Summary Self- and kin-discrimination are observed in most kingdoms of life and are mediated by highly polymorphic plasma membrane proteins [1-7]. Sequence polymorphism, which is essential for effective recognition, is maintained by balancing selection [8-10]. Dictyostelium discoideum are social amoebae that propagate as unicellular organisms, but aggregate upon starvation and from fruiting bodies with viable spores and dead stalk cells. Aggregative development exposes Dictyostelium to the perils of chimerism, including cheating, which raises questions about how the victims survive in nature and how social cooperation persists [11-15]. Dictyostelids can minimize the cost of chimerism by preferential cooperation with kin [16-18], but the mechanisms of kin-discrimination are largely unknown. Dictyostelium lag-genes encode transmembrane proteins with multiple immunoglobulin (Ig) repeats that participate in cell-adhesion and signaling [19-25]. Here we describe their role in kin-discrimination. We show that lagB1 and lagC1 are highly polymorphic in natural populations and that their sequence dissimilarity correlates well with wild-strain segregation. Deleting lagB1 and lagC1 results in strain segregation in chimerae with wild-type cells, whereas elimination of the nearly invariant homolog lagD1 has no such consequences. These findings reveal an early evolutionary origin of kin-discrimination and provide insight into the mechanism of social recognition and immunity.

In the social amoeba Dictyostelium discoideum, thousands of cells aggregate upon starvation to form a multicellular fruiting body, and approximately 20% of them die to form a stalk that benefits the others. The aggregative nature of multicellular development makes the cells vulnerable to exploitation by cheaters, and the potential for cheating is indeed high. Cells might avoid being victimized if they can discriminate among individuals and avoid those that are genetically different. We tested how widely social amoebae cooperate by mixing isolates from different localities that cover most of their natural range. We show here that different isolates partially exclude one another during aggregation, and there is a positive relationship between the extent of this exclusion and the genetic distance between strains. Our findings demonstrate that D. discoideum cells co-aggregate more with genetically similar than dissimilar individuals, suggesting the existence of a mechanism that discerns the degree of genetic similarity between individuals in this social microorganism.

Accurate identification of genetic variants from next-generation sequencing (NGS) data is essential for immediate largescale genomic endeavors such as the 1000 Genomes Project, and is crucial for further genetic analysis based on the discoveries. The key challenge in single nucleotide polymorphism (SNP) discovery is to distinguish true individual variants (occurring at a low frequency) from sequencing errors (often occurring at frequencies orders of magnitude higher). Therefore, knowledge of the error probabilities of base calls is essential. We have developed Atlas-SNP2, a computational tool that detects and accounts for systematic sequencing errors caused by context-related variables in a logistic regression model learned from training data sets. Subsequently, it estimates the posterior error probability for each substitution through a Bayesian formula that integrates prior knowledge of the overall sequencing error probability and the estimated SNP rate with the results from the logistic regression model for the given substitutions. The estimated posterior SNP probability can be used to distinguish true SNPs from sequencing errors. Validation results show that Atlas-SNP2 achieves a false-positive rate of lower than 10%, with an~5% or lower false-negative rate.[Supplemental material is available online at http://www.genome.org. Atlas-SNP2 and its documentation are available for download at http://www.hgsc.bcm.tmc.edu/cascade-tech-software-ti.hgsc.]In recent years, next-generation sequencing (NGS) technologies have propelled the rapid progress of genomics studies (Hillier et al. 2008;Srivatsan et al. 2008). Continuous improvement in NGS technologies are increasing the throughput while lowering costs, thus enabling ultra-large-scale sequencing efforts (Margulies et al. 2005;Shendure and Ji 2008). For example, the 1000 Genomes Project is aimed at sequencing more than 1000 human genomes to characterize the pattern of genetic variants (common and rare) in unprecedented detail (http://www.1000genomes.org/page.php) (Kaiser 2008). To realize this objective, it is essential that NGS technologies detect genomic variations accurately, including single nucleotide polymorphisms (SNPs), structural variations caused by insertions or deletions (indels), copy number variations (CNVs), and inversions or other rearrangements. However, the short read length and relatively high error rates present challenges to variant discovery from raw NGS data. While the error model for Sanger sequencing was well characterized (Ewing and Green 1998), systematic errors in NGS are not yet well studied, making it difficult to distinguish true genetic variations from the sequencing errors.Currently, there are several methods available for detecting SNPs from NGS data, including Pyrobayes , POLYBAYES (Marth et al. 1999), MAQ (Li et al. 2008), SOAP (Li et al. 2009), VarScan (Ley et al. 2008Koboldt et al. 2009), and other largely heuristic approaches (Wheeler et al. 2008). Pyrobayes-POLYBAYES recalibrates base-calling of all nucleotide positions from ...

Micromutational models of adaptation have placed considerable weight on antagonistic pleiotropy as a mechanism that prevents mutations of large effect from achieving fixation. However, there are few empirical studies of the distribution of pleiotropic effects, and no studies that have examined this distribution for a large number of adaptive mutations. Here we examine the form and extent of pleiotropy associated with beneficial mutations in Escherichia coli. To do so, we used a collection of independently evolved genotypes, each of which contains a beneficial mutation that confers increased fitness in a glucose-limited environment. To determine the pleiotropic effects of these mutations, we examined the fitnesses of the mutants in five novel resource environments. Our results show that the majority of mutations had significant fitness effects in alternative resources, such that pleiotropy was common. The predominant form of this pleiotropy was positive--that is, most mutations that conferred increased fitness in glucose also conferred increased fitness in novel resources. We did detect some deleterious pleiotropic effects, but they were primarily limited to one of the five resources, and within this resource, to only a subset of mutants. Although pleiotropic effects were generally positive, fitness levels were lower and more variable on resources that differed most in their mechanisms of uptake and catabolism from that of glucose. Positive pleiotropic effects were strongly correlated in magnitude with their direct effects, but no such correlation was found among mutants with deleterious pleiotropic effects. Whereas previous studies of populations evolved on glucose for longer periods of time showed consistent declines on some of the resources used here, our results suggest that deleterious pleiotropic effects were limited to only a subset of the beneficial mutations available.

Summary Cooperative systems are susceptible to invasion by selfish individuals that profit from receiving the social benefits but fail to contribute. These so-called “cheaters” can have a fitness advantage in the laboratory, but it is unclear whether cheating provides an important selective advantage in nature. We used a population genomic approach to examine the history of genes involved in cheating behaviors in the social amoeba Dictyostelium discoideum, testing whether these genes experience rapid evolutionary change as a result of conflict over spore-stalk fate. Candidate genes and surrounding regions showed elevated polymorphism, unusual patterns of linkage disequilibrium, and lower levels of population differentiation, but they did not show greater between-species divergence. The signatures were most consistent with frequency-dependent selection acting to maintain multiple alleles, suggesting that conflict may lead to stalemate rather than an escalating arms race. Our results reveal the evolutionary dynamics of cooperation and cheating and underscore how sequence-based approaches can be used to elucidate the history of conflicts that are difficult to observe directly.