法医学杂志

法医学杂志 ›› 2021, Vol. 37 ›› Issue (3): 366-371，377.DOI: 10.12116/j.issn.1004-5619.2019.590502

• 论著 • 上一篇    下一篇

基于土壤宏基因组分析的法医学个体来源地理位置推断

刘文丽1， 程凤2， 钱嘉林1， 方晨1，3， 刘旭1，3， 范庆炜2， 武会娟3，4， 严江伟2   

  1. 1. 北京市理化分析测试中心，北京 100089； 2. 山西医科大学法医学院，山西 太原 030001； 3. 北京市基因测序与功能分析工程技术研究中心，北京 100094； 4. 北京实验动物研究中心，北京 100871
  • 发布日期:2021-06-25 出版日期:2021-06-28
  • 通讯作者: 严江伟，男，博士，教授，主任法医师，主要从事法医遗传学研究；E-mail：yanjw@sxmu.edu.cn 武会娟，女，博士，研究员，主要从事分子生物学研究；E-mail：sunnywhj@126.com
  • 作者简介:刘文丽（1992—），女，硕士，主要从事法医宏基因组研究；E-mail：136509779@qq.com
  • 基金资助:
    国家重点研发计划资助项目（2017YFC0803504）；北京市财政资助项目（PXM2019_178305_000018）

Geolocation Inference of Forensic Individual Origin by Soil Metagenomic Analysis

LIU Wen-li1, CHENG Feng2, QIAN Jia-lin1, FANG Chen1,3, LIU Xu1,3, FAN Qing-wei2, WU Hui-juan3,4, YAN Jiang-wei2   

  1. 1. Beijing Center for Physical and Chemical Analysis, Beijing 100089, China; 2. School of Forensic Medicine, Shanxi Medical University, Taiyuan 030001, China; 3. Beijing Engineering Technique Research Center for Gene Sequencing & Function Analysis, Beijing 100094, China; 4. Beijing Laboratory Animal Research Center, Beijing 100871, China
  • Online:2021-06-25 Published:2021-06-28

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摘要： 目的 初步探讨基于土壤宏基因组分析方法应用于法医学个体来源地理位置推断的可行性。 方法 收集黑龙江省、青海省、西藏自治区土壤样本共33例，提取样本中全部细菌总DNA，采用通用引物扩增细菌16S rDNA V3-V4高变区并在MiSeq测序仪上完成高通量测序，对测序数据进行物种组成和样本比较等生物信息学分析，基于分类操作单元（operational taxonomic unit，OTU）结果计算丰富度指数及多样性指数。 结果 测序共得到2 720 149条序列，聚类得到114 848个OTU。黑龙江省、青海省、西藏自治区土壤微生物Chao1指数分别为797.45、745.11、535.98，Shannon指数分别为6.46、6.36、6.25，土壤中细菌物种数从多到少及群落多样性从高到低均依次为黑龙江省、青海省、西藏自治区。获得了3省土壤细菌在各分类水平下的结构组成，黑龙江省优势菌属为Chthoniobacteraceae科DA101属和Thermogemmatisporaceae科某一未注释的属；青海省优势菌属为Cytophagaceae科某一未注释的属和Nocardioidaceae科某一未注释的属；西藏自治区优势菌属为Comamonadaceae科某一未注释的属和Verrucomicrobiaceae科Luteolibacter属。主坐标分析结果显示，按照加权UniFrac度量分析，3个主成分代表总变量的56.36%，按照未加权UniFrac度量分析，3个主成分代表总变量的34.81%，同一省样本可分别聚类到一起，不同省来源的土壤微生物种类及含量则有明显差别。 结论 基于土壤宏基因组分析方法可以有效区分不同地区土壤样本，未来在法医学个体来源地理位置推断方面具有潜在的应用价值。

关键词: 法医遗传学, 土壤, 宏基因组分析, 个体来源, 地理位置推断

Abstract: Objective To preliminarily discuss the feasibility of geolocation inference of forensic individual origin by soil metagenomic analysis. Methods The 33 soil samples from Heilongjiang, Qinghai and Tibet were collected, total bacterial DNA in the samples were extracted, and universal primers were used to amplify the V3 and V4 hypervariable region of bacterial 16S rDNA. The region was sequenced by high-throughput sequencing （HTS） with the MiSeq sequencer. Bioinformatics analysis such as species composition and sample comparison was performed on sequencing data. The richness index and diversity index were calculated based on operational taxonomic unit （OTU） results. Results A total of 2 720 149 sequences were generated by sequencing. Those sequences were clustered into 114 848 OTUs. The Chao1 indexes of soil microorganisms in Heilongjiang, Qinghai, and Tibet were 797.45, 745.11 and 535.98, respectively, and Shannon indexes were 6.46, 6.36 and 6.25, respectively. The number of bacterial species and the community diversity in the soil from high to low were Heilongjiang > Qinghai > Tibet. The composition of soil bacteria in three provinces at various classification levels were obtained, the dominant genuses in Heilongjiang were Chthoniobacteraceae DA101 and an unannotated genus of Thermogemmatisporaceae; the dominant genuses in Qinghai were an unannotated genus of Cytophagaceae and an unannotated genus of Nocardioidaceae; the dominant genuses in Tibet were an unannotated genus of Comamonadaceae and Verrucomicrobiaceae Luteolibacter. The results of principal co-ordinates analysis demonstrated that, according to the weighted UniFrac analysis, the three principle components represented 56.36% of the total variable, and according to the unweighted UniFrac analysis, the three principle components represented 34.81% of the total variable. The samples from the same province could be clustered together, and the species and content of soil microorganisms from different provinces were significantly different. Conclusion Based on the metagenomic analysis method, soil samples from different regions can be effectively distinguished, which has potential application value in geolocation inference of forensic individual origin in the future.

Key words: forensic genetics, soil, metagenomic analysis, individual origin, geolocation inference

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