The use of DNA to determine the ancestry of an individual is becoming more and more important in the areas of forensics. Kidd et al. (Forensic Sci Int Genet 12:215-224, 2014) have been the first to identify and catalog haplotypes, termed as minihaplotypes (1-10-kilobase spans) and microhaplotypes (≤ 200 bp), with potential use in forensic analysis. In the present study, we selected 10 short ancestry informative microhaplotypes by calculating the informativeness (In) according to Rosenberg et al. (Am J Hum Genet 73(6):1402-1422, 2003). In total, 2504 individuals from 26 populations in 1000 Genomes Project database Phase 3 were enrolled. Among the studied microhaplotypes, eight of them are comprised of 3 SNPs while two microhaplotypes are made up of 4 SNPs. The size (molecular extent) range of 10 microhaplotypes is 5 to 48 bp with an average of 31.4 bp. The heterozygosity value ranges from 0.2235 to 0.8958 with an average of 0.6593. The average power of discrimination (PD) values is 0.7944 and ranges from 0.3786 to 0.9242. Analyses of this dataset provided clear differentiation of the populations from the Africa, East Asia, South Asia, and Europe biogeographic regions. However, individuals from American ancestry were not well separated. To conclude, our results revealed the significance of using microhaplotypes as an ancestry informative marker. The present panel could offer a valid complementary tool in forensic applications.

Identifying novel microhaplotypes for ancestry inference.

Population stratification analyses targeting genetically closely related East Asians have revealed that distinguishable differentiation exists between Han Chinese, Korean, and Japanese individuals, as well as between southern (S‐) and northern (N‐) Han Chinese. Previous studies offer a number of choices for ancestry informative single nucleotide polymorphisms (AISNPs) to discriminate East‐Asian populations. In this study, we collected and examined the efficiency of 1185 AISNPs using frequency and genotype data from various publicly available databases. With the aim to perform fine‐scale classification of S‐Han, N‐Han, Korean, and Japanese subjects, machine‐learning methods (Softmax and Random Forest) were used to screen a panel of highly informative AISNPs and to develop a superior classification model. Stepwise classification was implemented to increase and balance the discrimination in the process of AISNP selection, first discriminating Han, Korean, and Japanese individuals, and then characterizing stratification between S‐Han and N‐Han. The final 272‐AISNP panel is an alternative optimization of various previous works, which promises reliable and >90% accuracy in classification of the four East‐Asian groups. This AISNP panel and the machine‐learning model could be a useful and superior choice in medical genome‐wide association studies and in forensic investigations for unknown suspect identity.

A high‐performance SNP panel developed by machine‐learning approaches for characterizing genetic differences of Southern and Northern Han Chinese, Korean, and Japanese individuals

As evidenced by the large number of articles recently published in the literature, forensic scientists are making great efforts to infer externally visible features and biogeographical ancestry (BGA) from DNA analysis. Just as phenotypic, ancestry information obtained from DNA can provide investigative leads to identify the victims (missing/unidentified persons, crime/armed conflict/mass disaster victims) or trace their perpetrators when no matches were found with the reference profile or in the database. Recently, the advent of Massively Parallel Sequencing technologies associated with the possibility of harnessing high-throughput genetic data allowed us to investigate the associations between phenotypic and genomic variations in worldwide human populations and develop new BGA forensic tools capable of simultaneously analyzing up to millions of markers if for example the ancient DNA approach of hybridization capture was adopted to target SNPs of interest. In the present study, a selection of more than 3000 SNPs was performed to create a new BGA panel and the accuracy of the new panel to infer ancestry from unknown samples was evaluated by the PLS-DA method. Subsequently, the panel created was assessed using three variable selection techniques (Backward variable elimination, Genetic Algorithm and Regularized elimination procedure), and the best SNPs in terms of inferring bio-geographical ancestry at inter- and intra-continental level were selected to obtain panels to predict BGA with a reduced number of selected markers to be applied in routine forensic cases where PCR amplification is the best choice to target SNPs. 

Biogeographical ancestry, variable selection, and PLS-DA method: a new panel to assess ancestry in forensic samples via MPS technology.

Introduction to Forensic DNA Typing and Current Trends

Over the last decade, several panels of ancestry-informative markers have been proposed for the analysis of population genetic structure. The differentiation efficiency depends on the discriminatory ability of the included markers and the reference population coverage. We previously developed a small set of 27 autosomal single nucleotide polymorphisms (SNPs) for analyzing African, European, and East Asian ancestries. In the current study, we gathered a high-coverage reference database of 110 populations (10,350 individuals) from across the globe. The discrimination power of the panel was re-evaluated using four continental ancestry groups (as well as Indigenous Americans). We observed that all the 27 SNPs demonstrated stratified population specificity leading to a striking ancestral discrimination. Five markers (rs728404, rs7170869, rs2470102, rs1448485, and rs4789193) showed differences (δ > 0.3) in the frequency profiles between East Asian and Indigenous American populations. Ancestry components of all involved populations were accurately accessed compared with those from previous genome-wide analyses, thereafter achieved broadly population separation. Thus, our ancestral inference panel of a small number of highly informative SNPs in combination with a large-scale reference database provides a high-resolution in estimating ancestry compositions and distinguishing individual origins. We propose extensive usage in biomedical studies and forensics.

Global analysis of population stratification using a smart panel of 27 continental ancestry-informative SNPs

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Global analysis of population stratification using a smart panel of 27 continental ancestry-informative SNPs