Embryo timelapses can be compiled and quantified to understand canonical histone dynamics across multiple cell cycles

In the last decade, computational analysis of big datasets has facilitated the processing of unprecedented quantities of collected biological data. Thus, automations and big data analyses have been revolutionary in detecting and quantifying subtle phenotypes in cell biological contexts. Analyzing similar quantities of data in larger and more complicated biological systems such as live embryos has been more challenging due to experimental necessities impeding both compilations of data collection and informative analysis. Here we present a streamlined workflow that can quantify cell cycle dynamics in early developing embryos using fluorescently labeled proteins. We benchmark this pipeline using Caenorhabditis elegans (nematode) embryonic development and a fluorescently labeled histone. Using our pipeline, we find that histone proteins are broadly stable in early embryonic development. In sum, we have utilized the large biological and experimental variation associated with quantification of fluorescent proteins in embryonic systems, to quantify nuclear accumulation rate, chromatin incorporation, and turnover/stability of canonical histones during early development.