Pairwise kinship inference and pedigree reconstruction using 91 microhaplotypes.

Kinship inference has been a major issue in forensic genetics, and it remains to be solved when there is no prior hypothesis and the relationships between multiple individuals are unknown. In this study, we genotyped 91 microhaplotypes from 46 pedigree samples using massive parallel sequencing and inferred their relatedness by calculating the likelihood ratio (LR). Based on simulated and real data, different treatments were applied in the presence and absence of relatedness assumptions. The pedigree of multiple individuals was reconstructed by calculating pedigree likelihoods based on real pedigree samples. The results showed that the 91 MHs could discriminate pairs of second-degree relatives from unrelated individuals. And more highly polymorphic loci were needed to discriminate the pairs of second-degree or more distant relative from other degrees of relationship, but correct classification could be obtained by expanding the suspected relationship searched to other relationships with lower LR values. Multiple individuals with unknown relationships can be successfully reconstructed if they are closely related. Our study provides a solution for kinship inference when there are no prior assumptions, and explores the possibility of pedigree reconstruction when the relationships of multiple individuals are unknown.

Exploration of identifying individual tumor tissue based on probabilistic model.

Variations in the tumor genome can result in allelic changes compared to the reference profile of its homogenous body source on genetic markers. This brings a challenge to source identification of tumor samples, such as clinically collected pathological paraffin-embedded tissue and sections. In this study, a probabilistic model was developed for calculating likelihood ratio (LR) to tackle this issue, which utilizes short tandem repeat (STR) genotyping data. The core of the model is to consider tumor tissue as a mixture of normal and tumor cells and introduce the incidence of STR variants (φ) and the percentage of normal cells (Mxn) as a priori parameters when performing calculations. The relationship between LR values and φ or Mxn was also investigated. Analysis of tumor samples and reference blood samples from 17 colorectal cancer patients showed that all samples had Log 10(LR) values greater than 1014. In the non-contributor test, 99.9% of the quartiles had Log 10(LR) values less than 0. When the defense's hypothesis took into account the possibility that the tumor samples came from the patient's relatives, LR greater than 0 was still obtained. Furthermore, this study revealed that LR values increased with decreasing φ and increasing Mxn. Finally, LR interval value was provided for each tumor sample by considering the confidence interval of Mxn. The probabilistic model proposed in this paper could deal with the possibility of tumor allele variability and offers an evaluation of the strength of evidence for determining tumor origin in clinical practice and forensic identification.

Using simulated microhaplotype genotyping data to evaluate the value of machine learning algorithms for inferring DNA mixture contributor numbers.

Inferring the number of contributors (NoC) is a crucial step in interpreting DNA mixtures, as it directly affects the accuracy of the likelihood ratio calculation and the assessment of evidence strength. However, obtaining the correct NoC in complex DNA mixtures remains challenging due to the high degree of allele sharing and dropout. This study aimed to analyze the impact of allele sharing and dropout on NoC inference in complex DNA mixtures when using microhaplotypes (MH). The effectiveness and value of highly polymorphic MH for NoC inference in complex DNA mixtures were evaluated through comparing the performance of three NoC inference methods, including maximum allele count (MAC) method, maximum likelihood estimation (MLE) method, and random forest classification (RFC) algorithm. In this study, we selected the top 100 most polymorphic MH from the Southern Han Chinese (CHS) population, and simulated over 40 million complex DNA mixture profiles with the NoC ranging from 2 to 8. These profiles involve unrelated individuals (RM type) and related pairs of individuals, including parent-offspring pairs (PO type), full-sibling pairs (FS type), and second-degree kinship pairs (SE type). Our results indicated that how the number of detected alleles in DNA mixture profiles varied with the markers' polymorphism, kinship's involvement, NoC, and dropout settings. Across different types of DNA mixtures, the MAC and MLE methods performed best in the RM type, followed by SE, FS, and PO types, while RFC models showed the best performance in the PO type, followed by RM, SE, and FS types. The recall of all three methods for NoC inference were decreased as the NoC and dropout levels increased. Furthermore, the MLE method performed better at low NoC, whereas RFC models excelled at high NoC and/or high dropout levels, regardless of the availability of a priori information about related pairs of individuals in DNA mixtures. However, the RFC models which considered the aforementioned priori information and were trained specifically on each type of DNA mixture profiles, outperformed RFC_ALL model that did not consider such information. Finally, we provided recommendations for model building when applying machine learning algorithms to NoC inference.

Evaluation of large-scale highly polymorphic microhaplotypes in complex DNA mixtures analysis using RMNE method.

DNA mixture interpretation is one of the most challenging problems in forensics. Complex DNA mixtures are more difficult to analyze when there are more than two contributors or related contributors. Microhaplotypes (MHs) are polymorphic genetic markers recently discovered and employed in DNA mixture analysis. However, the evidentiary interpretation of the MH genotyping data needs more debate. The Random Man Not Excluded (RMNE) method analyzes DNA mixtures without using allelic peak height data or the number of contributors (NoC) assumptions. This study aimed to assess how well RMNE interpreted mixed MH genotyping data. We classified the MH loci from the 1000 Genomes Project database into groups based on their Ae values. Then we performed simulations of DNA mixtures with 2-10 unrelated contributors and DNA mixtures with a pair of sibling contributors. For each simulated DNA mixture, incorrectly included ratios were estimated for three types of non-contributors: random men, parents of contributors, and siblings of contributors. Meanwhile, RMNE probability was calculated for contributors and three types of non-contributors, allowing loci mismatch. The results showed that the MH number, the MH Ae values, and the NoC affected the RMNE probability of the mixture and the incorrectly included ratio of non-contributors. When there were more MHs, MHs with higher Ae values, and a mixture with less NoC, the RMNE probability, and the incorrectly included ratio decreased. The existence of kinship in mixtures complicated the mixture interpretation. Contributors' relatives as non-contributors and related contributors in the mixture increased the demands on the genetic markers to identify the contributors correctly. When 500 highly polymorphic MHs with Ae values higher than 5 were used, the four individual types could be distinguished according to the RMNE probabilities. This study reveals the promising potential of MH as a genetic marker for mixed DNA interpretation and the broadening of RMNE as a parameter indicating the relationship of a specific individual with a DNA mixture in the DNA database search.

Characterizing the amplification of STR markers in multiplex polymerase chain displacement reaction using massively parallel sequencing.

Polymerase chain displacement reaction (PCDR) showed advantages in forensic low-template DNA analysis with improved amplification efficiency, higher allele detection capacity, and lower stutter artifact than PCR. However, characteristics of STR markers after PCDR amplification remain unclarified for the limited resolving power of capillary electrophoresis (CE). This issue can be addressed by massively parallel sequencing (MPS) technology with higher throughput and discriminability. Here, we developed a multiplex PCDR system including 24 STRs and amelogenin. In addition, a PCR reference was established for comparison. After amplification, products were subjected to PCR-free library construction and sequenced on the Illumina NovaSeq system. We implemented a sequence-matching pipeline to separate different amplicon types of PCDR products from the combination of primers. In the sensitivity test, the PCDR multiplex obtained full STR profiles with as low as 125 pg 2800M control DNA. Based on that, single-source DNA samples were tested. First, highly concordant genotypes were observed among the PCDR multiplex, the PCR reference, and CE-based STR kits. Next, read counts of different PCDR amplicon types were investigated, showing a relative abundance of 78:12:12:1 for the shortest amplicon S, the two medium amplicons M1 and M2, and the longest amplicon L. We also analyzed the stutter artifacts for distinct amplicon types, and the results revealed the reduction of N - 1 and N - 2 contraction stutters, and the increase of N + 1 and N + 2 elongation stutters in PCDR samples. Moreover, we confirmed the feasibility of PCDR for amplifying degraded DNA samples and unbalanced DNA mixtures. Compared to the previous proof of principle study, our work took a further step to characterize the complete profile of STR markers in the PCDR context. Our results suggested that the PCDR-MPS workflow is an effective approach for forensic STR analysis. Corresponding findings in this study may help the development of PCDR-based assays and probabilistic methods in future studies.

An efficient ancestry informative SNPs panel for further discriminating East Asian populations.

In forensic genetics, the use of ancestry informative single-nucleotide polymorphisms (AISNPs) panels can narrow the direction of the investigation by estimating an individual's biogeographic ancestry. However, distinguishing subgroups within continental regions requires more specific panels. In this study, we screened 19 AISNPs from the 1000 Genomes Project (1KG) based on their FST values to distinguish target populations in East Asia and obtained genotypes through SNaPshot. The 19 AISNPs could divide the global population of the 1KG into five clusters and could further divide the East Asian population into four clusters: Japanese, Han Chinese, Dai Chinese, and Kinh in Ho Chi Minh City of Vietnam. In summary, the 19-AISNP panel may serve as a useful and cost-effective tool for forensic ancestry inference in East Asian populations at a finer scale.

Evaluation of microfluidics-based droplet PCR combined with multiplex STR system in forensic science.

Because of its excellent monodispersity, high throughput, and low volume, microfluidics-based droplet PCR has become the core technology of digital PCR, next-generation sequencing, and other technology platforms. This study constructed a microfluidic water-in-oil droplet PCR system and amplified a commercially available forensic 22-plex short tandem repeat detection system. We analyzed the sensitivity, concordance, amplification efficiency of the droplet PCR, and influence factors of the above aspects. The droplet PCR showed high concordance with conventional bulk PCR and had high sensitivity as 0.125 ng. Furthermore, we observed the performance of droplet PCR in high-order mixed DNA. As the mixture ratios from 10:1 to 30:1, droplet PCR presented more mixture proportion (Mx) increased loci from 11 (57.89%) to 17 (89.47%). In the mixture ratios 20:1, 25:1, and 30:1, significant Mx differences between droplet PCR and bulk PCR were observed (p < 0.05). The results showed that the droplet PCR could improve the identification of the minor contributor's DNA in a two-person mixture and alleviate the imbalanced amplification problem. This study provides a reference and basis for the wide application of droplet PCR in forensic science.

AI-SNPs screening based on the whole genome data and research on genetic structure differences of subcontinent populations.

The genetic structure differences in population is one of the key elements in medical research involving multi-population samples. A set of ancestry-informative single nucleotide polymorphisms (AI-SNPs) can be utilized to analyze genetic component of a population, infer ancestral origin of individuals and pre-filter samples to reduce the impact of population genetic structure differences on medical research. However, most of the published studies were focused on revealing the differences between populations of continents or regions of a continent. In this paper, AI-SNPs were screened by calculating FST value in each pair of five East Asian populations: Japanese in Tokyo (JPT), Han Chinese in Beijing (CHB), Southern Han Chinese (CHS), Chinese Dai in Xishuangbanna (CDX) and Kinh in Ho Chi Minh City (KHV) in the 1000 Genomes Project phase 3 (GRCh37.p13) to analyze differences in subcontinent populations. The results demonstrate that the five East Asian populations in our study were assigned to three clusters: JPT, CHB and CHS, CDX and KHV. A set of AI-SNPs can be used for analysis of individual genetic composition and selection of representative individuals. Individuals with over 80% population representative genetic components have good representativeness of a population. This paper demonstrated the practical value of the method, which was performed to verify the ancestral composition and select representative samples with a panel of screened AI-SNPs by FST value, thereby reducing the influence of genetic structure differences in subcontinent populations on population-related medical research.

Forensic genomics research on microhaplotypes.

Microhaplotype loci (microhaplotype, MHs), defined by two or more closely linked single nucleotide polymorphisms, are a type of molecular marker within a short segment of DNA. As emerging forensic genetic markers, MHs have no stutter artefacts and higher polymorphism, and permit the design of smaller amplicons. In order to identify the markers from a genome wide perspective and explore their potential application further, we constructed the most comprehensive MH dataset to date, based on the whole genome sequencing data of 105 Han individuals in Southern China from 1000 Genomes Project. The results showed that there were 9,490,075 MH loci in the range of 350 bp in the human genome, and the distribution density of microhaplotypes suggests gene variation. Polymorphism analysis of MHs from various base spans showed that the polymorphism of MHs could reach or exceed common short tandem repeat sites. In addition, based on their flexible assembly, a scheme to build the public database of microhaplotypes was proposed.

A targeted ancestry informative InDels panel on capillary electrophoresis for ancestry inference in Asian populations.

CE is the primary methodology used in forensic DNA typing. Alleles of commonly used types of genetic markers could be separated and detected via CE based on dye color and migration time. Insertion/deletion (InDel) is an ideal genetic marker for forensic DNA analysis due to their abundance in the human genome, low mutation rate, availability of their allele types via CE, and elimination of stutter peaks. Moreover, InDels could be used as ancestry informative markers since allele frequencies of InDels is different among geographically separated populations. Several ancestry informative insertion/deletion panels have been established based on CE platform to achieve the intercontinental populations distinction. However, improvements to differentiate intracontinental populations is few. In this study, 21 InDels with fixation index (FST ) > 0.15 were selected and assembled into one ancestry informative insertion/deletion panel. Using well-designed primers, those 21 InDels could be amplified successfully and genotyped on the CE platform accurately and completely. The panel showed a large FST distance distinction among the ten Asian populations. Using clustering analysis, ten Asian populations were classified into three subgroups: East Asian, Southeast Asian, and South Asian subgroups. To evaluate the panel's capability in ancestry inference, a validation experiment was undertaken with 319 individuals from four geographically separated populations in China. Four Chinese populations were classified into different ancestry subgroups and 81.8% test individuals' ancestry could be inferred correctly. Our result showed that development of high ancestry informative InDels panel based on CE platform is a potential for individual ancestry inference among intracontinental populations.

Forensic drowning site inference employing mixed pyrosequencing profile of DNA barcode gene (rbcL).

The development of DNA barcoding method has given rise to a promising way of studying genetic taxonomy. Our previous study showed that pyrosequencing profile of 18S rDNA V7 hypervariable region can be used for identifying water sources without resolving the exact components of diatom colonies in water samples. In this continued study, we aimed to improve the established analysis method and to provide scientific evidence for forensic practices. A drowning animal model was set up by injecting mimic drowning fluid into the respiratory tract of the rabbit. In order to minimize the interference of animal DNA, the hypervariable region of chloroplast ribulose-1,5-bisphosphate carboxylase large unit gene (rbcL) was used as the pyrosequencing target region for the consistency analysis of plankton populations in tissues and water samples. After decoding the pyrosequencing profile of the targeted rbcL gene with the AdvISER-M-PYRO algorithm, the plankton colony that was inhaled into drowning animal lung tissue could be successfully traced back to the source of drowning fluid. Our data suggest that this method could be a reliable tool assisting forensic drowning site inference.

[Correlation of K-ras Gene Mutations with the Protein Expressions of TAK1 and MAP4K2 in Colorectal Cancer].

OBJECTIVE: To analyze the correlation of K-ras gene mutations with the protein expressions of transforming growth factor-ß activating kinase 1 (TAK1) protein and mitogen-activated protein kinase kinase kinase kinase 2 (MAP4K2) protein in colorectal cancer. METHODS: K-ras gene mutations were detected by DNA sequencing analysis, and the expressions of TAK1 protein and MAP4K2 protein were detected by immunohistochemical method in 76 cases of colorectal cancer tissues. RESULTS: In 76 cases of colorectal cancer tissues, the mutation rate of K-ras gene was 32.89% (25 cases), and K-ras gene mutations were correlated with the degrees of cell differentiation ( P<0.05). The positive rates of TAK1 protein and MAP4K2 protein were 48.68% and 46.05%, respectively. The protein expressions of TAK1 and MAP4K2 were positively correlated with the degrees of cell differentiation and lymph node metastases, respectively ( P<0.05). There was no correlation between K-ras gene mutation and either TAK1 protein or MAP4K2 protein expression ( P>0.05). In 25 cases of colorectal cancer with K-ras mutation, the expression of TAK1 protein was positively correlated with the expression of MAP4K2 protein ( P<0.05). CONCLUSION: K-ras gene mutation, TAK1 and MAP4K2 protein expressions were related to the degree of differentiation of colorectal cancer, but not to the depth of invasion. In colorectal cancer with K-ras gene mutation, the expression of TAK1 protein was positively correlated with the expression of MAP4K2 protein.

NG25, a novel inhibitor of TAK1, suppresses KRAS-mutant colorectal cancer growth in vitro and in vivo.

KRAS mutations are one of the most prevalent genetic alterations in colorectal cancer (CRC). Although directly targeting KRAS still is a challenge in anti-cancer therapies, alternatively inhibiting KRAS related signaling pathways has been approached effectively. Here we firstly reported that MAP kinase, transforming growth factor-ß-activated kinase 1 (TAK1), commonly expressed in CRC cell lines and significantly associated with KRAS mutation status. Inhibition of TAK1 by the small molecular inhibitor NG25 could inhibit CRC cells proliferation in vitro and in vivo, especially in KRAS-mutant cells. NG25 induced caspase-dependent apoptosis in KRAS-mutant cells and in orthotopic CRC mouse models by regulating the B-cell lymphoma-2 (Bcl-2) family and the inhibitor of apoptosis protein (IAP) family. Besides inhibiting molecules downstream of MAPK, including ERK, JNK and p38 phosphorylation, NG25 could block NF-κB activation in KRAS-mutant cells. As a target gene of NF-κB, down-regulated XIAP expression may be not only involved in apoptosis induced by NG25, but also reducing the formation of TAK1-XIAP complex that can activate TAK1 downstream signaling pathways, which forms a positive feedback loop to further induce apoptosis in KRAS-mutant CRC cells. Together, these findings indicated that TAK1 is an important kinase for survival of CRCs harboring KRAS mutations, and that NG25 may be a potential therapeutic strategy for KRAS-mutant CRC.