RESUMEN
To cope with seasonal environmental changes, organisms have evolved approximately 1-y endogenous circannual clocks. These circannual clocks regulate various physiological properties and behaviors such as reproduction, hibernation, migration, and molting, thus providing organisms with adaptive advantages. Although several hypotheses have been proposed, the genes that regulate circannual rhythms and the underlying mechanisms controlling long-term circannual clocks remain unknown in any organism. Here, we show a transcriptional program underlying the circannual clock in medaka fish (Oryzias latipes). We monitored the seasonal reproductive rhythms of medaka kept under natural outdoor conditions for 2 y. Linear regression analysis suggested that seasonal changes in reproductive activity were predominantly determined by an endogenous program. Medaka hypothalamic and pituitary transcriptomes were obtained monthly over 2 y and daily on all equinoxes and solstices. Analysis identified 3,341 seasonally oscillating genes and 1,381 daily oscillating genes. We then examined the existence of circannual rhythms in medaka via maintaining them under constant photoperiodic conditions. Medaka exhibited approximately 6-mo free-running circannual rhythms under constant conditions, and monthly transcriptomes under constant conditions identified 518 circannual genes. Gene ontology analysis of circannual genes highlighted the enrichment of genes related to cell proliferation and differentiation. Altogether, our findings support the "histogenesis hypothesis" that postulates the involvement of tissue remodeling in circannual time-keeping.
Asunto(s)
Oryzias , Animales , Oryzias/genética , Estaciones del Año , Ritmo Circadiano/fisiología , Gónadas , FotoperiodoRESUMEN
Bow-tie architecture is a layered network structure that has a narrow middle layer with multiple inputs and outputs. Such structures are widely seen in the molecular networks in cells, suggesting that a universal evolutionary mechanism underlies the emergence of bow-tie architecture. The previous theoretical studies have implemented evolutionary simulations of the feedforward network to satisfy a given input-output goal and proposed that the bow-tie architecture emerges when the ideal input-output relation is given as a rank-deficient matrix with mutations in network link intensities in a multiplicative manner. Here, we report that the bow-tie network inevitably appears when the link intensities representing molecular interactions are small at the initial condition of the evolutionary simulation, regardless of the rank of the goal matrix. Our dynamical system analysis clarifies the mechanisms underlying the emergence of the bow-tie structure. Further, we demonstrate that the increase in the input-output matrix reduces the width of the middle layer, resulting in the emergence of bow-tie architecture, even when evolution starts from large link intensities. Our data suggest that bow-tie architecture emerges as a side effect of evolution rather than as a result of evolutionary adaptation.
Asunto(s)
Transducción de Señal , Transducción de Señal/fisiología , Transducción de Señal/genética , Simulación por Computador , Evolución Biológica , Modelos Biológicos , Algoritmos , Evolución Molecular , Biología de Sistemas/métodos , Mutación/genéticaRESUMEN
Recent progress in high throughput single cell RNA-seq (scRNA-seq) has activated the development of data-driven inferring methods of gene regulatory networks. Most network estimations assume that perturbations produce downstream effects. However, the effects of gene perturbations are sometimes compensated by a gene with redundant functionality (functional compensation). In order to avoid functional compensation, previous studies constructed double gene deletions, but its vast nature of gene combinations was not suitable for comprehensive network estimation. We hypothesized that functional compensation may emerge as a noise change without mean change (noise-only change) due to varying physical properties and strong compensation effects. Here, we show compensated interactions, which are not detected by mean change, are captured by noise-only change quantified from scRNA-seq. We investigated whether noise-only change genes caused by a single deletion of STP1 and STP2, which have strong functional compensation, are enriched in redundantly regulated genes. As a result, noise-only change genes are enriched in their redundantly regulated genes. Furthermore, novel downstream genes detected from noise change are enriched in "transport", which is related to known downstream genes. Herein, we suggest the noise difference comparison has the potential to be applied as a new strategy for network estimation that capture even compensated interaction.