Literature DB >> 30592300

A whole genome approach for discovering the genetic basis of blood group antigens: independent confirmation for P1 and Xga.

William J Lane1,2, Maria Aguad1, Robin Smeland-Wagman1, Sunitha Vege3, Helen H Mah1, Abigail Joseph1, Carrie L Blout4, Tiffany T Nguyen4, Matthew S Lebo1,2,5,6, Manpreet Sidhu3, Christine Lomas-Francis3, Richard M Kaufman1,2, Robert C Green2,4,6,7, Connie M Westhoff3.   

Abstract

BACKGROUND: Although P1 and Xga are known to be associated with the A4GALT and XG genes, respectively, the genetic basis of antigen expression has been elusive. Recent reports link both P1 and Xga expression with nucleotide changes in the promotor regions and with antigen-negative phenotypes due to disruption of transcription factor binding. STUDY DESIGN AND METHODS: Whole genome sequencing was performed on 113 individuals as part of the MedSeq Project with serologic RBC antigen typing for P1 (n = 77) and Xga (n = 15). Genomic data were analyzed by two approaches, nucleotide frequency correlation and serologic correlation, to find A4GALT and XG changes associated with P1 and Xga expression.
RESULTS: For P1, the frequency approach identified 29 possible associated nucleotide changes, and the serologic approach revealed four among them correlating with the P1+/P1- phenotype: chr22:43,115,523_43,115,520AAAG/delAAAG (rs66781836); chr 22:43,114,551C/T (rs8138197); chr22:43,114,020 T/G (rs2143918); and chr22:43,113,793G/T (rs5751348). For Xga , the frequency approach identified 82 possible associated nucleotide changes, and among these the serologic approach revealed one correlating with the Xg(a+)/Xg(a-) phenotype: chrX:2,666,384G/C (rs311103).
CONCLUSION: A bioinformatics analysis pipeline was created to identify genetic changes responsible for RBC antigen expression. This study, in progress before the recently published reports, independently confirms the basis for P1 and Xga . Although this enabled molecular typing of these antigens, the Y chromosome PAR1 region interfered with Xga typing in males. This approach could be used to identify and confirm the genetic basis of antigens, potentially replacing the historical approach using family pedigrees as genomic sequencing becomes commonplace.
© 2018 AABB.

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Year:  2018        PMID: 30592300      PMCID: PMC6402986          DOI: 10.1111/trf.15089

Source DB:  PubMed          Journal:  Transfusion        ISSN: 0041-1132            Impact factor:   3.157


  4 in total

1.  Major sex differences in allele frequencies for X chromosomal variants in both the 1000 Genomes Project and gnomAD.

Authors:  Zhong Wang; Lei Sun; Andrew D Paterson
Journal:  PLoS Genet       Date:  2022-05-31       Impact factor: 6.020

Review 2.  Banking with precision: transfusion medicine as a potential universal application in clinical genomics.

Authors:  Celina Montemayor; Patricia A R Brunker; Margaret A Keller
Journal:  Curr Opin Hematol       Date:  2019-11       Impact factor: 3.284

Review 3.  Next-Generation Sequencing Technologies in Blood Group Typing.

Authors:  Daniel Fürst; Chrysanthi Tsamadou; Christine Neuchel; Hubert Schrezenmeier; Joannis Mytilineos; Christof Weinstock
Journal:  Transfus Med Hemother       Date:  2019-12-11       Impact factor: 3.747

4.  Defining Blood Group Gene Reference Alleles by Long-Read Sequencing: Proof of Concept in the ACKR1 Gene Encoding the Duffy Antigens.

Authors:  Yann Fichou; Isabelle Berlivet; Gaëlle Richard; Christophe Tournamille; Lilian Castilho; Claude Férec
Journal:  Transfus Med Hemother       Date:  2019-12-11       Impact factor: 3.747

  4 in total

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