Interactive effects of previous and current thermal conditions on gene expression in Manduca sexta
Cite this dataset
Alston, Meggan A et al. (2020). Interactive effects of previous and current thermal conditions on gene expression in Manduca sexta [Dataset]. Dryad. https://doi.org/10.5061/dryad.k0p2ngf4w
High temperatures can negatively impact performance and survival of organisms, particularly ectotherms. While an organism’s response to high temperature stress clearly depends on current thermal conditions, its response may also be affected by the temporal pattern and duration of past temperature exposures. We used RNA sequencing of Manduca sexta larvae fat body tissue to evaluate how diurnal temperature fluctuations during development affected gene expression both independently and in conjunction with subsequent heat stress. Additionally, we compared gene expression between two M. sexta populations, a lab colony and a genetically related field population that have been separated for more than 300 generations and differ in their thermal sensitivities. Lab-adapted larvae were predicted to show increased expression responses to both single and repeated thermal stress, whereas recurrent exposure could decrease later stress responses for field individuals. We found large differences in overall gene expression patterns between the two populations (across all temperature treatments), as well as population-specific transcriptomic responses to temperature; most differentially expressed genes were upregulated in the field compared with lab larvae. Developmental temperature fluctuations alone had minimal effects on long-term gene expression patterns, with the exception of a somewhat elevated stress response in the lab population. Fluctuating rearing conditions did alter gene expression during exposure to later heat stress, but this effect depended on both the population and the particular temperature conditions. This study contributes to increased knowledge of molecular mechanisms underlying physiological responses of organisms to temperature fluctuations, which is needed for the development of more accurate thermal performance models.
1. RNAseq_counts.zip contains count files (number of reads that mapped to each gene) for all samples of the RNA sequencing dataset used in this study. Count files were generated using HTSeq.
2. RNAseq_DE_Analysis.Rmd is the R Markdown file containing code used to run differential expression analysis.
3. MS_sample_table.txt contains metadata for samples in RNAseq_counts.zip (required to run differential expression analysis using RNAseq_DE_Analysis.Rmd).
4. HSP_list.txt contains a list of Manduca sexta genes annotated as heat shock proteins (required to run RNAseq_DE_Analysis.Rmd).
5. Supplemental_figures_and_tables.pdf contains additional figures and tables that are not included in journal online supplement.
National Science Foundation, Award: IOS-1555959