Geolocation Inference of Forensic Individual Origin by Soil Metagenomic Analysis.
10.12116/j.issn.1004-5619.2019.590502
- Author:
Wen Li LIU
1
;
Feng CHENG
2
;
Jia Lin QIAN
1
;
Chen FANG
1
;
Xu LIU
1
;
Qing Wei FAN
2
;
Hui Juan WU
3
;
Jiang Wei YAN
2
Author Information
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.
- Publication Type:Journal Article
- Keywords:
forensic genetics;
soil;
metagenomic analysis;
individual origin;
geolocation inference
- MeSH:
Bacteria/genetics*;
High-Throughput Nucleotide Sequencing;
RNA, Ribosomal, 16S/genetics*;
Soil;
Soil Microbiology
- From:
Journal of Forensic Medicine
2021;37(3):366-371
- CountryChina
- Language:English
-
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.
