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Comprehensive red blood cell and platelet antigen prediction from whole genome sequencing: proof of principle.

ABSTRACT: BACKGROUND:There are 346 serologically defined red blood cell (RBC) antigens and 33 serologically defined platelet (PLT) antigens, most of which have known genetic changes in 45 RBC or six PLT genes that correlate with antigen expression. Polymorphic sites associated with antigen expression in the primary literature and reference databases are annotated according to nucleotide positions in cDNA. This makes antigen prediction from next-generation sequencing data challenging, since it uses genomic coordinates. STUDY DESIGN AND METHODS:The conventional cDNA reference sequences for all known RBC and PLT genes that correlate with antigen expression were aligned to the human reference genome. The alignments allowed conversion of conventional cDNA nucleotide positions to the corresponding genomic coordinates. RBC and PLT antigen prediction was then performed using the human reference genome and whole genome sequencing (WGS) data with serologic confirmation. RESULTS:Some major differences and alignment issues were found when attempting to convert the conventional cDNA to human reference genome sequences for the following genes: ABO, A4GALT, RHD, RHCE, FUT3, ACKR1 (previously DARC), ACHE, FUT2, CR1, GCNT2, and RHAG. However, it was possible to create usable alignments, which facilitated the prediction of all RBC and PLT antigens with a known molecular basis from WGS data. Traditional serologic typing for 18 RBC antigens were in agreement with the WGS-based antigen predictions, providing proof of principle for this approach. CONCLUSION:Detailed mapping of conventional cDNA annotated RBC and PLT alleles can enable accurate prediction of RBC and PLT antigens from whole genomic sequencing data.

SUBMITTER: Lane WJ

PROVIDER: S-EPMC5019240 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Comprehensive red blood cell and platelet antigen prediction from whole genome sequencing: proof of principle.

Lane William J WJ Westhoff Connie M CM Uy Jon Michael JM Aguad Maria M Smeland-Wagman Robin R Kaufman Richard M RM Rehm Heidi L HL Green Robert C RC Silberstein Leslie E LE

Transfusion 20151203 3

<h4>Background</h4>There are 346 serologically defined red blood cell (RBC) antigens and 33 serologically defined platelet (PLT) antigens, most of which have known genetic changes in 45 RBC or six PLT genes that correlate with antigen expression. Polymorphic sites associated with antigen expression in the primary literature and reference databases are annotated according to nucleotide positions in cDNA. This makes antigen prediction from next-generation sequencing data challenging, since it uses ...[more]

PMID: 26634332

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Project description:BackgroundThere are more than 300 known red blood cell (RBC) antigens and 33 platelet antigens that differ between individuals. Sensitisation to antigens is a serious complication that can occur in prenatal medicine and after blood transfusion, particularly for patients who require multiple transfusions. Although pre-transfusion compatibility testing largely relies on serological methods, reagents are not available for many antigens. Methods based on single-nucleotide polymorphism (SNP) arrays have been used, but typing for ABO and Rh-the most important blood groups-cannot be done with SNP typing alone. We aimed to develop a novel method based on whole-genome sequencing to identify RBC and platelet antigens.MethodsThis whole-genome sequencing study is a subanalysis of data from patients in the whole-genome sequencing arm of the MedSeq Project randomised controlled trial (NCT01736566) with no measured patient outcomes. We created a database of molecular changes in RBC and platelet antigens and developed an automated antigen-typing algorithm based on whole-genome sequencing (bloodTyper). This algorithm was iteratively improved to address cis-trans haplotype ambiguities and homologous gene alignments. Whole-genome sequencing data from 110 MedSeq participants (30 × depth) were used to initially validate bloodTyper through comparison with conventional serology and SNP methods for typing of 38 RBC antigens in 12 blood-group systems and 22 human platelet antigens. bloodTyper was further validated with whole-genome sequencing data from 200 INTERVAL trial participants (15 × depth) with serological comparisons.FindingsWe iteratively improved bloodTyper by comparing its typing results with conventional serological and SNP typing in three rounds of testing. The initial whole-genome sequencing typing algorithm was 99·5% concordant across the first 20 MedSeq genomes. Addressing discordances led to development of an improved algorithm that was 99·8% concordant for the remaining 90 MedSeq genomes. Additional modifications led to the final algorithm, which was 99·2% concordant across 200 INTERVAL genomes (or 99·9% after adjustment for the lower depth of coverage).InterpretationBy enabling more precise antigen-matching of patients with blood donors, antigen typing based on whole-genome sequencing provides a novel approach to improve transfusion outcomes with the potential to transform the practice of transfusion medicine.FundingNational Human Genome Research Institute, Doris Duke Charitable Foundation, National Health Service Blood and Transplant, National Institute for Health Research, and Wellcome Trust.

Project description:Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

Project description:In this work we demonstrate a novel method of methylation detection that utilises immunoaffinity to detect the presence of methylated DNA hybridised to a cDNA microarray. We use a monoclonal antibody specific to 5 methylcytosine to detect the presence of 5 methylcytosine in genomic DNA from human fibroblasts bearing the karyotype 45 XO. We report that over 2900 genes show the presence of methylation in this condition. We also report that 165 genes are consistently methylated in all replicates of these experiments. The methylated genes show a uniform distribution over all the chromosomes. The gene ontology of these also indicates no functional correlation between the genes that are methylated. We detect the presence of methylation in IGF2, an imprinted gene and thus known to harbour DNA methylation. The method is extremely specific and offers a quick and efficient way to analyse the methylation landscape on a high throughput scale. This method uses existing technology to assess methylation and thus can integrate very efficiently into any platform used. A method that detects DNA methylation that is not restricted to specific sequences would provide a useful platform to analyse methylation distribution among the genes in any given phenotypic condition.Availability of additional approaches to examine DNA methylation would lead to increase in our understanding of the methylome and would help define the intrinsic and extrinsic factors which govern it. Microarray based high throughput methods have been extensively used for gene expression analysis. The method described uses a microarray to analyse DNA methylation levels in a gene/cDNA/oligo specific manner. Here, genomic DNA is fragmented and used for hybridization to microarray slides. The presence of DNA cytosine methylation in the hybridized DNA is detected by employing Cy3 labelled anti 5mC( 5-methyl cytidine) antibody (monoclonal). The resolution provided by this method is dependent upon the microarray platform used. This method can be adapted to any platform thus enabling seamless integration with existing technology of gene expression analysis

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Comprehensive red blood cell and platelet antigen prediction from whole genome sequencing: proof of principle.

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Comprehensive red blood cell and platelet antigen prediction from whole genome sequencing: proof of principle.

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