity of the peptidome, were observed in the ERAP2-positive context. Thus, ERAP1 and ERAP2 have significant and distinct effects on the HLA-B*27 peptidome, suggesting that both enzymes largely act as separate entities in viv o. This may explain their different patterns of association with AS. [ABSTRACT FROM AUTHOR]

The era of genome-wide association studies (GWAS) has led to the discovery of numerous genetic variants associated with disease. Better understanding of whether these or other variants interact leading to differential risk compared with individual marker effects will increase our understanding of the genetic architecture of disease, which may be investigated using the family-based study design. We present M-TDT (the multi-locus transmission disequilibrium test), a tool for detecting family-based multi-locus multi-allelic effects for qualitative or quantitative traits, extended from the original transmission disequilibrium test (TDT). Tests to handle the comparison between additive and epistatic models, lack of independence between markers and multiple offspring are described. Performance of M-TDT is compared with a multifactor dimensionality reduction (MDR) approach designed for investigating families in the hypothesis-free genome-wide setting (the multifactor dimensionality reduction pedigree disequilibrium test, MDR-PDT). Other methods derived from the TDT or MDR to investigate genetic interaction in the family-based design are also discussed. The case of three independent biallelic loci is illustrated using simulations for one- to three-locus alternative hypotheses. M-TDT identified joint-locus effects and distinguished effectively between additive and epistatic models. We showed a practical example of M-TDT based on three genes already known to be implicated in malaria susceptibility. Our findings demonstrate the value of M-TDT in a hypothesis-driven context to test for multi-way epistasis underlying common disease etiology, whereas MDR-PDT-based methods are more appropriate in a hypothesis-free genome-wide setting. [ABSTRACT FROM AUTHOR]

Although it is well established theoretically that selective interference among mutations (Hill-Robertson interference) favours meiotic recombination, genomewide mean rates of mutation and strengths of selection appear too low to support this as the mechanism favouring recombination in nature. A possible solution to this discrepancy between theory and observation is that selection is at least intermittently very strong due to the antagonistic coevolution between a host and its parasites. The Red Queen theory posits that such coevolution generates fitness epistasis among loci, which generates negative linkage disequilibrium among beneficial mutations, which in turn favours recombination. This theory has received only limited support. However, Red Queen dynamics without epistasis may provide the ecological conditions that maintain strong and frequent selective interference in finite populations that indirectly selects for recombination. This hypothesis is developed here through the simulation of Red Queen dynamics. This approach required the development of a method to calculate the exact frequencies of multilocus haplotypes after recombination. Simulations show that recombination is favoured by the moderately weak selection of many loci involved in the interaction between a host and its parasites, which results in substitution rates that are compatible with empirical estimates. The model also reproduces the previously reported rapid increase in the rate of outcrossing in Caenorhabditis elegans coevolving with a bacterial pathogen. [ABSTRACT FROM AUTHOR]

I present analytical predictions for the equilibrium inbreeding load expected in a population under mutation, selection, and a regular mating system for any population size and for any magnitude and recessivity of the deleterious effects. Using this prediction, I deduce the relative fitness of mutant alleles with small effect on selfing to explore the situations where selfing or outcrossing are expected to evolve. The results obtained are in agreement with previous literature, showing that natural selection is expected to lead to stable equilibria where populations show either complete outcrossing or complete selfing, and that selfing is promoted by large deleterious mutation rates. I find that the evolution of selfing is favored by a large recessivity of deleterious effects, while the magnitude of homozygous deleterious effects only becomes relevant in relatively small populations. This result contradicts the standard assumption that purging in large populations will only promote selfing when homozygous deleterious effects are large, and implies that previously published results obtained assuming lethal mutations in large populations can be extrapolated to nonlethal alleles of similar recessivity. This conclusion and the general approach used in this analysis can be useful in the study of the evolution of mating systems. [ABSTRACT FROM AUTHOR]

Mutations conferring resistance to antibiotics are typically costly in the absence of the drug, but bacteria can reduce this cost by acquiring compensatory mutations. Thus, the rate of acquisition of compensatory mutations and their effects are key for the maintenance and dissemination of antibiotic resistances. While compensation for single resistances has been extensively studied, compensatory evolution of multiresistant bacteria remains unexplored. Importantly, since resistance mutations often interact epistatically, compensation of multiresistant bacteria may significantly differ from that of single-resistant strains. We used experimental evolution, next-generation sequencing, in silico simulations, and genome editing to compare the compensatory process of a streptomycin and rifampicin double-resistant Escherichia coli with those of single-resistant clones. We demonstrate that low-fitness double-resistant bacteria compensate faster than single-resistant strains due to the acquisition of compensatory mutations with larger effects. Strikingly, we identified mutations that only compensate for double resistance, being neutral or deleterious in sensitive or single-resistant backgrounds. Moreover, we show that their beneficial effects strongly decrease or disappear in conditions where the epistatic interaction between resistance alleles is absent, demonstrating that these mutations compensate for the epistasis. In summary, our data indicate that epistatic interactions between antibiotic resistances, leading to large fitness costs, possibly open alternative paths for rapid compensatory evolution, thereby potentially stabilizing costly multiple resistances in bacterial populations. [ABSTRACT FROM AUTHOR]

Effectors are molecules used by microbial pathogens to facilitate infection via effector-triggered susceptibility or tissue necrosis in their host. Much research has been focussed on the identification and elucidating the function of fungal effectors during plant pathogenesis. By comparison, knowledge of how phytopathogenic fungi regulate the expression of effector genes has been lagging. Several recent studies have illustrated the role of various transcription factors, chromosome-based control, effector epistasis, and mobilisation of endosomes within the fungal hyphae in regulating effector expression and virulence on the host plant. Improved knowledge of effector regulation is likely to assist in improving novel crop protection strategies. [ABSTRACT FROM AUTHOR]

The acquisition of a specific cellular identity is usually paralleled by a restriction of cellular plasticity. Whether and how these two processes are coordinated is poorly understood. Transcription factors called terminal selectors activate identity-specific effector genes during neuronal differentiation to define the structural and functional properties of a neuron. To study restriction of plasticity, we ectopically expressed C. elegans CHE-1, a terminal selector of ASE sensory neuron identity. In undifferentiated cells, ectopic expression of CHE-1 results in activation of ASE neuron type-specific effector genes. Once cells differentiate, their plasticity is restricted and ectopic expression of CHE-1 no longer results in activation of ASE effector genes. In striking contrast, removal of the respective terminal selectors of other sensory, inter-, or motor neuron types now enables ectopically expressed CHE-1 to activate its ASE-specific effector genes, indicating that terminal selectors not only activate effector gene batteries but also control the restriction of cellular plasticity. Terminal selectors mediate this restriction at least partially by organizing chromatin. The chromatin structure of a CHE-1 target locus is less compact in neurons that lack their resident terminal selector and genetic epistasis studies with H3K9 methyltransferases suggest that this chromatin modification acts downstream of a terminal selector to restrict plasticity. Taken together, terminal selectors activate identity-specific genes and make non-identity-defining genes less accessible, thereby serving as a checkpoint to coordinate identity specification with restriction of cellular plasticity. [ABSTRACT FROM AUTHOR]

Genome-wide studies have identified allele A (adenine) of single nucleotide polymorphism ( SNP) rs1006737 of the calcium-channel CACNA1C gene as a risk factor for both schizophrenia ( SZ) and bipolar disorder ( BD) as well as allele A for rs1344706 in the ZNF804A gene. These illnesses have also been associated with white matter abnormalities, reflected by reductions in fractional anisotropy ( FA), measured using diffusion tensor imaging ( DTI). We assessed the impact of the CACNA1C psychosis risk variant on FA in SZ, BD and health. 230 individuals (with existing ZNF804A rs1344706 genotype data) were genotyped for CACNA1C rs1006737 and underwent DTI. FA data was analysed with tract-based spatial statistics and threshold-free cluster enhancement significance correction ( P < 0.05) to detect effects of CACNA1C genotype on FA, and its potential interaction with ZNF804A genotype and with diagnosis, on FA. There was no significant main effect of the CACNA1C genotype on FA, nor diagnosis by genotype(s) interactions. Nevertheless, when inspecting SZ in particular, risk allele carriers had significantly lower FA than the protective genotype individuals, in portions of the left middle occipital and parahippocampal gyri, right cerebellum, left optic radiation and left inferior and superior temporal gyri. Our data suggests a minor involvement of CACNA1C rs1006737 in psychosis via conferring susceptibility to white matter microstructural abnormalities in SZ. Put in perspective, ZNF804A rs1344706, not only had a significant main effect, but its SZ-specific effects were two orders of magnitude more widespread than that of CACNA1C rs1006737. [ABSTRACT FROM AUTHOR]

We develop computational tools for the analysis of nonlinear genotype-phenotype relationships with epistasis among multiple loci or dominance interactions among multiple alleles within the same locus. Theory distinguishes between separable traits, with removable epistasis, and traits with essential epistasis. Separable traits can be transformed to a natural scale where additive methods apply. The methods we present solve for the natural scale, exactly when possible and approximately when not. Through graph methods, our methods allow for enumeration, counting, or sampling of distinct trait architectures satisfying constraints from the separability theory. A tool is provided for diagnosing which separability constraints are violated by a given nonseparable architecture. For genetic traits controlled by limited numbers of loci and alleles, our algorithm enumerates all possible trait structures and finds exact or error-minimizing linearizing transformations by formulating a constrained optimization program. We find that the fraction of possible distinct genetic traits satisfying simple criteria that can be fully or approximately linearized is high for small systems and falls as the number of alleles or loci increases. [ABSTRACT FROM AUTHOR]