Climate change will strongly affect the developmental timing of insects, as their development rate largely depends on ambient temperature. However, we know little about the genetic mechanisms underlying the temperature sensitivity of embryonic development in insects. We investigated embryonic development rate in the winter moth (Operophtera brumata), a species with egg dormancy that has been under selection due to climate change. We used RNAseq to investigate which genes are involved in the regulation of winter moth embryonic development rate in response to temperature. Over the course of development, we sampled eggs before and after an experimental change in ambient temperature, including two early development weeks when the temperature sensitivity of eggs is low and two late development weeks when temperature sensitivity is high. We found temperature-responsive genes that responded in a similar way across development, as well as genes with a temperature response specific to a particular development week. Moreover, we identified genes whose temperature effect size changed around the switch in temperature sensitivity of development rate. Interesting candidate genes for regulating the temperature sensitivity of egg development rate included genes involved in histone modification, hormonal signalling, nervous system development, and circadian clock genes. In conclusion, the diverse sets of temperature-responsive genes we found here indicate that there are many potential targets of selection to change the temperature sensitivity of embryonic development rate. Identifying for which of these genes there is genetic variation in wild insect populations will give insight into their adaptive potential in the face of climate change.

This dataset consists of all processed data and phenotypic data needed to reproduce the analysis of RNAseq data from winter moth embryos, published in Molecular Ecology under the same title.

Data included here: the final transcriptome incl. functional annotation, GO annotation table, final gene counts matrix, and phenotypic data. 

The raw RNAseq reads can be found on the European Nucleotide Archive (ENA) under accession no. PRJEB55675.

All the scripts needed to process the data and reproduce the analysis can be found on GitHub at https://github.com/NEvanDis/WM_RNAseq.

Briefly: raw RNAseq reads were quality screened and processed according to the 'new Tuxedo' pipeline (see Pertea et al. 2016 Nature Protocols 11(9). This pipeline includes transcript assembly and quantification with StringTie, guided by the winter moth reference genome v1 with annotation v2. StringTie produces a transcriptome including only transcripts in the dataset with each transcript coordinated to the winter moth reference genome. We functionally annotated this transcriptome e.g. with BLAST, which included producing a GO annotation table. StringTie then uses this transcriptome to do transcript quantification at the gene level, of which the product is the final gene counts matrix deposited here. This final gene counts matric and the phenotypic data were used for statistical analysis and the production of the final figures in the Mol Ecol publication. Please see the scripts on GitHub for pipeline and analysis details.

File extensions of the deposited data files include .gff, .txt, and .csv. These are all text-based file formats that can be opened with any text processor.