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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]

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]

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]

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]

Generation mean analysis was carried out on six generations (P1, P2, F1, F2, B1 and B2) in four tomato crosses viz. Cross-I (H7997 x CLN 1621 E), Cross- II (H7997 x BL 337), Cross - III (H7997 x Nagcarlan) and Cross- IV (H997 x CLN 2366A). Observstions were recorded on eight yield attributing characters including yield. The presence of epistasis was recorded in all the four crosses. From six parameter model regression of the components of six parameter model on environmental indices it was evident that it was evident that additive effect played a decisive role in the inheritance of number of primary branches per plant, number of fruiting clusters per plant and fruit yield per plant. Dominance effect was found significant and consistent in one or more crosses for days to flowering, number of fruiting clusters per plant and fruit yield per plant. Duplicate epistasis was more predominant for most of the characters in the crosses. [ABSTRACT FROM AUTHOR]

The question as to why most complex organisms reproduce sexually remains a very active research area in evolutionary biology. Theories dating back to Weismann have suggested that the key may lie in the creation of increased variability in offspring, causing enhanced response to selection. Under appropriate conditions, selection is known to result in the generation of negative linkage disequilibrium, with the effect of recombination then being to increase genetic variance by reducing these negative associations between alleles. It has therefore been a matter of significant interest to understand precisely those conditions resulting in negative linkage disequilibrium, and to recognise also the conditions in which the corresponding increase in genetic variation will be advantageous. Here, we prove rigorous results for the multi-locus case, detailing the build up of negative linkage disequilibrium, and describing the long term effect on population fitness for models with and without bounds on fitness contributions from individual alleles. Under the assumption of large but finite bounds on fitness contributions from alleles, the non-linear nature of the effect of recombination on a population presents serious obstacles in finding the genetic composition of populations at equilibrium, and in establishing convergence to those equilibria. We describe techniques for analysing the long term behaviour of sexual and asexual populations for such models, and use these techniques to establish conditions resulting in higher fitnesses for sexually reproducing populations. [ABSTRACT FROM AUTHOR]

Epistatic interactions can greatly impact evolutionary phenomena, particularly the process of adaptation. Here, we leverage four parallel experimentally evolved lineages to study the emergence and trajectories of epistatic interactions in the social bacterium Myxococcus xanthus. A social gene ( pilA) necessary for effective group swarming on soft agar had been deleted from the common ancestor of these lineages. During selection for competitiveness at the leading edge of growing colonies, two lineages evolved qualitatively novel mechanisms for greatly increased swarming on soft agar, whereas the other two lineages evolved relatively small increases in swarming. By reintroducing pilA into different genetic backgrounds along the four lineages, we tested whether parallel lineages showed similar patterns of epistasis. In particular, we tested whether a pattern of negative epistasis between accumulating mutations and pilA previously found in the fastest lineage would be found only in the two evolved lineages with the fastest and most striking swarming phenotypes, or rather was due to common epistatic structure across all lineages arising from the generic fixation of adaptive mutations. Our analysis reveals the emergence of negative epistasis across all four independent lineages. Further, we present results showing that the observed negative epistasis is not due exclusively to evolving populations approaching a maximum phenotypic value that inherently limits positive effects of pilA reintroduction, but rather involves direct antagonistic interactions between accumulating mutations and the reintroduced social gene. [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]

Key message : Genome-wide association mapping as well as marker- and haplotype-based genome-wide selection unraveled a complex genetic architecture of grain yield with absence of large effect QTL and presence of local epistatic effects. Abstract: The genetic architecture of grain yield determines to a large extent the optimum design of genomic-assisted wheat breeding programs. The main goal of our study was to examine the potential and limitations to dissect the genetic architecture of grain yield in wheat using a large experimental data set. Our study was based on phenotypic information and genomic data of 13,901 SNPs of a diverse set of 3816 elite wheat lines adapted to Central Europe. We applied genome-wide association mapping based on experimental and simulated data sets and performed marker- and haplotype-based genomic prediction. Computer simulations revealed for our mapping population a high power to detect QTL, even if they individually explained only 2.5% of the genetic variation. Despite this, we found no stable marker-trait associations when validating in independent subsets. A two-dimensional scan for marker-marker interactions indicated presence of local epistasis which was further supported by improved prediction abilities when shifting from marker- to haplotype-based genome-wide prediction approaches. We observed that marker effects estimated using genome-wide prediction approaches strongly varied across years albeit resulting in high prediction abilities. Thus, our results suggested that the prediction accuracy of genomic selection in wheat is mainly driven by relatedness rather than by exploiting knowledge of the genetic architecture. [ABSTRACT FROM AUTHOR]

The article focuses on a study related to endoscopic and microscopic transsphenoidal surgery of patients for pituitary adenoma removal. It mentions patients underwent preoperatively to volumetric magnetic resonance imaging and computerized tomography scanning for surgical planning and neuronavigation. It also mentions modification of endonasal structure anatomy like nasal septum is considered as the main cause of rhinological complications, such as sinusitis and epistasis.

Potts Hamiltonian models of protein sequence co-variation are statistical models constructed from the pair correlations observed in a multiple sequence alignment (MSA) of a protein family. These models are powerful because they capture higher order correlations induced by mutations evolving under constraints and help quantify the connections between protein sequence, structure, and function maintained through evolution. We review recent work with Potts models to predict protein structure and sequence-dependent conformational free energy landscapes, to survey protein fitness landscapes and to explore the effects of epistasis on fitness. We also comment on the numerical methods used to infer these models for each application. [ABSTRACT FROM AUTHOR]

The contribution of epistasis to human disease remains unclear. However, several studies have now identified epistatic interactions between common variants that increase the risk of a neuropsychiatric disorder, while there is growing evidence that genetic interactions contribute to the pathogenicity of rare, multigenic copy-number variants (CNVs) that have been observed in patients. This review discusses the current evidence for epistatic events and genetic interactions in neuropsychiatric disorders, how paradigm shifts in the phenotypic classification of patients would empower the search for epistatic effects, and how network and cellular models might be employed to further elucidate relevant epistatic interactions. [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]

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]

The present work is the development of a simple and specific kinetic method based on RT-PCR technique coupled with direct sequencing for quantification of various amyloid precursor protein-mRNA isoforms (APP-mRNA isoforms) in biological samples, especially for identifying the most abundant one that may decisive for the normal status or disease risk. Application of this kinetic method to the Lesch-Nyhan disease (LND) was performed and results indicated an epistasis between mutated hypoxanthine phosphoribosyltransferase1 (HPRT1) and APP genes. APP-mRNA isoform of 624 bp, with a deletion starting after 49 bp of the 5′ end of exon 3 followed by a complete deletion of exons 4–15, mutations in exon 1: c.22C > T, p.L18F, and exon 3: c.269A > G, p.Q90R encoding APP 207 isoform, was the most abundant one in most of the LND patients and would be responsible for the neurobehavioral syndrome in these patients. The method is useful for identifying the defective APP-mRNA isoform in LND patients, and in neurodevelopmental and neurodegenerative disorders in which the APP gene is involved in the pathogenesis of diseases such as autism, fragile X syndrome, amyotrophic lateral sclerosis, and Alzheimer’s disease, and may pave the way for new strategies applicable to rational antisense drugs design. [ABSTRACT FROM AUTHOR]

Background: Pepino mosaic virus (PepMV) is an emerging plant pathogen that infects tomatoes worldwide. Understanding the factors that influence its evolutionary success is essential for developing new control strategies that may be more robust against the evolution of new viral strains. One of these evolutionary factors is the distribution of mutational fitness effect (DMFE), that is, the fraction of mutations that are lethal, deleterious, neutral, and beneficial on a given viral strain and host species. The goal of this study was to characterize the DMFE of introduced nonsynonymous mutations on a mild isolate of PepMV from the Chilean 2 strain (PepMV-P22). Additionally, we also explored whether the fitness effect of a given mutation depends on the gene where it appears or on epistatic interactions with the genetic background. To address this latter possibility, a subset of mutations were also introduced in a mild isolate of the European strain (PepMV-P11) and the fitness of the resulting clones measured. Results: A collection of 25 PepMV clones each containing a single nucleotide nonsynonymous substitution was created by site-directed mutagenesis and the fitness of each mutant was determined. PepMV-P22 genome showed a high degree of robustness against point mutations, with 80% of mutations being either neutral or even beneficial and only 20% being deleterious or lethal. We found that the effect of mutations strongly depended on the gene in which they were introduced. Mutations with the largest average beneficial effects were those affecting the RdRp gene, in contrast to mutations affecting TGB1 and CP genes, for which the average effects were deleterious. Moreover, significant epistatic interactions were observed between nonsynonymous mutations and the genetic background, meaning that the effect of a given nucleotide substitution on a particular genomic context cannot be predicted by knowing its effect in a different one. Conclusions: Our results indicated that PepMV genome has a surprisingly high robustness against mutations. We also found that fitness consequences of a given mutation differ between the two strains analyzed. This discovery suggests that the strength of selection, and thus the rates of evolution, vary among PepMV strains. [ABSTRACT FROM AUTHOR]

High-order epistasis has been observed in many genotype-phenotype maps. These multi-way interactions between mutations may be useful for dissecting complex traits and could have profound implications for evolution. Alternatively, they could be a statistical artifact. High-order epistasis models assume the effects of mutations should add, when they could in fact multiply or combine in some other nonlinear way. A mismatch in the "scale" of the epistasis model and the scale of the underlying map would lead to spurious epistasis. In this article, we develop an approach to estimate the nonlinear scales of arbitrary genotype-phenotype maps. We can then linearize these maps and extract high-order epistasis. We investigated seven experimental genotype-phenotype maps for which high-order epistasis had been reported previously. We find that five of the seven maps exhibited nonlinear scales. Interestingly, even after accounting for nonlinearity, we found statistically significant high-order epistasis in all seven maps. The contributions of high-order epistasis to the total variation ranged from 2.2 to 31.0%, with an average across maps of 12.7%. Our results provide strong evidence for extensive high-order epistasis, even after nonlinear scale is taken into account. Further, we describe a simple method to estimate and account for nonlinearity in genotype-phenotype maps. [ABSTRACT FROM AUTHOR]

Oilseed rape (Brassica napus) is an economically important oil crop, yet the genetic architecture of its complex traits remain largely unknown. Here, genome-wide association study was conducted for eight yield-related traits to dissect the genetic architecture of additive, dominance, epistasis, and their environment interaction. Additionally, the optimal genotype combination and the breeding value of superior line, superior hybrid and existing best line in mapping population were predicted for each trait in two environments based on the predicted genotypic effects. As a result, 17 quantitative trait SNPs (QTSs) were identified significantly for target traits with total heritability varied from 58.47 to 87.98%, most of which were contributed by dominance, epistasis, and environment-specific effects. The results indicated that non-additive effects were large contributions to heritability and epistasis, and also noted that environment interactions were important variants for oilseed breeding. Our study facilitates the understanding of genetic basis of rapeseed yield trait, helps to accelerate rapeseed breading, and also offers a roadmap for precision plant breeding via marker-assisted selection. [ABSTRACT FROM AUTHOR]

The fitness effects of a mutation can depend, sometimes dramatically, on genetic background; this phenomenon is often referred to as "epistasis." Epistasis can have important practical consequences in the context of antimicrobial resistance (AMR). For example, genetic background plays an important role in determining the costs of resistance, and hence in whether resistance will persist in the absence of antibiotic pressure. Furthermore, interactions between resistance mutations can have important implications for the evolution of multi-drug resistance. I argue that there is a need to better characterize the extent and nature of epistasis for mutations and horizontally transferred elements conferring AMR, particularly in clinical contexts. Furthermore, I suggest that epistasis should be an important consideration in attempts to slow or limit the evolution of AMR. [ABSTRACT FROM AUTHOR]

The article discusses how researcher Skwark along with colleagues harnessed population genomic data to approach the challenge of epistasis analysis .Topics discussed include developing a computational method termed genome direct coupling analysis (DCA) to detect epistasis using geno type and allele frequencies estimated from genome sequences of thousands of individuals of the same species.

Recent advances in the scale and diversity of population genomic datasets for bacteria now provide the potential for genome-wide patterns of co-evolution to be studied at the resolution of individual bases. Here we describe a new statistical method, genomeDCA, which uses recent advances in computational structural biology to identify the polymorphic loci under the strongest co-evolutionary pressures. We apply genomeDCA to two large population data sets representing the major human pathogens Streptococcus pneumoniae (pneumococcus) and Streptococcus pyogenes (group A Streptococcus). For pneumococcus we identified 5,199 putative epistatic interactions between 1,936 sites. Over three-quarters of the links were between sites within the pbp2x, pbp1a and pbp2b genes, the sequences of which are critical in determining non-susceptibility to beta-lactam antibiotics. A network-based analysis found these genes were also coupled to that encoding dihydrofolate reductase, changes to which underlie trimethoprim resistance. Distinct from these antibiotic resistance genes, a large network component of 384 protein coding sequences encompassed many genes critical in basic cellular functions, while another distinct component included genes associated with virulence. The group A Streptococcus (GAS) data set population represents a clonal population with relatively little genetic variation and a high level of linkage disequilibrium across the genome. Despite this, we were able to pinpoint two RNA pseudouridine synthases, which were each strongly linked to a separate set of loci across the chromosome, representing biologically plausible targets of co-selection. The population genomic analysis method applied here identifies statistically significantly co-evolving locus pairs, potentially arising from fitness selection interdependence reflecting underlying protein-protein interactions, or genes whose product activities contribute to the same phenotype. This discovery approach greatly enhances the future potential of epistasis analysis for systems biology, and can complement genome-wide association studies as a means of formulating hypotheses for targeted experimental work. [ABSTRACT FROM AUTHOR]

The sclera is the protective outer layer of the eye. In fishes, birds, and reptiles, the sclera may be reinforced with additional bony elements called scleral ossicles. Teleost fish vary in the number and size of scleral ossicles; however, the genetic mechanisms responsible for this variation remain poorly understood. In this study, we examine the inheritance of scleral ossicles in the Mexican tetra, Astyanax mexicanus, which exhibits both a cave morph and a surface fish morph. As these morphs and their hybrids collectively exhibit zero, one, and two scleral ossicles, they represent a microcosm of teleost scleral ossicle diversity. Our previous research in F2 hybrids of cavefish from Pachón cave and surface fish from Texas suggested that three genes likely influence the formation of scleral ossicles in this group through an epistatic threshold model of inheritance, though our sample size was small. In this study, we expand our sample size using additional hybrids of Pachón cavefish and Mexican surface fish to (1) confirm the threshold model of inheritance, (2) refine the number of genes responsible for scleral ossicle formation, and (3) increase our power to detect quantitative trait loci (QTL) for this trait. To answer these three questions, we scored surface fish and cavefish F2 hybrids for the presence of zero, one, or two scleral ossicles. We then analyzed their distribution among the F2 hybrids using a chi-square (χ2) test, and used a genetic linkage map of over 100 microsatellite markers to identify QTL responsible for scleral ossicle number. We found that inheritance of scleral ossicles follows an epistatic threshold model of inheritance controlled by two genes, which contrasts the three-locus model estimated from our previous study. Finally, the combined analysis of hybrids from both crosses identified two strong QTL for scleral ossicle number on linkage groups 4.2 and 21, and a weaker QTL on linkage group 4.1. Scleral ossification remains a complex trait with limited knowledge of its genetic basis. This study provides new insight into the number and location of genes controlling the formation of scleral ossicles in a teleost fish species. [ABSTRACT FROM AUTHOR]

We characterise the evolutionary dynamics of influenza infection described by viral sequence data collected from two challenge studies conducted in human hosts. Viral genome sequence data were collected at regular intervals from infected hosts. Changes in the sequence data observed across time show that the within-host evolution of the virus was driven by the reversion of variants acquired during previous passaging of the virus. Treatment of some patients with oseltamivir on the first day of infection did not lead to the emergence of drug resistance variants in patients. Using an evolutionary model, we inferred the effective rate of reassortment between viral segments, measuring the extent to which randomly chosen viruses within the host exchange genetic material. We find strong evidence that the rate of effective reassortment is low, such that genetic associations between polymorphic loci in different segments are preserved during the course of an infection in a manner not compatible with epistasis. Combining our evidence with that of previous studies we suggest that spatial heterogeneity in the viral population may reduce the extent to which reassortment is observed. Our results do not contradict previous findings of high rates of viral reassortment in vitro and in small animal studies, but indicate that in human hosts the effective rate of reassortment may be substantially more limited. [ABSTRACT FROM AUTHOR]

Leaf architecture traits in maize are quantitative and have been studied by quantitative trait loci ( QTLs) mapping. However, additional QTLs for these traits require mapping and the interactions between mapped QTLs require studying because of the complicated genetic nature of these traits. To detect common QTLs and to find new ones, we investigated the maize traits of leaf angle, leaf flagging-point length, leaf length and leaf orientation value using a set of recombinant inbred line populations and single nucleotide polymorphism markers. In total, 19 QTLs contributed 4.13-13.52% of the phenotypic effects to the corresponding traits that were mapped, and their candidate genes are provided. Common and major QTLs have also been detected. All of the QTLs showed significant additive effects and non-significant additive × environment effects in combined environments. The majority showed additive × additive epistasis effects and non-significant QTL × environment effects under single environments. Common and major QTLs provided information for fine mapping and gene cloning, and SNP markers can be used for marker-assisted selection breeding. [ABSTRACT FROM AUTHOR]

The role of mitochondrial DNA for the evolution of life-history traits remains debated. We examined mitonuclear effects on the activity of the multisubunit complex of the electron transport chain (ETC) involved in oxidative phosphorylation (OXPHOS) across lines of the seed beetle Acanthoscelides obtectus selected for a short (E) or a long (L) life for more than >160 generations. We constructed and phenotyped mitonuclear introgression lines, which allowed us to assess the independent effects of the evolutionary history of the nuclear and the mitochondrial genome. The nuclear genome was responsible for the largest share of divergence seen in ageing. However, the mitochondrial genome also had sizeable effects, which were sex-specific and expressed primarily as epistatic interactions with the nuclear genome. The effects of mitonuclear disruption were largely consistent with mitonuclear coadaptation. Variation in ETC activity explained a large proportion of variance in ageing and life-history traits and this multivariate relationship differed somewhat between the sexes. In conclusion, mitonuclear epistasis has played an important role in the laboratory evolution of ETC complex activity, ageing, and life histories and these are closely associated. The mitonuclear architecture of evolved differences in life-history traits and mitochondrial bioenergetics was sex-specific. [ABSTRACT FROM AUTHOR]

Epistasis, the interaction between mutations and the genetic background, is a pervasive force in evolution that is difficult to predict yet derives from a simple principle − biological systems are interconnected. Therefore, one effect may be intimately linked to another, hence interdependent. Untangling epistatic interactions between and within genes is a vibrant area of research. Deriving a mechanistic understanding of epistasis is a major challenge. Particularly, elucidating how epistasis can attenuate the effects of otherwise dominant mutations that control phenotypes. Using the emergence of terpene cyclization in specialized metabolism as an excellent example, this review describes the process of discovery and interpretation of dominance and epistasis in relation to current efforts. Specifically, we outline experimental approaches to isolating epistatic networks of mutations in protein structure, formally quantifying epistatic interactions, then building biochemical models with chemical mechanisms in efforts to achieve an understanding of the physical basis for epistasis. From these models we describe informed conjectures about past evolutionary events that underlie the emergence, divergence and specialization of terpene synthases to illustrate key principles of the constraining forces of epistasis in enzyme function. [ABSTRACT FROM AUTHOR]

Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets, yet experimentally determining whether genes interact is technically nontrivial and time- consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in,, and . By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal. [ABSTRACT FROM AUTHOR]

Background: Susceptible barcode recognition plays an important role in the diagnosis and treatment of complex diseases. Numerous approaches have been proposed to identify risky barcodes involved in the progress of complex diseases. However, some methods only consider differences in barcode frequencies between the control and disease groups; as such, these methods may be partial or even wrong. For example, some barcodes with a high risk ratio yield a low frequency on cases or exhibit a high frequency on controls, which may unreasonable from a statistical point. Results: In our study, a stricter criteria, maximum discrepancy and maximum constituency, is designed to evaluate each barcode and ant colony algorithm is used to search combination space of epistasis. For complex diseases with multi-subtypes, our method can list several potential barcodes contributing to different subtypes of complex diseases. Another contribution of this work is to introduce a method for determining the length of barcodes and excluding noisy barcodes whose frequencies are abnormal. In addition, common pathogenic genes shared by different risky barcodes are also recognized, which may provide key clue for further study, such as gene function analysis. Conclusions: Experimental results reveal that our method can find multiple risky barcodes whose risk ratio and odds ratio are >1. These barcodes could be related to different subtypes of complex diseases. [ABSTRACT FROM AUTHOR]

Independently evolving populations may adapt to similar selection pressures via different genetic changes. The interactions between such changes, such as in a hybrid individual, can inform us about what course adaptation may follow and allow us to determine whether gene flow would be facilitated or hampered following secondary contact. We used Saccharomyces cerevisiae to measure the genetic interactions between first-step mutations that independently evolved in the same biosynthetic pathway following exposure to the fungicide nystatin. We found that genetic interactions are prevalent and predominantly negative, with the majority of mutations causing lower growth when combined in a double mutant than when alone as a single mutant (sign epistasis). The prevalence of sign epistasis is surprising given the small number of mutations tested and runs counter to expectations for mutations arising in a single biosynthetic pathway in the face of a simple selective pressure. Furthermore, in one third of pairwise interactions, the double mutant grew less well than either single mutant (reciprocal sign epistasis). The observation of reciprocal sign epistasis among these first adaptive mutations arising in the same genetic background indicates that partial postzygotic reproductive isolation could evolve rapidly between populations under similar selective pressures, even with only a single genetic change in each. The nature of the epistatic relationships was sensitive, however, to the level of drug stress in the assay conditions, as many double mutants became fitter than the single mutants at higher concentrations of nystatin. We discuss the implications of these results both for our understanding of epistatic interactions among beneficial mutations in the same biochemical pathway and for speciation. [ABSTRACT FROM AUTHOR]

Background: A large amount of research has been devoted to the detection and investigation of epistatic interactions in genome-wide association studies (GWASs). Most of the literature focuses on low-order interactions between single-nucleotide polymorphisms (SNPs) with significant main effects. Results: In this paper we propose an original approach for detecting epistasis at the gene level, without systematically filtering on significant genes. We first compute interaction variables for each gene pair by finding its Eigen-Epistasis component, defined as the linear combination of Gene SNPs having the highest correlation with the phenotype. The selection of significant effects is done using a penalized regression method based on Group Lasso controlling the False Discovery Rate. Conclusion: The method is tested against two recent alternative proposals from the literature using synthetic data, and shows good performances in different settings. We demonstrate the power of our approach by detecting new gene-gene interactions on three genome-wide association studies. [ABSTRACT FROM AUTHOR]

The genetic component of complex disease risk in humans remains largely unexplained. A corollary is that the allelic spectrum of genetic variants contributing to complex disease risk is unknown. Theoretical models that relate population genetic processes to the maintenance of genetic variation for quantitative traits may suggest profitable avenues for future experimental design. Here we use forward simulation to model a genomic region evolving under a balance between recurrent deleterious mutation and Gaussian stabilizing selection. We consider multiple genetic and demographic models, and several different methods for identifying genomic regions harboring variants associated with complex disease risk. We demonstrate that the model of gene action, relating genotype to phenotype, has a qualitative effect on several relevant aspects of the population genetic architecture of a complex trait. In particular, the genetic model impacts genetic variance component partitioning across the allele frequency spectrum and the power of statistical tests. Models with partial recessivity closely match the minor allele frequency distribution of significant hits from empirical genome-wide association studies without requiring homozygous effect-sizes to be small. We highlight a particular gene-based model of incomplete recessivity that is appealing from first principles. Under that model, deleterious mutations in a genomic region partially fail to complement one another. This model of gene-based recessivity predicts the empirically observed inconsistency between twin and SNP based estimated of dominance heritability. Furthermore, this model predicts considerable levels of unexplained variance associated with intralocus epistasis. Our results suggest a need for improved statistical tools for region based genetic association and heritability estimation. [ABSTRACT FROM AUTHOR]

Although gene-gene interaction, or epistasis, plays a large role in complex traits in model organisms, genome-wide by genome-wide searches for two-way interaction have limited power in human studies. We thus used knowledge of a biological pathway in order to identify a contribution of epistasis to autism spectrum disorders (ASDs) in humans, a reverse-pathway genetic approach. Based on previous observation of increased ASD symptoms in Mendelian disorders of the Ras/MAPK pathway (RASopathies), we showed that common SNPs in RASopathy genes show enrichment for association signal in GWAS (P = 0.02). We then screened genome-wide for interactors with RASopathy gene SNPs and showed strong enrichment in ASD-affected individuals (P < 2.2 x 10−16), with a number of pairwise interactions meeting genome-wide criteria for significance. Finally, we utilized quantitative measures of ASD symptoms in RASopathy-affected individuals to perform modifier mapping via GWAS. One top region overlapped between these independent approaches, and we showed dysregulation of a gene in this region, GPR141, in a RASopathy neural cell line. We thus used orthogonal approaches to provide strong evidence for a contribution of epistasis to ASDs, confirm a role for the Ras/MAPK pathway in idiopathic ASDs, and to identify a convergent candidate gene that may interact with the Ras/MAPK pathway. [ABSTRACT FROM AUTHOR]

Epistasis describes an interaction between the effects of loci. We included epistasis in quantitative trait locus (QTL) mapping of growth at a series of ages in a cross of a Chinese pig breed, Erhualian, with a commercial line, White Duroc. Erhualian pigs have much lower growth rates than White Duroc. We improved a method for genomewide testing of epistasis and present a clear analysis workflow. We also suggest a new approach for interpreting epistasis results where significant additive and dominance effects of a locus in specific backgrounds are determined. In total, seventeen QTL were found and eleven showed epistasis. Loci on chromosomes 2, 3, 4 and 7 were highlighted as affecting growth at more than one age or forming an interaction network. Epistasis resulted in both the QTL on chromosomes 3 and 7 having effects in opposite directions. We believe it is the first time for the chromosome 7 locus that an allele from a Chinese breed has been found to decrease growth. The consequences of epistasis were diverse. Results were impacted by using growth rather than body weight as the phenotype and by correcting for an effect of mother. Epistasis made a considerable contribution to growth in this population and modelling epistasis was important for accurately determining QTL effects. [ABSTRACT FROM AUTHOR]

Background: Epistasis marker effect models incorporating products of marker values as predictor variables in a linear regression approach (extended GBLUP, EGBLUP) have been assessed as potentially beneficial for genomic prediction, but their performance depends on marker coding. Although this fact has been recognized in literature, the nature of the problem has not been thoroughly investigated so far. Results: We illustrate how the choice of marker coding implicitly specifies the model of how effects of certain allele combinations at different loci contribute to the phenotype, and investigate coding-dependent properties of EGBLUP. Moreover, we discuss an alternative categorical epistasis model (CE) eliminating undesired properties of EGBLUP and show that the CE model can improve predictive ability. Finally, we demonstrate that the coding-dependent performance of EGBLUP offers the possibility to incorporate prior experimental information into the prediction method by adapting the coding to already available phenotypic records on other traits. Conclusion: Based on our results, for EGBLUP, a symmetric coding {-1, 1} or {-1, 0, 1} should be preferred, whereas a standardization using allele frequencies should be avoided. Moreover, CE can be a valuable alternative since it does not possess the undesired theoretical properties of EGBLUP. However, which model performs best will depend on characteristics of the data and available prior information. Data from previous experiments can for instance be incorporated into the marker coding of EGBLUP. [ABSTRACT FROM AUTHOR]

The assessment of nature of gene effect for yield and its contributing traits and detection of epistasis in wheat was studied in five crosses involving seven parents through generation mean analysis. Scaling test and joint scaling test were showed significant for almost traits all crosses. Additive gene effects (d) were positively significant for days to maturity and tillers per plant in cross II; for seed per plant in cross IV. Dominance gene effects (h) were highly significant for days to 75% heading in cross II, III and IV; for days to maturity and grains per spike in cross II, for grain yield per plant and grains per spike in cross I. Additive x additive type of gene (i) were positive significant effect for days to 75% heading in cross II, III and IV; for days to maturity in cross II and grains per spike in crosses I, II; for 1000 grain weight in cross II and IV; for grain yield per plant in cross I. Additive x dominance type of gene effect (j) was positive significant for days to 75% heading in cross III; for days to maturity in cross II and III; for plant height in cross III; tillers per plant in cross II; for grain per spike and seed per plant in cross III and grain yield in cross IV. Dominance x dominance effect (l) were positively significant for days to 75% heading, plant height in cross I; for plant height in cross III, IV and V; for tillers per plant in cross II and for grains per spike in cross IV and V; seed per plant, grain yield in cross IV. Therefore, it has been suggested that selection of studied characters based on different gene action of generation mean to be used further crop improvement through ideal breeding programme. [ABSTRACT FROM AUTHOR]

The genes interact according to classical mechanisms, namely, complementation, modification, polymery, and epistasis, in the cells and organisms carrying these genes. Here we describe a novel type of gene interaction when the interacting genes reside in parents, whereas the interaction event takes place in their progenies lacking these genes. The conditional mutations in the D. melanogaster male X chromosome caused the “prohibition on producing daughters” in its offspring. The chromosomal rearrangements in chromosomes 2 and 3 of its female partner removed the prohibition. The phenomena of “prohibition” and “removal of prohibition” appeared as a parental effect in both the male and female. Both phenomena ensued from the presence of the studied mutations in parents rather than their unviable or survived progenies. Thus, the gene interaction when the genes themselves are absent at the site of interaction and during the interaction event takes place in drosophila. [ABSTRACT FROM AUTHOR]

Short tandem repeats (STRs) are hypervariable genetic elements that occur frequently in coding regions. Their high mutation rate readily generates genetic variation, contributing to adaptive evolution and human diseases. We previously reported that natural ELF3 polyglutamine variants cause reciprocal genetic incompatibilities in two divergent Arabidopsis thaliana backgrounds. Here, we dissect the genetic architecture of this incompatibility, revealing as many as four loci putatively interacting with ELF3. We were able to specifically identify one such ELF3-interacting gene, LSH9. We further used a yeast two-hybrid strategy to identify proteins whose physical interactions with ELF3 were affected by polyglutamine tract length. We found two proteins for which this was the case, ELF4 and AtGLDP1. Using these two approaches, we identify specific genetic interactions and physical mechanisms by which the ELF3 polyglutamine tract may mediate the observed genetic incompatibilities. Our work elucidates how STR variation, which is generally underascertained in population-scale sequencing, can contribute to phenotypic variation. Furthermore, our results support our proposal that highly variable STR loci can contribute to the epistatic component of heritability. [ABSTRACT FROM AUTHOR]

In systems biology and genomics, epistasis characterizes the impact that a substitution at a particular location in a genome can have on a substitution at another location. This phenomenon is often implicated in the evolution of drug resistance or to explain why particular "disease-causing" mutations do not have the same outcome in all individuals. Hence, uncovering these mutations and their locations in a genome is a central question in biology. However, epistasis is notoriously difficult to uncover, especially in fastevolving organisms. Here, we present a novel statistical approach that replies on a model developed in ecology and that we adapt to analyze genetic data in fast-evolving systems such as the influenza A virus. We validate the approach using a two-pronged strategy: extensive simulations demonstrate a low-to-moderate sensitivity with excellent specificity and precision, while analyses of experimentally validated data recover known interactions, including in a eukaryotic system. We further evaluate the ability of our approach to detect correlated evolution during antigenic shifts or at the emergence of drug resistance. We show that in all cases, correlated evolution is prevalent in influenza A viruses, involving many pairs of sites linked together in chains; a hallmark of historical contingency. Strikingly, interacting sites are separated by large physical distances, which entails either long-range conformational changes or functional tradeoffs, for which we find support with the emergence of drug resistance. Our work paves a new way for the unbiased detection of epistasis in a wide range of organisms by performing whole-genome scans. [ABSTRACT FROM AUTHOR]

Background: The Interaction Network Ontology (INO) logically represents biological interactions, pathways, and networks. INO has been demonstrated to be valuable in providing a set of structured ontological terms and associated keywords to support literature mining of gene-gene interactions from biomedical literature. However, previous work using INO focused on single keyword matching, while many interactions are represented with two or more interaction keywords used in combination. Methods: This paper reports our extension of INO to include combinatory patterns of two or more literature mining keywords co-existing in one sentence to represent specific INO interaction classes. Such keyword combinations and related INO interaction type information could be automatically obtained via SPARQL queries, formatted in Excel format, and used in an INO-supported SciMiner, an in-house literature mining program. We studied the gene interaction sentences from the commonly used benchmark Learning Logic in Language (LLL) dataset and one internally generated vaccine-related dataset to identify and analyze interaction types containing multiple keywords. Patterns obtained from the dependency parse trees of the sentences were used to identify the interaction keywords that are related to each other and collectively represent an interaction type. Results: The INO ontology currently has 575 terms including 202 terms under the interaction branch. The relations between the INO interaction types and associated keywords are represented using the INO annotation relations: 'has literature mining keywords' and 'has keyword dependency pattern'. The keyword dependency patterns were generated via running the Stanford Parser to obtain dependency relation types. Out of the 107 interactions in the LLL dataset represented with two-keyword interaction types, 86 were identified by using the direct dependency relations. The LLL dataset contained 34 gene regulation interaction types, each of which associated with multiple keywords. A hierarchical display of these 34 interaction types and their ancestor terms in INO resulted in the identification of specific gene-gene interaction patterns from the LLL dataset. The phenomenon of having multi-keyword interaction types was also frequently observed in the vaccine dataset. Conclusions: By modeling and representing multiple textual keywords for interaction types, the extended INO enabled the identification of complex biological gene-gene interactions represented with multiple keywords. [ABSTRACT FROM AUTHOR]

Background: The large amount of data used in genomic analysis has allowed geneticists to achieve some understanding of the genetic architecture of complex traits. Although the information gathered by molecular markers has permitted gains in predictive accuracy and gene discovery, epistatic effects have been ignored based on exhaustive searches requesting estimates of its effects on the whole genome. In this work, we propose the reversible-jump technique to estimate epistasis in the genome without drastically altering the model dimension. To this end, we used a real maize dataset based on 256 F2:3 progenies plus a simulation data set based on 300 F2 individuals. In the simulation scenario, six QTL presenting main effects (additive and dominance) were combined with seven other epistatic effects totaling 13 QTL controlling the trait. Results: Our model explored 18,624 candidate epistases, but even in this vast space, only one spurious interaction was found. The three epistases selected by our model, named here as 18x26, 56x68 and 59x93, were very close to simulated ones (19x25, 54x72, 59x91 and 59x94). In the real dataset, we estimate 33,024 epistatic effects, and several minor epistatic combinations were found to explain a significant proportion of the genetic variance. The broad participation of epistasis in the real dataset may indicate the presence of pervasive epistasis acting on maize grain yield. Conclusions: The power of selecting true epistasis in thousands of possible combinations suggests the attractiveness of our model to handle genomic data. [ABSTRACT FROM AUTHOR]

The study of fitness landscapes, which aims at mapping genotypes to fitness, is receiving ever-increasing attention. Novel experimental approaches combined with next-generation sequencing (NGS) methods enable accurate and extensive studies of the fitness effects of mutations, allowing us to test theoretical predictions and improve our understanding of the shape of the true underlying fitness landscape and its implications for the predictability and repeatability of evolution. Here, we present a uniquely large multiallelic fitness landscape comprising 640 engineered mutants that represent all possible combinations of 13 amino acid-changing mutations at 6 sites in the heat-shock protein Hsp90 in Saccharomyces cerevisiae under elevated salinity. Despite a prevalent pattern of negative epistasis in the landscape, we find that the global fitness peak is reached via four positively epistatic mutations. Combining traditional and extending recently proposed theoretical and statistical approaches, we quantify features of the global multiallelic fitness landscape. Using subsets of the data, we demonstrate that extrapolation beyond a known part of the landscape is difficult owing to both local ruggedness and amino acid-specific epistatic hotspots and that inference is additionally confounded by the nonrandom choice of mutations for experimental fitness landscapes. [ABSTRACT FROM AUTHOR]

Understanding and predicting evolution is a central challenge in both population and quantitative genetics. The amount of genetic variance for quantitative traits available in a population conditions the particular way in which this population will (or will not) evolve under natural or artificial selection. Here, we explore the potential of gene-gene interactions (epistasis) to induce evolutionary plateaus at which evolutionary change virtually collapses for a number of generations, followed by the release of previously cryptic genetic variation. First, we demonstrate theoretically that a wide range of epistatic interactions has the potential to generate temporary decelerations in the course of response to selection. Second, we perform simulations to show that such microevolutionary plateaus may occur in selection responses under empirically based assumptions. Finally, we show that such events can be traced in artificial selection experiments, thus providing further empirical evidence for this phenomenon. [ABSTRACT FROM AUTHOR]