Demographic inference provides insights into the extirpation and ecological dominance of eusocial snapping shrimps

Although eusocial animals often achieve ecological dominance in the ecosystems where they occur, many populations are unstable, resulting in local extinction. Both patterns may be linked to the characteristic demography of eusocial species-high reproductive skew and reproductive division of labor support stable effective population sizes that make eusocial groups more competitive in some species, but also lower effective population sizes that increase susceptibility to population collapse in others. Here, we examine the relationship between demography and social organization in Synalpheus snapping shrimps, a group in which eusociality has evolved recently and repeatedly. We show using coalescent demographic modelling that eusocial species have had lower but more stable effective population sizes across 100,000 generations. Our results are consistent with the idea that stable population sizes may enable competitive dominance in eusocial shrimps, but they also suggest that recent population declines are likely caused by eusocial shrimps' heightened sensitivity to environmental changes, perhaps as a result of their low effective population sizes and localized dispersal. Thus, although the unique life histories and demography of eusocial shrimps have likely contributed to their persistence and ecological dominance over evolutionary timescales, these social traits may also make them vulnerable to contemporary environmental change.

Recent advances in population and quantitative genomics of honey bees

The increase in the availability of individual Apis mellifera genomes has resulted in significant progress toward understanding the evolution and adaptation of the honey bee. These efforts have identified new subspecies, evolutionary lineages, and a significant number of genes involved with adaptations and colony-level quantitative traits. Many studies have also developed genetic assays that are being used to monitor the movement and admixture of honey bee populations. These resources are valuable for conservation and breeding programs that seek to improve the economic value of colonies or preserve locally adapted populations and subspecies. This review provides a brief discussion on how population and quantitative genomic studies has improved our understanding of the honey bee.

Insects with similar social complexity show convergent patterns of adaptive molecular evolution

Eusociality has independently evolved multiple times in the hymenoptera, but the patterns of adaptive molecular evolution underlying the evolution and elaboration of eusociality remain uncertain. Here, we performed a population genomics study of primitively eusocial Polistes (paper wasps), and compared their patterns of molecular evolution to two social bees; Bombus (bumblebees), and Apis (honey bees). This species triad allowed us to study molecular evolution across a gradient of social complexity (Polistes < Bombus < Apis) and compare species pairs that have similar (i.e. Polistes and Bombus) or different (i.e. Polistes and Apis) life histories, while controlling for phylogenetic distance. We found that regulatory genes have high levels of positive selection in Polistes; consistent with the prediction that adaptive changes in gene regulation are important during early stages of social evolution. Polistes and Bombus exhibit greater similarity in patterns of adaptive evolution including greater overlap of genes experiencing positive selection, and greater positive selection on queen-biased genes. Our findings suggest that either adaptive evolution of a few key genes underlie the evolution of simpler forms of eusociality, or that the initial stages of social evolution lead to selection on a few key traits orchestrated by orthologous genes and networks.

Genes and genomic processes underpinning the social lives of ants

The >15000 ant species are all highly social and show great variation in colony organization, complexity and behavior. The mechanisms by which such sociality evolved, as well as those underpinning the elaboration of ant societies since their ∼140 million year old common ancestor, have long been pondered. Here, we review recent insights generated using various genomic approaches. This includes understanding the molecular mechanisms underlying caste differentiation and the diversity of social structures, studying the impact of eusociality on genomic evolutionary rates, and investigating gene expression changes associated with differences in lifespan between castes. Furthermore, functional studies involving RNAi and CRISPR have recently been successfully applied to ants, opening the door to exciting research that promises to revolutionize the understanding of the evolution and diversification of social living.

Cryptic genetic variation in an inbreeding and cosmopolitan pest, Xylosandrus crassiusculus, revealed using ddRADseq

Each year new exotic species are transported across the world through global commerce, causing considerable economic and ecological damage. An important component of managing invasion pathways is to identify source populations. Some of the most widespread exotic species are haplodiploid ambrosia beetles. The ability to mate with siblings (inbreed) and their transportable food source (symbiotic fungus) have enabled them to colonize most of the world and become pests of plant nurseries, lumber, and forests. One of the fastest spreading ambrosia beetles is Xylosandrus crassiusculus. In order to discover the source populations of this globally invasive species, track its movement around the world, and test biogeographical scenarios, we combined restriction site-associated DNA sequencing (RADseq) with comprehensive sampling across the species native and introduced range. From 1,365 genotyped SNP loci across 198 individuals, we determined that in its native range, X. crassiusculus is comprised of a population in Southeast Asia that includes mainland China, Thailand, and Taiwan, and a second island population in Japan. North America and Central America were colonized from the island populations, while Africa and Oceania were colonized from the mainland Asia, and Hawaii was colonized by both populations. Populations of X. crassiusculus in North America were genetically diverse and highly structured, suggesting (1) numerous, repeated introductions; (2) introduction of a large founding population; or (3) both scenarios with higher than expected outcrossing. X. crassiusculus, other wood-boring insects, and indeed many other pests with unusual genetic structure continue to spread around the world. We show that contemporary genetic methods offer a powerful tool for understanding and preventing pathways of future biosecurity threats.

Queens and Workers Contribute Differently to Adaptive Evolution in Bumble Bees and Honey Bees

Eusociality represents a major transition in evolution and is typified by cooperative brood care and reproductive division of labor between generations. In bees, this division of labor allows queens and workers to phenotypically specialize. Worker traits associated with helping are thought to be crucial to the fitness of a eusocial lineage, and recent studies of honey bees (genus Apis) have found that adaptively evolving genes often have worker-biased expression patterns. It is unclear however if worker-biased genes are disproportionately acted on by strong positive selection in all eusocial insects. We undertook a comparative population genomics study of bumble bees (Bombus) and honey bees to quantify natural selection on queen- and worker-biased genes across two levels of social complexity. Despite sharing a common eusocial ancestor, genes, and gene groups with the highest levels of positive selection were often unique within each genus, indicating that life history and the environment, but not sociality per se, drives patterns of adaptive molecular evolution. We uncovered differences in the contribution of queen- and worker-biased genes to adaptive evolution in bumble bees versus honey bees. Unlike honey bees, where worker-biased genes are enriched for signs of adaptive evolution, genes experiencing positive selection in bumble bees were predominately expressed by reproductive foundresses during the initial solitary-founding stage of colonies. Our study suggests that solitary founding is a major selective pressure and that the loss of queen totipotency may cause a change in the architecture of selective pressures upon the social insect genome.

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

This workflow allows novice researchers to leverage advanced computational resources such as cloud computing to carry out pairwise comparative transcriptomics. It also serves as a primer for biologists to develop data scientist computational skills, e.g. executing bash commands, visualization and management of large data sets. All command line code and further explanations of each command or step can be found on the wiki (https://wiki.cyverse.org/wiki/x/dgGtAQ). The Discovery Environment and Atmosphere platforms are connected together through the CyVerse Data Store. As such, once the initial raw sequencing data has been uploaded there is no more need to transfer large data files over an Internet connection, minimizing the amount of time needed to conduct analyses. This protocol is designed to analyze only two experimental treatments or conditions. Differential gene expression analysis is conducted through pairwise comparisons, and will not be suitable to test multiple factors. This workflow is also designed to be manual rather than automated. Each step must be executed and investigated by the user, yielding a better understanding of data and analytical outputs, and therefore better results for the user. Once complete, this protocol will yield de novo assembled transcriptome(s) for underserved (non-model) organisms without the need to map to previously assembled reference genomes (which are usually not available in underserved organism). These de novo transcriptomes are further used in pairwise differential gene expression analysis to investigate genes differing between two experimental conditions. Differentially expressed genes are then functionally annotated to understand the genetic response organisms have to experimental conditions. In total, the data derived from this protocol is used to test hypotheses about biological responses of underserved organisms.

Understanding the coevolutionary dynamics of mutualism with population genomics

Decades of research on the evolution of mutualism has generated a wealth of possible ways whereby mutually beneficial interactions between species persist in spite of the apparent advantages to individuals that accept the benefits of mutualism without reciprocating - but identifying how any particular empirical system is stabilized against cheating remains challenging. Different hypothesized models of mutualism stability predict different forms of coevolutionary selection, and emerging high-throughput sequencing methods allow examination of the selective histories of mutualism genes and, thereby, the form of selection acting on those genes. Here, I review the evolutionary theory of mutualism stability and identify how differing models make contrasting predictions for the population genomic diversity and geographic differentiation of mutualism-related genes. As an example of the possibilities offered by genomic data, I analyze genes with roles in the symbiosis of Medicago truncatula and nitrogen-fixing rhizobial bacteria, the first classic mutualism in which extensive genomic resources have been developed for both partners. Medicago truncatula symbiosis genes, as a group, differ from the rest of the genome, but they vary in the form of selection indicated by their diversity and differentiation - some show signs of selection expected from roles in sanctioning noncooperative symbionts, while others show evidence of balancing selection expected from coevolution with symbiont signaling factors. I then assess the current state of development for similar resources in other mutualistic interactions and look ahead to identify ways in which modern sequencing technology can best inform our understanding of mutualists and mutualism.