A phased SNP-based classification of sickle cell anemia HBB haplotypes

Detalhes bibliográficos
Autor(a) principal: Shaikho, Elmutaz M.
Data de Publicação: 2017
Outros Autores: Farrell, John J., Alsultan, Abdulrahman, Qutub, Hatem, Al-Ali, Amein K., Figueiredo, Maria Stella [UNIFESP], Chui, David H. K., Farrer, Lindsay A., Murphy, George J., Mostoslavsky, Gustavo, Sebastiani, Paola, Steinberg, Martin H.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNIFESP
Texto Completo: http://dx.doi.org/10.1186/s12864-017-4013-y
http://repositorio.unifesp.br/handle/11600/51394
Resumo: Background: Sickle cell anemia causes severe complications and premature death. Five common beta-globin gene cluster haplotypes are each associated with characteristic fetal hemoglobin (HbF) levels. As HbF is the major modulator of disease severity, classifying patients according to haplotype is useful. The first method of haplotype classification used restriction fragment length polymorphisms (RFLPs) to detect single nucleotide polymorphisms (SNPs) in the beta-globin gene cluster. This is labor intensive, and error prone. Methods: We used genome-wide SNP data imputed to the 1000 Genomes reference panel to obtain phased data distinguishing parental alleles. Results: We successfully haplotyped 813 sickle cell anemia patients previously classified by RFLPs with a concordance >98%. Four SNPs (rs3834466, rs28440105, rs10128556, and rs968857) marking four different restriction enzyme sites unequivocally defined most haplotypes. We were able to assign a haplotype to 86% of samples that were either partially or misclassified using RFLPs. Conclusion: Phased data using only four SNPs allowed unequivocal assignment of a haplotype that was not always possible using a larger number of RFLPs. Given the availability of genome-wide SNP data, our method is rapid and does not require high computational resources.
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spelling A phased SNP-based classification of sickle cell anemia HBB haplotypesSNPsSickle cellHaplotype classificationBackground: Sickle cell anemia causes severe complications and premature death. Five common beta-globin gene cluster haplotypes are each associated with characteristic fetal hemoglobin (HbF) levels. As HbF is the major modulator of disease severity, classifying patients according to haplotype is useful. The first method of haplotype classification used restriction fragment length polymorphisms (RFLPs) to detect single nucleotide polymorphisms (SNPs) in the beta-globin gene cluster. This is labor intensive, and error prone. Methods: We used genome-wide SNP data imputed to the 1000 Genomes reference panel to obtain phased data distinguishing parental alleles. Results: We successfully haplotyped 813 sickle cell anemia patients previously classified by RFLPs with a concordance >98%. Four SNPs (rs3834466, rs28440105, rs10128556, and rs968857) marking four different restriction enzyme sites unequivocally defined most haplotypes. We were able to assign a haplotype to 86% of samples that were either partially or misclassified using RFLPs. Conclusion: Phased data using only four SNPs allowed unequivocal assignment of a haplotype that was not always possible using a larger number of RFLPs. Given the availability of genome-wide SNP data, our method is rapid and does not require high computational resources.Boston Univ, Sch Med, Dept Med, 72 E Concord St, Boston, MA 02118 USABoston Univ, Bioinformat Program, Boston, MA 02215 USAKing Saud Univ, Coll Med, Sickle Cell Dis Res Ctr, Riyadh, Saudi ArabiaKing Saud Univ, Coll Med, Dept Pediat, Riyadh, Saudi ArabiaKing Faisal Univ, Al Omran Sci Chair, Al Hasa, Saudi ArabiaImam Abdulrahman bin Faisal Univ, Inst Res & Med Consultat, Dammam, Saudi ArabiaEscola Paulista Med, Hematol & Blood Transfus Div, São Paulo, BrazilBoston Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02118 USAEscola Paulista Med, Hematol & Blood Transfus Div, São Paulo, BrazilWeb of ScienceNIH Bethesda, MDNIH: R01 HL 068970NIH: RC2 HL 101212NIH: R01 87681NIH: T32 HL007501Biomed Central Ltd2019-08-19T11:49:45Z2019-08-19T11:49:45Z2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion-application/pdfhttp://dx.doi.org/10.1186/s12864-017-4013-yBmc Genomics. London, v. 18, p. -, 2017.10.1186/s12864-017-4013-yWOS000408035900004.pdf1471-2164http://repositorio.unifesp.br/handle/11600/51394WOS:000408035900004enginfo:eu-repo/semantics/openAccessShaikho, Elmutaz M.Farrell, John J.Alsultan, AbdulrahmanQutub, HatemAl-Ali, Amein K.Figueiredo, Maria Stella [UNIFESP]Chui, David H. K.Farrer, Lindsay A.Murphy, George J.Mostoslavsky, GustavoSebastiani, PaolaSteinberg, Martin H.reponame:Repositório Institucional da UNIFESPinstname:Universidade Federal de São Paulo (UNIFESP)instacron:UNIFESP2024-08-10T23:13:17Zoai:repositorio.unifesp.br/:11600/51394Repositório InstitucionalPUBhttp://www.repositorio.unifesp.br/oai/requestbiblioteca.csp@unifesp.bropendoar:34652024-08-10T23:13:17Repositório Institucional da UNIFESP - Universidade Federal de São Paulo (UNIFESP)false
dc.title.none.fl_str_mv A phased SNP-based classification of sickle cell anemia HBB haplotypes
title A phased SNP-based classification of sickle cell anemia HBB haplotypes
spellingShingle A phased SNP-based classification of sickle cell anemia HBB haplotypes
Shaikho, Elmutaz M.
SNPs
Sickle cell
Haplotype classification
title_short A phased SNP-based classification of sickle cell anemia HBB haplotypes
title_full A phased SNP-based classification of sickle cell anemia HBB haplotypes
title_fullStr A phased SNP-based classification of sickle cell anemia HBB haplotypes
title_full_unstemmed A phased SNP-based classification of sickle cell anemia HBB haplotypes
title_sort A phased SNP-based classification of sickle cell anemia HBB haplotypes
author Shaikho, Elmutaz M.
author_facet Shaikho, Elmutaz M.
Farrell, John J.
Alsultan, Abdulrahman
Qutub, Hatem
Al-Ali, Amein K.
Figueiredo, Maria Stella [UNIFESP]
Chui, David H. K.
Farrer, Lindsay A.
Murphy, George J.
Mostoslavsky, Gustavo
Sebastiani, Paola
Steinberg, Martin H.
author_role author
author2 Farrell, John J.
Alsultan, Abdulrahman
Qutub, Hatem
Al-Ali, Amein K.
Figueiredo, Maria Stella [UNIFESP]
Chui, David H. K.
Farrer, Lindsay A.
Murphy, George J.
Mostoslavsky, Gustavo
Sebastiani, Paola
Steinberg, Martin H.
author2_role author
author
author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Shaikho, Elmutaz M.
Farrell, John J.
Alsultan, Abdulrahman
Qutub, Hatem
Al-Ali, Amein K.
Figueiredo, Maria Stella [UNIFESP]
Chui, David H. K.
Farrer, Lindsay A.
Murphy, George J.
Mostoslavsky, Gustavo
Sebastiani, Paola
Steinberg, Martin H.
dc.subject.por.fl_str_mv SNPs
Sickle cell
Haplotype classification
topic SNPs
Sickle cell
Haplotype classification
description Background: Sickle cell anemia causes severe complications and premature death. Five common beta-globin gene cluster haplotypes are each associated with characteristic fetal hemoglobin (HbF) levels. As HbF is the major modulator of disease severity, classifying patients according to haplotype is useful. The first method of haplotype classification used restriction fragment length polymorphisms (RFLPs) to detect single nucleotide polymorphisms (SNPs) in the beta-globin gene cluster. This is labor intensive, and error prone. Methods: We used genome-wide SNP data imputed to the 1000 Genomes reference panel to obtain phased data distinguishing parental alleles. Results: We successfully haplotyped 813 sickle cell anemia patients previously classified by RFLPs with a concordance >98%. Four SNPs (rs3834466, rs28440105, rs10128556, and rs968857) marking four different restriction enzyme sites unequivocally defined most haplotypes. We were able to assign a haplotype to 86% of samples that were either partially or misclassified using RFLPs. Conclusion: Phased data using only four SNPs allowed unequivocal assignment of a haplotype that was not always possible using a larger number of RFLPs. Given the availability of genome-wide SNP data, our method is rapid and does not require high computational resources.
publishDate 2017
dc.date.none.fl_str_mv 2017
2019-08-19T11:49:45Z
2019-08-19T11:49:45Z
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1186/s12864-017-4013-y
Bmc Genomics. London, v. 18, p. -, 2017.
10.1186/s12864-017-4013-y
WOS000408035900004.pdf
1471-2164
http://repositorio.unifesp.br/handle/11600/51394
WOS:000408035900004
url http://dx.doi.org/10.1186/s12864-017-4013-y
http://repositorio.unifesp.br/handle/11600/51394
identifier_str_mv Bmc Genomics. London, v. 18, p. -, 2017.
10.1186/s12864-017-4013-y
WOS000408035900004.pdf
1471-2164
WOS:000408035900004
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv -
application/pdf
dc.publisher.none.fl_str_mv Biomed Central Ltd
publisher.none.fl_str_mv Biomed Central Ltd
dc.source.none.fl_str_mv reponame:Repositório Institucional da UNIFESP
instname:Universidade Federal de São Paulo (UNIFESP)
instacron:UNIFESP
instname_str Universidade Federal de São Paulo (UNIFESP)
instacron_str UNIFESP
institution UNIFESP
reponame_str Repositório Institucional da UNIFESP
collection Repositório Institucional da UNIFESP
repository.name.fl_str_mv Repositório Institucional da UNIFESP - Universidade Federal de São Paulo (UNIFESP)
repository.mail.fl_str_mv biblioteca.csp@unifesp.br
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