Construction and evaluation of in-house methylation-sensitive SNaPshot system and three classification prediction models for identifying the tissue origin of body fluid  

作　　者：Yating FANG Man CHEN Bofeng ZHU 

机构地区：[1]Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification,School of Forensic Medicine,Southern Medical University,Guangzhou,510515,China [2]School of Basic Medical Sciences,Anhui Medical University,Hefei,230031,China [3]Microbiome Medicine Center,Department of Laboratory Medicine,Zhujiang Hospital,Southern Medical University,Guangzhou,510515,China

出　　处：《Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)》2023年第9期839-852,共14页浙江大学学报（英文版）B辑（生物医学与生物技术）

基　　金：supported by the National Natural Science Foundation of China(Nos.81930055 and 81772031).

摘　　要：The identification of tissue origin of body fluid can provide clues and evidence for criminal case investigations.To establish an efficient method for identifying body fluid in forensic cases,eight novel body fluid-specific DNA methylation markers were selected in this study,and a multiplex single base extension reaction(SNaPshot)system for these markers was constructed for the identification of five common body fluids(venous blood,saliva,menstrual blood,vaginal fluid,and semen).The results indicated that the in-house system showed good species specificity,sensitivity,and ability to identify mixed biological samples.At the same time,an artificial body fluid prediction model and two machine learning prediction models based on the support vector machine(SVM)and random forest(RF)algorithms were constructed using previous research data,and these models were validated using the detection data obtained in this study(n=95).The accuracy of the prediction model based on experience was 95.79%;the prediction accuracy of the SVM prediction model was 100.00%for four kinds of body fluids except saliva(96.84%);and the prediction accuracy of the RF prediction model was 100.00%for all five kinds of body fluids.In conclusion,the in-house SNaPshot system and RF prediction model could achieve accurate tissue origin identification of body fluids.

关 键 词：DNA methylation Body fluid Forensic identification Single base extension reaction(SNaPshot) Machine learning 

分 类 号：D919.4[医药卫生—法医学]