Nuclear rerouting of paracrine Fgf3 in source cells represses target genes to pattern morphogen responses

Nuclear rerouting of paracrine Fgf3 in source cells represses target genes to pattern morphogen responses | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Nuclear rerouting of paracrine Fgf3 in source cells represses target genes to pattern morphogen responses View ORCID Profile Sevi Durdu , View ORCID Profile Murat Iskar , Alicia Roig-Merino , View ORCID Profile Elisa Gallo , View ORCID Profile Ezgi Karaca , Andreas Kunze , View ORCID Profile Erika Donà , View ORCID Profile Dirk Schübeler , View ORCID Profile Peer Bork , View ORCID Profile Darren Gilmour doi: https://doi.org/10.1101/2025.07.24.666518 Sevi Durdu 1 European Molecular Biology Laboratory , 69117 Heidelberg, Germany 2 Friedrich Miescher Institute for Biomedical Research , 4058 Basel, Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Sevi Durdu For correspondence: sevidurdu{at}gmail.com darren.gilmour{at}mls.uzh.ch Murat Iskar 1 European Molecular Biology Laboratory , 69117 Heidelberg, Germany 2 Friedrich Miescher Institute for Biomedical Research , 4058 Basel, Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Murat Iskar Alicia Roig-Merino 1 European Molecular Biology Laboratory , 69117 Heidelberg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Elisa Gallo 1 European Molecular Biology Laboratory , 69117 Heidelberg, Germany 3 Department of Molecular Life Sciences, University of Zürich , 8057 Zürich, Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Elisa Gallo Ezgi Karaca 1 European Molecular Biology Laboratory , 69117 Heidelberg, Germany 7 Izmir Biomedicine and Genome Center , 35340 Izmir, Turkey Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ezgi Karaca Andreas Kunze 1 European Molecular Biology Laboratory , 69117 Heidelberg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Erika Donà 1 European Molecular Biology Laboratory , 69117 Heidelberg, Germany 8 CNR Neuroscience Institute , 20854 Vedano al Lambro, Italy Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Erika Donà Dirk Schübeler 2 Friedrich Miescher Institute for Biomedical Research , 4058 Basel, Switzerland 9 Faculty of Science, University of Basel , Basel, Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Dirk Schübeler Peer Bork 1 European Molecular Biology Laboratory , 69117 Heidelberg, Germany 4 Molecular Medicine Partnership Unit, University of Heidelberg and European Molecular Biology Laboratory , 69117 Heidelberg, Germany 5 Max Delbrück Centre for Molecular Medicine , 13125 Berlin, Germany 6 Department of Bioinformatics, Biocentre, University of Würzburg , 97074 Würzburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Peer Bork Darren Gilmour 1 European Molecular Biology Laboratory , 69117 Heidelberg, Germany 3 Department of Molecular Life Sciences, University of Zürich , 8057 Zürich, Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Darren Gilmour For correspondence: sevidurdu{at}gmail.com darren.gilmour{at}mls.uzh.ch Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Morphogen gradients direct tissue patterning by inducing dose-dependent transcriptional responses, yet ligand-producing cells often respond differently from their neighbors. Using the zebrafish lateral line organogenesis model, we uncover a cell-autonomous role for the paracrine ligand Fgf3. Transcriptomic profiling and quantitative single-molecule imaging identify target genes, including the chemokine scavenger cxcr7b , whose expression decreases both when FGF receptor signaling is inhibited and when Fgf3 is overexpressed. High-resolution live imaging reveals nuclear accumulation of Fgf3 in producing cells, whereas neighbors receive only extracellular ligand, a feature also observed in other embryonic tissues. Mosaic gain- of-function and nanobody-mediated degradation demonstrate that the nuclear pool of Fgf3 autonomously represses specific targets without impairing canonical receptor signaling. Structure-guided comparative assays indicate nuclear targeting as a latent property of several paracrine FGFs. Dual secreted–nuclear functionality of FGF ligands may represent an intrinsic symmetry-breaking mechanism during organogenesis. Introduction Multicellular development depends on the regulated expression of genes that drive the differentiation of cell groups into tissues and organs of defined form and function. This spatiotemporal regulation is provided by potent secreted signals termed morphogens 1 – 3 . Fibroblast growth factors (FGFs) are well-studied morphogens that control diverse developmental processes, including early tissue specification, somitogenesis, and proximodistal limb patterning 4 – 7 . Studies in these and other model systems have provided key mechanistic insights into how morphogens generate complex spatiotemporal patterns of gene expression 8 – 11 . At the molecular level, secreted FGF ligands typically activate tyrosine kinase receptors, which in turn phosphorylate Ets transcription factors in the nucleus to enhance positive pathway targets and repress negative ones 7 , 12 – 15 . At the tissue scale, expression patterns are thought to arise primarily from the graded distribution of FGF ligands and the differential dose responses of target genes, each regulated at defined morphogen thresholds 11 , 16 . These mechanisms, however, can be further modulated by cell-specific features that remain less well understood. For example, cells at the source of morphogen gradients are exposed to the highest ligand levels, yet in many contexts respond less strongly than their immediate neighbors 3 , 17 , 18 . In some cases, this difference reflects reduced receptor expression in ligand-producing cells, leading to attenuated signaling 19 . More generally, however, the mechanisms that distinguish morphogen source cells from responders in differentiating tissues remain elusive. To investigate the roles of FGF signaling in gene regulation, we utilized the development of posterior zebrafish lateral line primordium (pLLP), a tractable in vivo model for studying dynamic tissue patterning at cellular resolution 20 – 22 . In this system, localized sources of FGF ligand expression direct the orderly assembly and deposition of rosette-like mechanosensory organs, termed neuromasts, by a migrating collective of epithelial cells 23 – 25 . The range of FGF action within the pLLP is restricted by the expression of extracellular matrix-associated molecules, such as HSPGs and Anosmin1, and the formation of multicellular lumina that concentrate the secreted ligand at the center of each neuromast progenitor 26 , 28 , 29 . While these mechanisms explain how FGF acts locally to promote neuromast assembly, it remains unclear whether and how FGF morphogens drive cell type diversification within these differentiating organs. Here, we investigate the impact of FGF signaling on gene expression patterning in the pLLP using RNA profiling combined with in vivo subcellular analyses. We show that tissue-specific upregulation of Fgf3 leads to transcriptional repression of a subset of genes that otherwise behave as bona fide positive targets of FGF receptor signaling, including the chemokine receptor cxcr7b . In line with this unexpected finding, mosaic expression of Fgf3-GFP demonstrates that repression of cxcr7b is autonomous to source cells and can be mediated by non-secreted forms of the ligand. Targeted depletion experiments further confirm that this activity depends on a nuclear-localized pool of Fgf3. Beyond contributing to the growing literature on proteins with proposed dual functionality 27 , these data support a general mechanism that distinguishes morphogen source cells from responders. Results To obtain a comprehensive view of the gene regulatory targets of FGF signaling in the posterior lateral line primordium (pLLP), we manipulated FGF activity using two approaches. First, we applied the small-molecule antagonist SU5402 to inhibit the kinase domain of FGF receptor 1 (Fgfr1), at a concentration previously shown to block FGF-dependent organ differentiation and target gene expression in this tissue (“Fgfr1-inhibited”). Second, we employed an inducible FGF ligand expression system that we had previously validated as a tunable enhancer of FGF signaling (“Fgf3-induced”) 28 , 29 . Treated pLLP cells were then isolated with high specificity by fluorescence-activated cell sorting (FACS), using expression of two fluorescent transgenic reporters, cxcr4b:nlsTomato 30 and cldnb:lyn-GFP 25 , as selection markers ( Figure S1 ). We next established the gene expression profiles of wild-type, Fgfr1-inhibited, and Fgf3-induced pLLPs in six replicates. Profiling and bioinformatic analysis revealed a comprehensive catalog of pLLP-specific genes with distinct responses to FGF signaling ( Figure 1A , Table S1). Download figure Open in new tab Figure 1. Gene expression profiling following FGF signaling perturbations uncovers atypical regulation of a subset of target genes in the zebrafish lateral line. A. Gene expression profiling pipeline. Left: Images of lateral line primordium upon manipulation of FGF signaling levels through FGF ligand induction ( fgf3 overexpression) and FGF receptor inhibition (Fgfr1 kinase domain inhibition with SU5402) on cldnb:lyn-GFP (green membrane), cxcr4b:nlsTomato (red nucleus) transgenic lines alongside controls. Middle: Isolation of lateral line cells from the rest of the embryo by FACS using fluorescent markers and scatter features. Red circle indicates the pLLP population (see Figure S1 ). Right: Gene expression profiling of 6 biological replicates with 3 treatment conditions; the graph shows hierarchical clustering of the 18 samples. B. Heatmap of differentially expressed genes in response to both Fgfr1 inhibition and Fgf3 induction (blue: downregulation, yellow: upregulation). Left: Anti-correlated genes are dose-responsive genes oppositely affected by Fgf3 induction and Fgfr1 inhibition (e.g., pea3 and lef1 ), whereas correlated (dose-independent) genes respond in the same direction (e.g., cxcr7b ). Gene expression profiles recapitulate previously documented responses to FGF signaling inhibition, including pea3 as a positive and lef1 as a negative target of FGF signaling. C. smFISH-based quantification of cxcr7b expression in pLLP across wild-type (WT), Fgf3 induction (IND), and Fgfr1 inhibition (INH) conditions. Zoomed regions are boxed. Boxplot shows cxcr7b transcript counts per cell, per primordium (n = 4, 5, 6). D–E. smFISH-based expression profiles of the canonical FGF signaling target pea3 and the dose-independent target cxcr7b along the pLLP in wild-type, Fgf3 induction, and Fgfr1 inhibition conditions. F. Probing gene expression upon clonal expression of constitutively active Fgfr1 (red, lexop:ca-fgfr1-RFP). Left panel: composite image of pLLP with ca-Fgfr1-expressing clones and cxcr7b RNA smFISH on membrane-labeled pLLP. Plot below: corresponding signal intensity profiles along the migration axis. Right panel: activation of pea3 and cxcr7b expression (white, smFISH) through clonally expressed ca-Fgfr1 (red, lexop:ca-fgfr1-RFP) at the leading edge of pLLP (green, cldnb:lyn-gfp). G. Illustration of cxcr7b expression domain (red cells) upon FGF perturbations (blue-lined cells: ca-fgfr1 clones, green cells: fgf3 overexpression). Scale bars: (A, C) 20 µm, (F) 5 µm. Differential gene expression analysis identified transcripts significantly affected by Fgfr1 inhibition and Fgf3 induction (Table S1, Figure S2A , see Methods). Of the 446 differentially expressed genes shared between both conditions, 329 showed opposing changes after Fgf3 induction versus Fgfr1 inhibition, allowing straightforward classification as either positive or negative FGF targets. For example, expression of the Ets transcription factor pea3 ( etv4 ) 14 , a known positive target, increased with FGF induction and decreased upon Fgfr1 inhibition. By contrast, the transcription factor lef1 decreased in response to Fgf3 induction and increased with Fgfr1 inhibition, consistent with its previous identification as a negative FGF target 31 – 33 ( Figure 1B , Figure S2B ). We also identified 117 genes that were repressed under both conditions, precluding their classification as either positive or negative targets ( Figure 1B , Table S2). Among these was the scavenger receptor cxcr7b , previously shown to generate local chemokine gradients that guide the ‘self-directed’ migration of the pLLP 34 , 35 . Transcription of cxcr7b was significantly reduced after Fgfr1 inhibition, consistent with earlier findings that its expression depends on FGF signaling 33 . However, its expression also decreased after Fgf3 induction ( Figure 1B-C , Figure S3A-C ). This paradoxical response prompted us to examine this novel class of differentially expressed genes more closely, using quantitative approaches comparing cxcr7b with the canonical positive target pea3 . Single-molecule FISH (smFISH) analysis of wild-type pLLPs confirmed that neither gene is normally transcribed at the tissue’s leading domain, and that their expression is turned on in regions where neuromast assembly is promoted by FGF signaling ( Figure 1D-E ). Consistently, Fgfr1 inhibition led to a reduction of both genes in these regions. However, while Fgf3 induction strongly increased pea3 expression ( Figure 1D ), the same manipulation repressed cxcr7b across the tissue 28 , 29 ( Figure 1E ), confirming its unexpected response to changes in FGF activity. The non-canonical nature of this regulation was further underscored by comparison with the closely related paralog cxcr7a , which responded to FGF inhibition and induction like a canonical positive target, similar to pea3 ( Figure S3D–G ). Since both Fgfr1 inhibition and Fgf3 induction suppressed cxcr7b expression, we investigated the impact of directly activating FGF receptor signaling by driving mosaic expression of a constitutively active form of the receptor (ca-Fgfr1a) in the pLLP. As shown in Figure 1F , ca-Fgfr1a triggered cell-autonomous activation of both pea3 and cxcr7b in leading-domain cells, where neither gene is normally expressed. These data support the conclusion that cxcr7b transcription is promoted by Fgfr1 signaling but repressed by increased expression of its ligand Fgf3 ( Figure 1G ). If cxcr7b expression is promoted by Fgfr1 activation, how does Fgf3 induction lead to its downregulation? To address this, we compared cxcr7b and Fgf3 expression patterns at cellular resolution using quantitative smFISH together with BAC live reporters ( Figure 2A–D , Figure S3H ). This analysis revealed that while cxcr7b was strongly expressed in neuromast progenitors, similar to pea3 , its levels were markedly lower in the central cells of rosette-like assemblies ( Figure 2A–B , Figure S4A ). To more precisely identify ligand-producing cells, we employed a fgf3:Fgf3-GFP line, in which a fluorescently tagged gene recapitulates the endogenous expression pattern and rescues ligand function in deficient embryos 29 . As expected, secreted Fgf3-GFP accumulated in extracellular luminal spaces, but gene expression was confined to central cells that lacked cxcr7b ( Figure 2C–D , Figure S4B ). A similar mutually exclusive pattern of cxcr7b and Fgf3-GFP was observed in other regions of the lateral line ( Figure 2A vs 2C , Figure 2E ). Despite the absence of cxcr7b in rosette centers, smFISH revealed strong expression of pea3 , indicating that loss of cxcr7b was not simply due to reduced autocrine FGF signaling ( Figure S4A , Figure 2B ). Download figure Open in new tab Figure 2. Fgf3 and cxcr7b have mutually exclusive expression patterns in the lateral line. A. Maximal projection image of cxcr7b RNA smFISH (white) in lateral line (left: deposited organ progenitor, right: primordium). B. Side view image (middle slice) of cxcr7b and pea3 RNA (white) in deposited organ progenitors (cldnb:lyn-GFP, red), displaying the expression patterns in central versus neighboring cells (see Figure S4A for top view). C. fgf3:Fgf3-GFP expression and localization in the lateral line (left: deposited organ progenitor, right: primordium). Blue arrow points to extracellular (luminal) Fgf3 and white arrow to intracellular Fgf3. D. Mapping Fgf3 expression domain (green lines) versus cxcr7b expression pattern in the same deposited organ (red lines) using fgf3:Fgf3-GFP rescue in Fgf3/Fgf10 knock-down embryos, showing centrally positioned FGF source cells with Fgf3-GFP (displayed in 16 color look-up-table, left panel), and cxcr7b RNA smFISH (white, right panel). Top panels: maximal projections; bottom panel: side view, highlighting diminished cxcr7b expression in Fgf3 source cells (see also Figure S4B ). E. Illustration of cxcr7b (red) and fgf3 (green) expression domains in lateral line (grey). Scale bars: (A, C) 20 µm, (B, D) 5 µm. Beyond its gene expression pattern, imaging Fgf3 ligand revealed a substantial pool of Fgf3-GFP localization to the nuclei of expressing cells, a finding not predicted for a canonical signaling ligand function 28 , 31 , 36 ( Figure 2C–D , Figure 3A ). This nuclear localization as well as its mutually exclusive pattern with cxcr7b expression was evident also in other embryonic tissues, including the developing pharyngeal arches and otic placode, where nuclear Fgf3-GFP–positive cells lacked cxcr7b expression, while juxtaposed neighbors expressed it strongly. These observations suggest that the underlying mechanism operates broadly in fgf3 -expressing tissues ( Figure 3B , Figure S4C ). We next asked whether a similar expression pattern could explain the non-canonical regulation of other genes in this class. The T-box transcription factor tbx1 , like cxcr7b , was downregulated both by receptor inhibition and by Fgf3-GFP induction ( Figure S4D–E ). smFISH confirmed that tbx1 expression was higher in cells neighboring Fgf3-GFP–positive cells and lower in source cells ( Figure 3C–D ). Download figure Open in new tab Figure 3. Fgf3-GFP shows nuclear localization and a mutually exclusive pattern with cxcr7b expression in multiple embryonic tissues. A. fgf3:Fgf3-GFP 30 hpf zebrafish transgenic line (green) with cxcr4b:cxcrb4-RFP counter-label (red), marking anatomical regions. Known fgf3 expression domains are revealed by the nuclear localization of Fgf3-GFP in expressing cells. Right panels show the close-up images of the boxed regions (for box #5, see pLLP in Figure 2C ). B. fgf3:Fgf3-GFP (green), cxcr7b:cxcr7b-mKate2 (red) double transgenic fish showing mutually exclusive neighboring patterns at the developing ear and pharynx (see also Figure S4C ). C, D. tbx1 RNA smFISH (white) with cldnb:lyn-GFP membrane label (red) in developing ear and a deposited organ progenitor of lateral line (see Figure S4D ). tbx1 gene expression is detected surrounding Fgf3 expressing regions (ear in Figure 3B , lateral line in Figure 2 ) but shows a mutually exclusive pattern with the Fgf3-expressing cells (region marked with a yellow star). Scale bars: (A) 100 µm, (B, C) 20 µm, (D) 5 µm. We next investigated whether this nuclear localization is a feature shared by other FGF family members. We first performed multiple sequence alignments of the FGF family members, which confirmed the previously defined seven subgroups 37 ( Figure 4A , Figure S5A ). We then selected a representative member from each subgroup and predicted their structures 38 ( Figure S5 ). This analysis identified features indicative of nuclear localization signals (NLSs), such as positively charged regions on the protein surfaces in an extended conformation 39 ( Figure S5B-E ). Except for Fgf19, which is classified as an “endocrine FGF” due to its reduced affinity for HSPGs and its systemic hormonal activity 40 , 41 , all analyzed FGF family members displayed putative nuclear-targeting features that overlap with their HSPG interaction surface. To test these predictions, we tagged representative FGFs with GFP between the secretory signal and the globular domain and imaged their subcellular localization after overexpression in early embryos ( Figure 4B–C ). The subcellular localization of FGF2, which lacks a typical secretory signal, confirmed the reported nuclear targeting of b-FGFs 42 , whereas FGF19 confirmed the exclusive extracellular targeting of the endocrine FGFs. All other FGFs showed varying degrees of nuclear localization, some consistent with previous observations 43 , 44 . To test the potential context dependence and the impact of the model system on nuclear localization, we imaged mouse FGF3-GFP in mouse embryonic stem cells (mESCs) upon its inducible expression. In mESCs, FGF3 was exclusively targeted to the secretory pathway, with no detectable nuclear localization. Upon differentiation of mESCs through embryoid body formation, however, a subset of cells began to show nuclear localization ( Figure S6 ). These experiments suggest that nuclear localization may be a more widespread latent property of FGFs. FRAP analysis further showed that the nuclear pool of Fgf3-GFP exhibited diffusion kinetics slower than NLS-tagged GFP, yet similar to a widely studied transcription factor, N-Myc, suggesting potential interactions with nuclear components ( Figure 4D ). Download figure Open in new tab Figure 4. Nuclear localization of Fgf3 has the potential to be a widespread feature among FGFs. A. Unrooted phylogenetic tree of FGF family members. Representative members (bold, colored) of each sub-family were chosen for structural modelling and cellular localization experiments. B. Scheme summarizing tagging and misexpression of FGF family members: transient misexpression of cmv:fgf-gfp DNA and nuclear counter-label H2b-RFP RNA (red) in 4hpf embryos. The image shows nuclear localization of Fgf3-GFP under conditions of high, transient expression in early embryos. C. Cellular localization of GFP-tagged FGF family members (green) with H2b-RFP nuclear marker (red). Arrowheads (white: positive, yellow: negative) indicate nuclear localization of FGFs D. Images and quantification of nuclear diffusion using fluorescence recovery after photobleaching (FRAP), contrasting Fgf3, a nuclear tag (nls), Mycn transcription factor and Histone H2B, tagged with a fluorescent protein. Images show pre- and post-bleach time-points. Bleached area is marked with a rectangle. Plots show FRAP of 10 replicates. H2b-RFP did not recover within imaging duration, as expected. Calculated mobile fraction: 0.98, 0.83, 0.86, t 1/2 : 0.24, 0.95, 0.97, respectively. Scale bars: (B, C) 10 µm. The mutually exclusive expression of fgf3 with a subset of its signaling targets, combined with nuclear ligand localization in source cells, indicates that Fgf3 may regulate this gene class through a mechanism distinct from canonical extracellular signaling. To probe this directly, we generated additional sources of inducible Fgf3-GFP in nascent neuromasts using cell transplantation ( Figure 5A ). Donor source cells and neighbor host cells were distinguished by specific reporters, and the impact of Fgf3 induction on pea3 and cxcr7b expression was quantified in individual 3D-segmented cells using smFISH ( Figure 5A ). Upon induction, pea3 expression increased in both neighbors and source cells, indicating paracrine and autocrine receptor activation ( Figure 5B ). Increased expression of the positive target pea3 in neighbor cells confirmed that paracrine FGF signaling is elevated, consistent with the previous demonstration that neuromast cells can share signals via common extracellular microlumen to ensure coordinated signaling 29 . An equivalent increase in pea3 mRNA level in source cells suggests that these cells are just as responsive to the ligand they secrete as neighboring cells ( Figure 5B ). By contrast, cxcr7b expression was significantly reduced only in Fgf3-GFP source cells, not in neighbors ( Figure 5B , Figure S7 ). These results support a dual mode of Fgf3 action: activating target genes in receiving cells via receptor-mediated autocrine and paracrine signaling, while cell-autonomously repressing the targets in ligand-producing source cells. Download figure Open in new tab Figure 5. Clonal misexpression of Fgf3 leads to increased signaling in all organ progenitor cells but cell autonomous downregulation of cxcr7b expression specifically in source cells. A. Schema showing possible outcomes of ectopic Fgf3 expression in clones. Fgf3-misexpressing cells are drawn in red, other cells in the same organ progenitor (neighbors) are drawn in green. B. pea3 and cxcr7b RNA smFISH in deposited mosaic organ progenitors with Fgf3-induced (Fgf3-GFP/lyn-RFP/nls-tdTomato) cell clones (red) among cldnb:lyn-GFP labeled neighbor cells (green). RNA spots identified by 3D segmentation are shown in yellow if located within FGF-expressing clones, or white if in surrounding cells of the same organ progenitor. Red outlines (right panels) mark the positions of the Fgf3-expressing clones. Box plots show the quantification of pea3 and cxcr7b levels per cell in deposited organ progenitors contrasting FGF expressing clones with the rest of the neighboring cells in the same organ progenitor ( n = 5, 11, 6; n = 10, 13, 7; Wilcoxon test, ***P < 0.001). Scale bar: 5 µm. The data described above demonstrate that Fgf3 localizes to the nucleus in expressing cells and can repress specific target genes in a cell-autonomous manner. To probe the causal link between these findings, we performed experiments manipulating the intracellular transport route of Fgf3. High-resolution imaging revealed that full-length Fgf3-GFP localized both to the nucleus and to the secretory pathway in source cells, with the secreted pool concentrated in the central microlumen 45 ( Figure 6A , Figure S8A ). To alter ligand routing, we manipulated its N-terminal signal peptide, which normally directs secretion and is cleaved from the ligand upon endoplasmic reticulum entry. Fusion of the signal peptide to GFP (secGFP) labeled only the secretory pathway and microlumen, with no detectable nuclear localization ( Figure 6B , Figure S8B ). Conversely, deleting the signal peptide from full-length Fgf3-GFP (nonsec–Fgf3-GFP) abolished secretion with exclusive nuclear localization and no detectable labelling of the secretory compartments or microlumina ( Figure 6C , Figure S8C ). This contrast is consistent with nuclear localization acting as the default transport pathway when secretion is diminished. Download figure Open in new tab Figure 6. Nuclear localization of Fgf3 in source cells exerts a distinct impact on gene expression compared with its signaling function. A, B, C. Localization of GFP-tagged Fgf3 constructs. Fgf3-GFP (sec-GFP-Fgf3) represents full-length Fgf3, tagged with GFP between the signal peptide and the globular domain. sec-GFP is GFP-tagged signal peptide and nonsec-Fgf3-GFP (GFP-Fgf3) is GFP-tagged globular domain of Fgf3 lacking the signal peptide. Left panel: schematic of cellular localization. Middle: cellular imaging of tagged proteins (green) with nuclear counter-label (nls-tdTomato, red). Right: multicellular imaging of the GFP-tagged proteins (green) in assembled organs with membrane counter-label (lyn-RFP). Arrowheads: extracellular space in rosette centers (microlumen). D . Boxplots showing quantification of pea3 expression (left) upon nonsec-Fgf3-GFP expression in organ progenitors and cxcr7b expression (right) upon nonsec-Fgf3-GFP and Fgf3-GFP expression ( n = 6 each). E. Scheme of anti-GFP nanobody targeted nuclear degradation. Nuclear-localized proteins were degraded upon recognition of GFP tag via AbSPOP. Mutant anti-GFP nanobody-SPOP fusion (mutAbSPOP) served as non-targeting control. F, G. Fgf3-GFP localization upon lexop:fgf3-gfp expression with targeted nuclear degradation (F) versus non-targeting (G). Left: schematic of cellular localizations and imaging of tagged proteins (green) with nuclear counter-label (nls-tdTomato, red). Right: multicellular imaging of the Fgf3-GFP (green) in organ progenitors with counter-labels (H2B-RFP and cxcr4b-RFP) and close-up views of the boxed regions highlighting Fgf3-GFP cellular localization. Microluminal (extracellular space) and nuclear spaces are indicated by yellow and white arrows, respectively. H, pea3 and cxcr7b expression in control versus nuclear degraded Fgf3-GFP expressing organ progenitors ( n = 8 each; n = 18 and 24, respectively) . I. Schematic of the FGF-driven gene regulation model. Scale bars: (A-C, F-G) 5 µm. Statistics: Wilcoxon test, **P < 0.01, ***P < 0.001. Functionally, nonsec–Fgf3-GFP was deficient in inducing receptor-mediated signaling as evidenced by the absence of detectable increase in pea3 mRNA in expressing neuromasts ( Figure 6D ). This absence rules out the possibility of Fgf3 signaling via non-canonical secretion pathways. The nonsec-Fgf3-GFP protein, however, repressed cxcr7b expression ( Figure 6D ), suggesting that nuclear Fgf3 can mediate repression of specific target genes in signal source cells. Performing the complementary experiment, preventing nuclear targeting specifically while leaving signaling activity intact, proved more challenging. Unlike the discrete signal peptide, the residues for the nuclear localization are distributed across the protein and overlap with other structural features ( Figure S7 ). An alternative approach, attaching a nuclear export sequence to Fgf3-GFP, reduced nuclear localization as anticipated but also hindered this variant from entering the secretory pathway, precluding functional distinction ( Figure S8D ). We therefore took an alternative approach to testing the requirement for Fgf3 nuclear localization by selectively depleting the nuclear pool using a nanobody-based degradation strategy. This targeted degradation is based on DeGradFP method, where anti-GFP nanobodies fused to the SPOP ubiquitin ligase (AbSPOP) specifically target GFP-tagged proteins in the nucleus for degradation without affecting cytosolic protein levels ( Figure 6E , Figure S9 ) 46 . Indeed, expressing AbSPOP in the Fgf3-GFP-induced cells depleted nuclear Fgf3-GFP signal while leaving the secreted luminal pool unaffected ( Figure 6F ). Validating the specificity of this approach, expressing a nanobody mutant version (mutAbSPOP), which retains functional SPOP but lacks the ability to bind GFP-tagged targets, did not interfere with Fgf3-GFP distribution ( Figure 6G ). Importantly, selective depletion of nuclear Fgf3-GFP by AbSPOP did not alter pea3 expression levels, confirming intact extracellular signaling, but increased cxcr7b levels as compared to mutAbSPOP ( Figure 6H ). Together, this reveals Fgf3’s ability to repress the expression of specific target genes in source cells through nuclear localization, a mechanism that is decoupled from its function in extracellular signaling ( Figure 6I ). Discussion Previous studies on cell signaling have primarily focused on how gene expression patterns are shaped by secreted ligands via paracrine and autocrine signaling 3 , 36 . By combining live imaging of the Fgf3 ligand with gene expression profiling of its downstream targets, we uncover an underexplored role for this classical paracrine signal in regulating gene expression within a multicellular tissue context. We propose a patterning model in which extracellular FGF regulates the expression of canonical target genes in all signal-receiving cells, while nuclear FGF selectively represses a subset of these targets in ligand-sending source cells ( Figure 6I ). By innately distinguishing source cells from their neighbors, this mechanism offers a general strategy for establishing self-organized gene expression differences across diverse tissues, such as the ear 47 and pharynx 47 , 48 . The dual function of FGF signaling revealed here appears to introduce an additional layer of regulatory control in developmental signaling. To address the basis of this dual function, we manipulated the subcellular localization of Fgf3, allowing us to deconvolve its nuclear and extracellular roles. Fgf3 secretion was specifically prevented by deleting its defined N-terminal signal peptide. This non-secreted variant localized to the nucleus and repressed cxcr7b transcription, consistent with the conclusion that nuclear-localized pool does not enter the secretory pathway. Interestingly, the non-secreted variant appears less effective at suppressing cxcr7b transcription than the full-length Fgf3-GFP ( Figure 6D ), raising the possibility that the signal sequence, which is normally cleaved from the secreted ligand only upon translocation into the ER, may enhance the activity of the nuclear-localized form. The converse rerouting experiment, preventing nuclear targeting, was challenging, nevertheless the targeted protein degradation approach directly demonstrated that nuclear Fgf3 is required to suppress cxcr7b expression, while leaving paracrine signaling intact. Looking ahead, it will be important to determine whether developmental regulation of Fgf3 partitioning between nuclear and secretory pathways provides adaptive control. Although beyond the scope of this study, future work defining the interaction of FGFs with chromatin and nuclear partners will clarify how nuclear-localized FGFs regulate specific target genes. The cell-autonomous nuclear role of Fgf3-GFP, both at physiological expression levels and upon targeted misexpression, prompted us to investigate the other FGF family members. Guided by the structural predictions, misexpression experiments in early embryos suggests that nuclear functions could represent a broader property of FGF ligands. Future studies leveraging endogenous detection of FGF proteins across cell-types will be required to test whether this nuclear localization occurs under physiological conditions and in specific cellular contexts. Together, these findings highlight an intriguing and underexplored dimension of FGF function in development with potential implications for disease. The detection of nuclear-localized FGF ligands prompts a re-evaluation of the roles and subcellular localization of other signaling molecules, particularly those containing exposed positively charged regions that could promote nuclear targeting, a sequence feature shared by many ECM-associated growth factors and signaling molecules 49 . Revisiting genetic disorders linked to mutations in such molecules could yield new insights 50 , especially considering the potential cell-autonomous activities distinct from their conventional paracrine functions 51 . Data availability Datasets generated in this study were deposited at Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/ ) under accession no GSE207538. Contributions S.D. and D.G. designed the study. S.D. performed all experiments, assisted by A.R.M for colorimetric in situ hybridizations. M.I. and S.D. analyzed the data and assembled the figures with input from P.B. and D.S.. E.G. developed the inducible ca-Fgfr1 system. A.K. generated GFP-tagged FGF ligand plasmids and assisted with 3D organ segmentation. E.K. performed FGF protein sequence and structure comparisons. E.D. cloned cxcr7a cDNA. S.D. and D.G. interpreted the data and wrote the paper with input from all authors. Competing interests The authors declare no competing financial interests. Supplementary Figures Download figure Open in new tab Figure S1. Identification and isolation of the lateral line cells with FACS. A. Left: Whole-embryo images of cxcl12a (sdf1a) mutant, wild-type, Fgf3-induced and Fgfr1-inhibited transgenic cldnb:lyn-GFP, cxcr4b:nlsTomato embryos at 30 hpf. Dashed lines indicate the dissection site for trunk isolation. Right: Corresponding fluorescence density plots (blue to red: low to high cell count density) showing gated cells dissociated from trunks. The sorted pLLP population is circled, absent in cxcl12a mutants due to impaired primordium migration. B. Sorting gates used to isolate lateral line primordium cells from embryo trunks. Ungated: all trunk cells plotted by tdTomato and GFP fluorescence. The regions corresponding to the reference population (blue box) and the primordium population (red box) are outlined. Scatter and singlet gate: Scatter and singlet gate: scatter plots of analyzed cells (density in grey) with primordium (red dots) and reference population (blue dots) overlaid. Gates used to sort pLLP are outlined with red lines. Gated: fluorescence plot of remaining cells after scatter and singlet gates with sorted primordium population outlined in red. Scale bar: (A) 200 µm. Download figure Open in new tab Figure S2. Fgf3 misexpression and Fgfr1 inhibition lead to differential gene regulation in pLLP, impacting known FGF and WNT signaling targets. A. Gene expression profiling of Fgf3 induction, wild-type, and Fgfr1 inhibition across six biological replicates. Volcano plots show thresholds used to identify genes differentially expressed under treatment relative to control. B. Differential regulation of FGF (red) and WNT (green) signaling components in lateral line primordium. Heatmaps show fold changes relative to wild-type (blue: down-regulation, yellow: up-regulation). Download figure Open in new tab Figure S3. Impact of FGF manipulations on cxcr7b expression. A. Establishing cxcr7b smFISH (grey) using control (cxcr4b:lexPR) and cxcr7b overexpressing (cxcr4b:lexPR/lexOP:cxcr7b) lateral line organs (cldnb:lyn-GFP, red), confirming the specific recognition of cxcr7b mRNA by the smFISH probes. B. Whole embryo image of cxcr7b:lyn-sfGFP (white) transgenic line marking cxcr7b expression domains with membrane-GFP (thus a low turn-over rate of the reporter). Lower panels: close-up images of lateral line in cxcr7b:lyn-sfGFP embryos, showing responses to early Fgf3 induction and inhibition. C. cxcr7b colorimetric RNA in situ hybridization (ISH) of whole embryos (black) and close-ups (red) upon FGF manipulations (cldnb:lyn-GFP, green). D. Bar plots of gene expression change of the paralogs, cxcr7b and cxcr7a, upon FGF induction and Fgfr1 inhibition, measured by microarrays. E. Rescue of Cxcr7b loss-of-function by Cxcr7a in cell migration. Upper: 2-day-old Cxcr7b mutant embryo with impaired primordium migration. Lower: transient Cxcr7a-GFP expression (gal4/uas:cxcr7a-GFP) rescuing the primordium migration. Migration quantified ( n = 15 control, 14 rescue). F. Left: cxcr7a colorimetric ISH (black) on wild-type and Fgf3 induced embryos, showing increased cxcr7a expression at lateral line organ progenitors upon Fgf3 induction. Right: close-up images of the lateral line with cxcr7a ISH (red) and cldnb:lyn-GFP counter-label (green). G. fgf3 , cxcr7b and cxcr7a ISH (black) on wild-type, Fgfr1 inhibited and Fgf3 induced lateral line primordium, highlighting the opposite responses of cxcr7b and cxcr7a to FGF induction when pLLP cells are induced to express the Fgf3 ligand. H. The known FGF ligand expression pattern (schema in blue) in contrast to the opposing expression pattern of cxcr7b (ISH in red) in the zebrafish lateral line (cldnb:lyn-GFP, green). Scale bars: (A) 5 µm, (B, E) 200 µm, (C) 20 µm, (H) 50 µm. Statistics: Wilcoxon test, ***P < 0.001. Download figure Open in new tab Figure S4. Probing cxcr7b and tbx1 gene expression patterns in comparison to Fgf3. A. Single smFISH channels of Figure 2B . B. Composite images of cxcr7b smFISH (white) and fgf3:Fgf3-GFP rescue (green) from Figure 2D , overlaid with membrane marker of twf2b:lyn-mKate2 (red) to facilitate 3D alignment of two imaging sets from the same organ progenitor. C. Composite image of a lateral line organ progenitor marked with cxcr7b:Cxcr7b-mkate2 (red) and fgf3:Fgf3-GFP (green). The cellular cxcr7b gene expression pattern cannot be resolved using the endogenously tagged Cxcr7b protein in pLLP due to high protein turnover (seen as endocytic punctate signal), unlike the plasma membrane signal in other tissues ( Figure 3B ). D. tbx1 RNA smFISH (white) on the lateral line (red, cldnb:lyn-GFP) and its response to FGF manipulations at the trailing edge of the primordium, resembling the pattern of cxcr7b . E . Colorimetric ISH (black) of tbx1 in whole fish embryos (cldnb:lyn-GFP, green) after FGF manipulations. Arrows point to the pLLP. Scale bars: (A, B, D-lower panel) 5 µm, (D-upper panel) 20 µm. Download figure Open in new tab Figure S5. Comparative sequence and structural analysis of zebrafish FGFs. A. Multiple sequence alignments of zebrafish FGFs performed using the T-Coffee server 52 and visualized with ESPript 3.0 53 . Scores above SimilarityGlobalscore are shown in red, and strictly conserved residues in white on red background. A previously predicted motif-4 39 is highlighted for its potential to act as a nuclear localization signal (positively charged, extended-exposed conformation, conserved). B. A closer look at the sequence conservation of motif-4 among the experimentally tested FGFs. C . Positive charge percentage of motif-4 among FGFs. FGFs tested experimentally are marked with a star. D. Electrostatic surface maps of zebrafish FGFs, with structures predicted by AlphaFold3.0. Surface charge scale spans from -10 (red) to +10 (blue). The region corresponding to motif-4 is boxed, which shows a highly positively charged domain on the surface of the FGFs except Fgf19. E. Closer inspection of the motif further showed that its 3D structure was conserved except for Fgf19. Download figure Open in new tab Figure S6. Subcellular localization of mouse FGF3-GFP in mouse embryonic stem cells (mESCs). A. Subcellular localization of mouse FGF3-GFP (upon 6 hour doxycycline induced expression) in mESCs cultured in pluripotent maintenance media (15%FCS+LIF) versus spontaneous differentiation induction media (10%FCS+retinoic acid). Nuclei counter-labeled with Hoechst staining (purple). B. Cross-sectional image of mESCs in spontaneous differentiation induction media, showing two cells at the same imaging plane, expressing FGF3-GFP, yet with variable subcellular localization. Download figure Open in new tab Figure S7. Clonal Fgf3 misexpression demonstrates the cell autonomous repression of cxcr7b . A, B. Maximum Z-projections of cxcr7b smFISH (white) following clonal Fgf3 misexpression (red) and neighboring cells (green) in a mature organ progenitor (A) and at the trailing end of a primordium (B). C. pea3 smFISH (white) on Fgf3 misexpression clones (red) along with surrounding cells (green) in a mature organ progenitor. Scale bars: (A-C) 5 µm. Download figure Open in new tab Figure S8. Cellular localization of Fgf3 constructs in lateral line organ progenitors. A-C. Apical and basal slices of the imaged organ progenitors as shown in Figure 6A-C , highlighting the corresponding extracellular (apical lumen in rosette center) and cellular localizations within the lateral line organ progenitors. Scale bar: 5 µm. D. Apical, basal slices, and the maximal projections of Fgf3-GFP construct with nuclear export signal (n.e.s), showing expected absence of nuclear Fgf3 and unintended block of Fgf3 localization to the extracellular space. Download figure Open in new tab Figure S9. Establishing a nuclear-targeted GFP degradation system for selective depletion of nuclear Fgf3-GFP. A. Specificity and efficiency of the anti-GFP degradation tested in zebrafish somites with triple RNA injections of H2B-RFP (red), nls-GFP (green) and either mutAbSPOP or AbSPOP. Left: corresponding example images. Right: intensity quantification. B. Fgf3-GFP cellular localization (green channel of Figure 6F-G ) upon control (mutAbSPOP) and nuclear degradation (AbSPOP). Scale bars: (A) 20 µm. Methods Zebrafish handling and stocks Zebrafish (Danio rerio) strains were maintained as described in Westerfield 54 . Embryos were raised in E3 buffer between 26-30°C. All experiments were conducted on embryos younger than 3 dpf, under the guidelines of the European Commission, Directive 2010/63/EU. All chemical treatments were conducted on embryos dechorionated with pronase. Embryos were anesthetized with 0.01% Tricane for live imaging and prior to dissection or chemical fixation procedures. To prevent pigmentation when required, embryos were treated with 0.002% PTU at 24 hpf. For live imaging, embryos were mounted in 0.8% LMP agarose on glass-bottom dishes (MatTek) and kept at 28°C. The following established mutants and transgenics were used: cxcl12a t 30516 from Valentin et al. 35 , cxcr4b:nls-tdTomato from Donà et al. 30 , cldnb:lyn-GFP 25 , gal4(ETLGA346) uas:mCherry 55 , atoh:tdTomato 56 , uas:Cxcr7b-GFP 30 , cxcr4b:lexPR/lexop:lyn-RFP, lexop:Fgf3-GFP, lexop: secGFP, fgf3:Fg3-GFP and cxcr4b:cxcr4b-tagRFP from Durdu et al. 29 . Constructs and Transgenic generation LexOP and UAS responder lines were generated using MultiSite Gateway cloning (Invitrogen) and the Tol2kit 57 : i) LexOP(p5E)/GFP(pME)/fgf3(p3E), ii) UAS(p5E)/ cxcr7a(pME)/GFP(p3E), iii) LexOP(p5E)/cxcr7b(pME)/GFP(p3E), iv) LexOP(p5E)/ caFgfr1(pME)/RFP(p3E), v)LexOP(p5E)/Mycn(pME)/GFP(p3E). All destination vectors carried SV40poly(A) at the C terminus in the final construct. As a transgenic marker, all clones carried a cmlc2:eGFP cassette at the backbone. ca-Fgfr1a was cloned using the hs:caFgfr1 construct from Marques et al. 58 . FGF family and cxcr7a cDNAs were generated from total RNA extracts of zebrafish embryos at 30 hpf. FGF open-reading frames (ORFs) were cloned into CMV plasmids, with GFP inserted downstream of the signal peptide, following the same design used for Fgf3. twf2b:lyn-mKate2 was generated by inserting lyn-mKate2 in Twf2b BAC clone CH211-14I3, replacing the first exon. cxcr7b:cxcr7b-mKate2 was generated by inserting mKate2 in cxcr7b BAC clone DKEY-96H14 and cxcr7b:lyn-sfGFP was generated by inserting lyn-sfGFP in the cxcr7b BAC clone, replacing the first exon. Recombinations were carried out by ET recombineering (Gene Bridges). As a transgenic marker, cry:FP/KanR cassette was inserted into the BAC backbone to drive the FP expression in the eye lens. BACs were purified with Large Construct Kit (Qiagen) and transgenic lines were generated by injecting the constructs at one-cell stage. Colorimetric In-Situ Hybridization (ISH) pea3 , fgf3 and cxcr7 in situ hybridization (DIG probes, anti-DIG Alkaline Phosphatase coupled antibody, NBT/BCIP substrate at 30°C) were performed as described previously 28 , 35 . cxcr7a in situ hybridization was carried out according to standard protocols with probes generated from cxcr7a cDNA. All in-situ probes were hybridized at 65°C. To counter-label the primordium, anti-GFP antibody staining (rabbit-anti GFP primary antibody with Alexa488-anti-rabbit secondary antibody) was performed on cldnb:lyn-GFP transgenic embryos during ISH protocol as in Valentin et al. 35 . Fluorescence Recovery After Photobleaching Fluorescence Recovery After Photobleaching (FRAP) experiments were performed using an Ultraview VoX spinning disk microscope equipped with a photokinesis unit and Zeiss ×63 water objective. To monitor fluorescence recovery after photobleach, 5 pre-bleach and 45 post-bleach images were acquired at 30 ms per frame. The bleached region was defined with a strip ROI at the edge of the pool. Mean signal intensity over time was quantified in the bleached region, total pool, and the background to calculate recovery half-times. Measurements were imported into easyFRAP software 59 , and recovery curves were analyzed with full-scale normalization and double-term fitting. Single molecule fluorescence in situ hybridization Single molecule fluorescence in situ hybridization (smFISH) probes (Custom Stellaris FISH probes, Biosearch Technologies) for pea3 ( etv4 ), cxcr7b and tbx1 were designed using the Stellaris RNA FISH probe designer, comprising at least 40 sequence specific oligonucleotides (20bp each). Probes were conjugated to either Cal Fluor 590 (red) or Quasar 670 (far red) fluorophores. Hybridization, imaging and analysis were performed as described previously 29 . Clonal and transient misexpression Cell transplantation protocols 54 were used to generate Fgf3-GFP misexpression cell clones. Donor cells isolated from cxcr4b:LexPR, lexOP:lyn-RFP, lexOP:Fgf3-GFP, cxcr4b:nls-tdTomato transgenic embryos were transplanted into cldnb:lyn-GFP transgenic recipient embryos. Expression of Fgf3-GFP was induced with 10 µM RU486 at 24 hpf. Misexpression clones of caFgfr1 were generated by injection of lexOP:caFgfr1-RFP construct into cxcr4b:LexPR, cldnb:lyn-GFP transgenic embryos at one-cell stage. Expression was induced with 10 µM RU486 treatment at 24 hpf. RNA injections at one-cell stage were used to express H2B-RFP, nls-GFP, AbSPOP 46 and mutAbSPOP mRNAs, generated with in vitro transcription (Ambion mMessage mMachine Kit) using linearized SP6- or T7-containing plasmids. Transient expression of GFP- tagged Fgf2, Fgf3, Fgf4, Fgf8, Fgf10, Fgf13, Fgf19 and Fgf20 in early embryos was achieved by injecting CMV promoter-driven DNA constructs together with in vitro transcribed H2B-RFP RNA at one-cell stage. Mouse embryonic stem cells (mESCs) with doxycycline inducible gene expression system (HA36CB1Tet3G) were cultured as described in Durdu et.al., 2025 (DOI: 10.1016/j.molcel.2025.07.005). Briefly, cells were grown at 37°C 7% CO2, seeded on plates coated with 0.2% gelatin and maintained in Dulbecco’s modified Eagle medium (DMEM), supplemented with 15% fetal calf serum (FCS), Glutamax, nonessential amino acids, 0.001% 2-Mercaptoethanol and leukemia inhibitory factor (LIF). Cells were recombined with L1-TRE-FGF3-GFP-1L plasmid (where the tetracycline responsive element (TRE) promoter drives the expression of mouse FGF3, GFP tagged between the secretion signal peptide and the globular FGF domain). mESCs were either maintained in stem cell media (15%FCS+LIF) or differentiated through embryoid body formation (10%FCS+5µM retinoic acid). FGF3-GFP expression was induced with 1 ug/ml doxycycline and cells were imaged at 6-hour post induction. Gene expression profiling Three experimental groups were used for gene expression profiling: (i) wild type (cldnb:lyn-GFP, cxcr4b:nls-tdTomato) incubated with 10 µM RU486, 0.1% DMSO; (ii) FGF inhibition (cldnb:lyn-GFP, cxcr4b:nls-tdTomato) treated with 1 µM SU5402, 0.1% DMSO, 10 µM RU486; (iii) FGF induction (cldnb:lyn-GFP, cxcr4b:nls-tdTomato, cxcr4b:LexPR, lexOP:Fgf3-GFP) incubated with 10 µM RU486, 0.1% DMSO. Embryos at 24 hpf stage were treated with inducers and inhibitors for 6 hours. At least 300 transgenic embryos were used per sample. Embryos were dissected with a scalpel by separating trunks and collected in 2 ml tubes. Embryos were dissociated with FACSmax (Genlantis) and passed through 40 µm cell strainer. Around 20,000 cells were sorted by FACS using GFP, RFP and scatter parameters, with gating determined by the lack of lateral line cell populations in cxcl12a mutant embryos. Total RNA was extracted with the RNeasy kit (Qiagen) and stored at -80°C. RNA quality was validated, and concentration was measured with Qubit. Samples were processed as described in Affymetrix GeneChip System Protocol and hybridized to Zebrafish Gene ST 1.0 arrays. Analysis of the microarray data Affymetrix Power Tools (APT) was used to pre-process and normalize CEL files generated for each sample. Expression values of ‘meta’ probe sets (transcripts) were summarized with the Robust Microarray Analysis (RMA) approach 60 as implemented in APT (log2 transformed). Quality control of the samples was initially carried out by checking chips with outlier values of ‘average raw intensity signal’ and ‘mean absolute deviation of the residuals’. Detected above background (DABG) method was applied to estimate whether probe sets were higher than the background distribution. As recommended 61 , ‘main/meta’ probe sets were retained if half or more of the associated probe sets were detected (DABG, P value<0.05) in ≥50% of replicates of any condition 62 , 63 . Out of 40,344 ‘main/meta’ probe sets, 24,720 ‘main/ meta’ probe sets were retained for further analysis. They were annotated with the corresponding gene symbols (21,446 unique) derived from the Affymetrix-ZebGene-1_0-st-v1.na34.zv9.transcript data and through manual curation. Unsupervised hierarchical clustering of the samples (Pearson’s correlation coefficient, average-linkage) was used to examine outliers and batch effects. The limma package 64 (Smyth, 2004) available from Bioconductor 65 was used to identify differentially expressed genes for the comparisons of the biological groups while accounting for the batch of the replicate experiments. False discovery rate (FDR) was applied for multiple-test correction 66 . Heat maps representing the fold-changes in figures were generated in R. Protein structure models Protein sequences of all FGF family members were compared by multiple sequence alignment using the T-Coffee server 52 and visualized with ESPript 3.0 server 53 . For protein structure modeling, protein sequences for Fgf2, Fgf3, Fgf4, Fgf8a, Fgf10a, Fgf13a, Fgf19, and Fgf20a were retrieved from the SMART database 67 , selecting the “Acidic and basic fibroblast growth factor family” domains. Structural models were generated using AlphaFold3 68 ( https://alphafoldserver.com/ ) with default parameters, and model confidence was assessed via per-residue pLDDT scores. Electrostatic surfaces were computed using APBS 69 server ( https://server.poissonboltzmann.org/ ) after preprocessing with pdb2pqr 70 under standard settings. All models were superimposed in PyMOL 71 (v2.5.0) using the align function, and electrostatic surfaces and structural features were visualized using custom PyMOL scripts. Classical NLS are characterized by clusters of positively charged amino acids that are typically exposed in an extended loop conformation 72 . Based on this, we focused on a conserved site (motif 4 39 ) in Fgf3 with such structural potential. This site was compared across the zebrafish FGF family using multiple sequence alignment and subsequently examined in 3D structural models to assess its charge, surface exposure, and conformation. Statistical analysis All the statistical analysis was performed in R 73 . Comparisons between two groups were conducted using the non-parametric, two-sided Wilcoxon rank-sum test. Sample sizes (n) and P values ( P ) are provided for each experiment and indicated in figures ( *P < 0.05, **P < 0.01, ***P < 0.001). Boxplots are displayed as standard box-and-whisker plots indicating the median and interquartile range. For all experiments, individual data points were overlaid on the boxplots as scatter plots using the beeswarm package, enabling direct visualization of the sample variance and distribution. Scatter and line plots were generated with the ggplot2 package 74 in R. P values and sample sizes: Figure 1C : n WT = 4, n FGFRinh = 5, n FGFind = 6, ∼40 cells per fish, P WT-FGFRinh = 0.015, P WT-FGFind = 0.0095, P FGFRinh-FGFind = 0.051. Figure 4B : pea3 expression: n ctrl = 5, n FGF = 11, n neigh = 6, P ctrl-FGF = 4.6 × 10 −4 , P ctrl-neigh = 4.3 × 10 −3 , P FGF-neigh = 0.88; cxcr7 expression: n ctrl = 10, n FGF = 13, n neigh = 7, P ctrl-FGF = 1.7 × 10 −4 , P ctrl-neigh = 0.53, P FGF-neigh = 1.2 × 10 −3 . Figure 5D : Calculated mobile fraction: nls-GFP 0.98, Fgf3-GFP 0.83, Mycn-GFP 0.86; t 1/2 (s): nls-GFP 0.24, Fgf3-GFP 0.95, Mycn-GFP 0.97. Figure 6D : n ctrl = 6, n nonsecFgf3 = 6, n Fgf3 = 6, pea3 : P ctrl-nonsecFgf3 = 4.6 × 10 −4 ; cxcr7b: P ctrl-nonsecFgf3 = 2.2 × 10 −3 , P ctrl-Fgf3 = 2.2 × 10 −3 , P nonsecFgf3-Fgf3 = 2.2 × 10 −3 . Figure 6H : pea3 : n mutAbSPOP = 8, n mutAbSPOP = 8, P Pea3 = 1; cxcr7b : n mutAbSPOP = 18, n mutAbSPOP = 24, P Cxcr7b = 1.1 × 10 −8 . Figure S3E : n cxcr7b -/- = 15, n cxcr7b -/-uas Cxcr7a misexp = 14, P ( cxcr7b -/-)-( cxcr7b -/-uas Cxcr7a misexp) = 2.6 × 10 −8 . Acknowledgements We acknowledge Gilmour laboratory for discussions and Noa Gil and Sena A. Uslu for feedback on the manuscript. We thank Andrea Gruia, Celine Revenu, Ulrike Schulze, E.D., A.K. and M.I. for the help with preprocessing embryos. We thank EMBL core facilities, Vladimir Benes and Jelena Pistolic (Genecore), Alex Perez Gonzalez (FACS), Yury Belyaev, Kota Miura, Stefan Terjung (ALMF). We thank Andrea Gruia (EMBL) and Cornelia Henkel (MLS-UZH) for fish care. S.D. acknowledges the EMBO Long-Term fellowship (ALTF 1101) and the Christiane-Nüsslein-Volhard stipend. D.S. acknowledges EU Horizon 2020 ERC Advanced Grant (884664) and support from Novartis Research Foundation. D.G. acknowledges the SNSF Grant (31003A_176235) and support from University of Zürich. E.K. acknowledges support from Izmir Biomedicine and Genome Center. E.D. acknowledges support from CNR Neuroscience Institute. Footnotes ↵ † Latest affiliation Abstract and discussion rephrased, further supplementary data added. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE207538 References 1. ↵ Li , P. , and Elowitz , M.B . ( 2019 ). Communication codes in developmental signaling pathways . Development 146 . doi: 10.1242/DEV.170977 . OpenUrl CrossRef 2. Hill , C.S. , and Treisman , R . ( 1995 ). Transcriptional regulation by extracellular signals: mechanisms and specificity . Cell 80 , 199 – 211 . doi: 10.1016/0092-8674(95)90403-4 . OpenUrl CrossRef PubMed Web of Science 3. ↵ Perrimon , N. , Pitsouli , C. , and Shilo , B.Z . ( 2012 ). Signaling mechanisms controlling cell fate and embryonic patterning . Cold Spring Harb Perspect Biol 4 . doi: 10.1101/CSHPERSPECT.A005975 . OpenUrl CrossRef 4. ↵ Martin , G.R . ( 1998 ). The roles of FGFs in the early development of vertebrate limbs . Genes Dev 12 , 1571 – 1586 . doi: 10.1101/GAD.12.11.1571 . OpenUrl FREE Full Text 5. Böttcher , R.T. , and Niehrs , C . ( 2005 ). Fibroblast growth factor signaling during early vertebrate development . Endocr Rev 26 , 63 – 77 . doi: 10.1210/ER.2003-0040 . OpenUrl CrossRef PubMed Web of Science 6. Dorey , K. , and Amaya , E . ( 2010 ). FGF signalling: diverse roles during early vertebrate embryogenesis . Development 137 , 3731 – 3742 . doi: 10.1242/DEV.037689 . OpenUrl Abstract / FREE Full Text 7. ↵ Ornitz , D.M. , and Itoh , N . ( 2015 ). The Fibroblast Growth Factor signaling pathway . Wiley Interdiscip Rev Dev Biol 4 , 215 – 266 . doi: 10.1002/WDEV.176 . OpenUrl CrossRef PubMed 8. ↵ Sagner , A. , and Briscoe , J . ( 2017 ). Morphogen interpretation: concentration, time, competence, and signaling dynamics . Wiley Interdiscip Rev Dev Biol 6 . doi: 10.1002/WDEV.271 . OpenUrl CrossRef 9. Kicheva , A. , and Briscoe , J . ( 2023 ). Control of Tissue Development by Morphogens . Annu Rev Cell Dev Biol 39 , 91 – 121 . doi: 10.1146/ANNUREV-CELLBIO-020823-011522 . OpenUrl CrossRef PubMed 10. Mosby , L.S. , Bowen , A.E. , and Hadjivasiliou , Z . ( 2024 ). Morphogens in the evolution of size, shape and patterning . Development 151 . doi: 10.1242/DEV.202412 . OpenUrl CrossRef 11. ↵ Stapornwongkul , K.S. , and Vincent , J.P . ( 2021 ). Generation of extracellular morphogen gradients: the case for diffusion . Nat Rev Genet 22 , 393 – 411 . doi: 10.1038/S41576-021-00342-Y . OpenUrl CrossRef PubMed 12. ↵ Bertrand , V. , Hudson , C. , Caillol , D. , Popovici , C. , and Lemaire , P . ( 2003 ). Neural Tissue in Ascidian Embryos Is Induced by FGF9/16/20, Acting via a Combination of Maternal GATA and Ets Transcription Factors . Cell 115 , 615 – 627 . doi: 10.1016/S0092-8674(03)00928-0 . OpenUrl CrossRef PubMed Web of Science 13. Brent , A.E. , and Tabin , C.J . ( 2004 ). FGF acts directly on the somitic tendon progenitors through the Ets transcription factors Pea3 and Erm to regulate scleraxis expression . Development 131 , 3885 – 3896 . doi: 10.1242/DEV.01275 . OpenUrl Abstract / FREE Full Text 14. ↵ Raible , F. , and Brand , M . ( 2001 ). Tight transcriptional control of the ETS domain factors Erm and Pea3 by Fgf signaling during early zebrafish development . Mech Dev 107 , 105 – 117 . doi: 10.1016/S0925-4773(01)00456-7 . OpenUrl CrossRef PubMed Web of Science 15. ↵ Roehl , H. , and Nüsslein-Volhard , C . ( 2001 ). Zebrafish pea3 and erm are general targets of FGF8 signaling . Curr Biol 11 , 503 – 507 . doi: 10.1016/S0960-9822(01)00143-9 . OpenUrl CrossRef PubMed Web of Science 16. ↵ Dailey , L. , Ambrosetti , D. , Mansukhani , A. , and Basilico , C . ( 2005 ). Mechanisms underlying differential responses to FGF signaling . Cytokine Growth Factor Rev 16 , 233 – 247 . doi: 10.1016/J.CYTOGFR.2005.01.007 . OpenUrl CrossRef PubMed Web of Science 17. ↵ Ingham , P.W. , and McMahon , A.P . ( 2001 ). Hedgehog signaling in animal development: paradigms and principles . Genes Dev 15 , 3059 – 3087 . doi: 10.1101/GAD.938601 . OpenUrl FREE Full Text 18. ↵ Artavanis-Tsakonas , S. , Rand , M.D. , and Lake , R.J . ( 1999 ). Notch signaling: Cell fate control and signal integration in development . Science (1979) 284 , 770 – 776 . doi: 10.1126/SCIENCE.284.5415.770/ASSET/355D0AAB-3A6D-428F-B213-5F1C35A50AB7/ASSETS/GRAPHIC/SE1797476004.JPEG . OpenUrl Abstract / FREE Full Text 19. ↵ Lecuit , T. , and Cohen , S.M . ( 1998 ). Dpp receptor levels contribute to shaping the Dpp morphogen gradient in the Drosophila wing imaginal disc . Development 125 , 4901 – 4907 . doi: 10.1242/dev.125.24.4901 . OpenUrl Abstract 20. ↵ Ghysen , A. , and Dambly-Chaudière , C . ( 2004 ). Development of the zebrafish lateral line . Curr Opin Neurobiol 14 , 67 – 73 . doi: 10.1016/j.conb.2004.01.012 . OpenUrl CrossRef PubMed Web of Science 21. Ghysen , A. , and Dambly-Chaudière , C . ( 2007 ). The lateral line microcosmos . Genes Dev 21 , 2118 – 2130 . doi: 10.1101/GAD.1568407 . OpenUrl Abstract / FREE Full Text 22. ↵ Revenu , C. , Streichan , S. , Donà , E. , Lecaudey , V. , Hufnagel , L. , and Gilmour , D . ( 2014 ). Quantitative cell polarity imaging defines leader-to-follower transitions during collective migration and the key role of microtubule-dependent adherens junction formation . Development 141 , 1282 – 1291 . doi: 10.1242/DEV.101675 . OpenUrl Abstract / FREE Full Text 23. ↵ Thomas , E.D. , Cruz , I.A. , Hailey , D.W. , and Raible , D.W . ( 2015 ). There and back again: development and regeneration of the zebrafish lateral line system . Wiley Interdiscip Rev Dev Biol 4 , 1 – 16 . doi: 10.1002/WDEV.160 . OpenUrl CrossRef PubMed 24. Chitnis , A.B. , Dalle Nogare , D. , and Matsuda , M . ( 2012 ). Building the posterior lateral line system in zebrafish . Dev Neurobiol 72 , 234 – 255 . doi: 10.1002/DNEU.20962 . OpenUrl CrossRef PubMed 25. ↵ Haas , P. , and Gilmour , D . ( 2006 ). Chemokine signaling mediates self-organizing tissue migration in the zebrafish lateral line . Dev Cell 10 , 673 – 680 . doi: 10.1016/J.DEVCEL.2006.02.019 . OpenUrl CrossRef PubMed Web of Science 26. ↵ Wang , J. , Yin , Y. , Lau , S. , Sankaran , J. , Rothenberg , E. , Wohland , T. , Meier-Schellersheim , M. , and Knaut , H . ( 2018 ). Anosmin1 Shuttles Fgf to Facilitate Its Diffusion, Increase Its Local Concentration, and Induce Sensory Organs . Dev Cell 46 , 751 – 766 .e12. doi: 10.1016/j.devcel.2018.07.015 . OpenUrl CrossRef PubMed 27. ↵ Pines , O. , Horwitz , M. , and Herrmann , J.M . ( 2024 ). Privileged proteins with a second residence: dual targeting and conditional re-routing of mitochondrial proteins . FEBS J 291 , 5379 – 5393 . doi: 10.1111/febs.17191 . OpenUrl CrossRef PubMed 28. ↵ Lecaudey , V. , Cakan-Akdogan , G. , Norton , W.H.J. , and Gilmour , D . ( 2008 ). Dynamic Fgf signaling couples morphogenesis and migration in the zebrafish lateral line primordium . Development 135 , 2695 – 2705 . doi: 10.1242/DEV.025981 . OpenUrl Abstract / FREE Full Text 29. ↵ Durdu , S. , Iskar , M. , Revenu , C. , Schieber , N. , Kunze , A. , Bork , P. , Schwab , Y. , and Gilmour , D . ( 2014 ). Luminal signalling links cell communication to tissue architecture during organogenesis . Nature 515 , 120 – 124 . doi: 10.1038/NATURE13852 . OpenUrl CrossRef PubMed 30. ↵ Donà , E. , Barry , J.D. , Valentin , G. , Quirin , C. , Khmelinskii , A. , Kunze , A. , Durdu , S. , Newton , L.R. , Fernandez-Minan , A. , Huber , W. , et al. ( 2013 ). Directional tissue migration through a self-generated chemokine gradient . Nature 503 , 285 – 289 . doi: 10.1038/NATURE12635 . OpenUrl CrossRef PubMed Web of Science 31. ↵ Ma , E.Y. , and Raible , D.W . ( 2009 ). Signaling pathways regulating zebrafish lateral line development . Curr Biol 19 . doi: 10.1016/J.CUB.2009.03.057 . OpenUrl CrossRef 32. McGraw , H.F. , Drerup , C.M. , Culbertson , M.D. , Linbo , T. , Raible , D.W. , and Nechiporuk , A. V . ( 2011 ). Lef1 is required for progenitor cell identity in the zebrafish lateral line primordium . Development 138 , 3921 – 3930 . doi: 10.1242/DEV.062554 . OpenUrl Abstract / FREE Full Text 33. ↵ Aman , A. , and Piotrowski , T . ( 2008 ). Wnt/beta-catenin and Fgf signaling control collective cell migration by restricting chemokine receptor expression . Dev Cell 15 , 749 – 761 . doi: 10.1016/J.DEVCEL.2008.10.002 . OpenUrl CrossRef PubMed Web of Science 34. ↵ Dambly-Chaudière , C. , Cubedo , N. , and Ghysen , A . ( 2007 ). Control of cell migration in the development of the posterior lateral line: antagonistic interactions between the chemokine receptors CXCR4 and CXCR7/RDC1 . BMC Dev Biol 7 . doi: 10.1186/1471-213X-7-23 . OpenUrl CrossRef PubMed 35. ↵ Valentin , G. , Haas , P. , and Gilmour , D . ( 2007 ). The chemokine SDF1a coordinates tissue migration through the spatially restricted activation of Cxcr7 and Cxcr4b . Curr Biol 17 , 1026 – 1031 . doi: 10.1016/J.CUB.2007.05.020 . OpenUrl CrossRef PubMed Web of Science 36. ↵ Nechiporuk , A. , and Raible , D.W . ( 2008 ). FGF-dependent mechanosensory organ patterning in zebrafish . Science 320 , 1774 – 1777 . doi: 10.1126/SCIENCE.1156547 . OpenUrl Abstract / FREE Full Text 37. ↵ Popovici , C. , Roubin , R. , Coulier , F. , and Birnbaum , D . ( 2005 ). An evolutionary history of the FGF superfamily . Bioessays 27 , 849 – 857 . doi: 10.1002/BIES.20261 . OpenUrl CrossRef PubMed Web of Science 38. ↵ Abramson , J. , Adler , J. , Dunger , J. , Evans , R. , Green , T. , Pritzel , A. , Ronneberger , O. , Willmore , L. , Ballard , A.J. , Bambrick , J. , et al. ( 2024 ). Accurate structure prediction of biomolecular interactions with AlphaFold 3 . Nature 630 , 493 – 500 . doi: 10.1038/S41586-024-07487-W . OpenUrl CrossRef PubMed 39. ↵ Kiefer , P. , and Dickson , C . ( 1995 ). Nucleolar association of fibroblast growth factor 3 via specific sequence motifs has inhibitory effects on cell growth . Mol Cell Biol 15 , 4364 – 4374 . doi: 10.1128/MCB.15.8.4364 . OpenUrl Abstract / FREE Full Text 40. ↵ Goetz , R. , Beenken , A. , Ibrahimi , O.A. , Kalinina , J. , Olsen , S.K. , Eliseenkova , A. V. , Xu , C. , Neubert , T.A. , Zhang , F. , Linhardt , R.J. , et al. ( 2007 ). Molecular insights into the klotho-dependent, endocrine mode of action of fibroblast growth factor 19 subfamily members . Mol Cell Biol 27 , 3417 – 3428 . doi: 10.1128/MCB.02249-06 . OpenUrl Abstract / FREE Full Text 41. ↵ Wu , X. , and Li , Y . ( 2012 ). Understanding the structure-function relationship between FGF19 and its mitogenic and metabolic activities . Adv Exp Med Biol 728 , 195 – 213 . doi: 10.1007/978-1-4614-0887-1_13 . OpenUrl CrossRef PubMed 42. ↵ Foletti , A. , Vuadens , F. , and Beermann , F . ( 2003 ). Nuclear localization of mouse fibroblast growth factor 2 requires N-terminal and C-terminal sequences . Cell Mol Life Sci 60 , 2254 – 2265 . doi: 10.1007/S00018-003-3258-6 . OpenUrl CrossRef PubMed 43. ↵ Beenken , A. , and Mohammadi , M . ( 2009 ). The FGF family: biology, pathophysiology and therapy . Nat Rev Drug Discov 8 , 235 – 253 . doi: 10.1038/NRD2792 . OpenUrl CrossRef PubMed Web of Science 44. ↵ Wiȩdłocha , A. , and Sørensen , V. ( 2004 ). Signaling, internalization, and intracellular activity of fibroblast growth factor . Curr Top Microbiol Immunol 286 , 45 – 79 . doi: 10.1007/978-3-540-69494-6_3 . OpenUrl CrossRef PubMed 45. ↵ Kiefer , P. , Strähle , U. , and Dickson , C . ( 1996 ). The zebrafish Fgf-3 gene: CDNA sequence, transcript structure and genomic organization . Gene 168 , 211 – 215 . doi: 10.1016/0378-1119(95)00736-9 . OpenUrl CrossRef PubMed Web of Science 46. ↵ Shin , Y.J. , Park , S.K. , Jung , Y.J. , Kim , Y.N. , Kim , K.S. , Park , O.K. , Kwon , S.H. , Jeon , S.H. , Trinh , L.A. , Fraser , S.E. , et al. ( 2015 ). Nanobody-targeted E3-ubiquitin ligase complex degrades nuclear proteins . Sci Rep 5 , 14269 . doi: 10.1038/srep14269 . OpenUrl CrossRef PubMed 47. ↵ Ebeid , M. , and Huh , S.H . ( 2017 ). FGF signaling: diverse roles during cochlear development . BMB Rep 50 , 487 – 495 . doi: 10.5483/BMBREP.2017.50.10.164 . OpenUrl CrossRef PubMed 48. ↵ Gardiner , J.R. , Jackson , A.L. , Gordon , J. , Lickert , H. , Manley , N.R. , and Albert Basson , M . ( 2012 ). Localised inhibition of FGF signalling in the third pharyngeal pouch is required for normal thymus and parathyroid organogenesis . Development 139 , 3456 – 3466 . doi: 10.1242/DEV.079400 . OpenUrl Abstract / FREE Full Text 49. ↵ Alshoubaki , Y.K. , Lu , Y.-Z. , Legrand , J.M.D. , Karami , R. , Fossat , M. , Salimova , E. , Julier , Z. , and Martino , M.M . ( 2023 ). A superior extracellular matrix binding motif to enhance the regenerative activity and safety of therapeutic proteins . NPJ Regen Med 8 , 25 . doi: 10.1038/s41536-023-00297-0 . OpenUrl CrossRef PubMed 50. ↵ Xie , Y. , Su , N. , Yang , J. , Tan , Q. , Huang , S. , Jin , M. , Ni , Z. , Zhang , B. , Zhang , D. , Luo , F. , et al. ( 2020 ). FGF/FGFR signaling in health and disease . Signal Transduct Target Ther 5 . doi: 10.1038/S41392-020-00222-7 . OpenUrl CrossRef 51. ↵ Mikolajczak , M. , Goodman , T. , and Hajihosseini , M.K . ( 2016 ). Interrogation of a lacrimo-auriculo-dento-digital syndrome protein reveals novel modes of fibroblast growth factor 10 (FGF10) function . Biochem J 473 , 4593 – 4607 . doi: 10.1042/BCJ20160441 . OpenUrl Abstract / FREE Full Text 52. ↵ Di Tommaso , P. , Moretti , S. , Xenarios , I. , Orobitg , M. , Montanyola , A. , Chang , J.M. , Taly , J.F. , and Notredame , C. ( 2011 ). T-Coffee: a web server for the multiple sequence alignment of protein and RNA sequences using structural information and homology extension . Nucleic Acids Res 39 . doi: 10.1093/NAR/GKR245 . OpenUrl CrossRef 53. ↵ Robert , X. , and Gouet , P . ( 2014 ). Deciphering key features in protein structures with the new ENDscript server . Nucleic Acids Res 42 . doi: 10.1093/NAR/GKU316 . OpenUrl CrossRef 54. ↵ Westerfield , M . ( 2007 ). The Zebrafish Book; A guide for the laboratory use of zebrafish (Danio rerio) . Univ. Oregon Press . 55. ↵ Distel , M. , Wullimann , M.F. , and Köster , R.W . ( 2009 ). Optimized Gal4 genetics for permanent gene expression mapping in zebrafish . Proc Natl Acad Sci U S A 106 , 13365 – 13370 . doi: 10.1073/PNAS.0903060106 . OpenUrl Abstract / FREE Full Text 56. ↵ Wada , H. , Ghysen , A. , Satou , C. , Higashijima , S. ichi , Kawakami , K. , Hamaguchi , S. , and Sakaizumi , M. ( 2010 ). Dermal morphogenesis controls lateral line patterning during postembryonic development of teleost fish . Dev Biol 340 , 583 – 594 . doi: 10.1016/J.YDBIO.2010.02.017 . OpenUrl CrossRef PubMed 57. ↵ Kwan , K.M. , Fujimoto , E. , Grabher , C. , Mangum , B.D. , Hardy , M.E. , Campbell , D.S. , Parant , J.M. , Yost , H.J. , Kanki , J.P. , and Chien , C. Bin ( 2007 ). The Tol2kit: a multisite gateway-based construction kit for Tol2 transposon transgenesis constructs . Dev Dyn 236 , 3088 – 3099 . doi: 10.1002/DVDY.21343 . OpenUrl CrossRef PubMed Web of Science 58. ↵ Marques , S.R. , Lee , Y. , Poss , K.D. , and Yelon , D . ( 2008 ). Reiterative roles for FGF signaling in the establishment of size and proportion of the zebrafish heart . Dev Biol 321 , 397 – 406 . doi: 10.1016/J.YDBIO.2008.06.033 . OpenUrl CrossRef PubMed Web of Science 59. ↵ Rapsomaniki , M.A. , Kotsantis , P. , Symeonidou , I.E. , Giakoumakis , N.N. , Taraviras , S. , and Lygerou , Z . ( 2012 ). easyFRAP: an interactive, easy-to-use tool for qualitative and quantitative analysis of FRAP data . Bioinformatics 28 , 1800 – 1801 . doi: 10.1093/BIOINFORMATICS/BTS241 . OpenUrl CrossRef PubMed Web of Science 60. ↵ Irizarry , R.A. , Hobbs , B. , Collin , F. , Beazer-Barclay , Y.D. , Antonellis , K.J. , Scherf , U. , and Speed , T.P . ( 2003 ). Exploration, normalization, and summaries of high density oligonucleotide array probe level data . Biostatistics 4 , 249 – 264 . doi: 10.1093/BIOSTATISTICS/4.2.249 . OpenUrl CrossRef PubMed Web of Science 61. ↵ Lockstone , H.E . ( 2011 ). Exon array data analysis using Affymetrix power tools and R statistical software . Brief Bioinform 12 , 634 – 644 . doi: 10.1093/BIB/BBQ086 . OpenUrl CrossRef PubMed 62. ↵ Lockstone , H.E . ( 2011 ). Exon array data analysis using Affymetrix power tools and R statistical software . Brief Bioinform 12 , 634 – 644 . doi: 10.1093/BIB/BBQ086 . OpenUrl CrossRef PubMed 63. ↵ Mackmull , M.T. , Iskar , M. , Parca , L. , Singer , S. , Bork , P. , Ori , A. , and Beck , M . ( 2015 ). Histone Deacetylase Inhibitors (HDACi) Cause the Selective Depletion of Bromodomain Containing Proteins (BCPs) . Mol Cell Proteomics 14 , 1350 – 1360 . doi: 10.1074/MCP.M114.042499 . OpenUrl Abstract / FREE Full Text 64. ↵ Ritchie , M.E. , Phipson , B. , Wu , D. , Hu , Y. , Law , C.W. , Shi , W. , and Smyth , G.K . ( 2015 ). limma powers differential expression analyses for RNA-sequencing and microarray studies . Nucleic Acids Res 43 , e47 . doi: 10.1093/NAR/GKV007 . OpenUrl CrossRef PubMed 65. ↵ Gentleman , R.C. , Carey , V.J. , Bates , D.M. , Bolstad , B. , Dettling , M. , Dudoit , S. , Ellis , B. , Gautier , L. , Ge , Y. , Gentry , J. , et al. ( 2004 ). Bioconductor: open software development for computational biology and bioinformatics . SpringerPaperpileRC Gentleman , VJ Carey , DM Bates , B Bolstad , M Dettling , S Dudoit , B Ellis , L Gautier , Y GeGenome biology, 2004•SpringerSign in 5. 66. ↵ Benjamini , Y. , and Hochberg , Y . ( 1995 ). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing . J R Stat Soc Series B Stat Methodol 57 . doi: 10.1111/j.2517-6161.1995.tb02031.x . OpenUrl CrossRef PubMed 67. ↵ Letunic , I. , Khedkar , S. , and Bork , P . ( 2021 ). SMART: Recent updates, new developments and status in 2020 . Nucleic Acids Res 49 , D458 – D460 . doi: 10.1093/NAR/GKAA937 ,. OpenUrl CrossRef PubMed 68. ↵ Abramson , J. , Adler , J. , Dunger , J. , Evans , R. , Green , T. , Pritzel , A. , Ronneberger , O. , Willmore , L. , Ballard , A.J. , Bambrick , J. , et al. ( 2024 ). Accurate structure prediction of biomolecular interactions with AlphaFold 3 . Nature 630 , 493 – 500 . doi: 10.1038/S41586-024-07487-W . OpenUrl CrossRef PubMed 69. ↵ Jurrus , E. , Engel , D. , Star , K. , Monson , K. , Brandi , J. , Felberg , L.E. , Brookes , D.H. , Wilson , L. , Chen , J. , Liles , K. , et al. ( 2018 ). Improvements to the APBS biomolecular solvation software suite . Protein Science 27 , 112 – 128 . doi: 10.1002/PRO.3280 , OpenUrl CrossRef 70. ↵ Dolinsky , T.J. , Czodrowski , P. , Li , H. , Nielsen , J.E. , Jensen , J.H. , Klebe , G. , and Baker , N.A . ( 2007 ). PDB2PQR: Expanding and upgrading automated preparation of biomolecular structures for molecular simulations . Nucleic Acids Res 35 . doi: 10.1093/NAR/GKM276 ,. OpenUrl CrossRef 71. ↵ Lunin , V.Y. , Urzhumtsev , A. , Bockmayr , A. , Fokin , A. , Urzhumtsev , A. , Afonine , P. , Lunin , V.Y. , Harding , M. , Turkenburg , M. , Ballard , C. , et al. Pymol: An open-source molecular graphics tool . CiteseerWL DeLanoCCP4 Newsl . Protein Crystallogr, 2002 •Citeseer. 72. ↵ Lange , A. , Mills , R.E. , Lange , C.J. , Stewart , M. , Devine , S.E. , and Corbett , A.H . ( 2007 ). Classical Nuclear Localization Signals: Definition, Function, and Interaction with Importin α . Journal of Biological Chemistry 282 , 5101 – 5105 . doi: 10.1074/jbc.R600026200 . OpenUrl Abstract / FREE Full Text 73. ↵ R Core Team . ( 2023 ). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria . Open J Stat 13 . 74. ↵ Wickham , H. ( 2016 ). ggplot2: Elegant Graphics for Data Analysis ( Springer-Verlag New York ). View the discussion thread. Back to top Previous Next Posted October 17, 2025. Download PDF Data/Code Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Nuclear rerouting of paracrine Fgf3 in source cells represses target genes to pattern morphogen responses Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Nuclear rerouting of paracrine Fgf3 in source cells represses target genes to pattern morphogen responses Sevi Durdu , Murat Iskar , Alicia Roig-Merino , Elisa Gallo , Ezgi Karaca , Andreas Kunze , Erika Donà , Dirk Schübeler , Peer Bork , Darren Gilmour bioRxiv 2025.07.24.666518; doi: https://doi.org/10.1101/2025.07.24.666518 Share This Article: Copy Citation Tools Nuclear rerouting of paracrine Fgf3 in source cells represses target genes to pattern morphogen responses Sevi Durdu , Murat Iskar , Alicia Roig-Merino , Elisa Gallo , Ezgi Karaca , Andreas Kunze , Erika Donà , Dirk Schübeler , Peer Bork , Darren Gilmour bioRxiv 2025.07.24.666518; doi: https://doi.org/10.1101/2025.07.24.666518 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Developmental Biology Subject Areas All Articles Animal Behavior and Cognition (7642) Biochemistry (17715) Bioengineering (13907) Bioinformatics (42005) Biophysics (21472) Cancer Biology (18624) Cell Biology (25534) Clinical Trials (138) Developmental Biology (13390) Ecology (19935) Epidemiology (2067) Evolutionary Biology (24356) Genetics (15617) Genomics (22529) Immunology (17753) Microbiology (40437) Molecular Biology (17200) Neuroscience (88697) Paleontology (667) Pathology (2840) Pharmacology and Toxicology (4829) Physiology (7653) Plant Biology (15171) Scientific Communication and Education (2046) Synthetic Biology (4304) Systems Biology (9827) Zoology (2272)