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Maternal effects can play an important role in a diversity of ecological and evolutionary processes such as population dynamics, phenotypic plasticity, niche construction, life-history evolution and the evolutionary response to selection. However, although maternal effects were defined by quantitative geneticists well over half a century ago, there remains some confusion over exactly what phenomena should be characterized as maternal effects and, more importantly, why it matters and how they are defined. We suggest a definition of maternal effects as the causal influence of the maternal genotype or phenotype on the offspring phenotype. This definition differs from some definitions in that it treats maternal effects as a phenomenon, not as a statistical construct. The causal link to maternal genotype or phenotype is the critical component of this definition providing the link between maternal effects and evolutionary and ecological processes. We show why phenomena such as maternal cytoplasmic inheritance and genomic imprinting are distinct genetically from and have different evolutionary consequences than true maternal effects. We also argue that one should consider cases where the maternal effect is conditional on offspring genotype as a class of maternal effects.

Key Points Parent-of-origin effects probably contribute to the genetic architecture of complex traits, but they are rarely included in studies of genetic architecture. It is crucial to distinguish between reciprocal heterozygotes when identifying parent-of-origin effects, but several phenomena besides genomic imprinting can potentially produce phenotypic differences between reciprocal heterozygotes. In human studies, large-scale samples that incorporate pedigree information will be important for developing models and tools that can accommodate parent-of-origin effects into analyses. Animal studies will be essential for developing a framework of DNA sequence–imprint–function relationships, particularly because parent-of-origin effects can be context dependent. Research that integrates complex trait mapping results with next-generation sequencing data to identify patterns that have predictive power will be essential to advance the field. Increasing evidence suggests that parent-of-origin effects, particularly genomic imprinting, contribute to complex traits. This Review discusses how such effects can be identified in order to expand our understanding of their roles in phenotypes such as human diseases and traits important for agriculture. Parent-of-origin effects occur when the phenotypic effect of an allele depends on whether it is inherited from the mother or the father. Several phenomena can cause parent-of-origin effects, but the best characterized is parent-of-origin-dependent gene expression associated with genomic imprinting. The development of new mapping approaches applied to the growing abundance of genomic data has demonstrated that imprinted genes can be important contributors to complex trait variation. Therefore, to understand the genetic architecture and evolution of complex traits, including complex diseases and traits of agricultural importance, it is crucial to account for these parent-of-origin effects. Here, we discuss patterns of phenotypic variation associated with imprinting, evidence supporting its role in complex trait variation and approaches for identifying its molecular signatures.

Imprinted genes are expressed either from the maternally or paternally inherited copy only, and they play a key role in regulating complex biological processes, including offspring development and mother-offspring interactions. There are several competing theories attempting to explain the evolutionary origin of this monoallelic pattern of gene expression, but a prevailing view has emerged that holds that genomic imprinting is a consequence of conflict between maternal and paternal gene copies over maternal investment. However, many imprinting patterns and the apparent overabundance of maternally expressed genes remain unexplained and may be incompatible with current theory. Here we demonstrate that sole expression of maternal gene copies is favored by natural selection because it increases the adaptive integration of offspring and maternal genomes, leading to higher offspring fitness. This novel coadaptation theory for the evolution of genomic imprinting is consistent with results of recent studies on epigenetic effects, and it provides a testable hypothesis for the origin of previously unexplained major imprinting patterns across different taxa. In conjunction with existing hypotheses, our results suggest that imprinting may have evolved due to different selective pressures at different loci.

Genomic imprinting is an epigenetic phenomenon in which the expression of a gene copy inherited from the mother differs from that of the copy inherited from the father. Many imprinted genes appear to be highly interconnected through interactions mediated by proteins, RNA, and DNA. These kinds of interactions often favor the evolution of genetic coadaptation, where beneficially interacting alleles evolve to become coinherited. Here I demonstrate theoretically that the presence of gene interactions that favor coadaptation can also favor the evolution of genomic imprinting. Selection favors genomic imprinting because it coordinates the coexpression of positively interacting alleles at different loci. Evolution is expected to proceed through a scenario where selection builds associations between beneficial combinations of alleles and, if one locus evolves to become imprinted, it leads to selection for its interacting partners to match its pattern of imprinting. This process should favor the evolution of physical linkage between interacting genes and therefore may help explain why imprinted genes tend to be found in clusters. The model suggests that, whereas some genes are expected to evolve their imprinting status because selection directly favors a specific pattern of parent-of-origin-dependent expression, other genes may evolve imprinting as a coevolutionary response to match the expression pattern of their interacting partners. As a result, some genes will show phenotypic effects consistent with the predictions of models for the evolution of genomic imprinting (e.g., conflict models), but other genes may not, having simply evolved imprinting to follow the lead of their interacting partners.

Contributing to cooperation is typically costly, while its rewards are often available to all members of a social group. So why should individuals be willing to pay these costs, especially if they could cheat by exploiting the investments of others? Kin selection theory broadly predicts that individuals should investmore into cooperation if their relatedness to group members is high (assuming they can discriminate kin from nonkin). To better understand how relatedness affects cooperation, we derived the ‟Collective Investment” game, which provides quantitative predictions for patterns of strategic investment depending on the level of relatedness. We then tested these predictions by experimentally manipulating relatedness (genotype frequencies) in mixed cooperative aggregations of the social amoeba Dictyostelium discoideum, which builds a stalk to facilitate spore dispersal. Measurements of stalk investment by natural strains correspond to the predicted patterns of relatedness-dependent strategic investment, wherein investment by a strain increases with its relatedness to the group. Furthermore, if overall group relatedness is relatively low (i.e., no strain is at high frequency in a group) strains face a scenario akin to the “Prisoner’s Dilemma” and suffer from insufficient collective investment. We find that strains employ relatedness-dependent segregation to avoid these pernicious conditions. These findings demonstrate that simple organisms like D. discoideum are not restricted to being ‟cheaters” or ‟cooperators” but instead measure their relatedness to their group and strategically modulate their investment into cooperation accordingly. Consequently, all individuals will sometimes appear to cooperate and sometimes cheat due to the dynamics of strategic investing.

Interactions among conspecifics influence social evolution through two distinct but intimately related paths. First, they provide the opportunity for indirect genetic effects (IGEs), where genes expressed in one individual influence the expression of traits in others. Second, interactions can generate social selection when traits expressed in one individual influence the fitness of others. Here, we present a quantitative genetic model of multivariate trait evolution that integrates the effects of both IGEs and social selection, which have previously been modeled independently. We show that social selection affects evolutionary change whenever the breeding value of one individual covaries with the phenotype of its social partners. This covariance can be created by both relatedness and IGEs, which are shown to have parallel roles in determining evolutionary response. We show that social selection is central to the estimation of inclusive fitness and derive a version of Hamilton's rule showing the symmetrical effects of relatedness and IGEs on the evolution of altruism. We illustrate the utility of our approach using altruism, greenbeards, aggression, and weapons as examples. Our model provides a general predictive equation for the evolution of social phenotypes that encompasses specific cases such as kin selection and reciprocity. The parameters can be measured empirically, and we emphasize the importance of considering both IGEs and social selection, in addition to relatedness, when testing hypotheses about social evolution.

Organisms often cooperate through the production of freely available public goods. This can greatly benefit the group but is vulnerable to the “tragedy of the commons” if individuals lack the motivation to make the necessary investment into public goods production. Relatedness to groupmates can motivate individual investment because group success ultimately benefits their genes’ own self-interests. However, systems often lack mechanisms that can reliably ensure that relatedness is high enough to promote cooperation. Consequently, groups face a persistent threat from the tragedy unless they have a mechanism to enforce investment when relatedness fails to provide adequate motivation. To understand the real threat posed by the tragedy and whether groups can avert its impact, we determine how the social amoeba Dictyostelium discoideum responds as relatedness decreases to levels that should induce the tragedy. We find that, while investment in public goods declines as overall within-group relatedness declines, groups avert the expected catastrophic collapse of the commons by continuing to invest, even when relatedness should be too low to incentivize any contribution. We show that this is due to a developmental buffering system that generates enforcement because insufficient cooperation perturbs the balance of a negative feedback system controlling multicellular development. This developmental constraint enforces investment under the conditions expected to be most tragic, allowing groups to avert a collapse in cooperation. These results help explain how mechanisms that suppress selfishness and enforce cooperation can arise inadvertently as a by-product of constraints imposed by selection on different traits.

Cheaters disrupt cooperation by reaping the benefits without paying their fair share of associated costs. Cheater impact can be diminished if cooperators display a tag (‘greenbeard’) and recognise and preferentially direct cooperation towards other tag carriers. Despite its popular appeal, the feasibility of such greenbeards has been questioned because the complex patterns of partner-specific cooperative behaviours seen in nature require greenbeards to come in different colours. Here we show that a locus (‘Tgr’) of a social amoeba represents a polychromatic greenbeard. Patterns of natural Tgr locus sequence polymorphisms predict partner-specific patterns of cooperation by underlying variation in partner-specific protein–protein binding strength and recognition specificity. Finally, Tgr locus polymorphisms increase fitness because they help avoid potential costs of cooperating with incompatible partners. These results suggest that a polychromatic greenbeard can provide a key mechanism for the evolutionary maintenance of cooperation. Cooperation can be stabilized against exploitation if cooperators can reliably recognize each other. Here, Gruenheit and colleagues show that different alleles of the Tgr locus of the social amoeba Dictyostelium discoideum underlie the ability of different strains to recognize and cooperate with socially compatible individuals.

Background Genomes can be sequenced with relative ease, but ascribing gene function remains a major challenge. Genetically tractable model systems are crucial to meet this challenge. One powerful model is the social amoeba Dictyostelium discoideum , a eukaryotic microbe widely used to study diverse questions in the cell, developmental and evolutionary biology. Results We describe REMI-seq, an adaptation of Tn-seq, which allows high throughput, en masse , and quantitative identification of the genomic site of insertion of a drug resistance marker after restriction enzyme-mediated integration. We use REMI-seq to develop tools which greatly enhance the efficiency with which the sequence, transcriptome or proteome variation can be linked to phenotype in D. discoideum . These comprise (1) a near genome-wide resource of individual mutants and (2) a defined pool of ‘barcoded’ mutants to allow large-scale parallel phenotypic analyses. These resources are freely available and easily accessible through the REMI-seq website that also provides comprehensive guidance and pipelines for data analysis. We demonstrate that integrating these resources allows novel regulators of cell migration, phagocytosis and macropinocytosis to be rapidly identified. Conclusions We present methods and resources, generated using REMI-seq, for high throughput gene function analysis in a key model system.

Natural selection should favour generalist predators that outperform specialists across all prey types. Two genetic solutions could explain why intraspecific variation in predatory performance is, nonetheless, widespread: mutations beneficial on one prey type are costly on another (antagonistic pleiotropy), or mutational effects are prey-specific, which weakens selection, allowing variation to persist (relaxed selection). To understand the relative importance of these alternatives, we characterised natural variation in predatory performance in the microbial predator Dictyostelium discoideum . We found widespread nontransitive differences among strains in predatory success across different bacterial prey, which can facilitate stain coexistence in multi-prey environments. To understand the genetic basis, we developed methods for high throughput experimental evolution on different prey (REMI-seq). Most mutations (~77%) had prey-specific effects, with very few (~4%) showing antagonistic pleiotropy. This highlights the potential for prey-specific effects to dilute selection, which would inhibit the purging of variation and prevent the emergence of an optimal generalist predator. What prevents a generalist predator from evolving and outperforming specialist predators? By combing analyses of natural variation with experimental evolution, Stewart et al. suggest that predator variation persists because most mutations have prey-specific effects, which results in relaxed selection