摘要Background Analysis of changes in recipient and donor hematopoietic cell origin is extremely useful to monitor the effect of hematopoietic stem cell transplantation (HSCT) and sequential adoptive immunotherapy by donor lymphocyte infusions. We developed a sensitive, reliable and rapid real-time PCR method based on sequence polymorphism systems to quantitatively assess the hematopoietic chimerism after HSCT.Methods A panel of 29 selected sequence polymorphism (SP) markers was screened by real-time PCR in 101 HSCT patients with leukemia and other hematological diseases. The chimerism kinetics of bone marrow samples of 8 HSCT patients in remission and relapse situations were followed longitudinally.Results Recipient genotype discrimination was possible in 97.0% (98 of 101) with a mean number of 2.5 (1-7)informative markers per recipient/donor pair. Using serial dilutions of plasmids containing specific SP markers, the linear correlation (r) of 0.99, the slope between -3.2 and -3.7 and the sensitivity of 0.1% were proved reproducible. By this method, it was possible to very accurately detect autologous signals in the range from 0.1% to 30%. The accuracy of the method in the very important range of autologous signals below 5% was extraordinarily high (standard deviation <1.85%),which might significantly improve detection accuracy of changes in autologous signals early in the post-transplantation course of follow-up. The main advantage of the real-time PCR method over short tandem repeat PCR chimerism assays is the absence of PCR competition and plateau biases, with demonstrated greater sensitivity and linearity. Finally, we prospectively analyzed bone marrow samples of 8 patients who received allografts and presented the chimerism kinetics of remission and relapse situations that illustrated the sensitivity level and the promising clinical application of this method.Conclusion This SP-based real-time PCR assay provides a rapid, sensitive, and accurate quantitative assessment of mixed chimerism that can be useful in predicting graft rejection and early relapse.