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      Transcriptomic Analysis of Naïve Human Embryonic Stem Cells Cultured in Three-Dimensional PEG Scaffolds

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          Abstract

          Naïve human embryonic stem cells (ESCs) are characterized by improved viability, proliferation, and differentiation capacity in comparison to traditionally derived primed human ESCs. However, currently used two-dimensional (2-D) cell culture techniques fail to mimic the three-dimensional (3-D) in vivo microenvironment, altering morphological and molecular characteristics of ESCs. Here, we describe the use of 3-D self-assembling scaffolds that support growth and maintenance of the naïve state characteristics of ESC line, Elf1. Scaffolds were formed via a Michael addition reaction upon the combination of two 8-arm polyethylene glycol (PEG) polymers functionalized with thiol (PEG-8-SH) and acrylate (PEG-8-Acr) end groups. 3-D scaffold environment maintained the naïve state and supported the long-term growth of ESCs. RNA-sequencing demonstrated significant changes in gene expression profiles between 2-D and 3-D grown cells. Gene ontology analysis revealed upregulation of biological processes involved in the regulation of transcription and translation, extracellular matrix organization, and chromatin remodeling in 3-D grown cells. 3-D culture conditions also induced upregulation of genes associated with Wnt and focal adhesion signaling, while p53 signaling pathway associated genes were downregulated. Our findings, for the first time, provide insight into the possible mechanisms of self-renewal of naïve ESCs stimulated by the transduction of mechanical signals from the 3-D microenvironment.

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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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            KEGG: kyoto encyclopedia of genes and genomes.

            M Kanehisa (2000)
            KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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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

                Journal
                Biomolecules
                Biomolecules
                biomolecules
                Biomolecules
                MDPI
                2218-273X
                28 December 2020
                January 2021
                : 11
                : 1
                : 21
                Affiliations
                [1 ]Department of Biological Sciences, Oakland University, Rochester, MI 48309, USA; cmmckee@ 123456oakland.edu (C.M.); brown3@ 123456oakland.edu (C.B.); sbakshi@ 123456umich.edu (S.B.); keeganjwalker22@ 123456gmail.com (K.W.); govind@ 123456oakland.edu (C.K.G.)
                [2 ]OU-WB Institute for Stem Cell and Regenerative Medicine, Rochester, MI 48309, USA
                Author notes
                [* ]Correspondence: chaudhry@ 123456oakland.edu ; Tel.: +1-248-370-3350
                Author information
                https://orcid.org/0000-0002-7488-2232
                https://orcid.org/0000-0003-1692-8420
                Article
                biomolecules-11-00021
                10.3390/biom11010021
                7824559
                33379237
                b31b7629-1ffe-4acb-b32e-8a6af01f9a66
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 November 2020
                : 24 December 2020
                Categories
                Article

                three-dimensional culture,self-assembling peg scaffolds,naïve embryonic stem cells,signaling pathways,mechanotransduction

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