Detailed stratified GWAS analysis for severe COVID-19 in four European populations

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended genome-wide association meta-analysis of a well-characterized cohort of 3255 COVID-19 patients with respiratory failure and 12 488 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a ~0.9-Mb inversion polymorphism that creates two highly differentiated haplotypes and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative including non-Caucasian individuals, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.S.E.H. and C.A.S. partially supported genotyping through a philanthropic donation. A.F. and D.E. were supported by a grant from the German Federal Ministry of Education and COVID-19 grant Research (BMBF; ID:01KI20197); A.F., D.E. and F.D. were supported by the Deutsche Forschungsgemeinschaft Cluster of Excellence ‘Precision Medicine in Chronic Inflammation’ (EXC2167). D.E. was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). D.E., K.B. and S.B. acknowledge the Novo Nordisk Foundation (NNF14CC0001 and NNF17OC0027594). T.L.L., A.T. and O.Ö. were funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project numbers 279645989; 433116033; 437857095. M.W. and H.E. are supported by the German Research Foundation (DFG) through the Research Training Group 1743, ‘Genes, Environment and Inflammation’. L.V. received funding from: Ricerca Finalizzata Ministero della Salute (RF-2016-02364358), Italian Ministry of Health ‘CV PREVITAL’—strategie di prevenzione primaria cardiovascolare primaria nella popolazione italiana; The European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- and for the project ‘REVEAL’; Fondazione IRCCS Ca’ Granda ‘Ricerca corrente’, Fondazione Sviluppo Ca’ Granda ‘Liver-BIBLE’ (PR-0391), Fondazione IRCCS Ca’ Granda ‘5permille’ ‘COVID-19 Biobank’ (RC100017A). A.B. was supported by a grant from Fondazione Cariplo to Fondazione Tettamanti: ‘Bio-banking of Covid-19 patient samples to support national and international research (Covid-Bank). This research was partly funded by an MIUR grant to the Department of Medical Sciences, under the program ‘Dipartimenti di Eccellenza 2018–2022’. This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació IGTP (The Institute for Health Science Research Germans Trias i Pujol) IGTP is part of the CERCA Program/Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIII-MINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). M.M. received research funding from grant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (European Regional Development Fund (FEDER)-Una manera de hacer Europa’). B.C. is supported by national grants PI18/01512. X.F. is supported by the VEIS project (001-P-001647) (co-funded by the European Regional Development Fund (ERDF), ‘A way to build Europe’). Additional data included in this study were obtained in part by the COVICAT Study Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, European Institute of Innovation & Technology (EIT), a body of the European Union, COVID-19 Rapid Response activity 73A and SR20-01024 La Caixa Foundation. A.J. and S.M. were supported by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). A.J. was also supported by national grant PI17/00019 from the Acción Estratégica en Salud (ISCIII) and the European Regional Development Fund (FEDER). The Basque Biobank, a hospital-related platform that also involves all Osakidetza health centres, the Basque government’s Department of Health and Onkologikoa, is operated by the Basque Foundation for Health Innovation and Research-BIOEF. M.C. received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de Investigación (AEI, Spain) and the European Regional Development Fund (FEDER, EU). M.R.G., J.A.H., R.G.D. and D.M.M. are supported by the ‘Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III’ (PI19/01404, PI16/01842, PI19/00589, PI17/00535 and GLD19/00100) and by the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018, COVID-Premed, COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant FI20/00215, PFIS Contratos Predoctorales de Formación en Investigación en Salud. Enrique Calderón’s team is supported by CIBER of Epidemiology and Public Health (CIBERESP), ‘Instituto de Salud Carlos III’. J.C.H. reports grants from Research Council of Norway grant no 312780 during the conduct of the study. E.S. reports grants from Research Council of Norway grant no. 312769. The BioMaterialBank Nord is supported by the German Center for Lung Research (DZL), Airway Research Center North (ARCN). The BioMaterialBank Nord is member of popgen 2.0 network (P2N). P.K. Bergisch Gladbach, Germany and the Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. He is supported by the German Federal Ministry of Education and Research (BMBF). O.A.C. is supported by the German Federal Ministry of Research and Education and is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy—CECAD, EXC 2030–390661388. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. This work was supported by grants of the Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland and Lower Saxony. K.U.L. is supported by the German Research Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the Institute of Human Genetics, University Hospital Bonn. F.H. was supported by the Bavarian State Ministry for Science and Arts. Part of the genotyping was supported by a grant to A.R. from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA BioBank, EADB) within the context of the EU Joint Programme—Neurodegenerative Disease Research (JPND). Additional funding was derived from the German Research Foundation (DFG) grant: RA 1971/6-1 to A.R. P.R. is supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH state funds for COVID19 research). F.T. is supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence ‘Precision Medicine in Chronic Inflammation’ (EXC2167). C.L. and J.H. are supported by the German Center for Infection Research (DZIF). T.B., M.M.B., O.W. und A.H. are supported by the Stiftung Universitätsmedizin Essen. M.A.-H. was supported by Juan de la Cierva Incorporacion program, grant IJC2018-035131-I funded by MCIN/AEI/10.13039/501100011033. E.C.S. is supported by the Deutsche Forschungsgemeinschaft (DFG; SCHU 2419/2-1).Peer reviewe

Detailed stratified GWAS analysis for severe COVID-19 in four European populations

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of a well-characterized cohort of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen (HLA) region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a highly pleiotropic ∼0.9-Mb inversion polymorphism and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.Andre Franke and David Ellinghaus were supported by a grant from the German Federal Ministry of Education and Research (01KI20197), Andre Franke, David Ellinghaus and Frauke Degenhardt were supported by the Deutsche Forschungsgemeinschaft Cluster of Excellence “Precision Medicine in Chronic Inflammation” (EXC2167). David Ellinghaus was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). David Ellinghaus, Karina Banasik and Søren Brunak acknowledge the Novo Nordisk Foundation (grant NNF14CC0001 and NNF17OC0027594). Tobias L. Lenz, Ana Teles and Onur Özer were funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project numbers 279645989; 433116033; 437857095. Mareike Wendorff and Hesham ElAbd are supported by the German Research Foundation (DFG) through the Research Training Group 1743, "Genes, Environment and Inflammation". This project was supported by a Covid-19 grant from the German Federal Ministry of Education and Research (BMBF; ID: 01KI20197). Luca Valenti received funding from: Ricerca Finalizzata Ministero della Salute RF2016-02364358, Italian Ministry of Health ""CV PREVITAL – strategie di prevenzione primaria cardiovascolare primaria nella popolazione italiana; The European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- and for the project ""REVEAL""; Fondazione IRCCS Ca' Granda ""Ricerca corrente"", Fondazione Sviluppo Ca' Granda ""Liver-BIBLE"" (PR-0391), Fondazione IRCCS Ca' Granda ""5permille"" ""COVID-19 Biobank"" (RC100017A). Andrea Biondi was supported by the grant from Fondazione Cariplo to Fondazione Tettamanti: "Biobanking of Covid-19 patient samples to support national and international research (Covid-Bank). This research was partly funded by a MIUR grant to the Department of Medical Sciences, under the program "Dipartimenti di Eccellenza 2018–2022". This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació IGTP. IGTP is part of the CERCA Program / Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIIIMINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). Marta Marquié received research funding from ant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIIISubdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER-Una manera de hacer Europa").Beatriz Cortes is supported by national grants PI18/01512. Xavier Farre is supported by VEIS project (001-P-001647) (cofunded by European Regional Development Fund (ERDF), “A way to build Europe”). Additional data included in this study was obtained in part by the COVICAT Study Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, EIT COVID-19 Rapid Response activity 73A and SR20-01024 La Caixa Foundation. Antonio Julià and Sara Marsal were supported by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). Antonio Julià was also supported the by national grant PI17/00019 from the Acción Estratégica en Salud (ISCIII) and the FEDER. The Basque Biobank is a hospitalrelated platform that also involves all Osakidetza health centres, the Basque government's Department of Health and Onkologikoa, is operated by the Basque Foundation for Health Innovation and Research-BIOEF. Mario Cáceres received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de Investigación (AEI, Spain) and the European Regional Development Fund (FEDER, EU). Manuel Romero Gómez, Javier Ampuero Herrojo, Rocío Gallego Durán and Douglas Maya Miles are supported by the “Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III” (PI19/01404, PI16/01842, PI19/00589, PI17/00535 and GLD19/00100), and by the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018, COVID-Premed, COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant FI20/00215, PFIS Contratos Predoctorales de Formación en Investigación en Salud. Enrique Calderón's team is supported by CIBER of Epidemiology and Public Health (CIBERESP), "Instituto de Salud Carlos III". Jan Cato Holter reports grants from Research Council of Norway grant no 312780 during the conduct of the study. Dr. Solligård: reports grants from Research Council of Norway grant no 312769. The BioMaterialBank Nord is supported by the German Center for Lung Research (DZL), Airway Research Center North (ARCN). The BioMaterialBank Nord is member of popgen 2.0 network (P2N). Philipp Koehler has received non-financial scientific grants from Miltenyi Biotec GmbH, Bergisch Gladbach, Germany, and the Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. He is supported by the German Federal Ministry of Education and Research (BMBF).Oliver A. Cornely is supported by the German Federal Ministry of Research and Education and is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – CECAD, EXC 2030 – 390661388. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. Genotyping was performed by the Genotyping laboratory of Institute for Molecular Medicine Finland FIMM Technology Centre, University of Helsinki. This work was supported by grants of the Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland and Lower Saxony. Kerstin U. Ludwig is supported by the German Research Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the Institute of Human Genetics, University Hospital Bonn. Frank Hanses was supported by the Bavarian State Ministry for Science and Arts. Part of the genotyping was supported by a grant to Alfredo Ramirez from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA BioBank, EADB) within the context of the EU Joint Programme – Neurodegenerative Disease Research (JPND). Additional funding was derived from the German Research Foundation (DFG) grant: RA 1971/6-1 to Alfredo Ramirez. Philip Rosenstiel is supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH state funds for COVID19 research). Florian Tran is supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence “Precision Medicine in Chronic Inflammation” (EXC2167). Christoph Lange and Jan Heyckendorf are supported by the German Center for Infection Research (DZIF). Thorsen Brenner, Marc M Berger, Oliver Witzke und Anke Hinney are supported by the Stiftung Universitätsmedizin Essen. Marialbert Acosta-Herrera was supported by Juan de la Cierva Incorporacion program, grant IJC2018-035131-I funded by MCIN/AEI/10.13039/501100011033. Eva C Schulte is supported by the Deutsche Forschungsgemeinschaft (DFG; SCHU 2419/2-1).N

Irx1 and Irx2 are coordinately expressed and regulated by retinoic acid, TGFβ and FGF signaling during chick hindlimb development.

The Iroquois homeobox (Irx) genes play a crucial role in the regionalization and patterning of tissues and organs during metazoan development. The Irx1 and Irx2 gene expression pattern during hindlimb development has been investigated in different species, but its regulation during hindlimb morphogenesis has not been explored yet. The aim of this study was to evaluate the gene expression pattern of Irx1 and Irx2 as well as their regulation by important regulators of hindlimb development such as retinoic acid (RA), transforming growth factor β (TGFβ) and fibroblast growth factor (FGF) signaling during chick hindlimb development. Irx1 and Irx2 were coordinately expressed in the interdigital tissue, digital primordia, joints and in the boundary between cartilage and non-cartilage tissue. Down-regulation of Irx1 and Irx2 expression at the interdigital tissue coincided with the onset of cell death. RA was found to down-regulate their expression by a bone morphogenetic protein-independent mechanism before any evidence of cell death. Furthermore, TGFβ protein regulated Irx1 and Irx2 in a stage-dependent manner at the interdigital tissue, it inhibited their expression when it was administered to the interdigital tissue at developing stages before their normal down-regulation. TGFβ administered to the interdigital tissue at developing stages after normal down-regulation of Irx1 and Irx2 evidenced that expression of these genes marked the boundary between cartilage tissue and non-cartilage tissue. It was also found that at early stages of hindlimb development FGF signaling inhibited the expression of Irx2. In conclusion, the present study demonstrates that Irx1 and Irx2 are coordinately expressed and regulated during chick embryo hindlimb development as occurs in other species of vertebrates supporting the notion that the genomic architecture of Irx clusters is conserved in vertebrates

Gene expression of <i>Irx1</i> and <i>Irx2</i> is down-regulated in the interdigital tissue and coincides with the onset of cell death.

<p>Whole mount <i>in situ</i> hybridization of <i>Irx1</i> (<b>A</b>–<b>G</b>) and <i>Irx2</i> (<b>H</b>–<b>N</b>) at stages 24 HH (<b>A</b>, <b>H</b>), 26 HH (<b>B</b>, <b>I</b>), 27 HH (<b>C</b>, <b>J</b>), 28 HH (<b>D</b>, <b>K</b>), 29 HH (<b>E</b>, <b>L</b>), 30 HH (<b>F</b>, <b>M</b>) and 31 HH (<b>G</b>, <b>N</b>), respectively. Note that <i>Irx1</i> and <i>Irx2</i> are coordinately expressed in the interdigital tissue, digital primordia, joints and in the boundary between cartilage and non-cartilage tissue. <i>Sox9</i> expression at stages 24 HH (<b>O</b>), 26 HH (P) and 27 HH (<b>Q</b>) is presented to compare cartilage differentiation with <i>Irx</i> expression at developing stages 24 HH, 26 HH and 27 HH. Active Caspase 3 immunolocalization (green) in the third interdigit region of hindlimbs at 28 HH (<b>R</b>), 29 HH (<b>S</b>), 30 HH (<b>T</b>) and 31 HH (<b>U</b>) is presented to compare <i>Irx</i> interdigital expression with the cell death pattern. (<b>R</b>–<b>U</b>) Slices were cut at 50 µm. The squares indicated in D, K, E, L, F, M, G, N are to compare with panels in which the activity of caspase 3 was analyzed in R–U. Natural red color of Cy3 used to detect active caspase 3 was changed to green color to obtain a better visualization of the images.</p

TGFβ regulates <i>Irx1</i> and <i>Irx2</i> expression in digit tip.

<p><i>Sox9</i> expression at 8 h (<b>A</b>) and 24 h (<b>D</b>); <i>Irx</i> and <i>Irx2</i> expression after 8 h (<b>B</b>, <b>C</b>) of TGFβ treatment in the digit tip at stage 27 HH. Note that TGFβ inhibits <i>Irx1</i> and <i>Irx2</i> expression over the bead, while below, their expression was noted as a transversal line in the phalanx. <i>Irx1</i> and <i>Irx2</i> expression after 24 h of TGFβ-treatment (<b>E</b>–<b>F</b>). Note that <i>Irx1</i> and <i>Irx2</i> are expressed around the enlarged and rounded cartilage and compare with (<b>D</b>) which shows <i>Sox9</i> expression at the digit tip after 24 h of TGFβ-treatment.</p

RA inhibits <i>Irx1</i> and <i>Irx2</i> expression before the onset of cell death by a BMP-independent mechanism.

<p><i>Irx1</i> and <i>Irx2</i> expression at stage 27 HH in chick hindlimbs, after RA-treatment (<b>A</b>, <b>B</b>), BMP7-treatment (<b>F</b>, <b>G</b>), NOGGIN-treatment (<b>K</b>, <b>L</b>), and RA/NOGGIN-double treatment (<b>O</b>, <b>P</b>) for 8 h in the interdigital area. Note that <i>Irx1</i> and <i>Irx2</i> expression is inhibited by RA but not by BMP7. Active Caspase 3 (green) was evaluated in the third interdigit region of hindlimbs after RA treatment at 8 h (<b>C</b>) and 12 h (<b>D</b>) and BMP7 at 8 h (<b>H</b>) and 12 h (<b>I</b>). Note that the first signs of cell death induced by RA were observed at 12 h (<b>C</b>, <b>D</b>); however, BMP7 was able to induce the first signs of cell death at 8 h and it was most abundant at 12 h (<b>H</b>, <b>I</b>). NOGGIN-treatment (<b>M</b>, <b>N</b>), and RA/NOGGIN-double treatment (<b>Q</b>, <b>R</b>) inhibited cell death induced by RA and BMP7. Control beads without RA or BMP7 never induced cell death (<b>E</b>, <b>J</b>). Experimental samples in A, B, F, G, K, L, O, P are presented on the left; controls on the right. Black arrows indicate the area of <i>Irx1</i> and <i>Irx2</i> inhibition. Autofluorescence in green was observed in ionic-exchange beads used for RA-treatment (black asterisks). The natural red color of Cy3 used to detect active caspase 3 was changed to green for better visualization of the images. (White asterisks indicate beads soaked in BMP7 or NOGGIN).</p

Model of interactions showing <i>Irx</i> regulation by RA, TGFβ and FGF.

<p>Schematic representation of the control of <i>Irx1</i> and <i>Irx2</i> (<i>Irx1</i>/2) expression in digit regions (blue) versus interdigit regions (yellow). White lines delineating the digits represent the expression of <i>Irx1</i>/<i>2</i> in the perichondrium. Dotted lines represent hypothetical inhibition of the IRX protein by <i>Bmp4</i>, and perhaps <i>Bmp7</i> and <i>Msx</i> (not shown) based on reports in the literature <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058549#pone.0058549-Glavic1" target="_blank">[14]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058549#pone.0058549-GomezSkarmeta2" target="_blank">[15]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058549#pone.0058549-VillaCuesta1" target="_blank">[26]</a>. <i>Fgf10</i> is not indicated, but it promotes <i>Fgf8</i> expression <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058549#pone.0058549-Merino2" target="_blank">[37]</a>. Cyan represents the undifferentiated region of the limb.</p

FGF Regulates <i>Irx2</i> expression.

<p><i>Irx2</i> expression (<b>A</b>–<b>D</b>) and the presence of active caspase 3, after 2 h (<b>F</b>), 4 h (<b>G</b>) and 14 h (<b>H</b>) of FGFR-inhibitor (I-FGFR) SU5402 treatment. The squares indicated in B–D are to compare with panels in which the activity of caspase 3 was analyzed in E–H. Control bead in PBS did not promote cell death (<b>E</b>). Note that inhibition of FGF signaling did not affect <i>Irx2</i> expression but promoted cell death from 2 h. <i>Irx2</i> expression after 4 h of FGF8 treatment at stage 24 HH (<b>I</b>) and FGF10 treatment at 8 h (<b>J</b>) in hindlimb posterior region. Note that inhibition of <i>Irx2</i> expression by action of FGF8 occurred earlier that FGF10.</p

<i>Irx1</i> and <i>Irx2</i> expression is regulated in a concentration-dependent manner by TGFβ.

<p><i>Irx1</i> and <i>Irx2</i> expression at stage 29 HH in chick hindlimbs after 21 hours of TGFβ treatment at different doses 12.5 ng/µl (<b>A</b>, <b>E</b>) 25 ng/µl (<b>B</b>, <b>F</b>) 50 ng/µl (<b>C</b>,<b>G</b>) 75 ng/µl (<b>D</b>, <b>H</b>), respectively in the interdigital area. The black arrows show the distance of <i>Irx1</i> and <i>Irx2</i> induction.</p

RA inhibits <i>Irx1</i> and <i>Irx2</i> expression at digit tip before the onset of cell death.

<p><i>Sox9</i> expression in hindlimbs at stage 27 HH at 4 h (<b>A</b>) and the presence of active caspase 3 at 4 or 12 h after RA treatment in digit tip (<b>B</b>, <b>C</b>). <i>Irx1</i> and <i>Irx2</i> expression after 4 h of RA-treatment (<b>D</b>, <b>E</b>). Note the <i>Sox9</i> inhibition in digit and the presence of active caspase 3 over bead in undifferentiated region. Notice the inhibition of <i>Irx1</i> and <i>Irx2</i> expression before the presence of active caspase 3. Arrows indicate the bead position. Autofluorescence in green was observed in ionic-exchange beads used for RA-treatment. Natural red color of Cy3 used to detect active caspase 3 was changed to green color to obtain a better visualization of the images.</p