Y Fichou1,2, M Mariez1,2, C Le Maréchal1,2,3,4, C Férec1,2,3,4. 1. Etablissement Français du Sang (EFS) - Région Bretagne, Brest, France. 2. Institut National de la Santé et de la Recherche Médicale (Inserm), UMR1078, Brest, France. 3. Laboratoire de Génétique Moléculaire et d'Histocompatibilité, Centre Hospitalier Régional Universitaire (CHRU), Hôpital Morvan, Brest, France. 4. Faculté de Médecine et des Sciences de la Santé, Université de Bretagne Occidentale (UBO), Brest, France.
Abstract
BACKGROUND: Patients suffering from haemoglobinopathies may be treated by red blood cell (RBC) transfusion on a regular basis and then exposed to multiple antigens with a recurrent, potential risk of alloimmunization routinely prevented by extended RBC antigen cross-matching. While time-consuming and labour-intensive serological analyses are the gold standard for RBC typing, genotyping by current high-throughput molecular tools, including next-generation sequencing (NGS), appears to offer a potent alternative. STUDY DESIGN AND METHODS: The potential of extended blood group genotyping (EBGG) by NGS of 17 genes involved in 14 blood group systems was evaluated in a cohort of 48 patients with sickle-cell disease. Sample preparation and sequencing were simplified and automated for future routine implementation. RESULTS: Sequencing data were obtained for all DNA samples with two different sequencing machines. Prediction of phenotypes could be made in 12 blood group systems and partially in two other blood group systems (Rh and MNS). Importantly, predicted phenotypes in the MNS (S/s), Duffy, Kidd and Kell systems matched well with serological data (98·9%), when available. Unreferenced alleles in the ACHE and ART4 genes, respectively, involved in the Yt and Dombrock blood groups, were identified, then contributing to extend the current knowledge of blood group molecular genetics. CONCLUSIONS: Overall, we consider that our strategy for NGS-based EBGG, assisted by a simple method for genotyping exons 1 and 2 of the pairs of homologous genes (i.e. RHD/RHCE and GYPA/GYPB), as well as the future support of potent bioinformatics tools, may be implemented for routine diagnosis in specific populations.
BACKGROUND:Patients suffering from haemoglobinopathies may be treated by red blood cell (RBC) transfusion on a regular basis and then exposed to multiple antigens with a recurrent, potential risk of alloimmunization routinely prevented by extended RBC antigen cross-matching. While time-consuming and labour-intensive serological analyses are the gold standard for RBC typing, genotyping by current high-throughput molecular tools, including next-generation sequencing (NGS), appears to offer a potent alternative. STUDY DESIGN AND METHODS: The potential of extended blood group genotyping (EBGG) by NGS of 17 genes involved in 14 blood group systems was evaluated in a cohort of 48 patients with sickle-cell disease. Sample preparation and sequencing were simplified and automated for future routine implementation. RESULTS: Sequencing data were obtained for all DNA samples with two different sequencing machines. Prediction of phenotypes could be made in 12 blood group systems and partially in two other blood group systems (Rh and MNS). Importantly, predicted phenotypes in the MNS (S/s), Duffy, Kidd and Kell systems matched well with serological data (98·9%), when available. Unreferenced alleles in the ACHE and ART4 genes, respectively, involved in the Yt and Dombrock blood groups, were identified, then contributing to extend the current knowledge of blood group molecular genetics. CONCLUSIONS: Overall, we consider that our strategy for NGS-based EBGG, assisted by a simple method for genotyping exons 1 and 2 of the pairs of homologous genes (i.e. RHD/RHCE and GYPA/GYPB), as well as the future support of potent bioinformatics tools, may be implemented for routine diagnosis in specific populations.
Authors: Celina Montemayor-Garcia; Panagiota Karagianni; David A Stiles; Erika M Reese; Danielle A Smellie; Debrean A Loy; Kimberly Y Levy; Magdalene Nwokocha; Marina U Bueno; Jeffery L Miller; Harvey G Klein Journal: Transfusion Date: 2018-10-12 Impact factor: 3.157
Authors: Silja M Tammi; Wajnat A Tounsi; Susanna Sainio; Michele Kiernan; Neil D Avent; Tracey E Madgett; Katri Haimila Journal: Blood Adv Date: 2020-10-27