ArticleBlood transfusion = Trasfusione del sangue
The RHCE*CeRN allele: molecular junction characterization and frequency distribution in Sub-Saharan African populations.
Article in Blood transfusion = Trasfusione del sangue. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe CeRN (RHCE*02.10) allele was described as resulting from hybrid RHCE-D-CE genes, involving either exon 4 alone or exon 4 and part of exon 3. No solution allows to distinguish between the two reported CeRN alleles. The objectives of this study were to determine the existence of both alleles, their genetic sequence and their frequencies. MATERIALS AND
methodsWe investigated 17 heterozygous CeRN samples and 10 homozygous CeRN samples, and described the junction between the RHCE and RHD genes. Analysis combined classical PCR associated with Sanger sequencing, and Oxford Nanopore NGS applied to long-range PCR.We also explored CeRN allelic frequency in sub-Saharan populations from the 1000 Genomes Project and the International Genome Sample Resource.
resultsOne CeRN allele sequence was observed, involving exon 4 alone with an RHCE-RHD junction approximately 400 base-pairs upstream of exon 4.We observed the CeRN allele in Gambian ethnic groups, with a maximum allelic frequency of 6.0% in the Fula group. DISCUSSION: The CeRN allele involving exon 4 and part of exon 3 was not observed here, supporting at least a low frequency, as our sample size limited the power to investigate this putative second CeRN variant.The homogeneity of the CeRN sequence observed in DNA samples and the high allelic frequency are consistent with a single genetic founder event in the Fula ancestral group.Nearly 20% of individuals in The Gambia have abnormal hemoglobin. Knowledge of CeRN genetic architecture and frequency may have significant implications for more precise molecular diagnostics and transfusion therapy.The probabilistic pipeline developed here, based on subset of samples for which both DNA and WGS data were available, showed that WGS low-coverage data can be used to investigate complex genetic variants in population studies.
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