A high-throughput droplet digital PCR system aiming eight DNA methylation targets for age prediction

数字聚合酶链反应 多路复用 化学 计算生物学 DNA甲基化 DNA 聚合酶链反应 一致相关系数 生物系统 分子生物学 分析化学(期刊) 统计 色谱法 遗传学 生物 生物化学 数学 基因 基因表达
作者
Yuxiang Zhou,Yanyun Wang,Mengyuan Song,Lanrui Jiang,Chaoran Sun,Shuangshuang Wang,Hewen Yao,Zefei Wang,Xindi Wang,Chunhui Liu,Haibo Luo,Feng Song
出处
期刊:Journal of Pharmaceutical and Biomedical Analysis [Elsevier BV]
卷期号:240: 115943-115943 被引量:2
标识
DOI:10.1016/j.jpba.2023.115943
摘要

The droplet digital Polymerase Chain Reaction (ddPCR) has garnered recognition for its distinctive attribute of absolute quantification. And it has found practical utility in age prediction through DNA methylation profiles. However, a prevalent limitation in current ddPCR methodologies is the restricted capacity to detect only two targets concurrently in most instruments, leading to high costs, sample wastage, and labor-intensive procedures. To address the limitations, a novel high-throughput ddPCR system allowing for the simultaneous detection of eight targets was developed. Through the implementation of a new 8-plex ddPCR assay, coupled with comprehensive linear regression analyses involving primers and probes ratios, diverse inputs of single CpG sites with distinct primers and probes, and varying plex assay configurations, stable DNA methylation values for four CpGs and stable measurement precisions for distinct multiplex systems were consistently observed. These findings pave the way for advancing the field of chemistry science by enabling more efficient and cost-effective methods. Furthermore, the comparative validation of ddPCR and SNaPshot demonstrated a remarkable concordance in results, and the system also displayed well in the field of various aspects, including species specificity, DNA input, and aged samples. In this study, the recommended input of bisulfite-converted DNA was determined to be 10–50 ng due to the double-positive droplets. Notably, the Pearson correlation coefficient squared values of four CpGs were 0.4878 (ASPA), 0.4832 (IGSF1), 0.6881 (COL1A1), and 0.6475 (MEIS1-AS3). And the testing set exhibited a mean absolute error of 4.5923 years, indicating the robustness and accuracy of the age-predictive model.
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