During their lifetime, animals must adapt their behavior to survive in changing environments. This ability requires the nervous system to adjust through dynamic expression of neurotransmitters and receptors but also through growth, spatial reorganization and connectivity while integrating external stimuli. For instance, despite having a fixed neuronal cell lineage, the nematode Caenorhabditis elegans’ nervous system remains plastic throughout its development. Here, we focus on a specific example of nervous system plasticity, the C. elegans dauer exit decision. Under unfavorable conditions, larvae will enter the non-feeding and non-reproductive dauer stage and adapt their behavior to cope with a new environment. Upon improved conditions, this stress resistant developmental stage is actively reversed to resume reproductive development. However, how different environmental stimuli regulate the exit decision mechanism and thereby drive the larva’s behavioral change is unknown. To fill this gap, we developed a new open hardware method for long-term imaging (12h) of C. elegans larvae. We identified dauer-specific behavioral motifs and characterized the behavioral trajectory of dauer exit in different environments to identify key decision points. Combining long-term behavioral imaging with transcriptomics, we find that bacterial ingestion triggers a change in neuropeptide gene expression to establish post-dauer behavior. Taken together, we show how a developing nervous system can robustly integrate environmental changes, activate a developmental switch and adapt the organism’s behavior to a new environment.

Fluorescent in-situ hybridization (FISH)-based methods are powerful tools to study molecular processes with subcellular resolution, relying on accurate identification and localization of diffraction-limited spots in microscopy images. We developed the Radial Symmetry-FISH (RS-FISH) software that accurately, robustly, and quickly detects single-molecule spots in two and three dimensions, making it applicable to several key assays, including single-molecule FISH (smFISH), spatial transcriptomics, and spatial genomics. RS-FISH allows interactive parameter tuning and scales to large sets of images as well as tera-byte sized image volumes such as entire brain scans using straight-forward distributed processing on workstations, clusters, and in the cloud.

We present a method to automatically identify and track nuclei in time-lapse microscopy recordings of entire developing embryos. The method combines deep learning and global optimization. On a mouse dataset, it reconstructs 75.8% of cell lineages spanning 1 h, as compared to 31.8% for the competing method. Our approach improves understanding of where and when cell fate decisions are made in developing embryos, tissues, and organs.

Circular RNAs (circRNAs) are formed in all domains of life and via different mechanisms. There has been an explosion in the number of circRNA papers in recent years; however, as a relatively young field, circRNA biology has an urgent need for common experimental standards for isolating, analyzing, expressing and depleting circRNAs. Here we propose a set of guidelines for circRNA studies based on the authors’ experience. This Perspective will specifically address the major class of circRNAs in Eukarya that are generated by a spliceosome-catalyzed back-splicing event. We hope that the implementation of best practice principles for circRNA research will help move the field forward and allow a better functional understanding of this fascinating group of RNAs.