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      Transcriptome profiling of the Caenorhabditis elegans intestine reveals that ELT-2 negatively and positively regulates intestinal gene expression within the context of a gene regulatory network

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          Abstract

          ELT-2 is the major transcription factor (TF) required for Caenorhabditis elegans intestinal development. ELT-2 expression initiates in embryos to promote development and then persists after hatching through the larval and adult stages. Though the sites of ELT-2 binding are characterized and the transcriptional changes that result from ELT-2 depletion are known, an intestine-specific transcriptome profile spanning developmental time has been missing. We generated this dataset by performing Fluorescence Activated Cell Sorting on intestine cells at distinct developmental stages. We analyzed this dataset in conjunction with previously conducted ELT-2 studies to evaluate the role of ELT-2 in directing the intestinal gene regulatory network through development. We found that only 33% of intestine-enriched genes in the embryo were direct targets of ELT-2 but that number increased to 75% by the L3 stage. This suggests additional TFs promote intestinal transcription especially in the embryo. Furthermore, only half of ELT-2's direct target genes were dependent on ELT-2 for their proper expression levels, and an equal proportion of those responded to elt-2 depletion with over-expression as with under-expression. That is, ELT-2 can either activate or repress direct target genes. Additionally, we observed that ELT-2 repressed its own promoter, implicating new models for its autoregulation. Together, our results illustrate that ELT-2 impacts roughly 20–50% of intestine-specific genes, that ELT-2 both positively and negatively controls its direct targets, and that the current model of the intestinal regulatory network is incomplete as the factors responsible for directing the expression of many intestinal genes remain unknown.

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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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              featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

              Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                Genetics
                Genetics
                genetics
                Genetics
                Oxford University Press (US )
                0016-6731
                1943-2631
                August 2023
                15 May 2023
                15 May 2023
                : 224
                : 4
                : iyad088
                Affiliations
                Department of Biochemistry and Molecular Biology, Colorado State University , Fort Collins, CO 80523, USA
                Department of Biochemistry and Molecular Biology, Colorado State University , Fort Collins, CO 80523, USA
                Department of Biochemistry and Molecular Biology, Colorado State University , Fort Collins, CO 80523, USA
                Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health , Bethesda, MD 20892, USA
                Department of Biochemistry and Molecular Biology, Colorado State University , Fort Collins, CO 80523, USA
                Department of Biochemistry and Molecular Biology, Colorado State University , Fort Collins, CO 80523, USA
                Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA 19104, USA
                Department of Biochemistry and Molecular Biology, Colorado State University , Fort Collins, CO 80523, USA
                Department of Cell and Molecular Biology, Colorado State University , Fort Collins, CO 80523, USA
                Department of Biochemistry and Molecular Biology, Colorado State University , Fort Collins, CO 80523, USA
                College of Veterinary Medicine and Biomedical Sciences, Colorado State University , Fort Collins, CO 80523, USA
                Department of Biochemistry and Molecular Biology, Colorado State University , Fort Collins, CO 80523, USA
                Department of Biochemistry and Molecular Biology, Colorado State University , Fort Collins, CO 80523, USA
                Department of Biochemistry and Molecular Biology, Colorado State University , Fort Collins, CO 80523, USA
                Author notes
                Corresponding author: Colorado State University, 1870 Campus Delivery; 200 W. Lake St., Email: erin.nishimura@ 123456colostate.edu

                Conflicts of interest statement The author(s) declare no conflict of interest.

                Author information
                https://orcid.org/0000-0002-3384-212X
                https://orcid.org/0000-0003-1601-1612
                https://orcid.org/0000-0003-3281-2807
                https://orcid.org/0000-0002-3323-8379
                https://orcid.org/0000-0003-1134-1890
                https://orcid.org/0000-0002-2818-6711
                https://orcid.org/0000-0002-2664-6892
                https://orcid.org/0000-0003-3267-669X
                https://orcid.org/0000-0002-1252-267X
                https://orcid.org/0000-0002-4313-4573
                Article
                iyad088
                10.1093/genetics/iyad088
                10411582
                37183501
                77f6e519-09c8-4b6b-8fa1-22fd7862bda0
                © The Author(s) 2023. Published by Oxford University Press on behalf of The Genetics Society of America.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 06 March 2023
                : 30 April 2023
                : 09 June 2023
                Page count
                Pages: 19
                Funding
                Funded by: National Institutes of Health, DOI 10.13039/100000002;
                Award ID: R35GM124877
                Funded by: National Science Foundation, DOI 10.13039/100000001;
                Award ID: CAREER-2143849
                Funded by: Boettcher Foundation, DOI 10.13039/100005508;
                Funded by: Erin Osborne Nishimura;
                Funded by: Bridge to Doctorate Program;
                Funded by: Colorado State University, DOI 10.13039/100007235;
                Award ID: 1612513
                Categories
                Investigation
                AcademicSubjects/SCI01180
                AcademicSubjects/SCI01140

                Genetics
                c. elegans,intestine,elt-2,rna-seq,chip-seq,transcription factor,organogenesis,master regulator,facs
                Genetics
                c. elegans, intestine, elt-2, rna-seq, chip-seq, transcription factor, organogenesis, master regulator, facs

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