Birth-death symmetry in the evolution of a social trait

Studies of the evolution of a social trait often make ecological assumptions (of population structure, life history), and thus a trait can be studied many different times with different assumptions. Here, I consider a Moran model of continuous reproduction and use an inclusive fitness analysis to investigate the relationships between fecundity or survival selection and birth-death (BD) or death-birth (DB) demography on the evolution of a social trait. A simple symmetry obtains: fecundity (respectively survival) effects under BD behave the same as survival (respectively fecundity) effects under DB. When these results are specialized to a homogeneous population, greatly simplified conditions for a positive inclusive fitness effect are obtained in both a finite and an infinite population. The results are established using the elegant formalism of mathematical group theory and are illustrated with an example of a finite population arranged in a cycle with asymmetric offspring dispersal.     

Familial selection and the evolution of social behaviour re-examined

The equation for the fitness requirements for the evolution of altruism by diploid workers in haplodiploid species was derived from the model. of Scudo & Ghiselin (1975). When the benefit to a family is proportional to the number of altruists, the constraints on fitness were found to be the same as for haploid altruists in haplodiploid species and for workers of ether sex in diploid species, in contrast to the equation given by Scudo & Ghiselin (1975). With this correction, their results are now in agreement both with comparable allele frequency models and with kin selection games theory. The general condition for evolution of altruism under this model, when benefits are not necessarily proportional to the number of altruists, was also derived. The result appears to differ from games theory predictions, but this is solely because the basic assumptions are not comparable. Altruism is less likely to arise under these conditions, which are less favorable for altruism at gene frequencies above 0·33.     

Combining experimental evolution with next-generation sequencing: a powerful tool to study adaptation from standing genetic variation

Evolve and resequence (E&R) is a new approach to investigate the genomic responses to selection during experimental evolution. By using whole genome sequencing of pools of individuals (Pool-Seq), this method can identify selected variants in controlled and replicable experimental settings. Reviewing the current state of the field, we show that E&R can be powerful enough to identify causative genes and possibly even single-nucleotide polymorphisms. We also discuss how the experimental design and the complexity of the trait could result in a large number of false positive candidates. We suggest experimental and analytical strategies to maximize the power of E&R to uncover the genotype–phenotype link and serve as an important research tool for a broad range of evolutionary questions.Experimental evolution has a long tradition in biology (Garland and Rose, 2009). By exposing an evolving population to conditions chosen by the researcher, it is possible to study the response to this selection regime. A recent review highlighted the broad range of applications that have been investigated with this methodology and concluded that the breadth of research questions is only limited by the creativity of the experimenter (Kawecki et al., 2012). In addition to the great diversity of experimental designs, experimental evolution provides a unique advantage compared with other evolutionary analyses: the ability to replicate an experiment under identical conditions. Through this replication, experimenters are able to distinguish between stochastic and deterministic effects. Until recently, experimental evolution has mainly focused on phenotypes, sometimes combined with the analysis of a small number of markers (see, for example, Nuzhdin et al., 1993; Teotonio et al., 2009). In the wake of the latest sequencing technologies and the ongoing drop in DNA sequencing costs, however, the ultimate goal to connect the phenotypic response to the underlying genetic changes during an experimental evolution study has now come within reach.Depending on the starting population, two conceptually different approaches of experimental evolution can be distinguished. Either the experiment starts from a genetically homogeneous (invariable) population or from a polymorphic population. In the first approach, adaptation occurs through the accumulation of new beneficial mutations during the experiment (Elena and Lenski, 2003). These experiments therefore require very large population sizes and many generations to ensure a sufficient mutation supply and are thus largely restricted to microorganisms. Alternatively, experiments starting with a polymorphic population do not require novel mutations as selection can act on beneficial alleles that are already present at the beginning of the experiment. Given the massive genetic variation that is present in the starting population, the key challenge for this approach is distinguishing between selected and neutral variants. Neither randomly selected markers nor whole genome sequencing of a few representative individuals can provide sufficient information about the true target(s) of selection. Rather, genome-wide polymorphism data are needed.As whole genome sequencing is still not feasible for large numbers of individuals, experimental evolution studies starting from polymorphic base populations rely on a modified next-generation sequencing approach. Rather than sequencing individuals separately, DNA of multiple individuals from a population are sequenced together (Pool-Seq). This method is more cost effective than sequencing of individuals (Futschik and Schlötterer, 2010) and yields highly accurate genome-wide allele frequency estimates (reviewed in Rellstab et al., 2013; Schlötterer et al., 2014). The combination of experimental evolution with Pool-Seq is also known as Evolve and Resequence (E&R; Turner et al., 2011; Figure 1). Here, we review the state of the art of whole genome polymorphism analysis in experimental evolution studies relying primarily on segregating variation in the starting population.Open in a separate windowFigure 1Overview of E&R studies. (a) A population of flies is exposed for 60 generations to ultraviolet (UV) radiation (purple arrows). We assume here, for the sake of illustration, that darker pigmentation is beneficial in high UV environments, whereby darker flies will increase in frequency. (b) At the genotypic level, the allele frequency of the causative allele (dark brown) will increase, more so than hitchhiking variants (dark gray background) that will be recombined onto other backgrounds (breaks between dark and light gray background). (c) The allele frequencies of the starting population and the selected population are measured with Pool-Seq. (d) Causative variants can be identified by contrasting the allele frequencies between base and selected population and visualized with Manhattan plots. A full color version of this figure is available at the Heredity journal online.In many experimental evolution studies, researchers select for a well-defined trait in a controlled environment. This assures that both the phenotypic and the underlying genomic response are triggered either directly or indirectly by the selection regime applied during the experiment. Thus, E&R studies provide a complementary approach to genome-wide association studies (GWASs) and linkage mapping experiments as strategies to connect genotype and phenotype.     

Probing the Boundaries of Orthology: The Unanticipated Rapid Evolution of Drosophila centrosomin

The rapid evolution of essential developmental genes and their protein products is both intriguing and problematic. The rapid evolution of gene products with simple protein folds and a lack of well-characterized functional domains typically result in a low discovery rate of orthologous genes. Additionally, in the absence of orthologs it is difficult to study the processes and mechanisms underlying rapid evolution. In this study, we have investigated the rapid evolution of centrosomin (cnn), an essential gene encoding centrosomal protein isoforms required during syncytial development in Drosophila melanogaster. Until recently the rapid divergence of cnn made identification of orthologs difficult and questionable because Cnn violates many of the assumptions underlying models for protein evolution. To overcome these limitations, we have identified a group of insect orthologs and present conserved features likely to be required for the functions attributed to cnn in D. melanogaster. We also show that the rapid divergence of Cnn isoforms is apparently due to frequent coding sequence indels and an accelerated rate of intronic additions and eliminations. These changes appear to be buffered by multi-exon and multi-reading frame maximum potential ORFs, simple protein folds, and the splicing machinery. These buffering features also occur in other genes in Drosophila and may help prevent potentially deleterious mutations due to indels in genes with large coding exons and exon-dense regions separated by small introns. This work promises to be useful for future investigations of cnn and potentially other rapidly evolving genes and proteins.     

Phenotypic evolution in stochastic environments: The contribution of frequency- and density-dependent selection

Understanding how environmental variation affects phenotypic evolution requires models based on ecologically realistic assumptions that include variation in population size and specific mechanisms by which environmental fluctuations affect selection. Here we generalize quantitative genetic theory for environmentally induced stochastic selection to include general forms of frequency- and density-dependent selection. We show how the relevant fitness measure under stochastic selection relates to Fisher's fundamental theorem of natural selection, and present a general class of models in which density regulation acts through total use of resources rather than just population size. In this model, there is a constant adaptive topography for expected evolution, and the function maximized in the long run is the expected factor restricting population growth. This allows us to generalize several previous results and to explain why apparently “-selected” species with slow life histories often have low carrying capacities. Our joint analysis of density- and frequency-dependent selection reveals more clearly the relationship between population dynamics and phenotypic evolution, enabling a broader range of eco-evolutionary analyses of some of the most interesting problems in evolution in the face of environmental variation.     

Simulating a base population in honey bee for molecular genetic studies

Background

Over the past years, reports have indicated that honey bee populations are declining and that infestation by an ecto-parasitic mite (Varroa destructor) is one of the main causes. Selective breeding of resistant bees can help to prevent losses due to the parasite, but it requires that a robust breeding program and genetic evaluation are implemented. Genomic selection has emerged as an important tool in animal breeding programs and simulation studies have shown that it yields more accurate breeding value estimates, higher genetic gain and low rates of inbreeding. Since genomic selection relies on marker data, simulations conducted on a genomic dataset are a pre-requisite before selection can be implemented. Although genomic datasets have been simulated in other species undergoing genetic evaluation, simulation of a genomic dataset specific to the honey bee is required since this species has a distinct genetic and reproductive biology. Our software program was aimed at constructing a base population by simulating a random mating honey bee population. A forward-time population simulation approach was applied since it allows modeling of genetic characteristics and reproductive behavior specific to the honey bee.

Results

Our software program yielded a genomic dataset for a base population in linkage disequilibrium. In addition, information was obtained on (1) the position of markers on each chromosome, (2) allele frequency, (3) χ² statistics for Hardy-Weinberg equilibrium, (4) a sorted list of markers with a minor allele frequency less than or equal to the input value, (5) average r² values of linkage disequilibrium between all simulated marker loci pair for all generations and (6) average r² value of linkage disequilibrium in the last generation for selected markers with the highest minor allele frequency.

Conclusion

We developed a software program that takes into account the genetic and reproductive biology specific to the honey bee and that can be used to constitute a genomic dataset compatible with the simulation studies necessary to optimize breeding programs. The source code together with an instruction file is freely accessible at http://msproteomics.org/Research/Misc/honeybeepopulationsimulator.html     

Losing the beat: deficits in temporal coordination

Tapping or clapping to an auditory beat, an easy task for most individuals, reveals precise temporal synchronization with auditory patterns such as music, even in the presence of temporal fluctuations. Most models of beat-tracking rely on the theoretical concept of pulse: a perceived regular beat generated by an internal oscillation that forms the foundation of entrainment abilities. Although tapping to the beat is a natural sensorimotor activity for most individuals, not everyone can track an auditory beat. Recently, the case of Mathieu was documented (Phillips-Silver et al. 2011 Neuropsychologia 49, 961–969. (doi:10.1016/j.neuropsychologia.2011.02.002)). Mathieu presented himself as having difficulty following a beat and exhibited synchronization failures. We examined beat-tracking in normal control participants, Mathieu, and a second beat-deaf individual, who tapped with an auditory metronome in which unpredictable perturbations were introduced to disrupt entrainment. Both beat-deaf cases exhibited failures in error correction in response to the perturbation task while exhibiting normal spontaneous motor tempi (in the absence of an auditory stimulus), supporting a deficit specific to perception–action coupling. A damped harmonic oscillator model was applied to the temporal adaptation responses; the model''s parameters of relaxation time and endogenous frequency accounted for differences between the beat-deaf cases as well as the control group individuals.     

Synthesis of 53 tissue and cell line expression QTL datasets reveals master eQTLs

Background

Gene expression genetic studies in human tissues and cells identify cis- and trans-acting expression quantitative trait loci (eQTLs). These eQTLs provide insights into regulatory mechanisms underlying disease risk. However, few studies systematically characterized eQTL results across cell and tissues types. We synthesized eQTL results from >50 datasets, including new primary data from human brain, peripheral plaque and kidney samples, in order to discover features of human eQTLs.

Results

We find a substantial number of robust cis-eQTLs and far fewer trans-eQTLs consistent across tissues. Analysis of 45 full human GWAS scans indicates eQTLs are enriched overall, and above nSNPs, among positive statistical signals in genetic mapping studies, and account for a significant fraction of the strongest human trait effects. Expression QTLs are enriched for gene centricity, higher population allele frequencies, in housekeeping genes, and for coincidence with regulatory features, though there is little evidence of 5′ or 3′ positional bias. Several regulatory categories are not enriched including microRNAs and their predicted binding sites and long, intergenic non-coding RNAs. Among the most tissue-ubiquitous cis-eQTLs, there is enrichment for genes involved in xenobiotic metabolism and mitochondrial function, suggesting these eQTLs may have adaptive origins. Several strong eQTLs (CDK5RAP2, NBPFs) coincide with regions of reported human lineage selection. The intersection of new kidney and plaque eQTLs with related GWAS suggest possible gene prioritization. For example, butyrophilins are now linked to arterial pathogenesis via multiple genetic and expression studies. Expression QTL and GWAS results are made available as a community resource through the NHLBI GRASP database [http://apps.nhlbi.nih.gov/grasp/].

Conclusions

Expression QTLs inform the interpretation of human trait variability, and may account for a greater fraction of phenotypic variability than protein-coding variants. The synthesis of available tissue eQTL data highlights many strong cis-eQTLs that may have important biologic roles and could serve as positive controls in future studies. Our results indicate some strong tissue-ubiquitous eQTLs may have adaptive origins in humans. Efforts to expand the genetic, splicing and tissue coverage of known eQTLs will provide further insights into human gene regulation.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-532) contains supplementary material, which is available to authorized users.     

Thoughts Toward a Theory of Natural Selection: The Importance of Microbial Experimental Evolution

Natural selection should no longer be thought of simply as a primitive (magical) concept that can be used to support all kinds of evolutionary theorizing. We need to develop causal theories of natural selection; how it arises. Because the factors contributing to the creation of natural selection are expected to be complex and intertwined, theories explaining the causes of natural selection can only be developed through the experimental method. Microbial experimental evolution provides many benefits that using other organisms does not. Microorganisms are small, so millions can be housed in a test tube; they have short generation times, so evolution over hundreds of generations can be easily studied; they can grow in chemically defined media, so the environment can be precisely defined; and they can be frozen, so the fitness of strains or populations can be directly compared across time. Microbial evolution experiments can be divided into two types. The first is to measure the selection coefficient of two known strains over the first 50 or so generations, before advantageous mutations rise to high frequency. This type of experiment can be used to directly test hypotheses. The second is to allow microbial cultures to evolve over many hundreds or thousands of generations and follow the genetic changes, to infer what phenotypes are selected. In the last section of this article, I propose that selection coefficients are not constant, but change as the population becomes fitter, introducing the idea of the selection space.This article is about natural selection. For many years, I have asked my undergraduate students to memorize this definition of natural selection: Natural selection is the differential reproduction and survival of different phenotypes when, at least, part of the differences in phenotypes is caused by differences in genotype. This can also be expressed as differential growth rates of subpopulations when the subpopulations are distinguished by genetic differences. When expressed as differences in the growth rates in terms of the Malthusian growth parameter, m, then natural selection is the difference in birth rates minus the difference in death rates.From demography, we know that birth rates are very variable depending on the environment. In humans in the United States, the birth rate dropped during the economic depression of the 1930s, rose after World War II to produce a baby boom, and dropped afterward. Worldwide, birth rates drop with the provision of government-provided old-age assistance, also with the increasing survival of children previously born. Thus, birth rates are very sensitive to many environmental conditions. Likewise for death rates. We have long known that starvation, disease, war, and fratricide will increase the death rate, often dramatically. There has been a drop in death rates since 1750 as transportation and social organization improved, preventing starvation in local areas as the crops failed. The 1918 flu spiked the death rate and disease could again raise the death rate dramatically. The black plague is famous for wiping out a third to half of some European populations and changing social conditions. Today, high fructose sweetener is blamed for increasing the death rate among lower class Americans. Thus, the environment changes birth and death rates, sometimes dramatically, sometimes very subtly.Turning back to natural selection, natural selection is the difference between two subpopulations, defined by a genetic difference in their birth and death rates weighted by the effects of all environments experienced by these subpopulations over the time period of the observation. Will natural selection be even more complex than population demography or will it be simpler? It could be much more complicated because the response of the birth and death rates of the two subpopulations in the different environments could be different, giving different norms of reaction. Also, the epistasis and dominance could make the reactions of various individuals within each subpopulation to the changing environment very different. Or it could be much simpler when the genetic difference gives different effects only in one environment. For example, continued synthesis of the lactase gene is selected in human populations that ingest lactose as adults.This complexity embedded in the concept of natural selection has been known for a long time. In population genetics, it is assumed that one can estimate an average selection coefficient over all the environments experienced by the population in a set period without needing to specify the environments or their effect on birth and death rates. This selection coefficient is then used to project gene frequency change over time. Because population genetics is interested in the effects or consequences of natural selection, not the causes, it is satisfactory to treat natural selection as a constant without understanding the causes of natural selection. Unfortunately, this simplification has led to a caricature of natural selection as a constant, given a genetic difference.The model of natural selection that I currently use is given in Figure 1. Here, the definition of natural selection as I gave to my students is an expanded definition because phenotypes are generated by genotypes in an environment (the epigenetic environment) and natural selection is generated by differences in phenotypes in an environment (the selective environment). The interaction of genetic variation, epigenetic environment, phenotypic variation, and the selective environment generate natural selection. These are the “causes” of natural selection. The “effects” of natural selection produce changes in allele frequencies giving rise to adaptive evolution. I believe that the most important function of experimental evolution will be to figure out the causal rules or laws of natural selection. I have previously made the analogy of natural selection evolution with force in physics (Dykhuizen 1995). Newton described the effects of force; the understanding of the causes of force were performed over the next 300 years leading to an understanding of electromagnetism, thermodynamics, atomic energy, etc. This understanding has led to most of the practical applications from physics. Hopefully, the same can be performed for natural selection. But, as the causes of force were much stranger than expected, the causes of natural selection will be stranger than we now imagine. Only by doing experiments will we be forced to accept whatever strangeness there is in natural selection.Open in a separate windowFigure 1.The current model of natural selection indicating the complexity of its causes and distinguishing causes from effects. Population genetics studies only the effects of natural selection.     

Allelic Variation,Aneuploidy, and Nongenetic Mechanisms Suppress a Monogenic Trait in Yeast

Clinically relevant features of monogenic diseases, including severity of symptoms and age of onset, can vary widely in response to environmental differences as well as to the presence of genetic modifiers affecting the trait’s penetrance and expressivity. While a better understanding of modifier loci could lead to treatments for Mendelian diseases, the rarity of individuals harboring both a disease-causing allele and a modifying genotype hinders their study in human populations. We examined the genetic architecture of monogenic trait modifiers using a well-characterized yeast model of the human Mendelian disease classic galactosemia. Yeast strains with loss-of-function mutations in the yeast ortholog (GAL7) of the human disease gene (GALT) fail to grow in the presence of even small amounts of galactose due to accumulation of the same toxic intermediates that poison human cells. To isolate and individually genotype large numbers of the very rare (∼0.1%) galactose-tolerant recombinant progeny from a cross between two gal7Δ parents, we developed a new method, called “FACS-QTL.” FACS-QTL improves upon the currently used approaches of bulk segregant analysis and extreme QTL mapping by requiring less genome engineering and strain manipulation as well as maintaining individual genotype information. Our results identified multiple distinct solutions by which the monogenic trait could be suppressed, including genetic and nongenetic mechanisms as well as frequent aneuploidy. Taken together, our results imply that the modifiers of monogenic traits are likely to be genetically complex and heterogeneous.     

Identification of Mob2, a Novel Regulator of Larval Neuromuscular Junction Morphology,in Natural Populations of Drosophila melanogaster

Although evolutionary changes must take place in neural connectivity and synaptic architecture as nervous systems become more complex, we lack understanding of the general principles and specific mechanisms by which these changes occur. Previously, we found that morphology of the larval neuromuscular junction (NMJ) varies extensively among different species of Drosophila but is relatively conserved within a species. To identify specific genes as candidates that might underlie phenotypic differences in NMJ morphology among Drosophila species, we performed a genetic analysis on one of two phenotypic variants we found among 20 natural isolates of Drosophila melanogaster. We discovered genetic polymorphisms for both positive and negative regulators of NMJ growth segregating within the variant line. Focusing on one subline, that displayed NMJ overgrowth, we mapped the phenotype to Mob2 [Monopolar spindle (Mps) one binding protein 2)], a gene encoding a Nuclear Dbf2 (Dumbbell formation 2)-Related (NDR) kinase activator. We confirmed this identification by transformation rescue experiments and showed that presynaptic expression of Mob2 is necessary and sufficient to regulate NMJ growth. Mob2 interacts in a dominant, dose-dependent manner with tricornered but not with warts, to cause NMJ overgrowth, suggesting that Mob2 specifically functions in combination with the former NDR kinase to regulate NMJ development. These results demonstrate the feasibility and utility of identifying genetic variants affecting NMJ morphology in natural populations of Drosophila. These variants can lead to discovery of new genes and molecular mechanisms that regulate NMJ development while also providing new information that can advance our understanding of mechanisms that underlie nervous system evolution.     

The evolution of menopause in cetaceans and humans: the role of demography

Human females stop reproducing long before they die. Among other mammals, only pilot and killer whales exhibit a comparable period of post-reproductive life. The grandmother hypothesis suggests that kin selection can favour post-reproductive survival when older females help their relatives to reproduce. But although there is an evidence that grandmothers can provide such assistance, it is puzzling why menopause should have evolved only among the great apes and toothed whales. We have previously suggested (Cant & Johnstone 2008 Proc. Natl Acad. Sci. USA 105, 5332–5336 (doi:10.1073/pnas.0711911105)) that relatedness asymmetries owing to female-biased dispersal in ancestral humans would have favoured younger females in reproductive competition with older females, predisposing our species to the evolution of menopause. But this argument appears inapplicable to menopausal cetaceans, which exhibit philopatry of both sexes combined with extra-group mating. Here, we derive general formulae for ‘kinship dynamics’, the age-related changes in local relatedness that occur in long-lived social organisms as a consequence of dispersal and mortality. We show that the very different social structures of great apes and menopausal whales both give rise to an increase in local relatedness with female age, favouring late-life helping. Our analysis can therefore help to explain why, of all long-lived, social mammals, it is specifically among the great apes and toothed whales that menopause and post-reproductive helping have evolved.     

Reinterpreting Long-Term Evolution Experiments: Is Delayed Adaptation an Example of Historical Contingency or a Consequence of Intermittent Selection?

Van Hofwegen et al. demonstrated that Escherichia coli rapidly evolves the ability to use citrate when long selective periods are provided (D. J. Van Hofwegen, C. J. Hovde, and S. A. Minnich, J Bacteriol 198:1022–1034, 2016, http://dx.doi.org/10.1128/JB.00831-15). This contrasts with the extreme delay (15 years of daily transfers) seen in the long-term evolution experiments of Lenski and coworkers. Their idea of “historical contingency” may require reinterpretation. Rapid evolution seems to involve selection for duplications of the whole cit locus that are too unstable to contribute when selection is provided in short pulses.     

Requirements for plant coexistence through pollination niche partitioning

Plant–pollinator interactions are often thought to have been a decisive factor in the diversification of flowering plants, but to be of little or no importance for the maintenance of existing plant diversity. In a recent opinion paper, Pauw (2013 Trends Ecol. Evol. 28, 30–37. (doi:10.1016/j.tree.2012.07.019)) challenged this view by proposing a mechanism of diversity maintenance based on pollination niche partitioning. In this article, I investigate under which conditions the mechanism suggested by Pauw can promote plant coexistence, using a mathematical model of plant and pollinator population dynamics. Numerical simulations show that this mechanism is most effective when the costs of searching for flowers are low, pollinator populations are strongly limited by resources other than pollen and nectar, and plant–pollinator interactions are sufficiently specialized. I review the empirical literature on these three requirements, discuss additional factors that may be important for diversity maintenance through pollination niche partitioning, and provide recommendations on how to detect this coexistence mechanism in natural plant communities.     

Why developmental psychology is incomplete without comparative and cross-cultural perspectives

As a discipline, developmental psychology has a long history of relying on animal models and data collected among distinct cultural groups to enrich and inform theories of the ways social and cognitive processes unfold through the lifespan. However, approaches that draw together developmental, cross-cultural and comparative perspectives remain rare. The need for such an approach is reflected in the papers by Heyes (2015 Phil. Trans. R. Soc. B 371, 20150069. (doi:10.1098/rstb.2015.0069)), Schmelz & Call (2015 Phil. Trans. R. Soc. B 371, 20150067. (doi:10.1098/rstb.2015.0067)) and Keller (2015 Phil. Trans. R. Soc. B 371, 20150070. (doi:10.1098/rstb.2015.0070)) in this theme issue. Here, we incorporate these papers into a review of recent research endeavours covering a range of core aspects of social cognition, including social learning, cooperation and collaboration, prosociality, and theory of mind. In so doing, we aim to highlight how input from comparative and cross-cultural empiricism has altered our perspectives of human development and, in particular, led to a deeper understanding of the evolution of the human cultural mind.     

LUMPY: a probabilistic framework for structural variant discovery

Comprehensive discovery of structural variation (SV) from whole genome sequencing data requires multiple detection signals including read-pair, split-read, read-depth and prior knowledge. Owing to technical challenges, extant SV discovery algorithms either use one signal in isolation, or at best use two sequentially. We present LUMPY, a novel SV discovery framework that naturally integrates multiple SV signals jointly across multiple samples. We show that LUMPY yields improved sensitivity, especially when SV signal is reduced owing to either low coverage data or low intra-sample variant allele frequency. We also report a set of 4,564 validated breakpoints from the NA12878 human genome. https://github.com/arq5x/lumpy-sv.     

Trait-based analyses for the detection of linkage between marker loci and quantitative trait loci in crosses between inbred lines

Summary Methods are presented for determining linkage between a marker locus and a nearby locus affecting a quantitative trait (quantitative trait locus=QTL), based on changes in the marker allele frequencies in selection lines derived from the F-2 of a cross between inbred lines, or in the high and low phenotypic classes of an F-2 or BC population. The power of such trait-based (TB) analyses was evaluated and compared with that of methods for determining linkage based on the mean quantitative trait value of marker genotypes in F-2 or BC populations [marker-based (MB) analyses]. TB analyses can be utilized for marker-QTL linkage determination in situations where the MB analysis is not applicable, including analysis of polygenic resistance traits where only a part of the population survives exposure to the Stressor and analysis of marker-allele frequency changes in selection lines. TB analyses may be a useful alternative to MB analyses when interest is centered on a single quantitative trait only and costs of scoring for markers are high compared with costs of raising and obtaining quantitative trait information on F-2 or BC individuals. In this case, a TB analysis will enable equivalent power to be obtained with fewer individuals scored for the marker, but more individuals scored for the quantitative trait. MB analyses remain the method of choice when more than one quantitative trait is to be analyzed in a given population.Contribution from the ARO, Bet Dagan, Israel. No. 1698-E, 1986 series     

An Indel Polymorphism in the Hybrid Incompatibility Gene Lethal Hybrid Rescue of Drosophila Is Functionally Relevant

Hybrid incompatibility (HI) genes are frequently observed to be rapidly evolving under selection. This observation has led to the attractive conjecture that selection-derived protein-sequence divergence is culpable for incompatibilities in hybrids. The Drosophila simulans HI gene Lethal hybrid rescue (Lhr) is an intriguing case, because despite having experienced rapid sequence evolution, its HI properties are a shared function inherited from the ancestral state. Using an unusual D. simulans Lhr hybrid rescue allele, Lhr², we here identify a conserved stretch of 10 amino acids in the C terminus of LHR that is critical for causing hybrid incompatibility. Altering these 10 amino acids weakens or abolishes the ability of Lhr to suppress the hybrid rescue alleles Lhr¹ or Hmr¹, respectively. Besides single-amino-acid substitutions, Lhr orthologs differ by a 16-aa indel polymorphism, with the ancestral deletion state fixed in D. melanogaster and the derived insertion state at very high frequency in D. simulans. Lhr² is a rare D. simulans allele that has the ancestral deletion state of the 16-aa polymorphism. Through a series of transgenic constructs we demonstrate that the ancestral deletion state contributes to the rescue activity of Lhr². This indel is thus a polymorphism that can affect the HI function of Lhr.