A chromosome-scale genome assembly and evaluation of mtDNA variation in the willow leaf beetle Chrysomela aeneicollis

The leaf beetle Chrysomela aeneicollis has a broad geographic range across Western North America but is restricted to cool habitats at high elevations along the west coast. Central California populations occur only at high altitudes (2,700-3,500 m) where they are limited by reduced oxygen supply and recent drought conditions that are associated with climate change. Here, we report a chromosome-scale genome assembly alongside a complete mitochondrial genome and characterize differences among mitochondrial genomes along a latitudinal gradient over which beetles show substantial population structure and adaptation to fluctuating temperatures. Our scaffolded genome assembly consists of 21 linkage groups; one of which we identified as the X chromosome based on female/male whole genome sequencing coverage and orthology with Tribolium castaneum. We identified repetitive sequences in the genome and found them to be broadly distributed across all linkage groups. Using a reference transcriptome, we annotated a total of 12,586 protein-coding genes. We also describe differences in putative secondary structures of mitochondrial RNA molecules, which may generate functional differences important in adaptation to harsh abiotic conditions. We document substitutions at mitochondrial tRNA molecules and substitutions and insertions in the 16S rRNA region that could affect intermolecular interactions with products from the nuclear genome. This first chromosome-level reference genome will enable genomic research in this important model organism for understanding the biological impacts of climate change on montane insects.

Snow modulates winter energy use and cold exposure across an elevation gradient in a montane ectotherm

Snow insulates the soil from air temperature, decreasing winter cold stress and altering energy use for organisms that overwinter in the soil. As climate change alters snowpack and air temperatures, it is critical to account for the role of snow in modulating vulnerability to winter climate change. Along elevational gradients in snowy mountains, snow cover increases but air temperature decreases, and it is unknown how these opposing gradients impact performance and fitness of organisms overwintering in the soil. We developed experimentally validated ecophysiological models of cold and energy stress over the past decade for the montane leaf beetle Chrysomela aeneicollis, along five replicated elevational transects in the Sierra Nevada mountains in California. Cold stress peaks at mid-elevations, while high elevations are buffered by persistent snow cover, even in dry years. While protective against cold, snow increases energy stress for overwintering beetles, particularly at low elevations, potentially leading to mortality or energetic tradeoffs. Declining snowpack will predominantly impact mid-elevation populations by increasing cold exposure, while high elevation habitats may provide refugia as drier winters become more common.

Addressing alpine plant phylogeography using integrative distributional, demographic and coalescent modeling

Phylogeographic studies of alpine plants have evolved considerably in the last two decades from ad hoc interpretations of genetic data to statistical model-based approaches. In this review we outline the developments in alpine plant phylogeography focusing on the recent approach of integrative distributional, demographic and coalescent (iDDC) modeling. By integrating distributional data with spatially explicit demographic modeling and subsequent coalescent simulations, the history of alpine species can be inferred and long-standing hypotheses, such as species-specific responses to climate change or survival on nunataks during the last glacial maximum, can be efficiently tested as exemplified by available case studies. We also discuss future prospects and improvements of iDDC.

Mitonuclear mismatch alters performance and reproductive success in naturally introgressed populations of a montane leaf beetle

Coordination between nuclear and mitochondrial genomes is critical to metabolic processes underlying animals' ability to adapt to local environments, yet consequences of mitonuclear interactions have rarely been investigated in populations where individuals with divergent mitochondrial and nuclear genomes naturally interbreed. Genetic variation in the leaf beetle Chrysomela aeneicollis was assessed along a latitudinal thermal gradient in California's Sierra Nevada. Variation at mitochondrial cytochrome oxidase II (COII) and the nuclear gene phosphoglucose isomerase (PGI) shows concordance and was significantly greater along a 65 km transect than 10 other loci. STRUCTURE analyses using neutral loci identified a southern and northern subpopulation, which interbreed in the central drainage Bishop Creek. COII and PGI were used as indicators of mitochondrial and nuclear genetic variation in field and laboratory experiments conducted on beetles from this admixed population. Fecundity, larval development rate, running speed and male mating frequency were higher for beetles with geographically "matched" than "mismatched" mitonuclear genotypes. Effects of mitonuclear mismatch were largest for individuals with northern nuclear genotypes possessing southern mitochondria and were most pronounced after heat treatment or at high elevation. These findings suggest that mitonuclear incompatibility diminishes performance and reproductive success in nature, effects that could intensify at environmental extremes.

Two disjunct Pleistocene populations and anisotropic postglacial expansion shaped the current genetic structure of the relict plant Amborella trichopoda

Past climate fluctuations shaped the population dynamics of organisms in space and time, and have impacted their present intra-specific genetic structure. Demo-genetic modelling allows inferring the way past demographic and migration dynamics have determined this structure. Amborella trichopoda is an emblematic relict plant endemic to New Caledonia, widely distributed in the understory of non-ultramafic rainforests. We assessed the influence of the last glacial climates on the demographic history and the paleo-distribution of 12 Amborella populations covering the whole current distribution. We performed coalescent genetic modelling of these dynamics, based on both whole-genome resequencing and microsatellite genotyping data. We found that the two main genetic groups of Amborella were shaped by the divergence of two ancestral populations during the last glacial maximum. From 12,800 years BP, the South ancestral population has expanded 6.3-fold while the size of the North population has remained stable. Recent asymmetric gene flow between the groups further contributed to the phylogeographical pattern. Spatially explicit coalescent modelling allowed us to estimate the location of ancestral populations with good accuracy (< 22 km) and provided indications regarding the mid-elevation pathways that facilitated post-glacial expansion.

Contrasting genetic patterns between two coexisting Eleutherococcus species in northern China

Climate oscillations are the key factors to understand the patterns in modern biodiversity. East Asia harbors the most diverse temperate flora, largely because an extensive terrestrial ice cap was absent during repeated Pleistocene glaciation-interglacial cycles. Comparing the demographic histories of species that are codistributed and are close relatives may provide insight into how the process of climate change influences species ranges. In this study, we compared the spatial genetic structure and demographic histories of two coexisting Eleutherococcus species, Eleutherococcus senticosus and E. sessiliflorus. Both species are distributed in northern China, regions that are generally considered to be sensitive to climatic fluctuations. These regions once hosted temperate forest, but this temperate forest was replaced by tundra and taiga forest during the Last Glacial Maximum (LGM), according to pollen records. Using three chloroplast DNA fragments, we assessed the genetic structure of 20 and 9 natural populations of E. senticosus and E. sessiliflorus, respectively. Extremely contrasting genetic patterns were found between the two species; E. sessiliflorus had little genetic variation, whereas E. senticosus had considerably higher levels of genetic variation (15 haplotypes). We speculated that a recent severe bottleneck may have resulted in the extremely low genetic diversity in E. sessiliflorus. In E. senticosus, populations in Northeast China (NEC) harbored all of the haplotypes found in this species and included private haplotypes. The populations in NEC had higher levels of genetic diversity than did those from North China (NC). Therefore, we suggest that both the NC and NEC regions can sustain LGM refugia and that lineage admixture from multiple refugia took place after the LGM elevated the local genetic diversity in NEC. In NEC, multiple genetic hot spots were found in the Changbai Mountains and the Xiaoxing'an Range, which implied that multiple locations in NEC may sustain LGM refugia, even in the Xiaoxing'an Range.

Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes

PREMISE OF THE STUDY

Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa.

METHODS

We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change.

KEY RESULTS

We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes.

CONCLUSIONS

To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning.