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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Cell Dev. Biol.</journal-id>
<journal-title>Frontiers in Cell and Developmental Biology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Cell Dev. Biol.</abbrev-journal-title>
<issn pub-type="epub">2296-634X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fcell.2021.661381</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Cell and Developmental Biology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>The Study of Alternative Splicing Events in Human Induced Pluripotent Stem Cells From a Down&#x00027;s Syndrome Patient</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Wang</surname> <given-names>Yunjie</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="author-notes" rid="fn002"><sup>&#x02020;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1239637/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Li</surname> <given-names>Zexu</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="author-notes" rid="fn002"><sup>&#x02020;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1223442/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Yang</surname> <given-names>Guanheng</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1285550/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Cai</surname> <given-names>Linlin</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1285163/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Yang</surname> <given-names>Fan</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1229260/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Zhang</surname> <given-names>Yaqiong</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1286409/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Zeng</surname> <given-names>Yitao</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Ma</surname> <given-names>Qingwen</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x0002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1288055/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Zeng</surname> <given-names>Fanyi</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="corresp" rid="c002"><sup>&#x0002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1042225/overview"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Shanghai Institute of Medical Genetics, Shanghai Children&#x00027;s Hospital, Shanghai Jiao Tong University</institution>, <addr-line>Shanghai</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>National Health Commission Key Laboratory of Embryo Molecular Biology, Shanghai Key Laboratory of Embryo and Reproduction Engineering</institution>, <addr-line>Shanghai</addr-line>, <country>China</country></aff>
<aff id="aff3"><sup>3</sup><institution>Department of Histoembryology, Genetics &#x00026; Development, Shanghai Jiao Tong University School of Medicine</institution>, <addr-line>Shanghai</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Desheng Liang, Central South University, China</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Fu Xiong, Southern Medical University, China; Feng Zhang, Fudan University, China; Guang He, Shanghai Jiao Tong University, China</p></fn>
<corresp id="c001">&#x0002A;Correspondence: Qingwen Ma <email>qwma1213&#x00040;163.com</email></corresp>
<corresp id="c002">Fanyi Zeng <email>fzeng&#x00040;VIP.163.com</email></corresp>
<fn fn-type="other" id="fn001"><p>This article was submitted to Epigenomics and Epigenetics, a section of the journal Frontiers in Cell and Developmental Biology</p></fn>
<fn fn-type="other" id="fn002"><p>&#x02020;These authors have contributed equally to this work and share first authorship</p></fn></author-notes>
<pub-date pub-type="epub">
<day>30</day>
<month>09</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>9</volume>
<elocation-id>661381</elocation-id>
<history>
<date date-type="received">
<day>30</day>
<month>01</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>16</day>
<month>03</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2021 Wang, Li, Yang, Cai, Yang, Zhang, Zeng, Ma and Zeng.</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Wang, Li, Yang, Cai, Yang, Zhang, Zeng, Ma and Zeng</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><p>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.</p></license></permissions>
<abstract><p>Down&#x00027;s syndrome (DS) is one of the most commonly known disorders with multiple congenital disabilities. Besides severe cognitive impairment and intellectual disability, individuals with DS also exhibit additional phenotypes of variable penetrance and severity, with one or more comorbid conditions, including Alzheimer&#x00027;s disease, congenital heart disease, or leukemia. Various vital genes and regulatory networks had been studied to reveal the pathogenesis of the disease. Nevertheless, very few studies have examined alternative splicing. Alternative splicing (AS) is a regulatory mechanism of gene expression when making one multi-exon protein-coding gene produce more than one unique mature mRNA. We employed the GeneChip Human Transcriptome Array 2.0 (HTA 2.0) for the global gene analysis with hiPSCs from DS and healthy individuals. Examining differentially expressed genes (DEGs) in these groups and focusing on specific transcripts with AS, 466 up-regulated and 722 down-regulated genes with AS events were identified. These genes were significantly enriched in biological processes, such as cell adhesion, cardiac muscle contraction, and immune response, through gene ontology (GO) analysis of DEGs. Candidate genes, such as <italic>FN1</italic> were further explored for potentially playing a key role in DS. This study provides important insights into the potential role that AS plays in DS.</p></abstract>
<kwd-group>
<kwd>Down&#x00027;s syndrome</kwd>
<kwd>alternative splicing</kwd>
<kwd>iPSCs</kwd>
<kwd>gene regulation</kwd>
<kwd>differentially expressed genes</kwd>
</kwd-group>
<contract-num rid="cn001">2016YFC1000503</contract-num>
<contract-sponsor id="cn001">National Science and Technology Major Project<named-content content-type="fundref-id">10.13039/501100018537</named-content></contract-sponsor>
<counts>
<fig-count count="6"/>
<table-count count="4"/>
<equation-count count="0"/>
<ref-count count="46"/>
<page-count count="13"/>
<word-count count="6718"/>
</counts>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<title>1. Introduction</title>
<p>Down&#x00027;s syndrome (DS) or trisomy 21 (OMIM &#x00023;<ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="190685">190685</ext-link>) is a well-recognized and studied complex genetic condition caused by a chromosomal disorder, namely the presence of a total or partial trisomy of chromosome 21 (HSA21). It occurs in &#x0007E;1:700&#x02013;1:1,000 newborns globally (Weijerman and de Winter, <xref ref-type="bibr" rid="B42">2010</xref>), and it is the most commonly known genetic etiology associated with moderate to severe intellectual disability. Furthermore, individuals with DS also exhibit additional phenotypes of variable penetrance and severity, with one or more comorbid conditions, including Alzheimer&#x00027;s disease, congenital heart disease, or leukemia (Ballard et al., <xref ref-type="bibr" rid="B3">2016</xref>). Further understanding of the relationship between redundant chromosome 21 and its associated diseases is expected to provide theoretical support for revealing the pathogenesis, and developing therapeutic approaches and drugs to treat DS (Ballard et al., <xref ref-type="bibr" rid="B3">2016</xref>). Moreover, due to the supernumerary copy of chromosome 21 (HSA21), some researchers hypothesized that the most dosage-sensitive genes in chromosome 21 are likely to contribute to the DS phenotype, also known as the &#x0201C;gene dosage effect&#x0201D; hypothesis (Korenberg et al., <xref ref-type="bibr" rid="B18">1994</xref>). Some results support the &#x0201C;gene dosage effect&#x0201D; hypothesis that most of the Down&#x00027;s syndrome phenotypes are related to alterations in gene expression due to the extra chromosome 21 (HSA21). However, some researchers doubted that the DS phenotype could merely be explained by gene dosage effects (Jiang et al., <xref ref-type="bibr" rid="B15">2013</xref>), the hypothesis of favor among medical geneticists. The factors influencing DS phenotypes include chromosome 21 DNA, functional elements and variability of chromosome 21, the variability of other chromosomes, chromatin structure, epigenetic modifications, stochastic events, and the environment (Antonarakis, <xref ref-type="bibr" rid="B2">2017</xref>).</p>
<p>Nevertheless, very few studies on DS to date have examined alternative splicing (AS), a widespread regulatory mechanism of gene expression and makes one multi-exon protein-coding gene capable of producing more than one unique mature mRNA. AS provides transcriptional plasticity by controlling which RNA isoforms are expressed at a given time point in a given cell type. Alternative splicing affects about 95% of mammalian genes (Pan et al., <xref ref-type="bibr" rid="B25">2008</xref>).</p>
<p>The emergence of induced pluripotent stem cells (iPSCs) provided important research tools for human disease research and drug screening (Takahashi et al., <xref ref-type="bibr" rid="B35">2007</xref>; Yu et al., <xref ref-type="bibr" rid="B45">2007</xref>). DS patient-derived induced pluripotent stem cells (DS hiPSCs) exhibit DS-like characteristics when they are induced to differentiate into somatic cells <italic>in vitro</italic> (Chou et al., <xref ref-type="bibr" rid="B7">2012</xref>; Shi et al., <xref ref-type="bibr" rid="B34">2012</xref>; Briggs et al., <xref ref-type="bibr" rid="B5">2013</xref>) and are ideal models to study the genetic mechanisms underlying DS, as well as its associated diseases (Weick et al., <xref ref-type="bibr" rid="B41">2013</xref>). Previous studies have shown that the proliferative ability of DS hiPSCs is much lower than that of normal human iPSCs (hiPSCs). This suggests that the extra chromosome 21 may also affect the biological characteristics of DS hiPSCs. However, the evidence at the molecular level is still lacking (Omori et al., <xref ref-type="bibr" rid="B24">2017</xref>). In order to further explore the critical role that key genes may play in the proliferative and developmental differences between DS hiPSCs and normal hiPSCs, as well as to reveal the related molecular mechanism, we used whole genome expression profiles to analyze and screen the differentially expressed genes, and global aberrant alternative splicing events between DS hiPSCs and normal hiPSCs.</p>
</sec>
<sec sec-type="results" id="s2">
<title>2. Results</title>
<sec>
<title>2.1. DS hiPSCs Maintain the Pluripotent State</title>
<p>To delve into whether the extra chromosome 21 affects the maintenance of pluripotency of DS hiPSCs, we primarily checked the cell morphology of DS hiPSCs and normal hiPSCs. The results showed that the DS hiPSCs exhibited pluripotent stem cells&#x00027; typical characteristics with a large nucleus and compact clone (<xref ref-type="fig" rid="F1">Figure 1A</xref>). A strong positive expression for alkaline phosphatase staining (<xref ref-type="fig" rid="F1">Figure 1B</xref>) and the results of cell immunofluorescence assays (<xref ref-type="fig" rid="F1">Figure 1C</xref>) showed no significant difference in cell morphology and surface marker expression between DS hiPSCs and normal hiPSCs. Overall, these results indicated that the maintenance of pluripotency of DS hiPSCs was similar to that of normal hiPSCs and was not significantly affected by the redundant chromosome 21.</p>
<fig id="F1" position="float">
<label>Figure 1</label>
<caption><p>Pluripotency of hiPSCs, <bold>(A)</bold> Morphological observation of DS and N (Normal) hiPSCs (100&#x000D7;, all scale bars are 500 <italic>&#x003BC;</italic>m), <bold>(B)</bold> Alkaline phosphatase staining of DS and N (Normal) hiPSCs, <bold>(C)</bold> Immunofluorescence images showing DAPI (blue), LIN28A (green), and TRA1-60 (red) expression in DS and N (Normal) hiPSCs (100&#x000D7;, all scale bars are 500 <italic>&#x003BC;</italic>m).</p></caption>
<graphic xlink:href="fcell-09-661381-g0001.tif"/>
</fig>
</sec>
<sec>
<title>2.2. Differentially Expressed Genes of DS and Healthy hiPSCs</title>
<p>As it is known that trisomy 21 causes alterations to both stem and precursor cells (Liu et al., <xref ref-type="bibr" rid="B20">2015</xref>), it is also possible that the alteration of the proliferative ability of DS hiPSCs is caused by the differences in expression of genes and the aberrant AS events. To determine if this is the case, we used the GeneChip Human Transcriptome Array 2.0 (HTA 2.0) for the global gene analysis with hiPSCs from DS and healthy individuals. We examined differentially expressed genes (DEGs) in these groups focusing on specific transcripts with AS events. The quality control analyses of the HTA 2.0 data highlight the correct segregation of samples from each cell line (<xref ref-type="fig" rid="F2">Figure 2</xref>).</p>
<fig id="F2" position="float">
<label>Figure 2</label>
<caption><p>Quality control for the HTA 2.0 data, <bold>(A)</bold> the correlation matrix heatmap of samples, <bold>(B)</bold> the heatmap of differential expression probe sets.</p></caption>
<graphic xlink:href="fcell-09-661381-g0002.tif"/>
</fig>
<p>A more detailed analysis of HTA 2.0 datasets revealed, the total differentially expressed genes are 466 up-regulated and 722 down-regulated genes (in total 1,188 significantly differentially expressed genes) in DS hiPSCs, compared with normal hiPSCs (<xref ref-type="fig" rid="F3">Figure 3</xref>). By summarizing the distribution of differentially expressed genes on each chromosome and the proportion of coding genes in the chromosome, we found that the proportion of up-regulated genes on chromosome 21 (5.20%) was significantly higher than that on the other chromosomes (0&#x02013;1.79%), which showed a gene dosage effect of the genes on chromosome 21. This result is consistent with previous studies of DS somatic cells that demonstrated that the redundant chromosome 21 leads to gene dosage effects (Moldrich et al., <xref ref-type="bibr" rid="B21">2007</xref>; Nawa et al., <xref ref-type="bibr" rid="B22">2019</xref>).</p>
<fig id="F3" position="float">
<label>Figure 3</label>
<caption><p>Analysis of global gene expression profile, <bold>(A)</bold> Differentially expressed genes (DS vs. Normal iPSCs, red and green represent up-regulated and down-regulated genes, respectively), the expression analysis settings: Gene-Level Fold Change &#x0003C; &#x02212;2 or &#x0003E; 2, Gene-Level <italic>P</italic>-Value &#x0003C; 0.01, <bold>(B)</bold> proportion of Coding and Non-Coding in the Up-Regulated and Down-Regulated genes, Filter criteria: Fold Change: &#x0003E; 2 or &#x0003C; &#x02212;2, <italic>P</italic>-value: &#x0003C; 0.01, <bold>(C)</bold> Volcano map of differentially expressed genes (DS vs. Normal iPSCs, red and violet represent up-regulated and down-regulated genes, respectively).</p></caption>
<graphic xlink:href="fcell-09-661381-g0003.tif"/>
</fig>
<p><xref ref-type="table" rid="T1">Tables 1</xref> and <xref ref-type="table" rid="T2">2</xref> list the top 10 up-regulated and down-regulated genes in DS hiPSCs sorted by the <italic>P</italic>-value, respectively. The up-regulated <italic>H1-6</italic> is a member of the histone H1 family. The linker histone, H1, interacts with linker DNA between nucleosomes and functions in chromatin compaction into higher-order structures. The down-regulated <italic>H3C11</italic> and <italic>H4C13</italic> are members of the histone H3 and H4 families, respectively, which are essential nuclear proteins responsible for the nucleosome structure of the chromosomal fiber in eukaryotes. The up- and down-regulation of these genes may affect the compaction of chromatin and the higher-order structures of chromosomes in DS hiPSCs, leading to the instability of chromosomes and alternative modifications of histones resulting in the aberrant regulation of gene expression. <italic>DYRK1A</italic>, a gene coding for a kinase known to regulate splicing factors that maps to chromosome 21 (Qian et al., <xref ref-type="bibr" rid="B28">2011</xref>), was identified as an up-regulated gene in DS hiPSCs. The aberrant expression of this regulator of splicing factors may lead to splicing changes in the trisomic cells.</p>
<table-wrap position="float" id="T1">
<label>Table 1</label>
<caption><p>Up-regulated genes in DS hiPSCs (Sort by <italic>P</italic>-value, and only the top 10 were listed).</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th/>
<th valign="top" align="center"><bold>logFC</bold></th>
<th valign="top" align="center"><bold>AveExpr</bold></th>
<th valign="top" align="center"><bold><italic>t</italic></bold></th>
<th valign="top" align="center"><bold><italic>P</italic>-value</bold></th>
<th valign="top" align="center"><bold>Adj. <italic>P</italic>-value</bold></th>
<th valign="top" align="center"><bold>B</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left"><italic>LINC02864</italic></td>
<td valign="top" align="center">2.274</td>
<td valign="top" align="center">4.758</td>
<td valign="top" align="center">36.646</td>
<td valign="top" align="center">5.880E-09</td>
<td valign="top" align="center">1.730E-05</td>
<td valign="top" align="center">10.570</td>
</tr>
<tr>
<td valign="top" align="left"><italic>MT1G</italic></td>
<td valign="top" align="center">2.166</td>
<td valign="top" align="center">7.572</td>
<td valign="top" align="center">14.490</td>
<td valign="top" align="center">2.690E-06</td>
<td valign="top" align="center">6.171E-04</td>
<td valign="top" align="center">5.561</td>
</tr>
<tr>
<td valign="top" align="left"><italic>MT2P1</italic></td>
<td valign="top" align="center">1.865</td>
<td valign="top" align="center">9.086</td>
<td valign="top" align="center">31.572</td>
<td valign="top" align="center">1.580E-08</td>
<td valign="top" align="center">3.290E-05</td>
<td valign="top" align="center">9.944</td>
</tr>
<tr>
<td valign="top" align="left"><italic>DDR2</italic></td>
<td valign="top" align="center">1.808</td>
<td valign="top" align="center">5.362</td>
<td valign="top" align="center">29.147</td>
<td valign="top" align="center">2.690E-08</td>
<td valign="top" align="center">5.040E-05</td>
<td valign="top" align="center">9.575</td>
</tr>
<tr>
<td valign="top" align="left"><italic>ODC1</italic></td>
<td valign="top" align="center">1.681</td>
<td valign="top" align="center">8.050</td>
<td valign="top" align="center">24.326</td>
<td valign="top" align="center">8.930E-08</td>
<td valign="top" align="center">1.054E-04</td>
<td valign="top" align="center">8.661</td>
</tr>
<tr>
<td valign="top" align="left"><italic>H1-6</italic></td>
<td valign="top" align="center">1.647</td>
<td valign="top" align="center">6.121</td>
<td valign="top" align="center">14.977</td>
<td valign="top" align="center">2.170E-06</td>
<td valign="top" align="center">5.613E-04</td>
<td valign="top" align="center">5.775</td>
</tr>
<tr>
<td valign="top" align="left"><italic>RWDD2B</italic></td>
<td valign="top" align="center">1.643</td>
<td valign="top" align="center">4.647</td>
<td valign="top" align="center">36.150</td>
<td valign="top" align="center">6.430E-09</td>
<td valign="top" align="center">1.750E-05</td>
<td valign="top" align="center">10.516</td>
</tr>
<tr>
<td valign="top" align="left"><italic>ARRDC3</italic></td>
<td valign="top" align="center">1.627</td>
<td valign="top" align="center">5.878</td>
<td valign="top" align="center">35.191</td>
<td valign="top" align="center">7.690E-09</td>
<td valign="top" align="center">1.940E-05</td>
<td valign="top" align="center">10.408</td>
</tr>
<tr>
<td valign="top" align="left"><italic>GTF2H2B</italic></td>
<td valign="top" align="center">1.578</td>
<td valign="top" align="center">5.973</td>
<td valign="top" align="center">12.428</td>
<td valign="top" align="center">7.250E-06</td>
<td valign="top" align="center">1.025E-03</td>
<td valign="top" align="center">4.557</td>
</tr>
<tr>
<td valign="top" align="left"><italic>RNU5A-8P</italic></td>
<td valign="top" align="center">1.539</td>
<td valign="top" align="center">7.621</td>
<td valign="top" align="center">17.312</td>
<td valign="top" align="center">8.400E-07</td>
<td valign="top" align="center">3.361E-04</td>
<td valign="top" align="center">6.689</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap position="float" id="T2">
<label>Table 2</label>
<caption><p>Down-regulated genes in DS hiPSCs (Sort by <italic>P</italic>-value, and only the top 10 were listed).</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th/>
<th valign="top" align="center"><bold>logFC</bold></th>
<th valign="top" align="center"><bold>AveExpr</bold></th>
<th valign="top" align="center"><bold><italic>t</italic></bold></th>
<th valign="top" align="center"><bold><italic>P</italic>-value</bold></th>
<th valign="top" align="center"><bold>Adj. <italic>P</italic>-value</bold></th>
<th valign="top" align="center"><bold>B</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left"><italic>DNAJC15</italic></td>
<td valign="top" align="center">&#x02212;2.474</td>
<td valign="top" align="center">5.292</td>
<td valign="top" align="center">&#x02212;48.004</td>
<td valign="top" align="center">9.730E-10</td>
<td valign="top" align="center">1.090E-05</td>
<td valign="top" align="center">11.492</td>
</tr>
<tr>
<td valign="top" align="left"><italic>LINC02335</italic></td>
<td valign="top" align="center">&#x02212;2.408</td>
<td valign="top" align="center">4.742</td>
<td valign="top" align="center">&#x02212;40.941</td>
<td valign="top" align="center">2.810E-09</td>
<td valign="top" align="center">1.390E-05</td>
<td valign="top" align="center">10.982</td>
</tr>
<tr>
<td valign="top" align="left"><italic>LINC02334</italic></td>
<td valign="top" align="center">&#x02212;2.316</td>
<td valign="top" align="center">4.670</td>
<td valign="top" align="center">&#x02212;28.118</td>
<td valign="top" align="center">3.420E-08</td>
<td valign="top" align="center">5.490E-05</td>
<td valign="top" align="center">9.402</td>
</tr>
<tr>
<td valign="top" align="left"><italic>TYW3</italic></td>
<td valign="top" align="center">&#x02212;2.309</td>
<td valign="top" align="center">5.466</td>
<td valign="top" align="center">&#x02212;40.264</td>
<td valign="top" align="center">3.140E-09</td>
<td valign="top" align="center">1.390E-05</td>
<td valign="top" align="center">10.923</td>
</tr>
<tr>
<td valign="top" align="left"><italic>TRPC4</italic></td>
<td valign="top" align="center">&#x02212;2.233</td>
<td valign="top" align="center">5.239</td>
<td valign="top" align="center">&#x02212;46.314</td>
<td valign="top" align="center">1.240E-09</td>
<td valign="top" align="center">1.090E-05</td>
<td valign="top" align="center">11.385</td>
</tr>
<tr>
<td valign="top" align="left"><italic>H3C11</italic></td>
<td valign="top" align="center">&#x02212;2.116</td>
<td valign="top" align="center">9.460</td>
<td valign="top" align="center">&#x02212;47.976</td>
<td valign="top" align="center">9.760E-10</td>
<td valign="top" align="center">1.090E-05</td>
<td valign="top" align="center">11.490</td>
</tr>
<tr>
<td valign="top" align="left"><italic>GPR50</italic></td>
<td valign="top" align="center">&#x02212;2.107</td>
<td valign="top" align="center">6.375</td>
<td valign="top" align="center">&#x02212;22.569</td>
<td valign="top" align="center">1.470E-07</td>
<td valign="top" align="center">1.328E-04</td>
<td valign="top" align="center">8.251</td>
</tr>
<tr>
<td valign="top" align="left"><italic>CRYZ</italic></td>
<td valign="top" align="center">&#x02212;2.084</td>
<td valign="top" align="center">5.146</td>
<td valign="top" align="center">&#x02212;43.538</td>
<td valign="top" align="center">1.860E-09</td>
<td valign="top" align="center">1.320E-05</td>
<td valign="top" align="center">11.190</td>
</tr>
<tr>
<td valign="top" align="left"><italic>H4C13</italic></td>
<td valign="top" align="center">&#x02212;2.024</td>
<td valign="top" align="center">8.563</td>
<td valign="top" align="center">&#x02212;13.833</td>
<td valign="top" align="center">3.630E-06</td>
<td valign="top" align="center">7.249E-04</td>
<td valign="top" align="center">5.260</td>
</tr>
<tr>
<td valign="top" align="left"><italic>LINC00458</italic></td>
<td valign="top" align="center">&#x02212;1.869</td>
<td valign="top" align="center">5.330</td>
<td valign="top" align="center">&#x02212;18.276</td>
<td valign="top" align="center">5.890E-07</td>
<td valign="top" align="center">2.738E-04</td>
<td valign="top" align="center">7.021</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec>
<title>2.3. Differences of AS Between DS and Healthy hiPSCs</title>
<p>We tested multiple splicing algorithms to identify differences in splicing between DS and normal hiPSCs and chose EventPointer (see Methods). Using this algorithm with the filter criteria: Exon Splicing Index &#x0003E; 2 or &#x0003C; &#x02212;2 and Exon <italic>P</italic>-value &#x0003C; 0.01, we identified 1,862 annotated genes with splicing changes when comparing DS with normal hiPSCs, half of which are the Cassette Exon events and more than one third are Alternative 5&#x02032; Donor Site events and the Alternative 3&#x02032; Acceptor Site (<xref ref-type="fig" rid="F4">Figure 4A</xref>).</p>
<fig id="F4" position="float">
<label>Figure 4</label>
<caption><p>Alternative splicing analysis, <bold>(A)</bold> Proportion of AS events, <bold>(B)</bold> Biological function enrichment analysis of the identified 1,862 annotated genes with splicing changes.</p></caption>
<graphic xlink:href="fcell-09-661381-g0004.tif"/>
</fig>
<p>To explore the effect of splicing changes on the DS hiPSCs, we performed the gene ontology (GO) and KEGG signaling pathway analysis on all selected genes with alternative splicing events (<xref ref-type="fig" rid="F4">Figure 4B</xref>). The results showed that 1,593 genes (87.8% of 1,862 annotated genes with splicing changes) are enriched in 188 biological processes, while 1,675 genes (92.3%) were enriched in 84 cellular components. We observed enrichment for 1,601 genes (88.2%) in 75 molecular functions, as well as 707 genes (39%) in 49 KEGG signaling pathways. The top 10 enrichment items are listed in <xref ref-type="fig" rid="F4">Figure 4B</xref>. Fifty-six genes with splicing changes are enriched in the cell division process; this might be the driving force behind the phenomenon that the proliferative ability of DS hiPSCs and normal hiPSCs is different.</p>
<p><xref ref-type="fig" rid="F5">Figure 5</xref> demonstrates the visualization of three genes as examples of splicing changes, namely the gene <italic>RPL39L</italic> (Ribosomal Protein L39 Like, OMIM: <ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="607547">607547</ext-link>), <italic>PARP2</italic> (Poly(ADP-Ribose) Polymerase 2, OMIM: <ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="607725">607725</ext-link>), and <italic>FN1</italic> (Fibronectin 1, OMIM: <ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="135600">135600</ext-link>).</p>
<fig id="F5" position="float">
<label>Figure 5</label>
<caption><p>Visualization of the alternative splice events of three selected genes, <bold>(A)</bold> <italic>RPL39L</italic>, <bold>(B)</bold> <italic>PARP2</italic> and <bold>(C)</bold> <italic>FN1</italic>.</p></caption>
<graphic xlink:href="fcell-09-661381-g0005.tif"/>
</fig>
</sec>
<sec>
<title>2.4. Differentially Expressed Genes of DS and Healthy hiPSCs Enriched in the Biological Processes Involved in Cell Growth</title>
<p>To explore the effect of differentially expressed genes on the DS hiPSCs, we further performed GO functional enrichment and KEGG signaling pathway analysis of 466 up-regulated and 722 down-regulated genes, respectively. The results show that 466 up-regulated genes are enriched in 64 biological processes, 34 cellular components, 18 molecular functions, and 10 KEGG signaling pathways. The 722 down-regulated genes are enriched in 50 biological processes, 27 cellular components, 16 molecular functions, and 8 KEGG signaling pathways. The top 10 enrichment items in up- and down-regulated genes are listed in <xref ref-type="table" rid="T3">Tables 3</xref> and <xref ref-type="table" rid="T4">4</xref>, respectively. Eight up-regulated genes were significantly enriched in the negative regulation of growth, which may be related to somatic cells&#x00027; lower proliferative ability and stem cells from patients with DS (Kimura et al., <xref ref-type="bibr" rid="B16">2005</xref>). Overexpression of genes related to negative growth regulation may inhibit cell proliferation, suggesting that the proliferation of DS hiPSCs may also be impaired. Nine up-regulated genes are significantly enriched in proteins targeting the mitochondria, which may affect ATP synthesis by damaging mitochondrial function, resulting in the inhibition of select cell functions (Valenti et al., <xref ref-type="bibr" rid="B37">2018</xref>). Fifteen up-regulated genes were significantly enriched in nucleosome assembly, implying that the redundant chromosome 21 may increase chromosome synthesis and assembly stress. Twenty-seven down-regulated genes were significantly enriched in cell adhesion. The impaired cell adhesion ability affects cell growth and neural cell migration during embryonic development in DS patients (Huo et al., <xref ref-type="bibr" rid="B14">2018</xref>). In nervous system development there were 17 down-regulated genes that were enriched, suggesting that the molecular regulation might be abnormal before the differentiation of DS neurocytes (Liu et al., <xref ref-type="bibr" rid="B20">2015</xref>). Moreover, in focal adhesion there were 16 down-regulated genes that were significantly enriched. This is consistent with the enrichment in cell adhesion of the GO analysis. Another 16 down-regulated genes were enriched in the PI3K Akt signaling pathway. The hyperactivity of this pathway promotes carcinogenesis (Yang et al., <xref ref-type="bibr" rid="B44">2019</xref>). The silencing of this signaling pathway in DS hiPSCs may be the critical cause of the low incidence of solid tumors in DS patients. The disorder of the whole-genome expression profile indicates that other biological characteristics of DS hiPSCs, such as proliferation and cell adhesion, are also affected.</p>
<table-wrap position="float" id="T3">
<label>Table 3</label>
<caption><p>GO and KEGG analysis of global up-regulated genes (Sort by <italic>P</italic>-value, and only the top ten GO items/pathways were listed in the table if there were more than 10).</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th valign="top" align="left"><bold>Category</bold></th>
<th valign="top" align="left"><bold>Pathway ID</bold></th>
<th valign="top" align="left"><bold>Pathway description</bold></th>
<th valign="top" align="center"><bold>Count</bold></th>
<th valign="top" align="center"><bold><italic>P</italic>-value</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0045926</td>
<td valign="top" align="left">Negative regulation of growth</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">7.25E-07</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0071294</td>
<td valign="top" align="left">Cellular response to zinc ion</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">7.25E-07</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0006626</td>
<td valign="top" align="left">Protein targeting mitochondrion</td>
<td valign="top" align="center">9</td>
<td valign="top" align="center">5.28E-06</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0071276</td>
<td valign="top" align="left">Cellular response to cadmium ion</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">6.26E-06</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0006334</td>
<td valign="top" align="left">Nucleosome assembly</td>
<td valign="top" align="center">15</td>
<td valign="top" align="center">1.19E-05</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0006418</td>
<td valign="top" align="left">tRNA aminoacylation for protein translation</td>
<td valign="top" align="center">9</td>
<td valign="top" align="center">1.91E-05</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0002381</td>
<td valign="top" align="left">Immunoglobulin production involved in immunoglobulin mediated immune response</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">0.000249</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0042594</td>
<td valign="top" align="left">Response to starvation</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">0.000521</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0002455</td>
<td valign="top" align="left">Humoral immune response mediated by circulating immunoglobulin</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">0.000835</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0007059</td>
<td valign="top" align="left">Chromosome segregation</td>
<td valign="top" align="center">9</td>
<td valign="top" align="center">0.000889</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0005829</td>
<td valign="top" align="left">Cytosol</td>
<td valign="top" align="center">150</td>
<td valign="top" align="center">6.53E-09</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0005654</td>
<td valign="top" align="left">Nucleoplasm</td>
<td valign="top" align="center">129</td>
<td valign="top" align="center">3.20E-08</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0005737</td>
<td valign="top" align="left">Cytoplasm</td>
<td valign="top" align="center">207</td>
<td valign="top" align="center">1.31E-07</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0005739</td>
<td valign="top" align="left">Mitochondrion</td>
<td valign="top" align="center">68</td>
<td valign="top" align="center">6.35E-06</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0000786</td>
<td valign="top" align="left">Nucleosome</td>
<td valign="top" align="center">13</td>
<td valign="top" align="center">1.70E-05</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0070062</td>
<td valign="top" align="left">Extracellular exosome</td>
<td valign="top" align="center">116</td>
<td valign="top" align="center">5.45E-05</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0005634</td>
<td valign="top" align="left">Nucleus</td>
<td valign="top" align="center">197</td>
<td valign="top" align="center">0.000125</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0005813</td>
<td valign="top" align="left">Centrosome</td>
<td valign="top" align="center">26</td>
<td valign="top" align="center">0.000713</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0030658</td>
<td valign="top" align="left">Transport vesicle membrane</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">0.000721</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0048471</td>
<td valign="top" align="left">Perinuclear region of cytoplasm</td>
<td valign="top" align="center">33</td>
<td valign="top" align="center">0.001252</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0005515</td>
<td valign="top" align="left">Protein binding</td>
<td valign="top" align="center">320</td>
<td valign="top" align="center">1.98E-07</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0042803</td>
<td valign="top" align="left">Protein homodimerization activity</td>
<td valign="top" align="center">39</td>
<td valign="top" align="center">0.000682</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0031492</td>
<td valign="top" align="left">Nucleosomal DNA binding</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">0.002361</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0042802</td>
<td valign="top" align="left">Identical protein binding</td>
<td valign="top" align="center">36</td>
<td valign="top" align="center">0.006196</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0098641</td>
<td valign="top" align="left">Cadherin binding involved in cell-cell adhesion</td>
<td valign="top" align="center">18</td>
<td valign="top" align="center">0.006583</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0046982</td>
<td valign="top" align="left">Protein heterodimerization activity</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">0.006996</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0042393</td>
<td valign="top" align="left">Histone binding</td>
<td valign="top" align="center">10</td>
<td valign="top" align="center">0.01105</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0004364</td>
<td valign="top" align="left">Glutathione transferase activity</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center">0.019906</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0000175</td>
<td valign="top" align="left">3&#x02032;-5&#x02032;-exoribonuclease activity</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">0.020776</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0031267</td>
<td valign="top" align="left">Small GTPase binding</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">0.020776</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa04978</td>
<td valign="top" align="left">Mineral absorption</td>
<td valign="top" align="center">10</td>
<td valign="top" align="center">1.66E-05</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa00670</td>
<td valign="top" align="left">One carbon pool by folate</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">0.00051</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa05322</td>
<td valign="top" align="left">Systemic lupus erythematosus</td>
<td valign="top" align="center">14</td>
<td valign="top" align="center">0.00079</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa00970</td>
<td valign="top" align="left">Aminoacyl-tRNA biosynthesis</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">0.007952</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa01230</td>
<td valign="top" align="left">Biosynthesis of amino acids</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">0.01261</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa01130</td>
<td valign="top" align="left">Biosynthesis of antibiotics</td>
<td valign="top" align="center">15</td>
<td valign="top" align="center">0.016534</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa03022</td>
<td valign="top" align="left">Basal transcription factors</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">0.01975</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa04115</td>
<td valign="top" align="left">p53 signaling pathway</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">0.029229</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa04144</td>
<td valign="top" align="left">Endocytosis</td>
<td valign="top" align="center">15</td>
<td valign="top" align="center">0.042538</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa00260</td>
<td valign="top" align="left">Glycine, serine, and threonine metabolism</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center">0.046341</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap position="float" id="T4">
<label>Table 4</label>
<caption><p>GO and KEGG analysis of global down-regulated genes (Sort by <italic>P</italic>-value, and only the top ten GO items/pathways were listed in the table if there were more than 10).</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th valign="top" align="left"><bold>Category</bold></th>
<th valign="top" align="left"><bold>Pathway ID</bold></th>
<th valign="top" align="left"><bold>Pathway description</bold></th>
<th valign="top" align="center"><bold>Count</bold></th>
<th valign="top" align="center"><bold><italic>P</italic>-value</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0007155</td>
<td valign="top" align="left">Cell adhesion</td>
<td valign="top" align="center">27</td>
<td valign="top" align="center">4.14E-05</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0030198</td>
<td valign="top" align="left">Extracellular matrix organization</td>
<td valign="top" align="center">14</td>
<td valign="top" align="center">0.000846</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0006865</td>
<td valign="top" align="left">Amino acid transport</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">0.001333</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0007156</td>
<td valign="top" align="left">Homophilic cell adhesion via plasma membrane adhesion molecules</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">0.001412</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0007399</td>
<td valign="top" align="left">Nervous system development</td>
<td valign="top" align="center">17</td>
<td valign="top" align="center">0.001454</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0030168</td>
<td valign="top" align="left">Platelet activation</td>
<td valign="top" align="center">10</td>
<td valign="top" align="center">0.001691</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0042493</td>
<td valign="top" align="left">Response to drug</td>
<td valign="top" align="center">17</td>
<td valign="top" align="center">0.002602</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0001666</td>
<td valign="top" align="left">Response to hypoxia</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">0.002759</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0032355</td>
<td valign="top" align="left">Response to estradiol</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">0.005937</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_BP</td>
<td valign="top" align="left">GO:0019827</td>
<td valign="top" align="left">Stem cell population maintenance</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">0.006509</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0005887</td>
<td valign="top" align="left">Integral component of plasma membrane</td>
<td valign="top" align="center">65</td>
<td valign="top" align="center">9.07E-08</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0005886</td>
<td valign="top" align="left">Plasma membrane</td>
<td valign="top" align="center">141</td>
<td valign="top" align="center">1.08E-07</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0031012</td>
<td valign="top" align="left">Extracellular matrix</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">1.60E-05</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0005925</td>
<td valign="top" align="left">Focal adhesion</td>
<td valign="top" align="center">24</td>
<td valign="top" align="center">3.47E-05</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0005578</td>
<td valign="top" align="left">Proteinaceous extracellular matrix</td>
<td valign="top" align="center">18</td>
<td valign="top" align="center">0.000148</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0009986</td>
<td valign="top" align="left">Cell surface</td>
<td valign="top" align="center">27</td>
<td valign="top" align="center">0.000309</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0030424</td>
<td valign="top" align="left">Axon</td>
<td valign="top" align="center">14</td>
<td valign="top" align="center">0.001796</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0005604</td>
<td valign="top" align="left">Basement membrane</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">0.002139</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0005615</td>
<td valign="top" align="left">Extracellular space</td>
<td valign="top" align="center">48</td>
<td valign="top" align="center">0.002263</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_CC</td>
<td valign="top" align="left">GO:0016323</td>
<td valign="top" align="left">Basolateral plasma membrane</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">0.002845</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0005509</td>
<td valign="top" align="left">Calcium ion binding</td>
<td valign="top" align="center">40</td>
<td valign="top" align="center">1.16E-06</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0004714</td>
<td valign="top" align="left">Transmembrane receptor protein tyrosine kinase activity</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">2.62E-05</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0005178</td>
<td valign="top" align="left">Integrin binding</td>
<td valign="top" align="center">11</td>
<td valign="top" align="center">0.00019</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0015171</td>
<td valign="top" align="left">Amino acid transmembrane transporter activity</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">0.000795</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0004716</td>
<td valign="top" align="left">Receptor signaling protein tyrosine kinase activity</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">0.00139</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0005201</td>
<td valign="top" align="left">Extracellular matrix structural constituent</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">0.004977</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0015293</td>
<td valign="top" align="left">Symporter activity</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">0.006927</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0043395</td>
<td valign="top" align="left">Heparan sulfate proteoglycan binding</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">0.008213</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0043548</td>
<td valign="top" align="left">Phosphatidylinositol 3-kinase binding</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">0.009585</td>
</tr>
<tr>
<td valign="top" align="left">GOTERM_MF</td>
<td valign="top" align="left">GO:0001948</td>
<td valign="top" align="left">Glycoprotein binding</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">0.018656</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa04510</td>
<td valign="top" align="left">Focal adhesion</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">0.000132</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa04974</td>
<td valign="top" align="left">Protein digestion and absorption</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">0.005345</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa04066</td>
<td valign="top" align="left">HIF-1 signaling pathway</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">0.008544</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa05205</td>
<td valign="top" align="left">Proteoglycans in cancer</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">0.009214</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa04512</td>
<td valign="top" align="left">ECM-receptor interaction</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">0.018733</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa04151</td>
<td valign="top" align="left">PI3K-Akt signaling pathway</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">0.020078</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa04022</td>
<td valign="top" align="left">cGMP-PKG signaling pathway</td>
<td valign="top" align="center">9</td>
<td valign="top" align="center">0.03806</td>
</tr>
<tr>
<td valign="top" align="left">KEGG_PATHWAY</td>
<td valign="top" align="left">hsa05146</td>
<td valign="top" align="left">Amoebiasis</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">0.043644</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec>
<title>2.5. Experimental Verification of the DEG Analysis Results</title>
<p>To test the reliability of gene expression microarray results, several genes were selected and were validated by real time qPCR. The relative quantifications of the expression of these genes in DS hiPSCs and normal hiPSCs are represented in <xref ref-type="fig" rid="F6">Figure 6</xref>.</p>
<fig id="F6" position="float">
<label>Figure 6</label>
<caption><p>qRT-PCR of <bold>(A)</bold> <italic>H1-6</italic>, <bold>(B)</bold> <italic>FN1</italic>, <bold>(C)</bold> <italic>H4C13</italic>, and <bold>(D)</bold> <italic>RPL13</italic> in normal iPSCs (N) and DS hiPSCs (DS). Data are represented as mean &#x000B1; s.e.m. &#x0002A; stand for <italic>P</italic> &#x0003C; 0.05 and &#x0002A;&#x0002A;&#x0002A; for <italic>P</italic> &#x0003C; 0.001 by one-way followed with Tukeys test from <italic>n</italic> = 3.</p></caption>
<graphic xlink:href="fcell-09-661381-g0006.tif"/>
</fig>
<p>In compare with normal hiPSCs, DS hiPSCs exhibited a 2.1-fold increase of <italic>H1-6</italic> (<xref ref-type="fig" rid="F6">Figure 6A</xref>), a linker histone, which interacts with DNA between nucleosomes and plays an important role in the compaction of chromatin into higher order structures. In DS hiPSCs, the expressions of <italic>FN1</italic> (<xref ref-type="fig" rid="F6">Figure 6B</xref>) and <italic>H4C13</italic> (<xref ref-type="fig" rid="F6">Figure 6C</xref>) were reduced 4- and 2.5-fold, respectively. The expression of the gene <italic>RPL13</italic> (<xref ref-type="fig" rid="F6">Figure 6D</xref>) was not significant changed in DS hiPSCs in comparison with the normal hiPSCs. All of these results are consistent with the DEG analysis of the microarray dataset.</p>
</sec>
</sec>
<sec sec-type="discussion" id="s3">
<title>3. Discussion</title>
<p>Although RNA-seq, a preferred platform for studying differentially expressed genes and alternative splicing nowadays, has some inherent advantages in comparison with microarrays, such as the ability to identify novel exons and splice junctions in an unbiased manner, the HTA 2.0 platform can nevertheless detect more weakly expressed events, which are missed in the RNA-seq results (Fumagalli et al., <xref ref-type="bibr" rid="B9">2014</xref>; Wang et al., <xref ref-type="bibr" rid="B38">2014</xref>; Romero et al., <xref ref-type="bibr" rid="B31">2018</xref>). Furthermore, the modern microarrays, HTA 2.0, can still outperform RNA-seq for the analysis of gene expression in terms of cost, reproducibility and time as well as memory resources for treating data (Nazarov et al., <xref ref-type="bibr" rid="B23">2017</xref>; Romero et al., <xref ref-type="bibr" rid="B31">2018</xref>). For these reasons, we have chosen the HAT 2.0 platform as the major research approach for the AS studies. The reliability of gene expression microarray results was tested by the relative quantification of the expression of several selected genes. All of these genes showed the same change direction as they were exhibited in the DEG analysis of the microarray dataset (<xref ref-type="fig" rid="F6">Figure 6</xref>).</p>
<p>The triploidy of chromosome 21 is the proximal cause of DS. Multi-omics studies of DS somatic cells revealed that the transcriptome and epigenetic modification disorders, leads to the disequilibrium of disease-related gene expression as a possible underlying mechanism contributing to the comorbidities associated with DS (Letourneau et al., <xref ref-type="bibr" rid="B19">2014</xref>; Waugh et al., <xref ref-type="bibr" rid="B40">2019</xref>). Therefore, the studies on DS&#x00027;s molecular regulatory mechanism can provide novel insight that could improve the clinical management of these patients. In this study, we examined differentially expressed genes (DEGs) in hiPSCs derived from DS and healthy individuals and focused on specific transcripts with AS. 1,188 differentially expressed genes and 1,862 annotated genes with splicing changes were analyzed by GO function enrichment and KEGG signaling pathway analysis, in order to dissect out the cause of the difference between DS and normal hiPSCs.</p>
<p>To more accurately analyze the possible dosage effects of chromosome 21 genes on DS hiPSCs, those genes determined to be up-regulated were analyzed. The biological functions and KEGG signaling pathways of the up-regulated genes on chromosome 21 suggested that dysfunctional neurodevelopment and metabolisms must have occurred in the early embryonic development of DS patients. However, the gene dosage effect can not fully explain the pathogenesis of the various comorbidities of DS patients. Bioinformatics analysis of differentially expressed genes in the whole-genome showed that the up-regulated genes were primarily involved in cell growth regulation, nucleosome assembly, and chromosome separation, suggesting that the formation and separation blockage of chromosome 21 might be the main reason for the abnormal cell cycle. KEGG signaling pathway analysis showed that the down-regulated genes are enriched in focal adhesion and extracellular matrix (ECM) receptor interaction, indicating that the migration and adhesion of DS hiPSCs may be impaired, and migration and colonization of both nervous and reproductive systems occurred during early embryonic development (Huo et al., <xref ref-type="bibr" rid="B14">2018</xref>). In addition, abnormal cell adhesion was also found in the bioinformatics analysis of other DS hiPSCs (Hibaoui et al., <xref ref-type="bibr" rid="B11">2014</xref>; Gonzales et al., <xref ref-type="bibr" rid="B10">2018</xref>). These results are consistent with the other studies, in which the RNA-seq are used as the major research platform (Hibaoui et al., <xref ref-type="bibr" rid="B11">2014</xref>; Gonzales et al., <xref ref-type="bibr" rid="B10">2018</xref>; Perepitchka et al., <xref ref-type="bibr" rid="B27">2020</xref>).</p>
<p>Key genes identified from the HTA 2.0 dataset analysis are histone coding genes involved in nucleosome formation and gene expression regulation. It appeared that alternation of histone-related genes, such as mutations in histone-modified genes, can lead to disorders related to DS, such as congenital heart disease (Zaidi et al., <xref ref-type="bibr" rid="B46">2013</xref>). Some of the key genes identified in this study are involved in disorders of neurodevelopment and neurogenesis. For example, <italic>H3C2</italic> plays an essential role in brain development in early embryonic development (Ren and van Nocker, <xref ref-type="bibr" rid="B29">2016</xref>), and <italic>H2BC12</italic> is involved in Alzheimer&#x00027;s disease (Pedrero-Prieto et al., <xref ref-type="bibr" rid="B26">2019</xref>). <italic>H1-2</italic>, on the other hand, plays a critical role in the stabilization of chromatin and is involved in cell cycles, apoptosis induced by DNA damage, and the stabilization of autophagy protein and fibrin (Konishi et al., <xref ref-type="bibr" rid="B17">2003</xref>; Sancho et al., <xref ref-type="bibr" rid="B33">2008</xref>; Roque et al., <xref ref-type="bibr" rid="B32">2015</xref>; Wang et al., <xref ref-type="bibr" rid="B39">2017</xref>). The up-regulated <italic>H1-6</italic> and down-regulated <italic>H3C11</italic> and <italic>H4C13</italic> are also essential for the stabilization and structure of chromatin and chromosomes. The alteration of the expression of these genes could also lead to variations of chromatin states and chromosome structure. These genes are worthy of further analysis to determine the reasonable correlations to pathological knowledge.</p>
<p>We observed trisomy-dependent splicing changes in the DS hiPSCs. Our identification of splicing changes resonance with the alternative splicing events in a selected set of genes in fetal DS tissue that has been previously reported (Toiber et al., <xref ref-type="bibr" rid="B36">2010</xref>). AS in DS endothelial progenitor cells has also been analyzed via RNA-seq, although no confirmatory studies have yet been performed (Costa et al., <xref ref-type="bibr" rid="B8">2011</xref>). The large majority of alternative splicing events we identified occur in genes located outside of chromosome 21, implying that these AS differences were not directly affected by gene dosage. It is more likely that altered expression or altered splicing activity could cause the splicing dysregulation in DS hiPSCs. Alternatively, up-regulation of the chromosome 21 gene, such as <italic>DYRK1A</italic>, a kinase known to regulate splicing factors (Qian et al., <xref ref-type="bibr" rid="B28">2011</xref>), could contribute to the alternative splicing events we identified. It has been reported that over-expression of <italic>DYRK1A</italic> in mice led to mimicry of splicing aberrations in DS (Toiber et al., <xref ref-type="bibr" rid="B36">2010</xref>). The role of <italic>DYRK1A</italic> or the other specific splicing factors in the alternative splicing changes we identified will require additional studies. The gene dosage effect and expression levels of these genes should be normalized in the DS hiPSCs backgrounds.</p>
</sec>
<sec sec-type="materials and methods" id="s4">
<title>4. Materials and Methods</title>
<sec>
<title>4.1. HiPSC Culture</title>
<p>DS hiPSC (ATCC&#x000AE; ACS-1003&#x02122;) and normal hiPSC (ATCC&#x000AE; ACS-1011&#x02122;) were from the ATCC (American Type Culture Collection) cell bank. HiPSCs were cultured using Gibco&#x00027;s StemFlex&#x02122; medium (ThermoFisher Scientific, USA). The petri dishes were pre-treated with Matrigel, and the medium was changed daily. After culturing for 4&#x02013;5 days, the iPSCs were digested, and the suspended cell clusters were collected and subcultured at a ratio of 1:6 at 37&#x000B0;C, 5% CO<sub>2</sub> (Aalders et al., <xref ref-type="bibr" rid="B1">2019</xref>).</p>
</sec>
<sec>
<title>4.2. Cellular Immunofluorescence Experiment</title>
<p>After removing the culture medium, hiPSCs were washed twice with PBS, adding blocking solution (PBS solution containing 0.6% BSA) within 30 min, a membrane breaker (PBS solution containing 0.02% Triton X-100) was added to break the cell membrane. The diluted primary antibody (1:250) [TRA1-60 primary antibody (ThermoFisher Scientific, USA) and LIN28A primary antibody (Cell Signaling, USA)] were added and incubated at 4&#x000B0;C overnight. The cells were washed twice with PBS the next day and then incubated with the fluorescent secondary antibody (1:500) [FITC-labeled goat anti-rabbit IgG (H &#x0002B; L), Cy3 labeled goat anti-mouse IgG (H &#x0002B; L)], respectively, at room temperature, avoiding light for 2 h. Finally, the anti-fluorescence quenching mount solution (containing DAPI) was added and incubated at room temperature for 10 min before the cells were observed under a fluorescence microscope (Weltner et al., <xref ref-type="bibr" rid="B43">2018</xref>).</p>
</sec>
<sec>
<title>4.3. Alkaline Phosphatase Staining</title>
<p>According to the instructions of the BCIP/NBT alkaline phosphatase staining kit&#x00027;s manufacturer (Beyotime Biotechnology, Shanghai, China), the protocol involved mixing 3 mL of alkaline phosphatase staining buffer with 10 <italic>&#x003BC;</italic>L of BCIP solution (300&#x000D7;) and 20 <italic>&#x003BC;</italic>L of NBT solution (150&#x000D7;) to prepare the working solution. Cells in 6-well plate were washed twice with PBS, then an appropriate amount of working solution was added to a single well of the 6-well plate while avoiding light exposure for 5&#x02013;30 min until the color displayed to the expected depth. The working solution was then removed, and the cells were washed twice with distilled water to stop coloring. Before the photographs were taken, the stained cells were dried at room temperature and keep away from light.</p>
</sec>
<sec>
<title>4.4. Extraction of Total RNA</title>
<p>DS hiPSC and normal hiPSC were seeded in a 6-well plate, each cultured for 3 days, and then digested to harvest about 5 &#x000D7; 10<sup>5</sup> cells. The experiment was repeated three times. The total RNA was extracted with TRIzol&#x02122; reagent (ThermoFisher Scientific, USA) and was first detected by the Agilent 2100 bioanalyzer with the Agilent RNA 6000 Nano Kit (Agilent Technologies, Waldbronn, Germany) according to the instruction of the manufacture. Total RNAs with an RNA integrity index (RIN) &#x0003E;7.0 were used for subsequent experiments.</p>
</sec>
<sec>
<title>4.5. Whole Transcriptome Profile Detection</title>
<p>By using WT Amplification Kit Module 1 and WT Amplification Kit Module 2 in the GeneChip&#x02122; WT PLUS Kit (ThermoFisher Scientific, USA), 100 ng of total RNA as input was performed <italic>in vitro</italic> transcription (IVT) to synthesize cRNA, and then reverse transcription and purification to obtain single-stranded cDNA (sscDNA). The GeneChip&#x02122; WT end labeling kit was used to fragment and label sscDNA, which was hybridized with the human transcriptome array (HTA 2.0), and the hybridization signals were detected on a chip scanner to obtain CEL files for DS and normal hiPSCs.</p>
</sec>
<sec>
<title>4.6. Real Time qPCR</title>
<p>The SuperScript&#x02122; IV reverse transcriptase (Invitrogen&#x02122;, USA) was used for the synthesis of first stand cDNA from the isolated RNA. 1 <italic>&#x003BC;</italic>g of total RNAs were reverse transcribed according to the manufacturer&#x00027;s instructions. cDNA was real time polymerase chain (PCR) amplified in a LightCycler&#x000AE; 96 System (Roche, USA) using the FastStart Essential DNA Green Master (Roche, USA). The LightCycler&#x000AE; 96 SW 1.1 software was used for raw data collection and gene expression comparisons (2<sup>&#x02212;&#x00394;&#x00394;CT</sup> method). The R packages &#x0201C;Rmisc&#x0201D; and &#x0201C;multcomp&#x0201D; are used for the data analysis and &#x0201C;ggplot2&#x0201D; for the visualization of the results.</p>
</sec>
<sec>
<title>4.7. Bioinformatic Analysis</title>
<sec>
<title>4.7.1. Screening of Differentially Expressed Genes</title>
<p>All data were reprocessed from raw images. Signal intensities, quality control, data normalization, and gene expression values for these samples were processed together with the RMA processing algorithm using the &#x0201C;oligo&#x0201D; package in R (Carvalho and Irizarry, <xref ref-type="bibr" rid="B6">2010</xref>). The DEG analysis was performed with Fold change (FC) &#x0003C; &#x02212;2 or &#x0003E; 2, <italic>P</italic>-value &#x0003C; 0.01.</p>
</sec>
<sec>
<title>4.7.2. Alternative Splicing Events Analysis</title>
<p>The alternative splicing events analysis was performed using the &#x0201C;EventPointer&#x0201D; package in R (Romero et al., <xref ref-type="bibr" rid="B30">2016</xref>) with the splicing index &#x0003C; &#x02212;2 or &#x0003E; 2 and exon-Level <italic>P</italic>-value &#x0003C; 0.01.</p>
</sec>
<sec>
<title>4.7.3. Gene Ontology (GO) and KEGG Signaling Pathway Analysis</title>
<p>GO enrichment was performed using DAVID (Huang et al., <xref ref-type="bibr" rid="B12">2009a</xref>,<xref ref-type="bibr" rid="B13">b</xref>) (<ext-link ext-link-type="uri" xlink:href="http://david.abcc.ncifcrf.gov/">http://david.abcc.ncifcrf.gov/</ext-link>). A hypergeometric test with the Benjamini and Hochberg false discovery rate (FDR) was performed using the default parameters to adjust the <italic>P</italic>-value (Benjamini and Hochberg, <xref ref-type="bibr" rid="B4">1995</xref>).</p>
</sec>
</sec>
</sec>
<sec sec-type="data-availability-statement" id="s5">
<title>Data Availability Statement</title>
<p>The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: <ext-link ext-link-type="uri" xlink:href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE168111">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE168111</ext-link>.</p>
</sec>
<sec id="s6">
<title>Author Contributions</title>
<p>YW, QM, YZe and FZ were the main contributors to designing experiments. YW, QM, and FZ interpreted results, wrote and revised the manuscript. ZL and QM performed microarray experiments and analyzed data. GY, LC and YZha performed cell culture experiments and analyzed data. FY analyzed microarray data. All authors agree to be accountable for the content of the work.</p>
</sec>
<sec sec-type="COI-statement" id="conf1">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
</body>
<back>
<ref-list>
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<fn fn-type="financial-disclosure"><p><bold>Funding.</bold> The research was funded by National Key R&#x00026;D Program of China (2016YFC1000503 and 2019YFA0801402) and Key disciplines of top priority in Shanghai (2017ZZ02019).</p>
</fn>
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