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Nearly three-quarters of the 143 genetic signals associated with platelet and erythrocyte phenotypes identified by meta-analyses of genome-wide association (GWA) studies are located at non-protein-coding regions. Here, we assessed the role of candidate regulatory variants associated with cell type-restricted, closely related hematological quantitative traits in biologically relevant hematopoietic cell types. We used formaldehyde-assisted isolation of regulatory elements followed by next-generation sequencing (FAIRE-seq) to map regions of open chromatin in three primary human blood cells of the myeloid lineage. In the precursors of platelets and erythrocytes, as well as in monocytes, we found that open chromatin signatures reflect the corresponding hematopoietic lineages of the studied cell types and associate with the cell type-specific gene expression patterns. Dependent on their signal strength, open chromatin regions showed correlation with promoter and enhancer histone marks, distance to the transcription start site, and ontology classes of nearby genes. Cell type-restricted regions of open chromatin were enriched in sequence variants associated with hematological indices. The majority (63.6%) of such candidate functional variants at platelet quantitative trait loci (QTLs) coincided with binding sites of five transcription factors key in regulating megakaryopoiesis. We experimentally tested 13 candidate regulatory variants at 10 platelet QTLs and found that 10 (76.9%) affected protein binding, suggesting that this is a frequent mechanism by which regulatory variants influence quantitative trait levels. Our findings demonstrate that combining large-scale GWA data with open chromatin profiles of relevant cell types can be a powerful means of dissecting the genetic architecture of closely related quantitative traits.
Maps of open chromatin highlight cell type-restricted patterns of regulatory sequence variation at hematological trait loci / Paul, D.s., Albers, C.a., Rendon, A., Voss, K., Stephens, J., Jan Willem N., A., Cornelis A., A., Ale, A., Abtehale Al, H., Hooman, A., Franco, A., Folkert W., A., Antony, A., Beverley, B., Stefania, B., François, B., Saonli, B., Sebastian E., B., Jacques, B., Beben, B., et al.. - In: GENOME RESEARCH. - ISSN 1088-9051. - (2013), pp. 1130-1141. [10.1101/gr.155127.113]
Maps of open chromatin highlight cell type-restricted patterns of regulatory sequence variation at hematological trait loci.
Paul DS;Albers CA;Rendon A;Voss K;Stephens J;Jan Willem N. Akkerman;Cornelis A. Albers;Ale Algra;Abtehale Al Hussani;Hooman Allayee;Franco Anni;Folkert W. Asselbergs;Antony Attwood;Beverley Balkau;Stefania Bandinelli;François Bastardot;Saonli Basu;Sebastian E. Baumeister;Jacques Beckmann;Beben Benyamin;Ginevra Biino;Joshua C. Bis;Lorenzo Bomba;Amélie Bonnefond;Dorret I. Boomsma;John R. Bradley;François Cambien;John C. Chambers;Marina Ciullo;William O. Cookson;Francesco Cucca;Ana Cvejic;D'ADAMO, ADAMO PIO;John Danesh;Fabrice Danjou;Debashish Das;Gail Davies;Paul IW de Bakker;Rudolf A. de Boer;Eco JC de Geus;Ian J. Deary;George V. Dedoussis;Panos Deloukas;Maria Dimitriou;Christian Dina;Angela Döring;Ulrich Elling;David Ellinghaus;Paul Elliott;Gunnar Engström;Jeanette Erdmann;Tõnu Esko;David M. Evans;Gudmundur I. Eyjolfsson;Mario Falchi;Wei Feng;Manuel A. Ferreira;Luigi Ferrucci;Krista Fischer;Aaron R. Folsom;Paolo Fortina;Andre Franke;Lude Franke;Ian H. Frazer;Philippe Froguel;Renzo Galanello;Santhi K. Ganesh;Stephen F. Garner;GASPARINI, PAOLO;Bernd Genser;Quince D. Gibson;Christian Gieger;GIROTTO, GIORGIA;Nicole L. Glazer;Martin Gögele;Alison H. Goodall;Andreas Greinacher;Daniel F. Gudbjartsson;Chris Hammond;Sarah E. Harris;Jaana Hartiala;Anna Liisa Hartikainen;Stanley L. Hazen;Susan R. Heckbert;Bo Hedblad;Christian Hengstenberg;Micha Hersch;Andrew A. Hicks;Hilma Holm;Jouke Jan Hottenga;Thomas Illig;Marjo Riitta Jarvelin;Jennifer Jolley;Steve Jupe;Mika Kähönen;Naoyuki Kamatani;Stavroula Kanoni;Ido P. Kema;John P. Kemp;Jyoti Khadake;Kay Tee Khaw;Marcus E. Kleber;Jaspal S. Kooner;Peter Kovacs;Brigitte Kühnel;Marie Christine Kyrtsonis;Yann Labrune;Vasiliki Lagou;Claudia Langenberg;Terho Lehtimäki;Xinzhong Li;Liming Liang;Lifelines Cohort Study;Heather Lloyd Jones;Ruth JF Loos;Lorna M. Lopez;Thomas Lumley;Leo Pekka Lyytikäinen;Winfried Maerz;Reedik Mägi;Massimo Mangino;Nicholas G. Martin;Andrea Maschio;Irene Mateo Leach;Barbara McKnight;Stuart Meacham;Sarah E. Medland;Christa Meisinger;Olle Melander;Yasin Memari;Andres Metspalu;Kathy Miller;Braxton D. Mitchell;Miriam F. Moffatt;Grant W. Montgomery;Carmel Moore;Federico Murgia;Yusuke Nakamura;Matthias Nauck;Gerjan Navis;Ilja M. Nolte;Ute Nöthlings;Teresa Nutile;Yukinori Okada;Isleifur Olafsson;Pall T. Onundarson;Paul F. O’Reilly;Willem H. Ouwehand;Debora Parracciani;Afshin Parsa;Dirk S. Paul;Josef M. Penninger;Brenda W. Penninx;Mario Pirastu;PIRASTU, Nicola;Giorgio Pistis;Eleonora Porcu;Laura Portas;David Porteous;Anneli Pouta;Peter P. Pramstaller;Inga Prokopenko;Bruce M. Psaty;Janne Pullat;Aparna Radhakrishnan;Olli Raitakari;Ramiro Ramirez Solis;Augusto Rendon;Janina S. Ried;Susan M. Ring;ROBINO, ANTONIETTA;Jerome I. Rotter;Daniela Ruggiero;Aimo Ruokonen;Cinzia Sala;Andres Saluments;Nilesh J. Samani;Jennifer Sambrook;Serena Sanna;David Schlessinger;Carsten O. Schmidt;Stefan Schreiber;Heribert Schunkert;James Scott;Joban Sehmi;Jovana Serbanovic Canic;So Youn Shin;Alan R. Shuldiner;Rob Sladek;Johannes H. Smit;George Davey Smith;J. Gustav Smith;Nicholas L. Smith;Harold Snieder;Nicole Soranzo;Rossella Sorice;Timothy D. Spector;John M. Starr;Kari Stefansson;Derek Stemple;Jonathan Stephens;Michael Stumvoll;Patrick Sulem;Atsushi Takahashi;Sian Tsung Tan;Toshiko Tanaka;Clara Tang;Weihong Tang;WH Wilson Tang;Kent Taylor;Albert Tenesa;Alexander Teumer;Swee Lay Thein;Unnur Thorsteinsdottir;Daniela Toniolo;Anke Tönjes;TRAGLIA, MICHELA;Manuela Uda;Sheila Ulivi;Pim van der Harst;C. Ellen van der Schoot;Wiek H. van Gilst;L. Joost van Pelt;Dirk J. van Veldhuisen;Niek Verweij;Peter M. Visscher;Uwe Völker;Peter Vollenweider;Katrin Voss;Nicholas J. Wareham;Lorenz Wernisch;Harm Jan Westra;John B. Whitfield;HErich Wichmann;Kerri L. Wiggins;Gonneke Willemsen;Bernhard R. Winkelmann;Gerald Wirnsberger;Bruce HR Wolffenbuttel;Jian Yang;Tsun Po Yang;Weihua Zhang;Jing Hua Zhao;Paavo Zitting;Jaap Jan Zwaginga;van der Harst P;Chambers JC;Soranzo N;Ouwehand WH;Deloukas P.
2013-01-01
Abstract
Nearly three-quarters of the 143 genetic signals associated with platelet and erythrocyte phenotypes identified by meta-analyses of genome-wide association (GWA) studies are located at non-protein-coding regions. Here, we assessed the role of candidate regulatory variants associated with cell type-restricted, closely related hematological quantitative traits in biologically relevant hematopoietic cell types. We used formaldehyde-assisted isolation of regulatory elements followed by next-generation sequencing (FAIRE-seq) to map regions of open chromatin in three primary human blood cells of the myeloid lineage. In the precursors of platelets and erythrocytes, as well as in monocytes, we found that open chromatin signatures reflect the corresponding hematopoietic lineages of the studied cell types and associate with the cell type-specific gene expression patterns. Dependent on their signal strength, open chromatin regions showed correlation with promoter and enhancer histone marks, distance to the transcription start site, and ontology classes of nearby genes. Cell type-restricted regions of open chromatin were enriched in sequence variants associated with hematological indices. The majority (63.6%) of such candidate functional variants at platelet quantitative trait loci (QTLs) coincided with binding sites of five transcription factors key in regulating megakaryopoiesis. We experimentally tested 13 candidate regulatory variants at 10 platelet QTLs and found that 10 (76.9%) affected protein binding, suggesting that this is a frequent mechanism by which regulatory variants influence quantitative trait levels. Our findings demonstrate that combining large-scale GWA data with open chromatin profiles of relevant cell types can be a powerful means of dissecting the genetic architecture of closely related quantitative traits.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2711479
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Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2023-2025 del proprio SC/SSD. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande.
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