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      Synaptic architecture of leg and wing premotor control networks in Drosophila

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          Is Open Access

          SciPy 1.0: fundamental algorithms for scientific computing in Python

          SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
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            Fly Cell Atlas: A single-nucleus transcriptomic atlas of the adult fruit fly

            For more than 100 years, the fruit fly Drosophila melanogaster has been one of the most studied model organisms. Here, we present a single-cell atlas of the adult fly, Tabula Drosophilae , that includes 580,000 nuclei from 15 individually dissected sexed tissues as well as the entire head and body, annotated to >250 distinct cell types. We provide an in-depth analysis of cell type–related gene signatures and transcription factor markers, as well as sexual dimorphism, across the whole animal. Analysis of common cell types between tissues, such as blood and muscle cells, reveals rare cell types and tissue-specific subtypes. This atlas provides a valuable resource for the Drosophila community and serves as a reference to study genetic perturbations and disease models at single-cell resolution. The fruit fly Drosophila melanogaster has served as a premier model organism for discovering fundamental and evolutionarily conserved biological mechanisms. Combining recent advances in single-cell sequencing with powerful fly genetic tools holds great promise for making further discoveries. Li et al . present a single-cell atlas of the entire adult fly that includes 580,000 cells and more than 250 annotated cell types. Cells from the head and body recapitulated cell types from 15 dissected tissues. In-depth analyses revealed rare cell types, cell-type-specific gene signatures, and sexual dimorphism. This atlas provides a resource for the Drosophila community to study genetic perturbations and diseases at single-cell resolution. —BAP A single-nucleus transcriptomic map reveals more than 250 distinct cell types in the entire adult Drosophila melanogaster . INTRODUCTION Drosophila melanogaster has had a fruitful history in biological research because it has contributed to many key discoveries in genetics, development, and neurobiology. The fruit fly genome contains ~14,000 protein-coding genes, ~63% of which have human orthologs. Single-cell RNA-sequencing has recently been applied to multiple Drosophila tissues and developmental stages. However, these data have been generated by different laboratories on different genetic backgrounds with different dissociation protocols and sequencing platforms, which has hindered the systematic comparison of gene expression across cells and tissues. RATIONALE We aimed to establish a cell atlas for the entire adult Drosophila with the same genetic background, dissociation protocol, and sequencing platform to (i) obtain a comprehensive categorization of cell types, (ii) integrate single-cell transcriptome data with existing knowledge about gene expression and cell types, (iii) systematically compare gene expression across the entire organism and between males and females, and (iv) identify cell type–specific markers across the entire organism. We chose single-nucleus RNA-sequencing (snRNA-seq) to circumvent the difficulties of dissociating cells that are embedded in the cuticle (e.g., sensory neurons) or that are multinucleated (e.g., muscle cells). We took two complementary strategies: sequencing nuclei from dissected tissues to know the identity of the tissue source and sequencing nuclei from the entire head and body to ensure that all cells are sampled. Experts from 40 laboratories participated in crowd annotation to assign transcriptomic cell types with the best knowledge available. RESULTS We sequenced 570,000 cells using droplet-based 10x Genomics from 15 dissected tissues as well as whole heads and bodies, separately in females and males. We also sequenced 10,000 cells from dissected tissues using the plate-based Smart-seq2 platform, providing deeper coverage per cell. We developed reproducible analysis pipelines using NextFlow and implemented a distributed cell-type annotation system with controlled vocabularies in SCope. Crowd-based annotations of transcriptomes from dissected tissues identified 17 main cell categories and 251 detailed cell types linked to FlyBase ontologies. Many of these cell types are characterized for the first time, either because they emerged only after increasing cell coverage or because they reside in tissues that had not been previously subjected to scRNA-seq. The excellent correspondence of transcriptomic clusters from whole body and dissected tissues allowed us to transfer annotations and identify a few cuticular cell types not detected in individual tissues. Cross-tissue analysis revealed location-specific subdivisions of muscle cells and heterogeneity within blood cells. We then determined cell type–specific marker genes and transcription factors with different specificity levels, enabling the construction of gene regulatory networks. Finally, we explored sexual dimorphism, finding a link between sex-biased expression and the presence of doublesex , and investigated tissue dynamics through trajectory analyses. CONCLUSION Our Fly Cell Atlas (FCA) constitutes a valuable resource for the Drosophila community as a reference for studies of gene function at single-cell resolution. All the FCA data are freely available for further analysis through multiple portals and can be downloaded for custom analyses using other single-cell tools. The ability to annotate cell types by sequencing the entire head and body will facilitate the use of Drosophila in the study of biological processes and in modeling human diseases at a whole-organism level with cell-type resolution. All data with annotations can be accessed from www.flycellatlas.org , which provides links to SCope, ASAP, and cellxgene portals.
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              A limited set of muscle synergies for force control during a postural task.

              Recently developed computational techniques have been used to reduce muscle activation patterns of high complexity to a simple synergy organization and to bring new insights to the long-standing degrees of freedom problem in motor control. We used a nonnegative factorization approach to identify muscle synergies during postural responses in the cat and to examine the functional significance of such synergies for natural behaviors. We hypothesized that the simplification of neural control afforded by muscle synergies must be matched by a similar reduction in degrees of freedom at the biomechanical level. Electromyographic data were recorded from 8-15 hindlimb muscles of cats exposed to 16 directions of support surface translation. Results showed that as few as four synergies could account for >95% of the automatic postural response across all muscles and all directions. Each synergy was activated for a specific set of perturbation directions, and moreover, each was correlated with a unique vector of endpoint force under the limb. We suggest that, within the context of active balance control, postural synergies reflect a neural command signal that specifies endpoint force of a limb.
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                Journal
                Nature
                Nature
                Springer Science and Business Media LLC
                0028-0836
                1476-4687
                June 26 2024
                Article
                10.1038/s41586-024-07600-z
                2212d2bc-9403-4b23-990d-7fdb7c4cfe36
                © 2024

                https://www.springernature.com/gp/researchers/text-and-data-mining

                https://www.springernature.com/gp/researchers/text-and-data-mining

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