Dynein-mediated transport and membrane trafficking control PAR3 polarised distribution

The scaffold protein PAR3 and the kinase PAR1 are essential proteins that control cell polarity. Their precise opposite localisations define plasma membrane domains with specific functions. PAR3 and PAR1 are mutually inhibited by direct or indirect phosphorylations, but their fates once phosphorylated are poorly known. Through precise spatiotemporal quantification of PAR3 localisation in the Drosophila oocyte, we identify several mechanisms responsible for its anterior cortex accumulation and its posterior exclusion. We show that PAR3 posterior plasma membrane exclusion depends on PAR1 and an endocytic mechanism relying on RAB5 and PI(4,5)P2. In a second phase, microtubules and the dynein motor, in connection with vesicular trafficking involving RAB11 and IKK-related kinase, IKKε, are required for PAR3 transport towards the anterior cortex. Altogether, our results point to a connection between membrane trafficking and dynein-mediated transport to sustain PAR3 asymmetry.


Sample-size estimation
• You should state whether an appropriate sample size was computed when the study was being designed • You should state the statistical method of sample size computation and any required assumptions • If no explicit power analysis was used, you should describe how you decided what sample (replicate) size (number) to use Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission:

Replicates
• You should report how often each experiment was performed • You should include a definition of biological versus technical replication • The data obtained should be provided and sufficient information should be provided to indicate the number of independent biological and/or technical replicates • If you encountered any outliers, you should describe how these were handled • Criteria for exclusion/inclusion of data should be clearly stated • High-throughput sequence data should be uploaded before submission, with a private link for reviewers provided (these are available from both GEO and ArrayExpress) Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: For each quantification experiments, about ten flies have been sacrificed and oocytes in their ovaries have been chosen randomly and the images acquired. Next the images of oocytes have been separate according to developmental stage. The number of oocytes used is indicated in the legend of each figure.

Statistical reporting
• Statistical analysis methods should be described and justified • Raw data should be presented in figures whenever informative to do so (typically when N per group is less than 10) • For each experiment, you should identify the statistical tests used, exact values of N, definitions of center, methods of multiple test correction, and dispersion and precision measures (e.g., mean, median, SD, SEM, confidence intervals; and, for the major substantive results, a measure of effect size (e.g., Pearson's r, Cohen's d) • Report exact p-values wherever possible alongside the summary statistics and 95% confidence intervals. These should be reported for all key questions and not only when the p-value is less than 0.05.
Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: (For large datasets, or papers with a very large number of statistical tests, you may upload a single table file with tests, Ns, etc., with reference to sections in the manuscript.)

Group allocation
• Indicate how samples were allocated into experimental groups (in the case of clinical studies, please specify allocation to treatment method); if randomization was used, please also state if restricted randomization was applied • Indicate if masking was used during group allocation, data collection and/or data analysis Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: Additional data files ("source data") • We encourage you to upload relevant additional data files, such as numerical data that are represented as a graph in a figure, or as a summary table • Where provided, these should be in the most useful format, and they can be uploaded as "Source data" files linked to a main figure or table For quantification experiment: we realized biological replicates by using several flies for each experiment. Moreover, for the control condition (TubGal4), we realized two times the experiment (flies crossing). Then, to verify the macro quantification process, we reiterate the quantification on the same sample with two different experimenters. For protein interaction experiments, the immunoprecipitation have been performed two or three times with independent protein extracts (coming from different flies) For all the quantification, the data are represented by Tukey's boxplot or column bar graph (mean with sem). A non-parametric test -Mann Whitney test was performed and p-value (two tailed / 95% confidence interval) are indicated on the graph or in the figure legends. • Include model definition files including the full list of parameters used • Include code used for data analysis (e.g., R, MatLab) • Avoid stating that data files are "available upon request" Please indicate the figures or tables for which source data files have been provided: None