Literature DB >> 18829352

High-density SNP genotyping to define beta-globin locus haplotypes.

Li Liu1, Shalini Muralidhar, Manisha Singh, Caprice Sylvan, Inderdeep S Kalra, Charles T Quinn, Onyinye C Onyekwere, Betty S Pace.   

Abstract

Five major beta-globin locus haplotypes have been established in individuals with sickle cell disease (SCD) from the Benin, Bantu, Senegal, Cameroon, and Arab-Indian populations. Historically, beta-haplotypes were established using restriction fragment length polymorphism (RFLP) analysis across the beta-locus, which consists of five functional beta-like globin genes located on chromosome 11. Previous attempts to correlate these haplotypes as robust predictors of clinical phenotypes observed in SCD have not been successful. We speculate that the coverage and distribution of the RFLP sites located proximal to or within the globin genes are not sufficiently dense to accurately reflect the complexity of this region. To test our hypothesis, we performed RFLP analysis and high-density single nucleotide polymorphism (SNP) genotyping across the beta-locus using DNA samples from healthy African Americans with either normal hemoglobin A (HbAA) or individuals with homozygous SS (HbSS) disease. Using the genotyping data from 88 SNPs and Haploview analysis, we generated a greater number of haplotypes than that observed with RFLP analysis alone. Furthermore, a unique pattern of long-range linkage disequilibrium between the locus control region and the beta-like globin genes was observed in the HbSS group. Interestingly, we observed multiple SNPs within the HindIII restriction site located in the Ggamma-globin intervening sequence II which produced the same RFLP pattern. These findings illustrated the inability of RFLP analysis to decipher the complexity of sequence variations that impacts genomic structure in this region. Our data suggest that high-density SNP mapping may be required to accurately define beta-haplotypes that correlate with the different clinical phenotypes observed in SCD.

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Year:  2008        PMID: 18829352      PMCID: PMC4251776          DOI: 10.1016/j.bcmd.2008.07.002

Source DB:  PubMed          Journal:  Blood Cells Mol Dis        ISSN: 1079-9796            Impact factor:   3.039


  36 in total

1.  Haplotypes of the beta-globin gene as prognostic factors in sickle-cell disease.

Authors:  M A el-Hazmi; A S Warsy; N Bashir; A Beshlawi; I R Hussain; S Temtamy; F Qubaili
Journal:  East Mediterr Health J       Date:  1999-11       Impact factor: 1.628

2.  Fetal hemoglobin levels in sickle cell disease and normal individuals are partially controlled by an X-linked gene located at Xp22.2.

Authors:  G J Dover; K D Smith; Y C Chang; S Purvis; A Mays; D A Meyers; C Sheils; G Serjeant
Journal:  Blood       Date:  1992-08-01       Impact factor: 22.113

3.  Association of klotho, bone morphogenic protein 6, and annexin A2 polymorphisms with sickle cell osteonecrosis.

Authors:  Clinton Baldwin; Vikki G Nolan; Diego F Wyszynski; Qian-Li Ma; Paola Sebastiani; Stephen H Embury; Alice Bisbee; John Farrell; Lindsay Farrer; Martin H Steinberg
Journal:  Blood       Date:  2005-03-22       Impact factor: 22.113

Review 4.  Predicting clinical severity in sickle cell anaemia.

Authors:  M H Steinberg
Journal:  Br J Haematol       Date:  2005-05       Impact factor: 6.998

5.  Comprehensive arrayed primer extension array for the detection of 59 sequence variants in 15 conditions prevalent among the (Ashkenazi) Jewish population.

Authors:  Iris Schrijver; Maigi Külm; Phyllis I Gardner; Eugene P Pergament; Morris B Fiddler
Journal:  J Mol Diagn       Date:  2007-04       Impact factor: 5.568

6.  Polymerase chain reaction amplification applied to the determination of beta-like globin gene cluster haplotypes.

Authors:  M Sutton; E E Bouhassira; R L Nagel
Journal:  Am J Hematol       Date:  1989-09       Impact factor: 10.047

7.  Heterogeneity of DNA fragments associated with the sickle-globin gene.

Authors:  J Feldenzer; J G Mears; A L Burns; C Natta; A Bank
Journal:  J Clin Invest       Date:  1979-09       Impact factor: 14.808

8.  Evaluation of arrayed primer extension for TP53 mutation detection in breast and ovarian carcinomas.

Authors:  Pedro Kringen; Anna Bergamaschi; Eldri Undlien Due; Yun Wang; Elda Tagliabue; Jahn M Nesland; Aune Nehman; Neeme Tönisson; Anne-Lise Børresen-Dale
Journal:  Biotechniques       Date:  2005-11       Impact factor: 1.993

9.  Fetal hemoglobin in sickle cell anemia: Bayesian modeling of genetic associations.

Authors:  Paola Sebastiani; Ling Wang; Vikki G Nolan; Efthymia Melista; Qianli Ma; Clinton T Baldwin; Martin H Steinberg
Journal:  Am J Hematol       Date:  2008-03       Impact factor: 10.047

10.  Molecular analysis of the high-hemoglobin-F phenotype in Saudi Arabian sickle cell anemia.

Authors:  B A Miller; N Olivieri; M Salameh; M Ahmed; G Antognetti; T H Huisman; D G Nathan; S H Orkin
Journal:  N Engl J Med       Date:  1987-01-29       Impact factor: 91.245

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  11 in total

1.  Extensive genomic variability of knops blood group polymorphisms is associated with sickle cell disease in Africa.

Authors:  Kimberley C Duru; Jenelle A Noble; Aldiouma Guindo; Li Yi; Ikhide G Imumorin; Dapa A Diallo; Bolaji N Thomas
Journal:  Evol Bioinform Online       Date:  2015-03-09       Impact factor: 1.625

Review 2.  Beta-globin gene haplotypes among cameroonians and review of the global distribution: is there a case for a single sickle mutation origin in Africa?

Authors:  Valentina J Ngo Bitoungui; Gift D Pule; Neil Hanchard; Jeanne Ngogang; Ambroise Wonkam
Journal:  OMICS       Date:  2015-03

3.  Acute chest syndrome is associated with single nucleotide polymorphism-defined beta globin cluster haplotype in children with sickle cell anaemia.

Authors:  Christopher J Bean; Sheree L Boulet; Genyan Yang; Amanda B Payne; Nafisa Ghaji; Meredith E Pyle; W Craig Hooper; Pallav Bhatnagar; Jeffrey Keefer; Emily A Barron-Casella; James F Casella; Michael R Debaun
Journal:  Br J Haematol       Date:  2013-08-16       Impact factor: 6.998

Review 4.  Genetic Modifiers of Fetal Haemoglobin in Sickle Cell Disease.

Authors:  Stephan Menzel; Swee Lay Thein
Journal:  Mol Diagn Ther       Date:  2019-04       Impact factor: 4.074

5.  Original Research: A case-control genome-wide association study identifies genetic modifiers of fetal hemoglobin in sickle cell disease.

Authors:  Li Liu; Alexander Pertsemlidis; Liang-Hao Ding; Michael D Story; Martin H Steinberg; Paola Sebastiani; Carolyn Hoppe; Samir K Ballas; Betty S Pace
Journal:  Exp Biol Med (Maywood)       Date:  2016-03-27

Review 6.  Evolutionary history of sickle-cell mutation: implications for global genetic medicine.

Authors:  Kevin Esoh; Ambroise Wonkam
Journal:  Hum Mol Genet       Date:  2021-04-26       Impact factor: 6.150

7.  Evolutionary constraints in the β-globin cluster: the signature of purifying selection at the δ-globin (HBD) locus and its role in developmental gene regulation.

Authors:  Ana Moleirinho; Susana Seixas; Alexandra M Lopes; Celeste Bento; Maria J Prata; António Amorim
Journal:  Genome Biol Evol       Date:  2013       Impact factor: 3.416

8.  Frequency and origin of haplotypes associated with the beta-globin gene cluster in individuals with trait and sickle cell anemia in the Atlantic and Pacific coastal regions of Colombia.

Authors:  Cristian Fong; María Alejandra Lizarralde-Iragorri; Diana Rojas-Gallardo; Guillermo Barreto
Journal:  Genet Mol Biol       Date:  2013-11-08       Impact factor: 1.771

9.  Haplotype Analysis of β-Thalassaemia Major and Carriers with Filipino β°-Deletion in Sabah, Malaysia.

Authors:  Lai Kuan Teh; George Elizabeth; Mei I Lai; Lily Wong; Patimah Ismail
Journal:  Malays J Med Sci       Date:  2018-08-30

10.  Genetic comparison of sickle cell anaemia cohorts from Brazil and the United States reveals high levels of divergence.

Authors:  Pedro R S Cruz; Galina Ananina; Vera Lucia Gil-da-Silva-Lopes; Milena Simioni; Farid Menaa; Marcos A C Bezerra; Igor F Domingos; Aderson S Araújo; Renata Pellegrino; Hakon Hakonarson; Fernando F Costa; Mônica Barbosa de Melo
Journal:  Sci Rep       Date:  2019-07-26       Impact factor: 4.379

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