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      Ehf and Fezf2 regulate late medullary thymic epithelial cell and thymic tuft cell development

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          Abstract

          Thymic epithelial cells are indispensable for T cell maturation and selection and the induction of central immune tolerance. The self-peptide repertoire expressed by medullary thymic epithelial cells is in part regulated by the transcriptional regulator Aire (Autoimmune regulator) and the transcription factor Fezf2. Due to the high complexity of mTEC maturation stages (i.e., post-Aire, Krt10+ mTECs, and Dclk1+ Tuft mTECs) and the heterogeneity in their gene expression profiles (i.e., mosaic expression patterns), it has been challenging to identify the additional factors complementing the transcriptional regulation. We aimed to identify the transcriptional regulators involved in the regulation of mTEC development and self-peptide expression in an unbiased and genome-wide manner. We used ATAC footprinting analysis as an indirect approach to identify transcription factors involved in the gene expression regulation in mTECs, which we validated by ChIP sequencing. This study identifies Fezf2 as a regulator of the recently described thymic Tuft cells (i.e., Tuft mTECs). Furthermore, we identify that transcriptional regulators of the ELF, ESE, ERF, and PEA3 subfamily of the ETS transcription factor family and members of the Krüppel-like family of transcription factors play a role in the transcriptional regulation of genes involved in late mTEC development and promiscuous gene expression.

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          Most cited references88

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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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            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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              Fast gapped-read alignment with Bowtie 2.

              As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                14 February 2024
                2023
                : 14
                : 1277365
                Affiliations
                [1] 1Institute for Theoretical Physics, Heidelberg University , Heidelberg, Germany
                [2] 2Bioinformatics Core, Harvard T.H. Chan School of Public Health , Boston, MA, United States
                [3] 3Department of Genetics, Stanford University, School of Medicine , Stanford, CA, United States
                [4] 4Stanford Genome Technology Center, Stanford University , Stanford, CA, United States
                [5] 5Diabetes Center, University of California, San Francisco (UCSF) , San Francisco, CA, United States
                [6] 6Genome Biology Unit, European Molecular Biology Laboratory (EMBL) , Heidelberg, Germany
                [7] 7Department of Immunology & HMS Center for Immune Imaging, Harvard Medical School , Boston, MA, United States
                [8] 8The Ragon Institute of MGH, MIT and Harvard , Cambridge, MA, United States
                [9] 9Pharmacological Institute, Biochemical Pharmacological Center, University of Marburg , Marburg, Germany
                Author notes

                Edited by: Anne Fletcher, Monash University, Australia

                Reviewed by: Izumi Ohigashi, Tokushima University, Japan

                Takeshi Nitta, The University of Tokyo, Japan

                *Correspondence: Kristin Rattay, kristin.rattay@ 123456uni-marburg.de

                †Present address: Sören Lammers, d-fine GmbH, Frankfurt, Germany

                ‡ORCID: Victor Barrera, orcid.org/0000-0003-0590-4634; Lars Steinmetz, orcid.org/0000-0002-3962-2865; Ulrich H. von Andrian, orcid.org/0000-0003-4231-2283; Kristin Rattay, orcid.org/0000-0003-3503-2136

                Article
                10.3389/fimmu.2023.1277365
                10901246
                38420512
                d4fd314e-5e60-4795-be53-9fc5f71338e1
                Copyright © 2024 Lammers, Barrera, Brennecke, Miller, Yoon, Balolong, Anderson, Ho Sui, Steinmetz, von Andrian and Rattay

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 14 August 2023
                : 29 December 2023
                Page count
                Figures: 6, Tables: 0, Equations: 0, References: 88, Pages: 18, Words: 10740
                Funding
                The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by the US National Institutes of Health grants P01 HG000205 and R01 GM068717 (PB and LS), AI155865 and HMS Center for Immune Imaging (UA), the University of Marburg (KR). The work by VB and SH was funded in part by a Harvard Medical School Foundry award. Open access funding was provided by the Open Access Publishing Fund of the Philipps-Universität Marburg with the support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation).
                Categories
                Immunology
                Original Research
                Custom metadata
                Immunological Tolerance and Regulation

                Immunology
                thymus,central tolerance,medullary thymic epithelial cell,tuft cells,fezf2,ehf
                Immunology
                thymus, central tolerance, medullary thymic epithelial cell, tuft cells, fezf2, ehf

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