Y-chromosomal short tandem repeats (Y-STRs) are highly informative tools in forensic investigations for tracing paternal lineages and generating investigative leads when direct autosomal STR matches are not available. However, the discriminative power of expanded Y-STR panels and optimal strategies for database searching remain inadequately defined. Here, we first presented kinshipY, an interactive online platform that streamlines the analysis of Y-STR mutations, pedigree structure visualization, genetic distance calculation, and statistical power evaluation. Using this tool, we then empirically estimated the mutation rates of 80 Y-STRs (Forensic Analysis System Multiplecues SetB Kit) based on 488 father-son pairs. Finally, the differentiation rates among male relatives and between unrelated males were evaluated using three deep-rooted families spanning 1-27 meioses. The results showed that a total of 120 mutations were identified, yielding an overall mutation rate of 3.1 × 10⁻³ (95 % CIs: 2.5 × 10-3 - 3.7 × 10-3). Single-step mutations accounted for 95 % of events, with gains and losses occurring at nearly equal frequencies. The SetB panel distinguished 27.96 % of father-son pairs and 50 % of siblings, with differentiation rates reaching 100 % for relationships separated by ≥ 11 meioses. To differentiate males from distinct lineages, we established a threshold‑setting strategy that balances both the false positive rate (FPR) and false negative rate (FNR), demonstrating that step‑difference‑based thresholds outperform locus‑difference‑based thresholds. For the SetB panel, a step‑difference threshold of ≥ 15 enabled the differentiation of 99.59 % of unrelated males. In contrast, panels with fewer Y‑STRs-Yfiler (16 Y‑STRs), Class A (19 Y‑STRs), Yfiler Plus (25 Y‑STRs), and Class A+B (32 Y‑STRs)-exhibited significantly higher FPR and FNR. In summary, this study demonstrates the enhanced resolution offered by the SetB panel. For Y-STR database searching, we recommend the following: (1) use a powerful marker set whenever possible; (2) adopt a step-difference-based matching strategy; (3) apply dynamic, panel-specific thresholds; and (4) when integrating forensic investigative genetic genealogy, include more distant relatives for threshold estimation. These recommendations could provide valuable guidance for forensic practice.

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.

Respiratory syncytial virus (RSV) is a major cause of severe lung injury, particularly in infants. Most previous studies have relied on single-omics or single-model systems, limiting a comprehensive understanding of the dynamic and coordinated host response. To overcome this, we employed an integrated multiomics approach across complementary in vivo (murine) and physiologically relevant ex vivo (human bronchial organoid) models, combining longitudinal transcriptomic and proteomic profiling to systematically delineate the spatiotemporal dynamics of RSV-induced lung injury and repair. Our analysis revealed a stage-specific progression from early inflammatory injury to late repair, in which extracellular matrix (ECM)-receptor interaction and PI3K-Akt signaling play central roles. Moreover, a core set of hub genes including Itgb3, Itga2b, and Fn1 were positively correlated with RSV-induced lung injury and clinical disease severity. Pharmacological inhibition of αIIbβ3 (encoded by Itga2b and Itgb3) or fibronectin (Fn1) in vivo significantly attenuated immunopathology and lung injury without affecting viral clearance, directly establishing their causal role in disease pathogenesis. Collectively, our study not only provides novel insights into the integrin-centric network driving RSV immunopathology but also identifies a potential biomarker panel for clinical severity stratification and therapeutic targets for intervention.

Method of moments(MoM)and identity by descent(IBD)segment methods are two popular algorithms for kinship inference in investigative genetic genealogy(IGG).However,there is no consensus on how or when to use them,and different criteria of IBD lengths or kinship coefficients are applied to consider a true match.In this study,we compared the performance of KING(representing the MoM method)and IBIS(representing the IBD segment method)for kinship inference in homogeneous populations,admixed populations,and sparse SNP panels.Both simulated and real family data were used.In addition,an equivalent threshold-based method for kinship inference was also proposed,based on either the kinship coefficients or the lengths of IBD segments.Results showed that the overall accuracies were 64.97%for homogeneous population and 54.71%for admixed population with KING while they were 72.92%and 70.88%,respectively,with IBIS.IBIS showed low recall and precision rates when the SNP number was below 164k.In contrast,KING performed still robustly with SNP number as low as 10k.Similar results were obtained with real family data.In conclusion,the two methods perform differently and different methods should be used for different scenarios.If the DNA is of high quality or the samples are from admixed populations,the IBD segment method is recommended.If the samples are of low quantity and/or quality,MoM is more appropriate.For more complex scenarios,both methods can be tried.More importantly,there is an urgent need to develop new algorithms to address related issues.

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.

Forensic analysis of body fluid stains is extremely important, which helps reconstruct crime scenes. It involves two main challenges: body fluid identification (BFID) and individualization. The former aims to ascertain the type/origin of the body fluid stain, while the latter tries to assign the stain to a specific donor. Generally, they are addressed through RNA and DNA analyses, respectively, but this can be time-consuming, laborious, and sometimes yield suboptimal results, especially mixed body fluid stains. To overcome these limitations, we developed an innovative mRNA-based sequencing panel with a dual function. This system comprises 34 body fluid-specific mRNA genes and 39 cSNP markers (amplicon length: 50 90 bp), enabling a direct link between specific body fluids and their donors. We thoroughly validated the integrated system according to the guidelines of the Scientific Working Group on DNA Analysis Methods (SWGDAM) on the MGI massively parallel sequencing (MPS) platform. As a result, this panel showed robust identification efficiency for body fluids at 20 ng RNA input, and the range of cumulative discrimination power (CDP) value was 0.802445047 0.999310789 in five types of body fluid. Furthermore, it had been employed in actual cases and provided the guidance. In conclusion, this system can efficiently, rapidly, and accurately perform body fluid identification and individualization for single-source and mixed samples, meeting the daily investigative demands in forensic genetics.

Hair samples are commonly encountered at crime scenes. However, most of them are telogen hairs, from which only partial DNA profiles can be yielded. These profiles are generally insufficient for forensic human identification and kinship testing. In this study, we sequenced the hair roots and hair shafts from ten unrelated individuals using a short-amplicon panel, and evaluated the performance of hair shafts of different lengths in terms of genotype calling and genotype accuracy. We also employed a pseudohaploid genotype-based approach for kinship coefficient estimation and proposed an error model for likelihood ratio (LR) calculation. The results showed that many SNPs could be successfully recovered from the nuclear DNA of hair shafts. However, approximately 30

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).

Full-sibling (FS) identification is a crucial aspect of kinship analysis. However, current FS identification methods need to be more accurate and effective for routine FS identification. In this study, the optimal cut-off values for FS identification by incorporating both the identical by state (IBS) and likelihood ratio (LR) methods under four different levels of error rates were assessed. The corresponding sensitivity, specificity, accuracy, and effectiveness were calculated for different numbers of short tandem repeats (STRs), ranging from 19 to 55. The identified cut-off values were validated using authentic pedigrees from the Han population in East China. It was determined that the cut-off values derived from the IBS method and LR method with an error rate below 0.01% were dependable and practical. The study also explored the impact of half-sibling relationships and the inclusion of reference relatives in FS identification. Currently, an updated technical specification for FS identification in China was released, serving as a valuable resource for FS testing in forensic applications.

Gliomas are the most prevalent and aggressive neoplasms of the central nervous system, representing a major challenge for effective treatment and patient prognosis. This study identifies the proteasome subunit beta type-8 (PSMB8/LMP7) as a promising prognostic biomarker for glioma. Using a multiparametric radiomic model derived from preoperative magnetic resonance imaging (MRI), we accurately predicted PSMB8 expression levels. Notably, radiomic prediction of poor prognosis was highly consistent with elevated PSMB8 expression. Our findings demonstrate that PSMB8 depletion not only suppressed glioma cell proliferation and migration but also induced apoptosis via activation of the transforming growth factor beta (TGF-β) signaling pathway. This was supported by downregulation of key receptors (TGFBR1 and TGFBR2). Furthermore, interference with PSMB8 expression impaired phosphorylation and nuclear translocation of SMAD2/3, critical mediators of TGF-β signaling. Consequently, these molecular alterations resulted in reduced tumor progression and enhanced sensitivity to temozolomide (TMZ), a standard chemotherapeutic agent. Overall, our findings highlight PSMB8's pivotal role in glioma pathophysiology and its potential as a prognostic marker. This study also demonstrates the clinical utility of MRI radiomics for preoperative risk stratification and pre-diagnosis. Targeted inhibition of PSMB8 may represent a therapeutic strategy to overcome TMZ resistance and improve glioma patient outcomes.

Background:Prolyl 4-hydroxylase subunit beta (P4HB) has been linked to glioma progression and treatment resistance; however, its role in the tumor microenvironment regulation remains unclear. Materials and Methods:A total of 90 human glioma samples and 30 normal traumatic brain injury (TBI) tissues from patients undergoing surgical resection were collected from the First Affiliated Hospital of Zhengzhou University for immunohistochemical (IHC) staining. The signaling pathway mechanism regulating prognosis and tumor proliferation was explored through bioinformatics analysis and functional assays via P4HB knockdown. Results:The IHC analysis of 90 glioma and 30 TBI tissues revealed that P4HB expression correlated with tumor malignancy, especially the WHO grade 4 and grade 2 (P < 0.0001). Furthermore, transcriptomic data analysis identified P4HB as a prognostic marker associated with poor survival and tumor-associated macrophage infiltration (P < 0.05 in all cohorts). Using shRNA lentiviral constructs, stable P4HB knockdown glioblastoma (GBM) cell lines were generated. mRNA sequencing revealed significant downregulation of the interleukin (IL)-6/signal transducer and activator of transcription 3 (IL-6/STAT3) signaling axis. Functional studies showed that P4HB deficiency resulted in reduced IL-6 secretion (P < 0.0001), suppressed M2 polarization of tumor-associated microglia, and inhibited glioma cell growth both in vitro and in vivo, with IL-6 neutralization recapitulating these effects. Mechanistically, P4HB promoted STAT3 phosphorylation in microglia, driving their pro-tumorigenic M2 phenotype. Conclusion:These findings establish P4HB as a regulator of glioma progression via IL-6/STAT3-mediated microglial polarization, highlighting its potential as a therapeutic target for GBM.

Integrating multimodal data can uncover causal features hidden in single-modality analyses, offering a comprehensive understanding of disease complexity. This study introduces a multimodal fusion subtyping (MOFS) framework that integrates radiological, pathological, genomic, transcriptomic, and proteomic data from 122 patients with IDH-wildtype adult glioma, identifying three subtypes: MOFS1 (proneural) with favorable prognosis, elevated neurodevelopmental activity, and abundant neurocyte infiltration; MOFS2 (proliferative) with the worst prognosis, superior proliferative activity, and genome instability; MOFS3 (TME-rich) with intermediate prognosis, abundant immune and stromal components, and sensitive to anti-PD-1 immunotherapy. STRAP emerges as a prognostic biomarker and potential therapeutic target for MOFS2, associated with its proliferative phenotype. Stromal infiltration in MOFS3 serves as a crucial prognostic indicator, allowing for further prognostic stratification. Additionally, we develop a deep neural network (DNN) classifier based on radiological features to further enhance the clinical translatability, providing a non-invasive tool for predicting MOFS subtypes. Overall, these findings highlight the potential of multimodal fusion in improving the classification, prognostic accuracy, and precision therapy of IDH-wildtype glioma, offering an avenue for personalized management.

This study investigates the expression of pyroptosis-related genes (PRGs) in head and neck squamous cell carcinoma (HNSCC) and their potential role in the tumor immune microenvironment. Additionally, we conducted an in-depth transcriptomic analysis of HNSCC with high GSDME expression. This study utilized the curated TCGA-HNSCC and GSE65858 datasets to analyze differentially expressed genes (DEGs) associated with pyroptosis in HNSCC. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed on these DEGs. The infiltration of 22 immune cell types was assessed using the CIBERSORTx algorithm. GSDME-overexpressing cells were sequenced using the Illumina NovaSeq 6000 platform, and immunohistochemistry (IHC) was conducted for validation. A total of 501 TCGA-HNSCC patient data and 270 tumor samples from the GSE65858 dataset were collected. Seventeen pyroptosis-related genes were found to have mutations in HNSCC samples, with TP53, CASP8, and NLRP3 exhibiting the highest mutation frequencies. GO enrichment analysis revealed that the DEGs were enriched in cellular components such as myofibrils and collagen-containing extracellular matrix, as well as in molecular functions including actin binding and receptor ligand activity. KEGG pathway enrichment analysis showed that DEGs were enriched in the focal adhesion biological pathway. GSEA analysis indicated a negative correlation between DEGs and the cytochrome P450 pathway. Transcriptomic analysis of high GSDME expression revealed a significant decrease in CK13 (KRT13) and CK19 (KRT19) in the GSDME-overexpressing group. Downregulated genes were significantly enriched in cell adhesion molecules and the arachidonic acid pathway. Immunohistochemistry confirmed a statistically significant reduction in CK13 and CK19 protein expression in the high GSDME expression group. Transcriptomic analysis of GSDME overexpression showed significant upregulation or downregulation of transcription factor families, including E2F, ETS, HMG, MYB, BZIP, and C2H2. Specifically, ELF3 from the ETS transcription factor family and PBX1 from the Homeobox transcription factor family were downregulated. GSDME is potentially associated with the ETS transcription factor ELF3 and the Homeobox transcription factor PBX1. The reduced expression of CK13 and CK19 in the GSDME-overexpressing group may serve as a potential mechanism by which GSDME inhibits HNSCC growth.

Identifying phase-separated structures remains challenging, and effective intervention methods are currently lacking1. Here we screened for phase-separated proteins in breast tumour cells and identified forkhead (FKH) box protein M1 (FOXM1) as the most prominent candidate. Oncogenic FOXM1 underwent liquid-liquid phase separation (LLPS) with FKH consensus DNA element, and compartmentalized the transcription apparatus in the nucleus, thereby sustaining chromatin accessibility and super-enhancer landscapes crucial for tumour metastatic outgrowth. Screening an epigenetics compound library identified AMPK agonists as suppressors of FOXM1 condensation. AMPK phosphorylated FOXM1 in the intrinsically disordered region (IDR), perturbing condensates, reducing oncogenic transcription, accumulating double-stranded DNA to stimulate innate immune responses, and endowing discrete FOXM1 with the ability to activate immunogenicity-related gene expressions. By developing a genetic code-expansion orthogonal system, we demonstrated that a phosphoryl moiety at a specific IDR1 site causes electrostatic repulsion, thereby abolishing FOXM1 LLPS and aggregation. A peptide targeting IDR1 and carrying the AMPK-phosphorylated residue was designed to disrupt FOXM1 LLPS and was shown to inhibit tumour malignancy, rescue tumour immunogenicity and improve tumour immunotherapy. Together, these findings provide novel and in-depth insights on function and mechanism of FOXM1 and develop methodologies that hold promising implications in clinics.

In forensic genetics, Y-chromosomal short tandem repeats (Y-STRs) are widely used in male lineage tracing, kinship analysis, and mixture interpretation. Conventional genotyping of Y-STRs relies on length-based detection via capillary electrophoresis (CE). However, massively parallel sequencing (MPS) enables simultaneous determination of both length and sequence genotypes, thereby increasing the information obtained per assay. While developing and validating an MPS panel, we made an unexpected observation: the DYS572 locus exhibited heterozygous genotypes in both male and female samples. This could misidentify a single-source sample as a mixed sample. Reference sequence alignment revealed that the DYS572 region on the Y chromosome (GRCh38, chrY: 3,811,419–3,811,858) shares 98.41

DNA mixtures are a common sample type in forensic genetics, and we typically assume that contributors to the mixture are unrelated when calculating the likelihood ratio (LR). However, scenarios involving mixtures with related contributors, such as in family murder or incest cases, can also be encountered. Compared to the mixtures with unrelated contributors, the kinship within the mixture would bring additional challenges for the inference of the number of contributors (NOC) and the construction of probabilistic genotyping models. To evaluate the influence of potential kinship on the individual identification of the person of interest (POI), we conducted simulations of two-person (2P) and three-person (3P) DNA mixtures containing unrelated or related contributors (parent-child, full-sibling, and uncle-nephew) at different mixing ratios (for 2P: 1:1, 4:1, 9:1, and 19:1; for 3P: 1:1:1, 2:1:1, 5:4:1, and 10:5:1), and performed massively parallel sequencing (MPS) using MGIEasy Signature Identification Library Prep Kit on MGI platform. In addition, in silico simulations of mixtures with unrelated and related contributors were also performed. In this study, we evaluated 1): the MPS performance; 2) the influence of multiple genetic markers on determining the presence of related contributors and inferring the NOC within the mixture; 3) the probability distribution of MAC (maximum allele count) and TAC (total allele count) based on in silico mixture profiles; 4) trends in LR values with and without considering kinship in mixtures with related and unrelated contributors; 5) trends in LR values with length- and sequence-based STR genotypes. Results indicated that multiple numbers and types of genetic markers positively influenced kinship and NOC inference in a mixture. The LR values of POI were strongly dependent on the mixing ratio. Non- and correct-kinship hypotheses essentially did not affect the individual identification of the major POI; the correct kinship hypothesis yielded more conservative LR values; the incorrect kinship hypothesis did not necessarily lead to the failure of POI individual identification. However, it is noteworthy that these considerations could lead to uncertain outcomes in the identification of minor contributors. Compared to length-based STR genotyping, using sequence-based STR genotype increases the individual identification power of the POI, concurrently improving the accuracy of mixing ratio inference using EuroForMix. In conclusion, the MGIEasy Signature Identification Library Prep kit demonstrated robust individual identification power, which is a viable MPS panel for forensic DNA mixture interpretations, whether involving unrelated or related contributors.

The inference of body fluids and tissues is critical in reconstructing crime scenes and inferring criminal behaviors. Nevertheless, present methods are incompatible with conventional DNA genotyping, and additional testing might result in excessive consumption of forensic scene materials. This study aims to investigate the feasibility of distinguishing common body fluids/tissues through the difference in mitochondrial DNA copy number (mtDNAcn). Four types of body fluids/tissues were analyzed in this study - hair, saliva, semen, and skeletal muscle. MtDNAcn was estimated by dividing the read counts of mitochondrial DNA to that of nuclear DNA (RRmt/nu). Results indicated that there were significant differences in RRmt/nu between different body fluids/tissues. Specifically, hair samples exhibited the highest RRmt/nu (log10RRmt/nu: 4.3 ± 0.28), while semen samples showed the lowest RRmt/nu (log10RRmt/nu: -0.1 ± 0.28). RRmt/nu values for DNA samples without extraction were notably higher (approximately 2.9 times) than those obtained after extraction. However, no significant difference in RRmt/nu was observed between various age and gender groups. Hierarchical clustering and Kmeans clustering analyses showed that body fluids/tissues of the same type clustered closely to each other and could be inferred with high accuracy. In conclusion, this study demonstrated that the simultaneous detection of nuclear and mitochondrial DNA made it possible to perform conventional DNA analyses and body fluid/tissue inference at the same time, thus killing two birds with one stone. Furthermore, mtDNAcn has the potential to serve as a novel and promising biomarker for the identification of body fluids/tissues.

l-lactate modifies proteins through lactylation1, but how this process occurs is unclear. Here we identify the alanyl-tRNA synthetases AARS1 and AARS2 (AARS1/2) as intracellular l-lactate sensors required for l-lactate to stimulate the lysine lactylome in cells. AARS1/2 and the evolutionarily conserved Escherichia coli orthologue AlaRS bind to l-lactate with micromolar affinity and they directly catalyse l-lactate for ATP-dependent lactylation on the lysine acceptor end. In response to l-lactate, AARS2 associates with cyclic GMP-AMP synthase (cGAS) and mediates its lactylation and inactivation in cells and in mice. By establishing a genetic code expansion orthogonal system for lactyl-lysine incorporation, we demonstrate that the presence of a lactyl moiety at a specific cGAS amino-terminal site abolishes cGAS liquid-like phase separation and DNA sensing in vitro and in vivo. A lactyl mimetic knock-in inhibits cGAS, whereas a lactyl-resistant knock-in protects mice against innate immune evasion induced through high levels of l-lactate. MCT1 blockade inhibits cGAS lactylation in stressed mice and restores innate immune surveillance, which in turn antagonizes viral replication. Thus, AARS1/2 are conserved intracellular l-lactate sensors and have an essential role as lactyltransferases. Moreover, a chemical reaction process of lactylation targets and inactivates cGAS.

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.

Immune rejection caused by mismatches in human leucocyte antigens (HLAs) remains a major obstacle to the success of allogeneic cell therapies. Current strategies for the generation of 'universal' immune-compatible cells, particularly the editing of HLA class I (HLA-I) genes or the modulation of proteins that inhibit natural killer cells, often result in genomic instability or cellular cytotoxicity. Here we show that a beta(2)-microglobulin super-enhancer (B2M-SE) that is responsive to interferon-gamma is a critical regulator of the expression of HLA-I on mesenchymal stromal cells (MSCs). Targeted epigenetic repression of B2M-SE in MSCs reduced the surface expression of HLA-I below the threshold required to activate allogenic T cells while maintaining levels sufficient to evade cytotoxicity mediated by natural killer cells. In a humanized mouse model, the epigenetically edited MSCs demonstrated improved survival by evading the immune system, allowing them to exert enhanced therapeutic effects on LPS-induced acute lung injury. Targeted epigenetic repression of B2M-SE may facilitate the development of off-the-shelf cell sources for allogeneic cell therapy.