Population genetics of a recent range expansion and subsequent loss of migration in monarch butterflies

Next-generation data filtering in the genomics era

Genomic data are ubiquitous across disciplines, from agriculture to biodiversity, ecology, evolution and human health. However, these datasets often contain noise or errors and are missing information that can affect the accuracy and reliability of subsequent computational analyses and conclusions. A key step in genomic data analysis is filtering - removing sequencing bases, reads, genetic variants and/or individuals from a dataset - to improve data quality for downstream analyses. Researchers are confronted with a multitude of choices when filtering genomic data; they must choose which filters to apply and select appropriate thresholds. To help usher in the next generation of genomic data filtering, we review and suggest best practices to improve the implementation, reproducibility and reporting standards for filter types and thresholds commonly applied to genomic datasets. We focus mainly on filters for minor allele frequency, missing data per individual or per locus, linkage disequilibrium and Hardy-Weinberg deviations. Using simulated and empirical datasets, we illustrate the large effects of different filtering thresholds on common population genetics statistics, such as Tajima's D value, population differentiation (FST), nucleotide diversity (π) and effective population size (Ne).

Boundary Effects Cause False Signals of Range Expansions in Population Genomic Data

Studying range expansions is central for understanding genetic variation through space and time as well as for identifying refugia and biological invasions. Range expansions are characterized by serial founder events causing clines of decreasing genetic diversity away from the center of origin and asymmetries in the two-dimensional allele frequency spectra. These asymmetries, summarized by the directionality index (ψ), are sensitive to range expansions and persist for longer than clines in genetic diversity. In continuous and finite meta-populations, genetic drift tends to be stronger at the edges of the species distribution in equilibrium populations and populations undergoing range expansions alike. Such boundary effects are expected to affect geographic patterns in genetic diversity and ψ. Here we demonstrate that boundary effects cause high false positive rates in equilibrium meta-populations when testing for range expansions. In the simulations, the absolute value of ψ (|ψ|) in equilibrium data sets was proportional to the fixation index (FST). By fitting signatures of range expansions as a function of ɛ |ψ|/FST and geographic clines in ψ, strong evidence for range expansions could be detected in data from a recent rapid invasion of the cane toad, Rhinella marina, in Australia, but not in 28 previously published empirical data sets from Australian scincid lizards that were significant for the standard range expansion tests. Thus, while clinal variation in ψ is still the most sensitive statistic to range expansions, to detect true signatures of range expansions in natural populations, its magnitude needs to be considered in relation to the overall levels of genetic structuring in the data.

Considerable genetic diversity and structure despite narrow endemism and limited ecological specialization in the Hayden's ringlet, Coenonympha haydenii

Understanding the processes that underlie the development of population genetic structure is central to the study of evolution. Patterns of genetic structure, in turn, can reveal signatures of isolation by distance (IBD), barriers to gene flow, or even the genesis of speciation. However, it is unclear how severe range restriction might impact the processes that dominate the development of genetic structure. In narrow endemic species, is population structure likely to be adaptive in nature, or rather the result of genetic drift? In this study, we investigated patterns of genetic diversity and structure in the narrow endemic Hayden's ringlet butterfly. Specifically, we asked to what degree genetic structure in the Hayden's ringlet can be explained by IBD, isolation by resistance (IBR) (in the form of geographic or ecological barriers to migration between populations), and isolation by environment (in the form of differences in host plant availability and preference). We employed a genotyping-by-sequencing (GBS) approach coupled with host preference assays, Bayesian modelling, and population genomic analyses to answer these questions. Our results suggest that despite their restricted range, levels of genetic diversity in the Hayden's ringlet are comparable to those seen in more widespread butterfly species. Hayden's ringlets showed a strong preference for feeding on grasses relative to sedges, but neither larval preference nor potential host availability at sampling sites correlated with genetic structure. We conclude that geography, in the form of IBR and simple IBD, was the major driver of contemporary patterns of differentiation in this narrow endemic species.

Widespread Deviant Patterns of Heterozygosity in Whole-Genome Sequencing Due to Autopolyploidy, Repeated Elements, and Duplication

Most population genomic tools rely on accurate single nucleotide polymorphism (SNP) calling and filtering to meet their underlying assumptions. However, genomic complexity, resulting from structural variants, paralogous sequences, and repetitive elements, presents significant challenges in assembling contiguous reference genomes. Consequently, short-read resequencing studies can encounter mismapping issues, leading to SNPs that deviate from Mendelian expected patterns of heterozygosity and allelic ratio. In this study, we employed the ngsParalog software to identify such deviant SNPs in whole-genome sequencing (WGS) data with low (1.5×) to intermediate (4.8×) coverage for four species: Arctic Char (Salvelinus alpinus), Lake Whitefish (Coregonus clupeaformis), Atlantic Salmon (Salmo salar), and the American Eel (Anguilla rostrata). The analyses revealed that deviant SNPs accounted for 22% to 62% of all SNPs in salmonid datasets and approximately 11% in the American Eel dataset. These deviant SNPs were particularly concentrated within repetitive elements and genomic regions that had recently undergone rediploidization in salmonids. Additionally, narrow peaks of elevated coverage were ubiquitous along all four reference genomes, encompassed most deviant SNPs, and could be partially associated with transposons and tandem repeats. Including these deviant SNPs in genomic analyses led to highly distorted site frequency spectra, underestimated pairwise FST values, and overestimated nucleotide diversity. Considering the widespread occurrence of deviant SNPs arising from a variety of sources, their important impact in estimating population parameters, and the availability of effective tools to identify them, we propose that excluding deviant SNPs from WGS datasets is required to improve genomic inferences for a wide range of taxa and sequencing depths.

Migration genetics take flight: genetic and genomic insights into monarch butterfly migration

Monarch butterflies have emerged as a model system in migration genetics. Despite inherent challenges associated with studying the integrative phenotypes that characterize migration, recent research has highlighted genes and transcriptional networks underlying aspects of the monarch's migratory syndrome. Circadian clock genes and the vitamin A synthesis pathway regulate reproductive diapause initiation, while diapause termination appears to involve calcium and insulin signaling. Comparative approaches have highlighted genes that distinguish migratory and nonmigratory monarch populations, as well as genes associated with natural variation in propensity to initiate diapause. Population genetic techniques demonstrate that seasonal migration can collapse patterns of spatial structure at continental scales, whereas loss of migration can drive differentiation between even nearby populations. Finally, population genetics can be applied to reconstruct the monarch's evolutionary history and search for contemporary demographic changes, which can provide relevant context for understanding recently observed declines in overwintering North American monarch numbers.

Reduced-representation libraries in insect genetics

Genotyping-by-sequencing of reduced-representation libraries has ushered in an era where genome-wide data can be gotten for any species. Here, I review research on this topic during the last two years, report meta-analysis of the results, and discuss analysis methods and issues. Scanning the literature from 2021 to 2022 identified 21 papers, the majority of which were on population differences, including local adaptation and migration, but several papers were on genetic maps and their use in assembly scaffolding or analysis of quantitative trait loci, on the origin of incursions of pest insects, or on infection rates of a pathogen in a disease vector. The research reviewed includes 33 species from 25 families and 11 orders. Meta-analysis showed that less than 16%, and most often, less than 1% of the genome was implicated in local adaptation and that the number of adaptive loci correlated with genetic divergence among populations.

Extent and impacts of winter breeding in the North American monarch butterfly

Since the 1960s, scientists have observed the North American monarch butterfly (Danaus plexippus) continuing reproductive activities past the fall migration and into the winter months when the climate is mild. Recent work suggests that small populations of winter breeding monarchs are present in western and southeastern USA, as well as northwestern Mexico, with new winter breeding populations forming in areas where non-native milkweeds are planted. The year-round presence of milkweed plants and temperatures suitable for immature monarch development are vital factors allowing for winter breeding. Non-native milkweeds, in conjunction with novel barriers to migration, are likely contributing to the rise in winter breeding behavior. Warmer climates are already impacting milkweed phenology and range, possibly favoring winter breeding behavior. Similar pressures but different implications are expected for eastern and western winter breeding monarchs given the differences in the migration ecology, milkweed species, and climate changes in the two regions.

Complexity, humility, and action: a current perspective on monarchs in Western North America

Recent studies have continued to shed light on the ecology of monarch butterflies (Danaus plexippus) in western North America. These studies have documented a declining overwintering population over several decades, punctuated by unexpected variability in recent years. Understanding this variability will require grappling with the spatial and temporal heterogeneity of resources and risks presented to western monarchs throughout their annual life cycle. Recent changes in the western monarch population further illustrate how interacting global change drivers can create complex causes and consequences in this system. The complexity of this system should inspire humility. However, even recognizing the limits of our current understanding, there is enough scientific common ground to take some conservation actions now.

Temporal matches between monarch butterfly and milkweed population changes over the past 25,000 years

In intimate ecological interactions, the interdependency of species may result in correlated demographic histories. For species of conservation concern, understanding the long-term dynamics of such interactions may shed light on the drivers of population decline. Here, we address the demographic history of the monarch butterfly, Danaus plexippus, and its dominant host plant, the common milkweed Asclepias syriaca (A. syriaca), using broad-scale sampling and genomic inference. Because genetic resources for milkweed have lagged behind those for monarchs, we first release a chromosome-level genome assembly and annotation for common milkweed. Next, we show that despite its enormous geographic range across eastern North America, A. syriaca is best characterized as a single, roughly panmictic population. Using approximate Bayesian computation with random forests (ABC-RF), a machine learning method for reconstructing demographic histories, we show that both monarchs and milkweed experienced population expansion during the most recent recession of North American glaciers 10,000-20,000 years ago. Our data also identify concurrent population expansions in both species during the large-scale clearing of eastern forests (∼200 years ago). Finally, we find no evidence that either species experienced a reduction in effective population size over the past 75 years. Thus, the well-documented decline of monarch abundance over the past 40 years is not visible in our genomic dataset, reflecting a possible mismatch of the overwintering census population to effective population size in this species.