Background: Forensic investigative genetic genealogy (FIGG) has developed rapidly in recent years and is considered a novel tool for crime investigation. However, crime scene samples are often of low quality and quantity and are challenging to analyze. Deciding which approach should be used for kinship inference in forensic practice remains a troubling problem for investigators. Methods: In this study, we selected four popular approaches—KING, IBS, TRUFFLE, and GERMLINE—comprising one method of moment (MoM) estimator and three identical by descent (IBD) segment-based tools and compared their performance at varying numbers of SNPs and levels of genotyping errors using both simulated and real family data. We also explored the possibility of making robust kinship inferences for samples with ultra-high genotyping errors by integrating MoM and the IBD segment-based methods. Results: The results showed that decreasing the number of SNPs had little effect on kinship inference when no fewer than 164 K SNPs were used for all four approaches. However, as the number decreased further, decreased efficiency was observed for the three IBD segment-based methods. Genotyping errors also had a significant effect on kinship inference, especially when they exceeded 1%. In contrast, MoM was much more robust to genotyping errors. Furthermore, the combination of the MoM and the IBD segment-based methods showed a higher overall accuracy, indicating its potential to improve the tolerance to genotyping errors. Conclusions: In conclusion, this study shows that different approaches have unique characteristics and should be selected for different scenarios. More importantly, the integration of the MoM and the IBD segment-based methods can improve the robustness of kinship inference and has great potential for applications in forensic practice.

The detection of identity-by-descent (IBD) segments is widely used to infer relatedness in many fields, including forensics and ancient DNA analysis. However, existing methods are often ineffective for poor-quality DNA samples. Here, we propose a method, clusIBD, which can robustly detect IBD segments using unphased genetic data with a high rate of genotyping error. We evaluated and compared the performance of clusIBD with that of IBIS, TRUFFLE, and IBDseq using simulated data, artificial poor-quality materials, and ancient DNA samples. The results show that clusIBD outperforms these existing tools and could be used for kinship inference in fields such as ancient DNA analysis and criminal investigation. clusIBD is publicly available at GitHub (https://github.com/Ryan620/clusIBD/) and BioCode (https://ngdc.cncb.ac.cn/biocode/tool/BT007882).

Background/Objectives: Kinship inference is commonly adopted in various forensic applications, but previous studies have often lacked precision. Methods: In this study, a new method for the nomenclature of kinship types, i.e., kinship chain (KC), was proposed, and then, six types of identity by state (IBS) scores were calculated for simulated and real families using four types of markers. Finally, several Bayesian network (BN)-based classifiers were constructed to investigate the efficiency of the kinship inference. Results: A total of 7, 22, 58, and 3 KCs were obtained for common first-, second-, and third-degree relatives and unrelated pairs, respectively. High accuracies could be achieved in distinguishing between related and unrelated pairs after combining the four types of genetic markers, with an accuracy of >99.99% for all 7 KCs of first-degree relationships and ~99% for 14 out of 22 KCs of second-degree relatives. When comparing relationships of the same degree, the accuracies were 99.28%, 42.31%, and 15.82% for first-, second-, and third-degree relationships, respectively. When it came to differentiating unspecific relationships, the overall accuracy was over 80%. All the results were validated on real family data. Conclusions: With the new nomenclature method of kinship types and the combination of autosomal and non-autosomal genetic markers, kinship inference can be realized with high accuracy and precision, which will be helpful in complex forensic cases, such as the identification of mass disaster victims.

Background/Objectives: Hair shafts are frequently encountered as forensic evidence, but their limited nuclear DNA content often constrains short tandem repeat (STR) profiling. Mitochondrial DNA (mtDNA) analysis provides an alternative approach; however, the extent to which hair-shaft physical characteristics affect MPS-derived mtDNA read counts, degradation state, and point heteroplasmy (PHP) remains insufficiently characterized. This study aimed to evaluate these associations in human hair shaft samples. Methods: mtDNA hypervariable regions were analyzed in 907 hair shaft fragments from 183 donors using the MGIEasy Signature Identification Library Prep Kit and massively parallel sequencing. Samples were grouped by hair-shaft length, longitudinal segment, scalp region, color, diameter, donor sex, and cosmetic treatment. MPS read counts were used as semi-quantitative indicators of relative mtDNA representation, the HVR7/HVR5 read-count ratio was used as an indirect indicator of degradation state, and PHP was called at a minor allele frequency of ≥10% with a sequencing depth of ≥100× at the site. Results: Under the present workflow, hair shafts generated higher mtDNA read counts than paired bloodstains, and PHP was detected more frequently in hair shafts than in bloodstains (15.93% versus 8.85%). In the exploratory subgroup analyses, longer hair shafts tended to show higher total MPS-derived mtDNA read counts, whereas longitudinally segmented hairs showed a tendency toward decreasing read counts and increasing degradation from the proximal to distal end. In a small paired black/white hair dataset, black hairs showed higher read counts than paired white hairs, but this observation should be interpreted cautiously. Scalp region, diameter, donor sex, and cosmetic treatment showed no consistent effects on read counts or degradation state, although cosmetic treatment was associated with descriptive differences in PHP type and regional distribution. Conclusions: These findings suggest that selected physical characteristics of hair shafts may be associated with MPS-derived mtDNA metrics under the present workflow. However, because several subgroup analyses were based on limited sample sizes and clustered samples, these results should be regarded as exploratory and require validation in larger independent datasets.

Inferring relatedness through the detection of identity-by-descent (IBD) segments is widely used in many fields. However, existing methods are often powerless for poor-quality DNA samples. Here, we propose a method, clusIBD, which can robustly detect IBD segments using unphased genetic data with high genotype errors. We evaluated and compared the performance of clusIBD with IBIS, TRUFFLE, and IBDseq using simulated data, artificial poor-quality materials and ancient DNA samples. The results showed that clusIBD outperformed these state-of-the-art existing tools and may be a promising tool for kinship inference in fields such as ancient DNA analysis and criminal investigation (freely available at https://github.com/Ryan620/clusIBD/ ).