Abstract：
In forensic investigations, identifying the type of body fluid allows for the interpretation of biological evidence at the activity level. Over the past two decades, significant research efforts have focused on developing molecular methods for this purpose. MicroRNAs (miRNAs) hold great promise due to their tissue-specific expression, abundance, lack of splice variants, and relative stability. Although initial findings are promising, achieving consistent results across studies is still challenging, underscoring the necessity for both original and replication studies. To address this, we selected 18 miRNA candidates and tested them on 6 body fluids commonly encountered in forensic cases: peripheral blood, menstrual blood, saliva, semen, vaginal secretion, and skin. Using reverse transcription quantitative PCR analysis, we confirmed eight miRNA candidates (miR-144-3p, miR-451a, miR-205-5p, miR-214-3p, miR-888-5p, miR-891a-5p, miR-193b-3p, miR-1260b) with high tissue specificity and four (miR-203a-3p, miR-141-3p, miR-200b-3p, miR-4286) with lesser discrimination ability but still contributing to body fluid differentiation. Through principal component analysis and hierarchical clustering, the set of 12 miRNAs successfully distinguished all body fluids, including the challenging discrimination of blood from menstrual blood and saliva from vaginal secretion. In conclusion, our results provide additional data supporting the use of a small set of miRNAs for predicting common body fluids in forensic contexts. Large population data need to be gathered to develop a body fluid prediction model and assess its accuracy.
摘要：
在法医调查中，识别体液的类型可以在活动水平上解释生物学证据。在过去的二十年里，重要的研究工作集中在开发用于此目的的分子方法上。microRNAs（miRNAs）由于其组织特异性表达而具有很大的前景，丰度,缺乏剪接变体，相对稳定。尽管最初的发现很有希望，在整个研究中实现一致的结果仍然具有挑战性，强调了原始研究和复制研究的必要性。为了解决这个问题，我们选择了18个miRNA候选物，并在法医病例中常见的6种体液中进行了测试：外周血，经血,唾液,精液,阴道分泌物，和皮肤。采用逆转录定量PCR分析,我们确认了八个候选miRNA（miR-144-3p，miR-451a,miR-205-5p,miR-214-3p,miR-888-5p,miR-891a-5p,miR-193b-3p,miR-1260b）具有高组织特异性和四个（miR-203a-3p，miR-141-3p,miR-200b-3p,miR-4286）具有较小的辨别能力，但仍有助于体液分化。通过主成分分析和层次聚类,一组12个miRNAs成功区分了所有体液，包括经血和阴道分泌物中唾液的区别。总之,我们的结果提供了额外的数据,支持在法医学背景下使用一小组miRNA预测常见体液.需要收集大量人口数据以开发体液预测模型并评估其准确性。
