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      Annelid adult cell type diversity and their pluripotent cellular origins

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          Abstract

          Many annelids can regenerate missing body parts or reproduce asexually, generating all cell types in adult stages. However, the putative adult stem cell populations involved in these processes, and the diversity of cell types generated by them, are still unknown. To address this, we recover 75,218 single cell transcriptomes of the highly regenerative and asexually-reproducing annelid Pristina leidyi. Our results uncover a rich cell type diversity including annelid specific types as well as novel types. Moreover, we characterise transcription factors and gene networks that are expressed specifically in these populations. Finally, we uncover a broadly abundant cluster of putative stem cells with a pluripotent signature. This population expresses well-known stem cell markers such as vasa, piwi and nanos homologues, but also shows heterogeneous expression of differentiated cell markers and their transcription factors. We find conserved expression of pluripotency regulators, including multiple chromatin remodelling and epigenetic factors, in piwi+ cells. Finally, lineage reconstruction analyses reveal computational differentiation trajectories from piwi+ cells to diverse adult types. Our data reveal the cell type diversity of adult annelids by single cell transcriptomics and suggest that a piwi+ cell population with a pluripotent stem cell signature is associated with adult cell type differentiation.

          Abstract

          The cellular atlas of Pristina leidyi reveals cell type diversity in adult annelids by single cell transcriptomics, discovering several novel cell types and suggesting a pluripotent stem cell signature associated with adult cell type differentiation

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          Most cited references116

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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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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              STAR: ultrafast universal RNA-seq aligner.

              Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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                Author and article information

                Contributors
                patricia.alvarez@uam.es
                bdozpolat@wustl.edu
                jsolana@brookes.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                12 April 2024
                12 April 2024
                2024
                : 15
                : 3194
                Affiliations
                [1 ]Department of Biological and Medical Sciences, Oxford Brookes University, ( https://ror.org/04v2twj65) Oxford, UK
                [2 ]Centro de Investigación en Biodiversidad y Cambio Global (CIBC-UAM) & Departamento de Biología (Zoología), Facultad de Ciencias, Universidad Autónoma de Madrid, ( https://ror.org/01cby8j38) Madrid, Spain
                [3 ]Eugene Bell Center for Regenerative Biology and Tissue Engineering, Marine Biological Laboratory, ( https://ror.org/046dg4z72) 7 MBL Street, Woods Hole, MA 05432 USA
                [4 ]Department of Biology, Washington University in St. Louis. 1 Brookings Dr. Saint Louis, ( https://ror.org/01yc7t268) Saint Louis, MO 63130 USA
                [5 ]Department of Biology, University of Maryland, ( https://ror.org/047s2c258) College Park, MD 20742 USA
                [6 ]Department of Biochemistry, University of Otago, ( https://ror.org/01jmxt844) P.O. Box 56, Dunedin, Aotearoa New Zealand
                [7 ]Present Address: Living Systems Institute, University of Exeter, ( https://ror.org/03yghzc09) Exeter, UK
                Author information
                http://orcid.org/0000-0001-9472-2378
                http://orcid.org/0000-0001-9106-3557
                http://orcid.org/0000-0001-5448-1039
                http://orcid.org/0000-0001-8834-4956
                http://orcid.org/0000-0003-2082-3939
                http://orcid.org/0000-0003-4816-4103
                http://orcid.org/0000-0002-1900-965X
                http://orcid.org/0000-0002-6770-3929
                Article
                47401
                10.1038/s41467-024-47401-6
                11014941
                38609365
                3e5c7a8c-1acc-4bf7-bc88-78ed55e4c9e0
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 28 July 2023
                : 27 March 2024
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000265, RCUK | Medical Research Council (MRC);
                Award ID: MR/S007849/1
                Award ID: MR/W017539/1
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000288, Royal Society;
                Award ID: RGS\R1\191278
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000057, U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS);
                Award ID: 1R35GM138008-01
                Award Recipient :
                Categories
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                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                regeneration,evolutionary developmental biology,adult stem cells
                Uncategorized
                regeneration, evolutionary developmental biology, adult stem cells

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