Evo-Devo applied to sleep research: an approach whose time has come

Abstract

Sleep occurs in all animals but its amount, form, and timing varies considerably between species and between individuals. Currently, little is known about the basis for these differences, in part because we lack a complete understanding of the brain circuitry controlling sleep-wake states and markers for the cell-types which can identify similar circuits across phylogeny. Here, I explain the utility of an ‘Evo-devo’ approach for comparative studies of sleep regulation and function as well as for sleep medicine. This approach focuses on the regulation of evolutionary ancient transcription factors which act as master controllers of cell-type specification. Studying these developmental transcription factor cascades can identify novel cell clusters which control sleep and wakefulness, reveal the mechanisms which control differences in sleep timing, amount and expression and identify the timepoint in evolution when different sleep-wake control neurons appeared. Spatial transcriptomic studies which identify cell clusters based on transcription factor expression will greatly aid this approach. Conserved developmental pathways regulate sleep in mice, Drosophila and C. Elegans. Members of the LIM Homeobox (Lhx) gene family control the specification of sleep and circadian neurons in the forebrain and hypothalamus. Increased Lhx9 activity may account for increased orexin/hypocretin neurons and reduced sleep in Mexican cavefish. Other transcription factor families specify sleep-wake circuits in the brainstem, hypothalamus, and basal forebrain. Expression of transcription factors allows generation of specific cell-types for transplantation approaches. Furthermore, mutations in developmental transcription factors are linked to variation in sleep duration in humans, risk for restless legs syndrome and sleep-disordered breathing. This paper is part of the Genetic and other molecular underpinnings of sleep, sleep disorders, and circadian rhythms including translational approaches collection.