<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD with MathML3 v1.2 20190208//EN"  "JATS-archivearticle1-mathml3.dtd"><article xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2"><front><journal-meta><journal-id journal-id-type="nlm-ta">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" pub-type="epub">2050-084X</issn><publisher><publisher-name>eLife Sciences Publications, Ltd</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">83806</article-id><article-id pub-id-type="doi">10.7554/eLife.83806</article-id><article-categories><subj-group subj-group-type="display-channel"><subject>Research Article</subject></subj-group><subj-group subj-group-type="heading"><subject>Neuroscience</subject></subj-group></article-categories><title-group><article-title>MeCP2 regulates <italic>Gdf11</italic>, a dosage-sensitive gene critical for neurological function</article-title></title-group><contrib-group><contrib contrib-type="author" id="author-294782"><name><surname>Bajikar</surname><given-names>Sameer S</given-names></name><contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0002-8868-881X</contrib-id><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="other" rid="fund1"/><xref ref-type="fn" rid="con1"/><xref ref-type="fn" rid="conf1"/></contrib><contrib contrib-type="author" id="author-294783"><name><surname>Anderson</surname><given-names>Ashley G</given-names></name><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="other" rid="fund2"/><xref ref-type="fn" rid="con2"/><xref ref-type="fn" rid="conf1"/></contrib><contrib contrib-type="author" id="author-294781"><name><surname>Zhou</surname><given-names>Jian</given-names></name><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="other" rid="fund4"/><xref ref-type="fn" rid="con3"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author" id="author-163373"><name><surname>Durham</surname><given-names>Mark A</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff3">3</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-163375"><name><surname>Trostle</surname><given-names>Alexander J</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff5">5</xref><xref ref-type="fn" rid="con5"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author" id="author-303745"><name><surname>Wan</surname><given-names>Ying-Wooi</given-names></name><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="fn" rid="con6"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author" id="author-1884"><name><surname>Liu</surname><given-names>Zhandong</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff5">5</xref><xref ref-type="fn" rid="con7"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author" corresp="yes" id="author-1029"><name><surname>Zoghbi</surname><given-names>Huda Y</given-names></name><contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0002-0700-3349</contrib-id><email>hzoghbi@bcm.edu</email><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff3">3</xref><xref ref-type="aff" rid="aff5">5</xref><xref ref-type="aff" rid="aff6">6</xref><xref ref-type="other" rid="fund3"/><xref ref-type="other" rid="fund5"/><xref ref-type="other" rid="fund6"/><xref ref-type="fn" rid="con8"/><xref ref-type="fn" rid="conf1"/></contrib><aff id="aff1"><label>1</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/02pttbw34</institution-id><institution>Department of Molecular and Human Genetics, Baylor College of Medicine</institution></institution-wrap><addr-line><named-content content-type="city">Houston</named-content></addr-line><country>United States</country></aff><aff id="aff2"><label>2</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/05cz92x43</institution-id><institution>Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital</institution></institution-wrap><addr-line><named-content content-type="city">Houston</named-content></addr-line><country>United States</country></aff><aff id="aff3"><label>3</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/02pttbw34</institution-id><institution>Program in Developmental Biology, Baylor College of Medicine</institution></institution-wrap><addr-line><named-content content-type="city">Houston</named-content></addr-line><country>United States</country></aff><aff id="aff4"><label>4</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/02pttbw34</institution-id><institution>Medical Scientist Training Program, Baylor College of Medicine</institution></institution-wrap><addr-line><named-content content-type="city">Houston</named-content></addr-line><country>United States</country></aff><aff id="aff5"><label>5</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/02pttbw34</institution-id><institution>Department of Pediatrics, Baylor College of Medicine</institution></institution-wrap><addr-line><named-content content-type="city">Houston</named-content></addr-line><country>United States</country></aff><aff id="aff6"><label>6</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/02pttbw34</institution-id><institution>Howard Hughes Medical Institute, Baylor College of Medicine</institution></institution-wrap><addr-line><named-content content-type="city">Houston</named-content></addr-line><country>United States</country></aff></contrib-group><contrib-group content-type="section"><contrib contrib-type="editor"><name><surname>Gleeson</surname><given-names>Joseph G</given-names></name><role>Reviewing Editor</role><aff><institution-wrap><institution-id institution-id-type="ror">https://ror.org/0168r3w48</institution-id><institution>University of California, San Diego</institution></institution-wrap><country>United States</country></aff></contrib><contrib contrib-type="senior_editor"><name><surname>VijayRaghavan</surname><given-names>K</given-names></name><role>Senior Editor</role><aff><institution-wrap><institution-id institution-id-type="ror">https://ror.org/03gf8rp76</institution-id><institution>National Centre for Biological Sciences, Tata Institute of Fundamental Research</institution></institution-wrap><country>India</country></aff></contrib></contrib-group><pub-date publication-format="electronic" date-type="publication"><day>27</day><month>02</month><year>2023</year></pub-date><pub-date pub-type="collection"><year>2023</year></pub-date><volume>12</volume><elocation-id>e83806</elocation-id><history><date date-type="received" iso-8601-date="2022-09-29"><day>29</day><month>09</month><year>2022</year></date><date date-type="accepted" iso-8601-date="2023-02-09"><day>09</day><month>02</month><year>2023</year></date></history><pub-history><event><event-desc>This manuscript was published as a preprint at bioRxiv.</event-desc><date date-type="preprint" iso-8601-date="2022-10-06"><day>06</day><month>10</month><year>2022</year></date><self-uri content-type="preprint" xlink:href="https://doi.org/10.1101/2022.10.05.510925"/></event></pub-history><permissions><copyright-statement>© 2023, Bajikar et al</copyright-statement><copyright-year>2023</copyright-year><copyright-holder>Bajikar et al</copyright-holder><ali:free_to_read/><license xlink:href="http://creativecommons.org/licenses/by/4.0/"><ali:license_ref>http://creativecommons.org/licenses/by/4.0/</ali:license_ref><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="elife-83806-v1.pdf"/><self-uri content-type="figures-pdf" xlink:href="elife-83806-figures-v1.pdf"/><abstract><p>Loss- and gain-of-function of MeCP2 causes Rett syndrome (RTT) and <italic>MECP2</italic> duplication syndrome (MDS), respectively. MeCP2 binds methyl-cytosines to finely tune gene expression in the brain, but identifying genes robustly regulated by MeCP2 has been difficult. By integrating multiple transcriptomics datasets, we revealed that MeCP2 finely regulates growth differentiation factor 11 (<italic>Gdf11</italic>). <italic>Gdf11</italic> is down-regulated in RTT mouse models and, conversely, up-regulated in MDS mouse models. Strikingly, genetically normalizing <italic>Gdf11</italic> dosage levels improved several behavioral deficits in a mouse model of MDS. Next, we discovered that losing one copy of <italic>Gdf11</italic> alone was sufficient to cause multiple neurobehavioral deficits in mice, most notably hyperactivity and decreased learning and memory. This decrease in learning and memory was not due to changes in proliferation or numbers of progenitor cells in the hippocampus. Lastly, loss of one copy of <italic>Gdf11</italic> decreased survival in mice, corroborating its putative role in aging. Our data demonstrate that <italic>Gdf11</italic> dosage is important for brain function.</p></abstract><kwd-group kwd-group-type="author-keywords"><kwd>growth differentiation factor 11</kwd><kwd>Methyl CpG Binding Protein 2</kwd><kwd>MECP2 duplication syndrome</kwd><kwd>GDF11</kwd><kwd>MeCP2</kwd></kwd-group><kwd-group kwd-group-type="research-organism"><title>Research organism</title><kwd>Mouse</kwd></kwd-group><funding-group><award-group id="fund1"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100009633</institution-id><institution>Eunice Kennedy Shriver National Institute of Child Health and Human Development</institution></institution-wrap></funding-source><award-id>F32HD100048</award-id><principal-award-recipient><name><surname>Bajikar</surname><given-names>Sameer S</given-names></name></principal-award-recipient></award-group><award-group id="fund2"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000065</institution-id><institution>National Institute of Neurological Disorders and Stroke</institution></institution-wrap></funding-source><award-id>F32NS122920</award-id><principal-award-recipient><name><surname>Anderson</surname><given-names>Ashley G</given-names></name></principal-award-recipient></award-group><award-group id="fund3"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000011</institution-id><institution>Howard Hughes Medical Institute</institution></institution-wrap></funding-source><principal-award-recipient><name><surname>Zoghbi</surname><given-names>Huda Y</given-names></name></principal-award-recipient></award-group><award-group id="fund4"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100007137</institution-id><institution>Texas Children's Hospital</institution></institution-wrap></funding-source><award-id>Zoghbi Scholar</award-id><principal-award-recipient><name><surname>Bajikar</surname><given-names>Sameer S</given-names></name><name><surname>Zhou</surname><given-names>Jian</given-names></name></principal-award-recipient></award-group><award-group id="fund5"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000065</institution-id><institution>National Institute of Neurological Disorders &amp; Stroke</institution></institution-wrap></funding-source><award-id>R01NS057819</award-id><principal-award-recipient><name><surname>Zoghbi</surname><given-names>Huda Y</given-names></name></principal-award-recipient></award-group><award-group id="fund6"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100009633</institution-id><institution>Eunice Kennedy Shriver National Institute of Child Health &amp; Human Development</institution></institution-wrap></funding-source><award-id>U54HD083092</award-id><principal-award-recipient><name><surname>Zoghbi</surname><given-names>Huda Y</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 specific-use="meta-only"><meta-name>Author impact statement</meta-name><meta-value>Integrated analysis of transcriptional profiles from mice carrying distinct <italic>Mecp2</italic> mutant alleles revealed that MeCP2 regulates <italic>Gdf11</italic> expression in the brain, and that <italic>Gdf11</italic> is a dosage-sensitive gene whose levels impact neuronal function and animal behavior.</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec id="s1" sec-type="intro"><title>Introduction</title><p>Intellectual disability (ID) and autism spectrum disorder (ASD) affect nearly 3% of children in the United States (<xref ref-type="bibr" rid="bib71">Zablotsky et al., 2019</xref>). These diseases can be caused by mutations in any one of hundreds of genes (<xref ref-type="bibr" rid="bib15">Deciphering Developmental Disorders Study, 2017</xref>; <xref ref-type="bibr" rid="bib56">Satterstrom et al., 2020</xref>), a subset of which is ‘dosage-sensitive’, causing neurological dysfunction by either loss-of-function mutations or an increase in expression due to copy-number gain (<xref ref-type="bibr" rid="bib51">Rice and McLysaght, 2017</xref>). Understanding how a dosage-sensitive gene drives molecular pathogenesis can reveal the mechanisms for two diseases, the loss-of-function and increased dosage disorders (<xref ref-type="bibr" rid="bib20">Javed et al., 2020</xref>).</p><p>Methyl-CpG binding protein 2 (<italic>MECP2</italic>) is the exemplary dosage-sensitive gene. <italic>MECP2</italic> is an X-linked gene whose loss-of-function causes Rett syndrome (RTT; OMIM: 312750) (<xref ref-type="bibr" rid="bib1">Amir et al., 1999</xref>) and whose duplication causes <italic>MECP2</italic> duplication syndrome (MDS; OMIM: 300260) (<xref ref-type="bibr" rid="bib34">Lugtenberg et al., 2009</xref>; <xref ref-type="bibr" rid="bib67">van Esch et al., 2005</xref>). Both RTT and MDS are devastating neurological disorders characterized by intellectual disability, motor dysfunction, and seizures. Despite identification of <italic>MECP2</italic> as the causative gene for both disorders, we still have poor understanding of MeCP2-driven pathogenesis. MeCP2 is a methyl-cytosine binding protein that regulates gene expression in the brain (<xref ref-type="bibr" rid="bib8">Chen et al., 2015</xref>; <xref ref-type="bibr" rid="bib16">Gabel et al., 2015</xref>; <xref ref-type="bibr" rid="bib42">Nan et al., 1997</xref>). Disruption of normal MeCP2 function causes subtle dysregulation of thousands of genes (<xref ref-type="bibr" rid="bib55">Sanfeliu et al., 2019</xref>). Importantly, many of these dysregulated genes are shared between mouse models of RTT and MDS, but their expression is altered in opposite directions (<xref ref-type="bibr" rid="bib7">Chahrour et al., 2008</xref>; <xref ref-type="bibr" rid="bib8">Chen et al., 2015</xref>). Interrogating transcripts that are highly sensitive to MeCP2 levels can reveal disease-driving genes that could be used to develop targeted therapies for RTT and MDS (<xref ref-type="bibr" rid="bib54">Samaco et al., 2012</xref>). Lastly, pinpointing the genes regulated by MeCP2 can enhance our understanding of molecular mechanisms of additional genes mediating neurological phenotypes (<xref ref-type="bibr" rid="bib27">Lavery et al., 2020</xref>; <xref ref-type="bibr" rid="bib75">Zhou et al., 2022</xref>).</p><p>To search for genes robustly regulated by MeCP2, we integrated gene expression studies that profiled RNA collected from mouse tissues bearing various <italic>MECP2</italic> loss- or gain-of-function alleles and discovered that growth differentiation factor 11 (<italic>Gdf11</italic>) expression is highly and positively correlated with MeCP2 protein level and function. <italic>Gdf11</italic> is a secreted ligand of the TGFβ superfamily most closely related to myostatin/GDF8 (<xref ref-type="bibr" rid="bib40">Morikawa et al., 2016</xref>). <italic>Gdf11</italic> was first identified as a regulator of the anterior/posterior patterning of the skeleton (<xref ref-type="bibr" rid="bib37">McPherron et al., 1999</xref>). Further studies have revealed that <italic>Gdf11</italic> negatively regulates neurogenesis both during development and in the adult brain (<xref ref-type="bibr" rid="bib36">Mayweather et al., 2021</xref>; <xref ref-type="bibr" rid="bib69">Wu et al., 2003</xref>). <italic>Gdf11</italic> has also been implicated as a ‘rejuvenating’ factor that mitigates the effects of aging and as a tumor suppressor in multiple organs (<xref ref-type="bibr" rid="bib2">Bajikar et al., 2017</xref>; <xref ref-type="bibr" rid="bib24">Katsimpardi et al., 2014</xref>; <xref ref-type="bibr" rid="bib32">Liu et al., 2018</xref>; <xref ref-type="bibr" rid="bib33">Loffredo et al., 2013</xref>; <xref ref-type="bibr" rid="bib61">Sinha et al., 2014</xref>). Recently, mutations in <italic>GDF11</italic> have been associated with a developmental disorder with craniofacial, vertebral, and neurological abnormalities, but the consequences of altered <italic>Gdf11</italic> dosage on mouse behavior had not been previously assessed (<xref ref-type="bibr" rid="bib14">Cox et al., 2019</xref>; <xref ref-type="bibr" rid="bib49">Ravenscroft et al., 2021</xref>).</p><p>In this study, we found that <italic>Gdf11</italic> expression is increased in mouse models of MDS and that genetically normalizing <italic>Gdf11</italic> dosage was sufficient to improve several behavioral deficits in a mouse model of MDS. Lastly, we found that loss of one copy of <italic>Gdf11</italic> alone is sufficient to cause broad neurological dysfunction. Our study highlights the importance of revealing key molecules downstream of dosage-sensitive genes by demonstrating that <italic>Gdf11</italic> is regulated by MeCP2 and that <italic>Gdf11</italic> dosage modifies neurological phenotypes.</p></sec><sec id="s2" sec-type="results"><title>Results</title><sec id="s2-1"><title>MeCP2 regulates the expression of <italic>Gdf11</italic> in the mammalian brain</title><p>Normalizing MeCP2 levels through genetic or pharmacological means is sufficient to rescue nearly all behavioral and molecular deficits in a mouse model of MDS (<xref ref-type="bibr" rid="bib66">Sztainberg et al., 2015</xref>). For example, bolus injection of an antisense oligonucleotide (ASO) targeting <italic>MECP2</italic> acutely reduces MeCP2 protein in MDS mice and ameliorates behavioral deficits (<xref ref-type="bibr" rid="bib60">Shao et al., 2021b</xref>). We reasoned that genes whose expression was corrected after ASO treatment and whose abundance highly correlated with MeCP2 protein levels would be candidate genes to contribute to the behavioral rescue. To this end, we calculated the correlation coefficient between the fold-change of the 100 genes rescued by ASO treatment and the fold-change of MeCP2 protein levels in the hippocampi of <italic>MECP2</italic> duplication mice (<xref ref-type="bibr" rid="bib60">Shao et al., 2021b</xref>; <xref ref-type="fig" rid="fig1">Figure 1A</xref>). We found 16 genes whose fold-changes were highly correlated (Spearman’s rho &gt;±0.75) with MeCP2 levels (<xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1A</xref>). To further refine these candidates, we flagged genes that were predicted to be loss-of-function intolerant in humans as these genes could have biological consequences if their expression level is mildly altered (<xref ref-type="bibr" rid="bib23">Karczewski et al., 2020</xref>; <xref ref-type="bibr" rid="bib30">Lek et al., 2016</xref>). Of the 16 MeCP2-correlated genes, we identified four genes – growth differentiation factor 11 (<italic>Gdf11</italic>), family with sequence similarity 131 member B (<italic>Fam131b</italic>), versican (<italic>Vcan</italic>), and forkhead box protein P1 (<italic>Foxp1</italic>) with a probability of loss intolerance (pLI) greater than 0.9 (<xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1A</xref>).</p><fig-group><fig id="fig1" position="float"><label>Figure 1.</label><caption><title><italic>Gdf11</italic> is positively regulated by MeCP2.</title><p>(<bold>A</bold>) Dynamic expression levels of <italic>MECP2</italic>, MeCP2, and <italic>Gdf11</italic> during anti-<italic>MECP2</italic> antisense oligonucleotide (ASO) treatment in <italic>MECP2</italic> duplication mice (data from <xref ref-type="bibr" rid="bib60">Shao et al., 2021b</xref>). Spearman correlation coefficient between <italic>Gdf11</italic> and MeCP2 is shown in the right panel. Gray interval represents a loess fit ± standard error. (<bold>B</bold>) Log<sub>2</sub> fold-change of <italic>GDF11</italic> expression in excitatory and inhibitory neurons isolated from post mortem brains from individuals with Rett syndrome and <italic>Gdf11</italic> expression in <italic>Mecp2</italic>-knockout (<italic>Mecp2</italic>-KO), mutant (<italic>Mecp2</italic> MT), and <italic>MECP2</italic> overexpression (<italic>MECP2</italic> OE) mouse model RNA-seq experiments. Abbreviations used to describe studies are as follows: CTX: cortex, CB: cerebellum, HYP: hypothalamus, DG: dentate gyrus, HIP: hippocampus, Dup.: duplication, Trip.: triplication, AAV: adeno-associated virus. Grayed color indicates <italic>p<sub>adjusted</sub></italic> &gt;0.1. Studies are ordered from 1 to 20 and correspond to the study number in <xref ref-type="supplementary-material" rid="supp1">Supplementary file 1</xref>. (<bold>C</bold>) A <italic>Gdf11</italic>-knockout first allele (<italic>Gdf11<sup>tm2b</sup></italic>) has a <italic>LacZ</italic> cassette with splice acceptor and polyA sequence knocked in between exons 1 and 3 of <italic>Gdf11</italic>, and exon 2 of <italic>Gdf11</italic> is deleted. Quantitative PCR of <italic>Mecp2</italic>, <italic>Gdf11</italic>, and the <italic>LacZ</italic> reporter from the cerebellum of wild-type, <italic>Gdf11<sup>tm2b/+</sup></italic>, <italic>Mecp2</italic><sup>-/y</sup>, <italic>Gdf11<sup>tm2b/+</sup>; Mecp2<sup>-/y</sup>, MECP2-</italic>TG1, and <italic>Gdf11<sup>tm2b/+</sup>; MECP2-</italic>TG1 (n=3–4 biological replicates per genotype). n.d. denotes the given gene expression measurement was not detected. qPCR data is shown as mean ± sem. (<bold>D</bold>) CUT&amp;RUN profiling of MeCP2 binding in <italic>MECP2</italic> transgenic mice (<italic>MECP2</italic>-TG1), wild-type, and <italic>Mecp2</italic>-knockout hippocampi (<italic>Mecp2-</italic>KO) at the <italic>Gdf11</italic> locus. Black bar represents a MeCP2 peak called by MACS2 software, and the gray bar represents an expanded region of ±3.5 kb of increased MeCP2 binding. Log<sub>2</sub> fold-change of MeCP2 occupancy within the gray region is shown relative to wild-type, and the <italic>p</italic>-value of the comparison is shown beneath the fold-change. Tracks are displayed as an aggregate of biological replicates (n=3–6 biological replicates per genotype). (<bold>E</bold>) CUT&amp;RUN profiling of H3K27me3 in wild-type and <italic>Mecp2</italic>-knockout (<italic>Mecp2</italic>-KO) at the <italic>Gdf11</italic> locus. Log<sub>2</sub> fold-change of binding within the gray region is shown relative to wild-type, and the <italic>p</italic>-value of the comparison is shown beneath the fold-change. Tracks are displayed as an aggregate of biological replicates (n=3 biological replicates per genotype). (*) <italic>p</italic>&lt;0.05, (****) <italic>p&lt;</italic>0.0001 from one way ANOVA followed by multiple comparisons testing.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-83806-fig1-v1.tif"/></fig><fig id="fig1s1" position="float" specific-use="child-fig"><label>Figure 1—figure supplement 1.</label><caption><title>Gene expression changes correlated with MeCP2 protein levels.</title><p>(<bold>A</bold>) Spearman correlation of genes misregulated in <italic>MECP2</italic> duplication mice quantifying how they track with MeCP2 levels during anti-<italic>MECP2</italic> antisense oligonucleotide treatment (<xref ref-type="bibr" rid="bib60">Shao et al., 2021b</xref>). Data points are colored by log<sub>2</sub> fold-change between <italic>MECP2</italic> duplication and wild-type mice. The size of the dot represents the probability of loss intolerance (pLI) of the human gene if an exact match exists from the gnomad database. Genes with correlation above a threshold of 0.75 (horizontal line) are labeled by name. Genes with pLI &gt;0.9 are bolded. (<bold>B–C</bold>) <italic>Fam131b</italic>, <italic>Vcan</italic>, and <italic>Foxp1</italic> are MeCP2-correlated genes predicted to be intolerant to loss-of-function but are not consistently misregulated in excitatory and inhibitory neurons isolated from post mortem brains from individuals with Rett syndrome and expression in <italic>Mecp2</italic>-knockout (<italic>Mecp2</italic>-KO), mutant (<italic>Mecp2</italic> MT), and <italic>MECP2</italic> overexpression (<italic>MECP2</italic> OE) mouse model RNA-seq experiments (see <xref ref-type="fig" rid="fig1">Figure 1B</xref>). Abbreviations used to describe studies are as follows: CTX: cortex, CB: cerebellum, HYP: hypothalamus, DG: dentate gyrus, HIP: hippocampus, Dup.: duplication, Trip.: triplication, AAV: adeno-associated virus. Dots denote log<sub>2</sub> fold-change between MeCP2 perturbed tissue and wild type, and gray color indicates <italic>p<sub>adj</sub></italic> &gt;0.1. Studies are ordered from 1 to 20 and correspond to the study number in <xref ref-type="supplementary-material" rid="supp1">Supplementary file 1</xref>. (<bold>E–F</bold>) Cell-type specific correlation of <italic>Gdf11</italic> and <italic>Mecp2</italic>. Single-cell expression of <italic>Gdf11</italic> and <italic>Mecp2</italic> was extracted from the DropViz database and split into the annotated cell types. (<bold>E</bold>) The total Spearman’s correlation across all cell types is shown in the upper left and the Spearman’s correlation for each cell type is denoted next to the legend label for each cell type. Correlations were not calculated for cell-types with fewer than 20 observations. (<bold>F</bold>) The neuron subtype was split into excitatory and inhibitory neurons using <italic>Slc17a7</italic> expression (see Materials and methods). Spearman’s correlation for each neuronal type is denoted next to the legend label for each neuron type.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-83806-fig1-figsupp1-v1.tif"/></fig><fig id="fig1s2" position="float" specific-use="child-fig"><label>Figure 1—figure supplement 2.</label><caption><title>Epigenetic changes correlated with MeCP2 protein levels.</title><p>(<bold>A–C</bold>) Global assessment of MeCP2 and H3K27me3 binding in <italic>Mecp2</italic>-knockout, wild-type, and <italic>MECP2-</italic>TG1 hippocampi assessed by principal component analysis (PCA). (<bold>A</bold>) PCA of MeCP2 (square), H3K27me3 (triangle), and IgG (circle) CUT&amp;RUN profiles in <italic>Mecp2-</italic>knockout (blue), wild-type (black), and <italic>MECP2</italic>-TG1 (red) hippocampi. (<bold>B</bold>) PCA of MeCP2 binding profiles only colored by genotype. (<bold>C</bold>) PCA of H3K27me3 binding profiles only colored by genotype. (<bold>D</bold>) Histone modifications, as measured by ChIP-seq, denoting open chromatin (H3K27ac), the transcriptional start site (H3K4me3), and putative enhancers (H3K4me1) from the hippocampus are shown alongside the MeCP2 binding profile around the <italic>Gdf11</italic> locus. (<bold>E</bold>) CUT&amp;RUN profiling of H3K27me3 in wild-type and <italic>MECP2</italic>-TG1 at the <italic>Gdf11</italic> locus. Black bar represents a MeCP2 peak called by MACS2 software, and the gray bar represents an expanded region of ±3.5 kb. Log<sub>2</sub> fold-change of binding within the gray region is shown relative to wild-type, and the <italic>p</italic>-value of the comparison is shown beneath the fold-change (n=3 biological replicates per genotype).</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-83806-fig1-figsupp2-v1.tif"/></fig></fig-group><p>Gene expression changes in <italic>Mecp2</italic> mutant mouse models have been inconsistent in published reports (<xref ref-type="bibr" rid="bib55">Sanfeliu et al., 2019</xref>). To test if any of the four MeCP2-correlated, loss-intolerant transcripts were robustly sensitive to MeCP2 levels, we queried expression changes in 20 readily available transcriptional profiles generated in <italic>MECP2</italic> perturbed rat (<xref ref-type="bibr" rid="bib68">Veeraragavan et al., 2016</xref>), mouse, and human brain samples (<xref ref-type="supplementary-material" rid="supp1">Supplementary file 1</xref>). Strikingly, we found that <italic>Gdf11</italic> was significantly altered in 19 of the 20 profiles, whereas the other three genes did not consistently exhibit significant difference compared to control (<xref ref-type="fig" rid="fig1">Figure 1B</xref> and <xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1B–D</xref>). <italic>GDF11</italic> levels were downregulated two-fold in human postmortem RTT excitatory neurons, while <italic>Gdf11</italic> levels were downregulated in the transcriptomes of <italic>Mecp2</italic>-null male mice, <italic>Mecp2</italic>-null heterozygous female mice (<xref ref-type="bibr" rid="bib46">Pohodich et al., 2018</xref>), and a panel of <italic>MECP2</italic> point mutant male mice in multiple brain regions (<xref ref-type="bibr" rid="bib21">Jiang et al., 2021</xref>; <xref ref-type="bibr" rid="bib6">Boxer et al., 2020</xref>; <xref ref-type="bibr" rid="bib3">Baker et al., 2013</xref>); these data suggest <italic>Gdf11</italic> is robustly sensitive to MeCP2 function. Additionally, we also found that <italic>Gdf11</italic> was significantly upregulated in mouse models overexpressing <italic>MECP2</italic> (<xref ref-type="fig" rid="fig1">Figure 1B</xref>). We then investigated whether <italic>Gdf11</italic> and <italic>Mecp2</italic> expression were correlated among individual cell types in the brain. We mined a previous single-nucleus RNA-sequencing experiment in the normal mouse brain and found that the overall Spearman’s correlation between <italic>Gdf11</italic> and <italic>Mecp2</italic> across all cell types was 0.65 (<xref ref-type="bibr" rid="bib57">Saunders et al., 2018</xref>). Further, <italic>Gdf11</italic> and <italic>Mecp2</italic> were highly correlated in neuronal and glial cell types (astrocytes, microglia, neurons, and oligodendrocytes; Spearman’s rho = 0.6–0.92) (<xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1E</xref>). Within neurons specifically, we found that <italic>Gdf11</italic> and <italic>Mecp2</italic> were highly correlated in both excitatory neurons (Spearman’s rho = 0.65) and inhibitory neurons (Spearman’s rho = 0.76) (<xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1F</xref>). Given the strong dynamic correlation of <italic>Gdf11</italic> with MeCP2 levels upon ASO treatment and with <italic>Mecp2</italic> expression in individual brain cell types (<xref ref-type="fig" rid="fig1">Figure 1A</xref> and <xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1E and F</xref>), these data suggest <italic>Gdf11</italic> is also sensitive to MeCP2 levels. Taken together, these results demonstrate <italic>Gdf11</italic> is a transcript that is robustly sensitive to both MeCP2 function and protein levels.</p><p>To further investigate if MeCP2 transcriptionally regulates the <italic>Gdf11</italic> locus, we took advantage of a <italic>Gdf11</italic>-knockout allele that has a <italic>LacZ</italic> reporter cassette knocked into the gene (<italic>Gdf11<sup>tm2b</sup></italic>; <xref ref-type="fig" rid="fig1">Figure 1C</xref>). We crossed this allele with both a <italic>Mecp2</italic>-knockout (<xref ref-type="bibr" rid="bib17">Guy et al., 2001</xref>) and a <italic>MECP2</italic> duplication (<italic>MECP2</italic>-TG1) (<xref ref-type="bibr" rid="bib11">Collins et al., 2004</xref>) mouse model to generate a series of <italic>Mecp2</italic> or <italic>Gdf11</italic> single-mutants and <italic>Mecp2; Gdf11</italic> double-mutants and performed qPCR for <italic>Mecp2</italic>, <italic>Gdf11</italic>, and <italic>LacZ</italic> in the cerebellum, a brain region where <italic>Gdf11</italic> is highly expressed in the mouse (<xref ref-type="bibr" rid="bib29">Lein et al., 2007</xref>; <xref ref-type="bibr" rid="bib57">Saunders et al., 2018</xref>). The expression of <italic>Mecp2</italic> was not changed by reduction of <italic>Gdf11</italic>, but <italic>Gdf11</italic> was significantly decreased in <italic>Mecp2</italic>-knockout males (<italic>p</italic>&lt;0.05) and increased in <italic>MECP2</italic>-TG1 animals (<italic>p</italic>&lt;0.0001). Furthermore, <italic>Mecp2</italic>-knockout trended towards a further decrease of <italic>Gdf11</italic> in the <italic>Mecp2<sup>-/y</sup>; Gdf11<sup>tm2b/+</sup></italic> double mutants while <italic>Gdf11</italic> was restored to wild-type expression in the <italic>MECP2</italic>-TG1; <italic>Gdf11<sup>tm2b/+</sup></italic> double mutants. Last, expression of the <italic>LacZ</italic> reporter was modulated by MeCP2 levels as well, being significantly downregulated in <italic>Mecp2</italic>-knockout (<italic>p</italic>&lt;0.05) and upregulated in <italic>MECP2</italic>-TG1 animals (<italic>p</italic>&lt;0.05) (<xref ref-type="fig" rid="fig1">Figure 1C</xref>). These results demonstrate that the <italic>Gdf11</italic> locus is transcriptionally sensitive to MeCP2 protein levels.</p><p>While MeCP2 has a well-described role as a transcriptional repressor and its loss leads to a de-repression of gene expression, MeCP2 loss has been shown to cause a down-regulation of gene expression (<xref ref-type="bibr" rid="bib4">Ben-Shachar et al., 2009</xref>; <xref ref-type="bibr" rid="bib6">Boxer et al., 2020</xref>; <xref ref-type="bibr" rid="bib7">Chahrour et al., 2008</xref>; <xref ref-type="bibr" rid="bib8">Chen et al., 2015</xref>; <xref ref-type="bibr" rid="bib9">Clemens et al., 2020</xref>; <xref ref-type="bibr" rid="bib35">Lyst et al., 2013</xref>; <xref ref-type="bibr" rid="bib43">Nan et al., 1998</xref>; <xref ref-type="bibr" rid="bib42">Nan et al., 1997</xref>; <xref ref-type="bibr" rid="bib54">Samaco et al., 2012</xref>). We next sought to mechanistically understand how loss of MeCP2 leads to down-regulation of <italic>Gdf11</italic>. We first investigated whether MeCP2 has enriched binding near the <italic>Gdf11</italic> locus. We performed <underline>C</underline>leavage <underline>U</underline>nder <underline>T</underline>argets &amp; <underline>R</underline>elease <underline>U</underline>sing <underline>N</underline>uclease (CUT&amp;RUN) (<xref ref-type="bibr" rid="bib65">Skene and Henikoff, 2017</xref>) to profile MeCP2 binding in wild-type, <italic>Mecp2</italic>-knockout, and <italic>MECP2-</italic>TG1 mouse hippocampus (<xref ref-type="fig" rid="fig1s2">Figure 1—figure supplement 2A and B</xref>). We next identified peaks of enriched binding using the MACS algorithm (<xref ref-type="bibr" rid="bib72">Zhang et al., 2008</xref>), which identified a peak upstream of the <italic>Gdf11</italic> transcriptional start site (TSS). To further define the characteristics of this region, we mined existing histone acetylation data for marks of open chromatin (H3K27ac), promoter (H3K4me3), and putative enhancers (H3K4me1) (<xref ref-type="bibr" rid="bib18">Halder et al., 2016</xref>). The peak of MeCP2 signal coincided with a region of high H3K27ac and H3K4me1, but low H3K4me3, suggesting that MeCP2 binds a putative enhancer of <italic>Gdf11</italic> (<xref ref-type="fig" rid="fig1s2">Figure 1—figure supplement 2D</xref>). Due to the broad binding pattern of MeCP2 (<xref ref-type="bibr" rid="bib8">Chen et al., 2015</xref>; <xref ref-type="bibr" rid="bib64">Skene et al., 2010</xref>), we integrated the signal in a symmetric window straddling the peak to robustly quantify MeCP2 occupancy. We observed a significant (<italic>p</italic>&lt;0.01) increase of MeCP2 binding within this region upstream of <italic>Gdf11</italic> in the <italic>MECP2</italic>-TG1 hippocampus. Importantly, the MeCP2 binding signal was almost completely absent in the <italic>Mecp2</italic>-knockout hippocampus in this same region (<xref ref-type="fig" rid="fig1">Figure 1D</xref>). Concurrently, we profiled the repressive histone modification H3K27me3 (<xref ref-type="fig" rid="fig1s2">Figure 1—figure supplement 2C</xref>), which has been shown to interact with and be modulated by MeCP2 (<xref ref-type="bibr" rid="bib28">Lee et al., 2020</xref>). Within the window of MeCP2 binding upstream of <italic>Gdf11</italic>, we found a significant (<italic>p</italic>&lt;0.01) increase in H3K27me3 occupancy in <italic>Mecp2</italic>-knockout tissue and a trend towards a reciprocal decrease in H3K27me3 occupancy in <italic>MECP2-</italic>TG1 tissue (<xref ref-type="fig" rid="fig1">Figure 1E</xref> and <xref ref-type="fig" rid="fig1s2">Figure 1—figure supplement 2E</xref>). The increase in H3K27me3 in <italic>Mecp2</italic>-knockout tissue corroborates the downregulation we observe in <italic>Gdf11</italic> expression in transcriptional profiles collected from <italic>Mecp2</italic>-deficient models (<xref ref-type="fig" rid="fig1">Figure 1B</xref>). These results suggest that MeCP2 binds upstream of <italic>Gdf11</italic>, at a putative enhancer, and modifies the chromatin landscape around the <italic>Gdf11</italic> locus to regulate <italic>Gdf11</italic> expression.</p></sec><sec id="s2-2"><title>Genetic reduction of <italic>Gdf11</italic> ameliorates behavioral deficits of <italic>MECP2</italic> duplication mice</title><p>Since <italic>Gdf11</italic> dysregulation is rescued upon normalization of <italic>MECP2</italic> dosage, we sought to determine if normalization of <italic>Gdf11</italic> alone can rescue behavioral deficits in <italic>MECP2</italic> duplication mice. We crossed the <italic>MECP2</italic>-TG1 allele with the <italic>Gdf11<sup>tm2b</sup></italic> allele to normalize <italic>Gdf11</italic> expression (<xref ref-type="fig" rid="fig1">Figure 1C</xref>). We generated a cohort of wild-type, <italic>MECP2</italic>-TG1, and <italic>MECP2</italic>-TG1; <italic>Gdf11<sup>tm2b/+</sup></italic> double mutant littermates and behaviorally characterized these mice with an extensive battery of assays starting at 16 weeks of age (<xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1A</xref>). Compared to wild-type mice, <italic>MECP2</italic>-TG1 mice are hypoactive when placed in an open arena, traveling less distance, and exhibiting fewer horizontal and vertical exploratory activities (<xref ref-type="fig" rid="fig2">Figure 2A</xref>). Normalizing <italic>Gdf11</italic> expression in the double mutant mice resulted in rescue of total distance traveled and horizontal activity. We also observed a partial rescue of vertical exploration and an improvement in anxiety-like behavior in the open arena as assessed by entries into the center (<xref ref-type="fig" rid="fig2">Figure 2A</xref> and <xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1B</xref>). We did not observe a difference in the ratio of the distance or time spent in the center of the arena (<xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1B</xref>). Next, <italic>MECP2</italic>-TG1 mice experience hypoactivity and anxiety-like behavior compared to wild-type mice when placed in an elevated plus maze apparatus, traveling less distance and entering the open arms fewer times. In contrast, we observed the double mutant animals entered the open arms and crossed the maze arms like wild-type animals, and the double mutant mice traveled significantly further (<italic>p</italic>&lt;0.01) on the maze compared to <italic>MECP2</italic>-TG1 mice (<xref ref-type="fig" rid="fig2">Figure 2B</xref>). Lastly, <italic>MECP2</italic>-TG1 mice exhibit improved learning compared to wild-type mice in a shock-tone cued fear paradigm. Specifically, mice are trained to associate a tone with a foot shock and then placed in the same environment without tone (context) or a new environment with a tone (cue). Learning in this assay is measured by the amount of time the mouse freezes, where <italic>MECP2</italic>-TG1 mice freeze more in both context and cued tests. Normalization of <italic>Gdf11</italic> led to wild-type levels of freezing during the training routine, and normalized the cued learning compared to <italic>MECP2</italic>-TG1 mice (<xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1C</xref>). Contextual learning was improved in double mutant mice with no significant difference observed compared to wild-type mice (<xref ref-type="fig" rid="fig2">Figure 2C</xref>). Reduction of <italic>Gdf11</italic> did not rescue all phenotypes present in <italic>MECP2</italic>-TG1 mice, as we did not observe a rescue in motor coordination on the rotating rod, change in the time spent in dark during the light-dark assay, nor any changes in sociability. However, we did observe rescue of total activity, as measured by distance traveled, in both light-dark and social assays (<xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1D–G</xref>). These data suggest that normalization of aberrant <italic>Gdf11</italic> expression improves several behavioral deficits, most notably locomotion, general activity, and hippocampal learning in <italic>MECP2</italic>-TG1 mice.</p><fig-group><fig id="fig2" position="float"><label>Figure 2.</label><caption><title>Genetic reduction and normalization of <italic>Gdf11</italic> dose ameliorates several behavioral deficits in <italic>MECP2</italic>-TG1 mice.</title><p>Behavioral characterization of <italic>MECP2-</italic>TG1, <italic>MECP2-</italic>TG1<italic>; Gdf11<sup>tm2b/+</sup></italic> double mutants, and their respective wild-type littermate controls was performed beginning at 16 weeks of age. (<bold>A</bold>) Open-field assessment of locomotion and activity. (<bold>B</bold>) Elevated plus maze assay measures of movement and anxiety-like behaviors. (<bold>C</bold>) Learning assessment using contextual fear-conditioning. Greater freezing indicates better memory of the context. Central estimate of data is shown as mean ± sem. Closed circles denote male mouse data points and open circles denote female mouse data points. For all open field and elevated plus maze (<bold>A,B</bold>), n=30 wild-type mice (19 male, 11 female); n=26 <italic>MECP2</italic>-TG1 mice (14 male, 12 female); and n=22 <italic>MECP2</italic>-TG1<italic>; Gdf11<sup>tm2b/+</sup></italic> mice (16 male, 6 female). For fear conditioning assay (<bold>C</bold>), n=17 wild-type mice (9 male, 8 female); n=25 <italic>MECP2</italic>-TG1 mice (13 male, 12 female); and n=22 <italic>MECP2</italic>-TG1<italic>; Gdf11<sup>tm2b/+</sup></italic> mice (16 male, 6 female). All data were analyzed using a Welsch one-way ANOVA with Dunnett’s post hoc multiple comparisons, and raw measurements are provided in <xref ref-type="supplementary-material" rid="fig2sdata1">Figure 2—source data 1</xref>. * <italic>p</italic>&lt;0.05, ** <italic>p</italic>&lt;0.01, *** <italic>p</italic>&lt;0.001, and **** <italic>p</italic>&lt;0.0001.</p><p><supplementary-material id="fig2sdata1"><label>Figure 2—source data 1.</label><caption><title>Raw data from all behavioral assays related to <xref ref-type="fig" rid="fig2">Figure 2</xref>, <xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1</xref>.</title></caption><media mimetype="application" mime-subtype="xlsx" xlink:href="elife-83806-fig2-data1-v1.xlsx"/></supplementary-material></p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-83806-fig2-v1.tif"/></fig><fig id="fig2s1" position="float" specific-use="child-fig"><label>Figure 2—figure supplement 1.</label><caption><title>Correction of <italic>Gdf11</italic> dose does not ameliorate all behavioral deficits in <italic>MECP2</italic>-TG1 mice.</title><p>Behavioral characterization of <italic>MECP2-</italic>TG1, <italic>MECP2-</italic>TG1<italic>; Gdf11<sup>tm2b/+</sup></italic> double mutants, and their respective wild-type littermate controls was performed beginning at 16 weeks of age. (<bold>A</bold>) Timeline and order of behavioral assays. (<bold>B</bold>) Open-field assessment of anxiety-like behavior as measured by entries into the center of the arena, ratio of the distance traveled in the center to total, and ratio of the time spent in the center over total. (<bold>C</bold>) Learning assessment during training and cued fear-conditioning. Greater freezing indicates better memory of the cue. (<bold>D</bold>) Motor coordination measured by the rotating rod assay. (<bold>E</bold>) Locomotion and anxiety-like behaviors measured by the light-dark assay. Mice with anxiety-like behaviors prefer to spend longer duration in the dark segment of the arena. (<bold>F, G</bold>) Sociability measured by the three-chamber assay, split into acclimation phase (<bold>F</bold>) and social phase (<bold>G</bold>). Central estimate of data is shown as mean ± sem. Closed circles denote male mouse data points and open circles denote female mouse data points. For all assays except fear conditioning, n=30 wild-type mice (19 male, 11 female); n=26 <italic>MECP2</italic>-TG1 mice (14 male, 12 female); and n=22 <italic>MECP2</italic>-TG1<italic>; Gdf11<sup>tm2b/+</sup></italic> mice (16 male, 6 female). For fear conditioning assay (<bold>C</bold>), n=17 wild-type mice (9 male, 8 female); n=25 <italic>MECP2</italic>-TG1 mice (13 male, 12 female); and n=22 <italic>MECP2</italic>-TG1<italic>; Gdf11<sup>tm2b/+</sup></italic> mice (16 male, 6 female). All data were analyzed using a Welsch one way ANOVA with Dunnett’s post hoc multiple comparisons, and raw measurements are provided in <xref ref-type="supplementary-material" rid="fig2sdata1">Figure 2—source data 1</xref>. * <italic>p</italic>&lt;0.05, ** <italic>p</italic>&lt;0.01, *** <italic>p</italic>&lt;0.001, and **** <italic>p</italic>&lt;0.0001.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-83806-fig2-figsupp1-v1.tif"/></fig></fig-group></sec><sec id="s2-3"><title>Loss of one copy of <italic>Gdf11</italic> causes neurobehavioral deficits in mice</title><p>The previous results raised the possibility that mouse neurological function is sensitive to changes in <italic>Gdf11</italic> dosage. Supporting this evidence, loss of one copy of <italic>GDF11</italic> function causes a developmental disorder with neurological features in humans (<xref ref-type="bibr" rid="bib49">Ravenscroft et al., 2021</xref>). Furthermore, <italic>GDF11</italic> is broadly and highly expressed in both the human and mouse brains, suggesting a potentially important role in brain function (<xref ref-type="fig" rid="fig3s1">Figure 3—figure supplement 1A and B</xref>; <xref ref-type="bibr" rid="bib31">Li et al., 2017</xref>).</p><p>To determine if loss of one copy of <italic>Gdf11</italic> resulted in neurobehavioral deficits, we generated a cohort of <italic>Gdf11<sup>tm2b/+</sup></italic> mice to characterize with a comprehensive battery of tests. We first confirmed that both <italic>Gdf11<sup>tm2b/+</sup></italic> and <italic>Gdf11<sup>tm2b/tm2b</sup></italic> mice exhibited abnormal anterior/posterior skeletal patterning by counting the number of attached and total ribs in neonatal pups. We observed that <italic>Gdf11<sup>tm2b/tm2b</sup></italic> pups had an abnormal number of 10 attached at 18 total ribs (n=4), while the <italic>Gdf11<sup>tm2b/+</sup></italic> pups had an abnormal number of 8 attached and 14 total ribs (n=24), matching the phenotypes previously described (<xref ref-type="fig" rid="fig3s1">Figure 3—figure supplement 1C</xref>; <xref ref-type="bibr" rid="bib37">McPherron et al., 1999</xref>). These skeletal abnormalities, the observed perinatal lethality of <italic>Gdf11<sup>tm2b/tm2b</sup></italic> pups (<xref ref-type="bibr" rid="bib37">McPherron et al., 1999</xref>), and the 50% reduction of <italic>Gdf11</italic> in the brains of <italic>Gdf11<sup>tm2b/+</sup></italic> mice (<xref ref-type="fig" rid="fig1">Figure 1C</xref>) demonstrate that the <italic>Gdf11<sup>tm2b</sup></italic> allele is a null allele. Interestingly, we also observed the same skeletal patterning defects in <italic>MECP2-</italic>TG1; <italic>Gdf11<sup>tm2b/+</sup></italic> pups, which had an abnormal number of 8 attached and 14 total ribs (n=4), while <italic>MECP2</italic>-TG1 pups had the same number of 7 attached and 13 total ribs (n=4) as wild-type pups (<xref ref-type="fig" rid="fig3s1">Figure 3—figure supplement 1C</xref>), further suggesting that the regulatory relationship between <italic>Gdf11</italic> and <italic>Mecp2</italic> is brain specific. Taken together, <italic>Gdf11<sup>tm2b</sup></italic> heterozygotes can be used to model the effects of losing one copy of <italic>Gdf11.</italic> Given these results, we generated a cohort of wild-type and <italic>Gdf11<sup>tm2b/+</sup></italic> littermates and began general health assessments at weaning (<xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2A</xref>). We observed that these mice did not display any overt phenotypes and did not have a change in body weight in either sex through sixteen weeks of age (<xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2B</xref>).</p><p>We began deeper behavioral characterization of the cohort at sixteen weeks of age. In the open field assay, we observed that <italic>Gdf11<sup>tm2b/+</sup></italic> mice are hyperactive as indicated by a significant increase in total distance traveled (<italic>p</italic>&lt;0.05), a significant increase in horizontal activity counts (<italic>p</italic>&lt;0.05), and a significant increase in vertical exploratory activity counts (<italic>p</italic>&lt;0.01) (<xref ref-type="fig" rid="fig3">Figure 3A</xref>). <italic>Gdf11<sup>tm2b/+</sup></italic> mice explored the center of the arena at a similar rate and ratio as wild-type mice (<xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2C</xref>). In the elevated plus maze, <italic>Gdf11<sup>tm2b/+</sup></italic> mice also displayed hyperactivity, traveling a significantly further distance (<italic>p</italic>&lt;0.01) and decreased anxiety-like behavior, entering the open arm a significantly higher number of times (<italic>p</italic>&lt;0.001; <xref ref-type="fig" rid="fig3">Figure 3B</xref>). <italic>Gdf11<sup>tm2b/+</sup></italic> mice traveled a significantly further distance (<italic>p</italic>&lt;0.05) in the light-dark assay while spending significantly more time (<italic>p</italic>&lt;0.05) in the dark (<xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2D</xref>). Furthermore, when placed in a three-chamber apparatus, <italic>Gdf11<sup>tm2b/+</sup></italic> mice explored more both during habituation and testing phases (<xref ref-type="fig" rid="fig3">Figure 3C</xref> and <xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2E</xref>). This manifests with a significantly (<italic>p</italic>&lt;0.05) decreased time socializing compared to control (<xref ref-type="fig" rid="fig3">Figure 3C</xref>). The ratio of time spent investigating the partner mouse over the total investigation time was significantly (<italic>p</italic>&lt;0.0001) less in <italic>Gdf11<sup>tm2b/+</sup></italic> mice (<xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2F</xref>), though importantly the <italic>Gdf11<sup>tm2b/+</sup></italic> mice are still social and prefer interacting with the partner mouse over the object (<italic>p</italic>&lt;0.001; <xref ref-type="fig" rid="fig3">Figure 3C</xref>). Next, we observed a significant (<italic>p</italic>&lt;0.0001) reduction in motor coordination and learning as assessed by the rotating rod assay (<xref ref-type="fig" rid="fig3">Figure 3D</xref>). Finally, we observed a trend in reduction in learning during the training phase of a shock-tone conditioning paradigm (<xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2G</xref>), while observing a significant reduction in contextual learning (<italic>p</italic>&lt;0.01) and cued learning (<italic>p</italic>&lt;0.05; <xref ref-type="fig" rid="fig3">Figure 3E</xref>). These data collectively suggest that neurological behaviors are sensitive to loss of one copy of <italic>Gdf11</italic> in mice.</p><fig-group><fig id="fig3" position="float"><label>Figure 3.</label><caption><title>Mice lacking one copy of <italic>Gdf11</italic> (<italic>Gdf11<sup>tm2b</sup></italic><sup>/+</sup>) display behavioral deficits.</title><p>Behavioral characterization of <italic>Gdf11<sup>tm2b/+</sup></italic> mice and their respective wild-type littermate controls was performed beginning at 16 weeks of age. (<bold>A</bold>) Open field assessment of locomotion and activity. (<bold>B</bold>) Elevated plus maze assay measures of movement and anxiety-like behaviors. (<bold>C</bold>) Distance traveled and time investigating novel mouse in 3-chamber sociability assay. (<bold>D</bold>) Motor coordination measured by the rotating rod assay. (<bold>E</bold>) Learning assessment using contextual and cued fear-conditioning. Greater freezing indicates better memory of the context. (<bold>F</bold>) Survival analysis. Central estimate of data is shown as mean ± sem. Closed circles denote male mouse data points and open circles denote female mouse data points. For behavioral measurements except fear conditioning, n=29 wild-type mice (15 male, 14 female) and n=34 <italic>Gdf11<sup>tm2b/+</sup></italic> mice (16 male, 18 female). For fear conditioning assay, n=28 wild-type mice (16 male, 12 female) and n=24 <italic>Gdf11<sup>tm2b/+</sup></italic> mice (9 male, 15 female). For survival analysis, n=15 wild-type mice and n=17 <italic>Gdf11<sup>tm2b/+</sup></italic> mice. Behavioral data were analyzed using Welsch t-test and raw measurements are provided in <xref ref-type="supplementary-material" rid="fig3sdata1">Figure 3—source data 1</xref>. Survival was analyzed using Mantel-Cox test. * <italic>p</italic>&lt;0.05, ** <italic>p</italic>&lt;0.01, *** <italic>p</italic>&lt;0.001, and **** <italic>p</italic>&lt;0.0001.</p><p><supplementary-material id="fig3sdata1"><label>Figure 3—source data 1.</label><caption><title>Raw data from all behavioral assays related to <xref ref-type="fig" rid="fig3">Figure 3</xref> and <xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2</xref>.</title></caption><media mimetype="application" mime-subtype="xlsx" xlink:href="elife-83806-fig3-data1-v1.xlsx"/></supplementary-material></p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-83806-fig3-v1.tif"/></fig><fig id="fig3s1" position="float" specific-use="child-fig"><label>Figure 3—figure supplement 1.</label><caption><title><italic>Gdf11</italic> is highly expressed in the brain and loss of one copy causes abnormal skeletal development.</title><p>(<bold>A</bold>) <italic>GDF11</italic> expression is higher in the brain compared to peripheral tissues. The consensus human tissue expression dataset from the Human Protein Atlas was queried for <italic>GDF11</italic> (top) and <italic>MECP2</italic> (bottom) expression levels by tissue. Tissues are sorted based on <italic>GDF11</italic> expression and tissues in the central nervous system are colored red. (<bold>B</bold>) <italic>Gdf11</italic> is highly expressed in the mouse brain. Mouse tissue RNA-seq expression dataset was taken from <xref ref-type="bibr" rid="bib31">Li et al., 2017</xref> and queried for <italic>Gdf11</italic> (top) and <italic>Mecp2</italic> (bottom) expression levels by tissue. Brain samples are colored red. Data from n=4 replicates is shown as a boxplot. (<bold>C</bold>) <italic>Gdf11<sup>tm2b/tm2b</sup></italic> and <italic>Gdf11<sup>tm2b/+</sup></italic> mice exhibit the same skeletal patterning defects as described in the original <italic>Gdf11<sup>-/-</sup></italic> line. Widefield imaging of the rib segments from P0 pups of the indicated genotype using Alcian blue and Alizarin red staining. Attached ribs are highlighted with white dotted lines, while unattached ribs are highlighted with black dotted lines. The top panels show the skeleton from a ventral view, while the bottom panels show the skeleton from a dorsal view. Image is representative of n=13 (WT), 4 (<italic>Gdf11<sup>tm2b/tm2b</sup></italic>), 24 (<italic>Gdf11<sup>tm2b/+</sup></italic>), 4 (<italic>MECP2-</italic>TG1), and 4 (<italic>MECP2-</italic>TG1; <italic>Gdf11<sup>tm2b/+</sup></italic>) pups. Scale bar is 2 mm. (C’, inset) Image of P0 <italic>Gdf11<sup>tm2b/tm2b</sup></italic> pup displaying truncated tail and perinatal lethality.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-83806-fig3-figsupp1-v1.tif"/></fig><fig id="fig3s2" position="float" specific-use="child-fig"><label>Figure 3—figure supplement 2.</label><caption><title>Loss of one copy of <italic>Gdf11</italic> does not alter all behavioral phenotypes.</title><p>Behavioral characterization of <italic>Gdf11<sup>tm2b/+</sup></italic> mice and their respective wild-type littermate controls was performed beginning at 16 weeks of age. (<bold>A</bold>) Timeline and order of behavioral assays. (<bold>B</bold>) Weight measurements in male and female <italic>Gdf11<sup>tm2b/+</sup></italic> and wild-type littermates. Left plot displays data for males, and right plot displays data for females. (<bold>C</bold>) Open field assessment of anxiety-like behavior as measured by entries into the center of area and ratios of distance and time spent in the center. (<bold>D</bold>) Locomotion and anxiety-like behavior measured by the light-dark assay. Mice with anxiety-like behaviors prefer to spend longer duration in the dark segment of the arena. (<bold>E,F</bold>) Sociability measured by the 3-chamber assay, split into acclimation phase (<bold>E</bold>) and social phase presented as the ratio of time investigating partner mouse over total time investigating (<bold>F</bold>). (<bold>G</bold>) Learning during shock-tone fear conditioning paradigm. Central estimate of behavior data is shown as mean ± sem. Closed circles denote male mouse data points and open circles denote female mouse data points. For behavioral measurements except fear conditioning, n=29 wild-type mice (15 male, 14 female) and n=34 <italic>Gdf11<sup>tm2b/+</sup></italic> mice (16 male, 18 female). For fear conditioning assay, n=28 wild-type mice (16 male, 12 female) and n=24 <italic>Gdf11<sup>tm2b/+</sup></italic> mice (9 male, 15 female). For survival analysis, n=15 wild-type mice and n=17 <italic>Gdf11<sup>tm2b/+</sup></italic> mice. Behavioral data were analyzed using Welsch t-test, and raw measurements are provided in <xref ref-type="supplementary-material" rid="fig3sdata1">Figure 3—source data 1</xref>. * <italic>p</italic>&lt;0.05, ** <italic>p</italic>&lt;0.01, *** <italic>p</italic>&lt;0.001, and **** <italic>p</italic>&lt;0.0001.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-83806-fig3-figsupp2-v1.tif"/></fig></fig-group><p>As <italic>Gdf11</italic> has been implicated to naturally decrease in aging in mice (<xref ref-type="bibr" rid="bib45">Poggioli et al., 2016</xref>), we tested if a reduction in <italic>Gdf11</italic> dosage can alter aging by tracking the survival of a cohort of <italic>Gdf11<sup>tm2b/+</sup></italic> mice. Strikingly, we found a significant (<italic>p</italic>&lt;0.001) reduction in survival of <italic>Gdf11<sup>tm2b/+</sup></italic> mice compared to wild-type littermates (n=15 wild-type and n=17 <italic>Gdf11<sup>tm2b/+</sup></italic>), exhibiting a median survival of 1.8 years (<xref ref-type="fig" rid="fig3">Figure 3F</xref>). Also, a portion <italic>Gdf11<sup>tm2b/+</sup></italic> mice were euthanized due to reaching ethical endpoints including poor body conditioning, self-lesioning, and development of tumors, which suggests that <italic>Gdf11</italic> dosage plays an important role in long-term health and survival in mice.</p></sec><sec id="s2-4"><title>Loss of one copy of <italic>Gdf11</italic> does not alter proliferation, amplifying progenitors, or neural stem cells in the adult hippocampus</title><p>Learning and memory is linked to the generation of adult-born neurons in the subgranular zone (SGZ) of the mouse dentate gyrus (<xref ref-type="bibr" rid="bib26">Kempermann and Gage, 2002</xref>). Complete loss of <italic>Gdf11</italic> in adulthood was shown to increase proliferation in the SGZ, specifically in the number of amplifying progenitors (SOX2 positive), while impairing the overall number of newborn neurons that survive and integrate into the existing hippocampal circuitry (<xref ref-type="bibr" rid="bib36">Mayweather et al., 2021</xref>). Additionally, neurogenesis is negatively impacted in the olfactory epithelium with loss or inhibition of GDF11 (<xref ref-type="bibr" rid="bib69">Wu et al., 2003</xref>). To test if loss of one copy of <italic>Gdf11</italic> altered overall proliferation in the SGZ, potentially acting as a mechanism for the changes in learning and memory observed in <italic>Gdf11<sup>tm2b/+</sup></italic> mice, we labeled newborn, dividing cells by injecting <italic>Gdf11<sup>tm2b/+</sup></italic> and control mice with 5-Ethyl-2’-deoxyuridine (EdU). We injected the animals with EdU (10 mg/kg) for 5 consecutive days and fixed the brains at 7 days after the first injection. We performed these injections in sixteen-week-old animals, matching the timepoint when we performed behavioral characterization. We then stained for EdU, SOX2, and GFAP to label proliferating cells (EdU<sup>+</sup>), neural stem cells (SOX2<sup>+</sup>GFAP<sup>+</sup>), and amplifying progenitors (SOX2<sup>+</sup>) (<xref ref-type="bibr" rid="bib13">Cope and Gould, 2019</xref>; <xref ref-type="bibr" rid="bib74">Zhao and Praag, 2020</xref>). We did not observe any significant changes in the number or density of these cell populations in <italic>Gdf11<sup>tm2b/+</sup></italic> mice using quantitative stereology (<xref ref-type="fig" rid="fig4">Figure 4</xref> and <xref ref-type="fig" rid="fig4s1">Figure 4—figure supplement 1A–D</xref>). Furthermore, no gross changes in brain anatomy or volume of the dentate gyrus were observed in <italic>Gdf11<sup>tm2b/+</sup></italic> mice (<xref ref-type="fig" rid="fig4s1">Figure 4—figure supplement 1E–G</xref>). These results indicate that the behavioral deficits caused by loss of one copy of <italic>Gdf11</italic> are not due to altered proliferation in the adult mouse SGZ.</p><fig-group><fig id="fig4" position="float"><label>Figure 4.</label><caption><title>Loss of one copy of <italic>Gdf11</italic> does not alter adult neurogenesis in the dentate gyrus.</title><p>Quantification of markers of (<bold>A</bold>) proliferative cells (EdU) or (<bold>B–D</bold>) neural progenitor pools (SOX2 and GFAP) in the subgranular zone of the dentate gyrus in wild-type or <italic>Gdf11<sup>tm2b/+</sup></italic> mice. Representative images of the dentate gyrus for the indicate stains are shown on the left. The projected total number of cells and the density of cells is shown on the plots to the right using stereology to quantify n=3–6 separate slices per animal (N=3 wild-type animals and 5 <italic>Gdf11<sup>tm2b/+</sup></italic> animals) (see Methods). Each data point is the aggregated value for one animal. Closed circles denote male animals and open circles denote female animals. Data are presented as mean ± sem. Data were analyzed using Welsch’s t-test, and raw measurements are provided in <xref ref-type="supplementary-material" rid="fig4sdata1">Figure 4—source data 1</xref>. Scale bar is 200 μm and is the same for all images.</p><p><supplementary-material id="fig4sdata1"><label>Figure 4—source data 1.</label><caption><title>Raw measurements and stereology quantification of neurogenesis markers.</title></caption><media mimetype="application" mime-subtype="xlsx" xlink:href="elife-83806-fig4-data1-v1.xlsx"/></supplementary-material></p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-83806-fig4-v1.tif"/></fig><fig id="fig4s1" position="float" specific-use="child-fig"><label>Figure 4—figure supplement 1.</label><caption><title>Loss of one copy of <italic>Gdf11</italic> does not cause gross anatomical abnormalities or gross differences in progenitor pools.</title><p>(<bold>A–D</bold>) Total number of EdU (<bold>A</bold>), SOX2 (<bold>B</bold>), GFAP (<bold>C</bold>), or SOX2; GFAP double positive (<bold>D</bold>) cells scored by stereology. Counts are sums from n=3–6 separate slices per animal (N=3 wild-type animals and 5 <italic>Gdf11<sup>tm2b/+</sup></italic> animals). (<bold>E</bold>) Estimated volume of the dentate gyrus from stereological quantification. (<bold>F,G</bold>) Images of Cresyl violet stain of sagittal sections from wild-type or <italic>Gdf11<sup>tm2b/+</sup></italic> brains. Scale bar is 1 mm. Each data point is the sum for one animal. Closed circles denote male animals and open circles denote female animals. Data are presented as mean ± sem. Data were analyzed using Welsch’s t-test, and raw measurements are provided in <xref ref-type="supplementary-material" rid="fig4sdata1">Figure 4—source data 1</xref>.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-83806-fig4-figsupp1-v1.tif"/></fig></fig-group></sec></sec><sec id="s3" sec-type="discussion"><title>Discussion</title><p>The heterogeneity in genetic causes for IDD and ASD has precluded the development of targeted therapies for these disorders. Distilling any common molecular processes that have gone awry in multiple disorders would give us a handle to investigate further and identify drug targets. In this study, we thoroughly investigated genes regulated by the exemplar dosage-sensitive gene <italic>MECP2</italic>, the causative gene of two different neurological disorders (RTT and MDS) to discover that MeCP2 sensitively and acutely regulates <italic>Gdf11</italic>. Intriguingly, <italic>Gdf11</italic> is inversely dysregulated in RTT and MDS and restoring normal <italic>Gdf11</italic> dosage ameliorated several behavioral deficits in a mouse model of MDS. This potential sensitivity of <italic>Gdf11</italic> dosage in the brain led us to further discover that reduction of <italic>Gdf11</italic> dosage alone caused neurobehavioral deficits in mice as well. Our study strongly suggests that GDF11 signaling is dysregulated in more than one neurodevelopmental disorder (RTT, MDS, and <italic>GDF11</italic> haploinsufficiency) and modifies MeCP2-driven abnormal behaviors.</p><p>Transcriptomics is often used to identify molecular pathways that are dysregulated in diseases. However, uncovering the core genes that are altered can be challenging due to secondary effects and neuronal dysfunction, which has been particularly problematic in dissecting the molecular pathogenesis of MeCP2 (<xref ref-type="bibr" rid="bib55">Sanfeliu et al., 2019</xref>). In this study, we leveraged dynamic gene expression changes upon acute decrease of <italic>MECP2</italic> in a mouse model of MDS (<xref ref-type="bibr" rid="bib60">Shao et al., 2021b</xref>), which specifically revealed that <italic>Gdf11</italic> is highly correlated with MeCP2 protein levels. Generalization of these results demonstrated that <italic>Gdf11</italic> is robustly dysregulated in mouse models of MeCP2-related disorders and regulated by MeCP2 at the chromatin level (<xref ref-type="fig" rid="fig1">Figure 1</xref>). These data suggest that <italic>Gdf11</italic> is proximally downstream of MeCP2, sensitive to both MeCP2 expression and function. Ongoing efforts are looking to restore MeCP2 dosage in mouse models of RTT and MDS (<xref ref-type="bibr" rid="bib60">Shao et al., 2021b</xref>; <xref ref-type="bibr" rid="bib62">Sinnamon et al., 2017</xref>; <xref ref-type="bibr" rid="bib63">Sinnett et al., 2021</xref>). Typically, these studies rely on behavioral outcomes to assess treatment efficacy. However, behavioral improvements downstream of restored MeCP2 dosage or function may take weeks and may require a large sample size to manifest (<xref ref-type="bibr" rid="bib25">Katz et al., 2012</xref>; <xref ref-type="bibr" rid="bib60">Shao et al., 2021b</xref>; <xref ref-type="bibr" rid="bib66">Sztainberg et al., 2015</xref>). We propose that <italic>Gdf11</italic> expression in the brain can be used as an endogenous reporter for MeCP2 dosage and function in preclinical studies that can leverage the sensitivity of biomolecular measurements. Adding <italic>Gdf11</italic> expression to the repertoire of metrics to evaluate treatment outcomes may prevent preliminary and promising candidates from being scrapped if behavioral outcomes are unclear or slow to normalize.</p><p>We showed that normalization of <italic>Gdf11</italic> dosage improved several behavioral deficits in a mouse model of MDS when normalization of <italic>Gdf11</italic> occurred using a constitutive germline deletion. If normalization of <italic>Gdf11</italic> dosage could be used to treat MeCP2-related disorders, we must first test if restoring <italic>Gdf11</italic> dosage in symptomatic RTT or MDS mouse models leads to outcome improvements. These experiments will decouple if MeCP2 regulation of <italic>Gdf11</italic> is critical during a presymptomatic window or throughout life. Importantly, GDF11 is a secreted factor, and its protein dosage could be modulated using recombinant protein to increase dosage (for RTT or <italic>GDF11</italic> haploinsufficiency) or using a neutralizing antibody to decrease dosage (for MDS) (<xref ref-type="bibr" rid="bib41">Morvan et al., 2017</xref>; <xref ref-type="bibr" rid="bib44">Ozek et al., 2018</xref>; <xref ref-type="bibr" rid="bib73">Zhang et al., 2018</xref>). Lastly, as GDF11 is present in the blood, there is a possibility that modulation of GDF11 dosage in the circulation impacts GDF11 dosage in the brain, affording an easily accessible route to modulating GDF11 levels (<xref ref-type="bibr" rid="bib45">Poggioli et al., 2016</xref>; <xref ref-type="bibr" rid="bib70">Xu et al., 2020</xref>).</p><p>Our study contributes to the growing body of work that <italic>GDF11</italic> is a dosage sensitive gene important to neural function. Loss-of-function mutations in <italic>GDF11</italic> have recently been described to cause neurological dysfunction as part of a broader developmental disorder. These patients exhibit abnormalities including intellectual disability, speech delay, and seizures (<xref ref-type="bibr" rid="bib14">Cox et al., 2019</xref>; <xref ref-type="bibr" rid="bib49">Ravenscroft et al., 2021</xref>). In this study, we show that reducing <italic>Gdf11</italic> dosage by one copy in mice also causes abnormal phenotypes, which we can now leverage to investigate mechanisms of neuronal dysfunction in <italic>GDF11</italic> haploinsufficiency. Furthermore, a recent genomic study predicted that <italic>GDF11</italic> is intolerant to copy number gains in humans (<xref ref-type="bibr" rid="bib12">Collins et al., 2022</xref>). Our work suggests that increased <italic>Gdf11</italic> expression contributes to abnormal phenotypes in mouse models of MDS. Using mouse models that overexpress <italic>GDF11</italic> alone could be used to determine if copy number gain in GDF11 is toxic (<xref ref-type="bibr" rid="bib22">Jones et al., 2018</xref>). These studies will be important to determine whether GDF11 can be a therapeutic target if appropriately dosed.</p><p>Our study also highlights the challenges that arise when studying the interaction of multiple dosage-sensitive genes. The decrease or gain of a dosage-sensitive gene by even as little as ±30% can cause exactly reciprocal phenotypes (<xref ref-type="bibr" rid="bib59">Shao et al., 2021a</xref>). In our case, <italic>Gdf11<sup>tm2b/+</sup></italic> mice have phenotypes that present in the opposing direction as the <italic>MECP2</italic>-TG1 mice and in the same direction of <italic>Mecp2</italic>-null male mice (<xref ref-type="bibr" rid="bib25">Katz et al., 2012</xref>), which have reduced <italic>Gdf11</italic> expression; thus parsing out the direct cause-and-effect relationships from a potential pseudonormalization remains difficult even with deeper molecular or neurophysiologic characterization (<xref ref-type="bibr" rid="bib27">Lavery et al., 2020</xref>; <xref ref-type="bibr" rid="bib75">Zhou et al., 2022</xref>). As <italic>Gdf11</italic> expression is rescued in ASO-treated <italic>MECP2</italic>-duplication mice before behavioral rescue (<xref ref-type="bibr" rid="bib60">Shao et al., 2021b</xref>), we speculate the normalization of <italic>Gdf11</italic> in the <italic>MECP2</italic>-TG1; <italic>Gdf11<sup>tm2b/+</sup></italic> mice plays a direct role in the improvement of neurological dysfunction of <italic>MECP2</italic>-TG1 mice. Furthermore, not all behaviors or phenotypes were rescued, like the rotarod in which <italic>MECP2</italic>-TG1 and <italic>Gdf11<sup>tm2b/+</sup></italic> mice have opposing phenotypes. Additionally, skeletal abnormalities observed in <italic>Gdf11<sup>tm2b/+</sup></italic> pups were not rescued by increased <italic>Mecp2</italic> dosage in <italic>MECP2</italic>-TG1; <italic>Gdf11<sup>tm2b/+</sup></italic> pups, further suggesting that pseudonormalization does not explain the overall phenotypic profile of <italic>MECP2</italic>-TG1; <italic>Gdf11<sup>tm2b/+</sup></italic> mice. Lastly, as both <italic>Mecp2</italic> and <italic>Gdf11</italic> have developmental roles (<xref ref-type="bibr" rid="bib37">McPherron et al., 1999</xref>; <xref ref-type="bibr" rid="bib58">Shahbazian et al., 2002</xref>), conditional genetics will be needed to precisely parse the mechanisms by which <italic>Gdf11</italic> and <italic>Mecp2</italic> dosage interact to regulate neurological function.</p><p>Though <italic>GDF11</italic> is broadly and highly expressed in the mouse and human brains, we have a limited understanding of its function. As a secreted factor, it is unclear why this gene must be expressed throughout the brain in multiple cell types (<xref ref-type="bibr" rid="bib57">Saunders et al., 2018</xref>). This may suggest that GDF11 has a strong autocrine and paracrine role in the brain rather than an endocrine role. We must therefore catalog which neurons or brain regions secrete or sense GDF11 at the protein level and understand the functional neuronal response to GDF11 stimulation. These studies will parse out the specific relationship of GDF11 dosage and neurological phenotypes. For example, we see robust hyperactivity in <italic>Gdf11<sup>tm2b</sup></italic> heterozygotes, but more variable effects on anxiety-like behaviors. How do the cells or circuits driving hyperactivity in <italic>Gdf11<sup>tm2b</sup></italic> heterozygotes interact with the cells and circuits responsible for learning and memory? Are these behaviors influenced because specific brain regions or cell types are producing or sensing GDF11? Furthermore, we discovered that <italic>Gdf11</italic> dosage is important to survival in mice, corroborating a role of GDF11 in aging (<xref ref-type="bibr" rid="bib24">Katsimpardi et al., 2014</xref>; <xref ref-type="bibr" rid="bib33">Loffredo et al., 2013</xref>; <xref ref-type="bibr" rid="bib61">Sinha et al., 2014</xref>), but it remains unknown whether this role is due to GDF11 expression in the brain. As such, understanding the production, transduction, and transmission mechanisms of GDF11 signaling in the brain will have long standing importance to multiple fields.</p><p>In summary, our study provides a framework for identifying putative disease-modifying genes by integrating multiple -omics level datasets. Through these analyses, we linked seemingly disparate disease-causing genes, <italic>MECP2</italic> and <italic>GDF11</italic> in this case, by characterizing a regulatory relationship between them. Probing other disease-causing genes in this way will allow us to stitch together a network of dosage-sensitive genes, which will reveal points of regulatory and molecular convergence across a wide range of diseases.</p></sec><sec id="s4" sec-type="materials|methods"><title>Materials and methods</title><table-wrap id="keyresource" position="anchor"><label>Key resources table</label><table frame="hsides" rules="groups"><thead><tr><th align="left" valign="bottom">Reagent type (species) or resource</th><th align="left" valign="bottom">Designation</th><th align="left" valign="bottom">Source or reference</th><th align="left" valign="bottom">Identifiers</th><th align="left" valign="bottom">Additional information</th></tr></thead><tbody><tr><td align="left" valign="bottom">Strain, strain background (<italic>Mus musculus</italic>; male and female)</td><td align="left" valign="bottom"><italic>Gdf11<sup>tm2a(EUCOMM)Hmgu</sup></italic></td><td align="left" valign="bottom">MMRRC</td><td align="left" valign="bottom">Cat. #037721-UCD; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:MMRRC_037721-UCD">MMRRC_037721-UCD</ext-link></td><td align="left" valign="bottom">Gdf11<italic><sup>tm2b</sup></italic> allele generated by breeding with <italic>Sox2</italic>-Cre; maintained on C57BL/6J background</td></tr><tr><td align="left" valign="bottom">Strain, strain background (<italic>Mus musculus</italic>; male and female)</td><td align="left" valign="bottom"><italic>MECP2</italic>-TG1 (Tg(<italic>MECP2)</italic>1Hzo)</td><td align="left" valign="bottom">The Jackson Laboratory</td><td align="left" valign="bottom">Cat. #008679; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:IMSR_JAX:008679">IMSR_JAX:008679</ext-link></td><td align="left" valign="bottom">Maintained on C57BL/6J background</td></tr><tr><td align="left" valign="bottom">Strain, strain background (<italic>Mus musculus</italic>; male and female)</td><td align="left" valign="bottom"><italic>Mecp2<sup>tm1.1Bird</sup></italic></td><td align="left" valign="bottom">The Jackson Laboratory</td><td align="left" valign="bottom">Cat. #003890; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:IMSR_JAX:003890">IMSR_JAX:003890</ext-link></td><td align="left" valign="bottom">Maintained on C57BL/6J background</td></tr><tr><td align="left" valign="bottom">Strain, strain background (<italic>Mus musculus</italic>; female)</td><td align="left" valign="bottom"><italic>Sox2-Cre</italic></td><td align="left" valign="bottom">The Jackson Laboratory</td><td align="left" valign="bottom">Cat. #008454; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:IMSR_JAX:008454">IMSR_JAX:008454</ext-link></td><td align="left" valign="bottom"/></tr><tr><td align="left" valign="bottom">Strain, strain background (<italic>Mus musculus</italic>; male and female)</td><td align="left" valign="bottom">C57BL/6J</td><td align="left" valign="bottom">The Jackson Laboratory</td><td align="left" valign="bottom">Cat. #000664; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:IMSR_JAX:000664">IMSR_JAX:000664</ext-link></td><td align="left" valign="bottom"/></tr><tr><td align="left" valign="bottom">Antibody</td><td align="left" valign="bottom">Rabbit anti-MeCP2 (clone D4F3) (rabbit monoclonal)</td><td align="left" valign="bottom">Cell Signaling Technology</td><td align="left" valign="bottom">Cat. #3456; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:AB_2143894">AB_2143894</ext-link></td><td align="char" char="." valign="bottom">1:100</td></tr><tr><td align="left" valign="bottom">Antibody</td><td align="left" valign="bottom">Rabbit anti-Try-Methyl-Histone H3 (Lys27) (clone C36B11) (rabbit monoclonal)</td><td align="left" valign="bottom">Cell Signaling Technology</td><td align="left" valign="bottom">Cat. #9733; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:AB_2616029">AB_2616029</ext-link></td><td align="char" char="." valign="bottom">1:100</td></tr><tr><td align="left" valign="bottom">Antibody</td><td align="left" valign="bottom">Rabbit IgG (rabbit polyclonal)</td><td align="left" valign="bottom">Millipore</td><td align="left" valign="bottom">Cat. #12–370; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:AB_145841">AB_145841</ext-link></td><td align="char" char="." valign="bottom">1:100</td></tr><tr><td align="left" valign="bottom">Antibody</td><td align="left" valign="bottom">Mouse anti-GFAP (mouse monoclonal)</td><td align="left" valign="bottom">Sigma-Aldrich</td><td align="left" valign="bottom">Cat. #G3893; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:AB_477010">AB_477010</ext-link></td><td align="char" char="." valign="bottom">1:1000</td></tr><tr><td align="left" valign="bottom">Antibody</td><td align="left" valign="bottom">Rabbit anti-SOX2 (rabbit polyclonal)</td><td align="left" valign="bottom">Abcam</td><td align="left" valign="bottom">Cat. #ab97959; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:AB_2341193">AB_2341193</ext-link></td><td align="char" char="." valign="bottom">1:500</td></tr><tr><td align="left" valign="bottom">Antibody</td><td align="left" valign="bottom">Donkey anti-rabbit Alexa 488 (donkey polyclonal)</td><td align="left" valign="bottom">Jackson ImmunoResearch</td><td align="left" valign="bottom">Cat #711-545-152; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:AB_2313584">AB_2313584</ext-link></td><td align="char" char="." valign="bottom">1:1000</td></tr><tr><td align="left" valign="bottom">Antibody</td><td align="left" valign="bottom">Donkey anti-mouse Alexa 555 (donkey polyclonal)</td><td align="left" valign="bottom">ThermoFisher Scientific</td><td align="left" valign="bottom">Cat #A-31570; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:AB_2536180">AB_2536180</ext-link></td><td align="char" char="." valign="bottom">1:1000</td></tr><tr><td align="left" valign="bottom">Other</td><td align="left" valign="bottom">Concanavalin A magnetic beads</td><td align="left" valign="bottom">Bangs Laboratories Inc</td><td align="left" valign="bottom">Cat. #BP531</td><td align="left" valign="bottom">See Materials and Methods, CUT&amp;RUN</td></tr><tr><td align="left" valign="bottom">Other</td><td align="left" valign="bottom">pAG-MNase</td><td align="left" valign="bottom">Epicypher</td><td align="left" valign="bottom">Cat. #15–1016</td><td align="left" valign="bottom">See Materials and Methods, CUT&amp;RUN</td></tr><tr><td align="left" valign="bottom">Other</td><td align="left" valign="bottom">RNAse A</td><td align="left" valign="bottom">ThermoFisher Scientific</td><td align="left" valign="bottom">Cat. #EN0531</td><td align="left" valign="bottom">See Materials and Methods, CUT&amp;RUN</td></tr><tr><td align="left" valign="bottom">Other</td><td align="left" valign="bottom"><italic>E. coli</italic> spike-in</td><td align="left" valign="bottom">Epicypher</td><td align="left" valign="bottom">Cat. #18–1401</td><td align="left" valign="bottom">See Materials and Methods, CUT&amp;RUN</td></tr><tr><td align="left" valign="bottom">Other</td><td align="left" valign="bottom">MaXtract tubes</td><td align="left" valign="bottom">Qiagen</td><td align="left" valign="bottom">Cat. #129046</td><td align="left" valign="bottom">See Materials and Methods, CUT&amp;RUN</td></tr><tr><td align="left" valign="bottom">Commercial assay or kit</td><td align="left" valign="bottom">NEB Next II DNA Ultra Kit</td><td align="left" valign="bottom">New England Biolabs</td><td align="left" valign="bottom">Cat. #E7645S</td><td align="left" valign="bottom"/></tr><tr><td align="left" valign="bottom">Commercial assay or kit</td><td align="left" valign="bottom">Unique Combinatorial Dual Index kit</td><td align="left" valign="bottom">New England Biolabs</td><td align="left" valign="bottom">Cat. #E6442S</td><td align="left" valign="bottom"/></tr><tr><td align="left" valign="bottom">Other</td><td align="left" valign="bottom">SPRI select beads</td><td align="left" valign="bottom">Beckman Coulter</td><td align="left" valign="bottom">Cat. #B23318</td><td align="left" valign="bottom">See Materials and Methods, CUT&amp;RUN Next Generation Sequencing Library Preparation</td></tr><tr><td align="left" valign="bottom">Commercial assay or kit</td><td align="left" valign="bottom">KAPA library quantification kit</td><td align="left" valign="bottom">Roche</td><td align="left" valign="bottom">Cat. #5067</td><td align="left" valign="bottom"/></tr><tr><td align="left" valign="bottom">Other</td><td align="left" valign="bottom">5-ethynyl-2’-deoxyuridine (EdU)</td><td align="left" valign="bottom">Invitrogen</td><td align="left" valign="bottom">Cat. #E10187</td><td align="left" valign="bottom">See Materials and Methods, EdU and Immunofluorescnece staining</td></tr><tr><td align="left" valign="bottom">Commercial assay or kit</td><td align="left" valign="bottom">Click-iT EdU Imaging Kit with AlexaFluor 647 dye</td><td align="left" valign="bottom">Invitrogen</td><td align="left" valign="bottom">Cat. #C10340</td><td align="left" valign="bottom"/></tr><tr><td align="left" valign="bottom">Other</td><td align="left" valign="bottom">Alcian blue</td><td align="left" valign="bottom">Sigma-Aldrich</td><td align="left" valign="bottom">Cat. #A5268</td><td align="left" valign="bottom">See Materials and Methods, Skeletal analysis</td></tr><tr><td align="left" valign="bottom">Other</td><td align="left" valign="bottom">Alizarin red</td><td align="left" valign="bottom">Sigma-Aldrich</td><td align="left" valign="bottom">Cat. #A5533</td><td align="left" valign="bottom">See Materials and Methods, Skeletal analysis</td></tr><tr><td align="left" valign="bottom">Software, algorithm</td><td align="left" valign="bottom">GraphPad Prism 9</td><td align="left" valign="bottom">GraphPad Software</td><td align="left" valign="bottom"><ext-link ext-link-type="uri" xlink:href="https://www.graphpad.com">https://www.graphpad.com</ext-link></td><td align="left" valign="bottom"/></tr><tr><td align="left" valign="bottom">Software, algorithm</td><td align="left" valign="bottom">Trimmomatic v 0.36</td><td align="left" valign="bottom">GitHub</td><td align="left" valign="bottom"><ext-link ext-link-type="uri" xlink:href="https://github.com/usadellab/Trimmomatic">https://github.com/usadellab/Trimmomatic</ext-link>; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:SCR_011848">SCR_011848</ext-link></td><td align="left" valign="bottom">Version 0.36</td></tr><tr><td align="left" valign="bottom">Software, algorithm</td><td align="left" valign="bottom">Bowtie2-2.3.4.1</td><td align="left" valign="bottom">GitHub</td><td align="left" valign="bottom"><ext-link ext-link-type="uri" xlink:href="https://github.com/BenLangmead/bowtie2">https://github.com/BenLangmead/bowtie2</ext-link>; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:SCR_016368">SCR_016368</ext-link></td><td align="left" valign="bottom">Version 2.3.4.1</td></tr><tr><td align="left" valign="bottom">Software, algorithm</td><td align="left" valign="bottom">Bedtools</td><td align="left" valign="bottom">GitHub</td><td align="left" valign="bottom"><ext-link ext-link-type="uri" xlink:href="https://github.com/arq5x/bedtools2">https://github.com/arq5x/bedtools2</ext-link>; <break/>RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:SCR_00646">SCR_00646</ext-link></td><td align="left" valign="bottom">Version v2.29.1</td></tr><tr><td align="left" valign="bottom">Software, algorithm</td><td align="left" valign="bottom">deeptools</td><td align="left" valign="bottom">GitHub</td><td align="left" valign="bottom"><ext-link ext-link-type="uri" xlink:href="https://github.com/deeptools/deepTools">https://github.com/deeptools/deepTools</ext-link>; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:SCR_016366">SCR_016366</ext-link></td><td align="left" valign="bottom">Version 3.3.0</td></tr><tr><td align="left" valign="bottom">Software, algorithm</td><td align="left" valign="bottom">MACSr</td><td align="left" valign="bottom">GitHub</td><td align="left" valign="bottom"><ext-link ext-link-type="uri" xlink:href="https://github.com/macs3-project/MACSr">https://github.com/macs3-project/MACSr</ext-link>; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:SCR_013291">SCR_013291</ext-link></td><td align="left" valign="bottom">MACS peak calling using R wrapper; Version 1.0.0</td></tr></tbody></table></table-wrap><sec id="s4-1"><title>Animals</title><p>Baylor College of Medicine Institutional Animal Care and Use Committee (IACUC, Protocol AN-1013) approved all mouse care and manipulation. Mice were housed in an AAALAS-certified level 3 facility on a 14 hr light cycle. Sperm from <italic>Gdf11<sup>tm2a(EUCOMM)Hmgu</sup></italic> mice was obtained from the MMRRC (Stock ID: 037721-UCD, RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:MMRRC_037721-UCD">MMRRC_037721-UCD</ext-link>). In vitro fertilization was performed with C57BL/6J donor eggs by the Genetic Engineering Mouse Core at Baylor College of Medicine. <italic>Gdf11<sup>tm2a</sup></italic> mice were maintained on C57BL/6J background. <italic>Gdf11<sup>tm2b</sup></italic> mice were generated by crossing male <italic>Gdf11<sup>tm2a</sup></italic> mice with <italic>Sox2-Cre</italic> female mice obtained from Jackson lab (Stock No: 008454; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:IMSR_JAX:008454">IMSR_JAX:008454</ext-link>). <italic>Gdf11<sup>tm2b</sup></italic> mice were maintained on C57BL/6J background. <italic>MECP2-</italic>TG1 and <italic>Mecp2</italic>-knockout mice were previously described (<xref ref-type="bibr" rid="bib11">Collins et al., 2004</xref>; <xref ref-type="bibr" rid="bib17">Guy et al., 2001</xref>), maintained on a C57BL/6J background, and available from Jackson lab (Stock Nos: 008679; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:IMSR_JAX:008679">IMSR_JAX:008679</ext-link> and 003890; RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:IMSR_JAX:003890">IMSR_JAX:003890</ext-link>). <italic>Gdf11</italic> and <italic>MECP2</italic> double mutant mice were generated by breeding male <italic>Gdf11<sup>tm2b/+</sup></italic> mice to female <italic>MECP2-</italic>TG1 or <italic>Mecp2<sup>+/-</sup></italic> mice. Mice were monitored daily by veterinary staff. Survival age was taken as the age in which a mouse died of natural causes or when a mouse was euthanized due to poor body condition, self-lesioning, or tumor growth according to the institutional veterinarian guidelines. All procedures to maintain and use these mice were approved by the Institutional Animal Care and Use Committee for Baylor College of Medicine and Affiliates.</p></sec><sec id="s4-2"><title>RNA-seq meta-analysis</title><sec id="s4-2-1"><title>Analysis of transcripts correlated with MeCP2 protein levels</title><p>To identify genes that correlate with MeCP2 protein levels, we reanalyzed the transcriptional response of humanized <italic>MECP2</italic> duplication mice treated with an anti-<italic>MECP2</italic> ASO over time (GSE #1512222). The differential gene expression was perform as previously described (<xref ref-type="bibr" rid="bib60">Shao et al., 2021b</xref>), and the log<sub>2</sub> fold-changes of the genes significantly altered between control and <italic>MECP2</italic> duplication mice per time point relative to control were extracted. The log<sub>2</sub> fold-change in MeCP2 protein levels between control-treatment and <italic>MECP2</italic>-ASO treatment for a similar cohort of treated mice was taken from <xref ref-type="fig" rid="fig4">Figure 4C</xref> of that paper. The Spearman correlation was calculated between protein level fold-change and gene expression level fold-change. The probability of loss intolerance (pLI) was extracted from the gnomad data base (<xref ref-type="bibr" rid="bib23">Karczewski et al., 2020</xref>).</p></sec><sec id="s4-2-2"><title>Extraction of gene expression changes from MeCP2 related transcriptional profiles</title><p>To extract the expression of RNA fold-changes for candidate, correlated genes across MeCP2-perturbed, we extracted log<sub>2</sub> fold-change of each transcript (MeCP2 mutant allele / wild-type) and an associated <italic>p</italic><sub>adjusted</sub>. A gene was considered significant if the false-discovery rate was below 0.1. Bulk RNA-sequencing data from MeCP2-perturbed models were preferred but in three unique cases: (1) Single-nuclei data from postmortem RTT tissue (<xref ref-type="bibr" rid="bib50">Renthal et al., 2018</xref>), microarrays from two <italic>MECP2</italic> truncation models that do not have a corresponding RNA-sequencing data set (<xref ref-type="bibr" rid="bib3">Baker et al., 2013</xref>), and bulk nuclei RNA-seq from <italic>MECP2</italic> AAV expressing neurons that do not have a corresponding bulk RNA-sequencing data set (<xref ref-type="bibr" rid="bib19">Ito-Ishida et al., 2020</xref>). Data were extracted from Supplemental Tables or processed files deposited on GEO as possible. The data table from the <italic>MECP2</italic> AAV expressing neurons was taken from the following <ext-link ext-link-type="uri" xlink:href="https://www.jneurosci.org/content/jneuro/40/45/8746/DC1/embed/inline-supplementary-material-1.xlsx?download=true">link</ext-link>. An additional set of data tables were found in the source data from a previous meta-analysis (<xref ref-type="bibr" rid="bib48">Raman et al., 2018</xref>). The remaining data tables were generated by obtaining raw counts from GEO and re-analyzing using DESeq2 between MeCP2 perturbed samples and wild-type samples. A summary of the studies and the sources of data tables are shown in <xref ref-type="supplementary-material" rid="supp1">Supplementary file 1</xref>.</p></sec><sec id="s4-2-3"><title>Cell-type-specific correlation of <italic>Gdf11</italic> and <italic>Mecp2</italic> expression</title><p>To extract the cell-type-specific expression of <italic>Gdf11</italic> and <italic>Mecp2</italic>, we obtained single-cell RNA-sequencing counts and cell-type annotation files from the DropViz database (<ext-link ext-link-type="uri" xlink:href="https://www.dropviz.org">https://www.dropviz.org</ext-link>; <xref ref-type="bibr" rid="bib57">Saunders et al., 2018</xref>). Using the annotation file, we divided the cells into the demarcated categories and performed Spearman correlation between <italic>Gdf11</italic> and <italic>Mecp2</italic>. To calculate neuron subtype specific correlation of <italic>Gdf11</italic> and <italic>Mecp2</italic>, we used <italic>Slc17a7</italic> (<italic>Vglut1</italic>) expression to coarsely separate excitatory and inhibitory neurons. We used a threshold of ≥5 counts per cell type to denote an excitatory neuron. The Spearman correlation was calculated for both excitatory and inhibitory neurons.</p></sec></sec><sec id="s4-3"><title>CUT&amp;RUN epigenetic profiling</title><sec id="s4-3-1"><title>Nuclear isolation</title><p>Nuclei were isolated from frozen 8-week-old hippocampi from <italic>MECP2</italic>-TG1, <italic>Mecp2</italic>-knockout, and wild-type littermates (n<italic>=</italic>3 for <italic>MECP2</italic>-TG1 and <italic>Mecp2</italic>-knockout, n=6 for wild-type) using an iodixanol gradient modified from <xref ref-type="bibr" rid="bib39">Mo et al., 2015</xref>. Briefly, both flash frozen hippocampi per animal were dropped into a 7 mL dounce homogenizer containing 5 mL buffer HB (0.25 M Sucrose, 25 mM KCl, 2 mM Tricine KOH pH 7.8, 500 μM Spermidine) and dounced 10 x with loose pestle A and 20 x with tight pestle B. Then 320 µL of HB-IGEPAL (HB Buffer +5% IGEPAL CA-630) was added to each homogenizer and dounced 20 x more with tight pestle. Each sample was incubated for 10 min on ice and filtered through a 30 µM filter into a conical tube containing 5 mL of iodixanol working solution (5 volumes Optiprep (Sigma Aldrich, D15556)+1 volume Optiprep Diluent (150 mM KCl, 30 mM MgCl<sub>2</sub>, 120 mM Tricine-KOH pH 7.8)) and mixed by tube inversion.</p><p>To set up the gradient, 4 mL of 40% Iodixanol (3 volumes working solution +1 volumes HB buffer) was added to a 50 mL round bottomed conical tube. Then, 7.5 mL 30% Iodixanol (3 volumes working solution +2 volumes HB) was slowly overlayed on top, followed by 10 mL of the sample containing mixture prepared above. This gradient was spun at 10,000 <italic>g</italic> for 20 min at 4 °C in a hanging bucket centrifuge (Sorvall Lynx 6000) with ‘decel’ turned off. After centrifugation, nuclei are located at the interface between 30% and 40% iodixanol layers. Iodixanol containing supernatant above the nuclei was slowly discarded with bulb pipette. Approximately 1.5–2 mL of the interface containing nuclei were collected and placed into 2 mL microcentrifuge tube.</p><p>The number of nuclei were quantified by taking 20 µ of sample and mixing it with 2 µL 0.2 mg/mL DAPI diluted in HB buffer. After three-minute incubation at RT, the nuclei were diluted 1:10 in buffer HB and counted on a Countess II with DAPI channel to quantify.</p></sec><sec id="s4-3-2"><title>CUT&amp;RUN</title><p><underline>C</underline>leavage <underline>U</underline>nder <underline>T</underline>argets &amp; <underline>R</underline>elease <underline>U</underline>sing <underline>N</underline>uclease (CUT&amp;RUN) was performed on nuclei isolated from above following <xref ref-type="bibr" rid="bib10">Coffin et al., 2022</xref>; <xref ref-type="bibr" rid="bib65">Skene and Henikoff, 2017</xref>. Briefly, we performed one nuclear isolation per animal and then split the nuclei into three individual tubes for the three antibodies surveyed (MeCP2, H3K27me3 and IgG). An individual sample will refer to one antibody from a unique animal.</p><p>To activate Concanavalin A coated magnetic beads (Bangs Laboratories Inc, #BP531) for binding, we incubated 25 µL per sample with 3 x volumes binding buffer (20 mM HEPES-NaOH pH 7.5, 10 mM KCl, 1 mM CaCl<sub>2</sub>, 1 mM MnCl<sub>2</sub>), rotated at RT for 5 min, and washed 2 x with 1 mL binding buffer. All washes are done by placing microcentrifuge tube on magnetic rack and waiting until solution is clear as beads separated from the solution. Following washes, the beads were resuspended in 50 µL binding buffer per sample.</p><p>After bead activation, 200 µL beads were added to 1.5x10<sup>6</sup> nuclei in the iodixanol mixture from each animal and rotated for 10 min at room temperature. Following binding of nuclei to beads, all further processing was done on ice. Bead bound nuclei from each animal was washed 2 x with 1.5 mL wash buffer (20 mM HEPES NaOH pH 7.5, 150 mM NaCl, 500 μM Spermidine [Sigma #S0266], and 0.5% Ultrapure BSA [Invitrogen #AM2618] with 1 tablet of Complete Protease Inhibitor Cocktail [Roche #11873580001] per 50 mL). After the second wash, 250 µL of nuclei bound beads (~250,000 nuclei) in wash buffer were added to individual microcentrifuge tubes corresponding to each antibody.</p><p>Supernatant was removed and beads were resuspended in 250 µL of antibody buffer (wash buffer +0.05% Digitonin [Calbiochem #11024-24-1]+2 mM EDTA) containing an individual antibody – rabbit anti-MeCP2 (1:100, Cell Signaling #3456, clone D4F3, RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:AB_2143894">AB_2143894</ext-link>), rabbit anti-Tri-Methyl-Histone H3 (Lys27) [H3K27me3] (1:100, Cell Signaling #9733, clone C36B11. RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:AB_2616029">AB_2616029</ext-link>), and rabbit IgG (1:100, Millipore #12–370, RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:AB_145841">AB_145841</ext-link>). Antibody buffer was added to nuclei bound beads during light vortexing (1100 rpm). Tubes were then placed at 4 °C to rotate overnight. Following rotation, a quick spin on a microcentrifuge was performed to remove liquid from the cap and then washed 2 x with 1 mL Dig-wash buffer (wash buffer +0.05% digitonin). Following the second wash, samples were resuspended in 200 µL dig wash buffer and transferred to PCR strip tubes. Supernatant was removed and beads were resuspended in 100 µL 1 x pAG-MNase (Epicypher #15–1016); 20 x stock pAG-MNase in dig-wash buffer and mixed with gentle flicking. Tubes were placed on nutator for 1 hr at 4 °C. Following incubation, samples were washed with 200 µL dig-wash buffer, transferred to new 1.5 mL microcentrifuge tube, and washed 1 additional time in 1 mL dig-wash buffer.</p><p>To initiate cleavage and release of DNA bound fragments, each sample was resuspended in 150 µL of dig-wash buffer while gently vortexing. Samples were placed on ice in 4 °C room for 10 min to equilibrate. To start digestion, while in 4 °C room, 3 µL of 100 µM CaCl<sub>2</sub> was added to each tube, quickly flicked, and immediately returned to ice. Following 45-min incubation on ice, 150 µL 2 x STOP 340 mM NaCl, 20 mM EDTA, 4 mM EGTA, 0.05% Digitonin, 100 µg/mL RNAse A (ThermoFisher Scientific #EN0531), 50 µg/mL Glycogen (ThermoFisher Scientific #10814010) and 1 ng <italic>E. coli</italic> spike-in / sample (Epicypher #18–1401) mixture was added to each sample. Tubes were then incubated at 37 °C for 30 min to digest RNA and release DNA. <italic>E. coli</italic> spike-in control was used for normalization of CUT&amp;RUN signal due to differences in library amplification and/or sequencing. Supernatant was transferred to new tube and incubated with 1.5 µL 20% SDS and 5 µL 10 mg/mL Proteinase K while lightly shaking at 50 °C for 1 hr. DNA was then purified by phenol-chloroform extraction using Maxtract Tubes (129046, Qiagen) and pellet resuspended in 36.5 µL TE Buffer.</p></sec><sec id="s4-3-3"><title>CUT&amp;RUN next-generation sequencing library preparation</title><p>Library preparation was modified from protocols.IO (<ext-link ext-link-type="uri" xlink:href="https://dx.doi.org/10.17504/protocols.io.bagaibse">dx.doi.org/10.17504/protocols.io.bagaibse</ext-link>) utilizing reagents from the NEB Next II DNA Ultra Kit (New England Biolabs #E7645S) and Unique Combinatorial Dual index kit (New England Biolabs #E6442S,) with modifications outlined below. Input DNA was quantified with Qubit, and 6 ng of CUT&amp;RUN DNA was used as input for the H3K27me3 samples and 25 µL of CUT&amp;RUN DNA was used for both MeCP2 and IgG samples. Volume of DNA was brought up to 25 μL and 1.5 µL End Prep Enzyme Mixture and 3.5 µL Reaction buffer were added and incubated at 20 °C for 30 min and 50 °C for 60 min. After end prep, 15 µL of NEB Next Ultra Ligation Mastermix, 0.5 µL Ligation Enhancer and 1.25 µL of Adapter (1.2 pmol adapter for H3K27me3, 0.6 pmol adapter for MeCP2 and IgG) were added directly to the PCR tube, mixed by pipetting, and incubated for 15 min at 20 °C. Then, 1.5 µL of USER Enzyme is added to each tube. Finally, SPRI select beads (Beckman Coulter # B23318) were used at 1.6 x ratio to remove excess adapter and eluted in 15 µL of TE buffer.</p><p>PCR amplification was performed using 13 µL of adaptor ligated fragments, 1 µL of Unique Combinatorial Dual Index (one index per sample), 1 µL of sterile water, and 15 µL 2 x Q5 Master Mix. Fourteen cycles of PCR were performed with 10 s of denaturation at 98 °C and 10 s of annealing/extension at 65 °C. Following PCR amplification, SPRI select beads were used for two-sided size selection; 0.65 x right sided selection was performed first followed by 1.2 x left sided size selection. Sample was eluted in 15 µL TE.</p><p>For quality control, each library size distribution was determined by Agilent Tapestation HS DNA 1000 (Agilent Technologies #5067) and concentration was determined by KAPA PCR (Roche #07960140001). Libraries were pooled together at equimolar concentrations and submitted to the Baylor Genomic and RNA Profiling Core. Each library was sequenced for approximately 40 million paired end reads of 100 bp in length on a Novaseq S1 flow cells.</p></sec></sec><sec id="s4-4"><title>CUT&amp;RUN analysis</title><sec id="s4-4-1"><title>CUT&amp;RUN sequence alignment</title><p>Our CUT&amp;RUN data analysis pipeline was adapted from CUT&amp;RUN Tools (<xref ref-type="bibr" rid="bib76">Zhu et al., 2019</xref>). Raw Fastq files were appended together using Linux cat function. Adapter sequences were removed from sequence reads using Trimmomatic version 0.36 (2:15:4:4:true LEADING:20 TRAILING:20 SLIDINGWINDOW:4:15 MINLEN:25) from the Truseq3.PE.fa adapter library and kseq (<xref ref-type="bibr" rid="bib5">Bolger et al., 2014</xref>; <xref ref-type="bibr" rid="bib76">Zhu et al., 2019</xref>). Confirmation of adapter removal and read quality was performed with fastqc (v0.11.8). Alignment was performed with bowtie2-2.3.4.1 (<monospace>--dovetail</monospace> <monospace>--phred33</monospace>) to both mm10 (GENCODE GRCm38p6 primary assembly version 18) and the spike-in Ecoli K12 Genomes (GCF_000005845.2_ASM584v2). Bedtools (v2.29.1) was used to process BAM files to BED files, remove blacklist (mm9 blacklist lifted over to mm10 and combined with mm10 blacklist downloaded with CUT&amp;RUNTools) Click or tap here to enter text.and to generate bedgraphs (<xref ref-type="bibr" rid="bib47">Quinlan and Hall, 2010</xref>). Each sample was normalized to internal Ecoli spike-in utilizing spike_in_calibration.sh as described previously (<xref ref-type="bibr" rid="bib38">Meers et al., 2019</xref>). Both spike-in normalized bedgraphs for each sample and merged bedgraphs were converted to bigwigs using UCSC bedgraph to bigwig. Spike-in normalized bigwigs from each genotype were merged using deeptools bigwigCompare and averaged for summary figures.</p></sec><sec id="s4-4-2"><title>MeCP2 Peak Calling</title><p>Peaks were called using the MACSr package (version 1.0.0) using the following parameters: gsize = “mm”, format = “BAMPE”, broad = “TRUE”, keepduplicates = “all”, qvalue = 0.0001 (<xref ref-type="bibr" rid="bib72">Zhang et al., 2008</xref>). Input to the peak calling function callpeak were the six replicates of wild-type MeCP2 BAM files and three replicate <italic>Mecp2</italic>-knockout MeCP2 BAM files as control. Peaks with a q-value less than 0.0001 were retained for further analysis. Peaks were associated with the closest gene using bedtools -closest and mm10 GRCm38 gene coordinates.</p></sec><sec id="s4-4-3"><title>Visualization and Quality Control of CUT&amp;RUN signal</title><p>Integrative Genomics Viewer (IGV) v2.11.1 was used to examine spike-in normalized bigwig tracks at individual loci (<xref ref-type="bibr" rid="bib53">Robinson et al., 2011</xref>). We extracted the integrated density at MeCP2 peaks ±3.5 kb of each filtered peak by using the bedtools function multicov for each BAM file generated (MeCP2, H3K27me3, and IgG). We performed differential binding using the DESeq2 package (version 1.32) using the E-coli spike in control counts as normalization factor and cooksCutoff set to FALSE. DESeq2 was used to perform principal component analysis of each mark individually and then together. Quantification of MeCP2 binding was performed across all samples, pooling two batches of sample collection due to no apparent batch effects by PCA. Quantification of H3K27me3 binding was performed in two batches, with <italic>MECP2</italic>-TG1 and <italic>Mecp2</italic>-knockout samples assessed with their respective wild-type samples within the batch. ChIP-seq measurements of H3K27ac, H3K4me1, and H3K4me3 generated from CA1 hippocampal neurons were obtained from GSE74971 as bigwig files (<xref ref-type="bibr" rid="bib18">Halder et al., 2016</xref>). The naïve, 0 hr measurement from CA1 neurons for each histone mark was evaluated. Replicate bigwig files were merged using deeptools bigwigCompare and averaged for summary figures.</p></sec></sec><sec id="s4-5"><title>RNA extraction, reverse transcription, and qPCR</title><p>Total RNA was isolated from one cerebellar hemisphere using the Qiagen miRNeasy Mini kit (Qiagen #217004). On column DNAse digestion (Qiagen #79254) was performed according to manufacturer’s protocol to remove genomic DNA. Two μg of total RNA was used to synthesized cDNA using the M-MLV reverse transcriptase (Invitrogen #28025013) according to manufacturer’s protocol. qRT-PCR was performed using a CFX96 Real-Time System (Bio-Rad) using PowerUp SYBR Green Master Mix (ThermoFisher #A25741), 0.4 μM forward and reverse primers, and 1:20 dilution of cDNA. The following cycling conditions were used: 95 °C for 5 min, 39 cycles of 95 °C for 11 s, 60 °C for 45 s, plate read, a final melt of 95 °C, and melt curve of 65–95°C at +0.5 °C increments. The specificity of the amplification products was verified using melt-curve analysis. The Ct values were calculated with the Bio-Rad software, and relative gene expression was calculated using the ΔΔCt method using <italic>Ppia</italic> for normalization. All reactions were performed in technical duplicate with a minimum of three biological replicates. Data are presented as mean ± SEM in main figure.</p><sec id="s4-5-1"><title>qPCR primer sequences</title><table-wrap id="inlinetable1" position="anchor"><table frame="hsides" rules="groups"><thead><tr><th align="left" valign="bottom">Primer name</th><th align="left" valign="bottom">Sequence (5’ – 3’)</th></tr></thead><tbody><tr><td align="left" valign="bottom"><italic>Ppia</italic> forward primer</td><td align="left" valign="bottom"><named-content content-type="sequence">GCATACAGGTCCTGGCATCT</named-content></td></tr><tr><td align="left" valign="bottom"><italic>Ppia</italic> reverse primer</td><td align="left" valign="bottom"><named-content content-type="sequence">CCATCCAGCCATTCAGTCTT</named-content></td></tr><tr><td align="left" valign="bottom"><italic>Gdf11</italic> forward primer</td><td align="left" valign="bottom"><named-content content-type="sequence">CTACCACCGAGACGGTCATAA</named-content></td></tr><tr><td align="left" valign="bottom"><italic>Gdf11</italic> reverse primer</td><td align="left" valign="bottom"><named-content content-type="sequence">CCGAAGGTACACCCACAGTT</named-content></td></tr><tr><td align="left" valign="bottom"><italic>Mecp2</italic> forward primer</td><td align="left" valign="bottom"><named-content content-type="sequence">TATTTGATCAATCCCCAGGG</named-content></td></tr><tr><td align="left" valign="bottom"><italic>Mecp2</italic> reverse primer</td><td align="left" valign="bottom"><named-content content-type="sequence">CTCCCTCTCCCAGTTACCGT</named-content></td></tr><tr><td align="left" valign="bottom"><italic>LacZ</italic> forward primer</td><td align="left" valign="bottom"><named-content content-type="sequence">ACTATCCCGACCGCCTTACT</named-content></td></tr><tr><td align="left" valign="bottom"><italic>LacZ</italic> reverse primer</td><td align="left" valign="bottom"><named-content content-type="sequence">TAGCGGCTGATGTTGAACTG</named-content></td></tr></tbody></table></table-wrap></sec></sec><sec id="s4-6"><title>Behavioral assays</title><p>All behavioral assays were performed during the light period. Mice were habituated to the test room for at least 30 min before each test. Mice were given at least one day to recover between different assays. All testing, data acquisition, and analyses were carried out by an individual blinded to the genotype. The order of assays is described in <xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1</xref> and <xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2</xref> beginning at approximately 16 weeks of age. The cohort details for each group of experiments are listed: (1) for <italic>MECP2-</italic>TG1; <italic>Gdf11<sup>tm2b/+</sup></italic> versus wild-type and <italic>MECP2</italic>-TG1: n=30 wild-type mice (19 male, 11 female); n=26 <italic>MECP2</italic>-TG1 mice (14 male, 12 female); and n=22 <italic>MECP2</italic>-TG1<italic>; Gdf11<sup>tm2b/+</sup></italic> mice (16 male, 6 female); and for fear conditioning assay (C), n=17 wild-type mice (9 male, 8 female); n=25 <italic>MECP2</italic>-TG1 mice (13 male, 12 female); and n=22 <italic>MECP2</italic>-TG1<italic>; Gdf11<sup>tm2b/+</sup></italic> mice (16 male, 6 female) for (2) <italic>Gdf11<sup>tm2b/+</sup></italic> versus wild type: n=29 wild-type mice (15 male, 14 female) and n=34 <italic>Gdf11<sup>tm2b/+</sup></italic> mice (16 male, 18 female); and for fear conditioning assay, n=28 wild-type mice (16 male, 12 female) and n=24 <italic>Gdf11<sup>tm2b/+</sup></italic> mice (9 male, 15 female). Outlier analysis was not performed on the data points, and no data points were removed from any assays.</p></sec><sec id="s4-7"><title>Elevated plus maze</title><p>The lighting in the test room was set to 750 lux, and the background noise level was set to 62 dB with a white noise generator. After habituation, the mice were placed in the center zone of a plus maze that has two open arms. The mice were placed facing one of the open arms and allowed to freely move for 10 min. The movement of the mice was tracked with the ANY-maze software system (Stoelting Inc). The total distance and distance traveled per zone, time spent in each arm zone, distance traveled in each arm zone, and number of zone crossings were recorded and tabulated by the software.</p></sec><sec id="s4-8"><title>Open-field assay</title><p>The lighting in the test room was set to 150 lux, and the background noise level was set to 62 dB with a white noise generator. After habituation, mice were placed in an open plexiglass area (40x40 x 30 cm), and their movement and behavior were tracked by laser photobeam breaks. Mice were allowed to freely move for 30 min. The total distance traveled, horizontal or vertical laser beam breaks (activity counts), entries into the center 10x10 cm, and time in the center 10x10 cm were recorded and tabulated by the AccuScan Fusion software (Omnitech Electronics Inc).</p></sec><sec id="s4-9"><title>Light-dark box assay</title><p>The lighting in the test room was set to 150 lux, and the background noise level was set to 62 dB with a white noise generator. After habituation, mice were placed in an plexiglass arena with an open zone (36x20 x 26 cm) and a closed, dark zone made of black plastic (15.5 x. 20x26 cm) with a 10.5 x. 5 cm opening. Mice were allowed to freely move for 10 min. The movement of the mice was tracked by laser photobeam breaks. The total and zone-specific distance traveled, the total or zone-specific horizontal or vertical laser beam breaks (activity counts), entries into the dark zone, and time spent in either zone were recorded and tabulated by the AccuScan Fusion software (Omnitech Electronics Inc).</p></sec><sec id="s4-10"><title>Three-chamber assay</title><p>The lighting in the test room was set to 150 lux, and the background noise level was set to 62 dB with a white noise generator. Age and sex matched C57BL/6J mice were used as novel partner mice, which were housed together and had no overtly aggressive behaviors observed. Two days before the test, the novel partner mice were habituated to the wire cups (3-inch diameter by 4-inch height) for 1 hr/day for 2 days. After habituation, the test mice were placed in a clear plexiglass chamber (24.75x16.75 x 8.75 inch) with two removable partitioned that divide the chamber into three zones. Empty wire cups were placed in the left and right chambers. For the acclimation phase, the mice were placed into the center zone and the partitions removed. The mice were allowed to freely explore the apparatus for 10 min. For the socialization phase, a novel partner mouse was randomly placed into the left or right wire cup. An inanimate object as control was plaed in the wire cup of the opposing chamber. The mice were allowed to explore the apparatus again for 10 minutes. The total distance traveled was tracked by the ANY-maze software system (Stoelting Inc). For all phases, the total amount of time the mice spent rearing, sniffing, or pawing the cup was recorded manually.</p></sec><sec id="s4-11"><title>Rotating rod</title><p>The lighting in the test room was at ambient levels, and the background noise level was set to 62 dB with a white noise generator. After habituation, mice were placed on an accelerating rotarod apparatus (Ugo Basile). The rod accelerated from 4 to 40 r.p.m. for 5 min. For cohorts containing the <italic>MECP2</italic>-TG1 allele (<xref ref-type="fig" rid="fig2">Figure 2</xref> and <xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1</xref>), the maximum trial length was 10 min in concordance with previous studies performing the rotarod assay in <italic>MECP2</italic>-TG1 mice and the observation that <italic>MECP2</italic>-TG1 mice perform above wild-type mice on this assay (<xref ref-type="bibr" rid="bib11">Collins et al., 2004</xref>); for all other testing, the maximum trial length was 5 min as a standard starting assay length for an uncharacterized mouse line. Mice were tested four trials each day, with an interval of at least 30 min between trials, for four consecutive days. The time it took for each mouse to fall from the rod (i.e. latency to fall) was recorded.</p></sec><sec id="s4-12"><title>Fear conditioning</title><p>Animals were habituated in an adjacent room to the testing room with a light level of 150 lux and noise level of 62 dB using a white noise generator. On the training day, mice were brought to the testing groom (ambient light, no noise) and placed into a chamber containing a grid floor that can deliver an electric shock with one mouse per chamber (Med Associates Inc). The chamber was housed within a sound-attenuating box with a digital camera, loudspeaker, and a light. The training paradigm consisted of 2 min of no noise or shock, then a tone for 30 s (5 kHz, 85 dB), ending with a foot shock for 2 s (1 mA). The tone and shock pairing was repeated after 2 min of no noise or shock. The mice were returned to their home cages after training. On the testing day, occurring 24 hr later, two tests are performed – context and cued learning. For the context test, the mice were placed in the exact same chamber with no noise or shock for 5 min. After 1-hr post-context test, the cued learning test was performed. For the cued learning test, the mice were placed in a novel environment for 6 min. The first 3 min with no noise or shock, and the last 3 min with tone only (5 kHz, 85 dB). Movement was recorded on video and freezing, as defined by absence of all movement except respiration, was quantified using the FreezeFrame software (ActiMetrics) using a bout duration of 1 s and movement threshold of 10.</p></sec><sec id="s4-13"><title>Histology and staining assays</title><sec id="s4-13-1"><title>Cresyl violet staining</title><p>Brains from 16-week-old mice were dissected and freshly embedded and frozen in OCT. Sagittal slices were made with frozen tissues and dehydrated in 95% and 100% ethanol washes (3x2 min). Slides were washed with 1:1 chloroform:100% ethanol for 20 min to strip lipids. Slides were rehydrated with 95% to 70% ethanol to distilled water gradients (2 min each). Then stain Cresyl-violet 5 min (Solution of 0.2% Cresyl Violet: 0.1 g Cresyl Violet; 100 mL ddH2O; 0.3 mL glacial acetic acid; 0.0205 g sodium acetate; pH 3.5). Then dehydrate slides in alcohol gradients (75%–95%−100%–100%) to xylene (2 mins each). Finally, the slides were mounted using Cytoseal 60 (VWR). The images were scanned with Zeiss Axio Scan.Z1 at 20 x.</p></sec><sec id="s4-13-2"><title>Brain tissue fixation and sectioning</title><p>We used design-based stereology protocol for fixing, sectioning, and quantifying proliferation markers in the subgranular zone of the dentate gyrus (<xref ref-type="bibr" rid="bib74">Zhao and Praag, 2020</xref>). Adult, 16-week-old mice (n=5 for <italic>Gdf11<sup>tm2b/+</sup></italic> and <italic>n</italic>=3 for wild-type littermate controls) were given a subcutaneous injection of analgesia (Buprenorphine, 0.5 mg/kg) 30 min prior to anesthesia (Rodent Combo III, 1.5 mL/kg) via intraperitoneal injection. Mice were perfused with ice-cold PBS followed by 4% PFA. Brains were removed and placed in 4% PFA overnight. Brain samples were then washed with ice-cold PBS, incubated in 15% sucrose in PBS overnight, and stored in 30% sucrose in PBS with 0.01% sodium azide. Experimenter was blind to genotype throughout the sectioning, imaging, and quantification process. Serial sections of the left hemisphere along the sagittal plane at 40 μm thickness were cut on a Leica SM2010 R sliding microtome and free-floating serial sections were stored in PBS +0.01% sodium azide at 4 °C.</p></sec><sec id="s4-13-3"><title>EdU and immunofluorescent staining</title><p>Mice were injected with 10 mg/kg of 5-ethynyl-2’-deoxyuridine (EdU; Invitrogen #E10187) by intraperitoneal injection for 5 consecutive days. Brains were perfused and sectioned as described above 2 days after the final injection. The Click-iT EdU Imaging Kit with AlexaFluor 647 dye (Invitrogen #C10340) was used to detect EdU in sections following manufactures protocol. Free-floating sections were stained with mouse anti-GFAP (Sigma #G3893, RRID:<ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:AB_477010">AB_477010</ext-link>, 1:1000 dilution) and rabbit anti-SOX2 (Abcam #ab97959, RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:AB_2341193">AB_2341193</ext-link>, 1:500 dilution) before or after EdU Click-it reaction. Sections were washed with PBS (3 X) and incubated in permeabilization buffer (0.3% Triton-X-100 in PBS) for 5 min at room temperature. Sections were placed in blocking buffer (0.3% Triton-X, 3% normal donkey serum) for 30 min at room temperature and then incubated with primary antibodies with 1% BSA in blocking buffer overnight, rocking at 4 °C. Sections were washed with PBS (3 X) then incubated with secondary antibodies at 1:1000 dilutions (donkey anti-rabbit Alexa 488; Jackson ImmunoResearch #711-545-152, RRID:<ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:AB_2313584">AB_2313584</ext-link> and donkey anti-mouse Alexa 555; Thermo Scientific #A-31570, RRID: <ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID/RRID:AB_2536180">AB_2536180</ext-link>) in blocking buffer with 1% BSA for 1 hr at room temperature. After final washes with PBS, sections were mounted onto slides and coverslips were placed using Prolong Diamond with DAPI mounting media (Invitrogen #P36966). Slides were allowed to dry overnight.</p></sec><sec id="s4-13-4"><title>Imaging and stereology quantification</title><p>Stained sections were imaged on a Leica SP8X confocal microscope. Z-stack images of the entire dentate gyrus were imaged to quantify absolute numbers of EdU<sup>+</sup>, GFAP<sup>+</sup>, and SOX2<sup>+</sup> cells per section. Images were analyzed in LAS X software to measure the area and thickness of each section (t). Image J software was used to count EdU<sup>+</sup>, SOX2<sup>+</sup>, and GFAP<sup>+</sup> cells (Q) following a standardized quantification method (<xref ref-type="bibr" rid="bib74">Zhao and Praag, 2020</xref>). Briefly, the section sampling interval (ssf) was 1/6 for EdU and GFAP and 1/10 for SOX2 quantification. The area sampling fraction (asf)=1, and h = 40. The following equation was used to calculate the total cell number per animal (<xref ref-type="bibr" rid="bib74">Zhao and Praag, 2020</xref>): <inline-formula><mml:math id="inf1"><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mrow><mml:mi>N</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:mo>[</mml:mo><mml:mrow><mml:mo>∑</mml:mo><mml:mrow><mml:mi>Q</mml:mi></mml:mrow><mml:mo>⋅</mml:mo><mml:mfrac><mml:mi>t</mml:mi><mml:mi>h</mml:mi></mml:mfrac><mml:mo>⋅</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mrow><mml:mi>a</mml:mi><mml:mi>s</mml:mi><mml:mi>f</mml:mi></mml:mrow></mml:mfrac><mml:mo>⋅</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mrow><mml:mi>s</mml:mi><mml:mi>s</mml:mi><mml:mi>f</mml:mi></mml:mrow></mml:mfrac></mml:mrow><mml:mo>]</mml:mo></mml:mrow><mml:mo>⋅</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:mstyle></mml:math></inline-formula>.</p></sec><sec id="s4-13-5"><title>Skeletal analysis</title><p>Newborn P0 pups were euthanized, and skeletal preparations were performed exactly as previously described (<xref ref-type="bibr" rid="bib52">Rigueur and Lyons, 2014</xref>). Briefly, skin and soft tissues were removed, pups were fixed in 95% ethanol at room temperature overnight, lipids cleared with acetone at room temperature overnight, stained with 0.03% Alcian blue (Sigma #A5268) in 20% glacial acetic acid and 80% ethanol at room temperature overnight, washed 2 x with 70% ethanol and stored in 95% ethanol overnight, pre-cleared with 1% KOH for one hour at room temperature, stained with 0.005% Alizarin red (Sigma #A5533) in 1% KOH for four hours at room temperature, washed in 50% glycerol:50%–1% KOH for 3–4 days at 4 °C, and stored in 100% glycerol until imaged on stereomicroscope. Excess tissues were trimmed before counting attached and total rib segments.</p></sec><sec id="s4-13-6"><title>Statistical analysis</title><p>Experimental analyses were performed in a blinded manner when possible. Statistical tests were performed in accordance with the experimental design. Data normality for behavioral data was assessed using the Kolmogorov-Smirnov test and the Shapiro-Wilk test for the immunofluorescence quantification. Outliers were not assessed nor removed. Single comparisons used Student’s t-test, whereas multi-group comparisons used one- or two-way ANOVAs as appropriate. The specific test used in each experiment is indicated in the figure legend. In each case, *, **, ***, ****, and n.s. denote <italic>p</italic>&lt;0.05, <italic>p</italic>&lt;0.01, <italic>p</italic>&lt;0.001, <italic>p</italic>&lt;0.0001, and <italic>p</italic>&gt;0.05, respectively.</p></sec></sec><sec id="s4-14"><title>Resource availability</title><sec id="s4-14-1"><title>Materials availability</title><p>Mouse lines used in this study are available through Jackson Labs (<italic>MECP2</italic>-TG1, Jackson lab stock: 008679; <italic>Mecp2</italic>-knockout, Jackson lab stock: 003890; or MMRRC, Stock ID: 037721).</p></sec></sec></sec></body><back><sec sec-type="additional-information" id="s5"><title>Additional information</title><fn-group content-type="competing-interest"><title>Competing interests</title><fn fn-type="COI-statement" id="conf1"><p>No competing interests declared</p></fn><fn fn-type="COI-statement" id="conf2"><p>No competing interests declared</p></fn></fn-group><fn-group content-type="author-contribution"><title>Author contributions</title><fn fn-type="con" id="con1"><p>Conceptualization, Data curation, Software, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft</p></fn><fn fn-type="con" id="con2"><p>Data curation, Formal analysis, Methodology, Writing – review and editing</p></fn><fn fn-type="con" id="con3"><p>Data curation, Investigation, Writing – review and editing</p></fn><fn fn-type="con" id="con4"><p>Software, Formal analysis</p></fn><fn fn-type="con" id="con5"><p>Data curation, Software</p></fn><fn fn-type="con" id="con6"><p>Data curation, Software, Methodology</p></fn><fn fn-type="con" id="con7"><p>Resources, Supervision</p></fn><fn fn-type="con" id="con8"><p>Conceptualization, Resources, Supervision, Funding acquisition, Project administration, Writing – review and editing, Data review</p></fn></fn-group><fn-group content-type="ethics-information"><title>Ethics</title><fn fn-type="other"><p>This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#AN-1013) of the Baylor College of Medicine.</p></fn></fn-group></sec><sec sec-type="supplementary-material" id="s6"><title>Additional files</title><supplementary-material id="supp1"><label>Supplementary file 1.</label><caption><title>Summary and source of transcriptomics studies mined in this study.</title></caption><media xlink:href="elife-83806-supp1-v1.docx" mimetype="application" mime-subtype="docx"/></supplementary-material><supplementary-material id="mdar"><label>MDAR checklist</label><media xlink:href="elife-83806-mdarchecklist1-v1.docx" mimetype="application" mime-subtype="docx"/></supplementary-material></sec><sec sec-type="data-availability" id="s7"><title>Data availability</title><p>CUT&amp;RUN data have been deposited in GEO under accession code GSE213752. This paper does not report original code. Raw data from behavioral analyses are provided in <xref ref-type="supplementary-material" rid="fig2sdata1">Figure 2—source data 1</xref> and <xref ref-type="supplementary-material" rid="fig3sdata1">Figure 3—source data 1</xref>, and raw quantification from immunofluorescence stereology quantification are provided in <xref ref-type="supplementary-material" rid="fig4sdata1">Figure 4—source data 1</xref>. 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xlink:href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE151222">GSE151222</pub-id></element-citation></p></sec><ack id="ack"><title>Acknowledgements</title><p>We thank Dr. Dah-eun Chloe Chung, Cole Deisseroth, and Yan Li for critical comments of this manuscript. We further thank the Baylor College of Medicine (BCM) Genome and RNA Profiling Core and the Jan and Dan Duncan Neurological Research Institute (NRI) RNA In Situ Hybridization Core, Microscopy Core, and Animal Behavior Core. This work was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) (F32HD100048 to SSB, P50HD103555 to Microscopy core, U54HD083092 to RNA In Situ Hybridization and Animal Behavior cores), Howard Hughes Medical Institute (HYZ), National Institute of Neurological Disorders and Stroke (NINDS) (R01NS057819 to HYZ, F32NS122920 to AGA), NRI Zoghbi Scholar Award through Texas Children’s Hospital (JZ and SSB). 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pub-id-type="doi">10.1186/s13059-019-1802-4</pub-id></element-citation></ref></ref-list></back><sub-article article-type="editor-report" id="sa0"><front-stub><article-id pub-id-type="doi">10.7554/eLife.83806.sa0</article-id><title-group><article-title>Editor's evaluation</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Gleeson</surname><given-names>Joseph G</given-names></name><role specific-use="editor">Reviewing Editor</role><aff><institution-wrap><institution-id institution-id-type="ror">https://ror.org/0168r3w48</institution-id><institution>University of California, San Diego</institution></institution-wrap><country>United States</country></aff></contrib></contrib-group><related-object id="sa0ro1" object-id-type="id" object-id="10.1101/2022.10.05.510925" link-type="continued-by" xlink:href="https://sciety.org/articles/activity/10.1101/2022.10.05.510925"/></front-stub><body><p>The <italic>MECP2</italic> gene, mutated in Rett syndrome, has been challenging to ascribe clear function, despite a clear effect binding methylated chromatin. Here the authors demonstrate one of the first clear examples of MeCP2 regulating a target gene. MeCP2 epigenetically regulates <italic>Gdf11</italic> through histone methylation of a nearby enhancer. The strength of the data lies in the direct effects observed between MeCP2 and <italic>Gdf11</italic>, in vivo documentation of the importance of this relationship, and the results will be of interest to researchers in epigenetics, chromatin biology, neurodevelopmental disorders, and aging.</p></body></sub-article><sub-article article-type="decision-letter" id="sa1"><front-stub><article-id pub-id-type="doi">10.7554/eLife.83806.sa1</article-id><title-group><article-title>Decision letter</article-title></title-group><contrib-group content-type="section"><contrib contrib-type="editor"><name><surname>Gleeson</surname><given-names>Joseph G</given-names></name><role>Reviewing Editor</role><aff><institution-wrap><institution-id institution-id-type="ror">https://ror.org/0168r3w48</institution-id><institution>University of California, San Diego</institution></institution-wrap><country>United States</country></aff></contrib></contrib-group></front-stub><body><boxed-text id="sa2-box1"><p>Our editorial process produces two outputs: (i) <ext-link ext-link-type="uri" xlink:href="https://sciety.org/articles/activity/10.1101/2022.10.05.510925">public reviews</ext-link> designed to be posted alongside <ext-link ext-link-type="uri" xlink:href="https://www.biorxiv.org/content/10.1101/2022.10.05.510925v1">the preprint</ext-link> for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.</p></boxed-text><p><bold>Decision letter after peer review:</bold></p><p>Thank you for submitting your article &quot;MeCP2 regulates <italic>Gdf11</italic>, a dosage-sensitive gene critical for neurological function&quot; for consideration by <italic>eLife</italic>. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by Joseph Gleeson as the Reviewing Editor and Catherine Dulac as the Senior Editor. The reviewers have opted to remain anonymous.</p><p>The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.</p><p>Essential revisions:</p><p>1) As Mecp2 is generally a transcriptional repressor, Reviewer 2 wonders how Mecp2 binding to Gdf11 TSS increase its expression. Please provide an explanation in the text or clarify experimentally as requested.</p><p>2) As Mecp2 and Gdf11 often have opposite effects on behavioral traits, raised by Reviewer 3, please provide an explanation for how to distinguish between pseudonormalization and a direct cause-and-effect relationship.</p><p><italic>Reviewer #1 (Recommendations for the authors):</italic></p><p>– It is important to understand and report to what extent skeletal phenotypes in Gdf11tm2b/+ mice are affecting behavioral outcomes, for example the reduced latency to fall in accelerating rotarod or other motor tasks. I would recommend the authors to examine skeletal phenotypes in Gdf11tm2b/+ based on those observed by McPherron et al. (1999).</p><p>– As hinted to in the section above, do MECP2-TG1;Gdf11tm2b/+ mice show changes in longevity compared to MECP2-TG1 mice?</p><p>– As indicated above, it would be helpful to have the open field data of the MECP2-TG1;Gdf11tm2b/- mice also indicated as ratio of the distance in the center vs. total traveled to allow comparisons with the measures reported in Collins (2004), as well as the ratio of the time spent in the center to classically assess thigmotaxis.</p><p>– As outlined in the section above, I am unclear about why freezing behavior declines after the second tone in fear conditioning learning, and how the observations of changes in learning reflect on the interpretation of context-dependent and cue-dependent memory recall. Also, is the cumulative freezing behavior shown driven by the initial recall of memory or persists over the 5 minutes in contextual testing or 3 minutes post-tone in cue testing? Please provide the plots as a function of time.</p><p>– The cell specificity of Mecp2 and Gdf11 interplay seems an important area of exploration. Using single-cell RNA sequencing studies from neurotypical brains, the authors could try to map the correlation between Mecp2 and Gdf11 expression by cell type to begin understanding if this is a universal mechanism or has cell specificity.</p><p>– Please investigate normality for all data and use tests for not normally distributed data whenever necessary. Also indicate if outliers have been examined and, if so, treated.</p><p>– The discussion of Gdf11 in the Introduction is limited to one sentence, and critical information on this gene and its involvement in neurological manifestations are scattered in the results and Discussion section. I recommend the authors to provide a more robust introduction on Gdf11, including molecular functions, known function in brain (e.g., neurogenesis) and association to disease. For example, the fact that Gdf11 is a secreted factor would be critical throughout the reading of the Results section and appears only at the end of the discussion.</p><p>– It would be helpful to number the studies listed in Table S1 and then add this numerical reference to the legends of Figure 1B and S1B-D. Also, in the legends of Figure 1B and S1B-D, please spell out the acronyms used on the top of the plots.</p><p>– I am not clear why the qPCR experiments were performed in cerebellum, while the rest of the paper focuses on the hippocampus. Please provide a rationale.</p><p>– The discussion about Gdf11 as a biomarker and target of modulation by neutralizing antibody is important. In this context, it would be important to discuss that Gdf11 is expressed in blood and the potential for systemic modulation of Gdf11.</p><p>– In the methods of the three-chamber assay, please specify if age- and sex-matched target mice have been inspected for aggressive behaviors prior to testing.</p><p>– In Figure S2F, the statistical comparisons conducted might mislead the reader. The appropriate comparisons is between time investigating partner vs time investigating cup within each genotype, and the general interpretation that all genotypes have intact sociability. This same plot is missing for the Gdf11tm2b/+ line (only preference index shown in Figure S3H) and should be shown.</p><p>– Also, in the acclimation phase, there seems to be a preference for the left chamber (statistically significant in Figure S2E and trending in Figure S3G). Why?</p><p>– Line 75. Please add a reference to Shao et al. (2021).</p><p>– Lines 109-110. I recommend removing the word &quot;strong&quot;. &quot;Demonstrate&quot; is sufficient.</p><p>– Line 905 (Figure S1 legend). Please add a reference to Shao et al. (2021).</p><p>– Lines 123-124. The sentence seems redundant. I would suggest just keeping &quot;completely absent&quot;.</p><p>– Line 150. Replace &quot;sans&quot; with &quot;without&quot;.</p><p>– Line 216. By &quot;amplifying progenitors&quot;, do you mean proliferating progenitors?</p><p>– Lines 236-237. Please rephrase. Sentences are redundant.</p><p>– Line 496. Please replace gender with sex.</p><p>– Line 510-511. Please, explain the difference in maximum trial length across cohorts.</p><p>– Figure S1C. Please, replace the Y axis label with &quot;Relative RNA levels&quot;.</p><p>– Please, clarify that &quot;Rett syndrome neurons&quot; indicated neurons isolated from postmortem brains of individuals with Rett syndrome.</p><p><italic>Reviewer #2 (Recommendations for the authors):</italic></p><p>Overall, the conclusions are well supported by the experiments and elegant genetic methods are used to demonstrate the Mecp2-mediated transcriptional regulation of gdf11. However, the mechanism by which Mecp2 increases Gdf11 is not clear. The loss of Mecp2 increases H3K27me3, which shows how Gdf11 will be downregulated in Mecp2 knockout mice. But Mecp2 is generally a transcriptional repressor, and it is not clear how Mecp2 binding to Gdf11 TSS will increase its expression. Additional experiments may help understand the mechanism of Mecp2-mediated regulates Gdf11 levels.</p><p><italic>Reviewer #3 (Recommendations for the authors):</italic></p><p>1. Please provide information for the animal experiments regarding the composition of the cohorts of animals used, and the timing, order, and ages of when behavioral experiments were conducted.</p><p>2. Discussion of the points raised in weakness #2 should be included in the manuscript, with consideration of experiments that would directly link to correction not just of behavioral abnormalities but also to underlying neural circuit, cellular, and molecular changes that underlie the observed behavioral changes in order to provide evidence of convergence related to correction of pathophysiology.</p><p>3. I think that weakness #3 could be easily addressed by providing raw data in some accessible format and is an important demonstration of commitment to scientific transparency, regardless of specific journal requirements.</p></body></sub-article><sub-article article-type="reply" id="sa2"><front-stub><article-id pub-id-type="doi">10.7554/eLife.83806.sa2</article-id><title-group><article-title>Author response</article-title></title-group></front-stub><body><disp-quote content-type="editor-comment"><p>Essential revisions:</p><p>1) As Mecp2 is generally a transcriptional repressor, Reviewer 2 wonders how Mecp2 binding to Gdf11 TSS increase its expression. Please provide an explanation in the text or clarify experimentally as requested.</p></disp-quote><p>To further define the peak of MeCP2 binding upstream of <italic>Gdf11</italic>, we mined previously generated ChIP-seq data of three histone modifications: H3K27ac, H3K4me1, and H3K4me3, that mark open chromatin, putative enhancers, and the transcriptional start site, respectively. We found that the MeCP2 peak co-occurs with an H3K27ac and H3K4me1 positive region , suggesting MeCP2 regulates a putative enhancer of <italic>Gdf11</italic>. Upon its loss, this enhancer region has an increase of H3K27me3 and leads to the down-regulation of <italic>Gdf11.</italic> These data are included in Figure 1—figure supplement 2D.</p><disp-quote content-type="editor-comment"><p>2) As Mecp2 and Gdf11 often have opposite effects on behavioral traits, raised by Reviewer 3, please provide an explanation for how to distinguish between pseudonormalization and a direct cause-and-effect relationship.</p></disp-quote><p>We have added a section to discuss these considerations in the Discussion. This is a challenging point that arises when studying the interaction of two dosage-sensitive genes. Even within one dosage sensitive gene, like <italic>MECP2</italic>, we observe opposing effects when its dosage is modulated by <sub>­</sub>± 30% (Shao et al., 2021). Thus, when considering the interaction of two dosage-sensitive genes, it is challenging to parse apart their additive and mechanistic relationships (Zhou et al., 2022). Because not all phenotypes are rescued in the double mutants (like rotarod), and <italic>Gdf11</italic> is one of a handful of genes rescued in <italic>MECP2</italic> duplication mice after antisense oligonucleotide treatment, we propose the effect is direct rather than through pseudonormalization.</p><disp-quote content-type="editor-comment"><p>Reviewer #1 (Recommendations for the authors):</p><p>– It is important to understand and report to what extent skeletal phenotypes in Gdf11tm2b/+ mice are affecting behavioral outcomes, for example the reduced latency to fall in accelerating rotarod or other motor tasks. I would recommend the authors to examine skeletal phenotypes in Gdf11tm2b/+ based on those observed by McPherron et al. (1999).</p></disp-quote><p>We thank the reviewer for this important suggestion and we have performed skeletal staining in P0 pups as previously described. We found that the <italic>Gdf11 <sup>tm2b/+</sup></italic> and <italic>Gdf11 <sup>tm2b/tm2b</sup></italic> pups recapitulate the vertebral patterning deficits of <italic>Gdf11<sup>+/-</sup></italic> and <italic>Gdf11<sup>-/-</sup></italic> pups as described in the first <italic>Gdf11</italic>-knockout study (McPherron et al., 1999). <italic>Gdf11 <sup>tm2b/+</sup></italic> heterozygous mice exhibit 8 attached ribs and 14 total ribs, while the knockout mice exhibited 10 attached ribs and 18 total ribs. Interestingly, we did observe that <italic>MECP2</italic>-TG1; <italic>Gdf11 <sup>tm2b/+</sup></italic> pups also displayed the same skeletal defects as <italic>Gdf11 <sup>tm2b/+</sup></italic> pups alone, suggesting that this skeletal patterning program is not altered by MeCP2 dosage. These data are included in Figure 3—figure supplement 1C. Because these double mutant mice do not have a reduced latency on the rotarod, we conclude that at least the rotarod is not influenced by changes in skeletal structure. We have also added these considerations to the Discussion section to account for phenotypes that may be influenced like locomotion. Future work will need to use conditional genetics to separate any potential specific role for skeletal abnormalities influencing behavior.</p><disp-quote content-type="editor-comment"><p>– As hinted to in the section above, do MECP2-TG1;Gdf11tm2b/+ mice show changes in longevity compared to MECP2-TG1 mice?</p></disp-quote><p>Unfortunately, the reduced survival phenotype of <italic>MECP2-TG1</italic> mice was observed on an FVB/N background. We have not observed a robust survival deficit on C57BL6/J background (used in this study) or in F1 hybrids (C57BL6/J x FVB/N) and were unable to assess survival of <italic>MECP2-TG1</italic>; <italic>Gdf11<sup>tm2b/+</sup></italic> mice. Anecdotally, we have not observed any premature deaths in either <italic>MECP2-TG1</italic> or <italic>MECP2-TG1</italic>; <italic>Gdf11<sup>tm2b/+</sup></italic> mice at the time of behavioral assessment (4 months) and up to 1 year; however, we do not have the longevity nor the sample size to conclusively state there is no changes in survival and have not included these data in the manuscript. This is a great experiment to include in a dedicated follow up study</p><disp-quote content-type="editor-comment"><p>– As indicated above, it would be helpful to have the open field data of the MECP2-TG1;Gdf11tm2b/- mice also indicated as ratio of the distance in the center vs. total traveled to allow comparisons with the measures reported in Collins (2004), as well as the ratio of the time spent in the center to classically assess thigmotaxis.</p></disp-quote><p>We have included the ratio of the distance traveled and time in the center of the total for both behavioral cohort assessments. These data are included in Figure 2—figure supplement 1B and Figure 3—figure supplement 2C.</p><disp-quote content-type="editor-comment"><p>– As outlined in the section above, I am unclear about why freezing behavior declines after the second tone in fear conditioning learning, and how the observations of changes in learning reflect on the interpretation of context-dependent and cue-dependent memory recall. Also, is the cumulative freezing behavior shown driven by the initial recall of memory or persists over the 5 minutes in contextual testing or 3 minutes post-tone in cue testing? Please provide the plots as a function of time.</p></disp-quote><p>Due to the short time frame of the test, and the variability of freezing on a per-bin basis, we have found the most reliable assessment of assay performance by aggregating the results for the entire segment of the test. Because of this, and to keep in concordance with previous reports of conditioned fear both in and amongst labs, we have chosen to keep our displays of the data as a function of bin rather than time. We also do not have an obvious explanation for the changes in freezing, but these results warrant future follow up. The decrease in freezing in <italic>Gdf11<sup>tm2b/+</sup></italic>mice after the second tone may be due to a diminished short-term memory or more complicated multi-system deficits we have yet to characterize. We have softened the interpretation of these results in the Discussion section.</p><disp-quote content-type="editor-comment"><p>– The cell specificity of Mecp2 and Gdf11 interplay seems an important area of exploration. Using single-cell RNA sequencing studies from neurotypical brains, the authors could try to map the correlation between Mecp2 and Gdf11 expression by cell type to begin understanding if this is a universal mechanism or has cell specificity.</p></disp-quote><p>We have mined single-cell sequencing data from the normal mouse brain (Saunders et al., 2018) and mapped three cell population correlations between <italic>Gdf11</italic> and <italic>Mecp2</italic>: first, broadly across all cell types; second, within each of the thirteen major cell types identified; and third, dividing the neuronal population into excitatory and inhibitory using <italic>Slc17a7</italic> expression to delineate the populations. Where both genes were reliably detected in multiple cell-types, we found that <italic>Gdf11</italic> and <italic>Mecp2</italic> expression were correlated (Spearman rho &gt; 0.6). We did note some cell types had stronger correlations than others like astrocytes (Spearman rho &gt; 0.9), but generally, the relationship between <italic>Gdf11</italic> and <italic>Mecp2</italic> appear to be universal across cell types in the normal mouse brain. These data are presented in Figure 1—figure supplement 1E,F.</p><disp-quote content-type="editor-comment"><p>– Please investigate normality for all data and use tests for not normally distributed data whenever necessary. Also indicate if outliers have been examined and, if so, treated.</p></disp-quote><p>We have added these details in the Methods section. Data normality was assessed using Kolmogorov-Smirnoff test for each behavioral metric and using the Shapiro-Wilk test for immunofluorescence quantification due to small sample size. We did not examine or remove any outlier data points.</p><disp-quote content-type="editor-comment"><p>– The discussion of Gdf11 in the Introduction is limited to one sentence, and critical information on this gene and its involvement in neurological manifestations are scattered in the results and Discussion section. I recommend the authors to provide a more robust introduction on Gdf11, including molecular functions, known function in brain (e.g., neurogenesis) and association to disease. For example, the fact that Gdf11 is a secreted factor would be critical throughout the reading of the Results section and appears only at the end of the discussion.</p></disp-quote><p>We have expanded our introduction of Gdf11 and its previously reported functions in normal and disease biology.</p><disp-quote content-type="editor-comment"><p>– It would be helpful to number the studies listed in Table S1 and then add this numerical reference to the legends of Figure 1B and S1B-D. Also, in the legends of Figure 1B and S1B-D, please spell out the acronyms used on the top of the plots.</p></disp-quote><p>We have made these changes to Supplementary Table 1 and the legends of Figure 1 and Figure1—figure supplement 1.</p><disp-quote content-type="editor-comment"><p>– I am not clear why the qPCR experiments were performed in cerebellum, while the rest of the paper focuses on the hippocampus. Please provide a rationale.</p></disp-quote><p>We expected a potential effect size of modulated <italic>Gdf11</italic> expression in the context of altered MeCP2 dosage to be small (Figure 1A and B), so we sought to make our measurements in a brain region where <italic>Gdf11</italic> is most robustly expressed. We used the Allen Brain Atlas in situ maps for <italic>Gdf11</italic> expression and found the cerebellum was the only brain region robustly and highly expressed across two in situ probes for which we had <italic>Mecp2</italic>-knockout RNA-seq. Furthermore, given the high correlation between <italic>Gdf11</italic> and <italic>Mecp2</italic> across cell types (see comment #5), we believe we would see similar results in other brain regions as well. We have added these clarifications and citation into the main section.</p><disp-quote content-type="editor-comment"><p>– The discussion about Gdf11 as a biomarker and target of modulation by neutralizing antibody is important. In this context, it would be important to discuss that Gdf11 is expressed in blood and the potential for systemic modulation of Gdf11.</p></disp-quote><p>We have added these considerations to the Discussion section.</p><disp-quote content-type="editor-comment"><p>– In the methods of the three-chamber assay, please specify if age- and sex-matched target mice have been inspected for aggressive behaviors prior to testing.</p></disp-quote><p>We have added this specification to the Methods section.</p><disp-quote content-type="editor-comment"><p>– In Figure S2F, the statistical comparisons conducted might mislead the reader. The appropriate comparisons is between time investigating partner vs time investigating cup within each genotype, and the general interpretation that all genotypes have intact sociability. This same plot is missing for the Gdf11tm2b/+ line (only preference index shown in Figure S3H) and should be shown.</p></disp-quote><p>We have added the statistics for these comparisons for both behavioral experiments. The plot for investigation time of the <italic>Gdf11<sup>tm2b/+</sup></italic> line was in Figure 3C, and we have added the statistics for partner-cup investigation time per genotype. We have also emphasized in the text that <italic>Gdf11<sup>tm2b/+</sup></italic> do have intact sociability.</p><disp-quote content-type="editor-comment"><p>– Also, in the acclimation phase, there seems to be a preference for the left chamber (statistically significant in Figure S2E and trending in Figure S3G). Why?</p></disp-quote><p>We do not have an explanation for the preference differences, and all mice were acclimated and tested with the exact same parameters and apparatus. For the <italic>Gdf11<sup>tm2b/+</sup></italic> vs. wild-type cohort, where we observed a difference in preference index, we separated the preference index based on the side of the partner mouse and found the same trends regardless of which side the partner mouse was on (<xref ref-type="fig" rid="sa2fig1">Author response image 1</xref>). Due to these considerations, we have tempered our interpretations of sociability and emphasized the persistence of locomotion differences during this assay (see comment #12).</p><fig id="sa2fig1" position="float"><label>Author response image 1.</label><caption><title>Partner side does not change preference index during social phase in <italic>Gdf11<sup>tm2b/+</sup></italic> mice.</title><p>Data from Figure 3 - figure supplement 2F were split into conditions with partner mice on left versus right and trends are preserved in this representation too. Data were analyzed with two-way ANOVA and post-hoc multiple comparisons. (****) <italic>p</italic> &lt; 0.0001 between genotypes.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-83806-sa2-fig1-v1.tif"/></fig><disp-quote content-type="editor-comment"><p>– Line 75. Please add a reference to Shao et al. (2021).</p><p>– Lines 109-110. I recommend removing the word &quot;strong&quot;. &quot;Demonstrate&quot; is sufficient.</p><p>– Line 905 (Figure S1 legend). Please add a reference to Shao et al. (2021).</p><p>– Lines 123-124. The sentence seems redundant. I would suggest just keeping &quot;completely absent&quot;.</p><p>– Line 150. Replace &quot;sans&quot; with &quot;without&quot;.</p><p>– Line 216. By &quot;amplifying progenitors&quot;, do you mean proliferating progenitors?</p></disp-quote><p>Yes, amplifying progenitors are proliferating, and the <italic>SOX2</italic> mark delineates a highly proliferative daughter cell of the radial glial stem cells and is termed amplifying progenitor (Cope and Gould, 2019).</p><disp-quote content-type="editor-comment"><p>– Lines 236-237. Please rephrase. Sentences are redundant.</p><p>– Line 496. Please replace gender with sex.</p><p>– Line 510-511. Please, explain the difference in maximum trial length across cohorts.</p><p>– Figure S1C. Please, replace the Y axis label with &quot;Relative RNA levels&quot;.</p></disp-quote><p>Yes, amplifying progenitors are proliferating, and the <italic>SOX2</italic> mark delineates a highly proliferative daughter cell of the radial glial stem cells and is termed amplifying progenitor (Cope and Gould, 2019).</p><disp-quote content-type="editor-comment"><p>– Please, clarify that &quot;Rett syndrome neurons&quot; indicated neurons isolated from postmortem brains of individuals with Rett syndrome.</p></disp-quote><p>We have made these precise changes or clarified per an individual edit, thank you.</p><disp-quote content-type="editor-comment"><p>Reviewer #2 (Recommendations for the authors):</p><p>Overall, the conclusions are well supported by the experiments and elegant genetic methods are used to demonstrate the Mecp2-mediated transcriptional regulation of gdf11. However, the mechanism by which Mecp2 increases Gdf11 is not clear. The loss of Mecp2 increases H3K27me3, which shows how Gdf11 will be downregulated in Mecp2 knockout mice. But Mecp2 is generally a transcriptional repressor, and it is not clear how Mecp2 binding to Gdf11 TSS will increase its expression. Additional experiments may help understand the mechanism of Mecp2-mediated regulates Gdf11 levels.</p></disp-quote><p>We have further clarified that this MeCP2 peak that is upstream of <italic>Gdf11</italic> co-occurs with a putative enhancer, as demarcated by H3K4me1 signal. Thus, our data supports MeCP2 regulating this cis-regulatory element, and loss of MeCP2 causes the increase of H3K27me3 at this enhancer, causing the downregulation of <italic>Gdf11</italic>. These data are included in Figure 1—figure supplement 2D.</p><disp-quote content-type="editor-comment"><p>Reviewer #3 (Recommendations for the authors):</p><p>1. Please provide information for the animal experiments regarding the composition of the cohorts of animals used, and the timing, order, and ages of when behavioral experiments were conducted.</p></disp-quote><p>We have added a schematic of the behavioral timeline in Figure 2—figure supplement 1 and Figure 3—figure supplement 2 and added the composition of the cohorts to the Methods section.</p><disp-quote content-type="editor-comment"><p>2. Discussion of the points raised in weakness #2 should be included in the manuscript, with consideration of experiments that would directly link to correction not just of behavioral abnormalities but also to underlying neural circuit, cellular, and molecular changes that underlie the observed behavioral changes in order to provide evidence of convergence related to correction of pathophysiology.</p></disp-quote><p>We have added these considerations to the Discussion section. This is an important point when dealing with the interaction of two dosage sensitive genes.</p><disp-quote content-type="editor-comment"><p>3. I think that weakness #3 could be easily addressed by providing raw data in some accessible format and is an important demonstration of commitment to scientific transparency, regardless of specific journal requirements.</p></disp-quote><p>We thank the reviewers for this suggestion and have provided the raw data for each data element as possible in Figure 2-Source Data 1, Figure 3 – Source Data 1, Figure 4-Source Data 1.</p><p>References</p><p>Cope EC, Gould E. 2019. Adult Neurogenesis, Glia, and the Extracellular Matrix. <italic>Cell Stem Cell</italic> 24:690–705. doi:10.1016/j.stem.2019.03.023</p><p>McPherron AC, Lawler AM, Lee SJ. 1999. Regulation of anterior/posterior patterning of the axial skeleton by growth/differentiation factor 11. <italic>Nat Genet</italic> 22:260–264. doi:10.1038/10320</p><p>Saunders A, Macosko EZ, Wysoker A, Goldman M, Krienen FM, de Rivera H, Bien E, Baum M, Bortolin L, Wang S, Goeva A, Nemesh J, Kamitaki N, Brumbaugh S, Kulp D, McCarroll SA. 2018. Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain. <italic>Cell</italic> 174:1015-1030 e16. doi:10.1016/j.cell.2018.07.028</p><p>Shao Y, Bajikar SS, Tirumala HP, Gutierrez MC, Wythe JD, Zoghbi HY. 2021. Identification and characterization of conserved noncoding cis-regulatory elements that impact Mecp2 expression and neurological functions. <italic>Genes Dev</italic> 35:489–494. doi:10.1101/gad.345397.120</p><p>Zhou J, Hamdan H, Yalamanchili HK, Pang K, Pohodich AE, Lopez J, Shao Y, Oses-Prieto JA, Li L, Kim W, Durham MA, Bajikar SS, Palmer DJ, Ng P, Thompson ML, Bebin EM, Müller AJ, Kuechler A, Kampmeier A, Haack TB, Burlingame AL, Liu Z, Rasband MN, Zoghbi HY. 2022. Disruption of MeCP2–TCF20 complex underlies distinct neurodevelopmental disorders. <italic>Proceedings of the National Academy of Sciences</italic> 119. doi:10.1073/pnas.2119078119</p></body></sub-article></article>