Canalized gene expression during development mediates caste differentiation in ants

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Ant colonies are higher-level organisms consisting of specialized reproductive and non-reproductive individuals that differentiate early in development, similar to germ–soma segregation in bilateral Metazoa. Analogous to diverging cell lines, developmental differentiation of individual ants has often been considered in epigenetic terms but the sets of genes that determine caste phenotypes throughout larval and pupal development remain unknown. Here, we reconstruct the individual developmental trajectories of two ant species, Monomorium pharaonis and Acromyrmex echinatior, after obtaining >1,400 whole-genome transcriptomes. Using a new backward prediction algorithm, we show that caste phenotypes can be accurately predicted by genome-wide transcriptome profiling. We find that caste differentiation is increasingly canalized from early development onwards, particularly in germline individuals (gynes/queens) and that the juvenile hormone signalling pathway plays a key role in this process by regulating body mass divergence between castes. We quantified gene-specific canalization levels and found that canalized genes with gyne/queen-biased expression were enriched for ovary and wing functions while canalized genes with worker-biased expression were enriched in brain and behavioural functions. Suppression in gyne larvae of Freja, a highly canalized gyne-biased ovary gene, disturbed pupal development by inducing non-adaptive intermediate phenotypes between gynes and workers. Our results are consistent with natural selection actively maintaining canalized caste phenotypes while securing robustness in the life cycle ontogeny of ant colonies.

OriginalsprogEngelsk
TidsskriftNature Ecology and Evolution
Vol/bind6
Udgave nummer11
Sider (fra-til)1753-1765
ISSN2397-334X
DOI
StatusUdgivet - 2022

Bibliografisk note

Funding Information:
We thank the China National Genebank for providing transcriptomics sequencing service with MGI sequencers and Danish National Life Science Supercomputing Center, Computerome, for providing computational resources. We thank Z. Xiong for uploading the A. echinatior genomic data to NCBI. This work was supported by the Lundbeck Foundation (grant no. R190-2014-2827 to G.Z.), the Villum Foundation (Villum Investigator Grant, grant no. 25900 to G.Z.), the European Research Council (advanced grant no. 323085 to J.J.B.), the National Natural Science Foundation of China (grant no. 31820573 to G.Z.; no. 31501057 to Q.L. and no. 31900399 to W.L.).

Publisher Copyright:
© 2022, The Author(s).

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