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      Parental genome unification is highly error-prone in mammalian embryos

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          Summary

          Most human embryos are aneuploid. Aneuploidy frequently arises during the early mitotic divisions of the embryo, but its origin remains elusive. Human zygotes that cluster their nucleoli at the pronuclear interface are thought to be more likely to develop into healthy euploid embryos. Here, we show that the parental genomes cluster with nucleoli in each pronucleus within human and bovine zygotes, and clustering is required for the reliable unification of the parental genomes after fertilization. During migration of intact pronuclei, the parental genomes polarize toward each other in a process driven by centrosomes, dynein, microtubules, and nuclear pore complexes. The maternal and paternal chromosomes eventually cluster at the pronuclear interface, in direct proximity to each other, yet separated. Parental genome clustering ensures the rapid unification of the parental genomes on nuclear envelope breakdown. However, clustering often fails, leading to chromosome segregation errors and micronuclei, incompatible with healthy embryo development.

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          Highlights

          • The parental genomes cluster at the pronuclear interface in human and bovine zygotes

          • Clustering is driven by centrosomes, which often reside at the pronuclear interface

          • Dynein orients chromosomes toward centrosomes via nuclear pore complexes as adaptors

          • Clustering defects lead to aneuploidy and micronuclei, impairing embryo development

          Abstract

          In human and bovine zygotes, parental genomes cluster and polarize toward each other in a highly error-prone process driven by centrosomes, dynein, microtubules, and nuclear pore complexes. Failure to cluster the parental genomes leads to chromosome segregation errors and micronuclei, which are incompatible with healthy embryo development.

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          Most cited references103

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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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            QuPath: Open source software for digital pathology image analysis

            QuPath is new bioimage analysis software designed to meet the growing need for a user-friendly, extensible, open-source solution for digital pathology and whole slide image analysis. In addition to offering a comprehensive panel of tumor identification and high-throughput biomarker evaluation tools, QuPath provides researchers with powerful batch-processing and scripting functionality, and an extensible platform with which to develop and share new algorithms to analyze complex tissue images. Furthermore, QuPath’s flexible design makes it suitable for a wide range of additional image analysis applications across biomedical research.
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              ImageJ2: ImageJ for the next generation of scientific image data

              Background ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software’s ability to handle the requirements of modern science. Results We rewrote the entire ImageJ codebase, engineering a redesigned plugin mechanism intended to facilitate extensibility at every level, with the goal of creating a more powerful tool that continues to serve the existing community while addressing a wider range of scientific requirements. This next-generation ImageJ, called “ImageJ2” in places where the distinction matters, provides a host of new functionality. It separates concerns, fully decoupling the data model from the user interface. It emphasizes integration with external applications to maximize interoperability. Its robust new plugin framework allows everything from image formats, to scripting languages, to visualization to be extended by the community. The redesigned data model supports arbitrarily large, N-dimensional datasets, which are increasingly common in modern image acquisition. Despite the scope of these changes, backwards compatibility is maintained such that this new functionality can be seamlessly integrated with the classic ImageJ interface, allowing users and developers to migrate to these new methods at their own pace. Conclusions Scientific imaging benefits from open-source programs that advance new method development and deployment to a diverse audience. ImageJ has continuously evolved with this idea in mind; however, new and emerging scientific requirements have posed corresponding challenges for ImageJ’s development. The described improvements provide a framework engineered for flexibility, intended to support these requirements as well as accommodate future needs. Future efforts will focus on implementing new algorithms in this framework and expanding collaborations with other popular scientific software suites. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1934-z) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Journal
                Cell
                Cell
                Cell
                Cell Press
                0092-8674
                1097-4172
                27 May 2021
                27 May 2021
                : 184
                : 11
                : 2860-2877.e22
                Affiliations
                [1 ]Max Planck Institute for Biophysical Chemistry, 37077 Göttingen, Germany
                [2 ]Wellcome Centre for Mitochondrial Research, Biosciences Institute, Newcastle University, NE1 4EP Newcastle upon Tyne, UK
                [3 ]Institute of Farm Animal Genetics, Biotechnology, Friedrich-Loeffler-Institute, Mariensee, 31535 Neustadt, Germany
                [4 ]Bourn Hall Clinic, CB23 2TN Cambridge, UK
                [5 ]Newcastle Fertility Centre at Life, Newcastle upon Tyne Hospitals NHS Foundation Trust, NE1 4EP Newcastle upon Tyne, UK
                Author notes
                []Corresponding author melina.schuh@ 123456mpibpc.mpg.de
                [6]

                Present address: Hannover Medical University, Clinic for Gastroenterology, Hepatology, Endocrinology/TwinCore, 30625 Hannover, Germany

                [7]

                These authors contributed equally

                [8]

                Lead contact

                Article
                S0092-8674(21)00492-X
                10.1016/j.cell.2021.04.013
                8162515
                33964210
                2ed21437-8c47-4cfe-beca-2284d4ea90fe
                © 2021 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 11 March 2020
                : 5 February 2021
                : 8 April 2021
                Categories
                Article

                Cell biology
                aneuploidy,human embryo,fertilization,chromosome segregation,genome organization,centrosomes,microtubules,spindle,nuclear pore complex,dynein

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