Beijing Genomics Institute

Physical activity can regulate and affect gene expression in multiple tissues and cells. Recently, with the development of next-generation sequencing, a large number of RNA-sequencing (RNA-seq)-based gene expression profiles about physical activity have been shared in public resources; however, they are poorly curated and underutilized. To tackle this problem, we developed a data atlas of such data through comprehensive data collection, curation, and organization.

The data atlas, termed gene expression profiles of RNA-seq-based exercise responses (GEPREP), was built on a comprehensive collection of high-quality RNA-seq data on exercise responses. The metadata of each sample were manually curated. Data were uniformly processed and batch effects corrected. All the information was well organized in an easy-to-use website for free search, visualization, and download.

GEPREP now includes 69 RNA-seq datasets of pre- and post-exercise, comprising 26 human datasets (1120 samples) and 43 mouse datasets (1006 samples). Specifically, there were 977 (87.2 %) human samples of skeletal muscle and 143 (12.8 %) human samples of blood. There were also samples across 9 mice tissues with skeletal muscle (359, 35.7 %) and brain (280, 27.8 %) accounting for the main fractions. Metadata-including subject, exercise interventions, sampling sites, and post-processing methods-are also included. The metadata and gene expression profiles are freely accessible at http://www.geprep.org.cn/.

GEPREP is a comprehensive data atlas of RNA-seq-based gene expression profiles responding to exercise. With its reliable annotations and user-friendly interfaces, it has the potential to deepen our understanding of exercise physiology.

Planarian regeneration is a complex process that involves the precise orchestration of cell proliferation, differentiation, migration, and autophagy. However, the role of autophagy in planarian regeneration remains poorly understood. In this study, we identified autophagy-related gene 1 from the planarian Dugesia japonica (designated as DjAtg1) and investigated its role in planarian brain regeneration. DjAtg1 transcripts are highly expressed in the cephalic ganglia of intact planarians. Following amputation, DjAtg1 is prominently expressed in the newly regenerated brain tissues. Knockdown of DjAtg1 via RNA interference (RNAi) induces head regression, with all RNAi-treated animals regenerating a small triangular-shaped head. Neoblast-marker labeling experiments demonstrate that DjAtg1 knockdown does not affect cell proliferation but impairs neoblast behavior. Notably, RNA-seq reveals that most of these down-regulated transcripts are linked to the extracellular matrix (ECM). Based on our findings and prior literature, we propose that the DjAtg1-mediated secretory pathway is essential for ECM remodeling. DjAtg1 knockdown disrupts the secretory pathway, which feedback-inhibits the expression of ECM-related genes. Our work provides new insights into the non-canonical role of autophagy in regulating of ECM remodeling during planarian regeneration.

Individuals with neuropsychiatric disorders often show metabolic symptoms. However, the mechanisms underlying this co-occurrence remain unclear. Here we show that induced pluripotent stem cell-derived pancreatic islets from individuals with bipolar disorder have insulin secretion deficits caused by increased expression of RORβ, a susceptibility gene for bipolar disorder. Enhancing RORβ expression in mouse pancreatic β cells induced depression-related behaviors in the light phase and mania-like behaviors in the dark phase. Pancreatic RORβ overexpression in the light phase reduced insulin release from islets, inducing hippocampal hyperactivity and depression-like behaviors. Furthermore, this hippocampal hyperactivity in the light phase had the delayed effect of promoting insulin release in the dark phase, resulting in mania-like behaviors and hippocampal neuronal hypoactivity. Our results in mice point to a pancreas-hippocampus feedback mechanism by which metabolic and circadian factors cooperate to generate behavioral fluctuations and which may play a role in bipolar disorder.