A hierarchical Bayesian model for a novel sparse partial diallel crossing design

Phenotypic Variation and the Impact of Admixture in the Oryza rufipogon Species Complex (ORSC)

Crop wild relatives represent valuable reservoirs of variation for breeding, but their populations are threatened in natural habitats, are sparsely represented in genebanks, and most are poorly characterized. The focus of this study is the Oryza rufipogon species complex (ORSC), wild progenitor of Asian rice (Oryza sativa L.). The ORSC comprises perennial, annual and intermediate forms which were historically designated as O. rufipogon, O. nivara, and O. sativa f. spontanea (or Oryza spp., an annual form of mixed O. rufipogon/O. nivara and O. sativa ancestry), respectively, based on non-standardized morphological, geographical, and/or ecologically-based species definitions and boundaries. Here, a collection of 240 diverse ORSC accessions, characterized by genotyping-by-sequencing (113,739 SNPs), was phenotyped for 44 traits associated with plant, panicle, and seed morphology in the screenhouse at the International Rice Research Institute, Philippines. These traits included heritable phenotypes often recorded as characterization data by genebanks. Over 100 of these ORSC accessions were also phenotyped in the greenhouse for 18 traits in Stuttgart, Arkansas, and 16 traits in Ithaca, New York, United States. We implemented a Bayesian Gaussian mixture model to infer accession groups from a subset of these phenotypic data and ascertained three phenotype-based group assignments. We used concordance between the genotypic subpopulations and these phenotype-based groups to identify a suite of phenotypic traits that could reliably differentiate the ORSC populations, whether measured in tropical or temperate regions. The traits provide insight into plant morphology, life history (perenniality versus annuality) and mating habit (self- versus cross-pollinated), and are largely consistent with genebank species designations. One phenotypic group contains predominantly O. rufipogon accessions characterized as perennial and largely out-crossing and one contains predominantly O. nivara accessions characterized as annual and largely inbreeding. From these groups, 42 "core" O. rufipogon and 25 "core" O. nivara accessions were identified for domestication studies. The third group, comprising 20% of our collection, has the most accessions identified as Oryza spp. (51.2%) and levels of O. sativa admixture accounting for more than 50% of the genome. This third group is potentially useful as a "pre-breeding" pool for breeders attempting to incorporate novel variation into elite breeding lines.

The molecular architecture of Drosophila melanogaster defense against Beauveria bassiana explored through evolve and resequence and quantitative trait locus mapping

Little is known about the genetic architecture of antifungal immunity in natural populations. Using two population genetic approaches, quantitative trait locus (QTL) mapping and evolve and resequence (E&R), we explored D. melanogaster immune defense against infection with the fungus Beauveria bassiana. The immune defense was highly variable both in the recombinant inbred lines from the Drosophila Synthetic Population Resource used for our QTL mapping and in the synthetic outbred populations used in our E&R study. Survivorship of infection improved dramatically over just 10 generations in the E&R study, and continued to increase for an additional nine generations, revealing a trade-off with uninfected longevity. Populations selected for increased defense against B. bassiana evolved cross resistance to a second, distinct B. bassiana strain but not to bacterial pathogens. The QTL mapping study revealed that sexual dimorphism in defense depends on host genotype, and the E&R study indicated that sexual dimorphism also depends on the specific pathogen to which the host is exposed. Both the QTL mapping and E&R experiments generated lists of potentially causal candidate genes, although these lists were nonoverlapping.

Low Additive Genetic Variation in a Trait Under Selection in Domesticated Rice

Quantitative traits are important targets of both natural and artificial selection. The genetic architecture of these traits and its change during the adaptive process is thus of fundamental interest. The fate of the additive effects of variants underlying a trait receives particular attention because they constitute the genetic variation component that is transferred from parents to offspring and thus governs the response to selection. While estimation of this component of phenotypic variation is challenging, the increasing availability of dense molecular markers puts it within reach. Inbred plant species offer an additional advantage because phenotypes of genetically identical individuals can be measured in replicate. This makes it possible to estimate marker effects separately from the contribution of the genetic background not captured by genotyped loci. We focused on root growth in domesticated rice, Oryza sativa, under normal and aluminum (Al) stress conditions, a trait under recent selection because it correlates with survival under drought. A dense single nucleotide polymorphism (SNP) map is available for all accessions studied. Taking advantage of this map and a set of Bayesian models, we assessed additive marker effects. While total genetic variation accounted for a large proportion of phenotypic variance, marker effects contributed little information, particularly in the Al-tolerant tropical japonica population of rice. We were unable to identify any loci associated with root growth in this population. Models estimating the aggregate effects of all measured genotypes likewise produced low estimates of marker heritability and were unable to predict total genetic values accurately. Our results support the long-standing conjecture that additive genetic variation is depleted in traits under selection. We further provide evidence that this depletion is due to the prevalence of low-frequency alleles that underlie the trait.

Creating outbred and inbred populations in haplodiploids to measure adaptive responses in the laboratory

Laboratory studies are often criticized for not being representative of processes occurring in natural populations. One reason for this is the fact that laboratory populations generally do not capture enough of the genetic variation of natural populations. This can be mitigated by mixing the genetic background of several field populations when creating laboratory populations. From these outbred populations, it is possible to generate inbred lines, thereby freezing and partitioning part of their variability, allowing each genotype to be characterized independently. Many studies addressing adaptation of organisms to their environment, such as those involving quantitative genetics or experimental evolution, rely on inbred or outbred populations, but the methodology underlying the generation of such biological resources is usually not explicitly documented. Here, we developed different procedures to circumvent common pitfalls of laboratory studies, and illustrate their application using two haplodiploid species, the spider mites Tetranychus urticae and Tetranychus evansi. First, we present a method that increases the chance of capturing high amounts of variability when creating outbred populations, by performing controlled crosses between individuals from different field-collected populations. Second, we depict the creation of inbred lines derived from such outbred populations, by performing several generations of sib-mating. Third, we outline an experimental evolution protocol that allows the maintenance of a constant population size at the beginning of each generation, thereby preventing bottlenecks and diminishing extinction risks. Finally, we discuss the advantages of these procedures and emphasize that sharing such biological resources and combining them with available genetic tools will allow consistent and comparable studies that greatly contribute to our understanding of ecological and evolutionary processes.

Decoupling the Variances of Heterosis and Inbreeding Effects Is Evidenced in Yeast's Life-History and Proteomic Traits

Heterosis (hybrid vigor) and inbreeding depression, commonly considered as corollary phenomena, could nevertheless be decoupled under certain assumptions according to theoretical population genetics works. To explore this issue on real data, we analyzed the components of genetic variation in a population derived from a half-diallel cross between strains from Saccharomyces cerevisiae and S. uvarum, two related yeast species involved in alcoholic fermentation. A large number of phenotypic traits, either molecular (coming from quantitative proteomics) or related to fermentation and life history, were measured during alcoholic fermentation. Because the parental strains were included in the design, we were able to distinguish between inbreeding effects, which measure phenotypic differences between inbred and hybrids, and heterosis, which measures phenotypic differences between a specific hybrid and the other hybrids sharing a common parent. The sources of phenotypic variation differed depending on the temperature, indicating the predominance of genotype-by-environment interactions. Decomposing the total genetic variance into variances of additive (intra- and interspecific) effects, of inbreeding effects, and of heterosis (intra- and interspecific) effects, we showed that the distribution of variance components defined clear-cut groups of proteins and traits. Moreover, it was possible to cluster fermentation and life-history traits into most proteomic groups. Within groups, we observed positive, negative, or null correlations between the variances of heterosis and inbreeding effects. To our knowledge, such a decoupling had never been experimentally demonstrated. This result suggests that, despite a common evolutionary history of individuals within a species, the different types of traits have been subject to different selective pressures.

Genomic Structural Variations Within Five Continental Populations of Drosophila melanogaster

Chromosomal structural variations (SV) including insertions, deletions, inversions, and translocations occur within the genome and can have a significant effect on organismal phenotype. Some of these effects are caused by structural variations containing genes. Large structural variations represent a significant amount of the genetic diversity within a population. We used a global sampling of Drosophila melanogaster (Ithaca, Zimbabwe, Beijing, Tasmania, and Netherlands) to represent diverse populations within the species. We used long-read sequencing and optical mapping technologies to identify SVs in these genomes. Among the five lines examined, we found an average of 2,928 structural variants within these genomes. These structural variations varied greatly in size and location, included many exonic regions, and could impact adaptation and genomic evolution.

Sexual dimorphism in Drosophila melanogaster survival of Beauveria bassiana infection depends on core immune signaling

In many animal species, females and males differ in physiology, lifespan, and immune function. The magnitude and direction of the sexual dimorphism in immune function varies greatly and the genetic and mechanistic bases for this dimorphism are often unknown. Here we show that Drosophila melanogaster females are more likely than males to die from infection with several strains of the fungal entomopathogen Beauveria bassiana. The sexual dimorphism is not exclusively due to barrier defenses and persists when flies are inoculated by injection as well as by surface exposure. Loss of function mutations of Toll pathway genes remove the dimorphism in survivorship. Surprisingly, loss of function mutation of relish, a gene in the Imd pathway, also removes the dimorphism, but the dimorphism persists in flies carrying other Imd pathway mutations. The robust sexual dimorphism in D. melanogaster survival to B. bassiana presents opportunities to further dissect its mechanistic details, with applications for biological control of insect vectors of human disease and insect crop pests.

Dissecting the Genetic Architecture of Shoot Growth in Carrot (Daucus carota L.) Using a Diallel Mating Design

Crop establishment in carrot (Daucus carota L.) is limited by slow seedling growth and delayed canopy closure, resulting in high management costs for weed control. Varieties with improved growth habit (i.e., larger canopy and increased shoot biomass) may help mitigate weed control, but the underlying genetics of these traits in carrot is unknown. This project used a diallel mating design coupled with recent Bayesian analytical methods to determine the genetic basis of carrot shoot growth. Six diverse carrot inbred lines with variable shoot size were crossed in WI in 2014. F1 hybrids, reciprocal crosses, and parental selfs were grown in a randomized complete block design with two blocks in WI (2015) and CA (2015, 2016). Measurements included canopy height, canopy width, shoot biomass, and root biomass. General and specific combining abilities were estimated using Griffing’s Model I, which is a common analysis for plant breeding experiments. In parallel, additive, inbred, cross-specific, and maternal effects were estimated from a Bayesian mixed model, which is robust to dealing with data imbalance and outliers. Both additive and nonadditive effects significantly influenced shoot traits, with nonadditive effects playing a larger role early in the growing season, when weed control is most critical. Results suggest the presence of heritable variation and thus potential for improvement of these phenotypes in carrot. In addition, results present evidence of heterosis for root biomass, which is a major component of carrot yield.

Bayesian Diallel Analysis Reveals Mx1-Dependent and Mx1-Independent Effects on Response to Influenza A Virus in Mice

Influenza A virus (IAV) is a respiratory pathogen that causes substantial morbidity and mortality during both seasonal and pandemic outbreaks. Infection outcomes in unexposed populations are affected by host genetics, but the host genetic architecture is not well understood. Here, we obtain a broad view of how heritable factors affect a mouse model of response to IAV infection using an 8 × 8 diallel of the eight inbred founder strains of the Collaborative Cross (CC). Expanding on a prior statistical framework for modeling treatment response in diallels, we explore how a range of heritable effects modify acute host response to IAV through 4 d postinfection. Heritable effects in aggregate explained ∼57% of the variance in IAV-induced weight loss. Much of this was attributable to a pattern of additive effects that became more prominent through day 4 postinfection and was consistent with previous reports of antiinfluenza myxovirus resistance 1 (Mx1) polymorphisms segregating between these strains; these additive effects largely recapitulated haplotype effects observed at the Mx1 locus in a previous study of the incipient CC, and are also replicated here in a CC recombinant intercross population. Genetic dominance of protective Mx1 haplotypes was observed to differ by subspecies of origin: relative to the domesticus null Mx1 allele, musculus acts dominantly whereas castaneus acts additively. After controlling for Mx1, heritable effects, though less distinct, accounted for ∼34% of the phenotypic variance. Implications for future mapping studies are discussed.

The Toll pathway underlies host sexual dimorphism in resistance to both Gram-negative and Gram-positive bacteria in mated Drosophila

BACKGROUND

Host sexual dimorphism is being increasingly recognized to generate strong differences in the outcome of infectious disease, but the mechanisms underlying immunological differences between males and females remain poorly characterized. Here, we used Drosophila melanogaster to assess and dissect sexual dimorphism in the innate response to systemic bacterial infection.

RESULTS

We demonstrated sexual dimorphism in susceptibility to infection by a broad spectrum of Gram-positive and Gram-negative bacteria. We found that both virgin and mated females are more susceptible than mated males to most, but not all, infections. We investigated in more detail the lower resistance of females to infection with Providencia rettgeri, a Gram-negative bacterium that naturally infects D. melanogaster. We found that females have a higher number of phagocytes than males and that ablation of hemocytes does not eliminate the dimorphism in resistance to P. rettgeri, so the observed dimorphism does not stem from differences in the cellular response. The Imd pathway is critical for the production of antimicrobial peptides in response to Gram-negative bacteria, but mutants for Imd signaling continued to exhibit dimorphism even though both sexes showed strongly reduced resistance. Instead, we found that the Toll pathway is responsible for the dimorphism in resistance. The Toll pathway is dimorphic in genome-wide constitutive gene expression and in induced response to infection. Toll signaling is dimorphic in both constitutive signaling and in induced activation in response to P. rettgeri infection. The dimorphism in pathway activation can be specifically attributed to Persephone-mediated immune stimulation, by which the Toll pathway is triggered in response to pathogen-derived virulence factors. We additionally found that, in absence of Toll signaling, males become more susceptible than females to the Gram-positive Enterococcus faecalis. This reversal in susceptibility between male and female Toll pathway mutants compared to wildtype hosts highlights the key role of the Toll pathway in D. melanogaster sexual dimorphism in resistance to infection.

CONCLUSION

Altogether, our data demonstrate that Toll pathway activity differs between male and female D. melanogaster in response to bacterial infection, thus identifying innate immune signaling as a determinant of sexual immune dimorphism.

Incomplete dominance of deleterious alleles contributes substantially to trait variation and heterosis in maize

Deleterious alleles have long been proposed to play an important role in patterning phenotypic variation and are central to commonly held ideas explaining the hybrid vigor observed in the offspring of a cross between two inbred parents. We test these ideas using evolutionary measures of sequence conservation to ask whether incorporating information about putatively deleterious alleles can inform genomic selection (GS) models and improve phenotypic prediction. We measured a number of agronomic traits in both the inbred parents and hybrids of an elite maize partial diallel population and re-sequenced the parents of the population. Inbred elite maize lines vary for more than 350,000 putatively deleterious sites, but show a lower burden of such sites than a comparable set of traditional landraces. Our modeling reveals widespread evidence for incomplete dominance at these loci, and supports theoretical models that more damaging variants are usually more recessive. We identify haplotype blocks using an identity-by-decent (IBD) analysis and perform genomic prediction analyses in which we weigh blocks on the basis of complementation for segregating putatively deleterious variants. Cross-validation results show that incorporating sequence conservation in genomic selection improves prediction accuracy for grain yield and other fitness-related traits as well as heterosis for those traits. Our results provide empirical support for an important role for incomplete dominance of deleterious alleles in explaining heterosis and demonstrate the utility of incorporating functional annotation in phenotypic prediction and plant breeding.

Extensive local adaptation within the chemosensory system following Drosophila melanogaster's global expansion

How organisms adapt to new environments is of fundamental biological interest, but poorly understood at the genetic level. Chemosensory systems provide attractive models to address this problem, because they lie between external environmental signals and internal physiological responses. To investigate how selection has shaped the well-characterized chemosensory system of Drosophila melanogaster, we have analysed genome-wide data from five diverse populations. By couching population genomic analyses of chemosensory protein families within parallel analyses of other large families, we demonstrate that chemosensory proteins are not outliers for adaptive divergence between species. However, chemosensory families often display the strongest genome-wide signals of recent selection within D. melanogaster. We show that recent adaptation has operated almost exclusively on standing variation, and that patterns of adaptive mutations predict diverse effects on protein function. Finally, we provide evidence that chemosensory proteins have experienced relaxed constraint, and argue that this has been important for their rapid adaptation over short timescales.

Fruit flies gain valuable information about their environment by sensing chemicals. Here, Arguello et al. show strong signals of recent selection on the chemosensory system of the fruit fly Drosophila melanogaster, consistent with the adaptation of populations to their local chemical environment.

Evidence for the fixation of gene duplications by positive selection in Drosophila

Gene duplications play a key role in the emergence of novel traits and in adaptation. But despite their centrality to evolutionary processes, it is still largely unknown how new gene duplicates are initially fixed within populations and later maintained in genomes. Long-standing debates on the evolution of gene duplications could be settled by determining the relative importance of genetic drift vs. positive selection in the fixation of new gene duplicates. Using the Drosophila Global Diversity Lines (GDL), we have combined genome-wide SNP polymorphism data with a novel set of copy number variant calls and gene expression profiles to characterize the polymorphic phase of new genes. We found that approximately half of the roughly 500 new complete gene duplications segregating in the GDL lead to significant increases in the expression levels of the duplicated genes and that these duplications are more likely to be found at lower frequencies, suggesting a negative impact on fitness. However, we also found that six of the nine gene duplications that are fixed or close to fixation in at least one of the five populations in our study show signs of being under positive selection, and that these duplications are likely beneficial because of dosage effects, with a possible role for additional mutations in two duplications. Our work suggests that in Drosophila, theoretical models that posit that gene duplications are immediately beneficial and fixed by positive selection are most relevant to explain the long-term evolution of gene duplications in this species.

Global diversity lines - a five-continent reference panel of sequenced Drosophila melanogaster strains

Reference collections of multiple Drosophila lines with accumulating collections of “omics” data have proven especially valuable for the study of population genetics and complex trait genetics. Here we present a description of a resource collection of 84 strains of Drosophila melanogaster whose genome sequences were obtained after 12 generations of full-sib inbreeding. The initial rationale for this resource was to foster development of a systems biology platform for modeling metabolic regulation by the use of natural polymorphisms as perturbations. As reference lines, they are amenable to repeated phenotypic measurements, and already a large collection of metabolic traits have been assayed. Another key feature of these strains is their widespread geographic origin, coming from Beijing, Ithaca, Netherlands, Tasmania, and Zimbabwe. After obtaining 12.5× coverage of paired-end Illumina sequence reads, SNP and indel calls were made with the GATK platform. Thorough quality control was enabled by deep sequencing one line to >100×, and single-nucleotide polymorphisms and indels were validated using ddRAD-sequencing as an orthogonal platform. In addition, a series of preliminary population genetic tests were performed with these single-nucleotide polymorphism data for assessment of data quality. We found 83 segregating inversions among the lines, and as expected these were especially abundant in the African sample. We anticipate that this will make a useful addition to the set of reference D. melanogaster strains, thanks to its geographic structuring and unusually high level of genetic diversity.

Quantitative genetics of learning ability and resistance to stress in Drosophila melanogaster

Even though laboratory evolution experiments have demonstrated genetic variation for learning ability, we know little about the underlying genetic architecture and genetic relationships with other ecologically relevant traits. With a full diallel cross among twelve inbred lines of Drosophila melanogaster originating from a natural population (0.75 < F < 0.93), we investigated the genetic architecture of olfactory learning ability and compared it to that for another behavioral trait (unconditional preference for odors), as well as three traits quantifying the ability to deal with environmental challenges: egg-to-adult survival and developmental rate on a low-quality food, and resistance to a bacterial pathogen. Substantial additive genetic variation was detected for each trait, highlighting their potential to evolve. Genetic effects contributed more than nongenetic parental effects to variation in traits measured at the adult stage: learning, odorant perception, and resistance to infection. In contrast, the two traits quantifying larval tolerance to low-quality food were more strongly affected by parental effects. We found no evidence for genetic correlations between traits, suggesting that these traits could evolve at least to some degree independently of one another. Finally, inbreeding adversely affected all traits.

Predicting performance and plasticity in the development of respiratory structures and metabolic systems

The scaling laws governing metabolism suggest that we can predict metabolic rates across taxonomic scales that span large differences in mass. Yet, scaling relationships can vary with development, body region, and environment. Within species, there is variation in metabolic rate that is independent of mass and which may be explained by genetic variation, the environment or their interaction (i.e., metabolic plasticity). Additionally, some structures, such as the insect tracheal respiratory system, change throughout development and in response to the environment to match the changing functional requirements of the organism. We discuss how study of the development of respiratory function meets multiple challenges set forth by the NSF Grand Challenges Workshop. Development of the structure and function of respiratory and metabolic systems (1) is inherently stable and yet can respond dynamically to change, (2) is plastic and exhibits sensitivity to environments, and (3) can be examined across multiple scales in time and space. Predicting respiratory performance and plasticity requires quantitative models that integrate information across scales of function from the expression of metabolic genes and mitochondrial biogenesis to the building of respiratory structures. We present insect models where data are available on the development of the tracheal respiratory system and of metabolic physiology and suggest what is needed to develop predictive models. Incorporating quantitative genetic data will enable mapping of genetic and genetic-by-environment variation onto phenotypes, which is necessary to understand the evolution of respiratory and metabolic systems and their ability to enable respiratory homeostasis as organisms walk the tightrope between stability and change.

Monophyly of Wolbachia pipientis genomes within Drosophila melanogaster: geographic structuring, titre variation and host effects across five populations

Wolbachia pipientis is one of the most widely studied endosymbionts today, yet we know little about its short-term adaptation and evolution. Here, using a set of 91 inbred Drosophila melanogaster lines from five populations, we explore patterns of diversity and recent evolution in the Wolbachia strain wMel. Within the D. melanogaster lines, we identify six major mitochondrial clades and four wMel clades. Concordant with past studies, the Wolbachia haplotypes contain an overall low level of nucleotide diversity, yet they still display geographic structuring. Using Bayesian analysis informed with demographic estimates of colonization times, we estimate that all extant D. melanogaster mitochondrial haplotypes coalesce to a Wolbachia-infected ancestor approximately 2200 years ago. Finally, we measure wMel titre within the infected flies and find that titre varies across populations, an effect attributable to host genetic factors. This demonstration of local phenotypic divergence suggests that intraspecific host genetic variation plays a key role in shaping this model symbiotic system.

Heritability and inter-population differences in lipid profiles of Drosophila melanogaster

Characterizing and understanding the complex spectrum of lipids in higher organisms lags far behind our analysis of genome and transcriptome sequences. Here we generate and evaluate comprehensive lipid profiles (>200 lipids) of 92 inbred lines from five different Drosophila melanogaster populations. We find that the majority of lipid species are highly heritable, and even lipids with odd-chain fatty acids, which cannot be generated by the fly itself, also have high heritabilities. Abundance of the endosymbiont Wolbachia, a potential provider of odd-chained lipids, was positively correlated with this group of lipids. Additionally, we show that despite years of laboratory rearing on the same medium, the lipid profiles of the five geographic populations are sufficiently distinct for population discrimination. Our data predicts a strikingly different membrane fluidity for flies from the Netherlands, which is supported by their increased ethanol tolerance. We find that 18% of lipids show strong concentration differences between males and females. Through an analysis of the correlation structure of the lipid classes, we find modules of co-regulated lipids and begin to associate these with metabolic constraints. Our data provide a foundation for developing associations between variation in lipid composition with variation in other metabolic attributes, with genome-wide variation, and with metrics of health and overall reproductive fitness.

Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype-phenotype relationships and its relevance to crop improvement

More accurate and precise phenotyping strategies are necessary to empower high-resolution linkage mapping and genome-wide association studies and for training genomic selection models in plant improvement. Within this framework, the objective of modern phenotyping is to increase the accuracy, precision and throughput of phenotypic estimation at all levels of biological organization while reducing costs and minimizing labor through automation, remote sensing, improved data integration and experimental design. Much like the efforts to optimize genotyping during the 1980s and 1990s, designing effective phenotyping initiatives today requires multi-faceted collaborations between biologists, computer scientists, statisticians and engineers. Robust phenotyping systems are needed to characterize the full suite of genetic factors that contribute to quantitative phenotypic variation across cells, organs and tissues, developmental stages, years, environments, species and research programs. Next-generation phenotyping generates significantly more data than previously and requires novel data management, access and storage systems, increased use of ontologies to facilitate data integration, and new statistical tools for enhancing experimental design and extracting biologically meaningful signal from environmental and experimental noise. To ensure relevance, the implementation of efficient and informative phenotyping experiments also requires familiarity with diverse germplasm resources, population structures, and target populations of environments. Today, phenotyping is quickly emerging as the major operational bottleneck limiting the power of genetic analysis and genomic prediction. The challenge for the next generation of quantitative geneticists and plant breeders is not only to understand the genetic basis of complex trait variation, but also to use that knowledge to efficiently synthesize twenty-first century crop varieties.

A general Bayesian approach to analyzing diallel crosses of inbred strains

The classic diallel takes a set of parents and produces offspring from all possible mating pairs. Phenotype values among the offspring can then be related back to their respective parentage. When the parents are diploid, sexed, and inbred, the diallel can characterize aggregate effects of genetic background on a phenotype, revealing effects of strain dosage, heterosis, parent of origin, epistasis, and sex-specific versions thereof. However, its analysis is traditionally intricate, unforgiving of unplanned missing information, and highly sensitive to imbalance, making the diallel unapproachable to many geneticists. Nonetheless, imbalanced and incomplete diallels arise frequently, albeit unintentionally, as by-products of larger-scale experiments that collect F(1) data, for example, pilot studies or multiparent breeding efforts such as the Collaborative Cross or the Arabidopsis MAGIC lines. We present a general Bayesian model for analyzing diallel data on dioecious diploid inbred strains that cleanly decomposes the observed patterns of variation into biologically intuitive components, simultaneously models and accommodates outliers, and provides shrinkage estimates of effects that automatically incorporate uncertainty due to imbalance, missing data, and small sample size. We further present a model selection procedure for weighing evidence for or against the inclusion of those components in a predictive model. We evaluate our method through simulation and apply it to incomplete diallel data on the founders and F(1)'s of the Collaborative Cross, robustly characterizing the genetic architecture of 48 phenotypes.

Environmental and genetic perturbations reveal different networks of metabolic regulation

Measurement of metabolic and physiological parameters in replicated crosses of Drosophila melanogaster inbred lines reveals that environmental and genetic perturbations uncover substantially different networks of metabolic regulation.

We collected extensive data on enzyme activities and physiological parameters from replicated crosses of D. melanogaster inbred lines.

We implemented a multivariate hierarchical Bayesian model to separately assess genetic and environmental covariation among system components and infer metabolic regulatory networks.

Networks revealed by both environmental and genetic perturbations are similar among populations and between sexes.

Environmental and genetic networks differ substantially, suggesting that environmental changes and mutations would have different systemic effects even when their primary targets are the same.

Progress in systems biology depends on accurate descriptions of biological networks. Connections in a regulatory network are identified as correlations of gene expression across a set of environmental or genetic perturbations. To use this information to predict system behavior, we must test how the nature of perturbations affects topologies of networks they reveal. To probe this question, we focused on metabolism of Drosophila melanogaster. Our source of perturbations is a set of crosses among 92 wild-derived lines from five populations, replicated in a manner permitting separate assessment of the effects of genetic variation and environmental fluctuation. We directly assayed activities of enzymes and levels of metabolites. Using a multivariate Bayesian model, we estimated covariance among metabolic parameters and built fine-grained probabilistic models of network topology. The environmental and genetic co-regulation networks are substantially the same among five populations. However, genetic and environmental perturbations reveal qualitative differences in metabolic regulation, suggesting that environmental shifts, such as diet modifications, produce different systemic effects than genetic changes, even if the primary targets are the same.

Male genotype influences female reproductive investment in Drosophila melanogaster

In many species, males can influence the amount of resources their mates invest in reproduction. Two favoured hypotheses for this observation are that females assess male quality during courtship or copulation and alter their investment in offspring accordingly, or that males manipulate females to invest heavily in offspring produced soon after mating. Here, we examined whether there is genetic variation for males to influence female short-term reproductive investment in Drosophila melanogaster, a species with strong sexual selection and substantial sexual conflict. We measured the fecundity and egg size of females mated to males from multiple isofemale lines collected from populations around the globe. Although these traits were not strongly influenced by the male's population of origin, we found that 22 per cent of the variation in female short-term reproductive investment was attributable to the genotype of her mate. This is the first direct evidence that male D. melanogaster vary genetically in their proximate influence on female fecundity, egg size and overall reproductive investment.