Evaluation of 12 Multi-InDel markers for forensic ancestry prediction in Asian populations

Investigating the effectiveness of forensic genetics and population genetic diversity using a multi-InDel system in Chinese Hezhou and Southern Shaanxi Han populations

INTRODUCTION

Multiple insertion-deletion (multi-InDel) has greater potential in forensic genetics than InDel, and its efficacy in kinship testing, individual identification, DNA mixture detection and ancestry inference remains to be explored.

METHODS

Consequently, we designed an efficient and robust system consisting of 41 multi-InDels to evaluate its efficacy in forensic applications in Chinese Hezhou Han (HZH) and Southern Shaanxi Han (SNH) populations and explore the genetic relationships between the SNH, HZH, and 26 reference populations.

RESULTS AND CONCLUSION

The obtained results showed that 38 out of the 41 multi-InDels had fairly high genetic variations. The the cumulative probability of discrimination and exclusion values of the multi-InDels (except MI38) in HZH and SNH populations both exceeded 1-e-25 and 1-e-6, correspondingly. The genetic compositions of HZH and SNH individuals were similar to that of East Asians and the Naive Bayes model could well distinguish East Asians, Africans and Americans. These results indicated that the multi-InDel systerm can serve as an effective tool to provide important evidence for the development of multi-InDels in forensic practice and better analyse the genetic background of the Han Chinese populations.

Systematic selection of ancestry informative SNPs for differentiating Han, Japanese, Dai, and Kinh populations

Biogeographical origin inferences of different populations can provide valuable clues in the forensic investigation by narrowing down the detection scope. However, much research mainly focuses on forensic ancestral origin analyses of major continental populations, which may provide limited information in forensic practice. To improve the ancestral resolution of East Asian populations, we systematically selected ancestry informative single-nucleotide polymorphisms (AISNPs) for differentiating Han, Dai, Japanese, and Kinh populations. In addition, we evaluated the performance of the selected AISNPs to differentiate these populations via multiple methods. Totally 116 AISNPs were selected from the genome-wide data to infer the population origins of these four populations. Results of principle component analysis and population genetic structure of these populations indicated that the selected 116 AISNPs could achieve ancestral resolution of most individuals. Furthermore, the machine learning model built by 116 AISNPs unveiled that most individuals from these four populations could be assigned to correct population origins. To sum up, the selected 116 SNPs could be available for ancestral origin predictions of Han, Dai, Japanese, and Kinh populations, which could provide valuable information for forensic research and genome-wide association study in East Asian populations to some extent.

Genome-wide association studies combined with k-fold cross-validation identify rs17822931 as an ancestry-informative marker in Han Chinese population

DNA-based ancestry inference has long been a research hot spot in forensic science. The differentiation of Han Chinese population, such as the northern-to-southern substructure, would benefit forensic practice. In the present study, we enrolled participants from northern and southern China, each participant was genotyped at ∼400 K single-nucleotide polymorphisms (SNPs) and data of CHB and CHS from 1000 Genomes Project were used to perform genome-wide association analyses. Meanwhile, a new method combining genome-wide association study (GWAS) analyses with k-fold cross-validation in a small sample size was introduced. As a result, one SNP rs17822931 emerged with a p-value of 7.51E - 6. We also simulated a huge dataset to verify whether k-fold cross-validation could reduce the false-negative rate of GWAS. The identified ABCC11 rs17822931 has been reported to have allele frequencies varied with the geographical gradient distribution in humans. We also found a great difference in the allele frequency distributions of rs17822931 among five different cohorts of the Chinese population. In conclusion, our study demonstrated that even small-scale GWAS can also have potential to identify effective loci with implemented k-fold cross-validation method and shed light on the potential maker of rs17822931 in differentiating the north-to-south substructure of the Han Chinese population.

Development of Omni InDel and supporting database for maize

Insertions-deletions (InDels) are the second most abundant molecular marker in the genome and have been widely used in molecular biology research along with simple sequence repeats (SSR) and single-nucleotide polymorphisms (SNP). However, InDel variant mining and marker development usually focuses on a single type of dimorphic InDel, which does not reflect the overall InDel diversity across the genome. Here, we developed Omni InDels for maize, soybean, and rice based on sequencing data and genome assembly that included InDel variants with base lengths from 1 bp to several Mb, and we conducted a detailed classification of Omni InDels. Moreover, we screened a set of InDels that are easily detected and typed (Perfect InDels) from the Omni InDels, verified the site authenticity using 3,587 germplasm resources from 11 groups, and analyzed the germplasm resources. Furthermore, we developed a Multi-InDel set based on the Omni InDels; each Multi-InDel contains multiple InDels, which greatly increases site polymorphism, they can be detected in multiple platforms such as fluorescent capillary electrophoresis and sequencing. Finally, we developed an online database website to make Omni InDels easy to use and share and developed a visual browsing function called "Variant viewer" for all Omni InDel sites to better display the variant distribution.

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.

Forensic efficiencies of individual identification, kinship testing and ancestral inference in three Yunnan groups based on a self-developed multiple DIP panel

Deletion/insertion polymorphism (DIP), as a short insertion/deletion sequence polymorphic genetic marker, has attracted the attention of forensic genetic scientist due to its lack of stutter, short amplicon and abundant ancestral information. In this study, based on a self-developed 43 autosomal deletion/insertion polymorphism (A-DIP) loci panel which could meet the forensic application purposes of individual identification, kinship testing and ancestral inference to some extent, we evaluated the forensic efficiencies of the above three forensic objectives in Chinese Yi, Hani and Miao groups of Yunnan province. The cumulative match probability (CPM) and combined probability of exclusion (CPE) of these three groups were 1.11433E-18, 8.24299E-19, 4.21721E-18; 0.999610217, 0.999629285 and 0.999582084, respectively. Average 96.65% full sibling pairs could be identified from unrelated individual pairs (as likelihood ratios > 1) using this DIP panel, whereas the average false positive rate was 3.69% in three target Yunnan groups. With the biogeographical ancestor prediction models constructed by extreme gradient boosting (XGBoost) and support vector machine (SVM) algorithms, 0.8239 (95% CI 0.7984, 0.8474) of the unrelated individuals could be correctly divided according to the continental origins based on the 43 A-DIPs which were large frequency distribution differentiations among different continental populations. The present results of principal component analysis (PCA), multidimensional scaling (MDS), neighbor joining (NJ) and maximum likelihood (ML) phylogenetic trees and STRUCTURE analyses indicated that these three Yunnan groups had relatively close genetic distances with East Asian populations.

Development and forensic efficiency evaluations of a novel multiplex amplification panel of 17 Multi-InDel loci on the X chromosome

Multi-InDel, as the novel genetic markers, showed great potential in forensic research. Whereas, most scholars mainly focused on autosomal Multi-InDels, which might provide limited genetic information in some complex kinship cases. In this study, we selected 17 Multi-InDels on the X chromosome and developed a multiplex amplification panel based on the next-generation sequencing (NGS) technology. Genetic distributions of these 17 loci in Beijing Han, Chinese Southern Han, and the studied Guizhou Han populations revealed that most loci showed relatively high forensic application values in these Han populations. In addition, more allelic variations of some loci were observed in the Guizhou Han than those in Beijing Han and Southern Han populations. Pairwise FST values, multi-dimensional analysis, and phylogenetic tree of different continental populations showed that selected 17 loci generally could differentiate African, European, East Asian, and South Asian populations. To sum up, the developed panel in this study is not only viewed as the high-efficient supplementary tool for forensic individual identification and paternity analysis, but it is also beneficial for inferring biogeographical origins of different continental populations.

Multivariate statistical approach and machine learning for the evaluation of biogeographical ancestry inference in the forensic field

The biogeographical ancestry (BGA) of a trace or a person/skeleton refers to the component of ethnicity, constituted of biological and cultural elements, that is biologically determined. Nowadays, many individuals are interested in exploring their genealogy, and the capability to distinguish biogeographic information about population groups and subgroups via DNA analysis plays an essential role in several fields such as in forensics. In fact, for investigative and intelligence purposes, it is beneficial to inference the biogeographical origins of perpetrators of crimes or victims of unsolved cold cases when no reference profile from perpetrators or database hits for comparative purposes are available. Current approaches for biogeographical ancestry estimation using SNPs data are usually based on PCA and Structure software. The present study provides an alternative method that involves multivariate data analysis and machine learning strategies to evaluate BGA discriminating power of unknown samples using different commercial panels. Starting from 1000 Genomes project, Simons Genome Diversity Project and Human Genome Diversity Project datasets involving African, American, Asian, European and Oceania individuals, and moving towards further and more geographically restricted populations, powerful multivariate techniques such as Partial Least Squares-Discriminant Analysis (PLS-DA) and machine learning techniques such as XGBoost were employed, and their discriminating power was compared. PLS-DA method provided more robust classifications than XGBoost method, showing that the adopted approach might be an interesting tool for forensic experts to infer BGA information from the DNA profile of unknown individuals, but also highlighting that the commercial forensic panels could be inadequate to discriminate populations at intra-continental level.

Systematic Evaluation of a Novel 6-dye Direct and Multiplex PCR-CE-Based InDel Typing System for Forensic Purposes

Insertion/deletion (InDel) polymorphisms, combined desirable characteristics of both short tandem repeats (STRs) and single nucleotide polymorphisms (SNPs), are considerable potential in the fields of forensic practices and population genetics. However, most commercial InDel kits designed based on non-Asians limited extensive forensic applications in East Asian (EAS) populations. Recently, a novel 6-dye direct and multiplex PCR-CE-based typing system was designed on the basis of genome-wide EAS population data, which could amplify 60 molecular genetic markers, consisting of 57 autosomal InDels (A-InDels), 2 Y-chromosomal InDels (Y-InDels), and Amelogenin in a single PCR reaction and detect by capillary electrophoresis, simultaneously. In the present study, the DNA profiles of 279 unrelated individuals from the Hainan Li group were generated by the novel typing system. In addition, we collected two A-InDel sets to evaluate the forensic performances of the novel system in the 1,000 Genomes Project (1KG) populations and Hainan Li group. For the Universal A-InDel set (UAIS, containing 44 A-InDels) the cumulative power of discrimination (CPD) ranged from 1-1.03 × 10-14 to 1-1.27 × 10-18, and the cumulative power of exclusion (CPE) varied from 0.993634 to 0.999908 in the 1KG populations. For the East Asia-based A-InDel set (EAIS, containing 57 A-InDels) the CPD spanned from 1-1.32 × 10-23 to 1-9.42 × 10-24, and the CPE ranged from 0.999965 to 0.999997. In the Hainan Li group, the average heterozygote (He) was 0.4666 (0.2366-0.5448), and the polymorphism information content (PIC) spanned from 0.2116 to 0.3750 (mean PIC: 0.3563 ± 0.0291). In total, the CPD and CPE of 57 A-InDels were 1-1.32 × 10-23 and 0.999965, respectively. Consequently, the novel 6-dye direct and multiplex PCR-CE-based typing system could be considered as the reliable and robust tool for human identification and intercontinental population differentiation, and supplied additional information for kinship analysis in the 1KG populations and Hainan Li group.

A Novel Panel of 43 Insertion/Deletion Loci for Human Identifications of Forensic Degraded DNA Samples: Development and Validation

Insertion/deletion polymorphism is a promising genetic marker in the forensic genetic fields, especially in the forensic application of degraded sample at crime scene. In this research, a novel five-dye multiplex amplification panel containing 43 highly polymorphic Insertion/deletion (InDel) loci and one Amelogenin gene locus is designed and constructed in-house for the individual identification in East Asian populations. The amplicon sizes of 43 InDel loci are less than 200 bp, which help to ensure that full allele profiles can be obtained from degraded DNA sample. A series of optimizations and developmental validations including optimization of PCR conditions, detection efficiency of the degraded and casework samples, sensitivity, reproducibility, precision, tolerance for inhibitors, species specificity and DNA mixtures are performed according to the Scientific Working Group on DNA Analysis Methods (SWGDAM) guideline. The results of the internal validation demonstrated that this novel InDel panel was a reliable, sensitive and accurate system with good tolerances to different inhibitors, and performed the considerable detection efficiency for the degraded or mixed samples, which could be used in the forensic applications.

Massively parallel sequencing of 165 ancestry-informative SNPs and forensic biogeographical ancestry inference in three southern Chinese Sinitic/Tai-Kadai populations

Ancestry informative markers (AIMs), which are distributed throughout the human genome, harbor significant allele frequency differences among diverse ethnic groups. The use of sets of AIMs to reconstruct population history and genetic relationships is attracting interest in the forensic community, because biogeographic ancestry information for a casework sample can potentially be predicted and used to guide the investigative process. However, subpopulation ancestry inference within East Asia remains in its infancy due to a lack of population reference data collection and incomplete validation work on newly developed or commercial AIM sets. In the present study, 316 Chinese persons, including 85 Sinitic-speaking Haikou Han, 120 Qiongzhong Hlai and 111 Daozhen Gelao individuals belonging to Tai-Kadai-speaking populations, were analyzed using the Precision ID Ancestry Panel (165 AISNPs). Combined with our previous 165-AISNP data (375 individuals from 6 populations), the 1000 Genomes Project and forensic literature, comprehensive population genetic comparisons and ancestry inference were further performed via ADMIXTURE, TreeMix, PCA, f-statistics and N-J tree. Although several nonpolymorphic loci were identified in the three southern Chinese populations, the forensic parameters of this ancestry inference panel were better than those for the 23 STR-based Huaxia Platinum System, which is suitable for use as a robust tool in forensic individual identification and parentage testing. The results based on the ancestry assignment and admixture proportion evaluation revealed that this panel could be used successfully to assign individuals at a continental scale but also possessed obvious limitations in discriminatory power in intercontinental individuals, especially for European-Asian admixed Uyghurs or in populations lacking reference databases. Population genetic analyses further revealed five continental population clusters and three East Asian-focused population subgroups, which is consistent with linguistic affiliations. Ancestry composition and multiple phylogenetic analysis further demonstrated that the geographically isolated Qiongzhong Hlai harbored a close phylogenetic relationship with Austronesian speakers and possessed a homogenous Tai-Kadai-dominant ancestry, which could be used as the ancestral source proxy in population history reconstruction of Tai-Kadai-speaking populations and as one of the representatives for forensic database establishment. In summary, more population-specific AIM sets focused on East Asian subpopulations, comprehensive algorithms and high-coverage population reference data should be developed and validated in the next step.

An 18 Multi-InDels panel for analysis of highly degraded forensic biological samples

DNA genotyping from trace and highly degraded biological samples is one of the most significant challenges of forensic DNA identification. There is a lack of simple and effective methods for genotyping highly degraded samples. In this study, a multiple loci insertion/deletion polymorphisms (Multi-InDels) panel was designed for detecting 18 autosomal Multi-InDels through capillary electrophoresis (CE) with amplicon sizes no longer than 125 bp. Studies of sensitivity, degradation, and species specificity were performed and a population study was carried out using 192 samples from Han populations in Hunan province in the south of China. The combined random match probability (CMP) of these 18 Multi-InDels was 3.23 × 10^-12 and the cumulative probability of exclusion (CPE) was 0.9989, suggesting this panel could be used independently for human identification and could provide efficient supporting information for parentage testing. Complete profiles were obtained from as low as 62.5 pg of total input DNA after increasing the number of PCR cycles. Moreover, all alleles were detected from artificially highly degraded DNA after 80 min of boiling water bath treatment. This 18 Multi-InDels panel is simple, fast, and effective for the forensic analysis of highly degraded DNA.