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Published August 24, 2021 | Version v1
Dataset Open

Timing of increased temperature sensitivity coincides with nervous system development in winter moth embryos

  • 1. Nederlands Instituut voor Ecologie
  • 2. Leiden University
  • 3. University of Groningen

Description

Climate change is rapidly altering the environment and many species will need to genetically adapt their seasonal timing to keep up with these changes. Insect development rate is largely influenced by temperature, but we know little about the mechanisms underlying temperature sensitivity of development. Here we investigate seasonal timing of egg hatching in the winter moth, one of the few species which has been found to genetically adapt to climate change, likely through selection on temperature sensitivity of egg development rate. To study when during development winter moth embryos are most sensitive to changes in ambient temperature, we gave eggs an increase or decrease in temperature at different moments during their development. We measured their developmental progression and timing of egg hatching, and used fluorescence microscopy to construct a timeline of embryonic development for the winter moth. We found that egg development rate responded more strongly to temperature once embryos were in the fully extended germband stage. This is the phylotypic stage at which all insect embryos have developed a rudimentary nervous system. Furthermore, at this stage timing of ecdysone signaling determines developmental progression, which could act as an environment dependent gateway. Intriguingly, this may suggest that, from the phylotypic stage onward, insect embryos can start to integrate internal and environmental stimuli to actively regulate important developmental processes. As we found evidence that there is genetic variation for temperature sensitivity of egg development rate in our study population, such regulation could be a target of selection imposed by climate change.

Notes

All code needed to run the analyses can be found in the two scripts, which also includes information on the raw data. The statistical models have been included in the data, so the user does not necessarily have to rerun the models (for which some processing power is needed).

Funding provided by: Rijksuniversiteit Groningen
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100001721
Award Number: Adaptive Life Fund

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