The association between DNA methylation and human height and a prospective model of DNA methylation-based height prediction.

As a vital anthropometric characteristic, human height information not only helps to understand overall developmental status and genetic risk factors, but is also important for forensic DNA phenotyping. We utilized linear regression analysis to test the association between each CpG probe and the height phenotype. Next, we designed a methylation sequencing panel targeting 959 CpGs and subsequent height inference models were constructed for the Chinese population. A total of 11,730 height-associated sites were identified. By employing KPCA and deep neural networks, a prediction model was developed, of which the cross-validation RMSE, MAE and R2 were 5.62 cm, 4.45 cm and 0.64, respectively. Genetic factors could explain 39.4% of the methylation level variance of sites used in the height inference models. Collectively, we demonstrated an association between height and DNA methylation status through an EWAS analysis. Targeted methylation sequencing of only 959 CpGs combined with deep learning techniques could provide a model to estimate human height with higher accuracy than SNP-based prediction models.

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.

Differences of circular RNA expression profiles between monozygotic twins' blood, with the forensic application in bloodstain and saliva.

Monozygotic twins (MZTs) possess identical genomic DNA sequences and are usually indistinguishable through routine forensic DNA typing methods, which can be relevant in criminal and paternity cases. Recently, novel epigenetic methods involving DNA methylation and microRNA analysis have been introduced to differentiate MZTs. In this study, we explore the potential of using epigenetic markers, specifically circular RNAs (circRNAs), a type of non-coding RNA (ncRNA), to identify MZTs, and investigate the unique expression patterns of circRNAs within pairs of MZTs, enabling effective differentiation. Epigenetics regulates gene expression at the post-transcriptional level and plays a crucial role in cell growth and aging. CircRNAs, a recently characterized subclass of ncRNA, have a distinct covalent loop structure without the typical 5' cap or 3' tail. They have been reported to modulate various cellular processes and play roles in embryogenesis and eukaryotic development. To achieve this, we conducted a comprehensive circRNA sequencing analysis (circRNA-seq) using total RNA extracted from the blood samples of five pairs of MZTs. We identified a total of 15,257 circRNAs in all MZTs using circRNA-seq. Among them, 3, 21, 338, and 2967 differentially expressed circRNAs (DEcircRNAs) were shared among five, four, three, and two pairs of MZTs, respectively. Subsequently, we validated twelve selected DEcircRNAs using real-time quantitative polymerase chain reaction (RT-qPCR) assays, which included hsa_circ_0004724, hsa_circ_0054196, hsa_circ_004964, hsa_circ_0000591, hsa_circ_0005077, hsa_circ_0054853, hsa_circ_0054716, hsa_circ_0002302, hsa_circ_0004482, hsa_circ_0001103, novel_circ_0030288 and novel_circ_0056831. Among them, hsa_circ_0005077 and hsa_circ_0004482 exhibited the best performance, showing differences in 7 out of 10 pairs of MZTs. These twelve differentially expressed circRNAs also demonstrated strong discriminative power when tested on saliva samples from 10 pairs of MZTs. Notably, hsa_circ_0004724 displayed differential expression in 8 out of 10 pairs of MZTs in their saliva. Additionally, we evaluated the detection sensitivity, longitudinal temporal stability, and suitability for aged bloodstains of these twelve DEcircRNAs in forensic scenarios. Our findings highlight the potential of circRNAs as molecular markers for distinguishing MZTs, emphasizing their suitability for forensic application.

Feature selection with a genetic algorithm can help improve the distinguishing power of microbiota information in monozygotic twins' identification.

Introduction: Personal identification of monozygotic twins (MZT) has been challenging in forensic genetics. Previous research has demonstrated that microbial markers have potential value due to their specificity and long-term stability. However, those studies would use the complete information of detected microbial communities, and low-value species would limit the performance of previous models. Methods: To address this issue, we collected 80 saliva samples from 10 pairs of MZTs at four different time points and used 16s rRNA V3-V4 region sequencing to obtain microbiota information. The data formed 280 inner-individual (Self) or MZT sample pairs, divided into four groups based on the individual relationship and time interval, and then randomly divided into training and testing sets with an 8:2 ratio. We built 12 identification models based on the time interval ( ≤ 1 year or ≥ 2 months), data basis (Amplicon sequence variants, ASVs or Operational taxonomic unit, OTUs), and distance parameter selection (Jaccard distance, Bray-Curist distance, or Hellinger distance) and then improved their identification power through genetic algorithm processes. The best combination of databases with distance parameters was selected as the final model for the two types of time intervals. Bayes theory was introduced to provide a numerical indicator of the evidence's effectiveness in practical cases. Results: From the 80 saliva samples, 369 OTUs and 1130 ASVs were detected. After the feature selection process, ASV-Jaccard distance models were selected as the final models for the two types of time intervals. For short interval samples, the final model can completely distinguish MZT pairs from Self ones in both training and test sets. Discussion: Our findings support the microbiota solution to the challenging MZT identification problem and highlight the importance of feature selection in improving model performance.

Identification Strategy of Biological Half Sibling Relationship.

OBJECTIVES: To compare the application value of the likelihood ratio (LR) method and identity by state (IBS) method in the identification involving half sibling relationships, and to provide a reference for the setting of relevant standards for identification of half sibling relationship. METHODS: (1) Based on the same genetic marker combinations, the reliability of computer simulation method was verified by comparing the distributions of cumulated identity by state score (CIBS) and combined full sibling index in actual cases with the distributions in simulated cases. (2) In different numbers of three genetic marker combinations, the simulation of full sibling, half sibling and unrelated individual pairs, each 1 million pairs, was obtained; the CIBS, as well as the corresponding types of cumulative LR parameters, were calculated. (3) The application value of LR method was compared with that of IBS method, by comparing the best system efficiency provided by LR method and IBS method when genetic markers in different amounts and of different types and accuracy were applied to distinguish the above three relational individual pairs. (4) According to the existing simulation data, the minimum number of genetic markers required to distinguish half siblings from the other two relationships using different types of genetic markers was estimated by curve fitting. RESULTS: (1) After the rank sum test, under the premise that the real relationship and the genetic marker combination tested were the same, there was no significant difference between the simulation method and the results obtained in the actual case. (2) In most cases, under the same conditions, the system effectiveness obtained by LR method was greater than that by IBS method. (3) According to the existing data, the number of genetic markers required for full-half siblings and half sibling identification could be obtained by curve fitting when the system effectiveness reached 0.95 or 0.99. CONCLUSIONS: When distinguishing half sibling from full sibling pairs or unrelated pairs, it is recommended to give preference to the LR method, and estimate the required number of markers according to the identification types and the population data, to ensure the identification effect.

Development and evaluation of a novel panel containing 188 microhaplotypes for 2nd-degree kinship testing in the Hebei Han population.

Distant kinship identification is one of the critical problems in forensic genetics. As a new type of genetic marker defined and discussed in the last decade, the microhaplotype (MH) has drawn much attention in such identification owing to its specific advantages to traditional short tandem repeat (STR) or single nucleotide polymorphism (SNP) markers. In this study, MH markers were screened step by step from the 1000 Genomes Project database, and a novel multiplex panel containing 188 MHs (in which 181 are reported the first time, while 1 was reported in a previous study and the other 6 have partial overlaps with known markers) was constructed for application in 2nd- and 3rd-degree kinship identification. Along with the construction, a novel MH nomenclature was proposed, in which the SNP position information they contained was taken into account to eliminate the possibility that the same locus was named differently interlaboratory. After a series of evaluations, the panel was shown to have good sequencing accuracy, high sensitivity, species specificity, and resistance to anti-PCR inhibitors or degradation. Population data of the 188 MHs were calculated based on the genetic information of 221 unrelated Hebei Han individuals, and the effective number of alleles (Ae) ranged from 2.0925 to 8.2634 (with an average of 2.9267). For the whole system, the cumulative matching probability (CMP), the cumulative power of exclusion in paternity testing of duos (CPEduo) and that of trios (CPEtrio) reached 2.8422 × 10-137, 1-1.3109 × 10-21, and 1-2.8975 × 10-39, respectively, indicating that this panel was satisfactory for individual identification and paternity testing. Then, the efficiency of the 188 MHs in 2nd- and 3rd-degree kinship testing was studied based on 30 extended families consisting of 179 2nd-degree and 121 3rd-degree relatives, as well as simulations of 0.5 million pairs of those two kinships. The results showed that clear opinions would be given in 83.36% of 2nd-degree identifications with a false rate less than 10-5, when the confirming and excluding thresholds of cumulative likelihood ratio (CLR) were set as 104 and 10-4, respectively. This panel is still not sufficient to solve the problem of 3rd-degree kinship identification alone, and approximately 300 or 870 MH loci would be needed in 2nd- or 3rd-degree kinship identification, respectively, to achieve a system efficiency not less than 0.99 with such a threshold set; such necessary numbers would be used only as a reference in further research.

Preliminary exploratory research on the application value of oral and intestinal meta-genomics in predicting subjects' occupations-A case study of the distinction between students and migrant workers.

Background: In the field of forensic science, accurately determining occupation of an individual can greatly assist in resolving cases such as criminal investigations or disaster victim identifications. However, estimating occupation can be challenging due to the intricate relationship between occupation and various factors, including gender, age, living environment, health status, medication use, and lifestyle habits such as alcohol consumption and smoking. All of these factors can impact the composition of oral or gut microbial community of an individual. Methods and results: In this study, we collected saliva and feces samples from individuals representing different occupational sectors, specifically students and manual laborers. We then performed metagenomic sequencing on the DNA extracted from these samples to obtain data that could be analyzed for taxonomic and functional annotations in five different databases. The correlation between occupation with microbial information was assisted from the perspective of α and ß diversity, showing that individuals belonging to the two occupations hold significantly different oral and gut microbial communities, and that this correlation is basically not affected by gender, drinking, and smoking in our datasets. Finally, random forest (RF) models were built with recursive feature elimination (RFE) processes. Models with 100% accuracy in both training and testing sets were constructed based on three species in saliva samples or on a single pathway annotated by the KEGG database in fecal samples, namely, "ko04145" or Phagosome. Conclusion: Although this study may have limited representativeness due to its small sample size, it provides preliminary evidence of the potential of using microbiome information for occupational inference.

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

Next generation sequencing (NGS)-based single nucleotide polymorphism (SNP) genotyping is widely used in the field of forensics. SNP genotyping data from several NGS platforms have been published, but forensic application trials of DNA nanoball sequencing platforms have been very limited. In this work, we developed a 448-plex SNP panel on the BGISEQ-500RS platform. The sequencing metrics of a total of 261 samples that were sequenced with this panel are reported in detail. The average sequencing depth was 8373 × and the average heterozygosity of the 448-plex assay was 0.85. Sensitivity analysis showed that 325 SNPs were successfully genotyped with as little as 50 pg of genomic DNA, with the mean quality score of the sequencing data above Q30. Forensic parameters were calculated based on the data of 142 unrelated Chinese Han individuals and the combined matching probability was as low as 5.21 × 10-101. Kinship analyses based on experiments and computer simulations showed that the 448-panel was as effective as the ForenSeq™ DNA Signature Prep Kit for second-degree kinship identification, and when the two panels were merged, the related pairs were almost completely distinguished from unrelated pairs. The 448-plex SNP panel on the BGISEQ-500RS platform provides a powerful tool for forensic individual identification and kinship analysis.

AUCP: An indicator for system effectiveness of panels in pairwise distant kinship identification.

Multiple studies have been done for the identification of pairwise distant kinship and several targeted panels have been constructed. For most of such constructions, pedigree analysis was applied to evaluate the system effectiveness of a certain panel. However, such analyses were hard to be compared to each other and could be affected by many factors, such as sample size and sampling randomness. A new indicator named predicted area under ROC curve (AUCP), where ROC curve stood for receiver operating characteristic curve, was derived applying binomial distribution theory and analyzed with simulated and real cases in this study. After comparing between the values of AUCPs and results of pedigree analyses with different loci sets and kinship types, the ability of these two methods evaluating the system effectiveness was proved to be close to each other. The implementation of AUCP was much easier than pedigree analysis, because a secondary sampling or simulation was not needed. Therefore, AUCP can be a better indicator for panels targeted to pairwise distant kinship identification and we are recommending it as an indicator calculated by default for such panels.

Development of an NGS panel containing 42 autosomal STR loci and the evaluation focusing on secondary kinship analysis.

High-throughput next-generation sequencing (NGS) is a feasible technique to detect considerably more markers and simultaneously obtain length and sequence information in a single reaction. In this study, we developed an NGS panel including 42 commonly used autosomal short tandem repeats (STRs) and amelogenin on the Illumina MiSeq FGx™. Sequencing accuracy was validated by the consistency of 2800M Control DNA detected using the ForenSeq™ DNA Signature Prep Kit and Sanger sequencing. Nomenclature incompatibility was found between NGS-STR and CE-STR typing at 9 loci (D3S3045, D6S477, D7S3048, D9S925, D14S608, D17S1290, D18S535, D21S1270, GATA198B05), despite the correct sequence. The difference was caused by the two different methods of identifying motif sequence and a one-to-one correspondence can be found. We evaluated the panel by investigating consistency, sequencing sensitivity and the effectiveness of the 2nd-degree relationship identification. Herein, we present sequencing results from 58 unrelated individuals of the Hebei Han population. The total discrimination power (TDP) and cumulative probability of exclusion for trio paternity testing (CPEtrio) of the 42 NGS-STR panels reached 1-2.84 × 10-57 and 1-9.87 × 10-21, respectively. By family simulation and likelihood ratio (LR) calculation, this panel was shown to have effectiveness for the 2nd-degree kinship identification similar to the ForenSeq™ DNA Signature Prep Kit and certain advantages compared with it due to the relatively small number of loci. As expected, it provides new data for the development of NGS-STR typing technology.

A new strategy to confirm the identity of tumour tissues using single-nucleotide polymorphisms and next-generation sequencing.

With growing cancer morbidity, forensics cases in which archived tumour tissues can be used as biological samples are increasing, and an effective method to identify the body source of tumour tissues is needed. Single nucleotide polymorphisms (SNPs) may be a promising biomarker to identify the source of tumour tissues because of their low mutation rate and small amplicon size. Next-generation sequencing techniques offers the ability to detect hundreds of SNPs in a single run. The Precision ID Identity Panel (Thermo Fisher Scientific, Waltham, MA, USA) detects 90 autosomal SNPs for individual identification and 34 lineage-informative SNPs on Y chromosome using the Ion PGM system (Thermo Fisher Scientific). In this study, we evaluated performance of the panel for individual identification of tumour tissues. One hundred and fifty pairs of tumour tissues and corresponding normal tissues were analysed. Loss of heterozygosity was detected only in tumour tissues. The identity-by-state (IBS) scoring system was adopted to identify the body source of tumour tissues. The IBS score, as well as the number of loci with 2 alleles (A2), 1 allele (A1) and 0 alleles (A0) shared, were analysed within each tumour-normal pair, unrelated individual pairs, parent-offspring pairs and full-sibling pairs. According to the probability distribution, threshold of A2 in the range of 69 to 89 could achieve accuracy > 99% in identifying the source of tumour tissues. Thus, we developed a new strategy (process and criteria) to identify the source of tumour tissues that could be used in practice.

Utility of ForenSeq™ DNA Signature Prep Kit in the research of pairwise 2nd-degree kinship identification.

The scope of forensic kinship analysis is being extended to more distant or complex relationships. However, current methods and standards in this field do not meet the needs of casework. The next-generation sequencing (NGS) technology may hold an advantage in this field to traditional methods due to its strong power to get much more genetic information. To evaluate the effectiveness of NGS to identify the 2nd-degree kinship pairs, DNA samples of 227 individuals from 49 Hebei Han pedigrees were tested by Goldeneye™ 20A kit using capillary electrophoresis (CE) to confirm the relationships within each pedigree, and those of 111 individuals within 97 confirmed grandparent-grandchild or avuncular pairs were analyzed by ForenSeq™ DNA Signature Prep Kit using MiSeq® FGx™ DNA sequencing platform. We calculated the likelihood ratio (LR) based on ITO method and the identical by state (IBS) score of 97 kinship pairs and compared with those of 97 unrelated pairs. According to the results summarized and analyzed by Fisher discriminant analysis and leave-one-out cross-validation (LOOCV) method, ITO method showed higher accuracy than IBS method, even with less information. Therefore, we proposed a recommendation of the thresholds for pairwise 2nd-degree kinship identification for Hebei Han population based on ITO method. When using ITO method based on 94 SNPs and the length information of 27 autosomal STRs, cumulative likelihood ratio (CLR) > 1 and CLR < 0.1 are recommended as the thresholds of confirming and excluding, respectively. The accuracy applying such thresholds is greater than 95%, indicating the promising application value of NGS in this field and providing a direction for further kinship identification strategy selection. Further studies are needed to get the population genetic data of loci contained in the kit based on all sequence information including flanking regions to make full use of the NGS data to improve the accuracy of kinship analysis.