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1.
Vox Sang ; 116(4): 451-463, 2021 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-33567470

RESUMEN

BACKGROUND AND OBJECTIVES: Next generation sequencing (NGS) has promising applications in transfusion medicine. Exome sequencing (ES) is increasingly used in the clinical setting, and blood group interpretation is an additional value that could be extracted from existing data sets. We provide the first release of an open-source software tailored for this purpose and describe its validation with three blood group systems. MATERIALS AND METHODS: The DTM-Tools algorithm was designed and used to analyse 1018 ES NGS files from the ClinSeq® cohort. Predictions were correlated with serology for 5 antigens in a subset of 108 blood samples. Discrepancies were investigated with alternative phenotyping and genotyping methods, including a long-read NGS platform. RESULTS: Of 116 genomic variants queried, those corresponding to 18 known KEL, FY and JK alleles were identified in this cohort. 596 additional exonic variants were identified KEL, ACKR1 and SLC14A1, including 58 predicted frameshifts. Software predictions were validated by serology in 108 participants; one case in the FY blood group and three cases in the JK blood group were discrepant. Investigation revealed that these discrepancies resulted from (1) clerical error, (2) serologic failure to detect weak antigenic expression and (3) a frameshift variant absent in blood group databases. CONCLUSION: DTM-Tools can be employed for rapid Kell, Duffy and Kidd blood group antigen prediction from existing ES data sets; for discrepancies detected in the validation data set, software predictions proved accurate. DTM-Tools is open-source and in continuous development.


Asunto(s)
Alelos , Antígenos de Grupos Sanguíneos/análisis , Antígenos de Grupos Sanguíneos/genética , Secuenciación del Exoma/métodos , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Programas Informáticos , Sistema del Grupo Sanguíneo Duffy/genética , Variación Genética , Técnicas de Genotipaje , Humanos , Glicoproteínas de Membrana/genética , Proteínas de Transporte de Membrana/genética , Metaloendopeptidasas/genética , Receptores de Superficie Celular/genética , Transportadores de Urea
2.
Transfusion ; 58(11): 2693-2704, 2018 11.
Artículo en Inglés | MEDLINE | ID: mdl-30312480

RESUMEN

BACKGROUND: The 1000 Genomes Project provides a database of genomic variants from whole genome sequencing of 2504 individuals across five continental superpopulations. This database can enrich our background knowledge of worldwide blood group variant geographic distribution and identify novel variants of potential clinical significance. STUDY DESIGN AND METHODS: The 1000 Genomes database was analyzed to 1) expand knowledge about continental distributions of known blood group variants, 2) identify novel variants with antigenic potential and their geographic association, and 3) establish a baseline scaffold of chromosomal coordinates to translate next-generation sequencing output files into a predicted red blood cell (RBC) phenotype. RESULTS: Forty-two genes were investigated. A total of 604 known variants were mapped to the GRCh37 assembly; 120 of these were reported by 1000 Genomes in at least one superpopulation. All queried variants, including the ACKR1 promoter silencing mutation, are located within exon pull-down boundaries. The analysis yielded 41 novel population distributions for 34 known variants, as well as 12 novel blood group variants that warrant further validation and study. Four prediction algorithms collectively flagged 79 of 109 (72%) known antigenic or enzymatically detrimental blood group variants, while 4 of 12 variants that do not result in an altered RBC phenotype were flagged as deleterious. CONCLUSION: Next-generation sequencing has known potential for high-throughput and extended RBC phenotype prediction; a database of GRCh37 and GRCh38 chromosomal coordinates for 120 worldwide blood group variants is provided as a basis for this clinical application.


Asunto(s)
Genoma Humano/genética , Genómica/métodos , Algoritmos , Antígenos de Grupos Sanguíneos/genética , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos
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