The Polymorphism Analyses of Short Tandem Repeats as a Basis for Understanding the Genetic Characteristics of the Guanzhong Han Population

Ancestry analysis using a self-developed 56 AIM-InDel loci and machine learning methods

Insertion/deletion (InDel) polymorphisms can be used as one of the ancestry-informative markers in ancestry analysis. In this study, a self-developed panel consisting of 56 ancestry-informative InDels was used to investigate the genetic structures and genetic relationships between Chinese Inner Mongolia Manchu group and 26 reference populations. The Inner Mongolia Manchu group was closely related in genetic background to East Asian populations, especially the Han Chinese in Beijing. Moreover, populations from northern and southern East Asia displayed obvious variations in ancestral components, suggesting the potential value of this panel in distinguishing the populations from northern and southern East Asia. Subsequently, four machine learning models were performed based on the 56 AIM-InDel loci to evaluate the performance of this panel in ancestry prediction. The random forest model presented better performance in ancestry prediction, with 91.87% and 99.73% accuracy for the five and three continental populations, respectively. The individuals of the Inner Mongolia Manchu group were assigned to the East Asian populations by the random forest model, and they exhibited closer genetic affinities with northern East Asian populations. Furthermore, the random forest model distinguished 87.18% of the Inner Mongolia Manchus from the East Asian populations, suggesting that the random forest model based on the 56 ancestry-informative InDels could be a potential tool for ancestry analysis.

Forensic parameters and population analysis of 21 autosomal STR loci in the Wuhu Han population from Anhui Province, East China

BACKGROUND

At present, there are no available genetic data on the AGCU EX22 Kit from the Wuhu Han population.

AIM

This study investigates the applicability of the AGCU EX22 kit, designed for the Chinese population for forensic analysis and population genetics of the Wuhu Han population.

SUBJECTS AND METHODS

Bloodstains from 1565 unrelated healthy individuals in Wuhu city, Anhui Province, were collected for analysis. The AGCU EX22 kit was used for amplification, and capillary electrophoresis was used to separate the amplification products. Allele frequencies and forensic parameters were determined. The Wuhu Han population was compared to 10 reference populations through genetic distance, a phylogenetic neighbor-joining tree and principal component analysis.

RESULTS

In total, 281 alleles and 1187 genotypes were observed. No significant deviations from Hardy-Weinberg equilibrium at any locus were found after Bonferroni's correction. The 21 autosomal short tandem repeat (STR) genetic markers exhibited high informativeness and polymorphism. The cumulative power of discrimination and power of exclusion were 0.999999999999999999999999913380 and 0.999999996752339, respectively. Population comparisons revealed a genetic affinity between Wuhu Han and southern Han populations, except for the Guangdong Han population, which aligned with the traditional geographical division in China.

CONCLUSION

The AGCU EX22 Kit, containing 21 STR loci, is suitable for forensic application and population genetics studies in the Wuhu Han population.

Short Tandem Repeat DNA Profiling Using Perylene-Oligonucleotide Fluorescence Assay

We report an amplification-free genotyping method to determine the number of human short tandem repeats (STRs). DNA-based STR profiling is a robust method for genetic identification purposes such as forensics and biobanking and for identifying specific molecular subtypes of cancer. STR detection requires polymerase amplification, which introduces errors that obscure the correct genotype. We developed a new method that requires no polymerase. First, we synthesized perylene-nucleoside reagents and incorporated them into oligonucleotide probes that recognize five common human STRs. Using these probes and a bead-based hybridization approach, accurate STR detection was achieved in only 1.5 h, including DNA preparation steps, with up to a 1000-fold target DNA enrichment. This method was comparable to PCR-based assays. Using standard fluorometry, the limit of detection was 2.00 ± 0.07 pM for a given target. We used this assay to accurately identify STRs from 50 human subjects, achieving >98% consensus with sequencing data for STR genotyping.

Opportunity of Next-Generation Sequencing-Based Short Tandem Repeat System for Tumor Source Identification

Personal identification using the tumor DNA not only plays an important role in postoperative tissue management but also might be the only accessible source of biological material in forensic identification. Short tandem repeat (STR) is the worldwide accepted forensic marker; however, widespread loss of heterozygosity (L) in tumor tissues challenges the personal identification using the conventional capillary electrophoresis (CE)-based STR typing system (CE-STR). Because the tumors are mixtures of tumor cells and basal cells, we inferred that every germline-originated allele should be detected if the detection method was sensitive enough. Next-generation sequencing (NGS) is known as a highly sensitive application, which might be a promising tool for tumor source identification. In the study, we genotyped and compared the STR results between the platforms, and we found that the concordance was only 91.43%. Higher sensitivity did help identify more germline-originated alleles as expected, and 93.89% of them could be captured by using an NGS-based STR system (NGS-STR). The identity-by-state (IBS) scoring system was applied to generate a new tumor source identification method based on NGS-STR, and the number of loci with 2 identical alleles (A₂) proved to be an ideal criterion for the larger area under the receiver operating characteristic (ROC) curve (AUC). Both the sensitivity and specificity were above 98% in the cutoff of A₂ to distinguish the paired carcinoma (PC) sample group from the unrelated individual (UI) group, the simulated full sibling (FS) group, and the simulated parent–offspring (PO) group.