Definition of supertypes for HLA molecules using clustering of specificity matrices

Ole Lund; Morten Nielsen; Can Kesmir; Anders Gorm Petersen; Claus Lundegaard; Peder Worning; Christina Sylvester-Hvid; Kasper Lamberth; Gustav Røder; Sune Justesen; Søren Buus; Søren Brunak

doi:10.1007/s00251-004-0647-4

Definition of supertypes for HLA molecules using clustering of specificity matrices

Ole Lund, Morten Nielsen, Can Kesmir, Anders Gorm Petersen, Claus Lundegaard, Peder Worning, Christina Sylvester-Hvid, Kasper Lamberth, Gustav Røder, Sune Justesen, Søren Buus, Søren Brunak

Department of Immunology and Microbiology

204 Citations (Scopus)

Abstract

Major histocompatibility complex (MHC) proteins are encoded by extremely polymorphic genes and play a crucial role in immunity. However, not all genetically different MHC molecules are functionally different. Sette and Sidney (1999) have defined nine HLA class I supertypes and showed that with only nine main functional binding specificities it is possible to cover the binding properties of almost all known HLA class I molecules. Here we present a comprehensive study of the functional relationship between all HLA molecules with known specificities in a uniform and automated way. We have developed a novel method for clustering sequence motifs. We construct hidden Markov models for HLA class I molecules using a Gibbs sampling procedure and use the similarities among these to define clusters of specificities. These clusters are extensions of the previously suggested ones. We suggest splitting some of the alleles in the A1 supertype into a new A26 supertype, and some of the alleles in the B27 supertype into a new B39 supertype. Furthermore the B8 alleles may define their own supertype. We also use the published specificities for a number of HLA-DR types to define clusters with similar specificities. We report that the previously observed specificities of these class II molecules can be clustered into nine classes, which only partly correspond to the serological classification. We show that classification of HLA molecules may be done in a uniform and automated way. The definition of clusters allows for selection of representative HLA molecules that can cover the HLA specificity space better. This makes it possible to target most of the known HLA alleles with known specificities using only a few peptides, and may be used in construction of vaccines. Supplementary material is available at http://www.cbs.dtu.dk/researchgroups/immunology/supertypes.html.

Original language	English
Journal	Immunogenetics
Volume	55
Issue number	12
Pages (from-to)	797-810
Number of pages	13
ISSN	0093-7711
DOIs	https://doi.org/10.1007/s00251-004-0647-4
Publication status	Published - 2004

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10.1007/s00251-004-0647-4

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@article{d35bc1b0ebca11ddbf70000ea68e967b,

title = "Definition of supertypes for HLA molecules using clustering of specificity matrices",

abstract = "Major histocompatibility complex (MHC) proteins are encoded by extremely polymorphic genes and play a crucial role in immunity. However, not all genetically different MHC molecules are functionally different. Sette and Sidney (1999) have defined nine HLA class I supertypes and showed that with only nine main functional binding specificities it is possible to cover the binding properties of almost all known HLA class I molecules. Here we present a comprehensive study of the functional relationship between all HLA molecules with known specificities in a uniform and automated way. We have developed a novel method for clustering sequence motifs. We construct hidden Markov models for HLA class I molecules using a Gibbs sampling procedure and use the similarities among these to define clusters of specificities. These clusters are extensions of the previously suggested ones. We suggest splitting some of the alleles in the A1 supertype into a new A26 supertype, and some of the alleles in the B27 supertype into a new B39 supertype. Furthermore the B8 alleles may define their own supertype. We also use the published specificities for a number of HLA-DR types to define clusters with similar specificities. We report that the previously observed specificities of these class II molecules can be clustered into nine classes, which only partly correspond to the serological classification. We show that classification of HLA molecules may be done in a uniform and automated way. The definition of clusters allows for selection of representative HLA molecules that can cover the HLA specificity space better. This makes it possible to target most of the known HLA alleles with known specificities using only a few peptides, and may be used in construction of vaccines. Supplementary material is available at http://www.cbs.dtu.dk/researchgroups/immunology/supertypes.html.",

author = "Ole Lund and Morten Nielsen and Can Kesmir and Petersen, {Anders Gorm} and Claus Lundegaard and Peder Worning and Christina Sylvester-Hvid and Kasper Lamberth and Gustav R{\o}der and Sune Justesen and S{\o}ren Buus and S{\o}ren Brunak",

note = "Keywords: Amino Acid Motifs; Cluster Analysis; Histocompatibility Antigens Class I; Histocompatibility Antigens Class II; Humans; Markov Chains",

year = "2004",

doi = "10.1007/s00251-004-0647-4",

language = "English",

volume = "55",

pages = "797--810",

journal = "Immunogenetics",

issn = "0093-7711",

publisher = "Springer",

number = "12",

}

TY - JOUR

T1 - Definition of supertypes for HLA molecules using clustering of specificity matrices

AU - Lund, Ole

AU - Nielsen, Morten

AU - Kesmir, Can

AU - Petersen, Anders Gorm

AU - Lundegaard, Claus

AU - Worning, Peder

AU - Sylvester-Hvid, Christina

AU - Lamberth, Kasper

AU - Røder, Gustav

AU - Justesen, Sune

AU - Buus, Søren

AU - Brunak, Søren

N1 - Keywords: Amino Acid Motifs; Cluster Analysis; Histocompatibility Antigens Class I; Histocompatibility Antigens Class II; Humans; Markov Chains

PY - 2004

Y1 - 2004

N2 - Major histocompatibility complex (MHC) proteins are encoded by extremely polymorphic genes and play a crucial role in immunity. However, not all genetically different MHC molecules are functionally different. Sette and Sidney (1999) have defined nine HLA class I supertypes and showed that with only nine main functional binding specificities it is possible to cover the binding properties of almost all known HLA class I molecules. Here we present a comprehensive study of the functional relationship between all HLA molecules with known specificities in a uniform and automated way. We have developed a novel method for clustering sequence motifs. We construct hidden Markov models for HLA class I molecules using a Gibbs sampling procedure and use the similarities among these to define clusters of specificities. These clusters are extensions of the previously suggested ones. We suggest splitting some of the alleles in the A1 supertype into a new A26 supertype, and some of the alleles in the B27 supertype into a new B39 supertype. Furthermore the B8 alleles may define their own supertype. We also use the published specificities for a number of HLA-DR types to define clusters with similar specificities. We report that the previously observed specificities of these class II molecules can be clustered into nine classes, which only partly correspond to the serological classification. We show that classification of HLA molecules may be done in a uniform and automated way. The definition of clusters allows for selection of representative HLA molecules that can cover the HLA specificity space better. This makes it possible to target most of the known HLA alleles with known specificities using only a few peptides, and may be used in construction of vaccines. Supplementary material is available at http://www.cbs.dtu.dk/researchgroups/immunology/supertypes.html.

AB - Major histocompatibility complex (MHC) proteins are encoded by extremely polymorphic genes and play a crucial role in immunity. However, not all genetically different MHC molecules are functionally different. Sette and Sidney (1999) have defined nine HLA class I supertypes and showed that with only nine main functional binding specificities it is possible to cover the binding properties of almost all known HLA class I molecules. Here we present a comprehensive study of the functional relationship between all HLA molecules with known specificities in a uniform and automated way. We have developed a novel method for clustering sequence motifs. We construct hidden Markov models for HLA class I molecules using a Gibbs sampling procedure and use the similarities among these to define clusters of specificities. These clusters are extensions of the previously suggested ones. We suggest splitting some of the alleles in the A1 supertype into a new A26 supertype, and some of the alleles in the B27 supertype into a new B39 supertype. Furthermore the B8 alleles may define their own supertype. We also use the published specificities for a number of HLA-DR types to define clusters with similar specificities. We report that the previously observed specificities of these class II molecules can be clustered into nine classes, which only partly correspond to the serological classification. We show that classification of HLA molecules may be done in a uniform and automated way. The definition of clusters allows for selection of representative HLA molecules that can cover the HLA specificity space better. This makes it possible to target most of the known HLA alleles with known specificities using only a few peptides, and may be used in construction of vaccines. Supplementary material is available at http://www.cbs.dtu.dk/researchgroups/immunology/supertypes.html.

U2 - 10.1007/s00251-004-0647-4

DO - 10.1007/s00251-004-0647-4

M3 - Journal article

C2 - 14963618

SN - 0093-7711

VL - 55

SP - 797

EP - 810

JO - Immunogenetics

JF - Immunogenetics

IS - 12

ER -

Definition of supertypes for HLA molecules using clustering of specificity matrices

Abstract

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