The liver plays a major role in regulating metabolic homeostasis and is vital for nutrient metabolism. Identifying the genetic factors regulating these processes could lead to a greater understanding of how liver function responds to a high-fat diet and how that response may influence susceptibilities to obesity and metabolic syndrome. In this study we examine differences in hepatic gene expression between the LG/J and SM/J inbred mouse strains and how gene expression in these strains is affected by high-fat diet. LG/J and SM/J are known to differ in their responses to a high-fat diet for a variety of obesity- and diabetes-related traits, with the SM/J strain exhibiting a stronger phenotypic response to diet.

Bluegill sunfish (Lepomis macrochirus) are one of the classic systems for studying male alternative reproductive tactics (ARTs) in teleost fishes. In this species, there are two distinct life histories: parental and cuckolder, encompassing three reproductive tactics, parental, satellite, and sneaker. The parental life history is fixed, whereas individuals who enter the cuckolder life history transition from sneaker to satellite tactic as they grow. For this study, we used RNAseq to characterize the brain transcriptome of the three male tactics and females during spawning to identify gene ontology (GO) categories and potential candidate genes associated with each tactic. We found that sneaker males had higher levels of gene expression differentiation compared to the other two male tactics. Sneaker males also had higher expression in ionotropic glutamate receptor genes, specifically AMPA receptors, compared to other males, which may be important for increased spatial working memory while attempting to cuckold parental males at their nests. Larger differences in gene expression also occurred among male tactics than between males and females. We found significant expression differences in several candidate genes that were previously identified in other species with ARTs and suggest a previously undescribed role for cAMP-responsive element modulator (crem) in influencing parental male behaviors during spawning.

Maintenance of genetic and phenotypic diversity is widely recognized as an important conservation priority, yet managers often lack basic information about spatial patterns of population structure and its relationship with habitat heterogeneity and species movement within it. To address this knowledge gap, we focused on the economically and ecologically prominent yellow perch (Perca flavescens). In the Lake Michigan basin, yellow perch reside in nearshore Lake Michigan, including drowned river mouths (DRMs)—protected, lake‐like habitats that link tributaries to Lake Michigan. The goal of this study was to examine the extent that population structure is associated with Great Lakes connected habitats (i.e., DRMs) in a mobile fish species using yellow perch as a model. Specifically, we tested whether DRMs and eastern Lake Michigan constitute distinct genetic stocks of yellow perch, and if so, whether those stocks migrate between the two connected habitats throughout the year. To do so, we genotyped yellow perch at 14 microsatellite loci collected from 10 DRMs in both deep and littoral habitats during spring, summer, and autumn and two nearshore sites in Lake Michigan (spring and autumn) during 2015–2016 and supplemented our sampling with fish collected in 2013. We found that yellow perch from littoral‐DRM habitats were genetically distinct from fish captured in nearshore Lake Michigan. Our data also suggested that Lake Michigan yellow perch likely use deep‐DRM habitats during autumn. Further, we found genetic structuring among DRMs. These patterns support hypotheses of fishery managers that yellow perch seasonally migrate to and from Lake Michigan, yet, interestingly, these fish do not appear to interbreed with littoral fish despite occupying the same DRM. We recommend that fisheries managers account for this complex population structure and movement when setting fishing regulations and assessing the effects of harvest in Lake Michigan.

Characterizing the diet of imperiled species using minimally invasive methods is crucial to understanding their ecology and conservation requirements. Here, we apply a DNA metabarcoding approach to study the diet of the eastern massasauga rattlesnake (Sistrurus catenatus), a Federally Threatened snake found throughout the Great Lakes region. Eighty‐three fecal samples collected across 10 different massasauga populations located in Michigan, USA, were sequenced, with 70 samples containing prey DNA. We used universal metazoan primers and developed a host‐specific oligonucleotide blocker to characterize their diet. We identified at least 12 different prey species, with eastern massasaugas exhibiting opportunistic feeding and a strong preference towards small mammals. Meadow voles (Microtus pennsylvanicus) were the most common prey item (70% of diet) followed by the northern short‐tailed shrew (Blarina brevicauda) and masked shrew (Sorex cinereus; 15.7% of diet each), along with occasional bird and snake prey. Adult individuals exhibited a more generalized diet, consuming a larger number of prey taxa on average. Younger snakes consumed a smaller variety of prey items and tended to consume smaller‐sized mammals such as masked shrews (Sorex cinereus) and northern short‐tailed shrews (Blarina brevicauda). We conclude that small mammals are a crucial part of eastern massasauga rattlesnake diet and recommend this be taken into consideration when conservation strategies are developed. The methods developed in this study can be applied to other reptile species, providing an accurate, minimally invasive, and thorough diet assessment for at‐risk reptile species.

During the last few decades, biologists have made remarkable progress in understanding the fundamental processes that shape life. But despite the unprecedented level of knowledge now available, large gaps still remain in our understanding of the complex interplay of eco-evolutionary mechanisms across scales of life. Rapidly changing environments on Earth provide a pressing need to understand the potential implications of eco-evolutionary dynamics, which can be achieved by improving existing eco-evolutionary models and fostering convergence among the sub-fields of biology. We propose a new, data-driven approach that harnesses our knowledge of the functioning of biological systems to expand current conceptual frameworks and develop corresponding models that can more accurately represent and predict future eco-evolutionary outcomes. We suggest a roadmap toward achieving this goal. This long-term vision will move biology in a direction that can wield these predictive models for scientific applications that benefit humanity and increase the resilience of natural biological systems. We identify short, medium, and long-term key objectives to connect our current state of knowledge to this long-term vision, iteratively progressing across three stages: (1) utilizing knowledge of biological systems to better inform eco-evolutionary models, (2) generating models with more accurate predictions, and (3) applying predictive models to benefit the biosphere. Within each stage, we outline avenues of investigation and scientific applications related to the timescales over which evolution occurs, the parameter space of eco-evolutionary processes, and the dynamic interactions between these mechanisms. The ability to accurately model, monitor, and anticipate eco-evolutionary changes would be transformational to humanity’s interaction with the global environment, providing novel tools to benefit human health, protect the natural world, and manage our planet’s biosphere.

Coastal sand dunes are dynamic ecosystems with elevated levels of disturbance and are highly susceptible to plant invasions. One invasive plant that is of concern to the Great Lakes system is Gypsophila paniculata L. (perennial baby’s breath). The presence of G. paniculata negatively impacts native species and has the potential to alter ecosystem dynamics. Our research goals were to (1) estimate the genetic structure of invasive G. paniculata along the Michigan dune system and (2) identify landscape features that influence gene flow in this area. We analyzed 12 populations at 14 nuclear and two chloroplast microsatellite loci. We found strong genetic structure among populations (global F_ST = 0.228), and pairwise comparisons among all populations yielded significant F_ST values. Results from clustering analysis via STRUCTURE and discriminant analysis of principal components (DAPC) suggest two main genetic clusters that are separated by the Leelanau Peninsula, and this is supported by the distribution of chloroplast haplotypes. Land cover and topography better explained pairwise genetic distances than geographic distance alone, suggesting that these factors influence the genetic distribution of populations within the dunes system. Together, these data aid in our understanding of how invasive populations move through the dune landscape, providing valuable information for managing the spread of this species.