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.

Patient Experience: A Call to Action for Nurse Leadership.

Health care organizations recognize that it is difficult to achieve consistent excellence in patient experience. Nursing leaders cannot underestimate the importance of the role they play in efforts to improve the patient experience. This article outlines a call to action for nurse leaders to consider reframing the patient experience as a focal point for the entire organization's strategic approach and tactics. This involves facilitating a dialogue about the organization's patient experience definition; building a strong, positive organization culture; creating processes to ensure the engagement of all voices; ensuring a focus across the continuum of care; and addressing the key drivers of patient experience excellence.

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.

Patient Experience: The New Heart of Healthcare Leadership.

In a healthcare world in which consumerism is no longer a question and value has claimed its place at center stage, leaders are called to think differently about how they operate and manage their organizations. Priorities are curving in new directions with shifts in policy, direction of dollars, and evolution of practice. At the center of this transition is an opportunity for healthcare leaders to recognize that patient experience is the new heart of healthcare leadership.To address quality, safety, service, cost, and population health outcomes, leaders must rethink how they understand and engage in experience efforts overall. An intentional and clear strategic line of sight and purpose are required, including how patient experience is defined, the core concepts it comprises and is influenced by, and the outcomes it ultimately helps achieve. The challenge for leaders is to reconceive how this maximum potential can be achieved as compared with how experience has been traditionally managed through tactical efforts.Quick lists of effective tactics are relatively easy to come by, and leaders are already aware of many, if not most, of them. So why do so many organizations applying these tactics today struggle to maintain the results they seek? The reason is that tactics are only as useful as the framework in which they are applied and as robust as the foundation on which they are implemented. The intent of this article is to stir a dialogue on how to reframe the issue of patient experience.In reframing a collective view about what patient experience is, the way leaders choose to address it must change. This adjustment requires balancing the work of defining patient experience with the strategic intent behind what organizations ultimately aim to achieve. In changing the conversation on patient experience, we move it from an idea that lurks at the edges of healthcare, or that stands as just one of many strategic pillars, to the central call to action for healthcare leaders.

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.

All voices matter in experience design: A commitment to action in engaging patient and family voice.

This article intends to frame the broader concept of experience design and the engagement of patient and family voice, reinforcing how truly aligned healthcare professionals are not only on the value of this work but also in understanding the benefits of it. When addressing the idea of design, it is important to look at the broadest possible construct and consider the engagement of patient and family voices in healthcare operational efforts, not as passive advisors but as active participants in data gathering, providing input, and with actual decision-making. The article offers engagement is not just part of process, facility, or experience design but must be part of the decisions made in how organizations in healthcare today are built, led, and sustained, fundamentally reinforcing our opportunity in healthcare is to focus on overall experience with purpose and intention. This commitment is what will lead to the outcomes all ultimately hope to achieve.

Why experience matters: moving from words to action.

This article explores the nature of patient experience from the perspective of the language we use at a systemic level, discussing the range of terminology that has an impact on how we involve the voices of patients and families in health care today. The author explores the recent evolution in the language of patient experience, acknowledging the diversity of perspective while offering that there is an opportunity for alignment, and presents a model for integrating the constructs that frame excellence in patient experience. The author leaves us with a challenge: to continue the conversation and to find opportunities to elevate the impact of patient experience overall.

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.

Transcriptional misexpression in hybrids between species linked by gene flow is associated with patterns of sequence divergence.

The extent to which hybridization disrupts a gene's pattern of expression likely governs its propensity for introgression, while its extent of molecular divergence can itself underlie such disruption. Together, these phenomena shape the landscape of sequence and transcriptional divergence across the genome as species diverge. To understand this process, we characterize gene expression inheritance, regulatory divergence, and molecular divergence in the reproductive transcriptomes of species linked by gene flow: the fruit flies Anastrepha fraterculus and A. obliqua, which show evidence of gene flow despite clear evolutionary divergence. We find that their transcriptional patterns are a mosaic between those typically observed within and between allopatric species. Transcripts showing transgressive expression in hybrids or cis-regulatory divergence between species are associated with greater sequence divergence. This may reflect pleiotropic constraints that make them resistant to gene flow or they may be more likely to experience divergent selection. While these more divergent gene classes are likely to be important contributors to species differences, they are relatively rare. Instead, most differentially regulated transcripts, including those linked to reproduction, show high degrees of dominance in hybrids and trans-regulated divergence between species, suggesting widespread genetic compatibility that potentially allowed for introgression. These findings provide insights into how postzygotic isolating mechanisms might evolve in the presence of gene flow: regions showing cis-regulatory divergence or transgressive expression contribute to reproductive isolation, while regions with dominant expression and trans-regulatory divergence allow for introgression. These patterns create a genomic mosaic of transcriptional regulation that is tied to sequence divergence.