Ultraspecific probes for high throughput HLA typing

Persistent Link:
http://hdl.handle.net/10150/610008
Title:
Ultraspecific probes for high throughput HLA typing
Author:
Feng, Chen; Putonti, Catherine; Zhang, Meizhuo; Eggers, Rick; Mitra, Rahul; Hogan, Mike; Jayaraman, Krishna; Fofanov, Yuriy
Affiliation:
Department of Computer Science, University of Houston, Houston, TX, USA; Department of Computer Science, Loyola University Chicago, Chicago, IL, USA; Department of Biology, Loyola University Chicago, Chicago, IL, USA; Collaborative Center for Statistics in Science, Yale University, New Haven, CT, USA; Genomics USA, Inverness, IL, USA; Department of Biology and Biochemistry, University of Houston, Houston, TX, USA
Issue Date:
2009
Publisher:
BioMed Central
Citation:
BMC Genomics 2009, 10:85 doi:10.1186/1471-2164-10-85
Journal:
BMC Genomics
Rights:
© 2009 Feng et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0)
Collection Information:
This item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at repository@u.library.arizona.edu.
Abstract:
BACKGROUND:The variations within an individual's HLA (Human Leukocyte Antigen) genes have been linked to many immunological events, e.g. susceptibility to disease, response to vaccines, and the success of blood, tissue, and organ transplants. Although the microarray format has the potential to achieve high-resolution typing, this has yet to be attained due to inefficiencies of current probe design strategies.RESULTS:We present a novel three-step approach for the design of high-throughput microarray assays for HLA typing. This approach first selects sequences containing the SNPs present in all alleles of the locus of interest and next calculates the number of base changes necessary to convert a candidate probe sequences to the closest subsequence within the set of sequences that are likely to be present in the sample including the remainder of the human genome in order to identify those candidate probes which are "ultraspecific" for the allele of interest. Due to the high specificity of these sequences, it is possible that preliminary steps such as PCR amplification are no longer necessary. Lastly, the minimum number of these ultraspecific probes is selected such that the highest resolution typing can be achieved for the minimal cost of production. As an example, an array was designed and in silico results were obtained for typing of the HLA-B locus.CONCLUSION:The assay presented here provides a higher resolution than has previously been developed and includes more alleles than previously considered. Based upon the in silico and preliminary experimental results, we believe that the proposed approach can be readily applied to any highly polymorphic gene system.
EISSN:
1471-2164
DOI:
10.1186/1471-2164-10-85
Version:
Final published version
Additional Links:
http://www.biomedcentral.com/1471-2164/10/85

Full metadata record

DC FieldValue Language
dc.contributor.authorFeng, Chenen
dc.contributor.authorPutonti, Catherineen
dc.contributor.authorZhang, Meizhuoen
dc.contributor.authorEggers, Ricken
dc.contributor.authorMitra, Rahulen
dc.contributor.authorHogan, Mikeen
dc.contributor.authorJayaraman, Krishnaen
dc.contributor.authorFofanov, Yuriyen
dc.date.accessioned2016-05-20T08:56:19Z-
dc.date.available2016-05-20T08:56:19Z-
dc.date.issued2009en
dc.identifier.citationBMC Genomics 2009, 10:85 doi:10.1186/1471-2164-10-85en
dc.identifier.doi10.1186/1471-2164-10-85en
dc.identifier.urihttp://hdl.handle.net/10150/610008-
dc.description.abstractBACKGROUND:The variations within an individual's HLA (Human Leukocyte Antigen) genes have been linked to many immunological events, e.g. susceptibility to disease, response to vaccines, and the success of blood, tissue, and organ transplants. Although the microarray format has the potential to achieve high-resolution typing, this has yet to be attained due to inefficiencies of current probe design strategies.RESULTS:We present a novel three-step approach for the design of high-throughput microarray assays for HLA typing. This approach first selects sequences containing the SNPs present in all alleles of the locus of interest and next calculates the number of base changes necessary to convert a candidate probe sequences to the closest subsequence within the set of sequences that are likely to be present in the sample including the remainder of the human genome in order to identify those candidate probes which are "ultraspecific" for the allele of interest. Due to the high specificity of these sequences, it is possible that preliminary steps such as PCR amplification are no longer necessary. Lastly, the minimum number of these ultraspecific probes is selected such that the highest resolution typing can be achieved for the minimal cost of production. As an example, an array was designed and in silico results were obtained for typing of the HLA-B locus.CONCLUSION:The assay presented here provides a higher resolution than has previously been developed and includes more alleles than previously considered. Based upon the in silico and preliminary experimental results, we believe that the proposed approach can be readily applied to any highly polymorphic gene system.en
dc.language.isoenen
dc.publisherBioMed Centralen
dc.relation.urlhttp://www.biomedcentral.com/1471-2164/10/85en
dc.rights© 2009 Feng et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0)en
dc.titleUltraspecific probes for high throughput HLA typingen
dc.typeArticleen
dc.identifier.eissn1471-2164en
dc.contributor.departmentDepartment of Computer Science, University of Houston, Houston, TX, USAen
dc.contributor.departmentDepartment of Computer Science, Loyola University Chicago, Chicago, IL, USAen
dc.contributor.departmentDepartment of Biology, Loyola University Chicago, Chicago, IL, USAen
dc.contributor.departmentCollaborative Center for Statistics in Science, Yale University, New Haven, CT, USAen
dc.contributor.departmentGenomics USA, Inverness, IL, USAen
dc.contributor.departmentDepartment of Biology and Biochemistry, University of Houston, Houston, TX, USAen
dc.identifier.journalBMC Genomicsen
dc.description.collectioninformationThis item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
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