MHCcluster, a method for functional clustering of MHC molecules
- Autores
- Thomsen, Martin; Lundegaard, Claus; Buus, Søren; Lund, Ole; Nielsen, Morten
- Año de publicación
- 2013
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- The identification of peptides binding to major histocompatibility complexes (MHC) is a critical step in the understanding of T cell immune responses. The human MHC genomic region (HLA) is extremely polymorphic comprising several thousand alleles, many encoding a distinct molecule. The potentially unique specificities remain experimentally uncharacterized for the vast majority of HLA molecules. Likewise, for nonhuman species, only a minor fraction of the known MHC molecules have been characterized. Here, we describe a tool, MHCcluster, to functionally cluster MHC molecules based on their predicted binding specificity. The method has a flexible web interface that allows the user to include any MHC of interest in the analysis. The output consists of a static heat map and graphical tree-based visualizations of the functional relationship between MHC variants and a dynamic TreeViewer interface where both the functional relationship and the individual binding specificities of MHC molecules are visualized. We demonstrate that conventional sequence-based clustering will fail to identify the functional relationship between molecules, when applied to MHC system, and only through the use of the predicted binding specificity can a correct clustering be found. Clustering of prevalent HLA-A and HLA-B alleles using MHCcluster confirms the presence of 12 major specificity groups (supertypes) some however with highly divergent specificities. Importantly, some HLA molecules are shown not to fit any supertype classification. Also, we use MHCcluster to show that chimpanzee MHC class I molecules have a reduced functional diversity compared to that of HLA class I molecules. MHCcluster is available at www.cbs.dtu.dk/services/MHCcluster-2.0.
Fil: Thomsen, Martin. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca
Fil: Lundegaard, Claus. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca
Fil: Buus, Søren. Universidad de Copenhagen; Dinamarca
Fil: Lund, Ole. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca
Fil: Nielsen, Morten. Universidad Nacional de San Martín; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Fisicoquímica Biológicas; Argentina. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca - Materia
-
Mhc
Specificity
Functional Clustering - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/4529
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MHCcluster, a method for functional clustering of MHC moleculesThomsen, MartinLundegaard, ClausBuus, SørenLund, OleNielsen, MortenMhcSpecificityFunctional Clusteringhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The identification of peptides binding to major histocompatibility complexes (MHC) is a critical step in the understanding of T cell immune responses. The human MHC genomic region (HLA) is extremely polymorphic comprising several thousand alleles, many encoding a distinct molecule. The potentially unique specificities remain experimentally uncharacterized for the vast majority of HLA molecules. Likewise, for nonhuman species, only a minor fraction of the known MHC molecules have been characterized. Here, we describe a tool, MHCcluster, to functionally cluster MHC molecules based on their predicted binding specificity. The method has a flexible web interface that allows the user to include any MHC of interest in the analysis. The output consists of a static heat map and graphical tree-based visualizations of the functional relationship between MHC variants and a dynamic TreeViewer interface where both the functional relationship and the individual binding specificities of MHC molecules are visualized. We demonstrate that conventional sequence-based clustering will fail to identify the functional relationship between molecules, when applied to MHC system, and only through the use of the predicted binding specificity can a correct clustering be found. Clustering of prevalent HLA-A and HLA-B alleles using MHCcluster confirms the presence of 12 major specificity groups (supertypes) some however with highly divergent specificities. Importantly, some HLA molecules are shown not to fit any supertype classification. Also, we use MHCcluster to show that chimpanzee MHC class I molecules have a reduced functional diversity compared to that of HLA class I molecules. MHCcluster is available at www.cbs.dtu.dk/services/MHCcluster-2.0.Fil: Thomsen, Martin. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; DinamarcaFil: Lundegaard, Claus. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; DinamarcaFil: Buus, Søren. Universidad de Copenhagen; DinamarcaFil: Lund, Ole. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; DinamarcaFil: Nielsen, Morten. Universidad Nacional de San Martín; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Fisicoquímica Biológicas; Argentina. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; DinamarcaSpringer2013-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/4529Thomsen, Martin; Lundegaard, Claus; Buus, Søren; Lund, Ole; Nielsen, Morten; MHCcluster, a method for functional clustering of MHC molecules; Springer; Immunogenetics; 65; 9; 9-2013; 655-6650093-7711enginfo:eu-repo/semantics/altIdentifier/doi/10.1007/s00251-013-0714-9info:eu-repo/semantics/altIdentifier/issn/0093-7711info:eu-repo/semantics/altIdentifier/url/http://link.springer.com/article/10.1007%2Fs00251-013-0714-9info:eu-repo/semantics/altIdentifier/url/http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3750724/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:47:30Zoai:ri.conicet.gov.ar:11336/4529instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:47:30.339CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
MHCcluster, a method for functional clustering of MHC molecules |
title |
MHCcluster, a method for functional clustering of MHC molecules |
spellingShingle |
MHCcluster, a method for functional clustering of MHC molecules Thomsen, Martin Mhc Specificity Functional Clustering |
title_short |
MHCcluster, a method for functional clustering of MHC molecules |
title_full |
MHCcluster, a method for functional clustering of MHC molecules |
title_fullStr |
MHCcluster, a method for functional clustering of MHC molecules |
title_full_unstemmed |
MHCcluster, a method for functional clustering of MHC molecules |
title_sort |
MHCcluster, a method for functional clustering of MHC molecules |
dc.creator.none.fl_str_mv |
Thomsen, Martin Lundegaard, Claus Buus, Søren Lund, Ole Nielsen, Morten |
author |
Thomsen, Martin |
author_facet |
Thomsen, Martin Lundegaard, Claus Buus, Søren Lund, Ole Nielsen, Morten |
author_role |
author |
author2 |
Lundegaard, Claus Buus, Søren Lund, Ole Nielsen, Morten |
author2_role |
author author author author |
dc.subject.none.fl_str_mv |
Mhc Specificity Functional Clustering |
topic |
Mhc Specificity Functional Clustering |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.6 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
The identification of peptides binding to major histocompatibility complexes (MHC) is a critical step in the understanding of T cell immune responses. The human MHC genomic region (HLA) is extremely polymorphic comprising several thousand alleles, many encoding a distinct molecule. The potentially unique specificities remain experimentally uncharacterized for the vast majority of HLA molecules. Likewise, for nonhuman species, only a minor fraction of the known MHC molecules have been characterized. Here, we describe a tool, MHCcluster, to functionally cluster MHC molecules based on their predicted binding specificity. The method has a flexible web interface that allows the user to include any MHC of interest in the analysis. The output consists of a static heat map and graphical tree-based visualizations of the functional relationship between MHC variants and a dynamic TreeViewer interface where both the functional relationship and the individual binding specificities of MHC molecules are visualized. We demonstrate that conventional sequence-based clustering will fail to identify the functional relationship between molecules, when applied to MHC system, and only through the use of the predicted binding specificity can a correct clustering be found. Clustering of prevalent HLA-A and HLA-B alleles using MHCcluster confirms the presence of 12 major specificity groups (supertypes) some however with highly divergent specificities. Importantly, some HLA molecules are shown not to fit any supertype classification. Also, we use MHCcluster to show that chimpanzee MHC class I molecules have a reduced functional diversity compared to that of HLA class I molecules. MHCcluster is available at www.cbs.dtu.dk/services/MHCcluster-2.0. Fil: Thomsen, Martin. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca Fil: Lundegaard, Claus. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca Fil: Buus, Søren. Universidad de Copenhagen; Dinamarca Fil: Lund, Ole. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca Fil: Nielsen, Morten. Universidad Nacional de San Martín; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Fisicoquímica Biológicas; Argentina. Technical University of Denmark. Department of Systems Biology. Center for Biological Sequence Analysis; Dinamarca |
description |
The identification of peptides binding to major histocompatibility complexes (MHC) is a critical step in the understanding of T cell immune responses. The human MHC genomic region (HLA) is extremely polymorphic comprising several thousand alleles, many encoding a distinct molecule. The potentially unique specificities remain experimentally uncharacterized for the vast majority of HLA molecules. Likewise, for nonhuman species, only a minor fraction of the known MHC molecules have been characterized. Here, we describe a tool, MHCcluster, to functionally cluster MHC molecules based on their predicted binding specificity. The method has a flexible web interface that allows the user to include any MHC of interest in the analysis. The output consists of a static heat map and graphical tree-based visualizations of the functional relationship between MHC variants and a dynamic TreeViewer interface where both the functional relationship and the individual binding specificities of MHC molecules are visualized. We demonstrate that conventional sequence-based clustering will fail to identify the functional relationship between molecules, when applied to MHC system, and only through the use of the predicted binding specificity can a correct clustering be found. Clustering of prevalent HLA-A and HLA-B alleles using MHCcluster confirms the presence of 12 major specificity groups (supertypes) some however with highly divergent specificities. Importantly, some HLA molecules are shown not to fit any supertype classification. Also, we use MHCcluster to show that chimpanzee MHC class I molecules have a reduced functional diversity compared to that of HLA class I molecules. MHCcluster is available at www.cbs.dtu.dk/services/MHCcluster-2.0. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-09 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/4529 Thomsen, Martin; Lundegaard, Claus; Buus, Søren; Lund, Ole; Nielsen, Morten; MHCcluster, a method for functional clustering of MHC molecules; Springer; Immunogenetics; 65; 9; 9-2013; 655-665 0093-7711 |
url |
http://hdl.handle.net/11336/4529 |
identifier_str_mv |
Thomsen, Martin; Lundegaard, Claus; Buus, Søren; Lund, Ole; Nielsen, Morten; MHCcluster, a method for functional clustering of MHC molecules; Springer; Immunogenetics; 65; 9; 9-2013; 655-665 0093-7711 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1007/s00251-013-0714-9 info:eu-repo/semantics/altIdentifier/issn/0093-7711 info:eu-repo/semantics/altIdentifier/url/http://link.springer.com/article/10.1007%2Fs00251-013-0714-9 info:eu-repo/semantics/altIdentifier/url/http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3750724/ |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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1842268862980030464 |
score |
13.13397 |