Acute thermal stress elicits interactions between gene expression and alternative splicing in a fish of conservation concern

Abstract

Transcriptomic research provides a mechanistic understanding of an organism's response to environmental challenges such as increasing temperatures, which can provide key insights into the threats posed by thermal challenges associated with urbanization and climate change. Differential gene expression and alternative splicing are two elements of the transcriptomic stress response that may work in tandem, but relatively few studies have investigated these interactions in fishes of conservation concern. We studied the imperilled redside dace (Clinostomus elongatus) as thermal stress is hypothesized to be an important cause of population declines. We tested the hypothesis that gene expression-splicing interactions contribute to the thermal stress response. Wild fish exposed to acute thermal stress were compared with both handling controls and fish sampled directly from a river. Liver tissue was sampled to study the transcriptomic stress response. With a gene set enrichment analysis, we found that thermally stressed fish showed a transcriptional response related to transcription regulation and responses to unfolded proteins, and alternatively spliced genes related to gene expression regulation and metabolism. One splicing factor, prpf38b, was upregulated in the thermally stressed group compared with the other treatments. This splicing factor may have a role in the Jun/AP-1 cellular stress response, a pathway with wide-ranging and context-dependent effects. Given large gene interaction networks and the context-dependent nature of transcriptional responses, our results highlight the importance of understanding interactions between gene expression and splicing for understanding transcriptomic responses to thermal stress. Our results also reveal transcriptional pathways that can inform conservation breeding, translocation and reintroduction programs for redside dace and other imperilled species by identifying appropriate source populations.

Keywords: Clinostomus elongatus; CTmax; Differential exon usage; Redside dace; Species at risk; Transcriptomics; mRNA transcription.