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BehaveSeq: behavioral age-detection in single individuals for reconstruction of high-resolution transcriptional dynamics during development

ABSTRACT: Capturing rapid changes in gene expression states across development time is crucial for revealing underlying molecular pathways that organize dynamic developmental processes. Here, we present ‘BehaveSeq’, a framework that integrates behavioral age detection with transcriptomic profiling in the same individuals, to reconstruct minute-resolution developmental profiles of gene expression. By densely sampling isolated C. elegans individuals every ~3 minutes during the L4 stage, we identified thousands of genes showing fast and temporally-structured expression patterns during development. These genes were organized into distinct clusters associated with specific developmental and cellular functions. Further applying the new framework to serotonin-deficient individuals revealed both conserved and altered expression patterns across conditions. Interestingly, using the same single-animal dataset, we were able to train a neural network model to accurately predict the developmental age of each individual solely based on its individual-specific transcriptional signature. Overall, our approach offers a new, generalizable framework for revealing dynamic processes of gene regulation with high temporal precision across the developmental trajectory.

ORGANISM(S): Caenorhabditis elegans

PROVIDER: GSE306572 | GEO | 2025/08/31

REPOSITORIES: GEO

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