Only three principal components account for inter-embryo variability of the spindle length over time

Author:

Cunff Yann LeORCID,Chesneau LaurentORCID,Pastezeur SylvainORCID,Pinson Xavier,Soler NinaORCID,Fairbrass Danielle,Mercat Benjamin,Garcia Ruddi Rodriguez,Alayan Zahraa,Abdouni Ahmed,de Neidhardt Gary,Costes Valentin,Anjubault Mélodie,Bouvrais HélèneORCID,Héligon ChristopheORCID,Pécréaux JacquesORCID

Abstract

AbstractHow does inter-individual variability emerge? When measuring a large number of features per experiment/individual, this question becomes non-trivial. One challenge lies in choosing features to recapitulate high-dimension data. In this paper, we focus on spindle elongation phenotype to highlight how a data-driven approach can help. We showed that only three typical elongation patterns could describe spindle elongation in C.elegansone-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 85% 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 both in late metaphase and anaphase. However, our archetypes were not strictly corresponding to these manually-set features. The third archetype, accounting for 6% of the variance, was novel and corresponded to a transient spindle shortening in late metaphase. We propose that it is part of spindle elongation dynamics in all conditions. It is reminiscent of the elongation pattern observed upon defects in kinetochore function. Notably, the same archetypes emerged when analysing non-treated embryos only at various temperatures. Interestingly, because these archetypes were not specific to metaphase or anaphase, it implied that spindle elongation around anaphase-onset is sufficient to predict its late anaphase length. We validated this idea using a machine-learning approach.Despite the apparent variability in phenotypes across the various conditions, inter-individual differences between embryos depleted from one cell division-related protein have the same underlying nature as inter-individual differences naturally arising between wild-type embryos. The same conclusion holds when analysing embryos dividing at various temperatures. We thus propose that beyond the apparent complexity of the spindle, only three independent mechanisms account for spindle elongation, and contribute differently in the various conditions, meanwhile, no mechanism is specific to any condition.

Publisher

Cold Spring Harbor Laboratory

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