Tissue-specific genetic features inform prediction of drug side effects in clinical trials

Adverse side effects often account for the failure of drug clinical trials. We evaluated whether a phenome-wide association study (PheWAS) of 1167 phenotypes in >360,000 U.K. Biobank individuals, in combination with gene expression and expression quantitative trait loci (eQTL) in 48 tissues, can inform prediction of drug side effects in clinical trials. We determined that drug target genes with five genetic features—tissue specificity of gene expression, Mendelian associations, phenotype- and tissue-level effects of genome-wide association (GWA) loci driven by eQTL, and genetic constraint—confer a 2.6-fold greater risk of side effects, compared to genes without such features. The presence of eQTL in multiple tissues resulted in more unique phenotypes driven by GWA loci, suggesting that drugs delivered to multiple tissues can induce several side effects. We demonstrate the utility of PheWAS and eQTL data from multiple tissues for informing drug side effect prediction and highlight the need for tissue-specific drug delivery.

Plastic responses to novel environments are biased towards phenotype dimensions with high additive genetic variation

Environmentally induced phenotypes have been proposed to initiate and bias adaptive evolutionary change toward particular directions. The potential for this to happen depends in part on how well plastic responses are aligned with the additive genetic variance and covariance in traits. Using meta-analysis, we demonstrate that plastic responses to novel environments tend to occur along phenotype dimensions that harbor substantial amounts of additive genetic variation. This suggests that selection for or against environmentally induced phenotypes typically will be effective. One interpretation of the alignment between the direction of plasticity and the main axis of additive genetic variation is that developmental systems tend to respond to environmental novelty as they do to genetic mutation. This makes it challenging to distinguish if the direction of evolution is biased by plasticity or genetic “constraint.” Our results therefore highlight a need for new theoretical and empirical approaches to address the role of plasticity in evolution.

Linking sex differences to the evolution of infectious disease life-histories

Sex differences in the prevalence, course and severity of infection are widespread, yet the evolutionary consequences of these differences remain unclear. Understanding how male–female differences affect the trajectory of infectious disease requires connecting the contrasting dynamics that pathogens might experience within each sex to the number of susceptible and infected individuals that are circulating in a population. In this study, we build on theory using genetic covariance functions to link the growth of a pathogen within a host to the evolution and spread of disease between individuals. Using the Daphnia–Pasteuria system as a test case, we show that on the basis of within-host dynamics alone, females seem to be more evolutionarily liable for the pathogen, with higher spore loads and greater divergence among pathogen genotypes as infection progresses. Between-host transmission, however, appears to offset the lower performance of a pathogen within a male host, making even subtle differences between the sexes evolutionarily relevant, as long as the selection generated by the between-host dynamics is sufficiently strong. Our model suggests that relatively simple differences in within-host processes occurring in males and females can lead to complex patterns of genetic constraint on pathogen evolution, particularly during an expanding epidemic. This article is part of the theme issue ‘Linking local adaptation with the evolution of sex differences’.

Evidence for stabilizing selection at pleiotropic loci for human complex traits

How genetic variation contributes to phenotypic variation is a central question in genetics. Association signals for a complex trait are found throughout the majority of the genome suggesting much of the genome is under some degree of genetic constraint. Here, we develop a intraspecific population genetics approach to define a measure of population structure for each single nucleotide polymorphism (SNP). Using this approach, we test for evidence of stabilizing selection at complex traits and pleiotropic loci arising from the evolutionary history of 47 complex traits and common diseases. Our approach allowed us to identify traits and regions under stabilizing selection towards both global and subpopulation optima. Strongest depletion of allelic diversity was found at disease loci, indicating stabilizing selection has acted on these phenotypes in all subpopulations. Pleiotropic loci predominantly displayed evidence of stabilizing selection, often contributed to multiple disease risks, and sometimes also affected non-disease traits such as height. Risk alleles at pleiotropic disease loci displayed a more consistent direction of effect than expected by chance suggesting that stabilizing selection acting on pleiotropic loci is amplified through multiple disease phenotypes.

Breaking through evolutionary constraint by environmental fluctuations

Epistatic interactions can frustrate and shape evolutionary change. Indeed, phenotypes may fail to evolve because essential mutations can only be selected positively if fixed simultaneously. How environmental variability affects such constraints is poorly understood. Here we studied genetic constraints in fixed and fluctuating environments, using theEscherichia coli lacoperon as a model system for genotype-environment interactions. The data indicated an apparent paradox: in different fixed environments, mutational trajectories became trapped at sub-optima where no further improvements were possible, while repeated switching between these same environments allowed unconstrained adaptation by continuous improvements. Pervasive cross-environmental trade-offs transformed peaks into valleys upon environmental change, thus enabling escape from entrapment. This study shows that environmental variability can lift genetic constraint, and that trade-offs not only impede but can also facilitate adaptive evolution.

Genetic constraints predict evolutionary divergence in Dalechampia blossoms

If genetic constraints are important, then rates and direction of evolution should be related to trait evolvability. Here we use recently developed measures of evolvability to test the genetic constraint hypothesis with quantitative genetic data on floral morphology from the Neotropical vine Dalechampia scandens (Euphorbiaceae). These measures were compared against rates of evolution and patterns of divergence among 24 populations in two species in the D. scandens species complex. We found clear evidence for genetic constraints, particularly among traits that were tightly phenotypically integrated. This relationship between evolvability and evolutionary divergence is puzzling, because the estimated evolvabilities seem too large to constitute real constraints. We suggest that this paradox can be explained by a combination of weak stabilizing selection around moving adaptive optima and small realized evolvabilities relative to the observed additive genetic variance.