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      The role of polycystic kidney disease-like homologs in planarian nervous system regeneration and function

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          Abstract

          Planarians are an excellent model for investigating molecular mechanisms necessary for regenerating a functional nervous system. Numerous studies have led to the generation of extensive genomic resources, especially whole-animal single-cell RNA-seq resources. These have facilitated in silico predictions of neuronal subtypes, many of which have been anatomically mapped by in situ hybridization. However, our knowledge of the function of dozens of neuronal subtypes remains poorly understood. Previous investigations identified that polycystic kidney disease (pkd)-like genes in planarians are strongly expressed in sensory neurons and have roles in mechanosensation. Here, we examine the expression and function of all the pkd genes found in the Schmidtea mediterranea genome and map their expression in the asexual and hermaphroditic strains. Using custom behavioral assays, we test the function of pkd genes in response to mechanical stimulation and in food detection. Our work provides insight into the physiological function of sensory neuron populations and protocols for creating inexpensive automated setups for acquiring and analyzing mechanosensory stimulation in planarians.

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          Most cited references53

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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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            MRBAYES: Bayesian inference of phylogenetic trees

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              Polycystic kidney disease.

              A number of inherited disorders result in renal cyst development. The most common form, autosomal dominant polycystic kidney disease (ADPKD), is a disorder most often diagnosed in adults and caused by mutation in PKD1 or PKD2. The PKD1 protein, polycystin-1, is a large receptor-like protein, whereas polycystin-2 is a transient receptor potential channel. The polycystin complex localizes to primary cilia and may act as a mechanosensor essential for maintaining the differentiated state of epithelia lining tubules in the kidney and biliary tract. Elucidation of defective cellular processes has highlighted potential therapies, some of which are now being tested in clinical trials. ARPKD is the neonatal form of PKD and is associated with enlarged kidneys and biliary dysgenesis. The disease phenotype is highly variable, ranging from neonatal death to later presentation with minimal kidney disease. ARPKD is caused by mutation in PKHD1, and two truncating mutations are associated with neonatal lethality. The ARPKD protein, fibrocystin, is localized to cilia/basal body and complexes with polycystin-2. Rare, syndromic forms of PKD also include defects of the eye, central nervous system, digits, and/or neural tube and highlight the role of cilia and pathways such as Wnt and Hh in their pathogenesis.
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                Author and article information

                Journal
                bioRxiv
                BIORXIV
                bioRxiv
                Cold Spring Harbor Laboratory
                2692-8205
                22 July 2024
                : 2024.07.17.603829
                Affiliations
                [1 ]Department of Biology, San Diego State University, 5500 Campanile Dr., San Diego, CA 92182-4614, USA
                Author notes
                [* ] Correspondence: Ricardo M. Zayas, rzayas@ 123456sdsu.edu
                Author information
                http://orcid.org/0000-0002-6272-0519
                Article
                10.1101/2024.07.17.603829
                11291080
                39091889
                722cc0e9-eeb1-4391-aaa8-29db6f8999a4

                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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