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Plant–insect interactions are ubiquitous, and have been studied intensely because of their relevance to damage and pollination in agricultural plants, and to the ecology and evolution of biodiversity. Variation within species can affect the outcome of these interactions. Specific genes and chemicals that mediate these interactions have been identified, but genome‐ or metabolome‐scale studies might be necessary to better understand the ecological and evolutionary consequences of intraspecific variation for plant–insect interactions. Here, we present such a study. Specifically, we assess the consequences of genome‐wide genetic variation in the model plantMedicago truncatulaforLycaeides melissacaterpillar growth and survival (larval performance). Using a rearing experiment and a whole‐genome SNP data set (>5 million SNPs), we found that polygenic variation inM. truncatulaexplains 9%–41% of the observed variation in caterpillar growth and survival. Genetic correlations among caterpillar performance and other plant traits, including structural defences and some anonymous chemical features, suggest that multipleM. truncatulaalleles have pleiotropic effects on plant traits and caterpillar performance (or that substantial linkage disequilibrium exists among distinct loci affecting subsets of these traits). A moderate proportion of the genetic effect ofM. truncatulaalleles onL. melissaperformance can be explained by the effect of these alleles on the plant traits we measured, especially leaf toughness. Taken together, our results show that intraspecific genetic variation inM. truncatulahas a substantial effect on the successful development ofL. melissacaterpillars (i.e., on a plant–insect interaction), and further point toward traits potentially mediating this genetic effect.

 

The study of ecological speciation is inherently linked to the study of selection. Methods for estimating phenotypic selection within a generation based on associations between trait values and fitness (e.g. survival) of individuals are established. These methods attempt to disentangle selection acting directly on a trait from indirect selection caused by correlations with other traits via multivariate statistical approaches (i.e. inference of selection gradients). The estimation of selection on genotypic or genomic variation could also benefit from disentangling direct and indirect selection on genetic loci. However, achieving this goal is difficult with genomic data because the number of potentially correlated genetic loci (p) is very large relative to the number of individuals sampled (n). In other words, the number of model parameters exceeds the number of observations (p ≫ n). We present simulations examining the utility of whole‐genome regression approaches (i.e. Bayesian sparse linear mixed models) for quantifying direct selection in cases wherep ≫ n. Such models have been used for genome‐wide association mapping and are common in artificial breeding. Our results show they hold promise for studies of natural selection in the wild and thus of ecological speciation. But we also demonstrate important limitations to the approach and discuss study designs required for more robust inferences.

 

Host-associated microbiomes play important roles in host health and pathogen defense. In amphibians, the skin-associated microbiota can contribute to innate immunity with potential implications for disease management. Few studies have examined season-long temporal variation in the amphibian skin-associated microbiome, and the interactions between bacteria and fungi on amphibian skin remain poorly understood. We characterize season-long temporal variation in the skin-associated microbiome of the western tiger salamander ( Ambystoma mavortium ) for both bacteria and fungi between sites and across salamander life stages. Two hundred seven skin-associated microbiome samples were collected from salamanders at two Rocky Mountain lakes throughout the summer and fall of 2018, and 127 additional microbiome samples were collected from lake water and lake substrate. We used 16S rRNA and ITS amplicon sequencing with Bayesian Dirichlet-multinomial regression to estimate the relative abundances of bacterial and fungal taxa, test for differential abundance, examine microbial selection, and derive alpha diversity. We predicted the ability of bacterial communities to inhibit the amphibian chytrid fungus Batrachochytrium dendrobatidis ( Bd ), a cutaneous fungal pathogen, using stochastic character mapping and a database of Bd -inhibitory bacterial isolates. For both bacteria and fungi, we observed variation in community composition through time, between sites, and with salamander age and life stage. We further found that temporal trends in community composition were specific to each combination of salamander age, life stage, and lake. We found salamander skin to be selective for microbes, with many taxa disproportionately represented relative to the environment. Salamander skin appeared to select for predicted Bd -inhibitory bacteria, and we found a negative relationship between the relative abundances of predicted Bd -inhibitory bacteria and Bd . We hope these findings will assist in the conservation of amphibian species threatened by chytridiomycosis and other emerging diseases. 

Plant–insect interactions are common and important in basic and applied biology. Trait and genetic variation can affect the outcome and evolution of these interactions, but the relative contributions of plant and insect genetic variation and how these interact remain unclear and are rarely subject to assessment in the same experimental context. Here, we address this knowledge gap using a recent host-range expansion onto alfalfa by the Melissa blue butterfly. Common garden rearing experiments and genomic data show that caterpillar performance depends on plant and insect genetic variation, with insect genetics contributing to performance earlier in development and plant genetics later. Our models of performance based on caterpillar genetics retained predictive power when applied to a second common garden. Much of the plant genetic effect could be explained by heritable variation in plant phytochemicals, especially saponins, peptides, and phosphatidyl cholines, providing a possible mechanistic understanding of variation in the species interaction. We find evidence of polygenic, mostly additive effects within and between species, with consistent effects of plant genotype on growth and development across multiple butterfly species. Our results inform theories of plant–insect coevolution and the evolution of diet breadth in herbivorous insects and other host-specific parasites. 

Identifying the genetic basis of adaptation is a central goal of evolutionary biology. However, identifying genes and mutations affecting fitness remains challenging because a large number of traits and variants can influence fitness. Selected phenotypes can also be difficult to know a priori , complicating top–down genetic approaches for trait mapping that involve crosses or genome-wide association studies. In such cases, experimental genetic approaches, where one maps fitness directly and attempts to infer the traits involved afterwards, can be valuable. Here, we re-analyse data from a transplant experiment involving Timema stick insects, where five physically clustered single-nucleotide polymorphisms associated with cryptic body coloration were shown to interact to affect survival. Our analysis covers a larger genomic region than past work and revealed a locus previously not identified as associated with survival. This locus resides near a gene, Punch ( Pu ) , involved in pteridine pigments production, implying that it could be associated with an unmeasured coloration trait. However, by combining previous and newly obtained phenotypic data, we show that this trait is not eye or body coloration. We discuss the implications of our results for the discovery of traits, genes and mutations associated with fitness in other systems, as well as for supergene evolution. This article is part of the theme issue ‘Genetic basis of adaptation and speciation: from loci to causative mutations’. 

There is increasing evidence that genetic evolution can occur rapidly enough to affect the ecological dynamics of populations and communities ( 1 – 3 ). To better predict the future of ecosystems, it is necessary to understand how evolutionary changes within species influence and interact with ecological changes through processes known as “eco-evolutionary dynamics” ( 4 ). On page 70 of this issue, Barbour et al. ( 5 ) demonstrate that a gene affecting a plant’s resistance to herbivory also influences the persistence of the food web through the gene’s effect on plant growth (see the figure). Subsequent studies of natural selection in the wild can help explain how variations of such “keystone genes” can be maintained ( 6 , 7 ). The maintenance of genetic variation in keystone genes is required for eco-evolutionary dynamics to be perpetual rather than transient. 

Here we evaluate undergraduate student attitudes about science after each of three authentic research experiences in a semester of an introductory biology laboratory course at Utah State University. The three course-based research experiences (CUREs) vary in length and student freedom, and they cover different areas of biology. Students responded to the science attitude items of the CURE Survey. When compared to national data, our students faired similarly, and all students struggled with certain epistemic assumptions about science knowledge. As also seen in the national database, change in science attitude was slight and nonlinear. Student self confidence in what a career scientist is and in scientific process skills was the best predictor of scientific maturity, not the three CUREs or other aspects of students’ background. We discuss the slight positive and negative change in attitude we did influence, and we note that most students would choose to have another research experience.