BGISEQ-500RS sequencing of a 448-plex SNP panel for forensic individual identification and kinship analysis

An approach to unified formulae for likelihood ratio calculation in pairwise kinship analysis

Introduction: The likelihood ratio (LR) can be an efficient means of distinguishing various relationships in forensic fields. However, traditional list-based methods for derivation and presentation of LRs in distant or complex relationships hinder code editing and software programming. This paper proposes an approach for a unified formula for LRs, in which differences in participants' genotype combinations can be ignored for specific identification. This formula could reduce the difficulty of by-hand coding, as well as running time of large-sample-size simulation. Methods: The approach is first applied to a problem of kinship identification in which at least one of the participants is alleged to be inbred. This can be divided into two parts: i) the probability of different identical by descent (IBD) states according to the alleged kinship; and ii) the ratio of the probability that specific genotype combination can be detected assuming the alleged kinship exists between the two participants to the similar probability assuming that they are unrelated, for each state. For the probability, there are usually recognized results for common identification purposes. For the ratio, subscript letters representing IBD alleles of individual A's alleles are used to eliminate differences in genotype combinations between the two individuals and to obtain a unified formula for the ratio in each state. The unification is further simplified for identification cases in which it is alleged that both of the participants are outbred. Verification is performed to show that the results obtained with the unified and list-form formulae are equivalent. Results: A series of unified formulae are derived for different identification purposes, based on which an R package named KINSIMU has been developed and evaluated for use in large-size simulations for kinship analysis. Comparison between the package with two existing tools indicated that the unified approach presented here is more convenient and time-saving with respect to the coding process for computer applications compared with the list-based approach, despite appearing more complicated. Moreover, the method of derivation could be extended to other identification problems, such as those with different hypothesis sets or those involving multiple individuals. Conclusion: The unified approach of LR calculation can be beneficial in kinship identification field.

Genetic polymorphism analysis and forensic application evaluation of 57 insertion/deletion polymorphisms from Yi ethnic group in Yunnan

BACKGROUND

As a new kind of diallelic genetic marker, insertion/deletion (InDel) polymorphisms have recently been used in forensic science. However, there are relatively few studies on the forensic evaluation of InDel genetic polymorphisms from different populations.

AIM

The aim of the present work is to assess the genetic polymorphism and forensic applicability of 57 InDels from the Yi ethnic group and explore the genetic background of this group.

SUBJECTS AND METHODS

A total sample of 122 unrelated individuals of Yi group from the Yunnan province were genotyped by the AGCU indel 60 Kit. Multiplex population genetic analyses on the same 57 InDels were carried out among the Yunnan Yi group and 29 reference populations.

RESULTS

The average allele frequency of these loci in the Yi ethnic group was 0.485. Heterozygosity, polymorphism information content, and the power of discrimination were 0.477, 0.362, and 0.612, respectively. The combined power of discrimination and the combined power of exclusion reached to 0.99999999999999999669 and 0.999962965, respectively. The results showed that 57 InDels polymorphisms have high genetic polymorphisms in the Yi ethnic group.

CONCLUSIONS

The 57 InDels could be used for forensic individual identification, paternity testing, and intercontinental population discrimination, with the potential for use in biogeographic ancestry inference.

Targeted sequencing of high-density SNPs provides an enhanced tool for forensic applications and genetic landscape exploration in Chinese Korean ethnic group

BACKGROUND

In this study, we present a NGS-based panel designed for sequencing 1993 SNP loci for forensic DNA investigation. This panel addresses unique challenges encountered in forensic practice and allows for a comprehensive population genetic study of the Chinese Korean ethnic group. To achieve this, we combine our results with datasets from the 1000 Genomes Project and the Human Genome Diversity Panel.

RESULTS

We demonstrate that this panel is a reliable tool for individual identification and parentage testing, even when dealing with degraded DNA samples featuring exceedingly low SNP detection rates. The performance of this panel for complex kinship determinations, such as half-sibling and grandparent-grandchild scenarios, is also validated by various kinship simulations. Population genetic studies indicate that this panel can uncover population substructures on both global and regional scales. Notably, the Han population can be distinguished from the ethnic minorities in the northern and southern regions of East Asia, suggesting its potential for regional ancestry inference. Furthermore, we highlight that the Chinese Korean ethnic group, along with various Han populations from different regional areas and certain northern ethnic minorities (Daur, Tujia, Japanese, Mongolian, Xibo), exhibit a higher degree of genetic affinities when examined from a genomic perspective.

CONCLUSION

This study provides convincing evidence that the NGS-based panel can serve as a reliable tool for various forensic applications. Moreover, it has helped to enhance our knowledge about the genetic landscape of the Chinese Korean ethnic group.

Developmental validation of a high-resolution panel genotyping 639 Y-chromosome SNP and InDel markers and its evolutionary features in Chinese populations

Uniparental-inherited haploid genetic marker of Y-chromosome single nucleotide polymorphisms (Y-SNP) have the power to provide a deep understanding of the human evolutionary past, forensic pedigree, and bio-geographical ancestry information. Several international cross-continental or regional Y-panels instead of Y-whole sequencing have recently been developed to promote Y-tools in forensic practice. However, panels based on next-generation sequencing (NGS) explicitly developed for Chinese populations are insufficient to represent the Chinese Y-chromosome genetic diversity and complex population structures, especially for Chinese-predominant haplogroup O. We developed and validated a 639-plex panel including 633 Y-SNPs and 6 Y-Insertion/deletions, which covered 573 Y haplogroups on the Y-DNA haplogroup tree. In this panel, subgroups from haplogroup O accounted for 64.4% of total inferable haplogroups. We reported the sequencing metrics of 354 libraries sequenced with this panel, with the average sequencing depth among 226 individuals being 3,741×. We illuminated the high level of concordance, accuracy, reproducibility, and specificity of the 639-plex panel and found that 610 loci were genotyped with as little as 0.03 ng of genomic DNA in the sensitivity test. 94.05% of the 639 loci were detectable in male-female mixed DNA samples with a mix ratio of 1:500. Nearly all of the loci were genotyped correctly when no more than 25 ng/μL tannic acid, 20 ng/μL humic acid, or 37.5 μM hematin was added to the amplification mixture. More than 80% of genotypes were obtained from degraded DNA samples with a degradation index of 11.76. Individuals from the same pedigree shared identical genotypes in 11 male pedigrees. Finally, we presented the complex evolutionary history of 183 northern Chinese Hans and six other Chinese populations, and found multiple founding lineages that contributed to the northern Han Chinese gene pool. The 639-plex panel proved an efficient tool for Chinese paternal studies and forensic applications.

Applications of 1993 single nucleotide polymorphism loci in forensic pairwise kinship identifications and inferences

Kinship testing plays critical roles in criminal investigations, missing person searches, civil disputes, as well as identifying disaster victims. The existing commonly used short tandem repeat (STR) loci have limited effectiveness in the identification of second-degree and more distant kinships. In this study, a total of 1993 SNP loci of 119 Chinese Han individuals from eight families were sequenced on the MGISEQ-2000RS platform. The system powers of this panel for kinship identifications were evaluated based on both the likelihood ratio (LR) and identical by state (IBS) methods. The results indicated that this panel could be used as an effective tool to kinship analyses including paternity testing, full sibling testing, second-degree kinships, and first cousin kinship analyses. Both the LR and IBS methods could be applied in distinguishing first-degree and second-degree pairs from unrelated individuals. Based on the 1993 SNP loci, LR>1000 and LR<0.001 are recommended as the thresholds of identifying first-cousin kinships from unrelated individuals, and the system power of such thresholds was 0.9470. Besides, kinship coefficients for different kinship pairs were estimated and then were used to predict the kinships for pairwise individuals. This panel performs an effective kinship inference power for the predictions of first-degree, second-degree kinships and unrelated individual pairs, while presenting low sensitivity in the prediction of first-cousin kinships.

A pipeline for sample tagging of whole genome bisulfite sequencing data using genotypes of whole genome sequencing

BACKGROUND

In large-scale high-throughput sequencing projects and biobank construction, sample tagging is essential to prevent sample mix-ups. Despite the availability of fingerprint panels for DNA data, little research has been conducted on sample tagging of whole genome bisulfite sequencing (WGBS) data. This study aims to construct a pipeline and identify applicable fingerprint panels to address this problem.

RESULTS

Using autosome-wide A/T polymorphic single nucleotide variants (SNVs) obtained from whole genome sequencing (WGS) and WGBS of individuals from the Third China National Stroke Registry, we designed a fingerprint panel and constructed an optimized pipeline for tagging WGBS data. This pipeline used Bis-SNP to call genotypes from the WGBS data, and optimized genotype comparison by eliminating wildtype homozygous and missing genotypes, and retaining variants with identical genomic coordinates and reference/alternative alleles. WGS-based and WGBS-based genotypes called from identical or different samples were extensively compared using hap.py. In the first batch of 94 samples, the genotype consistency rates were between 71.01%-84.23% and 51.43%-60.50% for the matched and mismatched WGS and WGBS data using the autosome-wide A/T polymorphic SNV panel. This capability to tag WGBS data was validated among the second batch of 240 samples, with genotype consistency rates ranging from 70.61%-84.65% to 49.58%-61.42% for the matched and mismatched data, respectively. We also determined that the number of genetic variants required to correctly tag WGBS data was on the order of thousands through testing six fingerprint panels with different orders for the number of variants. Additionally, we affirmed this result with two self-designed panels of 1351 and 1278 SNVs, respectively. Furthermore, this study confirmed that using the number of genetic variants with identical coordinates and ref/alt alleles, or identical genotypes could not correctly tag WGBS data.

CONCLUSION

This study proposed an optimized pipeline, applicable fingerprint panels, and a lower boundary for the number of fingerprint genetic variants needed for correct sample tagging of WGBS data, which are valuable for tagging WGBS data and integrating multi-omics data for biobanks.

Insight into forensic efficiency and genetic structure of the Guizhou Dong group via a 64-plex panel

Insertion/deletion polymorphisms (InDels) show great application values in forensic research because they own superiorities of short tandem repeats (STRs) and single nucleotide polymorphisms (SNPs). Whereas, InDels commonly display low genetic diversities in comparison to STRs. Therefore, they may provide limited genetic information in forensic kinship testing. Here, we evaluated forensic application efficiency of a novel multiplex amplification system including two STRs, 59 InDels, and three sex-determination loci in the Guizhou Dong group. In addition, we explored the genetic background of the Guizhou Dong group in comparison to other reported populations based on 59 InDels. We found that 59 InDels displayed relatively high genetic diversities in the Guizhou Dong group. Moreover, the cumulative forensic efficiency of two STRs and 59 InDels could meet the requirement of individual identification and paternity testing in the Guizhou Dong group. For these 59 InDels, we observed that some loci exhibited relatively high genetic differentiations among different continental populations, especially for African and Non-African populations, which could be viewed as candidate ancestry informative markers in the future. Genetic structure results indicated that the Dong group had close genetic relationships with East Asian and some Southern Chinese Han populations. To sum up, we stated that the 64-plex panel could be performed for forensic application of the Guizhou Dong group.

Evaluation of a SNP-STR haplotype panel for forensic genotype imputation

Short tandem repeat polymorphism (STR)-based individual identification is a popular and reliable method in many forensic applications. However, STRs still frequently fail to find any matched records. In such cases, if known STRs could provide more information, it would be very helpful to solve specific problems. Genotype imputation has long been used in the study of single nucleotide polymorphisms (SNPs) and has recently been introduced into forensic fields. The idea is that, through a reference haplotype panel containing SNPs and STRs, we can obtain unknown genetic information through genotype imputation based on known STR or SNP genotypes. Several recent studies have already demonstrated this exciting idea, and a 1000 Genomes SNP-STR haplotype panel has also been released. To further study the performance of genotype imputation in forensic fields, we collected STR, microhaplotype (MH) and SNP array genotypes from Chinese Han population individuals and then performed genotype imputation analysis based on the released reference panel. As a result, the average locus imputation accuracy was ∼83 % (or ∼70 %) when SNPs in the SNP array (or MH SNPs) were imputed from STRs, and was ∼30 % when highly polymorphic markers (STRs and MHs) were imputed from each other. When STRs were imputed from SNP array, the average locus imputation accuracy increased to ∼48 %. After analyzing the match scores between real STRs and the STRs imputed from SNPs, ∼80 % of studied STR records can be connected to corresponding SNP records, which may help for individual identification. Our results indicate that genotype imputation has great potential for forensic applications.

Identification of novel SNP markers for kinship analysis in the Korean population

Kinship testing using genetic markers such as short tandem repeats (STRs) and single nucleotide polymorphisms (SNPs) is crucial for forensic analysis. Although STR markers have superior discriminatory power due to their highly polymorphic properties, they have several weak points in determining extended distant or complex relationships because of high mutation rates and low success rates in degraded samples. Therefore, SNPs are regarded as promising tools in forensic science because they have low mutation rates and small amplicon sizes. Herein, we propose an SNP panel consisting of 1400 autosomal SNPs obtained from the Korean National Standard Reference Variome (KoVariome) database. To evaluate its performance, in-silico analysis was performed using whole-genome sequencing (WGS) data from 21 Korean families. Subsequently, to estimate pairwise relatedness, kinship coefficients were calculated using PLINK, and Welch's one-way ANOVA test with Games-Howell's pairwise comparison test was performed. As a result, the average kinship coefficients of first- (parent-offspring and full siblings), second- (grandparent-grandchildren and aunt/uncle-niece/nephew), and third- (first cousin and grandniece/grandnephew) degree relatives, and unrelated were 0.24, 0.11, - 0.054, and - 0.0082, respectively. Consequently, relatives (first and second degree) were distinguished from non-relatives; however, further studies are required to investigate more effective SNP markers for discriminating extended kinship. Nevertheless, the results of this study go beyond the scope of screening using the discovered 1400 SNPs in Korean families and suggest the applicability of kinship analysis in the Korean population.

Improving the regional Y-STR haplotype resolution utilizing haplogroup-determining Y-SNPs and the application of machine learning in Y-SNP haplogroup prediction in a forensic Y-STR database: A pilot study on male Chinese Yunnan Zhaoyang Han population

Improving the resolution of the current widely used Y-chromosomal short tandem repeat (Y-STR) dataset is of great importance for forensic investigators, and the current approach is limited, except for the addition of more Y-STR loci. In this research, a regional Y-DNA database was investigated to improve the Y-STR haplotype resolution utilizing a Y-SNP Pedigree Tagging System that includes 24 Y-chromosomal single nucleotide polymorphism (Y-SNP) loci. This pilot study was conducted in the Chinese Yunnan Zhaoyang Han population, and 3473 unrelated male individuals were enrolled. Based on data on the male haplogroups under different panels, the matched or near-matching (NM) Y-STR haplotype pairs from different haplogroups indicated the critical roles of haplogroups in improving the regional Y-STR haplotype resolution. A classic median-joining network analysis was performed using Y-STR or Y-STR/Y-SNP data to reconstruct population substructures, which revealed the ability of Y-SNPs to correct misclassifications from Y-STRs. Additionally, population substructures were reconstructed using multiple unsupervised or supervised dimensionality reduction methods, which indicated the potential of Y-STR haplotypes in predicting Y-SNP haplogroups. Haplogroup prediction models were built based on nine publicly accessible machine-learning (ML) approaches. The results showed that the best prediction accuracy score could reach 99.71% for major haplogroups and 98.54% for detailed haplogroups. Potential influences on prediction accuracy were assessed by adjusting the Y-STR locus numbers, selecting Y-STR loci with various mutabilities, and performing data processing. ML-based predictors generally presented a better prediction accuracy than two available predictors (Nevgen and EA-YPredictor). Three tree models were developed based on the Yfiler Plus panel with unprocessed input data, which showed their strong generalization ability in classifying various Chinese Han subgroups (validation dataset). In conclusion, this study revealed the significance and application prospects of Y-SNP haplogroups in improving regional Y-STR databases. Y-SNP haplogroups can be used to discriminate NM Y-STR haplotype pairs, and it is important for forensic Y-STR databases to develop haplogroup prediction tools to improve the accuracy of biogeographic ancestry inferences.