Developmental constraints enforce altruism and avert the tragedy of the commons in a social microbe.

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.

Bivariate GWAS reveals pleiotropic regions among feed efficiency and beef quality-related traits in Nelore cattle.

Feed-efficient cattle selection is among the most leading solutions to reduce cost for beef cattle production. However, technical difficulties in measuring feed efficiency traits had limited the application in livestock. Here, we performed a Bivariate Genome-Wide Association Study (Bi-GWAS) and presented candidate biological mechanisms underlying the association between feed efficiency and meat quality traits in a half-sibling design with 353 Nelore steers derived from 34 unrelated sires. A total of 13 Quantitative Trait Loci (QTL) were found explaining part of the phenotypic variations. An important transcription factor of adipogenesis in cattle, the TAL1 (rs133408775) gene located on BTA3 was associated with intramuscular fat and average daily gain (IMF-ADG), and a region located on BTA20, close to CD180 and MAST4 genes, both related to fat accumulation. We observed a low positive genetic correlation between IMF-ADG (r = 0.30 ± 0.0686), indicating that it may respond to selection in the same direction. Our findings contributed to clarifying the pleiotropic modulation of the complex traits, indicating new QTLs for bovine genetic improvement.

Runaway evolution from male-male competition.

Wondrously elaborate weapons and displays that appear to be counter to ecological optima are widespread features of male contests for mates across the animal kingdom. To understand how such diverse traits evolve, here we develop a quantitative genetic model of sexual selection for a male signaling trait that mediates aggression in male-male contests and show that an honest indicator of aggression can generate selection on itself by altering the social environment. This can cause selection to accelerate as the trait is elaborated, leading to runaway evolution. Thus, an evolving source of selection provided by the social environment is the fundamental unifying feature of runaway sexual selection driven by either male-male competition or female mate choice. However, a key difference is that runaway driven by male-male competition requires signal honesty. Our model identifies simple conditions that provide clear, testable predictions for empirical studies using standard quantitative genetic methods.

Inferring Adaptive Codon Preference to Understand Sources of Selection Shaping Codon Usage Bias.

Alternative synonymous codons are often used at unequal frequencies. Classically, studies of such codon usage bias (CUB) attempted to separate the impact of neutral from selective forces by assuming that deviations from a predicted neutral equilibrium capture selection. However, GC-biased gene conversion (gBGC) can also cause deviation from a neutral null. Alternatively, selection has been inferred from CUB in highly expressed genes, but the accuracy of this approach has not been extensively tested, and gBGC can interfere with such extrapolations (e.g., if expression and gene conversion rates covary). It is therefore critical to examine deviations from a mutational null in a species with no gBGC. To achieve this goal, we implement such an analysis in the highly AT rich genome of Dictyostelium discoideum, where we find no evidence of gBGC. We infer neutral CUB under mutational equilibrium to quantify "adaptive codon preference," a nontautologous genome wide quantitative measure of the relative selection strength driving CUB. We observe signatures of purifying selection consistent with selection favoring adaptive codon preference. Preferred codons are not GC rich, underscoring the independence from gBGC. Expression-associated "preference" largely matches adaptive codon preference but does not wholly capture the influence of selection shaping patterns across all genes, suggesting selective constraints associated specifically with high expression. We observe patterns consistent with effects on mRNA translation and stability shaping adaptive codon preference. Thus, our approach to quantifying adaptive codon preference provides a framework for inferring the sources of selection that shape CUB across different contexts within the genome.

Mutant resources for functional genomics in Dictyostelium discoideum using REMI-seq technology.

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.

Strategic investment explains patterns of cooperation and cheating in a microbe.

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 invest more 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.

Genomic imprinting and parent-of-origin effects on complex traits.

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.

Genomic Perspective on Multivariate Variation, Pleiotropy, and Evolution.

Multivariate quantitative genetics provides a powerful framework for understanding patterns and processes of phenotypic evolution. Quantitative genetics parameters, like trait heritability or the G-matrix for sets of traits, can be used to predict evolutionary response or to understand the evolutionary history of a population. These population-level approaches have proven to be extremely successful, but the underlying genetics of multivariate variation and evolutionary change typically remain a black box. Establishing a deeper empirical understanding of how individual genetic effects lead to genetic (co)variation is then crucial to our understanding of the evolutionary process. To delve into this black box, we exploit an experimental population of mice composed from lineages derived by artificial selection. We develop an approach to estimate the multivariate effect of loci and characterize these vectors of effects in terms of their magnitude and alignment with the direction of evolutionary divergence. Using these estimates, we reconstruct the traits in the ancestral populations and quantify how much of the divergence is due to genetic effects. Finally, we also use these vectors to decompose patterns of genetic covariation and examine the relationship between these components and the corresponding distribution of pleiotropic effects. We find that additive effects are much larger than dominance effects and are more closely aligned with the direction of selection and divergence, with larger effects being more aligned than smaller effects. Pleiotropic effects are highly variable but are, on average, modular. These results are consistent with pleiotropy being partly shaped by selection while reflecting underlying developmental constraints.

Coadaptation between mother and offspring: why not?

A Formal Comment has challenged the interpretation of a study into an imprinted gene, maintaining that conflict, rather than mother-offspring co-adaptation, provides a better mechanistic explanation. Here authors of the original Research Article reply.

Developmental programming mediated by complementary roles of imprinted Grb10 in mother and pup.

Developmental programming links growth in early life with health status in adulthood. Although environmental factors such as maternal diet can influence the growth and adult health status of offspring, the genetic influences on this process are poorly understood. Using the mouse as a model, we identify the imprinted gene Grb10 as a mediator of nutrient supply and demand in the postnatal period. The combined actions of Grb10 expressed in the mother, controlling supply, and Grb10 expressed in the offspring, controlling demand, jointly regulate offspring growth. Furthermore, Grb10 determines the proportions of lean and fat tissue during development, thereby influencing energy homeostasis in the adult. Most strikingly, we show that the development of normal lean/fat proportions depends on the combined effects of Grb10 expressed in the mother, which has the greater effect on offspring adiposity, and Grb10 expressed in the offspring, which influences lean mass. These distinct functions of Grb10 in mother and pup act complementarily, which is consistent with a coadaptation model of imprinting evolution, a model predicted but for which there is limited experimental evidence. In addition, our findings identify Grb10 as a key genetic component of developmental programming, and highlight the need for a better understanding of mother-offspring interactions at the genetic level in predicting adult disease risk.

Evolution of genomic imprinting as a coordinator of coadapted gene expression.

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.

A simple mechanism for complex social behavior.

The evolution of cooperation is a paradox because natural selection should favor exploitative individuals that avoid paying their fair share of any costs. Such conflict between the self-interests of cooperating individuals often results in the evolution of complex, opponent-specific, social strategies and counterstrategies. However, the genetic and biological mechanisms underlying complex social strategies, and therefore the evolution of cooperative behavior, are largely unknown. To address this dearth of empirical data, we combine mathematical modeling, molecular genetic, and developmental approaches to test whether variation in the production of and response to social signals is sufficient to generate the complex partner-specific social success seen in the social amoeba Dictyostelium discoideum. Firstly, we find that the simple model of production of and response to social signals can generate the sort of apparent complex changes in social behavior seen in this system, without the need for partner recognition. Secondly, measurements of signal production and response in a mutant with a change in a single gene that leads to a shift in social behavior provide support for this model. Finally, these simple measurements of social signaling can also explain complex patterns of variation in social behavior generated by the natural genetic diversity found in isolates collected from the wild. Our studies therefore demonstrate a novel and elegantly simple underlying mechanistic basis for natural variation in complex social strategies in D. discoideum. More generally, they suggest that simple rules governing interactions between individuals can be sufficient to generate a diverse array of outcomes that appear complex and unpredictable when those rules are unknown.

Genetic effects at pleiotropic loci are context-dependent with consequences for the maintenance of genetic variation in populations.

Context-dependent genetic effects, including genotype-by-environment and genotype-by-sex interactions, are a potential mechanism by which genetic variation of complex traits is maintained in populations. Pleiotropic genetic effects are also thought to play an important role in evolution, reflecting functional and developmental relationships among traits. We examine context-dependent genetic effects at pleiotropic loci associated with normal variation in multiple metabolic syndrome (MetS) components (obesity, dyslipidemia, and diabetes-related traits). MetS prevalence is increasing in Western societies and, while environmental in origin, presents substantial variation in individual response. We identify 23 pleiotropic MetS quantitative trait loci (QTL) in an F(16) advanced intercross between the LG/J and SM/J inbred mouse strains (Wustl:LG,SM-G16; n = 1002). Half of each family was fed a high-fat diet and half fed a low-fat diet; and additive, dominance, and parent-of-origin imprinting genotypic effects were examined in animals partitioned into sex, diet, and sex-by-diet cohorts. We examine the context-dependency of the underlying additive, dominance, and imprinting genetic effects of the traits associated with these pleiotropic QTL. Further, we examine sequence polymorphisms (SNPs) between LG/J and SM/J as well as differential expression of positional candidate genes in these regions. We show that genetic associations are different in different sex, diet, and sex-by-diet settings. We also show that over- or underdominance and ecological cross-over interactions for single phenotypes may not be common, however multidimensional synthetic phenotypes at loci with pleiotropic effects can produce situations that favor the maintenance of genetic variation in populations. Our findings have important implications for evolution and the notion of personalized medicine.

The genetic architecture underlying prey-dependent performance in a microbial predator.

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.

Genetic factors and diet affect long-bone length in the F34 LG,SM advanced intercross.

Previous studies on the LG,SM advanced intercross line have identified approximately 40 quantitative trait loci (QTL) for long -bone (humerus, ulna, femur, and tibia) lengths. In this study, long-bone-length QTL were fine-mapped in the F(34) generation (n = 1424) of the LG,SM advanced intercross. Environmental effects were assessed by dividing the population by sex between high-fat and low-fat diets, producing eight sex/diet cohorts. We identified 145 individual bone-length QTL comprising 45 pleiotropic QTL; 69 replicated QTL from previous studies, 35 were new traits significant at previously identified loci, and 41 were novel QTL. Many QTL affected only a subset of the population based on sex and/or diet. Eight of ten known skeletal growth genes were upregulated in 3-week-old LG/J male proximal tibial growth plates relative to SM/J. The sequences of parental strains LG/J and SM/J indicated the presence of over half a million polymorphisms in the confidence intervals of these 45 QTL. We examined 526 polymorphisms and found that 97 represented radical changes to amino acid composition while 40 were predicted to be deleterious to protein function. Additional experimentation is required to understand how changes in gene regulation or protein function can alter the genetic architecture and interact with the environment to produce phenotypic variation.

The importance of context to the genetic architecture of diabetes-related traits is revealed in a genome-wide scan of a LG/J × SM/J murine model.

Variations in diabetic phenotypes are caused by complex interactions of genetic effects, environmental factors, and the interplay between the two. We tease apart these complex interactions by examining genome-wide genetic and epigenetic effects on diabetes-related traits among different sex, diet, and sex-by-diet cohorts in a Mus musculus model. We conducted a genome-wide scan for quantitative trait loci that affect serum glucose and insulin levels and response to glucose stress in an F(16) Advanced Intercross Line of the LG/J and SM/J intercross (Wustl:LG,SM-G16). Half of each sibship was fed a high-fat diet and half was fed a relatively low-fat diet. Context-dependent genetic (additive and dominance) and epigenetic (parent-of-origin imprinting) effects were characterized by partitioning animals into sex, diet, and sex-by-diet cohorts. We found that different cohorts often have unique genetic effects at the same loci, and that genetic signals can be masked or erroneously assigned to specific cohorts if they are not considered individually. Our data demonstrate that the effects of genes on complex trait variation are highly context-dependent and that the same genomic sequence can affect traits differently depending on an individual's sex and/or dietary environment. Our results have important implications for studies of complex traits in humans.

Genome-wide analysis reveals a complex pattern of genomic imprinting in mice.

Parent-of-origin-dependent gene expression resulting from genomic imprinting plays an important role in modulating complex traits ranging from developmental processes to cognitive abilities and associated disorders. However, while gene-targeting techniques have allowed for the identification of imprinted loci, very little is known about the contribution of imprinting to quantitative variation in complex traits. Most studies, furthermore, assume a simple pattern of imprinting, resulting in either paternal or maternal gene expression; yet, more complex patterns of effects also exist. As a result, the distribution and number of different imprinting patterns across the genome remain largely unexplored. We address these unresolved issues using a genome-wide scan for imprinted quantitative trait loci (iQTL) affecting body weight and growth in mice using a novel three-generation design. We identified ten iQTL that display much more complex and diverse effect patterns than previously assumed, including four loci with effects similar to the callipyge mutation found in sheep. Three loci display a new phenotypic pattern that we refer to as bipolar dominance, where the two heterozygotes are different from each other while the two homozygotes are identical to each other. Our study furthermore detected a paternally expressed iQTL on Chromosome 7 in a region containing a known imprinting cluster with many paternally expressed genes. Surprisingly, the effects of the iQTL were mostly restricted to traits expressed after weaning. Our results imply that the quantitative effects of an imprinted allele at a locus depend both on its parent of origin and the allele it is paired with. Our findings also show that the imprinting pattern of a locus can be variable over ontogenetic time and, in contrast to current views, may often be stronger at later stages in life.

Genomic imprinting effects on adult body composition in mice.

Genomic imprinting results in the differential expression of genes, depending on which allele is inherited from the mother and which from the father. The effects of such differential gene expression are reflected in phenotypic differences between the reciprocal heterozygotes (Aa vs. aA). Although many imprinted genes have been identified and play a key role in development, little is known about the contribution of imprinting to quantitative variation in trait expression. Here, we examine this problem by mapping imprinting effects on adult body composition traits in the F(3) generation of an intercross between the Large (LG/J) and Small (SM/J) inbred mouse strains. We identified eight pleiotropic imprinted quantitative trait loci (iQTL) located throughout the genome. Most iQTL are in novel locations that have not previously been associated with imprinting effects, but those on chromosomes 7, 12, and centromeric 18 lie in regions previously identified as containing imprinted genes. Our results show that the effects of genomic imprinting are relatively small, with reciprocal heterozygotes differing by approximately 0.25 standard deviation units and the effects at each locus accounting for 1% to 4% of the phenotypic variance. We detected a variety of imprinting patterns, with paternal expression being the most common. These results indicate that genomic imprinting has small, but detectable, effects on the normal variation of complex traits in adults and is likely to be more common than usually thought.

Evolutionary robustness of killer meiotic drives.

A meiotic driver is a selfish genetic element that interferes with the process of meiosis to promote its own transmission. The most common mechanism of interference is gamete killing, where the meiotic driver kills gametes that do not contain it. A killer meiotic driver is predicted to spread rapidly through a population at the expense of other genes in the rest of the genome. The rapid spread of a killer meiotic driver is expected to be chased by the rapid spread of a suppressor that returns fair meiosis. Paradoxically, while this might imply that meiotic drivers should be evolutionarily transient, numerous ancient killer meiotic drivers have been discovered that have persisted for millions of years. To understand the rationale that could potentially explain such evolutionary robustness, we explore different possible mechanisms of killer meiotic drive and the different possible associated mechanisms of suppression. We use a framework that considers how the different stages of meiosis result in different structured interactions among cells with different genotypes in various combinations. Across possible interactions, we show that there are three genotypically distinct drive mechanisms that create alternative selective conditions for the spread of different types of suppressors. We show that killer meiotic drivers are more evolutionarily robust if they operate among sister cells (after meiosis I and before meiosis II) than at any other point during meiosis. The different drive mechanisms we identify make testable predictions that could explain why some killer meiotic drivers are transient while others are ancient.