Co-expression gene networks and machine-learning algorithms unveil a core genetic toolkit for reproductive division of labour in rudimentary insect societies

The evolution of eusociality requires that individuals forgo some or all their own reproduction to assist the reproduction of others in their group, such as a primary egg-laying queen. A major open question is how genes and genetic pathways sculpt the evolution of eusociality, especially in rudimentary forms of sociality—those with smaller cooperative nests when compared with species such as honeybees that possess large societies. We lack comprehensive comparative studies examining shared patterns and processes across multiple social lineages. Here we examine the mechanisms of molecular convergence across two lineages of bees and wasps exhibiting such rudimentary societies. These societies consist of few individuals and their life histories range from facultative to obligately social. Using six species across four independent origins of sociality, we conduct a comparative meta-analysis of publicly available transcriptomes. Standard methods detected little similarity in patterns of differential gene expression in brain transcriptomes among reproductive and non-reproductive individuals across species. By contrast, both supervised machine learning and consensus co-expression network approaches uncovered sets of genes with conserved expression patterns among reproductive and non-reproductive phenotypes across species. These sets overlap substantially, and may comprise a shared genetic “toolkit” for sociality across the distantly related taxa of bees and wasps and independently evolved lineages of sociality. We also found many lineage-specific genes and co-expression modules associated with social phenotypes and possible signatures of shared life-history traits. These results reveal how taxon-specific molecular mechanisms complement a core toolkit of molecular processes in sculpting traits related to the evolution of eusociality

Using citizen science data to assess the population genetic structure of the common yellowjacket wasp, Vespula vulgaris

Monitoring insect genetic diversity and population structure has never been more important to manage the biodiversity crisis. Citizen science has become an increasingly popular tool to gather ecological data affordably across a wide range of spatial and temporal scales. To date, most insect-related citizen science initiatives have focused on occurrence and abundance data. Here, we show that poorly preserved insect samples collected by citizen scientists can yield population genetic information, providing new insights into population connectivity, genetic diversity and dispersal behaviour of little-studied insects. We analysed social wasps collected by participants of the Big Wasp Survey, a citizen science project that aims to map the diversity and distributions of vespine wasps in the UK. Although Vespula vulgaris is a notorious invasive species around the world, it remains poorly studied in its native range. We used these data to assess the population genetic structure of the common yellowjacket V. vulgaris at different spatial scales. We found a single, panmictic population across the UK with little evidence of population genetic structuring; the only possible limit to gene flow is the Irish sea, resulting in significant differentiation between the Northern Ireland and mainland UK populations. Our results suggest that queens disperse considerable distances from their natal nests to found new nests, resulting in high rates of gene flow and thus little differentiation across the landscape. Citizen science data has made it feasible to perform this study, and we hope that it will encourage future projects to adopt similar practices in insect population monitoring

Putting hornets on the genomic map

Hornets are the largest of the social wasps, and are important regulators of insect populations in their native ranges. Hornets are also very successful as invasive species, with often devastating economic, ecological and societal effects. Understanding why these wasps are such successful invaders is critical to managing future introductions and minimising impact on native biodiversity. Critical to the management toolkit is a comprehensive genomic resource for these insects. Here we provide the annotated genomes for two hornets, Vespa crabro and Vespa velutina. We compare their genomes with those of other social Hymenoptera, including the northern giant hornet Vespa mandarinia. The three hornet genomes show evidence of selection pressure on genes associated with reproduction, which might facilitate the transition into invasive ranges. Vespa crabro has experienced positive selection on the highest number of genes, including those putatively associated with molecular binding and olfactory systems. Caste-specific brain transcriptomic analysis also revealed 133 differentially expressed genes, some of which are associated with olfactory functions. This report provides a spring-board for advancing our understanding of the evolution and ecology of hornets, and opens up opportunities for using molecular methods in the future management of both native and invasive populations of these over-looked insects

Sequenceserver: A Modern Graphical User Interface for Custom BLAST Databases

Comparing newly obtained and previously known nucleotide and amino-acid sequences underpins modern biological research. BLAST is a well-established tool for such comparisons but is challenging to use on new data sets. We combined a user-centric design philosophy with sustainable software development approaches to create Sequenceserver, a tool for running BLAST and visually inspecting BLAST results for biological interpretation. Sequenceserver uses simple algorithms to prevent potential analysis errors and provides flexible text-based and visual outputs to support researcher productivity. Our software can be rapidly installed for use by individuals or on shared servers

BWS_Microsatellite_Data.csv

This dataset contains genetic information for 383 Vespula vulgaris individuals genotyped at up to 14 loci, as part of a study on the population genetic structure of the species across the UK, using samples collected by citizen scientists through the project the Big Wasp Survey (https://www.bigwaspsurvey.org/).  This file contains: - Sample name  - Trap ID (each trap is unique) - Method (DNA extraction method used) - Cluster number (see study) - Region ID (see study) - Year collected - Genotype data - Latitude/Longitude data  Missing values are NA.  </p

Co-expression Gene Networks and Machine-learning Algorithms Unveil a Core Genetic Toolkit for Reproductive Division of Labour in Rudimentary Insect Societies

The evolution of eusociality requires that individuals forgo some or all their own reproduction to assist the reproduction of others in their group, such as a primary egg-laying queen. A major open question is how genes and genetic pathways sculpt the evolution of eusociality, especially in rudimentary forms of sociality—those with smaller cooperative nests when compared with species such as honeybees that possess large societies. We lack comprehensive comparative studies examining shared patterns and processes across multiple social lineages. Here we examine the mechanisms of molecular convergence across two lineages of bees and wasps exhibiting such rudimentary societies. These societies consist of few individuals and their life histories range from facultative to obligately social. Using six species across four independent origins of sociality, we conduct a comparative meta-analysis of publicly available transcriptomes. Standard methods detected little similarity in patterns of differential gene expression in brain transcriptomes among reproductive and non-reproductive individuals across species. By contrast, both supervised machine learning and consensus co-expression network approaches uncovered sets of genes with conserved expression patterns among reproductive and non-reproductive phenotypes across species. These sets overlap substantially, and may comprise a shared genetic “toolkit” for sociality across the distantly related taxa of bees and wasps and independently evolved lineages of sociality. We also found many lineage-specific genes and co-expression modules associated with social phenotypes and possible signatures of shared life-history traits. These results reveal how taxon-specific molecular mechanisms complement a core toolkit of molecular processes in sculpting traits related to the evolution of eusociality.This article is published as Emeline Favreau, Katherine S Geist, Christopher D R Wyatt, Amy L Toth, Seirian Sumner, Sandra M Rehan, Co-expression Gene Networks and Machine-learning Algorithms Unveil a Core Genetic Toolkit for Reproductive Division of Labour in Rudimentary Insect Societies, Genome Biology and Evolution, Volume 15, Issue 1, January 2023, evac174, https://doi.org/10.1093/gbe/evac174. Posted with permission.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited

Using citizen science data to assess the population genetic structure of the common yellowjacket wasp, Vespula vulgaris.

Funder: Royal Entomological Society; doi: http://dx.doi.org/10.13039/100013849Monitoring insect genetic diversity and population structure has never been more important to manage the biodiversity crisis. Citizen science has become an increasingly popular tool to gather ecological data affordably across a wide range of spatial and temporal scales. To date, most insect-related citizen science initiatives have focused on occurrence and abundance data. Here, we show that poorly preserved insect samples collected by citizen scientists can yield population genetic information, providing new insights into population connectivity, genetic diversity and dispersal behaviour of little-studied insects. We analysed social wasps collected by participants of the Big Wasp Survey, a citizen science project that aims to map the diversity and distributions of vespine wasps in the UK. Although Vespula vulgaris is a notorious invasive species around the world, it remains poorly studied in its native range. We used these data to assess the population genetic structure of the common yellowjacket V. vulgaris at different spatial scales. We found a single, panmictic population across the UK with little evidence of population genetic structuring; the only possible limit to gene flow is the Irish sea, resulting in significant differentiation between the Northern Ireland and mainland UK populations. Our results suggest that queens disperse considerable distances from their natal nests to found new nests, resulting in high rates of gene flow and thus little differentiation across the landscape. Citizen science data has made it feasible to perform this study, and we hope that it will encourage future projects to adopt similar practices in insect population monitoring

Using citizen science data to assess the population genetic structure of the Common Yellowjacket Wasp, Vespula vulgaris

Monitoring insect genetic diversity and population structure has never been more important to manage the biodiversity crisis. Citizen science has become an increasingly popular tool to gather ecological data affordably across a wide range of spatial and temporal scales. To date, most insect-related citizen science initiatives have focused on occurrence and abundance data. Here we show that poorly preserved insect samples collected by citizen scientists can yield population genetic information, providing new insights into population connectivity, genetic diversity, and dispersal behaviour of little-studied insects. We analysed social wasps collected by participants of the Big Wasp Survey, a citizen science project which aims to map the diversity and distributions of vespine wasps in the UK. Although V. vulgaris is a notorious invasive species around the world, it remains poorly studied in its native range. We used these data to assess the population genetic structure of the common yellowjacket Vespula vulgaris at different spatial scales. We found a single, panmictic population across the UK with little evidence of population genetic structuring; the only possible limit to gene flow is the Irish sea, resulting in significant differentiation between the Northern Ireland and mainland UK populations.. Our results suggest that queens disperse considerable distances from their natal nests to found new nests, resulting in high rates of gene flow and thus little differentiation across the landscape. Citizen science data has made it feasible to perform this study, and we hope that it will encourage future projects to adopt similar practices in insect population monitoring

Social complexity, life-history and lineage influence the molecular basis of castes in vespid wasps

A key mechanistic hypothesis for the evolution of division of labour in social insects is that a shared set of genes co-opted from a common solitary ancestral ground plan (a genetic toolkit for sociality) regulates caste differentiation across levels of social complexity. Using brain transcriptome data from nine species of vespid wasps, we test for overlap in differentially expressed caste genes and use machine learning models to predict castes using different gene sets. We find evidence of a shared genetic toolkit across species representing different levels of social complexity. We also find evidence of additional fine-scale differences in predictive gene sets, functional enrichment and rates of gene evolution that are related to level of social complexity, lineage and of colony founding. These results suggest that the concept of a shared genetic toolkit for sociality may be too simplistic to fully describe the process of the major transition to sociality