Establishment of Rapid Detection Methods for rs76971248 Related to Leukemia

Abstract

Background. The HLA-E gene is a member of the HLA-I gene family. Its genetic polymorphism is regarded as associated with numerous diseases. Establishing a rapid and accurate detection method of disease-related SNP sites in HLA-E is particularly important. Methods. Blood samples from 226 healthy blood donors and 228 leukemia patients were collected, and DNA was extracted. Three typing methods based on PCR-sequence-based typing, TaqMan genotyping, and high-resolution melting curve were established to identify rs76971248 (G>T). The Chi-square test was used for statistical analysis by SPSS. Results. Three methods based on PCR-SBT, TaqMan genotyping, and HRM were all able to identify rs76971248. The software for analyzing the results of HLA-E sequencing was easy to use, and the results were accurate. The frequency of rs76971248 in different types of leukemia patients was significantly lower than that in healthy blood donors ( p < 0.05 ). And the frequency of the G/G genotype in leukemia patients was significantly higher than that in healthy blood donors ( p < 0.05 ). Conclusions. For the screening of known SNP sites in large-scale populations, among the three methods, the TaqMan genotyping method had the advantage of shortest time consumption, simplest operation, and greatest specificity, which was the most appropriate method for this experiment. The analysis software for HLA-E gene sequencing needed to be further optimized. rs76971248 had a protective effect against leukemia. And the G/G genotype was a risk factor for leukemia.

ATAXIC: An Algorithm to Quantify Transcriptomic Perturbation Heterogeneity in Single Cancer Cells

“…In particular, the single-cell RNA sequencing (scRNA-seq) has shown its power in analyzing gene expression pro les in thousands of individual cells in one test [2,3]. A major advantage of the scRNA-seq technology is that it enables characterization of sophisticated biological processes at single-cell resolution to capture transcriptional snapshots of rare events [4,5]. us, this technology has recently been widely used to quantify transcriptomic pro les in di erent components of bulk tumors, including cancer cells, immune cells, stromal cells, and normal cells [6][7][8][9][10][11][12][13].…”