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• W4311794314 abstract "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." @default.
• W4311794314 created "2022-12-28" @default.
• W4311794314 creator A5021680827 @default.
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• W4311794314 creator A5056925004 @default.
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• W4311794314 date "2022-12-17" @default.
• W4311794314 modified "2023-09-30" @default.
• W4311794314 title "Co-expression Gene Networks and Machine-learning Algorithms Unveil a Core Genetic Toolkit for Reproductive Division of Labour in Rudimentary Insect Societies" @default.
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• W4311794314 doi "https://doi.org/10.1093/gbe/evac174" @default.
• W4311794314 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36527688" @default.
• W4311794314 hasPublicationYear "2022" @default.
• W4311794314 type Work @default.
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