Cryptic genetic variation

Plasticity and environment-specific relationships between gene expression and fitness in Saccharomyces cerevisiae

The environment influences how an organism's genotype determines its phenotype and how this phenotype affects its fitness. Here, to better understand this dual role of environment in the production and selection of phenotypic variation, we determined genotype-phenotype-fitness relationships for mutant strains of Saccharomyces cerevisiae in four environments. Specifically, we measured how promoter mutations of the metabolic gene TDH3 modified expression level and affected growth for four different carbon sources. In each environment, we observed a clear relationship between TDH3 expression level and fitness, but this relationship differed among environments. Mutations with similar effects on expression in different environments often had different effects on fitness and vice versa. Such environment-specific relationships between phenotype and fitness can shape the evolution of phenotypic plasticity. We also found that mutations disrupting binding sites for transcription factors had more variable effects on expression among environments than those disrupting the TATA box, which is part of the core promoter. However, mutations with the most environmentally variable effects on fitness were located in the TATA box, because of both the lack of plasticity of TATA box mutations and environment-specific fitness functions. This observation suggests that mutations affecting different molecular mechanisms contribute unequally to regulatory sequence evolution in changing environments.

Plasticity and environment-specific relationships between gene expression and fitness in Saccharomyces cerevisiae

Phenotypic evolution is shaped by interactions between organisms and their environments. The environment influences how an organism's genotype determines its phenotype and how this phenotype affects its fitness. To better understand this dual role of the environment in the production and selection of phenotypic variation, we empirically determined and compared the genotype-phenotype-fitness relationship for mutant strains of the budding yeast Saccharomyces cerevisiae in four environments. Specifically, we measured how mutations in the promoter of the metabolic gene TDH3 modified its expression level and affected its growth on media with four different carbon sources. In each environment, we observed a clear relationship between TDH3 expression level and fitness, but this relationship differed among environments. Genetic variants with similar effects on TDH3 expression in different environments often had different effects on fitness and vice versa. Such environment-specific relationships between phenotype and fitness can shape the evolution of phenotypic plasticity. The set of mutants we examined also allowed us to compare the effects of mutations disrupting binding sites for key transcriptional regulators and the TATA box, which is part of the core promoter sequence. Mutations disrupting the binding sites for the transcription factors had more variable effects on expression among environments than mutations disrupting the TATA box, yet mutations with the most environmentally variable effects on fitness were located in the TATA box. This observation suggests that mutations affecting different molecular mechanisms are likely to contribute unequally to regulatory sequence evolution in changing environments.

The genetic control paradigm in biology: What we say, and what we are entitled to mean

We comment on the article by Keith Baverstock (2021) and provide critiques of the concepts of genetic control, genetic blueprint and genetic program.

Transcriptional enhancers and their communication with gene promoters

Transcriptional enhancers play a key role in the initiation and maintenance of gene expression programmes, particularly in metazoa. How these elements control their target genes in the right place and time is one of the most pertinent questions in functional genomics, with wide implications for most areas of biology. Here, we synthesise classic and recent evidence on the regulatory logic of enhancers, including the principles of enhancer organisation, factors that facilitate and delimit enhancer-promoter communication, and the joint effects of multiple enhancers. We show how modern approaches building on classic insights have begun to unravel the complexity of enhancer-promoter relationships, paving the way towards a quantitative understanding of gene control.

Does Phenological Plasticity Help or Hinder Range Shifts Under Climate Change?

Climate warming is predicted to shift species’ ranges as previously uninhabitable environments just beyond the leading range edges become suitable habitat and trailing range edges become increasingly unsuitable. Understanding which aspects of the environment and species traits mediate these range shifts is critical for understanding species’ possible redistributions under global change, yet we have a limited understanding of the ecological and evolutionary responses underlying population spread or extinction at species’ range edges. Within plant populations, shifts in flowering phenology have been one of the strongest and most consistent responses to climate change, and are likely to play an important role in mediating population dynamics within and beyond species’ ranges. However, the role of phenological shifts, and particularly phenological plasticity, in species’ range shifts remains relatively unstudied. Here, we synthesize literature on phenology, plasticity, and adaptation to suggest ways in which phenological responses to climate may vary across species’ ranges and review the empirical evidence for and against these hypotheses. We then outline how phenological plasticity could facilitate or hinder persistence and potential consequences of phenological plasticity in range expansions, including phenological cues, shifts in correlated traits, altered species interactions, and effects on gene flow. Finally, we suggest future avenues for research, such as characterizing reaction norms for phenology across a species’ range and in beyond-the-range transplant experiments. Given the prevalence and magnitude of phenological shifts, future work should carefully dissect its costs and benefits for population persistence, and incorporate phenological plasticity into models predicting species’ persistence and geographic range shifts under climate change.

Genetic assimilation and accommodation: Models and mechanisms

Genetic assimilation and genetic accommodation are mechanisms by which novel phenotypes are produced and become established in a population. Novel characters may be fixed and canalized so they are insensitive to environmental variation, or can be plastic and adaptively responsive to environmental variation. In this review we explore the various theories that have been proposed to explain the developmental origin and evolution of novel phenotypes and the mechanisms by which canalization and phenotypic plasticity evolve. These theories and models range from conceptual to mathematical and have taken different views of how genes and environment contribute to the development and evolution of the properties of phenotypes. We will argue that a deeper and more nuanced understanding of genetic accommodation requires a recognition that phenotypes are not static entities but are dynamic system properties with no fixed deterministic relationship between genotype and phenotype. We suggest a mechanistic systems-view of development that allows one to incorporate both genes and environment in a common model, and that enables both quantitative analysis and visualization of the evolution of canalization and phenotypic plasticity.

A heuristic model of the effects of phenotypic robustness in adaptive evolution

A recent theoretical, deterministic model of the effects of phenotypic robustness on adaptive evolutionary dynamics showed that a certain level of phenotypic robustness (critical robustness) is a required condition for adaptation to occur and to be maintained during evolution in most real organismal systems. We built an individual-based heuristic model to verify the soundness of these theoretical results through computer simulation, testing expectations under a range of scenarios for the relevant parameters of the evolutionary dynamics. These include the mutation probability, the presence of stochastic effects, the introduction of environmental influences and the possibility for some features of the population (like selection coefficients and phenotypic robustness) to change themselves during adaptation. Overall, we found a good match between observed and expected results, even for evolutionary parameter values that violate some of the assumptions of the deterministic model, and that robustness can itself evolve. However, from more than one simulation it appears that very high robustness values, higher than the critical value, can limit or slow-down adaptation. This possible trade-off was not predicted by the deterministic model.

A Cell Fate Switch in the Caenorhabditis elegans Seam Cell Lineage Occurs Through Modulation of the Wnt Asymmetry Pathway in Response to Temperature Increase

Populations often display consistent developmental phenotypes across individuals despite inevitable biological stochasticity. Nevertheless, developmental robustness has limits, and systems can fail upon change in the environment or the genetic background. We use here the seam cells, a population of epidermal stem cells in Caenorhabditis elegans, to study the influence of temperature change and genetic variation on cell fate. Seam cell development has mostly been studied so far in the laboratory reference strain (N2), grown at 20° temperature. We demonstrate that an increase in culture temperature to 25° introduces variability in the wild-type seam cell lineage, with a proportion of animals showing an increase in seam cell number. We map this increase to lineage-specific symmetrization events of normally asymmetric cell divisions at the fourth larval stage, leading to the retention of seam cell fate in both daughter cells. Using genetics and single-molecule imaging, we demonstrate that this symmetrization occurs via changes in the Wnt asymmetry pathway, leading to aberrant Wnt target activation in anterior cell daughters. We find that intrinsic differences in the Wnt asymmetry pathway already exist between seam cells at 20° and this may sensitize cells toward a cell fate switch at increased temperature. Finally, we demonstrate that wild isolates of C. elegans display variation in seam cell sensitivity to increased culture temperature, although their average seam cell number is comparable at 20°. Our results highlight how temperature can modulate cell fate decisions in an invertebrate model of stem cell patterning.

Do traits separated by metamorphosis evolve independently? Concepts and methods

Despite the ubiquity of complex life cycles, we know little of the evolutionary constraints exerted by metamorphosis. Here, we present pitfalls and methods to answer whether animals with a complex life cycle can independently adapt to the environments encountered at each life stage, with a specific focus on the microevolution of quantitative characters. We first discuss challenges associated with study traits and populations. We further emphasize the benefits of using a combination of approaches. We then develop how multivariate methods can limit several issues by revealing genetic patterns that are invisible when only considering trait-by-trait genetic correlations. Finally, we detail how Lande's work on sexual dimorphism can be applied in measuring G matrices across life stages. The methods and tools described here will contribute towards building a predictive framework for trait evolution across life stages.

Climate change shifts natural selection and the adaptive potential of the perennial forb Boechera stricta in the Rocky Mountains

Heritable genetic variation is necessary for populations to evolve in response to anthropogenic climate change. However, antagonistic genetic correlations among traits may constrain the rate of adaptation, even if substantial genetic variation exists. We examine potential genetic responses to selection by comparing multivariate genetic variance-covariances of traits and fitness (multivariate Robertson-Price identities) across different environments in a reciprocal transplant experiment of the forb Boechera stricta in the Rocky Mountains. By transplanting populations into four common gardens arrayed along an elevational gradient, and exposing populations to control and snow removal treatments, we simulated future and current climates and snowmelt regimes. Genetic variation in flowering and germination phenology declined in plants moved downslope to warmer, drier sites, suggesting that these traits may have a limited ability to evolve under future climates. Simulated climate change via snow removal altered the strength of selection on flowering traits, but we found little evidence that genetic correlations among traits are likely to affect the rate of adaptation to climate change. Overall, our results suggest that climate change may alter the evolutionary potential of B. stricta, but reduced expression of genetic variation may be a larger impediment to adaptation than constraints imposed by antagonistic genetic correlations.

Novel approach to quantitative spatial gene expression uncovers genetic stochasticity in the developing Drosophila eye

Robustness in development allows for the accumulation of genetically based variation in expression. However, this variation is usually examined in response to large perturbations, and examination of this variation has been limited to being spatial, or quantitative, but because of technical restrictions not both. Here we bridge these gaps by investigating replicated quantitative spatial gene expression using rigorous statistical models, in different genotypes, sexes, and species (Drosophila melanogaster and D. simulans). Using this type of quantitative approach with molecular developmental data allows for comparison among conditions, such as different genetic backgrounds. We apply this approach to the morphogenetic furrow, a wave of differentiation that patterns the developing eye disc. Within the morphogenetic furrow, we focus on four genes, hairy, atonal, hedgehog, and Delta. Hybridization chain reaction quantitatively measures spatial gene expression, co-staining for all four genes simultaneously. We find considerable variation in the spatial expression pattern of these genes in the eye between species, genotypes, and sexes. We also find that there has been evolution of the regulatory relationship between these genes, and that their spatial interrelationships have evolved between species. This variation has no phenotypic effect, and could be buffered by network thresholds or compensation from other genes. Both of these mechanisms could potentially be contributing to long term developmental systems drift.

Decanalizing thinking on genetic canalization

The concept of genetic canalization has had an abiding influence on views of complex-trait evolution. A genetically canalized system has evolved to become less sensitive to the effects of mutation. When a gene product that supports canalization is compromised, the phenotypic impacts of a mutation should be more pronounced. This expected increase in mutational effects not only has important consequences for evolution, but has also motivated strategies to treat disease. However, recent studies demonstrate that, when putative agents of genetic canalization are impaired, systems do not behave as expected. Here, we review the evidence that is used to infer whether particular gene products are agents of genetic canalization. Then we explain how such inferences often succumb to a converse error. We go on to show that several candidate agents of genetic canalization increase the phenotypic impacts of some mutations while decreasing the phenotypic impacts of others. These observations suggest that whether a gene product acts as a 'buffer' (lessening mutational effects) or a 'potentiator' (increasing mutational effects) is not a fixed property of the gene product but instead differs for the different mutations with which it interacts. To investigate features of genetic interactions that might predispose them toward buffering versus potentiation, we explore simulated gene-regulatory networks. Similarly to putative agents of genetic canalization, the gene products in simulated networks also modify the phenotypic effects of mutations in other genes without a strong overall tendency towards lessening or increasing these effects. In sum, these observations call into question whether complex traits have evolved to become less sensitive (i.e., are canalized) to genetic change, and the degree to which trends exist that predict how one genetic change might alter another's impact. We conclude by discussing approaches to address these and other open questions that are brought into focus by re-thinking genetic canalization.

A sibling method for identifying vQTLs

The propensity of a trait to vary within a population may have evolutionary, ecological, or clinical significance. In the present study we deploy sibling models to offer a novel and unbiased way to ascertain loci associated with the extent to which phenotypes vary (variance-controlling quantitative trait loci, or vQTLs). Previous methods for vQTL-mapping either exclude genetically related individuals or treat genetic relatedness among individuals as a complicating factor addressed by adjusting estimates for non-independence in phenotypes. The present method uses genetic relatedness as a tool to obtain unbiased estimates of variance effects rather than as a nuisance. The family-based approach, which utilizes random variation between siblings in minor allele counts at a locus, also allows controls for parental genotype, mean effects, and non-linear (dominance) effects that may spuriously appear to generate variation. Simulations show that the approach performs equally well as two existing methods (squared Z-score and DGLM) in controlling type I error rates when there is no unobserved confounding, and performs significantly better than these methods in the presence of small degrees of confounding. Using height and BMI as empirical applications, we investigate SNPs that alter within-family variation in height and BMI, as well as pathways that appear to be enriched. One significant SNP for BMI variability, in the MAST4 gene, replicated. Pathway analysis revealed one gene set, encoding members of several signaling pathways related to gap junction function, which appears significantly enriched for associations with within-family height variation in both datasets (while not enriched in analysis of mean levels). We recommend approximating laboratory random assignment of genotype using family data and more careful attention to the possible conflation of mean and variance effects.

Gene-gene and gene-environment interactions in complex traits in yeast

One of the fundamental questions in biology is how the genotype regulates the phenotype. An increasing number of studies indicate that, in most cases, the effect of a genetic locus on the phenotype is context-dependent, i.e. it is influenced by the genetic background and the environment in which the phenotype is measured. Still, the majority of the studies, in both model organisms and humans, that map the genetic regulation of phenotypic variation in complex traits primarily identify additive loci with independent effects. This does not reflect an absence of the contribution of genetic interactions to phenotypic variation, but instead is a consequence of the technical limitations in mapping gene-gene interactions (GGI) and gene-environment interactions (GEI). Yeast, with its detailed molecular understanding, diverse population genomics and ease of genetic manipulation, is a unique and powerful resource to study the contributions of GGI and GEI in the regulation of phenotypic variation. Here we review studies in yeast that have identified GGI and GEI that regulate phenotypic variation, and discuss the contribution of these findings in explaining missing heritability of complex traits, and how observations from these GGI and GEI studies enhance our understanding of the mechanisms underlying genetic robustness and adaptability that shape the architecture of the genotype-phenotype map.

Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits

Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets.

Transcriptome dynamics along axolotl regenerative development are consistent with an extensive reduction in gene expression heterogeneity in dedifferentiated cells

Although in recent years the study of gene expression variation in the absence of genetic or environmental cues or gene expression heterogeneity has intensified considerably, many basic and applied biological fields still remain unaware of how useful the study of gene expression heterogeneity patterns might be for the characterization of biological systems and/or processes. Largely based on the modulator effect chromatin compaction has for gene expression heterogeneity and the extensive changes in chromatin compaction known to occur for specialized cells that are naturally or artificially induced to revert to less specialized states or dedifferentiate, I recently hypothesized that processes that concur with cell dedifferentiation would show an extensive reduction in gene expression heterogeneity. The confirmation of the existence of such trend could be of wide interest because of the biomedical and biotechnological relevance of cell dedifferentiation-based processes, i.e., regenerative development, cancer, human induced pluripotent stem cells, or plant somatic embryogenesis. Here, I report the first empirical evidence consistent with the existence of an extensive reduction in gene expression heterogeneity for processes that concur with cell dedifferentiation by analyzing transcriptome dynamics along forearm regenerative development in Ambystoma mexicanum or axolotl. Also, I briefly discuss on the utility of the study of gene expression heterogeneity dynamics might have for the characterization of cell dedifferentiation-based processes, and the engineering of tools that afforded better monitoring and modulating such processes. Finally, I reflect on how a transitional reduction in gene expression heterogeneity for dedifferentiated cells can promote a long-term increase in phenotypic heterogeneity following cell dedifferentiation with potential adverse effects for biomedical and biotechnological applications.

Drosophila as a Model for Diabetes and Diseases of Insulin Resistance

Despite the importance of insulin signaling pathways in human disease, initial concerns that insect physiology and sugar metabolism differ enough from humans that flies would not model human disease hampered research in this area. However, during the past 10-15 years, evidence has accumulated that flies can indeed model various aspects of diabetes and related human disorders. This cluster of diseases impact insulin and insulin signaling pathways, fields which have been discussed in many excellent review articles in recent years. In this chapter, we restrict our focus to specific examples of diabetes-related disease models in Drosophila, discussing the advantages and limitations of these models in light of physiological similarities and differences between insects and mammals. We discuss features of metabolism and sugar regulation that are shared between flies and mammals, and specific Drosophila models for Type 1 and Type 2 diabetes, Metabolic syndrome, and related abnormalities including insulin resistance and heart disease. We conclude that fly models for diabetes and related disorders enhance our ability to identify genes and discern functional interactions that can be exploited for disease intervention.

Metabolomic and Gene Expression Profiles Exhibit Modular Genetic and Dietary Structure Linking Metabolic Syndrome Phenotypes in Drosophila

Genetic and environmental factors influence complex disease in humans, such as metabolic syndrome, and Drosophila melanogaster serves as an excellent model in which to test these factors experimentally. Here we explore the modularity of endophenotypes with an in-depth reanalysis of a previous study by Reed et al. (2014), where we raised 20 wild-type genetic lines of Drosophila larvae on four diets and measured gross phenotypes of body weight, total sugar, and total triglycerides, as well as the endophenotypes of metabolomic and whole-genome expression profiles. We then perform new gene expression experiments to test for conservation of phenotype-expression correlations across different diets and populations. We find that transcript levels correlated with gross phenotypes were enriched for puparial adhesion, metamorphosis, and central energy metabolism functions. The specific metabolites L-DOPA and N-arachidonoyl dopamine make physiological links between the gross phenotypes across diets, whereas leucine and isoleucine thus exhibit genotype-by-diet interactions. Between diets, we find low conservation of the endophenotypes that correlate with the gross phenotypes. Through the follow-up expression study, we found that transcript-trait correlations are well conserved across populations raised on a familiar diet, but on a novel diet, the transcript-trait correlations are no longer conserved. Thus, physiological canalization of metabolic phenotypes breaks down in a novel environment exposing cryptic variation. We cannot predict the physiological basis of disease in a perturbing environment from profiles observed in the ancestral environment. This study demonstrates that variation for disease traits within a population is acquired through a multitude of physiological mechanisms, some of which transcend genetic and environmental influences, and others that are specific to an individual’s genetic and environmental context.

Dearth of polymorphism associated with a sustained response to selection for flowering time in maize

Background

Long term selection experiments bring unique insights on the genetic architecture of quantitative traits and their evolvability. Indeed, they are utilized to (i) monitor changes in allele frequencies and assess the effects of genomic regions involved traits determinism; (ii) evaluate the role of standing variation versus new mutations during adaptation; (iii) investigate the contribution of non allelic interactions. Here we describe genetic and phenotypic evolution of two independent Divergent Selection Experiments (DSEs) for flowering time conducted during 16 years from two early maize inbred lines.

Results

Our experimental design uses selfing as the mating system and small population sizes, so that two independent families evolved within each population, Late and Early. Observed patterns are strikingly similar between the two DSEs. We observed a significant response to selection in both directions during the first 7 generations of selection. Within Early families, the response is linear through 16 generations, consistent with the maintenance of genetic variance. Within Late families and despite maintenance of significant genetic variation across 17 generations, the response to selection reached a plateau after 7 generations. This plateau is likely caused by physiological limits. Residual heterozygosity in the initial inbreds can partly explain the observed responses as evidenced by 42 markers derived from both Methyl-Sensitive Amplification- and Amplified Fragment Length- Polymorphisms. Among the 42, a subset of 13 markers most of which are in high linkage disequilibrium, display a strong association with flowering time variation. Their fast fixation throughout DSEs’ pedigrees results in strong genetic differentiation between populations and families.

Conclusions

Our results reveal a paradox between the sustainability of the response to selection and the associated dearth of polymorphisms. Among other hypotheses, we discuss the maintenance of heritable variation by few mutations with strong epistatic interactions whose effects are modified by continuous changes of the genetic background through time.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-015-0382-5) contains supplementary material, which is available to authorized users.

Genetic complexity in a Drosophila model of diabetes-associated misfolded human proinsulin

Drosophila melanogaster has been widely used as a model of human Mendelian disease, but its value in modeling complex disease has received little attention. Fly models of complex disease would enable high-resolution mapping of disease-modifying loci and the identification of novel targets for therapeutic intervention. Here, we describe a fly model of permanent neonatal diabetes mellitus and explore the complexity of this model. The approach involves the transgenic expression of a misfolded mutant of human preproinsulin, hINS^C96Y, which is a cause of permanent neonatal diabetes. When expressed in fly imaginal discs, hINS^C96Y causes a reduction of adult structures, including the eye, wing, and notum. Eye imaginal discs exhibit defects in both the structure and the arrangement of ommatidia. In the wing, expression of hINS^C96Y leads to ectopic expression of veins and mechano-sensory organs, indicating disruption of wild-type signaling processes regulating cell fates. These readily measurable “disease” phenotypes are sensitive to temperature, gene dose, and sex. Mutant (but not wild-type) proinsulin expression in the eye imaginal disc induces IRE1-mediated XBP1 alternative splicing, a signal for endoplasmic reticulum stress response activation, and produces global change in gene expression. Mutant hINS transgene tester strains, when crossed to stocks from the Drosophila Genetic Reference Panel, produce F₁ adults with a continuous range of disease phenotypes and large broad-sense heritability. Surprisingly, the severity of mutant hINS-induced disease in the eye is not correlated with that in the notum in these crosses, nor with eye reduction phenotypes caused by the expression of two dominant eye mutants acting in two different eye development pathways, Drop (Dr) or Lobe (L), when crossed into the same genetic backgrounds. The tissue specificity of genetic variability for mutant hINS-induced disease has, therefore, its own distinct signature. The genetic dominance of disease-specific phenotypic variability in our model of misfolded human proinsulin makes this approach amenable to genome-wide association study in a simple F₁ screen of natural variation.

A novel genetic locus modulates infarct volume independently of the extent of collateral circulation

In the mouse model of permanent, middle cerebral artery occlusion, infarct volume varies widely across inbred strains but generally is inversely correlated with collateral vessel number. However, we also observed certain mouse strains that share similar collateral vessel anatomy but exhibit significantly different infarct volume. To identify genetic factors determining infarct volume in a collateral vessel-independent manner, we performed quantitative trait locus analysis on a F2 cross between C57BL/6J and C3H/HeJ strains. We mapped four novel loci (Civq4 through Civq7) that modulate infarct volume. Civq4, on chromosome 8, is the strongest locus (logarithm of the odds 9.8) that contributes 21% of the phenotypic variance of infarct volume in the cross. The Civq4 and Civq6 loci represent transgressive B6 alleles that render animals susceptible to larger infarcts. Based on genomic sequence and microarray analyses, we propose candidate genes for the Civq4 locus. By selecting inbred strains with similar collateral vessel anatomy but that vary significantly in infarct volume, we have mapped four loci determining infarct volume in a mouse model of ischemic stroke. Two of the loci appear to modulate infarct volume through a collateral vessel-independent mechanism. Based on strain-specific sequence variants and differences in transcript levels, Msr1 and Mtmr7 appear to be strong candidate genes for Civq4. Identifying the underlying genetic factors of these loci will elucidate the genetic architecture response to cerebral ischemia, shed new light on disease mechanisms of ischemic stroke, and identify potential therapeutic targets for clinical applications.

The role of robustness in phenotypic adaptation and innovation

Phenotypes that vary in response to DNA mutations are essential for evolutionary adaptation and innovation. Therefore, it seems that robustness, a lack of phenotypic variability, must hinder adaptation. The main purpose of this review is to show why this is not necessarily correct. There are two reasons. The first is that robustness causes the existence of genotype networks--large connected sets of genotypes with the same phenotype. I discuss why genotype networks facilitate phenotypic variability. The second reason emerges from the evolutionary dynamics of evolving populations on genotype networks. I discuss how these dynamics can render highly robust phenotypes more variable, using examples from protein and RNA macromolecules. In addition, robustness can help avoid an important evolutionary conflict between the interests of individuals and populations-a conflict that can impede evolutionary adaptation.

Genotype-by-diet interactions drive metabolic phenotype variation in Drosophila melanogaster

The rising prevalence of complex disease suggests that alterations to the human environment are increasing the proportion of individuals who exceed a threshold of liability. This might be due either to a global shift in the population mean of underlying contributing traits, or to increased variance of such underlying endophenotypes (such as body weight). To contrast these quantitative genetic mechanisms with respect to weight gain, we have quantified the effect of dietary perturbation on metabolic traits in 146 inbred lines of Drosophila melanogaster and show that genotype-by-diet interactions are pervasive. For several metabolic traits, genotype-by-diet interactions account for far more variance (between 12 and 17%) than diet alone (1-2%), and in some cases have as large an effect as genetics alone (11-23%). Substantial dew point effects were also observed. Larval foraging behavior was found to be a quantitative trait exhibiting significant genetic variation for path length (P = 0.0004). Metabolic and fitness traits exhibited a complex correlation structure, and there was evidence of selection minimizing weight under laboratory conditions. In addition, a high fat diet significantly increases population variance in metabolic phenotypes, suggesting decreased robustness in the face of dietary perturbation. Changes in metabolic trait mean and variance in response to diet indicates that shifts in both population mean and variance in underlying traits could contribute to increases in complex disease.