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

Shaikho, Elmutaz M.; Farrell, John; Alsultan, Abdulrahman; Qutub, Hatem; Al-Ali, Amein K.; Figueiredo, Maria Stella; Chui, David H.K.; Farrer, Lindsay A.; Murphy, George J.; Mostoslavsky, Gustavo; Sebastiani, Paola; Steinberg, Martin H.

doi:10.1186/s12864-017-4013-y

Cited by 37 publications

(29 citation statements)

References 18 publications

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“…Of the canonical sites, we predicted 5′ ε HincII with rs3834466, Gγ1 HindIII with rs2070972, Aγ1 HindIII with rs28440105, and 3′ ψβ HincII with rs968857 ( Table 1 ); similar results were described in a previously reported analysis of rs3834466, rs28440105, rs10128556, and rs968857. 40 Pairwise correlation (measured via

) between these variants and rs334 was weak to nonexistent ( Table 1 ). On the basis of these four RFLP-predicting markers, we identified ten unique haplotypes.…”

Section: Resultsmentioning

confidence: 98%

Whole-Genome-Sequence-Based Haplotypes Reveal Single Origin of the Sickle Allele during the Holocene Wet Phase

Shriner

Rotimi

2018

The American Journal of Human Genetics

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Five classical designations of sickle haplotypes are made on the basis of the presence or absence of restriction sites and are named after the ethno-linguistic groups or geographic regions from which the individuals with sickle cell anemia originated. Each haplotype is thought to represent an independent occurrence of the sickle mutation rs334 (c.20A>T [p.Glu7Val] in HBB). We investigated the origins of the sickle mutation by using whole-genome-sequence data. We identified 156 carriers from the 1000 Genomes Project, the African Genome Variation Project, and Qatar. We classified haplotypes by using 27 polymorphisms in linkage disequilibrium with rs334. Network analysis revealed a common haplotype that differed from the ancestral haplotype only by the derived sickle mutation at rs334 and correlated collectively with the Central African Republic (CAR), Cameroon, and Arabian/Indian haplotypes. Other haplotypes were derived from this haplotype and fell into two clusters, one composed of Senegal haplotypes and the other composed of Benin and Senegal haplotypes. The near-exclusive presence of the original sickle haplotype in the CAR, Kenya, Uganda, and South Africa is consistent with this haplotype predating the Bantu expansions. Modeling of balancing selection indicated that the heterozygote advantage was 15.2%, an equilibrium frequency of 12.0% was reached after 87 generations, and the selective environment predated the mutation. The posterior distribution of the ancestral recombination graph yielded a sickle mutation age of 259 generations, corresponding to 7,300 years ago during the Holocene Wet Phase. These results clarify the origin of the sickle allele and improve and simplify the classification of sickle haplotypes.

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) between these variants and rs334 was weak to nonexistent ( Table 1 ). On the basis of these four RFLP-predicting markers, we identified ten unique haplotypes.…”

Section: Resultsmentioning

confidence: 98%

Whole-Genome-Sequence-Based Haplotypes Reveal Single Origin of the Sickle Allele during the Holocene Wet Phase

Shriner

Rotimi

2018

The American Journal of Human Genetics

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“…The 1KGP dataset is frequently used for population-based downstream applications, such as genotype phasing and imputation, due to its genetic diversity and large sample size [30][31][32][33] . To illustrate how the accuracy of the DV-GLN-OPT callset translates into improved results for these downstream analyses, we assessed the performance of imputing variants using it as a reference panel.…”

Section: Evaluation Of 1kgp Callsets As Imputation Reference Panelsmentioning

confidence: 99%

Accurate, scalable cohort variant calls using DeepVariant and GLnexus

Yun

Chang

et al. 2020

Preprint

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Population-scale sequenced cohorts are foundational resources for many genetic analyses, but creating them from single-sample variant calls remains challenging. Here we introduce an open-source cohort-calling method that uses the highly accurate germline caller DeepVariant and scalable merging tool GLnexus. Using callset quality metrics based on variant recall and precision in benchmark samples and Mendelian consistency in father-mother-child trios, we optimized the method across a range of cohort sizes, sequencing methods, and sequencing depths. The resulting callsets show consistent quality improvements over those generated using existing best practices. We further evaluated the DeepVariant+GLnexus pipeline in the deeply sequenced 1000 Genomes Project phase 3 samples (1KGP) and show superior callset quality metrics and imputation reference panel performance compared to an independently-generated GATK Best Practices pipeline. We publicly release the 1KGP individual-level variant calls and cohort callset to foster additional development and evaluation of cohort merging methods as well as broad studies of genetic variation.

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“…Reticulocyte count was also significantly higher in Hb SS group (p 0.013) suggesting increased rates of haemolysis compared to SBT. rs28440105, rs10128556 and rs968857) in 9 Hb SS patients as described previously [17]. When looking at the genetic variants that moderate Hb F levels, rs6545816 in BCL11A was found at the highest allele frequency (88%) followed by rs7482144 in Xmn I-HBG2 (47%) ( Table 3).…”

Section: Haematological Datamentioning

confidence: 56%

Sickle cell disease in Sri Lanka: Clinical and molecular basis and the unanswered questions about disease severeity.

Darshana

Bandara²,

Nawarathne³

et al. 2020

Preprint

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Background Though case reports and limited case series of Sickle cell disease in Sri Lanka have been reported previously, no attempt has been made hitherto to undertake a comprehensive genotypic-phenotypic analysis of this “rare” group of patients.Results All accessible Sickle cell disease patients, totaling 60, including, 51 Sickle β-thalassaemia and 9 homozygous sickle patients were enrolled from seven thalassaemia treatment centres between December 2016 - March 2019. The majority of patients were of Sinhalese ethnicity (n=52, 86.67%). Geographically, two prominent clusters were identified and the distribution of Sickle haemoglobin in the island contrasted markedly with the other haemoglobinopathies. 3/ 9 homozygous sickle patients and 3/ 51 Sickle β-thalassaemia patients were receiving regular transfusion. Joint pain was the commonest clinical presentation among all sickle cell disease patients (n=39, 65.0%). Dactylitis was significantly more common in homozygous sickle patients compared with the Sickle β-thalassaemia group ( p 0.034). Two genetic backgrounds sickle mutation were identified namely, Arab Indian and Benin. Among the regulators of Foetal hemoglobin in Sickle patients of the present study rs1427407 G>T seemed to be the most prominent modifier, with a significant association with Foetal haemoglobin levels ( p 0.04).Conclusions Overall, the clinical course of the Asian version of Sickle cell disease in Sri Lanka appears to be milder than that described in India.

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

Cited by 37 publications

References 18 publications

Whole-Genome-Sequence-Based Haplotypes Reveal Single Origin of the Sickle Allele during the Holocene Wet Phase

Whole-Genome-Sequence-Based Haplotypes Reveal Single Origin of the Sickle Allele during the Holocene Wet Phase

Accurate, scalable cohort variant calls using DeepVariant and GLnexus

Sickle cell disease in Sri Lanka: Clinical and molecular basis and the unanswered questions about disease severeity.

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