Unveiling Inter-Embryo Variability in Spindle Length over time: towards Quantitative Phenotype Analysis.
Yann Le CunffiD, Laurent ChesneauiD, Sylvain PastezeuriD, Xavier PinsoniD, Nina SoleriD, Danielle Fairbrass, Benjamin Mercat, Ruddi Rodríguez-García, Zahraa Alayan, Ahmed Abdouni, Gary de Neidhardt, Valentin CostesiD, Mélodie Anjubault, Hélène BouvraisiD, Christophe HéligoniD, Jacques PécréauxiD
Abstract
How to quantify inter-individual variability? When measuring many features per experiment/individual, this question becomes non-trivial. One challenge lies in choosing features to recapitulate high-dimensional data. This paper focuses on spindle elongation phenotypes to highlight how a data-driven approach can help tackle this challenge. We showed that only three typical elongation patterns describe spindle elongation in C. elegans one-cell embryo. We called them archetypes. These archetypes were automatically extracted from the experimental data using principal component analysis (PCA) rather than defined a priori. They accounted for more than 95% of inter-individual variability in a dataset of more than 1600 experiments across more than 100 different experimental conditions (RNAi, mutants, changes in temperature, etc.). The two first archetypes were consistent with standard measures in the field, namely the average spindle length and the spindle elongation rate in late metaphase and anaphase. However, our archetypes were not strictly corresponding to these classic, manually-set, features. The third archetype, accounting for 6% of the variability, was novel and corresponded to a transient spindle shortening in late metaphase. We revealed that it is part of spindle elongation dynamics in all conditions. It is reminiscent of the spindle elongation pattern observed upon kinetochore function defects. Interestingly, because these archetypes were all three present from metaphase on, it implied that spindle elongation around the anaphase onset is sufficient to predict its late anaphase length. We validated this idea using a machine-learning approach. The inter-individual differences between embryos depleted from cell division-related proteins have the same underlying nature as inter-individual differences naturally arising between wild-type embryos. The same conclusion holds also when analysing embryos dividing at various temperatures. We thus propose that beyond the apparent complexity of the spindle and variability in the phenotypes of various gene depletions, only three independent mechanisms account for spindle elongation, weighted differently in the various conditions; meanwhile, no mechanism is specific to any condition. As such, given amounts of these three archetypes could represent a quantitative phenotype.
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