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      The cell cycle oscillator and spindle length set the speed of chromosome separation in Drosophila embryos

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          Summary

          Anaphase is tightly controlled in space and time to ensure proper separation of chromosomes. The mitotic spindle, the self-organized microtubule structure driving chromosome segregation, scales in size with the available cytoplasm. Yet, the relationship between spindle size and chromosome movement remains poorly understood. Here, we address how the movement of chromosomes changes during the cleavage divisions of the Drosophila blastoderm. We show that the speed of chromosome separation gradually decreases during the 4 nuclear divisions of the blastoderm. This reduction in speed is accompanied by a similar reduction in the length of the spindle, thus ensuring that these two quantities are tightly linked. Using a combination of genetic and quantitative imaging approaches, we find that two processes contribute to controlling the speed at which chromosomes move at mitotic exit: the activity of molecular motors important for microtubule depolymerization and the cell cycle oscillator. Specifically, we found that the levels of Klp10A, Klp67A, and Klp59C, three kinesin-like proteins important for microtubule depolymerization, contribute to setting the speed of chromosome separation. This observation is supported by quantification of microtubule dynamics indicating that poleward flux rate scales with the length of the spindle. Perturbations of the cell cycle oscillator using heterozygous mutants of mitotic kinases and phosphatases revealed that the duration of anaphase increases during the blastoderm cycles and is the major regulator of chromosome velocity. Thus, our work suggests a potential link between the biochemical rate of mitotic exit and the forces exerted by the spindle. Collectively, we propose that the cell cycle oscillator and spindle length set the speed of chromosome separation in anaphase.

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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            ilastik: interactive machine learning for (bio)image analysis

            We present ilastik, an easy-to-use interactive tool that brings machine-learning-based (bio)image analysis to end users without substantial computational expertise. It contains pre-defined workflows for image segmentation, object classification, counting and tracking. Users adapt the workflows to the problem at hand by interactively providing sparse training annotations for a nonlinear classifier. ilastik can process data in up to five dimensions (3D, time and number of channels). Its computational back end runs operations on-demand wherever possible, allowing for interactive prediction on data larger than RAM. Once the classifiers are trained, ilastik workflows can be applied to new data from the command line without further user interaction. We describe all ilastik workflows in detail, including three case studies and a discussion on the expected performance.
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              TrackMate 7: integrating state-of-the-art segmentation algorithms into tracking pipelines

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                Author and article information

                Contributors
                Role: ConceptualizationRole: MethodologyRole: SoftwareRole: Formal AnalysisRole: InvestigationRole: WritingRole: Visualization
                Role: Investigation
                Role: Investigation
                Role: Investigation
                Role: MethodologyRole: SupervisionRole: Funding Acquisition
                Role: ConceptualizationRole: MethodologyRole: Formal AnalysisRole: WritingRole: VisualizationRole: SupervisionRole: Funding Acquisition
                Journal
                bioRxiv
                BIORXIV
                bioRxiv
                Cold Spring Harbor Laboratory
                2692-8205
                18 June 2024
                : 2024.06.17.598879
                Affiliations
                [1 ]Department of Cell Biology, Duke University Medical Center, Durham NC 27705, USA
                [2 ]Cluster of Excellence Physics of Life, TU Dresden, Dresden, 01307 Germany
                [3 ]Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, 01307 Germany
                [4 ]Center of Systems Biology, Dresden, 01307 Germany
                Author notes
                [* ]correspondence to: stefano.ditalia@ 123456duke.edu
                Author information
                http://orcid.org/0000-0001-8392-8610
                http://orcid.org/0000-0002-8040-9468
                http://orcid.org/0000-0001-9758-7925
                Article
                10.1101/2024.06.17.598879
                11212860
                38948726
                cc6353dd-b7e9-4e17-aaa2-74dad6f27eef

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.

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