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CD36 may defect on platelets and/or monocytes in healthy individuals, which was defined as CD36 deficiency. However, we did not know the correlation between the molecular and protein levels completely. Here, we aim to determine the polymorphisms of the CD36 gene, RNA level, and CD36 on platelets and in plasma. The individuals were sequenced by Sanger sequencing. Bioinformational analysis was used by the HotMuSiC, CUPSAT, SAAFEC-SEQ, and FoldX. RNA analysis and CD36 protein detection were performed by qPCR, flow cytometry, and ELISA. In this study, we found c.1228_1239delATTGTGCCTATT (allele frequency = 0.0072) with the highest frequency among our cohort, and one mutation (c.1329_1354dupGATAGAAATGATCTTACTCAGTGTTG) was not present in the dbSNP database. 5 mutations located in the extracellular domain sequencing region with confirmation in deficient individuals, of which c.284T>C, c.512A>G, c.572C>T, and c.869T>C were found to have a deleterious impact on CD36 protein stability. Furthermore, the MFI of CD36 expression on platelets in the mutation-carry, deleterious-effect, and deficiency group was significantly lower than the no-mutation group (P < 0.0500). In addition, sCD36 levels in type II individuals were significantly lower compared with positive controls (P = 0.0060). Nevertheless, we found the presence of sCD36 in a type I individual. RNA analysis showed CD36 RNA levels in platelets of type II individuals were significantly lower than the positive individuals (P = 0.0065). However, no significant difference was observed in monocytes (P = 0.7500). We identified the most prevalent mutation (c.1228_1239delATTGTGCCTATT) among Kunming donors. Besides, our results suggested RNA level alterations could potentially underlie type II deficiency. Furthermore, sCD36 may hold promise for assessing immune reaction risk in CD36-deficient individuals, but more studies should be conducted to validate this hypothesis.
CD36 may defect on platelets and/or monocytes in healthy individuals, which was defined as CD36 deficiency. However, we did not know the correlation between the molecular and protein levels completely. Here, we aim to determine the polymorphisms of the CD36 gene, RNA level, and CD36 on platelets and in plasma. The individuals were sequenced by Sanger sequencing. Bioinformational analysis was used by the HotMuSiC, CUPSAT, SAAFEC-SEQ, and FoldX. RNA analysis and CD36 protein detection were performed by qPCR, flow cytometry, and ELISA. In this study, we found c.1228_1239delATTGTGCCTATT (allele frequency = 0.0072) with the highest frequency among our cohort, and one mutation (c.1329_1354dupGATAGAAATGATCTTACTCAGTGTTG) was not present in the dbSNP database. 5 mutations located in the extracellular domain sequencing region with confirmation in deficient individuals, of which c.284T>C, c.512A>G, c.572C>T, and c.869T>C were found to have a deleterious impact on CD36 protein stability. Furthermore, the MFI of CD36 expression on platelets in the mutation-carry, deleterious-effect, and deficiency group was significantly lower than the no-mutation group (P < 0.0500). In addition, sCD36 levels in type II individuals were significantly lower compared with positive controls (P = 0.0060). Nevertheless, we found the presence of sCD36 in a type I individual. RNA analysis showed CD36 RNA levels in platelets of type II individuals were significantly lower than the positive individuals (P = 0.0065). However, no significant difference was observed in monocytes (P = 0.7500). We identified the most prevalent mutation (c.1228_1239delATTGTGCCTATT) among Kunming donors. Besides, our results suggested RNA level alterations could potentially underlie type II deficiency. Furthermore, sCD36 may hold promise for assessing immune reaction risk in CD36-deficient individuals, but more studies should be conducted to validate this hypothesis.
CD36, also known as glycoprotein IV, is classified into two distinct subgroups based on the presence or absence of its expression on monocytes. The CD36 gene spans approximately 50,000 base pairs. Historically, research has focused on identifying CD36 mutations through Sanger sequencing and next-generation sequencing (NGS), with limited exploration of haplotypes. In this study, we collected blood samples from donors with type I and type II CD36 deficiencies as well as from healthy controls, and employed single-molecule long-read sequencing (also known as Third-Generation Sequencing) of genomic DNA to analyze the genetic basis of CD36. The study identified 180 genetic variants, 12 of which were found to alter the amino acid sequence. Notably, four of these mutations (c.220 C > T; c.329_330delAC; c.430-1 G > C; c.1006 + 2 T > G) are premature termination mutations that lead to protein truncation. Using Fisher’s exact test, we statistically analyzed a specific haplotype, c.-132A > C and c.329_330delAC, along with their clinical phenotypes, revealing a strong association between these variants in the 5’ block and type I CD36 deficiency. We analyzed the CD36 gene sequences in platelet donors and patients with PTR (platelet transfusion refractoriness) and FNAIT (fetal and neonatal alloimmune thrombocytopenia), conducting a detailed haplotype analysis associated with type I CD36 deficiency and FNAIT. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-74917-0.
Background and ObjectivesAccurate human leucocyte antigen (HLA) and human platelet antigen (HPA) typing is essential for establishing a blood platelet donor bank to deal with refractoriness in patients undergoing multiple platelet transfusions. Current methods, such as Sanger and next‐generation sequencing, encounter difficulties in haplotyping. Herein, the aim of this study was to establish a method for HLA and HPA typing based on the long read sequencing.Study Design and MethodsThe HPA and HLA class I genotypes of 268 platelet donors from the Taiyuan Blood Center, China were identified using long‐read sequencing on the PacBio platform. Allele frequencies for HPA systems and HLA class I genes were calculated, and genetic variability within HPA system genes was analysed.ResultsPolymorphisms were identified in 8 of the 35 HPA systems (HPA‐1 to HPA‐6w, HPA‐15 and HPA‐21w), with the frequencies of the ‘b’ allele at 0.0187, 0.0709, 0.4086, 0.0075, 0.0149, 0.0317, 0.4310 and 0.0019, respectively. The alleles with the highest frequencies at the HLA‐A, HLA‐B and HLA‐C loci are HLA‐A02:01, B51:01, B46:01 and C06:02, respectively. Additionally, several genetic patterns in HPA systems were identified, including the c.166‐1029C>T variant, which was found exclusively in samples carrying the HPA‐1b allele.ConclusionThis study developed a targeted long‐read sequencing method characterized by high throughput and simultaneity, capable of resolving allele ambiguities for effective HLA class I genotyping in establishing a platelet donor bank.
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