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Development and evaluation of a transfusion medicine genome wide genotyping array
Author(s) -
Guo Yuelong,
Busch Michael P.,
Seielstad Mark,
EndresDighe Stacy,
Westhoff Connie M.,
Keating Brendan,
Hoppe Carolyn,
Bordbar Aarash,
Custer Brian,
Butterworth Adam S.,
Kanias Tamir,
Mast Alan E.,
Kleinman Steve,
Lu Yontao,
Page Grier P.
Publication year - 2019
Publication title -
transfusion
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.045
H-Index - 132
eISSN - 1537-2995
pISSN - 0041-1132
DOI - 10.1111/trf.15012
Subject(s) - genotyping , concordance , single nucleotide polymorphism , snp array , copy number variation , snp genotyping , minor allele frequency , genetics , biology , transfusion medicine , snp , imputation (statistics) , human genome , computational biology , genome , blood transfusion , gene , genotype , computer science , immunology , machine learning , missing data
BACKGROUND Many aspects of transfusion medicine are affected by genetics. Current single‐nucleotide polymorphism (SNP) arrays are limited in the number of targets that can be interrogated and cannot detect all variation of interest. We designed a transfusion medicine array (TM‐Array) for study of both common and rare transfusion‐relevant variations in genetically diverse donor and recipient populations. STUDY DESIGN AND METHODS The array was designed by conducting extensive bioinformatics mining and consulting experts to identify genes and genetic variation related to a wide range of transfusion medicine clinical relevant and research‐related topics. Copy number polymorphisms were added in the alpha globin, beta globin, and Rh gene clusters. RESULTS The final array contains approximately 879,000 SNP and copy number polymorphism markers. Over 99% of SNPs were called reliably. Technical replication showed the array to be robust and reproducible, with an error rate less than 0.03%. The array also had a very low Mendelian error rate (average parent–child trio accuracy of 0.9997). Blood group results were in concordance with serology testing results, and the array accurately identifies rare variants (minor allele frequency of 0.5%). The array achieved high genome‐wide imputation coverage for African‐American (97.5%), Hispanic (96.1%), East Asian (94.6%), and white (96.1%) genomes at a minor allele frequency of 5%. CONCLUSIONS A custom array for transfusion medicine research has been designed and evaluated. It gives wide coverage and accurate identification of rare SNPs in diverse populations. The TM‐Array will be useful for future genetic studies in the diverse fields of transfusion medicine research.