Back to Search Start Over

Development of 18S rRNA gene arrays for forensic detection of diatoms

Authors :
Quyi Xu
Jian Zhao
Chao Liu
Lin Jiang
Jun Lin
Weiwen Cai
Tao Jiang
Cheng Xiao
Source :
Forensic Science International. 317:110482
Publication Year :
2020
Publisher :
Elsevier BV, 2020.

Abstract

Diatom test is the most commonly used method to diagnose drowning in forensic laboratories. However, microscopic examination and identification of diatom frustules is time-consuming and requires taxonomic expertise. At present, the identification of drowning is still a challenge in forensic casework. In this study, we developed a novel diatom microarray based on the detection of specific 18S rRNA gene fragments of diatom species. The array covers 169 diatom species which were documented as commonly found in a wide range of fresh waters in China. Diatom arrays were prepared from species specific oligonucleotide probes targeting to variable regions of the 18S rRNA gene. We also developed an auxiliary sample preparation method for isolation of diatom DNA from tissues, which enabled detection of diatom species in real forensic samples as well as environmental waters. We applied the diatom arrays to analyze six drowned cases and eight environmental samples. The diatom arrays showed much better sensitivity and more consistent results than those of the conventional SEM methods. We discovered major discrepancies between results generated by the diatom arrays and the routinely used SEM based diatom tests. We verified the results of our diatom arrays by species specific PCR and Sanger sequencing and found that the currently used SEM diatom test method has a serious deficiency in sensitivity due to high loss rate of frustules in the sample preparation procedure. We anticipate that the application of diatom arrays will transform current forensic practice of diagnosing drowning deaths.

Details

ISSN :
03790738
Volume :
317
Database :
OpenAIRE
Journal :
Forensic Science International
Accession number :
edsair.doi.dedup.....f9c9c07ff9695b37d88f462e9d73c6fe