Back

Climate drives long-term landscape and rapid short-term promoter evolution in the Western Canaries lizard, Gallotia galloti

Gilbert, E.; Megia-Palma, R.; Zagar, A.; Lopez-Darias, M.; Carretero, M. A.; Seren, N.; Sellers, G. S.; Beltran-Alvarez, P.; Wollenberg Valero, K. C.

2024-12-21 evolutionary biology
10.1101/2024.12.18.628907 bioRxiv
Show abstract

Climate adaptation is caused by multiple mechanisms, including evolution of regulatory promoter sequences under broad environmental pressures, however, little is known about these processes in response to climate pressures in animals. Here, we examined spatial and temporal evolution of climate-related gene promoters in an insular species, the Western-Canaries lizard Gallotia galloti, across diverse environmental conditions over nine years. Outlier SNPs linked to elevation-sensitive environmental factors identified adaptively significant loci, including in aquaporin and Electron Transfer Flavoprotein Subunit Alpha (ETFA) gene promoters, demonstrating roles in local climate adaptation. Adaptive indexing mapped climate-driven genetic differentiation across the landscape, revealing local adaptation along an elevational gradient. Signatures of climate-related selection at the temporal scale showed specific promoters shaped by balancing selection supporting survival across environments, while others experienced positive selection, revealing a selective sweep of beneficial alleles. In addition, elevation-based ancestry groups of climate loci differed from the pattern observed in neutral loci, and temporal shifts in ancestry composition responded to preceding extreme weather events over the span of a single generation. Selection on specific promoter regions indicated adaptive evolution in transcription factor binding sites with the potential to enhance transcriptional flexibility, resulting in increased cellular stress tolerance. Our findings open new avenues into genomic mechanisms of resilience across spatially heterogeneous environments and how rapid evolution correlates with extreme weather events associated with climate change.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.