Repeated evolution of circadian clock dysregulation in cavefish populations

Abstract

Circadian rhythms are nearly ubiquitous throughout nature, suggesting they are critical for survival in diverse environments. Organisms inhabiting largely arrhythmic environments, such as caves, offer a unique opportunity to study the evolution of circadian rhythms in response to changing ecological pressures. Populations of the Mexican tetra, Astyanax mexicanus, have repeatedly invaded caves from surface rivers, where individuals must contend with perpetual darkness, reduced food availability, and limited fluctuations in daily environmental cues. To investigate the molecular basis for evolved changes in circadian rhythms, we investigated rhythmic transcription across multiple independently-evolved cavefish populations. Our findings reveal that evolution in a cave environment has led to the repeated disruption of the endogenous biological clock, and its entrainment by light. The circadian transcriptome shows widespread reductions and losses of rhythmic transcription and changes to the timing of the activation/repression of core-transcriptional clock. In addition to dysregulation of the core clock, we find that rhythmic transcription of the melatonin regulator aanat2 and melatonin rhythms are disrupted in cavefish under darkness. Mutants of aanat2 and core clock gene rorca disrupt diurnal regulation of sleep in A. mexicanus, phenocopying circadian modulation of sleep and activity phenotypes of cave populations. Together, these findings reveal multiple independent mechanisms for loss of circadian rhythms in cavefish populations and provide a platform for studying how evolved changes in the biological clock can contribute to variation in sleep and circadian behavior.

Sensory conflict disrupts circadian rhythms in the sea anemone Nematostella vectensis

“…This would be consistent with circadian dysregulation in cavefish, which have evolved in arrhythmic environments and have fewer rhythmic transcripts than surface populations [62]. The imposition of arrhythmic feeding regimes also reduces the number of rhythmic transcripts in mouse liver [63].…”

“…Having observed that 12h SC resulted in the disruption of rhythmic locomotion, we had expected that, perhaps, Nematostella would simply have fewer rhythmic genes during SC. This would be consistent with circadian dysregulation in cavefish, which have evolved in arrhythmic environments and have fewer rhythmic transcripts than surface populations [62]. The imposition of arrhythmic feeding regimes also reduces the number of rhythmic transcripts in mouse liver [63].…”

“…The phase distribution of circadian transcripts was bimodal during both aligned and SC conditions, as in many other systems (e.g. [62, 64–66]). Genes with phases during the two transcriptional “peaks” (ZT0-6 and ZT12-18) were less likely to lose rhythmicity during SC (38% lost rhythmicity compared to 53% of other genes; Chi-squared test, p < 2 × 10 − 16 ), suggesting that rhythmic gene expression during these windows is somehow more robust.…”

“…Although one study measured the expression of individual clock genes during sensory conflict ( Rivas et al, 2018 ), the effects on downstream gene expression are entirely unknown. Animals exposed to arrhythmic conditions, such as mice in feeding experiments ( Greenwell et al, 2019 ) or cavefish over evolutionary time ( Mack et al, 2021 ), often express fewer rhythmic transcripts. Transcriptome-scale studies are needed to test whether sensory conflict similarly disrupts expression of core clock genes or of downstream clock-controlled genes, resulting in a general loss of rhythmic gene expression.…”

CaveCrawler: an interactive analysis suite for cavefish bioinformatics

“…CaveCrawler currently pools data from multiple publications and authors can request that their own data be integrated into CaveCrawler’s repository. As of publication, CaveCrawler’s data bank includes transcriptional datasets ( Mack et al 2021 ; Moran et al 2022 ), population genetics datasets ( Herman et al 2018 ; McGaugh, Passow, et al 2020 ), GO data from UniProt and the Gene Ontology Consortium ( Ashburner et al 2000 ; The Gene Ontology Consortium 2021 ; The UniProt Consortium 2021 ), and genome architecture data from Ensembl Genome Browser, release 104 ( Howe, Achuthan, et al 2021 ). The specific datasets which CaveCrawler draws data from are described in Table 1 .…”