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| <?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD v1.1d1 20130915//EN" "JATS-archivearticle1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.1d1"><front><journal-meta><journal-id journal-id-type="nlm-ta">elife</journal-id><journal-id journal-id-type="hwp">eLife</journal-id><journal-id journal-id-type="publisher-id">eLife</journal-id><journal-title-group><journal-title>eLife</journal-title></journal-title-group><issn publication-format="electronic">2050-084X</issn><publisher><publisher-name>eLife Sciences Publications, Ltd</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">03915</article-id><article-id pub-id-type="doi">10.7554/eLife.03915</article-id><article-categories><subj-group subj-group-type="display-channel"><subject>Research article</subject></subj-group><subj-group subj-group-type="heading"><subject>Genomics and evolutionary biology</subject></subj-group><subj-group subj-group-type="heading"><subject>Human biology and medicine</subject></subj-group></article-categories><title-group><article-title>Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state</article-title></title-group><contrib-group><contrib contrib-type="author" id="author-16430" equal-contrib="yes"><name><surname>Katz</surname><given-names>Yarden</given-names></name><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff4">4</xref><xref ref-type="fn" rid="equal-contrib">†</xref><xref ref-type="fn" rid="con1"/><xref ref-type="fn" rid="conf2"/><xref ref-type="other" rid="dataro1"/></contrib><contrib contrib-type="author" id="author-16493" equal-contrib="yes"><name><surname>Li</surname><given-names>Feifei</given-names></name><xref ref-type="aff" rid="aff3">3</xref><xref ref-type="fn" rid="equal-contrib">†</xref><xref ref-type="fn" rid="con2"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author" id="author-16432"><name><surname>Lambert</surname><given-names>Nicole J</given-names></name><xref ref-type="aff" rid="aff4">4</xref><xref ref-type="fn" rid="con3"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author" id="author-16433"><name><surname>Sokol</surname><given-names>Ethan S</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff4">4</xref><xref ref-type="fn" rid="con4"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author" id="author-16494"><name><surname>Tam</surname><given-names>Wai-Leong</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="fn" rid="con5"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author" id="author-16435"><name><surname>Cheng</surname><given-names>Albert W</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff4">4</xref><xref ref-type="fn" rid="con6"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author" id="author-16436"><name><surname>Airoldi</surname><given-names>Edoardo M</given-names></name><xref ref-type="aff" rid="aff5">5</xref><xref ref-type="aff" rid="aff6">6</xref><xref ref-type="other" rid="par-4"/><xref ref-type="fn" rid="con7"/><xref ref-type="fn" rid="conf1"/></contrib><contrib contrib-type="author" id="author-16437"><name><surname>Lengner</surname><given-names>Christopher J</given-names></name><xref ref-type="aff" rid="aff7">7</xref><xref ref-type="aff" rid="aff8">8</xref><xref ref-type="fn" rid="con8"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author" id="author-16438"><name><surname>Gupta</surname><given-names>Piyush B</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff4">4</xref><xref ref-type="fn" rid="con9"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author" corresp="yes" id="author-16439"><name><surname>Yu</surname><given-names>Zhengquan</given-names></name><xref ref-type="aff" rid="aff3">3</xref><xref ref-type="corresp" rid="cor1">*</xref><xref ref-type="fn" rid="con10"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author" corresp="yes" id="author-16440"><name><surname>Jaenisch</surname><given-names>Rudolf</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff4">4</xref><xref ref-type="corresp" rid="cor2">*</xref><xref ref-type="other" rid="par-3"/><xref ref-type="fn" rid="con11"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author" corresp="yes" id="author-15948"><name><surname>Burge</surname><given-names>Christopher B</given-names></name><xref ref-type="aff" rid="aff4">4</xref><xref ref-type="corresp" rid="cor3">*</xref><xref ref-type="other" rid="par-1"/><xref ref-type="other" rid="par-2"/><xref ref-type="fn" rid="con12"/><xref ref-type="fn" rid="conf2"/><xref ref-type="other" rid="dataro1"/></contrib><aff id="aff1"><label>1</label><institution content-type="dept">Department of Brain and Cognitive Sciences</institution>, <institution>Massachusetts Institute of Technology</institution>, <addr-line><named-content content-type="city">Cambridge</named-content></addr-line>, <country>United States</country></aff><aff id="aff2"><label>2</label><institution>Whitehead Institute for Biomedical Research</institution>, <addr-line><named-content content-type="city">Cambridge</named-content></addr-line>, <country>United States</country></aff><aff id="aff3"><label>3</label><institution content-type="dept">State Key Laboratories for Agrobiotechnology, College of Biological Sciences</institution>, <institution>China Agricultural University</institution>, <addr-line><named-content content-type="city">Beijing</named-content></addr-line>, <country>China</country></aff><aff id="aff4"><label>4</label><institution content-type="dept">Department of Biology</institution>, <institution>Massachusetts Institute of Technology</institution>, <addr-line><named-content content-type="city">Cambridge</named-content></addr-line>, <country>United States</country></aff><aff id="aff5"><label>5</label><institution content-type="dept">Department of Statistics</institution>, <institution>Harvard University</institution>, <addr-line><named-content content-type="city">Cambridge</named-content></addr-line>, <country>United States</country></aff><aff id="aff6"><label>6</label><institution>The Broad Institute</institution>, <addr-line><named-content content-type="city">Cambridge</named-content></addr-line>, <country>United States</country></aff><aff id="aff7"><label>7</label><institution content-type="dept">Department of Animal Biology, School of Veterinary Medicine</institution>, <institution>University of Pennsylvania</institution>, <addr-line><named-content content-type="city">Philadelphia</named-content></addr-line>, <country>United States</country></aff><aff id="aff8"><label>8</label><institution content-type="dept">Institute for Regenerative Medicine</institution>, <institution>University of Pennsylvania</institution>, <addr-line><named-content content-type="city">Philadelphia</named-content></addr-line>, <country>United States</country></aff></contrib-group><contrib-group content-type="section"><contrib contrib-type="editor"><name><surname>Blencowe</surname><given-names>Benjamin J</given-names></name><role>Reviewing editor</role><aff><institution>University of Toronto,</institution> <country>Canada</country></aff></contrib></contrib-group><author-notes><corresp id="cor1"><label>*</label>For correspondence: <email>zyu@cau.edu.cn</email> (ZY);</corresp><corresp id="cor2"><email>jaenisch@wi.mit.edu</email> (RJ);</corresp><corresp id="cor3"><email>cburge@mit.edu</email> (CBB)</corresp><fn fn-type="con" id="equal-contrib"><label>†</label><p>These authors contributed equally to this work</p></fn></author-notes><pub-date publication-format="electronic" date-type="pub"><day>07</day><month>11</month><year>2014</year></pub-date><pub-date pub-type="collection"><year>2014</year></pub-date><volume>3</volume><elocation-id>e03915</elocation-id><history><date date-type="received"><day>06</day><month>07</month><year>2014</year></date><date date-type="accepted"><day>05</day><month>11</month><year>2014</year></date></history><permissions><copyright-statement>Copyright © 2014, Katz et al</copyright-statement><copyright-year>2014</copyright-year><copyright-holder>Katz et al</copyright-holder><license xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This article is distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>, which permits unrestricted use and redistribution provided that the original author and source are credited.</license-p></license></permissions><self-uri content-type="pdf" xlink:href="elife03915.pdf"/><abstract><object-id pub-id-type="doi">10.7554/eLife.03915.001</object-id><p>The conserved Musashi (Msi) family of RNA binding proteins are expressed in stem/progenitor and cancer cells, but generally absent from differentiated cells, consistent with a role in cell state regulation. We found that Msi genes are rarely mutated but frequently overexpressed in human cancers and are associated with an epithelial-luminal cell state. Using ribosome profiling and RNA-seq analysis, we found that Msi proteins regulate translation of genes implicated in epithelial cell biology and epithelial-to-mesenchymal transition (EMT), and promote an epithelial splicing pattern. Overexpression of Msi proteins inhibited the translation of Jagged1, a factor required for EMT, and repressed EMT in cell culture and in mammary gland <italic>in vivo</italic>. Knockdown of Msis in epithelial cancer cells promoted loss of epithelial identity. Our results show that mammalian Msi proteins contribute to an epithelial gene expression program in neural and mammary cell types.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.001">http://dx.doi.org/10.7554/eLife.03915.001</ext-link></p></abstract><abstract abstract-type="executive-summary"><object-id pub-id-type="doi">10.7554/eLife.03915.002</object-id><title>eLife digest</title><p>All living things start life as a single cell, but many organisms develop into a collection of different, specialized cells. Most of the cells in an organism can only divide to make more of the same type of cell; however, stem cells are different because they can ‘differentiate’ and develop into several different cell types.</p><p>A key step in the development of an embryo is called the epithelial-to-mesenchymal transition, in which an epithelial cell—a cell type that normally lines body surfaces and cavities—begins to crawl away from the tissue it is in and starts to differentiate. This transition also allows cancer cells to leave tumors and spread around the body, in a process known as metastasis.</p><p>In mammals, two proteins called Musashi1 and Musashi2 are abundant in stem cells and brain cancers, but are rarely found in specialized tissues and cells. Katz, Li et al. now find that the Musashi proteins are also often overexpressed in human breast, lung, and prostate tumors. In addition, Musashi proteins are much less abundant in cells that have completed an epithelial-to-mesenchymal transition.</p><p>When Katz, Li et al. artificially reduced the amounts of Musashi proteins in breast cancer cells, the cells migrated and dispersed, as if becoming mesenchymal cells. Furthermore, many of the genes normally used in epithelial cells were switched off. In comparison, artificially increasing the levels of Musashi proteins halted the movement of mesenchymal cells and led to increased levels of genes used in epithelial cells, as if they were reverting to epithelial cells. Therefore, it appears that the Musashi proteins prevent epithelial cells from developing mesenchymal properties.</p><p>Katz, Li et al. investigated how Musashi proteins work at the molecular level by studying neural and mammary cells in mice. This revealed that Musashi proteins control the steps that lead to the epithelial-to-mesenchymal transition by binding to the tail end of the RNA molecules that include the instructions to make certain proteins. This affects how often these proteins can be made from the RNA molecules. Katz, Li et al. suggest that Musashi proteins may similarly control the behavior of progenitor and stem cells in many other tissues as well; however, further study is needed to confirm this.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.002">http://dx.doi.org/10.7554/eLife.03915.002</ext-link></p></abstract><kwd-group kwd-group-type="author-keywords"><title>Author keywords</title><kwd>cancer genomics</kwd><kwd>translational regulation</kwd><kwd>alternative splicing</kwd><kwd>epithelial–mesenchymal transition</kwd></kwd-group><kwd-group kwd-group-type="research-organism"><title>Research organism</title><kwd>human</kwd><kwd>mouse</kwd></kwd-group><funding-group><award-group id="par-1"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000057</institution-id><institution content-type="university">National Institute of General Medical Sciences</institution></institution-wrap></funding-source><award-id>R01-GM085319</award-id><principal-award-recipient><name><surname>Burge</surname><given-names>Christopher B</given-names></name></principal-award-recipient></award-group><award-group id="par-2"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000054</institution-id><institution content-type="university">National Cancer Institute</institution></institution-wrap></funding-source><award-id>U01-CA184897</award-id><principal-award-recipient><name><surname>Burge</surname><given-names>Christopher B</given-names></name></principal-award-recipient></award-group><award-group id="par-3"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000054</institution-id><institution content-type="university">National Cancer Institute</institution></institution-wrap></funding-source><award-id>RO1-CA084198</award-id><principal-award-recipient><name><surname>Jaenisch</surname><given-names>Rudolf</given-names></name></principal-award-recipient></award-group><award-group id="par-4"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000057</institution-id><institution content-type="university">National Institute of General Medical Sciences</institution></institution-wrap></funding-source><award-id>R01-GM096193</award-id><principal-award-recipient><name><surname>Airoldi</surname><given-names>Edoardo M</given-names></name></principal-award-recipient></award-group><funding-statement>The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.</funding-statement></funding-group><custom-meta-group><custom-meta><meta-name>elife-xml-version</meta-name><meta-value>2.0</meta-value></custom-meta><custom-meta specific-use="meta-only"><meta-name>Author impact statement</meta-name><meta-value>Genetic mouse models and human cell lines show that Musashi proteins promote an epithelial/luminal state and inhibit epithelial–mesenchymal transition (EMT), and genome-wide maps of translational regulatory targets connect Musashi proteins to an epithelial alternative splicing program and to the regulation of EMT.</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec sec-type="intro" id="s1"><title>Introduction</title><p>During both normal development and cancer progression, cells undergo state transitions marked by distinct gene expression profiles and changes in morphology, motility, and other properties. The Epithelial-to-Mesenchymal Transition (EMT) is one such transition, which is essential in development and is thought to be co-opted by tumor cells undergoing metastasis (<xref ref-type="bibr" rid="bib34">Polyak and Weinberg, 2009</xref>). Much work on cell state transitions in both the stem cell and cancer biology fields has focused on the roles that transcription factors play in driving these transitions (<xref ref-type="bibr" rid="bib34">Polyak and Weinberg, 2009</xref>; <xref ref-type="bibr" rid="bib21">Lee and Young, 2013</xref>), such as the induction of EMT by ectopic expression of the transcription factors Snail, Slug, or Twist (<xref ref-type="bibr" rid="bib25">Mani et al., 2008</xref>).</p><p>Recent work has shown that RNA-binding proteins (RBPs) also play important roles in cell state transitions, by driving post-transcriptional gene expression programs specific to a particular cell state. The epithelial specific regulatory protein (ESRP) family of RBPs are RNA splicing factors with epithelial tissue-specific expression whose ectopic expression can partially reverse EMT (<xref ref-type="bibr" rid="bib46">Warzecha et al., 2009</xref>; <xref ref-type="bibr" rid="bib39">Shapiro et al., 2011</xref>). RBPs have also been implicated in other cell state transitions, such as reprogramming of somatic cells to induced pluripotent stem cells (iPSCs), which have the essential characteristics of embryonic stem cells (ESCs). For example, overexpression of the translational regulator and microRNA processing factor Lin28 along with three transcription factors is sufficient to reprogram somatic cells (<xref ref-type="bibr" rid="bib48">Yu et al., 2007</xref>). The Muscleblind-like (Mbnl) family of RBPs promote differentiation by repressing an ESC-specific alternative splicing program, and inhibition of Mbnls promotes cellular reprogramming (<xref ref-type="bibr" rid="bib10">Han et al., 2013</xref>). For ESRP, Lin28, and Mbnl proteins, the developmental or cell-type-specific expression pattern of the protein provided clues to their functions in the maintenance of epithelial, stem cell, or differentiated cell state.</p><p>The Musashi (Msi) family comprises some of the most highly conserved and tissue-specific RBPs, with <italic>Drosophila Msi</italic> expressed exclusively in the nervous system (<xref ref-type="bibr" rid="bib28">Nakamura et al., 1994</xref>; <xref ref-type="bibr" rid="bib3">Busch and Hertel, 2011</xref>). In mammals, the two family members <italic>Msi1</italic> and <italic>Msi2</italic> are highly expressed in stem cell compartments but are mostly absent from differentiated tissues. <italic>Msi1</italic> is a marker of neural stem cells (NSCs) (<xref ref-type="bibr" rid="bib37">Sakakibara et al., 1996</xref>) and is also expressed in stem cells in the gut (<xref ref-type="bibr" rid="bib16">Kayahara et al., 2003</xref>) and epithelial cells in the mammary gland (<xref ref-type="bibr" rid="bib5">Colitti and Farinacci, 2009</xref>), while <italic>Msi2</italic> is expressed in hematopoietic stem cells (HSCs) (<xref ref-type="bibr" rid="bib17">Kharas et al., 2010</xref>). This expression pattern led to the proposal that Msi proteins generally mark the epithelial stem cell state across distinct tissues (<xref ref-type="bibr" rid="bib31">Okano et al., 2005</xref>), with HSCs being an exception. <italic>Msi1</italic> is not expressed in the normal adult brain outside a minority of adult NSCs but is induced in glioblastoma (<xref ref-type="bibr" rid="bib27">Muto et al., 2012</xref>).</p><p>Msi proteins affect cell proliferation in several cancer types. In glioma and medulloblastoma cell lines, knockdown of <italic>Msi1</italic> reduced the colony-forming capacity of these cells and reduced their tumorigenic growth in a xenograft assay in mice (<xref ref-type="bibr" rid="bib27">Muto et al., 2012</xref>). Msi expression correlates with HER2 expression in breast cancer cell lines, and knockdown of Msi proteins resulted in decreased proliferation (<xref ref-type="bibr" rid="bib45">Wang et al., 2010</xref>). These observations, together with the cell-type specific expression of Msi proteins in normal development, suggested that Msi proteins might function as regulators of cell state, with potential relevance to cancer.</p><p>Msi proteins have been proposed to act as translational repressors of mRNAs—and sometimes as activators (<xref ref-type="bibr" rid="bib24">MacNicol et al., 2011</xref>)—when bound to mRNA 3′ UTRs, and were speculated to affect pre-mRNA processing in <italic>Drosophila</italic> (<xref ref-type="bibr" rid="bib28">Nakamura et al., 1994</xref>; <xref ref-type="bibr" rid="bib30">Okano et al., 2002</xref>). However, no conclusive genome-wide evidence for either role has been reported for the mammalian Msi family. Here, we aimed to investigate the roles of these proteins in human cancers and to gain a better understanding of their genome-wide effects on the transcriptome using mouse models.</p></sec><sec sec-type="results" id="s2"><title>Results</title><sec id="s2-1"><title>Msi genes are frequently overexpressed in multiple human cancers</title><p>To obtain a broad view of the role Msis might play in human cancer, we surveyed the expression and mutation profiles of Msi genes in primary tumors using genomic and RNA sequencing (RNA-Seq) data from The Cancer Genome Atlas (TCGA) (<xref ref-type="bibr" rid="bib41">Cancer Genome Atlas Network., 2012</xref>). To determine whether Msi genes are generally upregulated in human cancers, we analyzed RNA-Seq data from five cancer types for which matched tumor-control pairs were available. In these matched designs, a pair of RNA samples was obtained in parallel from a single patient's tumor and healthy tissue-matched biopsy, thus minimizing the contribution of individual genetic variation to expression differences. We observed that <italic>Msi1</italic> was upregulated in at least 40% of breast, lung, and prostate tumors, while <italic>Msi2</italic> was upregulated in at least 50% of breast and prostate tumors (<xref ref-type="fig" rid="fig1">Figure 1A</xref>, top). Overall, <italic>Msi1</italic> or <italic>Msi2</italic> were significantly upregulated in matched tumor-control pairs for 3 of the 5 cancer types, compared to control pairs. Kidney tumors showed the opposite expression pattern, with <italic>Msi1</italic> and <italic>Msi2</italic> downregulated in a majority of tumors and rarely upregulated, and in thyroid cancer neither <italic>Msi1</italic> nor <italic>Msi2</italic> showed a strong bias towards up- or down-regulation (<xref ref-type="fig" rid="fig1">Figure 1A</xref>, top). In breast tumors, a bimodal distribution of <italic>Msi1</italic> expression was observed, with a roughly even split between up- and down-regulation of <italic>Msi1</italic>, consistent with the idea that <italic>Msi1</italic> upregulation might be specific to a subtype of breast tumors. The bimodality of <italic>Msi1</italic> expression was not seen when comparing control pairs, so is not explained by general variability in <italic>Msi1</italic> levels (<xref ref-type="fig" rid="fig1">Figure 1A</xref>, bottom, solid vs dotted lines).<fig-group><fig id="fig1" position="float"><object-id pub-id-type="doi">10.7554/eLife.03915.003</object-id><label>Figure 1.</label><caption><title>Msi genes are frequently overexpressed in breast, lung, and prostate cancer but downregulated in kidney cancer.</title><p>(<bold>A</bold>) Top: percentage of matched tumor–control pairs with upregulated (black-fill bars) or downregulated (grey-fill bars) <italic>Msi1</italic> or <italic>Msi2</italic> in five cancer types with matched RNA-Seq data. Upregulated/downregulated defined as at least two-fold change in expression in tumor relative to matched control. Asterisks indicate one-tailed statistical significance levels relative to control pairs. Bottom: distribution of fold changes for <italic>Msi1</italic> and <italic>Msi2</italic> in matched tumor–control pairs (solid red and green lines, respectively) and in an equal number of control pairs (dotted red and green lines, respectively.) Shaded gray density shows the fold change across all genes. (<bold>B</bold>) Percentage of tumors with non-silent mutations in <italic>Msi1</italic>/<italic>Msi2</italic> and a select set of oncogenes and tumor suppressors across nine cancer types. Bold entries indicate genes whose mutation rate is at least two-fold above the cancer type average mutation rate.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.003">http://dx.doi.org/10.7554/eLife.03915.003</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915f001"/></fig><fig id="fig1s1" position="float" specific-use="child-fig"><object-id pub-id-type="doi">10.7554/eLife.03915.004</object-id><label>Figure 1—figure supplement 1.</label><caption><title>Analysis of <italic>Msi1/Msi2</italic> mutation and expression profiles in TCGA datasets.</title><p>(<bold>A</bold>) Distributions of the percent of tumors with non-silent mutations across cancer types in TCGA DNA sequencing data. Red and green triangles indicate values for Msi1 and Msi2, respectively. (<bold>B</bold>) Unsupervised hierarchical clustering of breast cancer tumors and matched controls, with overlaid sample labels, clinical markers and PAM50 subtypes.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.004">http://dx.doi.org/10.7554/eLife.03915.004</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915fs001"/></fig></fig-group></p><p>Examining genome sequencing data from matched tumor-control pairs across nine diverse cancer types, we found that <italic>Msi1</italic> and <italic>Msi2</italic> were not significantly mutated in most of these cancers (<xref ref-type="fig" rid="fig1">Figure 1B</xref>). One notable exception was kidney cancer (KIRC), where non-silent mutations in <italic>Msi1</italic> were significantly overrepresented, detectable in 9% of tumors (ranked in the 99<sup>th</sup> percentile of mutations per gene in this cancer) (<xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1A</xref>). This observation, together with the lower Msi mRNA levels observed in matched kidney tumors (<xref ref-type="fig" rid="fig1">Figure 1A</xref>), is consistent with a model in which loss of Msi function is selected for in kidney tumor cells, either as a result of downregulation or mutation. The observation that <italic>Msi1</italic>/<italic>Msi2</italic> was not significantly mutated in most tumors but are overexpressed in several tumor types (including glioblastoma) makes their profile more similar to oncogenes like FOS or HER2, than to tumor suppressors like PTEN and TP53, which tend to have the opposite pattern (<xref ref-type="bibr" rid="bib43">Verhaak et al., 2010</xref>; <xref ref-type="bibr" rid="bib41">Cancer Genome Atlas Network., 2012</xref>) (<xref ref-type="fig" rid="fig1">Figure 1B</xref>).</p></sec><sec id="s2-2"><title>Msi expression marks an epithelial-luminal state and is downregulated upon EMT</title><p>To determine whether Msi overexpression is specific to a particular cancer cell state, we focused on breast cancer, where tumors with distinct properties can be robustly classified by gene expression (<xref ref-type="bibr" rid="bib33">Parker et al., 2009</xref>; <xref ref-type="bibr" rid="bib41">Cancer Genome Atlas Network., 2012</xref>). Unsupervised hierarchical clustering of matched tumor and control samples produced a nearly perfect separation of tumors from control samples, rather than clustering by patient/genome of origin (<xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1B</xref>). We overlaid on top of our clustering a classification of samples into Normal, HER2+, Luminal A, Luminal B, and Basal states using RNA-Seq data to measure expression of the PAM50 gene set (<xref ref-type="bibr" rid="bib33">Parker et al., 2009</xref>). Our clustering using all genes corresponded well to the PAM50 classification (<xref ref-type="bibr" rid="bib41">Cancer Genome Atlas Network., 2012</xref>), separating most Luminal A from Luminal B tumors and showing a general grouping of HER2+ tumors (<xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1B</xref>). Using this classification, we found that <italic>Msi2</italic> was highly expressed in Luminal tumors (<xref ref-type="fig" rid="fig2">Figure 2A</xref>). <italic>Msi1</italic> was more variable across tumor subtypes, often showing a bimodal profile, split between up- and down-regulation (<xref ref-type="fig" rid="fig1">Figure 1A</xref> and <xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1B</xref>). <italic>Msi2</italic> expression was highest in Luminal B tumors, which are known to be more aggressive and highly proliferating (Ki67-high) than Luminal A types and are thought to share properties with epithelial mammary progenitor cells (<xref ref-type="bibr" rid="bib6">Das et al., 2013</xref>). These observations prompted the hypothesis that Msi proteins might be localized to epithelial cells in breast cancer tumors. The splicing factors <italic>Rbfox2</italic> and <italic>Mbnl1</italic> were previously identified as regulators of EMT and are upregulated during this transition (<xref ref-type="bibr" rid="bib52">Venables et al., 2013</xref>). Using TCGA expression analysis, we confirmed that <italic>Rbfox2</italic> and <italic>Mbnl1</italic> are more highly expressed in luminal tumors compared with mesenchymal tumors, as predicted by their role in EMT (<xref ref-type="fig" rid="fig2s2">Figure 2—figure supplement 2</xref>).<fig-group><fig id="fig2" position="float"><object-id pub-id-type="doi">10.7554/eLife.03915.005</object-id><label>Figure 2.</label><caption><title>Msi is associated with the epithelial-luminal state in breast cancer.</title><p>(<bold>A</bold>) mRNA expression of <italic>Msi2</italic> across different breast tumor types in TCGA RNA-Seq. (<bold>B</bold>) Immunofluorescence staining for Ecadherin (ECAD, red) and <italic>Msi1</italic> (MSI1, green). Top: luminal human breast tumor with high number of ECAD-positive cells. MSI1 shows primarily cytoplasmic localization (white arrowheads). Inset shows magnified version of ECAD and MSI staining. Bottom: triple negative, basal-like tumor. ECAD-positive cells showed strong cytoplasmic MSI1 stain (blue arrowheads) while ECAD-negative cells were MSI1-negative (red). Single confocal stacks shown, 10 μm scale. (<bold>C</bold>) mRNA expression of <italic>Msi1</italic>, <italic>Msi2</italic>, <italic>Ecad</italic>, <italic>Fn1</italic>, <italic>Vim</italic>, and <italic>Jag1</italic> in breast cancer cell lines by RNA-Seq (datasets are listed in <xref ref-type="supplementary-material" rid="SD1-data">Supplementary file 1</xref>). (<bold>D</bold>) Western blot for MSI1/2 (MSI1/2 cross react. antibody), MSI2, phosphorylated HER2 (p-HER2) and HER2 in panel of breast cell lines. ‘HMLE + pB’ indicates HMLE cells infected with pB empty vector, ‘HMLE + Twist’ indicates HMLE cells infected with Twist transcription factor to induce EMT. MDAMB231-derived metastatic lines (231-Brain, 231-Bone) and Sum159 are basal, HER2-negative cancer cell lines. BT474 and SKBR3 are HER2-positive, epithelial-luminal cancer cell lines. Epithelial-luminal (HER2-positive) lines show increased expression of Msi proteins compared with basal lines, and Twist-induced EMT reduces Msi expression. (<bold>E</bold>) mRNA expression of <italic>Msi1</italic>, <italic>Msi2</italic>, <italic>Ecad</italic>, <italic>Fn1</italic>, <italic>Vim</italic>, and <italic>Twist1</italic> in GBM tumors classified as mesenchymal (<italic>n</italic> = 20) or epithelial (<italic>n</italic> = 20) using an EMT gene signature.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.005">http://dx.doi.org/10.7554/eLife.03915.005</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915f002"/></fig><fig id="fig2s1" position="float" specific-use="child-fig"><object-id pub-id-type="doi">10.7554/eLife.03915.006</object-id><label>Figure 2—figure supplement 1.</label><caption><title>Expression of <italic>Msi1/Msi2</italic> in subtypes of breast cancer cell lines and breast cancer tumors.</title><p>(<bold>A</bold>) Unsupervised hierarchical clustering of gene expression from RNA-seq of breast cancer cell lines. (<bold>B</bold>) Fold-change in tumor–control pairs of TCGA breast cancer tumors for Msi1 and Msi2 across tumor subtypes. Msi1 shows a variable bimodal distribution of fold changes, while Msi2 is enriched in Luminal B tumors relative to Basal tumors. (<bold>C</bold>) Ratio of luminal to basal cancer cell line fold changes for Msi1, Msi2, Jag1, and Fn1.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.006">http://dx.doi.org/10.7554/eLife.03915.006</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915fs002"/></fig><fig id="fig2s2" position="float" specific-use="child-fig"><object-id pub-id-type="doi">10.7554/eLife.03915.007</object-id><label>Figure 2—figure supplement 2.</label><caption><title>Expression of Rbfox2 (Rbm9) and Mbnl1 in subtypes of breast cancer tumors from TCGA.</title><p>Expression values for Rbfox2/Mbnl1 plotted across PAM50 subtypes, after TMM normalization.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.007">http://dx.doi.org/10.7554/eLife.03915.007</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915fs003"/></fig></fig-group></p><p>To examine the expression and distribution of Msi proteins in tumors, we stained a panel of human breast cancer tumors for MSI1 and the epithelial marker E-cadherin (ECAD). MSI1 expression was predominantly cytoplasmic (<xref ref-type="fig" rid="fig2">Figure 2B</xref>, top panel). Across luminal tumors, MSI1 was co-expressed with ECAD (as in <xref ref-type="fig" rid="fig2">Figure 2B</xref>, top panel). In triple negative/basal-like tumors, a minority of ECAD-positive cells showed strong MSI1 staining, whereas ECAD-negative cells showed little to no expression (<xref ref-type="fig" rid="fig2">Figure 2B</xref>, blue and red arrowheads, respectively), supporting an association between Msi and epithelial cell state in tumors. Given the heterogeneity of human tumor samples, it is possible that the increased expression of Msi genes in luminal tumors (compared with basal) reflects the generally higher fraction of epithelial cells in these tumors.</p><p>To explore whether Msi expression is associated with a luminal as opposed to basal state in a more homogenous system, we analyzed RNA-Seq data for luminal and basal breast cancer cell lines generated by multiple independent labs (RNA-Seq data sets used are listed in <xref ref-type="supplementary-material" rid="SD1-data">Supplementary file 1</xref>). Gene expression profiles from the same cell lines generated independently tended to cluster together in unsupervised clustering (supporting consistency of data across labs), and overall the basal cell lines were distinguishable from the luminal lines (<xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1A</xref>). Matching the pattern observed in primary tumors, we observed higher <italic>Msi1</italic> and <italic>Msi2</italic> expression in luminal breast cancer lines than in basal lines (<xref ref-type="fig" rid="fig2">Figure 2C</xref>, left panel). Expression of Fibronectin (<italic>Fn1</italic>), Vimentin (<italic>Vim</italic>), and Jagged1 (<italic>Jag1</italic>), which are associated with the basal/mesenchymal state (<xref ref-type="bibr" rid="bib47">Yamamoto et al., 2013</xref>), had the opposite pattern, showing strong enrichment in basal over luminal lines (<xref ref-type="fig" rid="fig2">Figure 2C</xref>, right panel). The enrichments of these four genes for either the luminal or basal state were unusual when compared to the background distribution of these enrichments across all expressed genes (<xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1C</xref>), indicating that these genes are strong indicators of the two states.</p><p>To further investigate the connection between Msi expression and EMT in breast cancer, we examined Msi expression in a panel of breast cancer-derived cell lines. Consistent with the RNA-Seq data from primary tumors, HER2+ epithelial cell lines expressed higher levels of <italic>Msi1</italic> and <italic>Msi2</italic> compared with HER2– lines (<xref ref-type="fig" rid="fig2">Figure 2D</xref>, lane 6 and 7). A standard cell culture model of EMT is the immortalized inducible-Twist human mammary epithelial (HMLE-Twist) cell line, which undergoes EMT when induced to express the transcription factor Twist (<xref ref-type="bibr" rid="bib25">Mani et al., 2008</xref>). We found that <italic>Msi1</italic> was strongly downregulated in HMLE cells following Twist-induced EMT (<xref ref-type="fig" rid="fig2">Figure 2D</xref>), consistent with the epithelial-associated expression pattern of Msis in primary tumors (<xref ref-type="fig" rid="fig2">Figure 2A–C</xref>). Similarly, Msi protein expression was higher in luminal, HER2+ breast cancer lines (BT474, SKBR3 in <xref ref-type="fig" rid="fig2">Figure 2D</xref>) compared with basal HER2– breast cancer lines (brain and bone metastatic derivatives of MDAMB231, 231-Brain and 231-Bone, and SUM159 in <xref ref-type="fig" rid="fig2">Figure 2D</xref>).</p><p>We next asked whether the epithelial expression signature of Msis is present in other primary tumors. Given the established role of Msi proteins as regulators of Glioblastoma (GBM) cell growth and as markers of primary tumors (<xref ref-type="bibr" rid="bib27">Muto et al., 2012</xref>), we examined whether there is a similar subtype expression pattern in GBM tumors from TCGA (<xref ref-type="bibr" rid="bib43">Verhaak et al., 2010</xref>). We used an EMT gene signature to rank GBM tumors from more epithelial to more mesenchymal, based on the similarity of each tumor's gene expression profile to that of cells undergoing EMT in culture (<xref ref-type="bibr" rid="bib9">Feng et al., 2014</xref>). Using this ranking, we found that the top 20 most epithelial tumors expressed higher levels of Msi and epithelial markers like ECAD (<xref ref-type="fig" rid="fig2">Figure 2E</xref>). By contrast, the top 20 most mesenchymal tumors expressed lower levels of Msi and higher levels of mesenchymal markers like Fibronectin and Vimentin (<xref ref-type="fig" rid="fig2">Figure 2E</xref>). Thus, Msi expression is enriched in epithelial tumors in GBM as well, consistent with the results obtained in breast cancer tumors and cell lines.</p><p>Taken together, these results show that Msi genes are rarely mutated but frequently overexpressed across human cancers and are strong markers of the epithelial-luminal state. This pattern suggests that Msi proteins may play a role in the maintenance of an epithelial state and/or repression of EMT, in both breast and neural cell types. To better understand the molecular functions of Msi proteins, we turned to a controlled cell culture system.</p></sec><sec id="s2-3"><title>Genetic system for inducible overexpression and depletion of <italic>Msi1/2</italic> in NSCs</title><p>The upregulation of Msi genes in glioblastoma motivated the choice of NSCs as a system to study the molecular roles of Msi proteins, a cell type where both proteins are highly expressed in normal development, and where their target mRNAs are likely to be present. NSCs provide a well-characterized system for homogeneous cell culture (<xref ref-type="bibr" rid="bib18">Kim et al., 2003</xref>), which is not always available for progenitor/stem cell types cultured from other primary tissues like the mammary gland, making NSCs grown in culture amenable to analysis by genome-wide techniques. Furthermore, the conserved expression of Msi genes in the nervous system and their reactivation in human glioblastoma suggests that molecular insights obtained in this system could be informative about the roles of Msi proteins in glioblastoma cells.</p><p>We cultured cortical NSCs from E12.5 embryos obtained from transgenic mice with a Dox-inducible <italic>Msi1</italic> or <italic>Msi2</italic> allele, and from double conditional knockout mice for <italic>Msi1/Msi2</italic>, whose deletion was driven by a Tamoxifen-inducible Cre (<xref ref-type="fig" rid="fig3">Figure 3A</xref>). These systems enabled robust overexpression or depletion of Msi proteins (<xref ref-type="fig" rid="fig3">Figure 3B</xref>) within 48–72 hr of induction. To study the effects of Msi depletion and induction on mRNA processing, expression, and translation, we used ribosome footprint profiling (Ribo-Seq) (<xref ref-type="bibr" rid="bib13">Ingolia et al., 2009</xref>) and high-throughput sequencing of polyA-selected RNA (RNA-Seq) (<xref ref-type="bibr" rid="bib26">Mortazavi et al., 2008</xref>) (<xref ref-type="fig" rid="fig3">Figure 3A</xref>).<fig-group><fig id="fig3" position="float"><object-id pub-id-type="doi">10.7554/eLife.03915.008</object-id><label>Figure 3.</label><caption><title>Genetic system for studying effects of Msi loss/gain of function on gene expression.</title><p>(<bold>A</bold>) Experimental setup and use of <italic>Msi1/2</italic> inducible overexpression and conditional double knockout mice for derivation of neural stem cells, which were then used for ribosome profiling (Ribo-Seq) and mRNA sequencing (RNA-Seq). (<bold>B</bold>) Western blot analysis of Musashi overexpression and knockout in neural stem cells. Overexpression and conditional knockout cells were exposed to Dox and 4-OHT for 72 hr, respectively. (<bold>C</bold>) mRNA-Seq expression values (RPKM) scatters between <italic>Msi1</italic> overexpressing cells and controls (left), <italic>Msi2</italic> overexpressing cells and controls right (72 hr Dox). <italic>Msi1/2</italic> each robustly overexpressed with similar magnitude following Dox. (<bold>D</bold>) Comparison of translational efficiency (TE) values using Ribo-Seq on Msi1 overexpressing cells on Dox (72 hr) vs controls (left) and conditional knockout cells following 4-OHT for 48 hr (right). Colored points indicate select genes with large changes in TE.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.008">http://dx.doi.org/10.7554/eLife.03915.008</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915f003"/></fig><fig id="fig3s1" position="float" specific-use="child-fig"><object-id pub-id-type="doi">10.7554/eLife.03915.009</object-id><label>Figure 3—figure supplement 1.</label><caption><title>Quality control metrics for Ribo-Seq libraries.</title><p>(<bold>A</bold>) Quality control metrics for overexpression Ribo-Seq libraries. Left panel: percentage of reads mapped to genome, and the percentages of reads that are unique (‘percent_unique’) and mapping to rRNA (‘percent_ribo’) out of those mapped. Right panel: percentage of reads mapping to exons (‘percent_exons’), and out of those the percentage of reads in CDS regions (‘percent_cds’), 3′ UTRs (‘percent_3p_utr’), 5′ UTRs (‘percent_5p_utr’). Percentage of reads mapping to introns (‘percent_introns’) also shown. (<bold>B</bold>) Quality control metrics for knockout Ribo-Seq libraries, same format as (<bold>A</bold>).</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.009">http://dx.doi.org/10.7554/eLife.03915.009</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915fs004"/></fig></fig-group></p></sec><sec id="s2-4"><title>Overexpression of <italic>Msi1</italic> alters translation of targets without causing large changes in mRNA levels</title><p>When <italic>Msi1</italic> or <italic>Msi2</italic> were overexpressed, few significant changes in mRNA expression were observed after 48 hr (<xref ref-type="fig" rid="fig3">Figure 3C</xref>). This observation suggests that these factors do not directly impact transcription or mRNA stability/decay but leaves open possible effects on other steps in gene expression such as mRNA translation. To determine the genome-wide effects of Msi proteins on translation, we performed Ribo-Seq on <italic>Msi1</italic>-overexpressing cells and double knockout cells. Reads from these Ribo-Seq libraries showed the expected enrichment in coding exons relative to UTRs and introns, and yielded high scores in various quality control (QC) metrics (<xref ref-type="fig" rid="fig3s1">Figure 3—figure supplement 1</xref>). These QC metrics were highly consistent across libraries, supporting comparative analysis of the resulting data (<xref ref-type="fig" rid="fig3s1">Figure 3—figure supplement 1</xref>). To examine changes in translation, we computed ‘Translational Efficiency’ (TE) values for all protein-coding genes, a measure of ribosome occupancy along messages that is defined as the ratio of the ribosome footprint read density in the ORF to the RNA-seq read density. Examination of TEs across overexpression and knockout samples yielded a handful of genes with very large changes in ribosome occupancy (<xref ref-type="fig" rid="fig3">Figure 3D</xref>, ‘Materials and methods’).</p></sec><sec id="s2-5"><title><italic>Msi1</italic> represses translation of Notch ligand Jagged1 and regulates translation of RBPs</title><p>Several genes exhibited substantial changes in their translation efficiency in response to overexpression of <italic>Msi1</italic>, including six genes with increased TE and three with reduced TE (<xref ref-type="fig" rid="fig3">Figure 3D</xref>). Genes with increased translation included the RNA processing factor <italic>Prpf3/Prp3p</italic>, a U4/U6 snRNP-associated factor, and genes involved in epithelial cell biology such as Kirrel3/NEPH2. Genes with repressed translation included: <italic>Rbm22/Cwc2</italic>, another splicing factor associated with U6 snRNP; <italic>Dhx37</italic>, an RNA helicase with possible role in alternative splicing (<xref ref-type="bibr" rid="bib11">Hirata et al., 2013</xref>); and <italic>Jag1</italic>, a ligand of Notch receptors and an important regulator of Notch signaling. No change was detected in translation of previously reported Msi target <italic>Numb</italic> (<xref ref-type="bibr" rid="bib30">Okano et al., 2002</xref>), though Numb had low coverage of Ribo-Seq reads in NSCs, reducing our statistical power to detect regulation (‘Materials and methods’). To explore whether the observed changes are mediated by direct protein binding to RNA targets, we mapped the RNA binding specificity of Msis.</p></sec><sec id="s2-6"><title>MSI1 shows high affinity for specific RNA motifs containing one or more UAGs</title><p>To determine sequence-specific RNA binding preferences of Msi proteins, we used ‘RNA Bind-n-Seq’ (RBNS) to obtain quantitative and unbiased measurement of the spectrum of RNA motifs bound by recombinant MSI1 protein in vitro (<xref ref-type="bibr" rid="bib20">Lambert et al., 2014</xref>) (<xref ref-type="fig" rid="fig4">Figure 4A</xref>). For each 6mer, the ‘R value’ was defined as the occurrence frequency in libraries derived from MSI1-bound RNAs divided by the corresponding frequency in the input RNA library, and 6mer ‘enrichment’ was defined as the maximum R value observed across all protein concentrations. The fold enrichment profiles obtained by RBNS for the top five most enriched 6mers and five randomly chosen 6mers are shown in <xref ref-type="fig" rid="fig4">Figure 4B</xref>. Enriched 6mers exhibited similar enrichment profiles across concentrations, peaking in fold enrichment at concentrations typically between 16–64 nM (<xref ref-type="fig" rid="fig4">Figure 4B</xref>). To summarize the binding preferences of MSI1 from RBNS, we aligned the most enriched 6mers to generate a motif, which emphasizes that MSI1 binds predominantly to UAG-containing sequences, preferentially flanked by Us (<xref ref-type="fig" rid="fig4">Figure 4C</xref>). The MSI1 binding site (G/A)UAGU from a previous SELEX study was ∼threefold enriched by RBNS, along with highly similar sequences, confirming binding under our assay conditions (<xref ref-type="bibr" rid="bib12">Imai et al., 2001</xref>; <xref ref-type="bibr" rid="bib35">Ray et al., 2013</xref>). Closer examination of the RBNS data revealed evidence for longer, higher-affinity motifs containing multiple UAGs with short intervening spacers (not shown).<fig-group><fig id="fig4" position="float"><object-id pub-id-type="doi">10.7554/eLife.03915.010</object-id><label>Figure 4.</label><caption><title>Profiling MSI1 binding preferences by RNA Bind-n-Seq.</title><p>(<bold>A</bold>) Schemaic of Bind-n-Seq experiment for MSI1 protein. Increased concentrations of MSI1-SBP fusion protein incubated with random RNA pool, pulled by straptavidin pull-down, reverse-transcribed and sequenced. (<bold>B</bold>) Fold enrichment of top five enriched 6mers (red curves) and five randomly chosen 6mers (blue curves) across protein concentrations. (<bold>C</bold>) Binding motif for MSI1. Position-weight matrix generated by global alignment of top 20 enriched 6mers. (<bold>D</bold>) Two sites in <italic>Jag1</italic> 3' UTR, region 1 and region 2, containing a high density of enriched 6mers. Top: PhyloP conservation score for 3' UTR in 20 nt windows (based on UCSC vertebrates multiple alignment). Bottom: number of enriched 6mers from BNS in 20 nt windows of 3' UTR. (<bold>E</bold>) Percent binding of MSI1 protein to region 1 and region 2 (red curves) and mutants where UAG sites are disrupted (blue curves), measured by gel-shift (see <xref ref-type="fig" rid="fig4s1">Figure 4—figure supplement 1</xref>). K<sub>d</sub> estimates for region 1 and region 2 are shown (mean of 2 gel-shifts per sequence). (<bold>F</bold>) Western blot analysis of <italic>Jag1</italic> regulation by Msi: top left panel, <italic>Jag1</italic> expression in <italic>Msi1</italic> overexpression cells and controls in cellular fractions (T—total lysate, <bold>C</bold>—cytoplasmic and N—nuclear fractions). <italic>Jag1</italic> is translationally repressed upon induction of <italic>Msi1</italic> and detected only in total and cytoplasmic lysates. hnRNP A1, known to shuttle between the nucleus and the cytoplasm and alpha-Tubulin used as loading controls. (<bold>G</bold>) Increased JAG1 protein levels in double knockout cells. (<bold>H</bold>) Reduced JAG1 protein levels upon <italic>Msi2</italic> overexpression.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.010">http://dx.doi.org/10.7554/eLife.03915.010</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915f004"/></fig><fig id="fig4s1" position="float" specific-use="child-fig"><object-id pub-id-type="doi">10.7554/eLife.03915.011</object-id><label>Figure 4—figure supplement 1.</label><caption><title>Validation by gel-shift of MSI1 binding to Jag1 3' UTR sequences.</title><p>(<bold>A</bold>) Top: gel-shift MSI1 binding assay for Jag1 3' UTR sequence 1. Kd estimate shown (15 nM) is average of two gel shifts. Bottom: gel-shift for Jag1 3′ UTR sequence 1 mutant, where UAG sites mutated to UCC. Kd cannot be estimated (no binding to mutant could be detected.) (<bold>B</bold>) Top: gel-shift MSI1 binding assay for Jag1 3′ UTR sequence 2. Kd estimate shown (9 nM) is average of two gel shifts. Bottom: gel-shift for <italic>Jag1</italic> 3′ UTR sequence 2 mutant, where UAG sites are also mutated to UCC. Kd for mutant sequence was 649 nM.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.011">http://dx.doi.org/10.7554/eLife.03915.011</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915fs005"/></fig><fig id="fig4s2" position="float" specific-use="child-fig"><object-id pub-id-type="doi">10.7554/eLife.03915.012</object-id><label>Figure 4—figure supplement 2.</label><caption><title>Effect of <italic>Msi1</italic> gain and loss of function on <italic>Jag1</italic> mRNA levels and protein expression.</title><p>Fold-change in <italic>Jag1</italic> expression in Msi1 overexpression and double knockout samples for Ribo-Seq and RNA-Seq experiments.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.012">http://dx.doi.org/10.7554/eLife.03915.012</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915fs006"/></fig><fig id="fig4s3" position="float" specific-use="child-fig"><object-id pub-id-type="doi">10.7554/eLife.03915.013</object-id><label>Figure 4—figure supplement 3.</label><caption><title>Validation of Msi-dependent regulation of <italic>Jag1</italic> protein levels using luciferase reporters containing <italic>Jag1</italic> 3' UTR.</title><p>Luciferase expression for <italic>Jag1</italic> 3′ UTR reporter transfected into 293T cells. Mean values shown for three biological replicates (±standard deviation). For knockdown lines, <italic>Jag1</italic> 3′ UTR reporter expression was normalized relative to reporter expression in mock transfected 293T cells (represented by dashed horizontal line.) Note that Msi2 sh.4 was effective in knocking down Msi2, but consistently increased Msi1 mRNA levels, and therefore did not reduce total Msi mRNA levels. This likely explains why Msi2 sh.4 293T cells did not show increased <italic>Jag1</italic> 3′ UTR reporter expression.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.013">http://dx.doi.org/10.7554/eLife.03915.013</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915fs007"/></fig></fig-group></p><p>Previous studies suggested that MSI1 binds 3′ UTR regions of mRNAs to regulate translation (<xref ref-type="bibr" rid="bib31">Okano et al., 2005</xref>). We calculated the density of RBNS-enriched 6mers in 3′ UTR regions genome-wide and ranked genes by the density of enriched 6mers in their 3′ UTR (‘Materials and methods’). We observed that the 3′ UTR of <italic>Jag1</italic>—which is translationally repressed by Msi (<xref ref-type="fig" rid="fig3">Figure 3D</xref>)—contains a moderately high density of RBNS-enriched 6mers, ranking in the 85<sup>th</sup> percentile of all 3′ UTRs (<xref ref-type="fig" rid="fig4">Figure 4D</xref>). To ask whether Msi proteins can directly bind the <italic>Jag1</italic> mRNA and test the RBNS motif, we selected two regions of the <italic>Jag1</italic> 3′ UTR that contained the highest density of RBNS-enriched 6mers for in vitro analysis (<xref ref-type="fig" rid="fig4">Figure 4B</xref>, top). A gel-shift assay detected strong binding of RNAs representing both regions by recombinant Msi protein, with estimated K<sub>d</sub> values of 15 nM and 9 nM for regions 1 and 2, respectively (representative gel shifts are shown in <xref ref-type="fig" rid="fig4s1">Figure 4—figure supplement 1</xref>). Since both sequences contain UAGs (<xref ref-type="fig" rid="fig4s1">Figure 4—figure supplement 1</xref>), we hypothesized that the UAGs nucleate binding. Mutation of the UAG sites to UCC reduced binding to MSI1 protein by an order of magnitude or more in each case (<xref ref-type="fig" rid="fig4">Figure 4E</xref>), supporting a model where MSI1 binding occurs primarily at these sites.</p><p>Following Msi overexpression, the Ribo-Seq density of the <italic>Jag1</italic> coding region was reduced by ∼fivefold, while its mRNA level was little changed, suggesting a predominant effect at the translational level (<xref ref-type="fig" rid="fig4s2">Figure 4—figure supplement 2</xref>). In double knockout cells, <italic>Jag1</italic> mRNA increased ∼1.5-fold by RNA-Seq (<xref ref-type="fig" rid="fig4s2">Figure 4—figure supplement 2</xref>), with a similar increase in Ribo-Seq density, suggesting effects on message stability either in the absence of or as a consequence of translational derepression. Western blot analysis confirmed repression of JAG1 protein by <italic>Msi1</italic> overexpression (<xref ref-type="fig" rid="fig4">Figure 4F</xref>) and derepression in double knockout cells (<xref ref-type="fig" rid="fig4">Figure 4G</xref>). The high similarity between MSI1 and MSI2 proteins (over 70% identity at the amino acid level, with highly similar RNA recognition motifs) suggests similarity in function, and we confirmed that <italic>Msi2</italic> overexpression also repressed JAG1 protein expression by Western analysis (<xref ref-type="fig" rid="fig4">Figure 4H</xref>). To directly test the hypothesis that Msi proteins regulate <italic>Jag1</italic> translation via UTR binding, we constructed luciferase reporters for the <italic>Jag1</italic> 3' UTR and transfected these into 293T cells. Knockdown of <italic>MSI1</italic> or knockdown of both <italic>MSI1</italic> and <italic>MSI2</italic> increased luciferase expression in these cells, relative to mock knockdown treatments (<xref ref-type="fig" rid="fig4s3">Figure 4—figure supplement 3</xref>). This observation also indicates that Msi-dependent regulation of <italic>Jag1</italic> translation is conserved from murine to human cells. In sum, our results support a model where Msi proteins directly bind to the <italic>Jag1</italic> 3′ UTR to mediate post-transcriptional repression of protein levels.</p></sec><sec id="s2-7"><title>Msi proteins regulate alternative splicing</title><p>Since some of the largest changes in translation observed by Ribo-Seq affected RBPs with functions in RNA splicing, we hypothesized that Msi overexpression might trigger changes in pre-mRNA splicing. Changes in mRNA splicing following Msi overexpression or depletion were assessed by analysis of RNA-seq data using the MISO software (<xref ref-type="bibr" rid="bib14">Katz et al., 2010</xref>). For example, exon 38 in the <italic>Myo18a</italic> gene, which is predominantly included under control conditions, was modestly repressed following <italic>Msi2</italic> overexpression and strongly repressed following <italic>Msi1</italic> overexpression (<xref ref-type="fig" rid="fig5">Figure 5A</xref>). In total, we observed several hundred alternatively spliced exons that were either repressed or enhanced by overexpression or knockout of Msis (<xref ref-type="fig" rid="fig5">Figure 5B</xref>). Msi proteins are predominantly localized in the cytoplasm (<xref ref-type="fig" rid="fig5s1">Figure 5—figure supplement 1</xref>), even when overexpressed (<xref ref-type="fig" rid="fig3">Figure 3F</xref>), suggesting that these changes in pre-mRNA splicing are indirect. For example, these splicing changes may result from changes in the levels of splicing factors whose mRNAs are translationally regulated by Msi proteins.<fig-group><fig id="fig5" position="float"><object-id pub-id-type="doi">10.7554/eLife.03915.014</object-id><label>Figure 5.</label><caption><title>Global impact of Msi proteins on alternative splicing.</title><p>(<bold>A</bold>) Sashimi plot for <italic>Myo18a</italic> alternative exon 38 with Percent Spliced In (Ψ) estimates by MISO (values with 95% confidence intervals, right panel.) Exon splicing is repressed by <italic>Msi1</italic> overexpression and slightly increased in knockout <italic>Msi1/2</italic> cells. ‘+’ indicates samples treated with Dox/Tam for overexpression/knockout cells, respectively. E12.5 neural stem cells were used for all samples except <italic>Msi1</italic> overexpression for which an additional E13.5 NSC time point was sequenced. (<bold>B</bold>) Number of differential events (MISO Bayes factor ≥10, ΔΨ ≥ 0.12) in each alternative RNA processing category (SE—skipped exons, A5SS—alternative 5′ splice site, A3SS—alternative 3′ splice site, MXE—mutually exclusive exons, RI—retained introns) for <italic>Msi1</italic> overexpression (‘Msi1 OE’), <italic>Msi2</italic> overexpression (‘Msi2 OE’), double knockouts (‘Double KO’), and a Dox control pair (‘Control’). (<bold>C</bold>) Comparison of ΔΨ in <italic>Msi1</italic> overexpression vs control binned by direction (‘Spliced in’ or ‘Spliced out’, x-axis) to ΔΨ in <italic>Msi2</italic> overexpression cells and in double knockout cells (along with respective Tam and Dox controls, y-axis). (<bold>D</bold>) Computational strategy for identifying human orthologs of alternative exon trios regulated in mouse neural stem cells. Orthologous exon trios were identified by synteny using multiple genome alignments. (<bold>E</bold>) Comparison of ΔΨ mouse alternative exons by <italic>Msi1</italic> (comparing overexpression to control, x-axis) and ΔΨ of their orthologous exon trios in human (comparing luminal and basal cell lines, y-axis). Two pairs of luminal and basal cells compared: BT474 vs MDAMB231 and SKBR3 vs MDAMB231. ΔΨ value distributions summarized by violin plots with a dot indicating the mean ΔΨ value.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.014">http://dx.doi.org/10.7554/eLife.03915.014</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915f005"/></fig><fig id="fig5s1" position="float" specific-use="child-fig"><object-id pub-id-type="doi">10.7554/eLife.03915.015</object-id><label>Figure 5—figure supplement 1.</label><caption><title>Subcellular localization of MSI1 protein in murine NSCs.</title><p>(<bold>A</bold>) Immunofluorescence staining in mouse neural stem cells for MSI1 (red) and hnRNP A2/B1 (green). MSI1 shows predominantly cytoplasmic localization, while hnRNP A2/B1, a splicing factor, is predominantly nuclear. Confocal maximum Z intensity projections shown, 10 μm scale. (<bold>B</bold>) Western blot analysis for MSI1/2 and alpha-Tubulin (TUB) in total protein lysate (T), cytoplasmic protein lysate (<bold>C</bold>) and nuclear protein lysate (N) in control and Msi2 overexpressing cells.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.015">http://dx.doi.org/10.7554/eLife.03915.015</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915fs008"/></fig><fig id="fig5s2" position="float" specific-use="child-fig"><object-id pub-id-type="doi">10.7554/eLife.03915.016</object-id><label>Figure 5—figure supplement 2.</label><caption><title>Analysis of two conserved Msi-induced splicing changes in breast cancer tumors.</title><p>(<bold>A</bold>) Distribution of MISO ΔΨ values in matched tumor–control pairs for Erbin (Erbb2ip) exon in light blue and Myo18a in dark blue. Right and left shifts from center (marked by dotted grey line at ΔΨ = 0) indicate tumor-enhanced and tumor-repressed splicing patterns, respectively. (<bold>B</bold>) Comparison of RNA fold changes in matched tumor–control pairs for Msi1 and Msi2 in Basal (left) and Luminal (right) tumors with ΔΨ values for Erbin and Myo18a exons. Points/triangles indicate luminal/basal tumor types determined by PAM50.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.016">http://dx.doi.org/10.7554/eLife.03915.016</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915fs009"/></fig></fig-group></p><p>To test whether <italic>Msi1</italic> and <italic>Msi2</italic> affect pre-mRNA splicing in similar ways, we compared the direction of splicing changes following <italic>Msi1</italic> or <italic>Msi2</italic> overexpression. Exons with increased inclusion following <italic>Msi1</italic> overexpression tended to show increased inclusion following <italic>Msi2</italic> overexpression as well, while <italic>Msi1</italic> OE-induced splicing changes were uncorrelated with Dox-induced changes (<xref ref-type="fig" rid="fig5">Figure 5C</xref>). A similar pattern was observed for exons with decreased inclusion (<xref ref-type="fig" rid="fig5">Figure 5C</xref>). These observations suggested that <italic>Msi1</italic> and <italic>Msi2</italic> trigger similar effects on mRNA splicing. Splicing changes observed in the <italic>Msi1/Msi2</italic> double knockout cells exposed to 4-OHT were inversely correlated to those observed following Msi overexpression (<xref ref-type="fig" rid="fig5">Figure 5C</xref>). This observation further supports that Msi proteins affect splicing at physiological expression levels. No correlation in splicing was observed between <italic>Msi1</italic>-induced cells and exposure to 4-OHT of double floxed cells lacking the Cre driver (<xref ref-type="fig" rid="fig5">Figure 5C</xref>).</p></sec><sec id="s2-8"><title>Msi-associated splicing changes are observed in cancer lines and associated with luminal state</title><p>We next considered whether the splicing changes associated with Msi mis-expression in NSCs might be related to splicing changes observed in human breast cancer cells or with a particular cell state. The natural variation in Msi levels across breast cancer cell lines (<xref ref-type="fig" rid="fig2">Figure 2C–E</xref>) enabled a comparison of splicing patterns between Msi-high (luminal) vs Msi-low (basal) cells. To compare mouse and human splicing patterns, we identified human alternative exon trios orthologous to mouse alternative and flanking exon trios using synteny in a multi-genome alignment (<xref ref-type="fig" rid="fig5">Figure 5D</xref> and Supp. ‘Materials and methods’). We first compared changes (ΔΨ) in the percent spliced in (PSI or Ψ) values of mouse exons between <italic>Msi1</italic> overexpressing cells vs controls, to ΔΨ values of orthologous exons between luminal and basal breast cancer cell lines (<xref ref-type="fig" rid="fig5">Figure 5E</xref>). The splicing patterns were consistent: the human orthologs of exons up-regulated in Msi1-OE NSCs had higher inclusion in luminal (Msi-high) than in basal (Msi-low) cell lines, and similarly for down-regulated exons (<xref ref-type="fig" rid="fig5">Figure 5E</xref>). Such agreement was observed for several different luminal and basal pairs, but was strongest when comparing HER2+ luminal lines such as BT474 and SKBR3 to basal lines, consistent with the higher Msi levels observed in HER2+ cell lines (<xref ref-type="fig" rid="fig2">Figure 2D</xref>). These observations support the proposition that Msi contributes to a luminal splicing program in human breast cancers by triggering changes similar to those induced in mouse NSCs.</p><p>Two of the most strongly affected alternative exons in murine NSCs, <italic>Myo18a</italic> exon 38 (<xref ref-type="fig" rid="fig5">Figure 5A</xref>) and <italic>Erbin</italic> exon 21 (Erbb2ip, a direct binding-partner of the breast cancer oncogene HER2/Erbb2) were conserved in the human genome and detected in the transcriptomes of all analyzed breast tumors and controls. In primary tumors, these exons showed a striking cancer-associated splicing pattern, with the <italic>ERBIN</italic> exon enhanced in tumors and the <italic>MYO18A</italic> exon repressed in tumors (<xref ref-type="fig" rid="fig5s2">Figure 5—figure supplement 2A</xref>). To test whether the regulation of these exons is responsive to Msi levels, we correlated the fold change in Msi expression for each matched tumor–control pair with the ΔΨ value of the <italic>ERBIN</italic> and <italic>MYO18A</italic> exons in that pair (<xref ref-type="fig" rid="fig5s2">Figure 5—figure supplement 2B</xref>). We observed high correlation between the extent of Msi overexpression and the change in splicing in luminal tumors, particularly for <italic>MSI2</italic>. As in mouse NSCs, increased expression of Msis was associated with increased inclusion of the <italic>ERBIN</italic> exon and repression of <italic>MYO18A</italic> exon splicing, suggesting that Msi-dependent regulation of splicing may be conserved not only in breast cancer cell lines but also in primary tumors.</p></sec><sec id="s2-9"><title>Msi proteins are required to maintain epithelial-luminal state in breast cancer cells and regulate EMT processes</title><p>To address whether Msi proteins are functionally required for the maintenance of the luminal state, we performed RNAi knockdown of <italic>Msi1</italic> and <italic>Msi2</italic> in two luminal breast cancer cell lines, BT474 and MCF7-Ras, where Msi proteins are highly expressed (<xref ref-type="fig" rid="fig2">Figure 2C</xref> and <xref ref-type="fig" rid="fig6s1">Figure 6—figure supplement 1A</xref>). In the HER2+ luminal cell line BT474, cells grow in tightly packed epithelial colonies (<xref ref-type="fig" rid="fig6">Figure 6A</xref>). We observed a striking morphological change upon knockdown of <italic>MSI1</italic> or <italic>MSI2</italic>, where cells progressively separated and acquired a basal-like appearance 3–5 days after knockdown (<xref ref-type="fig" rid="fig6">Figure 6A</xref>), accompanied by reduced proliferation (not shown). A similar phenotype was observed in MCF7-Ras cells upon knockdown of <italic>MSI1</italic> or <italic>MSI2</italic> (<xref ref-type="fig" rid="fig6s1">Figure 6—figure supplement 1B</xref>). These results argue that Msi expression is required for the maintenance of the epithelial-luminal state in breast cancer cell lines.<fig-group><fig id="fig6" position="float"><object-id pub-id-type="doi">10.7554/eLife.03915.017</object-id><label>Figure 6.</label><caption><title>Msi levels alter EMT processes breast cancer cell lines.</title><p>(<bold>A</bold>) Knockdown of <italic>Msi1/Msi2</italic> in BT474 breast cancer cell line using lentiviruses carrying short hairpins (shRNAs). Brightfield images (10x magnification) shown at 24, 72, and 120 hr after Puromycin-selection. (<bold>B</bold>) mRNA expression of epithelial and mesenchymal markers upon knockdown of <italic>Msi1/Msi2</italic> in epithelial-luminal breast cancer cell line (BT474) and overexpression of <italic>Msi1</italic> in mesenchymal-basal line (MDAMB231). Values plotted are fold changes normalized to GAPDH. For BT474 knockdown, cells infected with hairpin against luciferase were used as control (‘Control sh’). For MDAMB231 overexpression, cells infected with tdTomato were used as controls (‘Msi1-tdT’). <italic>Msi1</italic> levels were below detection limit in control MDAMB231 cells, therefore <italic>Msi1</italic> fold change in MDAMB231 <italic>Msi1</italic>-overexpression cells (relative to controls) was truncated arbitrarily in plot, indicated by ‘^’. (<bold>C</bold>) Representative transwell assay image for LM2 control and Msi1-OE breast cancer cells. (<bold>D</bold>) Quantification of percent of well covered in transwell assay for LM2 control and Msi1-OE cells (4 wells per condition, individual well values plotted as dots.).</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.017">http://dx.doi.org/10.7554/eLife.03915.017</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915f006"/></fig><fig id="fig6s1" position="float" specific-use="child-fig"><object-id pub-id-type="doi">10.7554/eLife.03915.018</object-id><label>Figure 6—figure supplement 1.</label><caption><title>Knockdown of <italic>Msi1/2</italic> in breast cancer cell lines.</title><p>(<bold>A</bold>) Western blot for BT474 cells with control (shLuc) or Msi1/2 targeting hairpins. (<bold>B</bold>) Morphology of MCF7-Ras cells upon Musashi knockdown.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.018">http://dx.doi.org/10.7554/eLife.03915.018</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915fs010"/></fig></fig-group></p><p>The Notch pathway regulator <italic>Jag1</italic>, which we found was translationally repressed by Msi, is known to be required for EMT. <italic>Jag1</italic>-depleted keratinocytes undergoing TGFβ-induced EMT fail to express mesenchymal markers and retain epithelial morphology (<xref ref-type="bibr" rid="bib49">Zavadil et al., 2004</xref>). Furthermore, knockdown of <italic>Jag1</italic> in keratinocytes strongly impairs wound healing (<xref ref-type="bibr" rid="bib4">Chigurupati et al., 2007</xref>), a process that requires cells to acquire mesenchymal properties such as migration and protrusion. Our gene expression analysis also supported the mesenchymal-basal specific expression of <italic>Jag1</italic>, which is particularly pronounced in breast cancer (<xref ref-type="fig" rid="fig2">Figure 2</xref>). The epithelial-associated expression pattern of Msi genes and the antagonistic relation between Msi and <italic>Jag1</italic> (<xref ref-type="fig" rid="fig2">Figure 2</xref>) prompted the hypothesis that Msi activation promotes an epithelial cell identity, effectively blocking EMT.</p><p>To test the hypothesis that Msi activation may hinder EMT processes by promoting the epithelial state, we assessed the effect of Msi knockdown and overexpression on EMT marker expression. Knockdown of <italic>MSI1</italic> or <italic>MSI2</italic> in the luminal cell line BT474 generally resulted in a decrease in epithelial marker expression and an increase in mesenchymal marker expression, consistent with Msi loss promoting EMT (<xref ref-type="fig" rid="fig6">Figure 6B</xref>). To test whether ectopic expression of Msi in mesenchymal cancer cells can promote an epithelial state, we overexpressed <italic>Msi1</italic> in the mesenchymal cell line MDAMB231, where <italic>Msi1</italic> levels are extremely low. <italic>Msi1</italic>-overexpressing cells had decreased mesenchymal marker expression and increased levels of epithelial marker expression (<xref ref-type="fig" rid="fig6">Figure 6B</xref>), consistent with promotion of the epithelial state. We conclude that Msi activation promotes the epithelial state in breast cancer cells.</p><p>We next asked whether the increase in epithelial markers following Msi overexpression is accompanied by functional changes that reflect the epithelial state. We predicted that ectopic expression of Msi proteins in a mesenchymal cell line would hinder EMT-associated processes such as migration. <italic>Msi1</italic> overexpression in the LM2 cell line (an MDAMB231-derivative) resulted in sevenfold reduction in migration in a transwell assay (<xref ref-type="fig" rid="fig6">Figure 6C,D</xref>). We were unable to observe this phenotype in the mesenchymal cell lines MDAMB231 or SUM159, where <italic>Msi1</italic> overexpression caused no significant change in migration in the same transwell assays (data not shown). In NSCs, overexpression of <italic>Msi1</italic> or <italic>Msi2</italic> impaired migration as assayed by a scratch assay as well (data not shown), consistent with the phenotype observed in LM2 breast cancer cells. These results show that depending on the cell-type context, Msi activation can decrease the migration capacity of cells, consistent with promotion of an epithelial state and suppression of mesenchymal properties.</p></sec><sec id="s2-10"><title><italic>Msi2</italic> overexpression in the basal cell layer perturbs mammary ductal branching</title><p>The association of Msis with the luminal state in breast cancer tumors and their effect on the epithelial-luminal state in breast cancer cell lines prompted us to ask whether Msi proteins play similar roles in the mammary gland in vivo. During maturation, epithelial cells in the mammary gland migrate and form ducts within the mammary fat pad through a process termed mammary ductal branching morphogenesis. The formation of the mammary ductal system is thought to be a kind of EMT (<xref ref-type="bibr" rid="bib50">Chakrabarti et al., 2012</xref>; <xref ref-type="bibr" rid="bib9a">Foubert et al., 2010</xref>), making mammary gland an attractive system to study the regulation of EMT in vivo.</p><p>The mammary gland Terminal End Buds (TEBs) from which ducts form are organized into discrete layers of cell types, including epithelial luminal and basal cells. The identity of luminal and basal tumors is thought to resemble their mammary gland cell type counterparts. Analysis of RNA-Seq expression analysis of purified mouse mammary luminal (CD24<sup>high</sup>CD29<sup>+</sup>) and basal (CD24<sup>+</sup>CD29<sup>high</sup>) cells generated by <xref ref-type="bibr" rid="bib8">dos Santos et al. (2013)</xref> revealed enrichment of <italic>Msi1</italic> and <italic>Msi2</italic> expression in luminal cells (not shown). As predicted by the mRNA expression profile, we observed higher MSI2 protein levels in the luminal cell layer and far lower levels in the basal (K14-positive) cell layer of mouse mammary ducts (<xref ref-type="fig" rid="fig7">Figure 7A</xref>).<fig-group><fig id="fig7" position="float"><object-id pub-id-type="doi">10.7554/eLife.03915.019</object-id><label>Figure 7.</label><caption><title>Msi2 activation represses EMT and expands mammary luminal cell layer in vivo.</title><p>(<bold>A</bold>) Immunostaining for MSI2, K14, and DAPI in control sections of mammary gland. Scale bar: 50 μm (<bold>B</bold>) qRT-PCR for <italic>Msi2</italic> in mammary epithelial cells from control and <italic>Msi2</italic> overexpressing mice (‘Msi2-OE’). (<bold>C</bold>) Whole mount stain for mammary glands from control and <italic>Msi2</italic> overexpressing mice (left: low magnification, right: high magnification.) (<bold>D</bold>) Immunostaining for K14, K8, and DAPI in mammary gland sections from control and <italic>Msi2</italic> overexpressing mice. Scale bar: 100 μm (<bold>E</bold>) qRT-PCR for luminal markers (K8, K18), basal markers (K14), and smooth-muscle Actin (SMA) in mammary epithelial cells from control and <italic>Msi2</italic> overexpressing mice. (<bold>F</bold>) Staining for E-cadherin (ECAD) (top) and EMT-marker SLUG (bottom) in mammary glands from control and <italic>Msi2</italic> overexpressing mice. Luminal cell layer is expanded upon Dox (arrows). Scale bar: 100 μm. (<bold>G</bold>) qRT-PCR for Slug, Gata3, Twist1, Twist2 in mammary epithelial cells from control and <italic>Msi2</italic> overexpressing mice. Slug expression in basal cell layer is reduced upon Dox (arrows). Scale bar: 50 μm.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.019">http://dx.doi.org/10.7554/eLife.03915.019</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915f007"/></fig><fig id="fig7s1" position="float" specific-use="child-fig"><object-id pub-id-type="doi">10.7554/eLife.03915.020</object-id><label>Figure 7—figure supplement 1.</label><caption><title><italic>Msi2</italic> overexpression in mouse mammary gland alters mammary duct morphology.</title><p>(<bold>A</bold>) Msi2 expression in mammary glands co-stained with basal cell marker K14 in control and Msi2 overexpressing mice. (<bold>B</bold>) Quantification of number of branch points in control and Msi2 overexpression mice. Student's <italic>t</italic>-test was used to compute p-values. (<bold>C</bold>) Lengths of longest mammary ductal branches (measured from Center of Lymph Node, CLN) for control and Msi2 overexpression mice. CLN defined as ‘0’: negative length values indicate that longest ductal branch ends prior to start of CLN, positive length values indicate that longest ductal branch grew past center of CLN. Student's <italic>t</italic>-test was used to compute p-values. (<bold>D</bold>) Co-staining for luminal cell marker K8 and basal cell marker K14 in control (left) and Msi2 overexpressing (right) mice.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.020">http://dx.doi.org/10.7554/eLife.03915.020</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915fs011"/></fig><fig id="fig7s2" position="float" specific-use="child-fig"><object-id pub-id-type="doi">10.7554/eLife.03915.021</object-id><label>Figure 7—figure supplement 2.</label><caption><title><italic>Msi2</italic> overexpression in mouse mammary gland represses Slug and Jag1.</title><p>(<bold>A</bold>) Staining for EMT marker Slug in control and Msi2 overexpressing mice. Scale bar: 50 μm. (<bold>B</bold>) Western blot for JAG1 protein in mammary epithelial cells of control and Msi2 overexpressing mice 7 weeks after induction with Dox. Arrow indicates expected JAG1 band (150 kD). (<bold>C</bold>) Immunohistochemistry for JAG1 protein in mammary gland from control and Msi2 overexpressing mice 7 weeks after induction with Dox.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.021">http://dx.doi.org/10.7554/eLife.03915.021</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915fs012"/></fig></fig-group></p><p>We next examined the effect of Msi overexpression on epithelial cell state in the mammary gland in order to see whether its in vivo effects on epithelial-luminal state are similar to those observed in culture models. We ectopically expressed <italic>Msi2</italic> in the basal cell layer, where it is nearly absent normally (<xref ref-type="fig" rid="fig7">Figure 7A</xref>), using a basal cell-specific Dox-inducible driver, K14-rtTA. As expected, mice administered Dox showed significantly higher levels of MSI2 protein in the basal cell layer (<xref ref-type="fig" rid="fig7s1">Figure 7—figure supplement 1A</xref>) and overall higher levels of <italic>Msi2</italic> mRNA in mammary epithelial cells (<xref ref-type="fig" rid="fig7">Figure 7B</xref>).</p><p>Overexpression of <italic>Msi2</italic> altered mammary ductal branching morphology (<xref ref-type="fig" rid="fig7">Figure 7C</xref>). Overexpression mice showed both a defective and delayed mammary ductal branching pattern. <italic>Msi2</italic> overexpression resulted in fewer mammary duct branch points given, after either 4 or 7 weeks of induction with Dox, with the difference between controls and overexpression mice more pronounced after 7 weeks (<xref ref-type="fig" rid="fig7s1">Figure 7—figure supplement 1B</xref>). The TEBs in glands overexpressing <italic>Msi2</italic> were smaller relative to controls, following either 4 or 7 weeks of induction (<xref ref-type="fig" rid="fig7">Figure 7C</xref>, right inset). In addition, after 4 weeks of induction, glands from overexpression mice had shorter ductal lengths relative to controls, but ductal lengths returned to lengths similar to wild type after 7 weeks of induction (<xref ref-type="fig" rid="fig7s1">Figure 7—figure supplement 1C</xref>). These results indicate that <italic>Msi2</italic> overexpression resulted in a defect in mammary branching morphogenesis (evidenced by the reduced number of branch points), and a delay in this process, as indicated by the slower rate of branch ductal growth.</p><p>Since branching morphogenesis requires cells to lose their epithelial identity and undergo migration, we hypothesized that the observed defect in branching morphology might result from inability of cells to lose their epithelial identity and/or expansion of an epithelial cell layer. Consistent with this hypothesis, we observed that <italic>Msi2</italic> overexpression resulted in expansion of the luminal cell layer (<xref ref-type="fig" rid="fig7">Figure 7D</xref> and <xref ref-type="fig" rid="fig7s1">Figure 7—figure supplement 1D</xref>), confirmed by a corresponding increase in expression of luminal cell markers and a decrease in basal markers (<xref ref-type="fig" rid="fig7">Figure 7E</xref>). Furthermore, <italic>Msi2</italic> overexpression led to an increase in epithelial marker E-cadherin and reduction in Slug, a marker of EMT and mesenchymal cells. Expression of EMT regulators <italic>Slug</italic>, <italic>Twist1,</italic> and <italic>Twist2</italic> decreased upon <italic>Msi2</italic> overexpression, while expression of the luminal epithelial cell marker <italic>Gata3</italic> increased (<xref ref-type="fig" rid="fig7">Figure 7G</xref> and <xref ref-type="fig" rid="fig7s2">Figure 7—figure supplement 2A</xref>). Expression of JAG1 protein was also reduced upon <italic>Msi2</italic> overexpression, consistent with the results observed in murine NSCs (<xref ref-type="fig" rid="fig7s2">Figure 7—figure supplement 2B,C</xref>). These results support a model in which ectopic Msi expression leads to expansion of epithelial-luminal cells in the mammary gland, effectively blocking EMT processes required for normal branching morphogenesis, and resulting in the defective ductal branching pattern described above. The observed functions of Msi proteins in regulation of mammary epithelial cell state mirror the functions we observed in breast cancer cell lines and murine NSCs, and suggest that Msi proteins play similar roles in a healthy in vivo context as in cancer cells.</p></sec></sec><sec sec-type="discussion" id="s3"><title>Discussion</title><p>The specific expression patterns of Msi proteins in stem and epithelial cells have aroused interest in their functional roles. Here, we show that Msi proteins are associated with the epithelial-luminal cell state in several cancer types, notably breast cancer, where Msi genes are highly enriched in luminal tumors and luminal breast cancer cell lines. We showed that in breast cancer cells, knockdown of Msi genes leads to loss of epithelial identity and upregulation of mesenchymal markers, while their ectopic activation promotes the epithelial state and suppresses mesenchymal properties such as cell migration. As in cancer cells, overexpression of <italic>Msi2</italic> in healthy mammary gland tissue suppressed EMT and resulted in a defective mammary ductal branching pattern. These observations all support a role for Msi proteins in maintenance of a luminal/epithelial cell state and inhibition of EMT (<xref ref-type="fig" rid="fig8">Figure 8</xref>). The consistency between our observations in mammary epithelial cells and NSCs and between mouse and human suggests that these functions are shared across cell types and evolutionarily conserved.<fig id="fig8" position="float"><object-id pub-id-type="doi">10.7554/eLife.03915.022</object-id><label>Figure 8.</label><caption><title>Model for Msi roles in regulation of cell state.</title><p>Model for Msi role in the control of the epithelial state. We show that Msi represses translation of <italic>Jag1</italic>, a positive regulator of Notch and EMT. We also show that Msi promotes expression of an epithelial-luminal splicing program, which we hypothesize occurs through translational regulation of splicing factors. In the model, both the direct regulation of <italic>Jag1</italic> and indirect regulation of splicing contribute to maintenance of an epithelial-luminal cell state and inhibition of EMT.</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.022">http://dx.doi.org/10.7554/eLife.03915.022</ext-link></p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="elife03915f008"/></fig></p><p>Our genome-wide data support the hypothesis that Msi proteins are translational regulators. We showed that Msi proteins can translationally repress <italic>Jag1</italic>, an important regulator of Notch signaling. However, the role of Notch signaling in cancer remains complex and may vary between cancer types (<xref ref-type="bibr" rid="bib7">Dickson et al., 2007</xref>; <xref ref-type="bibr" rid="bib23">Lobry et al., 2011</xref>). The upregulation of <italic>Jag1</italic> in the basal state suggests that Notch pathway activity is high in and required for the entry into the mesenchymal state, consistent with previous studies (<xref ref-type="bibr" rid="bib49">Zavadil et al., 2004</xref>; <xref ref-type="bibr" rid="bib7">Dickson et al., 2007</xref>). In mammary epithelial cells, <italic>Jag1</italic>-triggered activation of Notch was shown to reduce E-cadherin expression and increase Slug expression (<xref ref-type="bibr" rid="bib22">Leong et al., 2007</xref>). Furthermore, <italic>Jag1</italic> activation in breast cancer cells promotes their metastasis into the bone in vivo by activating Notch in neighboring bone cells (<xref ref-type="bibr" rid="bib38">Sethi et al., 2011</xref>). The dependence of EMT on Notch activation has been observed in normal development as well. During heart development, cardiac valves are generated from endocardium through EMT, and Notch activity was shown to be required for this process (<xref ref-type="bibr" rid="bib42">Timmerman et al., 2004</xref>). Collectively, these studies are consistent with our working model in which Msi represses <italic>Jag1</italic> translationally, in turn altering Notch activity required for EMT.</p><p>The molecular mechanisms by which Msi proteins regulate translation of a subset of mRNAs like <italic>Jag1</italic> remains unclear. Our genome-wide data and in vitro binding assays indicate that Msi proteins act by binding UAG-containing motifs at 3' UTRs of messages. A model where Msi proteins repress translation by outcompeting eIF4G for PolyA-binding protein (PABP) was proposed (<xref ref-type="bibr" rid="bib15">Kawahara et al., 2008</xref>), but the conditions under which binding to mRNA results in translational repression are unclear, since only a subset of mRNAs are detectably regulated. It is possible that co-factors are required in vivo for Msi to affect translation following binding to the mRNA. It is also possible that other RNA-binding factors outcompete Msi protein for binding, though MSI1 has relative high RNA-binding affinity. The molecular mechanism underlying Musashi-dependent translational control and the nature of any co-factors involved are not known.</p><p>This study complements recent reports of the involvement of post-transcriptional regulatory factors in cell state maintenance and EMT. For example, the epithelial-specific splicing factors of the ESRP family play important roles in maintenance of epithelial state (<xref ref-type="bibr" rid="bib46">Warzecha et al., 2009</xref>; <xref ref-type="bibr" rid="bib36">Reinke et al., 2012</xref>). A recent study presented evidence that the transcription factor Snail can promote the mesenchymal state in part by repressing <italic>Esrp1</italic> (<xref ref-type="bibr" rid="bib36">Reinke et al., 2012</xref>), further highlighting the importance of post-transcriptional control in driving cell state transitions like EMT.</p><p>Like master transcription factors, master post-transcriptional regulatory factors globally alter gene expression—by affecting RNA splicing, stability, localization, or translation—which makes them suitable for controlling cell identity (<xref ref-type="bibr" rid="bib51">Jangi and Sharp, 2014</xref>). Our study shows that post-transcriptional regulatory factors like Msi proteins can impact both translation and pre-mRNA splicing, utilizing multiple layers of RNA regulation to reshape the transcriptome for a particular cell state. Many of the impacted splicing events are part of an epithelial splicing program, suggesting that effects of Msis on splicing may reinforce the effects of <italic>Jag1</italic> repression on maintenance of epithelial cell state. The predominantly cytoplasmic expression of Msis makes it likely that splicing is affected indirectly, e.g., through translational regulation of specific splicing factors, though our data do not rule out that a small fraction of Msi protein may be nuclear localized and could directly regulate splicing. We have also observed that other RBPs are also enriched in the epithelial state (<xref ref-type="bibr" rid="bib39">Shapiro et al., 2011</xref>), suggesting that RBPs as a group may play a broad role in maintenance of this state, and might provide attractive targets for therapeutic efforts to manipulate cell state.</p><p>Msi proteins are co-expressed with various proliferation markers in a wide variety of stem cell niches, including the breast, stomach, intestine, lung, and brain. This observation suggests the hypothesis that Msis may act as general epithelial stem cell/progenitor regulators across tissues. Our findings are consistent with this hypothesis, but further study of Msi in multiple stem cell compartments will be needed to directly test it. The role of Msi in the normal development and transformation of other adult tissues will also be important to understand. For example, our observation that Msi is frequently overexpressed in lung tumors suggests that ectopic expression of Msi proteins in the lung could elucidate their role in lung cancer. Furthermore, the systematic downregulation of <italic>Msi1/Msi2</italic> and high frequency of <italic>Msi1</italic> mutations in kidney tumors suggests that kidney would be an informative model for studying Msi loss-of-function and its consequences in cancer.</p></sec><sec sec-type="materials|methods" id="s4"><title>Materials and methods</title><sec id="s4-1"><title>Mouse strains and derivation of neural stem cell lines</title><p>Inducible overexpression mice (tetO-Msi1/Msi2) were generated as previously described in <xref ref-type="bibr" rid="bib1">Beard et al. (2006)</xref>; <xref ref-type="bibr" rid="bib17">Kharas et al. (2010)</xref>. The generation of <italic>Msi2</italic> conditional knockout mice was previously described in <xref ref-type="bibr" rid="bib32">Park et al. (2014)</xref>, and the generation of <italic>Msi1</italic> conditional knockout mice will be described elsewhere (Yu et al., under review). Mice of the 129SvJae strain were used, and the K14-rtTA strain was obtained from JAX (stock number: 007678). Animal care was in accordance with institutional guidelines and approved by the Committee on Animal Care, Department of Comparative Medicine, Massachusetts Institute of Technology, under animal protocol 1013-088-16. For derivation of embryonic neural stem cells (NSCs), littermate embryos were used whenever possible. Cortical NSCs were derived from embryos following <xref ref-type="bibr" rid="bib18">Kim et al. (2003)</xref>. Briefly, cortical tissue was isolated from E12.5 embryos (unless otherwise noted) under a light dissection microscope inside a sterile fume hood and collected by centrifugation. Cortical tissues were dissociated into single cells by trituration in Magnesium/Calcium-free HBSS buffer (Gibco, Woburn MA) followed by 15-min incubation at room temperature. Dissociated tissue was collected by centrifugation, resuspended in N2 medium containing growth factors and Laminin (Life Technologies, Woburn MA, Catalog Number: 23017015) and plated onto Polyornithin/Laminin-coated tissue culture dishes as in <xref ref-type="bibr" rid="bib29">Okabe et al. (1996)</xref>.</p></sec><sec id="s4-2"><title>Culture conditions for embryonic neural stem cells</title><p>NSCs were grown in N2 medium (<xref ref-type="bibr" rid="bib29">Okabe et al., 1996</xref>) containing EGF (20 ng/ml) and bFGF (20 ng/ml) and Laminin (Life Technologies). Cells were grown on Polyornithin/Laminin-coated dishes. EMT was induced by switching cells to N2 medium containing LIF/FBS as described in <xref ref-type="bibr" rid="bib2">Ber et al. (2012)</xref>.</p></sec><sec id="s4-3"><title>Culture conditions for human breast cancer lines, shRNA knockdowns and overexpression assays</title><p>All breast cancer lines were cultured in DME containing 10% FBS, 1% GlutaMAX (Gibco), and Penn/Strep, except for BT474, which was cultured in RPMI base medium, and SKBR3 which was cultured with McCoy's 5A supplement. Lentiviruses carrying pLKO vectors with hairpins against <italic>Msi1</italic>, <italic>Msi2</italic>, or Luciferase (control) were used for knockdowns. Hairpins were obtained from Broad Institute shRNA library. Cells were infected in a centrifuge spin-infection step (1500 RPM, 37°C, 20 min) following a 2-hr incubation with polybrene or protamine sulfate, and viral medium was added to the cells overnight. Cells were subjected to 4–6 day Puromycin selection (2 μg/ml) 48 hr after infection. Msi1-OE vector (Thermo OpenBiosystems) was used for overexpression assays. Virus was prepared was described above and cell lines infected with virus were selected for 4–6 days with Blasticidin (5 μg/ml) 48 hr after infection.</p></sec><sec id="s4-4"><title>Migration assay in breast cancer cell lines</title><p>Migration assay was performed using the transwells (Corning 6.5 mm Diameter inserts with 8um pore size, polycarbonate membrane; product #3422, lot #19614003). 50,000 cells were seeded into wells in each condition and allowed to migrate for 9 hr. Cells were stained with Crystal Violet and then percent area covered was calculated using ImageJ. Images were threshold filtered on Hue and Saturation (Hue: 192-255 'pass'; Saturation: 72-255 'pass') and passed to the ‘Analyze Particles’ function with a threshold size of 2000.</p></sec><sec id="s4-5"><title>Western blotting, immunofluorescence staining, and antibodies used</title><p>For western blotting, cells were lysed on ice and protein lysates were loaded onto 4-12% gradient Bis-Tris Gel (Life Technologies). Primary antibodies and dilutions used in western blotting on murine NSCs: anti-MSI1/2 (Cell Signaling Technology #2154, 1:800), anti-MSI2 (Abcam #57341, 1:800), anti-Jag1 (Cell Signaling Technology #2620, 1:800), anti-HER2 (Cell Signaling Technologies #2248, 1:1000), anti-phos-HER2 (Cell Signaling Technology #2241, 1:1000), anti-alpha-Tubulin (Sigma-Aldrich T9026, 1:5000), anti-HNRNPA1 (Abcam ab5832, 1:800). Immunofluorescene was performed on cells grown on glass bottom chambers (LabTek II, #1.5), fixed in 4% PFA. Cells were blocked and permeabilized in 5% FBS, .1% Triton in PBS(+). Antibodies were applied in 1% FBS in PBS(+). Immunofluorescence antibodies and dilutions: anti-MSI1 (MBL D270-3, 1:500), anti-HNRNP A2/B1 (Santa Cruz, sc-374052, 1:200). For IHC on murine mammary glands, anti-Jag1 (Santa Cruz, SC-6011, 1:100) was used. For western on murine mammary glands, anti-Jag1 (Santa Cruz, SC-6011, 1:1000) and anti-Tubulin (Sigma-Aldrich, T5168, 1:4000) were used.</p></sec><sec id="s4-6"><title>Immunohistochemistry on human breast cancer sections</title><p>Paraffin-embedded human breast cancer sections were obtained from Biomax US (BR1505a) and stained using standard protocols with antigen retrieval. Antibodies used: anti-ECAD1 (BD Biosciences, 1:50) and anti-MSI1 (MBL D270-3, 1:200).</p></sec><sec id="s4-7"><title>Confocal imaging for immunofluorescence</title><p>Confocal imaging was performed using a Perkin–Elmer microscope using oil-immersion 63× objective, imaged with Velocity software. Single confocal stacks or maximum Z intensity projections were obtained using Fiji (Bioformats-LOCI plugin).</p></sec><sec id="s4-8"><title>RNA-seq and ribosome profiling library generation</title><p>RNA-Seq libraries were prepared from polyA-selected RNA using standard Illumina protocol. Ribosome profiling libraries were prepared following <xref ref-type="bibr" rid="bib13">Ingolia et al. (2009)</xref> with several modifications. Briefly, cells were collected by centrifugation and immediately flash-frozen. Cells were thawed in lysis buffer (20 mM HEPES [pH 7.0], 100 mM KCl, 5 mM MgCl2, 0.5% Na-Deoxycholate, 0.5% NP-40, 1 mM DTT, Roche mini EDTA-free protease inhibitor tablets [1 tablet/10 ml]) and briefly treated with DNase I and RNAse I. Nuclei and cell debris were removed by centrifugation and lysates were treated with RNase I (NEB) for 75 min at room temperature to generate monosome-protected RNA fragments. Monosomes were collected by ultracentrifugation in a sucrose cushion, denatured in 8 M Guanidium HCl, and protected RNA fragments (footprints) were extracted with Phenol–Chloroform. Footprints were dephosphorylated by PNK treatment and size-selected (∼31–35 nt fragments) by purification from a 15% TBE-Urea gel. Subtractive hybridization of ribosomal RNA from footprints was performed as in (<xref ref-type="bibr" rid="bib44">Wang et al., 2012</xref>). Footprints were then polyA-tailed, and Illumina sequencing adaptors were added in a reverse transcription step to obtain footprint cDNA, which was then isolated by gel purification. cDNA was then circularized, PCR-amplified, and PCR products isolated by gel purification and submitted for sequencing on Illumina Hi-Seq platform.</p></sec><sec id="s4-9"><title>Computational analysis of RNA-Seq, ribosome profiling and bind-n-seq</title><p>Source code for the pipelines used to analyze RNA-Seq, ribosome profiling and Bind-n-Seq data is available through the open-source library <underline>rnaseqlib</underline> (available at the git repository: <ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="http://www.github.com/yarden/rnaseqlib">http://www.github.com/yarden/rnaseqlib</ext-link>). Protocols, raw sequencing data and additional information about genomic datasets are available at <ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="http://www.musashi-genes.org/">http://www.musashi-genes.org</ext-link>.</p><sec id="s4-9-1"><title>Ribosome profiling (ribo-seq) analysis</title><p>To define a set of translationally regulated targets, we first filtered out genes that had low read counts (5 reads or less) in constitutive CDS exons in either RNA-Seq or Ribo-Seq data. We then further filtered out from this set genes that showed 1.5-fold change or greater in mRNA levels between control and experimental samples, to avoid instances where changes in TE may be confounded by changes in mRNA abundances, and therefore are less likely to be controlled solely at the level of translation. From this set of genes, we defined the subset that had a threefold or higher change in TE as the set of translational targets.</p></sec><sec id="s4-9-2"><title>Bind-n-seq (RBNS) analysis</title><p>To define a set of genes with enriched Msi binding sites, we ranked genes according to the abundance of RBNS-enriched 6mers in their 3' UTR. For each gene <italic>g</italic>, we calculated the density an RBNS-enriched 6mer <italic>k</italic> in the gene, <italic>D</italic><sub><italic>g,k</italic>,</sub> as follows:<disp-formula id="equ1"><mml:math id="m1"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mrow><mml:mi>g</mml:mi><mml:mo>,</mml:mo><mml:mi>k</mml:mi></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mi>k</mml:mi></mml:msub></mml:mrow><mml:mrow><mml:mi>u</mml:mi><mml:mo>−</mml:mo><mml:mn>6</mml:mn><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mfrac></mml:mrow></mml:math></disp-formula>where <italic>n</italic><sub><italic>k</italic></sub> is the number of occurrences of the 6mer <italic>k</italic> in the longest 3' UTR of <italic>g</italic>, and <italic>u</italic> is the UTR length. We defined the enrichment density score <italic>S</italic><sub><italic>g</italic></sub> for each gene <italic>g</italic> as the sum of densities of all RBNS-enriched 6mers in the gene:<disp-formula id="equ2"><mml:math id="m2"><mml:mrow><mml:msub><mml:mi>S</mml:mi><mml:mi>g</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mstyle displaystyle="true"><mml:munder><mml:mo>∑</mml:mo><mml:mi>k</mml:mi></mml:munder><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mrow><mml:mi>g</mml:mi><mml:mo>,</mml:mo><mml:mi>k</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mstyle></mml:mrow></mml:math></disp-formula></p><p>We then calculated the distribution of <italic>S</italic><sub><italic>g</italic></sub> for all genes and ranked each gene by its percentile rank. The score for <italic>Jag1</italic> (<italic>S</italic><sub><italic>Jag1</italic></sub>) ranked in the 85<sup>th</sup> percentile of the score distribution.</p></sec></sec><sec id="s4-10"><title>On <italic>Numb</italic> as a translational target of Msi proteins</title><p>Early work on mammalian Musashi proteins by the Okano group and colleagues suggested that <italic>Numb</italic> mRNA is translationally repressed by MSI1 (<xref ref-type="bibr" rid="bib30">Okano et al., 2002</xref>). A later study by the same group showed that in the gastric system, <italic>Msi1</italic> KO mice had lower, not higher, levels of Numb protein, opposite of the expected change under the translational repression model (<xref ref-type="bibr" rid="bib40">Takahashi et al., 2013</xref>). Recent work in HSCs (where only <italic>Msi2</italic> is expressed) showed a <italic>Numb</italic>-independent phenotype for <italic>Msi2</italic> and found that <italic>Msi2</italic> KO HSCs have unchanged levels of Numb protein (<xref ref-type="bibr" rid="bib32">Park et al., 2014</xref>). Thus, it is unclear if <italic>Msi1</italic> or <italic>Msi2</italic> directly regulate <italic>Numb</italic> mRNA translation in all systems and whether such regulation always promotes or represses translation of the mRNA.</p><p>In our data from NSCs, we were unable to detect a large difference in <italic>Numb</italic> translational efficiency upon <italic>Msi1</italic> overexpression as measured by Ribo-Seq, though a small effect cannot be excluded since coverage of the <italic>Numb</italic> mRNA in our Ribo-Seq data was low. It is possible that <italic>Msi1</italic> affects the translation of certain <italic>Numb</italic> mRNA isoforms in a context-specific manner, potentially through alternative mRNA processing of the <italic>Numb</italic> mRNA, as proposed by <xref ref-type="bibr" rid="bib40">Takahashi et al. (2013)</xref>.</p></sec><sec id="s4-11"><title>Sequencing data availability</title><p>All RNA sequencing data was submitted to GEO (accession GSE58423).</p></sec><sec id="s4-12"><title>Computational analysis of TCGA data</title><p>Publicly available TCGA data sets (Level 2 and Level 3) were downloaded from NIH ‘Bulk Download’ website (RNASeqV2: <ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://wiki.nci.nih.gov/display/TCGA/RNASeq+Version+2">https://wiki.nci.nih.gov/display/TCGA/RNASeq+Version+2</ext-link>). RNA-Seq analyses were performed using ‘RNASeqV2’ TCGA files. Fold changes for genes were normalized by correction with Lowess-fit of MA-values calculated using raw gene expression estimates. Alternative exon expression was quantified using MISO.</p></sec><sec id="s4-13"><title>Computational identification of orthologous exon trios between mouse and human</title><p>Syntenic regions for exons in mouse alternative exon trios (mm9) were computed using Ensembl Compara Database (Release 66) PECAN multiple genomes alignment, using the Pycogent Python framework (<xref ref-type="bibr" rid="bib19">Knight et al., 2007</xref>). Syntenic coordinates in human genome (hg19) were then matched to annotated hg19 exon coordinates given in TCGA data files.</p></sec><sec id="s4-14"><title>RNA bind-n-seq protein expression, RNA preparation and binding</title><p>A streptavidin binding peptide (SBP) tag was added to the pGEX6P-1 vector (GE) after the Presceission protease site. Full-length Musashi (<italic>Msi1</italic>) was cloned downstream of the SBP tag with infusion (Clontech) using BamHI and NotI cloning sites. Expression of tagged MSI1 was induced with 0.5 mM IPTG at 18° for 4 hr in the Rosetta(DE3)pLysS <italic>E. coli</italic> strain and subsequently purified on a GST GraviTrap column (GE). MSI1 was eluted from the GST column with PreScission protease (GE) in 4 mL of Protease Buffer (50 mM Tris pH 7.0, 150 mM NaCl, 1 mM EDTA, 1 mM DTT) at 4° C overnight (∼16 hr). Protein purity was assayed SDS-PAGE gel electrophoresis and visualized with SimplyBlue SafeStain (Invitrogen).</p><p>Input random RNA was generated by T7 in vitro transcription: 1 μg T7 oligo was annealed to 1 μg of RBNS T7 template by heating the mixture at 65° C for 5 min then allowing the reaction to cool at room temperature for 2 min. The random RNA was then in vitro transcribed with HiScribe T7 In vitro transcription kit (NEB) according to manufacturer's instructions. The RNA was then gel-purified from a 6% TBE-urea gel.</p><p>Nine concentrations of purified MSI1 (0 nM, 0.5 nM, 2 nM, 8 nM, 16 nM, 64 nM, 256 nM, 1 μM, and 2 μM) were equilibrated in 250 μl of Binding Buffer (25 mM Tris pH 7.5, 150 mM KCl, 3 mM MgCl2, 0.01% Tween, 1 mg/ml BSA, 1 mM DTT, 30 μg/ml poly I/C [Sigma]) for 30 min at room temperature. 40 U of Superasin (Ambion) and 1 μM random RNA (final concentration) was added to the MSI1 solutions and incubated for 1 hr at room temperature. During this incubation, Streptavidin magnetic beads (Invitrogen) were washed three times with 1 ml of wash buffer (25 mM Tris pH 7.5, 150 mM KCl, 60 μg/ml BSA, 0.5 mM EDTA, 0.01% Tween) and then equilibrated in Binding Buffer until needed. MSI1 and interacting RNA was pulled down by adding the RNA/protein solutions to 1 mg of washed streptavidin magnetic beads and incubated for 1 hr at room temperature. Supernatant (unbound RNA) was removed from the beads and the beads washed once with 1 ml of Wash Buffer. The beads were incubated at 70° for 10 min in 100 μl of Elution Buffer (10 mM tris pH 7.0, 1 mM EDTA, 1% SDS) and the supernatant was collected. Bound RNA was extracted from the eluate by phenol/chloroform extraction and ethanol precipitation. Half of the extracted RNA from each condition was reverse transcribed into cDNA using Superscript III (Invitrogen) according to manufacturer’s instructions using the RBNS RT primer. To control for any nucleotide biases in the input random library, 0.5 pmol of the RBNS input RNA pool was also reverse transcribed and Illumina sequencing library prep followed by 8–10 cycles of PCR using High Fidelity Phusion (NEB). As Msi1 concentration was increased, decreasing input RT reaction was required in the PCR. For instance, the highest MSI1 condition required 30-fold less input RT product than the no MSI1 condition. All libraries were barcoded in the PCR step, pooled together, and sequenced one HiSeq 2000 lane.</p></sec><sec id="s4-15"><title>Primers and sequences related to RNA Bind-n-Seq</title><sec id="s4-15-1"><title>RBNS T7 template:</title><p>CCTTGACACCCGAGAATTCCA(N<sub>40</sub>)GATCGTCGGACTGTAGAACTCCCTATAGTGAGTCGTATTA</p></sec><sec id="s4-15-2"><title>T7 oligo:</title><p>TAATACGACTCACTATAGGG</p></sec><sec id="s4-15-3"><title>Resulting RNA Pool:</title><p>GAGTTCTACAGTCCGACGATC(N)40TGGAATTCTCGGGTGTCAAGG</p></sec><sec id="s4-15-4"><title>Binding site used for validation:</title><p>GGCUUCUUAAGCGUUAGUUAUUUAGUUCGUUUGUU</p></sec><sec id="s4-15-5"><title>RBNS RT primer:</title><p>GCCTTGGCACCCGAGAATTCCA</p></sec><sec id="s4-15-6"><title>RNA PCR (RP1):</title><p>AATGATACGGCGACCACCGAGATCTACACGTTCAGAGTTCTACAGTCCGACGATC</p></sec><sec id="s4-15-7"><title>Barcoded Primers:</title><p>CAAGCAGAAGACGGCATACGAGAT–BARCODE-GTGACTGGAGTTCCTTGGCACCCGAGAATTCCA</p></sec><sec id="s4-15-8"><title><italic>Jag1</italic> region 1 sequence:</title><p>UGUCCAGU<bold>UAG</bold>AUCACUGUU<bold>UAG</bold>AU</p></sec><sec id="s4-15-9"><title><italic>Jag1</italic> region 1 mutant:</title><p>UGUCCAGU<bold>UCC</bold>AUCACUGUU<bold>UCC</bold>AU</p></sec><sec id="s4-15-10"><title><italic>Jag1</italic> region 2 sequence:</title><p>UCAAAG<bold>UAG</bold>AAUUUUUGUA<bold>UAG</bold>UUAUGUAAAUAAU</p></sec><sec id="s4-15-11"><title><italic>Jag1</italic> region 2 mutant:</title><p>UCAAAG<bold>UCC</bold>AAUUUUUGUA<bold>UCC</bold>UUAUGUAAAUAAU</p></sec></sec><sec id="s4-16"><title>Luciferase reporter assays for protein translation</title><p>The <italic>Jag1</italic> 3' UTR was cloned into the pRL-SV40 vector (Promega) downstream of Renilla luciferase using the XbaI and NotI restriction sites creating the Renilla-Jag1-UTR construct. Firefly luciferase expression was used as the internal control and expressed from the PGL3 vector (Promega). Renilla and the Firefly luciferase vectors were co-transfected into 293 cells stably expressing hairpins against <italic>Msi1</italic>, <italic>Msi2</italic>, or both <italic>Msi1</italic> and <italic>Msi2</italic>, or into mock transfected 293T cells. Cells were harvested between 30–36 hr after transfection and the Renilla and Firefly luciferase signals measured using the Dual-luciferase Reporter Assay System (Promega) according to manufacture's instructions.</p></sec><sec id="s4-17"><title>In vivo overexpression and whole mount mammary gland staining</title><p>Mice were given Dox (Sigma) via drinking water at 2 g/l. Mice were induced with Dox for 7 weeks unless otherwise indicated. Inguinal mammary glands were spread on glass slides, fixed in Carnoy's fixative (6:3:1, 100% ethanol: chloroform: glacial acetic acid) for 2 to 4 hr at room temperature, washed in 70% ethanol for 15 min, rinsed through graded alcohol followed by distilled water for 5 min, then stained in carmine alum overnight, washed in 70%, 95%, 100% ethanol for 15 min each, cleared in xylene, and mounted with Permount.</p></sec><sec id="s4-18"><title>Immunofluorescence on mammary gland sections</title><p>Mammary glands were fixed in 4% PFA, paraffin-embedded and 5-μm sections were used for immunofluorescence assay. Paraffin sections were microwave pretreated and incubated with primary antibodies, then incubated with secondary antibodies (Invitrogen) and counterstained with DAPI in mounting media. The following antibodies were used: anti-K14 (Abcam), anti-K8 (Abcam), anti-E-cadherin (CST), anti-Msi2 (Novus Biologicals), anti-Hes1 (Abcam), anti-Slug (CST).</p></sec><sec id="s4-19"><title>Quantitative RT-PCR analysis in mammary glands</title><p>Mouse mammary epithelial cells were prepared according to the manufacturer's protocol (StemCell Technologies, Vancouver, Canada). Briefly, following removal of the lymph node, mammary glands dissected from 10-week-old virgin female mice were digested in EpiCult-B with 5% fetal bovine serum (FBS), 300 U/ml collagenase, and 100 U/ml hyaluronidase for 8 hr at 37°C. After vortexing and lysis of the red blood cells in NH<sub>4</sub>Cl, mammary epithelial cells were obtained by sequential dissociation of the fragments by gentle pipetting for 1–2 min in 0.25% trypsin, and 2 min in 5 mg/ml dispase plus 0.1 mg/ml DNase I (DNase; Sigma). Total RNA was isolated from mammary epithelial cells. Complementary DNA was prepared using the MMLV cDNA synthesis kit (Promega). Quantitative RT-PCR was performed using the SYBR-green detection system (Roche). Primers were as follows:</p><p><italic>Msi2</italic> forward primer: ACGACTCCCAGCACGACC; <italic>Msi2</italic> reverse primer: GCCAGCTCAGTCCACCGATA.</p><p><italic>K8</italic> forward primer: ATCAAGAAGGATGTGGACGAA; <italic>K8</italic> Reverse primer: TTGGCAATGTCCTCGTACTG.</p><p><italic>K14</italic> forward primer: CAGCCCCTACTTCAAGACCA; <italic>K14</italic> Reverse primer: AATCTGCAGGAGGACATTGG.</p><p>K18 forward primer: TGCCGCCGATGACTTTAGA; K18 Reverse primer: TTGCTGAGGTCCTGAGATTTG.</p></sec><sec id="s4-20"><title>Quantitative RT-PCR analysis in breast cancer cell lines</title><p>RNA was extracted using Trizol and cDNA was prepared using SuperScript III (Invitrogen). Primers used are listed below (‘h’ prefix denotes human gene, ‘F’ denotes forward primer, ‘R’ denotes reverse primer):</p><p>hEcad-F:</p><p>TGCCCAGAAAATGAAAAAGG</p><p>hEcad-R:</p><p>GTGTATGTGGCAATGCGTTC</p><p>hTwist-F:</p><p>GGAGTCCGCAGTCTTACGAG</p><p>hTwist-R:</p><p>TCTGGAGGACCTGGTAGAGG</p><p>hEpCAM-F:</p><p>CTTTAAGGCCAAGCAGTGCA</p><p>hEpCAM-R:</p><p>CGCGTTGTGATCTCCTTCTG</p><p>hCD24-F:</p><p>GGTTTGACTAGATGATGGATGCC</p><p>hCD24-R:</p><p>TCCATTCCACAATCCCATCCT</p><p>hMsi1-F:</p><p>GGGACTCAGTTGGCAGACTAC</p><p>hMsi1-R:</p><p>CTGGTCCATGAAAGTGACGAA</p><p>hMsi2-F:</p><p>ACCTCACCAGATAGCCTTAGAG</p><p>hMsi2-R:</p><p>AGCGTTTCGTAGTGGGATCTC</p><p>hJag1-F:</p><p>GTCCATGCAGAACGTGAACG</p><p>hJag1-R:</p><p>GCGGGACTGATACTCCTTGA</p></sec></sec></body><back><ack id="ack"><title>Acknowledgements</title><p>We thank V Butty, P Reddien, P Sharp, F Soldner, J Muffat, R Weinberg, L Surface, N Spies, R Friedman, M Kharas and M Lodato for helpful discussions, R Flannery for assistance with mouse colony maintenance, and D. Fu for assistance processing histology sections. We thank Shmulik Motola and Stuart Levine (MIT BioMicroCenter) for high-throughput sequencing, and Wendy Solomon from Keck Microscopy Facility (Whitehead Institute) for assistance with microscopy. Supported by NIH grants R01-GM096193 (EMA), RO1-CA084198 (RJ), U01-CA184897 and R01-GM085319 (CBB). ZY and FL are supported by the National Basic Research program of China (973 program, 2011CB944103), the National Natural Science Foundation of China (NSFC, 31271584), and the National Transgenic Breeding Project of China (2011ZX08009-001-003). EMA is supported by Alfred P Sloan fellowship, and ESS by an NSF Graduate Research Fellowship (Grant No. 1122374).</p></ack><sec sec-type="additional-information"><title>Additional information</title><fn-group content-type="competing-interest"><title>Competing interests</title><fn fn-type="conflict" id="conf1"><p>EMA: Reviewing Editor, <italic>eLife</italic>.</p></fn><fn fn-type="conflict" id="conf2"><p>The other authors declare that no competing interests exist.</p></fn></fn-group><fn-group content-type="author-contribution"><title>Author contributions</title><fn fn-type="con" id="con1"><p>YK, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article</p></fn><fn fn-type="con" id="con2"><p>FL, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article</p></fn><fn fn-type="con" id="con3"><p>NJL, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article</p></fn><fn fn-type="con" id="con4"><p>ESS, Acquisition of data, Drafting or revising the article</p></fn><fn fn-type="con" id="con5"><p>W-LT, Acquisition of data, Drafting or revising the article</p></fn><fn fn-type="con" id="con6"><p>AWC, Analysis and interpretation of data, Drafting or revising the article, Contributed unpublished essential data or reagents</p></fn><fn fn-type="con" id="con7"><p>EMA, Analysis and interpretation of data, Drafting or revising the article, Contributed unpublished essential data or reagents</p></fn><fn fn-type="con" id="con8"><p>CJL, Analysis and interpretation of data, Drafting or revising the article, Contributed unpublished essential data or reagents</p></fn><fn fn-type="con" id="con9"><p>PBG, Analysis and interpretation of data, Drafting or revising the article</p></fn><fn fn-type="con" id="con10"><p>ZY, Analysis and interpretation of data, Drafting or revising the article</p></fn><fn fn-type="con" id="con11"><p>RJ, Analysis and interpretation of data, Drafting or revising the article</p></fn><fn fn-type="con" id="con12"><p>CBB, Analysis and interpretation of data, Drafting or revising the article</p></fn></fn-group><fn-group content-type="ethics-information"><title>Ethics</title><fn fn-type="other"><p>Animal experimentation: Mice of the 129SvJae strain were used, and the K14-rtTA strain were obtained from JAX (stock number: 007678). Animal care was performed in accordance with institutional guidelines and approved by the Committee on Animal Care, Department of Comparative Medicine, Massachusetts Institute of Technology, under animal protocol 1013-088-16.</p></fn></fn-group></sec><sec sec-type="supplementary-material"><title>Additional files</title><supplementary-material id="SD1-data"><object-id pub-id-type="doi">10.7554/eLife.03915.023</object-id><label>Supplementary file 1.</label><caption><p>Breast cancer RNA-Seq datasets used in analysis (apart from TCGA).</p><p><bold>DOI:</bold> <ext-link ext-link-type="doi" xlink:href="10.7554/eLife.03915.023">http://dx.doi.org/10.7554/eLife.03915.023</ext-link></p></caption><media xlink:href="elife03915s001.xls" mimetype="application" mime-subtype="xls"/></supplementary-material><sec sec-type="datasets"><title>Major dataset</title><p>The following dataset was generated:</p><p><related-object content-type="generated-dataset" 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pub-id-type="doi">10.7554/eLife.03915.024</article-id><title-group><article-title>Decision letter</article-title></title-group><contrib-group content-type="section"><contrib contrib-type="editor"><name><surname>Blencowe</surname><given-names>Benjamin J</given-names></name><role>Reviewing editor</role><aff><institution>University of Toronto,</institution> <country>Canada</country></aff></contrib></contrib-group></front-stub><body><boxed-text><p>eLife posts the editorial decision letter and author response on a selection of the published articles (subject to the approval of the authors). An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent (see <ext-link ext-link-type="uri" xlink:href="http://elifesciences.org/review-process">review process</ext-link>). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.</p></boxed-text><p>Thank you for sending your work entitled “Musashi Proteins are Post-transcriptional Regulators of the Epithelial-luminal Cell State” for consideration at <italic>eLife.</italic> Your article has been favorably evaluated by James Manley (Senior editor), a Reviewing editor, and 2 reviewers.</p><p>The Reviewing editor and the two reviewers discussed their comments before we reached this decision, and the Reviewing editor has assembled the following comments to help you prepare a revised submission.</p><p>This manuscript addresses the function of Msi proteins, a class of RNA binding proteins for which little is known. The authors initially analyze tumour and normal tissue RNA-Seq data from the Cancer Genomic Atlas repository, as well as from cancer cell lines, to document changes between Msi expression and specific cancer/normal cell types. Ribosome profiling and RNA-sequencing analyses are then used to identify Msi mRNA targets. The results suggest that Msi functions in establishing epithelial status. An important finding is that Msi proteins inhibit the translation of the Notch ligand Jag, which plays an important role in EMT. An indirect role for Msi proteins in alternative splicing is also suggested. The data supporting the first set of observations and associated conclusions in the manuscript are extensive, well presented, and backed by statistical analyses. The second part of the manuscript documents cellular phenotypes associated with altered expression of Msi. While these data are less quantitative, overall they are consistent with the view that Msi contributes to establishing and maintaining the epithelial state in both cancerous and normal developmental contexts.</p><p>Main points:</p><p>1) <xref ref-type="fig" rid="fig1">Figure 1</xref>. The relationship between Msi expression and cancer is complex, as expression levels for these factors display increases and decreases within the same type of cancer, between different cancers, and there are also substantial differences between Msi1 and Msi2 expression. Given that tumors are typically highly heterogeneous and that epithelial tumor tissues are often contaminated with surrounding normal stromal/mesenchymal cells, do the above variations reflect this heterogeneity? While the subsequent analysis of cell lines partially addresses this issue, the authors should at least discuss that levels of Msi in tumour tissues may be more reflective of epithelial content than cancerous state.</p><p>2) It would be informative to use the Cancer Genomic Atlas data to compare expression levels of additional RBPs that have been linked to post-transcriptional regulatory programs associated with EMT/MET transitions, such as RBFOX2 and MBNLs. In this regard, the authors are referred to relevant work by Venables et al. (Mol Cell Biol. 2013 Jan;33(2):396-405), which should be referenced.</p><p>3) The authors' study would be strengthened by providing a more definitive functional link between one or more targets of Msi1/2 and epithelial state. For example, they could test whether Jag1 knockdown and/or over-expression rescues Msi manipulations in scratch wound (see below), or cell scatter assays in <xref ref-type="fig" rid="fig6">Figure 6A and C</xref>, respectively.</p><p>4) The authors should provide more information on how they define Msi translation targets. How many genes were considered as targets? What fraction of genes have 3' UTRs enriched in UAGs (in the 85% percentile range) that are not regulated by Msi?</p><p>5) The changes in splicing are proposed to be indirect, in large part because the bulk of Msi proteins are cytoplasmic. However, a possible direct role should be acknowledged in the absence of additional data.</p><p>6) It is an overstatement to say that Msi OE inhibits wound healing. Wound healing is a complex process that is tightly regulated and involves multiple layers of tissues acting in a coordinated way. To say that Msis inhibit wound healing may be taken to suggest that the authors have observed Msis actually acting in the process of wound healing rather than in the in vitro phenotypic scratch wound assay. The authors should change their language from “wound healing” to “migration”.</p><p>7) The authors should verify induction of EMT upon knock down of Msis in the cell scatter assays in <xref ref-type="fig" rid="fig6">Figure 6</xref>, and recovery of an epithelial phenotype upon Msi expression in the scratch assays.</p><p>8) Msi OE causes a slight delay in cell migration as it may also do to mammary ductal branching. The defect in mammary ductal branching is actually unclear (is it amplitude, number of branches?). Where possible, quantification should be applied. The authors propose that mammary gland development is a « a type of EMT ». References linking mammary development to EMT should be provided.</p><p>9) Typically, EMT has been linked to metastasis. It would be most relevant to test the impact of Msi OE on the metastatic potential of cancer cells injected into mice.</p></body></sub-article><sub-article article-type="reply" id="SA2"><front-stub><article-id pub-id-type="doi">10.7554/eLife.03915.025</article-id><title-group><article-title>Author response</article-title></title-group></front-stub><body><p>Our primary new results are summarized below. We have:</p><p>1) Showed that knockdown of Msi1/Msi2 in luminal breast cancer cell lines decreases epithelial marker expression, and increases mesenchymal marker expression. We showed this using qRT-PCR for EMT markers, as suggested by reviewers. We additionally overexpressed Msi1 in a mesenchymal breast cancer cell line, which resulted in reduced mesenchymal marker expression and increased epithelial marker expression, supporting our model that Msi activation promotes an epithelial state.</p><p>2) Performed a transwell migration in a mesenchymal cancer cell line and showed that overexpression of Msi1 significantly hinders migration, consistent with Msi activation suppressing EMT.</p><p>3) Further explored regulation of Msi targets, by performing luciferase reporter assays for the Notch-ligand <italic>Jag1.</italic> We showed that knockdown of Msi1/Msi2 in 293T cells increases expression of the <italic>Jag1</italic> 3’ UTR reporter, supporting our model that <italic>Jag1</italic> protein expression is regulated by Msi binding to its 3' UTR. This result not only further strengthens Msi’s role in regulating <italic>Jag1</italic>, but also demonstrates that this regulation is conserved in human cells. Finally, we showed that Msi2 overexpression in the healthy mouse mammary gland results in reduced <italic>Jag1</italic> expression. Together, our results show that Msi proteins regulate <italic>Jag1</italic> in mouse and human, and across distinct cell types (NSCs and mammary epithelial cells).</p><p>4) Extended our computational analyses to other EMT-associated RNA-binding proteins in the TCGA dataset, as suggested by reviewers, and clarified our methods of analysis.</p><p>5) Quantified the ductal branching phenotype in mammary glands of Msi2 overexpressing mice.</p><p><italic>Main points:</italic></p><p><italic>1)</italic> <xref ref-type="fig" rid="fig1"><italic>Figure 1</italic></xref><italic>. The relationship between Msi expression and cancer is complex, as expression levels for these factors display increases and decreases within the same type of cancer, between different cancers, and there are also substantial differences between Msi1 and Msi2 expression. Given that tumors are typically highly heterogeneous and that epithelial tumor tissues are often contaminated with surrounding normal stromal/mesenchymal cells, do the above variations reflect this heterogeneity? While the subsequent analysis of cell lines partially addresses this issue, the authors should at least discuss that levels of Msi in tumour tissues may be more reflective of epithelial content than cancerous state</italic>.</p><p>We agree that tumor heterogeneity is an important issue that should be discussed and we have added text discussing the possibility that increased Musashi levels may reflect the higher content of epithelial cells in certain tumors.</p><p><italic>2) It would be informative to use the Cancer Genomic Atlas data to compare expression levels of additional RBPs that have been linked to post-transcriptional regulatory programs associated with EMT/MET transitions, such as RBFOX2 and MBNLs. In this regard, the authors are referred to relevant work by Venables et al. (Mol Cell Biol. 2013 Jan;33(2):396-405), which should be referenced</italic>.</p><p>We examined the expression of RBFOX2 and MBNL1 in breast cancer tumors from TCGA. Consistent with the findings of Venables et. al. (2013), we observed that both RBFOX2 and MBNL1 are more highly expressed in basal tumors compared with the epithelial-luminal tumor subtypes. These data are shown in <xref ref-type="fig" rid="fig2s2">Figure 2–figure supplement 2</xref>, and we have added a citation of Venables et. al. 2013 to the text.</p><p><italic>3) The authors' study would be strengthened by providing a more definitive functional link between one or more targets of Msi1/2 and epithelial state. For example, they could test whether Jag1 knockdown and/or over-expression rescues Msi manipulations in scratch wound (see below), or cell scatter assays in</italic> <xref ref-type="fig" rid="fig6"><italic>Figure 6A and C</italic></xref><italic>, respectively</italic>.</p><p>We have directly tested the link between Msi and Jag1 using luciferase reporters. We showed that translation of a reporter with the Jag1 3' UTR is enhanced by knockdown of Msi1/Msi2 in 293T cells. These experiments strengthen the link between Msi and Jag1 and also demonstrate that the regulation of Jag1 by Msi is conserved in human cells. The responses to MPs 7 & 8 below provide more information. In addition, we now show that Jag1 protein expression is reduced in mouse mammary glands following overexpression of Msi2.</p><p><italic>4) The authors should provide more information on how they define Msi translation targets. How many genes were considered as targets? What fraction of genes have 3' UTRs enriched in UAGs (in the 85% percentile range) that are not regulated by Msi?</italic></p><p>We have included more information in the manuscript on how translational targets were defined using filters to eliminate genes with low read coverage or large mRNA level changes and requiring a minimum 3-fold change in TE. The majority of genes containing the UAG motif in the 3' UTR are not translationally regulated by Msi in NPCs, since only a small number of genes were differentially translated, while the UAG motif is relatively common in 3' UTR regions. For example, only 39 genes in were differentially expressed in the Msi1 overexpression experiments, out of which only a handful of genes showed very large changes in TE. It is possible that co-factors are required in vivo for Msi to affect translation following binding to the mRNA, or that other RNA-binding factors outcompete Msi protein for binding. The molecular mechanism underlying Musashi-dependent translational control and the nature of any co-factors involved are not known.</p><p><italic>5) The changes in splicing are proposed to be indirect, in large part because the bulk of Msi proteins are cytoplasmic. However, a possible direct role should be acknowledged in the absence of additional data</italic>.</p><p>We agree that we cannot exclude based on current data that Msi proteins directly affect splicing and have added this point to the Discussion.</p><p><italic>6) It is an overstatement to say that Msi OE inhibits wound healing. Wound healing is a complex process that is tightly regulated and involves multiple layers of tissues acting in a coordinated way. To say that Msis inhibit wound healing may be taken to suggest that the authors have observed Msis actually acting in the process of wound healing rather than in the in vitro phenotypic scratch wound assay. The authors should change their language from “wound healing” to “migration”</italic>.</p><p>We agree with the reviewers that “migration” is more precise than “wound healing” given our data. We have changed the text to use “migration” in place of “wound healing”, and used a new assay to specifically test migration (see response to MPs 7 & 8 below).</p><p><italic>7) The authors should verify induction of EMT upon knock down of Msis in the cell scatter assays in</italic> <xref ref-type="fig" rid="fig6"><italic>Figure 6</italic></xref><italic>, and recovery of an epithelial phenotype upon Msi expression in the scratch assays</italic>.</p><p>Response is combined with response to main point 8 below.</p><p><italic>8) Msi OE causes a slight delay in cell migration as it may also do to mammary ductal branching. The defect in mammary ductal branching is actually unclear (is it amplitude, number of branches?). Where possible, quantification should be applied. The authors propose that mammary gland development is a « a type of EMT ». References linking mammary development to EMT should be provided</italic>.</p><p>Response to MPs #7 and #8. We verified induction of EMT upon knockdown of Msis in cancer cell lines, where the EMT transition is most relevant. Our new data (<xref ref-type="fig" rid="fig6">Figure 6</xref>) show that epithelial markers are generally downregulated while mesenchymal markers are upregulated upon knockdown of Msis in an epithelial cancer cell line. To further solidify this connection, we overexpressed Msi1 in a mesenchymal cell line (MDAMB231) where Msi1 levels were initially extremely low. We found that Msi1 overexpression led to a decrease in mesenchymal markers and an increase in epithelial markers, consistent with our model that Msi proteins promote an epithelial state. To address reviewer comments regarding cell migration, we performed a migration transwell assay in breast cancer cell lines. We found that overexpression of Msi1 in the mesenchymal cell line LM2 (a derivative of MDAMB231) strongly impaired migration in the transwell assay (<xref ref-type="fig" rid="fig6">Figure 6D</xref>). These migration assays are more quantitative and controlled than the scratch assay we performed previously, and we feel that the use of breast cancer cell lines for migration analysis is particularly relevant, given the roles for EMT in breast cancer.</p><p>We added quantitation and additional explanation of the mammary ductal branching phenotype that occurs upon Msi2 overexpression (<xref ref-type="fig" rid="fig7s1">Figure 7–figure supplement 1</xref>). The results show that Msi2 overexpression reduces the number of ductal branch points by approximately twofold at both 4 weeks and 7 weeks following induction of Msi2 (both P < 0.01 by t-test), and that Msi2 overexpression also delays ductal branch growth (P < 0.01 at 4 weeks, but indistinguishable from control at 7 weeks).</p><p><italic>9) Typically, EMT has been linked to metastasis. It would be most relevant to test the impact of Msi OE on the metastatic potential of cancer cells injected into mice</italic>.</p><p>We agree that it would be worthwhile to investigate the impact of Musashi proteins on metastasis in vivo, but we feel that this is beyond the scope of our manuscript. While we have linked Musashi proteins to regulation of the epithelial state and EMT in cancer (through functional analysis of cancer cell lines and computational analysis of TCGA data), and in normal development (through in vivo analyses of healthy mammary gland development), we do not directly address metastasis in this work. We have been careful not to imply in the text that our work bears directly on metastasis, or that the role of Musashi proteins in cancer occurs through their effect on metastatic processes. We believe that our results on the regulation of the epithelial state (and of EMT in a healthy mammary gland context) have consequences that are significant independent of possible effects on metastasis, and may not directly bear on metastasis. In some cancers like glioblastoma, where Msis are highly expressed, metastases are rare. In breast cancer, highly proliferative epithelial tumors (like Luminal B type tumors) can be aggressive and harmful to patients without possessing the mesenchymal properties that lead to metastases. Therefore, we feel that potential links to metastasis are very worthwhile to explore, but are not essential to the conclusions of this paper.</p></body></sub-article></article> |