An open‐source python library for detection of known and novel Kell, Duffy and Kidd variants from exome sequencing

Abstract

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.

Resolving Genotype–Phenotype Discrepancies of the Kidd Blood Group System Using Long-Read Nanopore Sequencing

“…The majority of JK weak and null alleles listed in the ISBT tables are known to occur at very low frequencies across different populations [4,21,22], supporting the low number of discrepancies identified in our study. Specifically, nanopore sequencing allowed us to identify the following known SNVs: c.130G>A (rs2298720), c.191G>A (rs114362217), c.742G>A (rs763095261), c.871T>C (rs78242949) and c.956C>T (rs565898944).…”

“…The latest advancements in third-generation long-read sequencing (TGS) technologies offer notable advantages, including the capacity to elucidate extensive haplotypes and characterize genomic regions that pose challenges for Sanger sequencing or next-generation short-read sequencing [1]. In the specific field of transfusion medicine, TGS complements traditional approaches used for the blood group assessment of samples with complex or discordant serological and genetic results [2][3][4][5][6]. Such cases include serological reactions Biomedicines 2024, 12, 225 2 of 12 exhibiting unexpected weak agglutination or null phenotypes, often resulting from rare or unknown genetic variants that are not typed in routine genotyping workflows [7].…”

Resolving genotype-phenotype discrepancies of the Kidd blood group system using long-read nanopore sequencing

“…The majority of JK weak and null alleles listed in the ISBT tables are known to occur at very low frequencies across different populations 4,19,20 , indirectly supporting the low number of discrepancies identified in our donor population. Specifically, we detected the rare SNVs c.742G>A (rs763095261), c.871T>C (rs78242949), c.956C>T (rs565898944), and c.191G>A (rs114362217) in our discrepant samples, as part of JK*01W.05, JK*02N.06, JK*02N.08 and JK*02N.09 alleles, respectively (Table 1).…”

“…The latest advancements in third-generation long-read sequencing (TGS) technologies offer notable advantages, including the capacity to elucidate extensive haplotypes and characterize genomic regions that pose challenges to Sanger sequencing or next-generation short-read sequencing [1]. In the specific field of transfusion medicine, TGS complements traditional approaches used for the blood group assessment of samples with complex or discordant serological and genetic results [2][3][4][5][6]. Such cases include serological reactions exhibiting unexpected weak agglutination or null phenotypes, often resulting from rare or unknown genetic variants that are not typed in routine genotyping workflows [7].…”