Inferring temporal organization of postembryonic development from high-content behavioral tracking

Denis F. Faerberg, Victor Gurarie, Ilya Ruvinsky*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Understanding temporal regulation of development remains an important challenge. Whereas average, species-typical timing of many developmental processes has been established, less is known about inter-individual variability and correlations in timing of specific events. We addressed these questions in the context of postembryonic development in Caenorhabditis elegans. Based on patterns of locomotor activity of freely moving animals, we inferred durations of four larval stages (L1-L4) in over 100 individuals. Analysis of these data supports several conclusions. Individuals have consistently faster or slower rates of development because durations of L1 through L3 stages are positively correlated. The last larval stage, the L4, is less variable than the earlier stages and its duration is largely independent of the rate of early larval development, implying existence of two distinct larval epochs. We describe characteristic patterns of variation and correlation, as well as the fact that stage durations tend to scale relative to total developmental time. This scaling relationship suggests that each larval stage is not limited by an absolute duration, but is instead terminated when a subset of events that must occur prior to adulthood have been completed. The approach described here offers a scalable platform that will facilitate the study of temporal regulation of postembryonic development.

Original languageEnglish (US)
Pages (from-to)54-64
Number of pages11
JournalDevelopmental Biology
StatePublished - Jul 2021


  • C. elegans
  • Developmental timing
  • Larval
  • Postembryonic
  • Variability

ASJC Scopus subject areas

  • Molecular Biology
  • Developmental Biology
  • Cell Biology


Dive into the research topics of 'Inferring temporal organization of postembryonic development from high-content behavioral tracking'. Together they form a unique fingerprint.

Cite this