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

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

A plausible explanation for statistical epistasis revealed in genome wide association analyses is the presence of high order linkage disequilibrium (LD) between the genotyped markers tested for interactions and unobserved functional polymorphisms. Based on findings in experimental data, it has been suggested that high order LD might be a common explanation for statistical epistasis inferred between local polymorphisms in the same genomic region. Here, we empirically evaluate how prevalent high order LD is between local, as well as distal, polymorphisms in the genome. This could provide insights into whether we should account for this when interpreting results from genome wide scans for statistical epistasis. An extensive and strong genome wide high order LD was revealed between pairs of markers on the high density 250k SNP-chip and individual markers revealed by whole genome sequencing in the Arabidopsis thaliana 1001-genomes collection. The high order LD was found to be more prevalent in smaller populations, but present also in samples including several hundred individuals. An empirical example illustrates that high order LD might be an even greater challenge in cases when the genetic architecture is more complex than the common assumption of bi-allelic loci. The example shows how significant statistical epistasis is detected for a pair of markers in high order LD with a complex multi allelic locus. Overall, our study illustrates the importance of considering also other explanations than functional genetic interactions when genome wide statistical epistasis is detected, in particular when the results are obtained in small populations of inbred individuals. [ABSTRACT FROM AUTHOR]

The genetic basis of earlobe attachment has been a matter of debate since the early 20 th century, such that geneticists argue both for and against polygenic inheritance. Recent genetic studies have identified a few loci associated with the trait, but large-scale analyses are still lacking. Here, we performed a genome-wide association study of lobe attachment in a multiethnic sample of 74,660 individuals from four cohorts (three with the trait scored by an expert rater and one with the trait self-reported). Meta-analysis of the three expert-rater-scored cohorts revealed six associated loci harboring numerous candidate genes, including EDAR , SP5 , MRPS22 , ADGRG6 ( GPR126 ), KIAA1217 , and PAX9 . The large self-reported 23andMe cohort recapitulated each of these six loci. Moreover, meta-analysis across all four cohorts revealed a total of 49 significant (p < 5 × 10 −8 ) loci. Annotation and enrichment analyses of these 49 loci showed strong evidence of genes involved in ear development and syndromes with auricular phenotypes. RNA sequencing data from both human fetal ear and mouse second branchial arch tissue confirmed that genes located among associated loci showed evidence of expression. These results provide strong evidence for the polygenic nature of earlobe attachment and offer insights into the biological basis of normal and abnormal ear development. [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]

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]

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.

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.

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]

In evolution, the effects of a single deleterious mutation can sometimes be compensated for by a second mutation which recovers the original phenotype. Such epistatic interactions have implications for the structure of genome space—namely, that networks of genomes encoding the same phenotype may not be connected by single mutational moves. We use the folding of RNA sequences into secondary structures as a model genotype–phenotype map and explore the neutral spaces corresponding to networks of genotypes with the same phenotype. In most of these networks, we find that it is not possible to connect all genotypes to one another by single point mutations. Instead, a network for a phenotypic structure with n bonds typically fragments into at least 2n neutral components, often of similar size. While components of the same network generate the same phenotype, they show important variations in their properties, most strikingly in their evolvability and mutational robustness. This heterogeneity implies contingency in the evolutionary process. [ABSTRACT FROM AUTHOR]

Evolutionary theory predicts that a population in a new environment will accumulate adaptive substitutions, but precisely how they accumulate is poorly understood. The dynamics of adaptation depend on the underlying fitness landscape. Virtually nothing is known about fitness landscapes in nature, and few methods allow us to infer the landscape from empirical data. With a view toward this inference problem, we have developed a theory that, in the weak-mutation limit, predicts how a population's mean fitness and the number of accumulated substitutions are expected to increase over time, depending on the underlying fitness landscape. We find that fitness and substitution trajectories depend not on the full distribution of fitness effects of available mutations but rather on the expected fixation probability and the expected fitness increment of mutations. We introduce a scheme that classifies landscapes in terms of the qualitative evolutionary dynamics they produce. We show that linear substitution trajectories, long considered the hallmark of neutral evolution, can arise even when mutations are strongly selected. Our results provide a basis for understanding the dynamics of adaptation and for inferring properties of an organism's fitness landscape from temporal data. Applying these methods to data from a long-term experiment, we infer the sign and strength of epistasis among beneficial mutations in the Escherichia coli genome. [ABSTRACT FROM AUTHOR]

The abundance of sex and recombination is still one of the most puzzling questions in the theory of evolution: Most models find that recombination can evolve, but only under a limited range of parameters. Here we review the major models and supporting evidence, concentrating on recent approaches where more realistic assumptions help explain the evolution of sex and recombination under a wider parameter range: finite populations, selection over long genomes, variation in recombination across the genome, and plasticity of sex and recombination. We discuss the similarities and differences between the evolution of sex and that of recombination. [ABSTRACT FROM AUTHOR]

The role of epistasis in evolution has long been contentious. Resolving the issue requires empirical measurements that are statistically adequate and evolutionarily relevant. We review experimental methods for measuring epistasis, some that are commonly used but weak and others that are less frequently used hut stronger. We review statistical genetic methods based on analyses of variances and means as well as molecular genetic methods for detecting gene interactions. We also highlight relevant empirical studies that illustrate the implementation of particular methods. In spite of the inherent weaknesses of most methods, epistasis is surprisingly common. We conclude with a discussion of how technologies for investigating genome-wide epistasis are bridging the gap between physiological and statistical epistasis for model organisms. [ABSTRACT FROM AUTHOR]

Fitness interactions between loci in the genome, or epistasis, can result in mutations that are individually deleterious but jointly beneficial. Such epistasis gives rise to multiple peaks on the genotypic fitness landscape. The problem of evolutionary escape from such local peaks has been a central problem of evolutionary genetics for at least 75 years. Much attention has focused on models of small populations, in which the sequential fixation of valley genotypes carrying individually deleterious mutations operates most quickly owing to genetic drift. However, valley genotypes can also be subject to mutation while transiently segregating, giving rise to copies of the high fitness escape genotype carrying the jointly beneficial mutations. In the absence of genetic recombination, these mutations may then fix simultaneously. The time for this process declines sharply with increasing population size, and it eventually comes to dominate evolutionary behavior. Here we develop an analytic expression for Ncrit, the critical population size that defines the boundary between these regimes, which shows that both are likely to operate in nature. Frequent recombination may disrupt high-fitness escape genotypes produced in populations larger than Ncrit before they reach fixation, defining a third regime whose rate again slows with increasing population size. We develop a novel expression for this critical recombination rate, which shows that in large populations the simultaneous fixation of mutations that are beneficial only jointly is unlikely to be disrupted by genetic recombination if their map distance is on the order of the size of single genes. Thus, counterintuitively, mass selection alone offers a biologically realistic resolution to the problem of evolutionary escape from local fitness peaks in natural populations. [ABSTRACT FROM AUTHOR]

Genetic studies of behavior have traditionally come in two flavors: quantitative genetic studies of natural variants and single-gene studies of induced mutants. Each employed different techniques and methods of analysis toward the common, ultimate goal of understanding how genes influence behavior. With the advent of new genomic technologies, and also the realization that mechanisms underlying behavior involve a considerable degree of complex gene interaction, the traditionally separate strands of behavior genetics are merging into a single, synthetic strategy. [ABSTRACT FROM AUTHOR]

The pathogenesis of all forms of psoriasis remains obscure. Segregation analysis and twin studies together with ethnic differences in disease frequency all point to an underlying genetic susceptibility to psoriasis, which is both complex and likely to reflect the action of a number of genes. We performed a genome wide analysis using a total of 271 polymorphic autosomal markers on 284 sib relative pairs identified within 158 independent families. We detected evidence for linkage at 6p21 (PSORS1) with a non-parametric linkage score (NPL)=4.7, p=2 x 10-6 and at chromosome 1p (NPL=3.6, p=1.9 x 10-4) in all families studied. Significant excess (p=0.004) paternal allele sharing was detected for markers spanning the PSORS1 locus. A further three regions reached NPL scores of 2 or greater, including a region at chromosome 7 (NPL 2.1), for which linkage for a number of autoimmune disorders has been reported. Partitioning of the data set according to allele sharing at 6p21 (PSORS1) favoured linkage to chromosomes 2p (NPL 2.09) and 14q (NPL 2.0), both regions implicated in previous independent genome scans, and suggests evidence for epistasis between PSORS1 and genes at other genomic locations. This study has provided linkage evidence in favour of a novel susceptibility locus for psoriasis and provides evidence of the complex mechanisms underlying the genetic predisposition to this common skin disease. [ABSTRACT FROM AUTHOR]