Next generation sequencing of a set of ancestry-informative SNPs: ancestry assignment of three continental populations and estimating ancestry composition for Mongolians

Systematically exploring the performance of a self-developed Multi-InDel system in forensic identification, ancestry inference and genetic structure analysis of Chinese Manchu and Mongolian groups

The insertion/deletion (InDel) polymorphism has promising applications in forensic DNA analysis. However, the insufficient forensic efficiencies of the present InDel-based systems restrict their applications in parentage testing, due to the lower genetic polymorphism of the biallelic InDel locus and the limited number of InDel loci in a multiplex amplification system. Here, we introduced an in-house developed system which contained 41 polymorphic Multi-InDel markers (equivalent to 82 InDels in total), to serve as an efficient and reliable tool for different forensic applications in the Manchu and Mongolian groups. We demonstrated that the new system exhibited potential efficiencies for personal identification, parentage testing, two-person DNA mixture interpretation and ancestry inference of intercontinental populations. Meanwhile, we explored the genetic backgrounds of the Manchu and Mongolian groups by conducting a series of population genetic analyses. We showed that the Manchu and Mongolian groups shared closer genetic relationships with East Asian populations, especially Han Chinese populations in northern China. Moreover, more similar genetic compositions were detected between the Manchu group and the northern Han populations in this study, suggesting that the Manchu group had higher genetic affinities with northern Han populations than the Mongolian group. Overall. this study provided the necessary evidence that these Multi-InDel genetic markers could play an important role in forensic applications.

Advancement in Human Face Prediction Using DNA

The rapid improvements in identifying the genetic factors contributing to facial morphology have enabled the early identification of craniofacial syndromes. Similarly, this technology can be vital in forensic cases involving human identification from biological traces or human remains, especially when reference samples are not available in the deoxyribose nucleic acid (DNA) database. This review summarizes the currently used methods for predicting human phenotypes such as age, ancestry, pigmentation, and facial features based on genetic variations. To identify the facial features affected by DNA, various two-dimensional (2D)- and three-dimensional (3D)-scanning techniques and analysis tools are reviewed. A comparison between the scanning technologies is also presented in this review. Face-landmarking techniques and face-phenotyping algorithms are discussed in chronological order. Then, the latest approaches in genetic to 3D face shape analysis are emphasized. A systematic review of the current markers that passed the threshold of a genome-wide association (GWAS) of single nucleotide polymorphism (SNP)-face traits from the GWAS Catalog is also provided using the preferred reporting items for systematic reviews and meta-analyses (PRISMA), approach. Finally, the current challenges in forensic DNA phenotyping are analyzed and discussed.

Open-Access Worldwide Population STR Database Constructed Using High-Coverage Massively Parallel Sequencing Data Obtained from the 1000 Genomes Project

Achieving accurate STR genotyping by using next-generation sequencing data has been challenging. To provide the forensic genetics community with a reliable open-access STR database, we conducted a comprehensive genotyping analysis of a set of STRs of broad forensic interest obtained from 1000 Genome populations. We analyzed 22 STR markers using files of the high-coverage dataset of Phase 3 of the 1000 Genomes Project. We used HipSTR to call genotypes from 2504 samples obtained from 26 populations. We were not able to detect the D21S11 marker. The Hardy-Weinberg equilibrium analysis coupled with a comprehensive analysis of allele frequencies revealed that HipSTR was not able to identify longer alleles, which resulted in heterozygote deficiency. Nevertheless, AMOVA, a clustering analysis that uses STRUCTURE, and a Principal Coordinates Analysis showed a clear-cut separation between the four major ancestries sampled by the 1000 Genomes Consortium. Except for larger Penta D and Penta E alleles, and two very small Penta D alleles (2.2 and 3.2) usually observed in African populations, our analyses revealed that allele frequencies and genotypes offered as an open-access database are consistent and reliable.

Determining the Area of Ancestral Origin for Individuals From North Eurasia Based on 5,229 SNP Markers

Currently available genetic tools effectively distinguish between different continental origins. However, North Eurasia, which constitutes one-third of the world’s largest continent, remains severely underrepresented. The dataset used in this study represents 266 populations from 12 North Eurasian countries, including most of the ethnic diversity across Russia’s vast territory. A total of 1,883 samples were genotyped using the Illumina Infinium Omni5Exome-4 v1.3 BeadChip. Three principal components were computed for the entire dataset using three iterations for outlier removal. It allowed the merging of 266 populations into larger groups while maintaining intragroup homogeneity, so 29 ethnic geographic groups were formed that were genetically distinguishable enough to trace individual ancestry. Several feature selection methods, including the random forest algorithm, were tested to estimate the number of genetic markers needed to differentiate between the groups; 5,229 ancestry-informative SNPs were selected. We tested various classifiers supporting multiple classes and output values for each class that could be interpreted as probabilities. The logistic regression was chosen as the best mathematical model for predicting ancestral populations. The machine learning algorithm for inferring an ancestral ethnic geographic group was implemented in the original software “Homeland” fitted with the interface module, the prediction module, and the cartographic module. Examples of geographic maps showing the likelihood of geographic ancestry for individuals from different regions of North Eurasia are provided. Validating methods show that the highest number of ethnic geographic group predictions with almost absolute accuracy and sensitivity was observed for South and Central Siberia, Far East, and Kamchatka. The total accuracy of prediction of one of 29 ethnic geographic groups reached 71%. The proposed method can be employed to predict ancestries from the populations of Russia and its neighbor states. It can be used for the needs of forensic science and genetic genealogy.

Forensic Feature Exploration and Comprehensive Genetic Insights Into Yugu Ethnic Minority and Northern Han Population via a Novel NGS-Based Marker Set

The MPS technology has expanded the potential applications of DNA markers and increased the discrimination power of the targeted loci by taking variations in their flanking regions into consideration. Here, a collection of nuclear and extranuclear DNA markers (totally six kinds of nuclear genetic markers and mtDNA hypervariable region variations) were comprehensively and systematically assessed for polymorphism detections, further employed to dissect the population backgrounds in the Yugu ethnic group from Gansu province (Yugu) and Han population from the Inner Mongolia Autonomous Region (NMH) of China. The elevated efficiencies of the marker set in separating full sibling and challenging half sibling determination cases in parentage tests (iiSNPs), as well as predicting ancestry origins of unknown individuals from at least four continental populations (aiSNPs) and providing informative characteristic-related clues for Chinese populations (piSNPs) are highlighted in the present study. To sum up, different sets of DNA markers revealed sufficient effciencies to serve as promising tools in forensic applications. Genetic insights from the perspectives of autosomal DNA, Y chromosomal DNA, and mtDNA variations yielded that the Yugu ethnic group was genetically close related to the Han populations of the northern region. But we admit that more reference populations (like Mongolian, Tibetan, Hui, and Tu) should be incorporated to gain a refined genetic background landscape of the Yugu group in future studies.