Behavioral age-detection in individuals reconstructs minute-scale developmental transcriptomics

Abstract

Capturing rapid changes in gene-expression across development time is crucial for uncovering the molecular pathways that organize dynamic developmental processes. Here, we introduce BehaveSeq, a method that enables time reconstruction of minute-resolution developmental patterns of gene-expression by integrating longitudinal behavioral monitoring for precise age detection with genome-wide transcriptomic profiling in single individuals. By densely sampling individuals every [~]3 minutes during hours of C. elegans development, we uncovered thousands of genes exhibiting rapid and temporally structured expression trajectories. These genes were organized into distinct dynamical patterns associated with specific developmental functions. Moreover, time-reconstruction of transcriptional trajectories in serotonin-deficient individuals revealed time-specific neuromodulatory effects on developmental expression programs. Interestingly, using the same single-animal datasets, we were able to train a neural network model that accurately predicts the developmental age of each individual based on its individual-specific molecular signature. Overall, our method provides a new framework for revealing dynamic gene regulation with high temporal precision across developmental timescales.