法医学二代测序标准化进展与展望

二代测序技术可检测多种法医遗传标记获取海量序列信息,满足法医学实践中精准个体识别、复杂亲缘关系鉴定、特征刻画等应用需求。国内外已开展大量二代测序法医学应用科研工作,但由于缺乏行业标准,二代测序在我国公安实战中并未得到有效应用。目前,法医学二代测序的标准制定面临检测靶标特殊、测序技术流程和结果分析不统一等挑战。本文从核酸标准参考物、测序技术要求、序列多态STR等位基因命名规则等方面,梳理国外法医学二代测序标准化工作进展,并总结国内二代测序检测行业标准现状,希冀为我国法医学二代测序的标准建设提供思路和参考。     

Calculation and implementation of sample-wide stochastic thresholds for forensic genetic analysis of STRs and SNPs for massively parallel sequencing platforms

Capillary electrophoresis (CE) analysis of short tandem repeats (STRs) and single nucleotide polymorphisms (SNPs) use a stochastic threshold to consider the possibility of missing alleles (dropouts) or detecting additional alleles (drop-ins). In CE, this threshold may be approximately 200 RFU, and peak heights are assessed relative to this threshold. In next generation sequencing (NGS), also known as massively parallel sequencing (MPS), STRs are identified by their sequence, and specific alleles are identified by their repeat number and intra-allelic variation. Abundance is approximated by the number of sequence reads for each allele. The total number of reads generated for each marker in a sample depends on factors such as the numbers of samples pooled for sequencing, the number of markers in the assay, the integrity and quantity of the input DNA sample, and the inter-locus balance of the assay. For multiplexes that contain both autosomal and sex-linked markers, the biological sex of the sample also influences total reads per locus. To normalize these variables and better establish a robust stochastic threshold, a sample-wide metric is proposed for estimating the possibility of dropouts or drop-ins based on the variance of the inter-locus balance of the markers across a sample. The intuition is that samples with variable allele balance globally are more likely to have noisier data and therefore require more stringent read count thresholds. This method is robust to sequencing multiplexity, biological sex and manufacturing lot variation.     

Time Radically Alters Ex Situ Evidentiary Soil 16S Bacterial Profiles Produced Via Next‐Generation Sequencing,,

Previous research has revealed the potential of soil bacterial profiling for forensic purposes; however, investigators have not thoroughly examined fluctuations in microbial profiles from soil aged on evidence. In this research, soils collected from multiple habitats were placed on evidence items and sampled over time, and then bacterial profiles were generated via next‐generation sequencing of the 16S rRNA locus. Bacterial abundance charts and nonmetric multidimensional scaling plots provided visual representation of bacterial profiles temporally, while supervised classification was used to statistically associate evidence to a source. The ex situ evidence soils displayed specific, consistent taxonomic changes as they aged, resulting in their drift in multidimensional space, but never toward a different habitat. Ninety‐five percent of the 364 evidentiary profiles statistically classified to the correct habitat, with misclassification generally stemming from evidence type and increased age. Ultimately, understanding bacterial changes that occur temporally in ex situ soils should enhance their use in forensic investigations.     

Assessing three soil removal methods for environmental DNA analysis of mock forensic geology evidence

Soil is useful in criminal investigations as it is highly variable and readily transferred. Forensic geologists use several different techniques to removal soil from evidence prior to the analysis of inorganic components. There has been recent interest from the forensic science community to analyze environmental deoxyribonucleic acid (eDNA) associated with soil to augment existing forensic analyses. Notably however, limited research has been conducted to compare commonly used soil removal methods for downstream eDNA analysis. In this study, three soil removal methods were assessed: picking/scraping, sonication, and swabbing. Three mock evidence types (t-shirts, boot soles, and trowels) were sampled in triplicate with each removal method (n = 27). Soil samples underwent DNA isolation, quantification, and amplification of four genomic barcode regions: 16S for bacteria, ITS1 for fungi, ITS2 for plants, and COI for arthropods. Amplicons were prepared into libraries for DNA sequencing on an Illumina^® MiniSeq. DNA concentrations were highest in picked/scraped samples and were statistically significant compared with swabbed and sonicated samples. Amplicon sequence variants (ASVs) were identified, and removal methods had no impact on the recovery of the total number of target ASVs. Additionally, when assessing each sample in multidimensional space, picked/scraped samples tended to cluster separately from swabbed and sonicated samples. The soil core used a reference in this study also clustered with the picked/scraped samples, indicating that these samples may be more reflective of the communities collected from soil cores. Based on these data, we identified that picking/scraping is an acceptable soil removal method for eDNA analysis.     

Introduction of the python script MHinNGS for analysis of microhaplotypes

MHinNGS is a Python application developed for analysis of microhaplotypes (MHs) in single-end sequencing data. MHinNGS analyses reads in standard formats and store each sequence into bins, one bin for each MH as defined by the two flanking sequences. MHinNGS requires a reference genome and a configuration file with information about each locus. Four mandatory and 15 optional criteria defined in the configuration file allow detailed locus-specific analyses of the MH loci. The program 1) removes noise, 2) identify and name alleles, 3) test the genotypes, and 4) test unique sequences not identified as noise or alleles. MHinNGS produces a result file, where every unique sequence that passed the noise filter is presented with MH allele, read depth, warning flags based on the genotyping criteria, sequence, heterozygote balance, and MH name. Furthermore, variation in other parts of the fragment that is not defined as SNPs in the MH, linked variants, or rare SNPs are listed in a separate column of the result file.     

Discrimination between sediment and soil samples for forensic purposes using elemental data: an investigation of particle size effects

This paper reports the results of an investigation to quantify variations in elemental concentrations amongst different particle size fractions obtained from a suite of sediment samples collected from the River Avon, UK. Concentrations of 49 elements determined by inductively coupled plasma spectrometry (ICP-AES and ICP-MS) were compared using conventional and multivariate statistical methods in order to assess compositional differences between different size fractions and between different samples. The results showed significant differences between different size fractions and the bulk sediments, but indicated that all of the size fractions considered (<150, 63-150, 20-63 and <20microm) provided an adequate basis on which to identify associations and differences between samples. It was concluded that, while in certain specific circumstances it may be most appropriate to make forensic comparisons based on a very narrowly defined particle size range, for the majority of purposes the <150microm fraction provides the best compromise between sample size requirements and data resolution.     

Forensic data management and database systems in forensic investigations for cases of missing and unidentified persons in Brazil

Forensic investigations, especially those related to missing persons and unidentified remains, produce different types of data that must be managed and understood. The data collected and produced are extensive and originate from various sources: the police, non-governmental organizations (NGOs), medical examiner offices, specialised forensic teams, family members, and others. Some examples of information include, but are not limited to, the investigative background information, excavation data of burial sites, antemortem data on missing persons, and postmortem data on the remains of unidentified individuals. These complex data must be stored in a secured place, analysed, compared, shared, and then reported to the investigative actors and the public, especially the families of missing persons, who should be kept informed of the investigation. Therefore, a data management system with the capability of performing the tasks relevant to the goals of the investigation and the identification of an individual, while respecting the deceased and their families, is critical for standardising investigations. Data management is crucial to assure the quality of investigative processes, and it must be recognised as a holistic integrated system. The aim of this article is to discuss some of the most important components of an effective forensic data management system. The discussion is enriched by examples, challenges, and lessons learned from the erratic development and launching of databases for missing and unidentified persons in Brazil. The main objective of this article is to bring attention to the urgent need for an effective and integrated system in Brazil.     

Inference structures for crime analysis and intelligence: the example of burglary using forensic science data

There has been much work dedicated to crime analysis and intelligence in recent times. Independently, physical evidence has shown great potential for linking crimes and bringing solid informative data through the increased use of multiple databases. However, their informative potential is still often underestimated and has been poorly integrated into police information systems. We propose a framework that fully introduces this data into an intelligence based system. This framework is built on the study of inference structures extracted from investigators’ every day implicit reasoning processes. Five specific inferences are studied with the particular problem of serial burglary investigation across independent police and legal structures. On the basis of such an analytical approach, a computer prototype has been designed; it has shown great promise and has resulted in several operational successes.     

Routine forensic use of the mitochondrial 12S ribosomal RNA gene for species identification

Since July 2004, Mitotyping Technologies has been amplifying and sequencing a approximately 150 base pair fragment of mitochondrial DNA (mtDNA) that codes for 12S ribosomal RNA, to identify the species origin of nonhuman casework samples. The approximately 100 base pair sequence product is searched at http://www.ncbi.nlm.nih.gov/BLAST and the species match is reported. The use of this assay has halved the number of samples for which no mtDNA results are obtained and is especially useful on hairs and degraded samples. The availability of species determination may aid forensic investigators in opening or closing off lines of inquiry where a highly probative but challenging sample has been collected.