A SNP panel for identification of DNA and RNA specimens

Identification of individuals from low template blood samples using whole transcriptome shotgun sequencing

Biological trace samples consisting of very few cells pose a challenge to conventional forensic genetic DNA analysis. RNA may be an alternative to DNA when handling low template samples. Whereas each cell only contains two copies of an autosomal DNA segment, the transcriptome retains much of the genomic variation replicated in abundant RNA fragments. In this study, we describe the development of a prototype RNA-based SNP selection set for forensic human identification from low template samples (50 pg gDNA). Whole blood from a subset of the Danish population (41 individuals) and blood stains subjected to degradation at room temperature for up to two weeks were analysed by whole transcriptome shotgun sequencing. Concordance was determined by DNA genotyping with the Infinium Omni5-4 SNP chip. In the 100 protein-coding genes with the most reads, 5214 bi-allelic SNPs with gnomAD minor allele frequencies > 0.1 in the African/African American, East Asian, and (non-Finnish) European populations were identified. Of these, 24 SNPs in 21 genes passed screening in whole blood and degraded blood stains, with a resulting mean match probability of 4.5 ∙ 10-9. Additionally, ancestry informative SNPs and SNPs in genes useful for body fluid identification were identified in the transcriptome. Consequently, shotgun sequencing of RNA from low template samples may be used for a vast host of forensic genetics purposes, including simultaneous human and body fluid identification, leading to direct donor identification in the identified body fluid.

Genetic sex validation for sample tracking in next-generation sequencing clinical testing

OBJECTIVE

Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups.

RESULTS

Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors (49.09%), samples from transgender participants (3.64%) and stem cell or bone marrow transplant patients (7.27%) along with undetermined sample mix-ups (40%) for which sample swaps occurred prior to arrival at genome centers, however the exact cause of the events at the sampling sites resulting in the mix-ups were not able to be determined.

Single Nucleotide Polymorphism (SNP) and Antibody-based Cell Sorting (SNACS): A tool for demultiplexing single-cell DNA sequencing data

Motivation

Recently, single-cell DNA sequencing (scDNA-seq) and multi-modal profiling with the addition of cell-surface antibodies (scDAb-seq) have provided key insights into cancer heterogeneity. Scaling these technologies across large patient cohorts, however, is cost and time prohibitive. Multiplexing, in which cells from unique patients are pooled into a single experiment, offers a possible solution. While multiplexing methods exist for scRNAseq, accurate demultiplexing in scDNAseq remains an unmet need.

Results

Here, we introduce SNACS: Single-Nucleotide Polymorphism (SNP) and Antibody-based Cell Sorting. SNACS relies on a combination of patient-level cell-surface identifiers and natural variation in genetic polymorphisms to demultiplex scDNAseq data. We demonstrated the performance of SNACS on a dataset consisting of multi-sample experiments from patients with leukemia where we knew truth from single-sample experiments from the same patients. Using SNACS, accuracy ranged from 0.948 - 0.991 vs 0.552 - 0.934 using demultiplexing methods from the single-cell literature.

RNA therapeutics for neurological disease

Neurological disorders are the group of diseases that primarily affect the center nervous system, which could lead to a significant negative impact on the ability of learning new skills, speaking, breathing, walking, judging, making decision, and other essential living skills. In the last decade, neurological disorders have significantly increased their impact to our community and become the one of leading causes of disability and death. The World Health Organization has identified neurological disorders including Alzheimer's disease and other dementia as the health crisis for the modern life. Tremendous ongoing research efforts focus on understanding of disease genetics, molecular mechanisms and developing therapeutic interventions. Because of the urgent need of the effective therapeutics and the recent advances in the toolkits and understanding for developing more drug-like RNA molecules, there is a growing interest for developing RNA therapeutics for neurological disorders. This article will discuss genetics and mechanisms of neurological disorders and how RNA-based molecules have been used to develop therapeutics for this group of diseases, challenges of RNA therapeutics and future perspectives on this rising therapeutic intervention tool.

Vaccinomics: Paving the Way for Personalized Immunization

Vaccines are one of the most important medical advancements in human history. They have been successfully used to control and limit the spread of many of the lethal diseases that have plagued us, such as smallpox and polio. Previous vaccine design methodologies were based on the model of "isolate-inactivateinject", which amounts to giving the same vaccine dose to everyone susceptible to infection. In recent years, the importance of how the host genetic background alters vaccine response necessitated the introduction of vaccinomics, which is aimed at studying the variability of vaccine efficacy by associating genetic variability and immune response to vaccination. Despite the rapid developments in variant screening, data obtained from association studies is often inconclusive and cannot be used to guide the new generation of vaccines. This review aims to compile the polymorphisms in HLA and immune system genes and examine the link with their immune response to vaccination. The compiled data can be used to guide the development of new strategies for vaccination for vulnerable groups. Overall, the highly polymorphic HLA locus had the highest correlation with vaccine response variability for most of the studied vaccines, and it was linked to variation in multiple stages of the immune response to the vaccines for both humoral and cellular immunity. Designing new vaccine technologies and immunization regiments to accommodate for this variability is an important step for reaching a vaccinomics-based approach to vaccination.

Genetic Sex Validation for Sample Tracking in Clinical Testing

Objective

Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups.

Results

Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors, samples from transgender participants and stem cell or bone marrow transplant patients along with undetermined sample mix-ups.

Genomic screening methodology not requiring barcoding: Single nucleotide polymorphism-based, mixed-cell screening (SMICS)

Although high-throughput, cancer cell-line screening is a time-honored, important tool for anti-cancer drug development, this process involves the testing of each, individual drug in each, individual cell-line. Despite the availability of robotic liquid handling systems, this process remains a time-consuming and costly investment. The Broad Institute developed a new method called Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) to screen a mixture of barcoded, tumor cell-lines. Although this methodology significantly improved the efficiency of screening large numbers of cell-lines, the barcoding process itself was tedious that requires gene transfection and subsequent selection of stable cell-lines. In this study, we developed a new, genomic approach for screening multiple cancer cell-lines using endogenous "tags" that did not require prior barcoding: single nucleotide polymorphism-based, mixed-cell screening (SMICS). The code for SMICS is available at https://github.com/MarkeyBBSRF/SMICS.

A pipeline for sample tagging of whole genome bisulfite sequencing data using genotypes of whole genome sequencing

BACKGROUND

In large-scale high-throughput sequencing projects and biobank construction, sample tagging is essential to prevent sample mix-ups. Despite the availability of fingerprint panels for DNA data, little research has been conducted on sample tagging of whole genome bisulfite sequencing (WGBS) data. This study aims to construct a pipeline and identify applicable fingerprint panels to address this problem.

RESULTS

Using autosome-wide A/T polymorphic single nucleotide variants (SNVs) obtained from whole genome sequencing (WGS) and WGBS of individuals from the Third China National Stroke Registry, we designed a fingerprint panel and constructed an optimized pipeline for tagging WGBS data. This pipeline used Bis-SNP to call genotypes from the WGBS data, and optimized genotype comparison by eliminating wildtype homozygous and missing genotypes, and retaining variants with identical genomic coordinates and reference/alternative alleles. WGS-based and WGBS-based genotypes called from identical or different samples were extensively compared using hap.py. In the first batch of 94 samples, the genotype consistency rates were between 71.01%-84.23% and 51.43%-60.50% for the matched and mismatched WGS and WGBS data using the autosome-wide A/T polymorphic SNV panel. This capability to tag WGBS data was validated among the second batch of 240 samples, with genotype consistency rates ranging from 70.61%-84.65% to 49.58%-61.42% for the matched and mismatched data, respectively. We also determined that the number of genetic variants required to correctly tag WGBS data was on the order of thousands through testing six fingerprint panels with different orders for the number of variants. Additionally, we affirmed this result with two self-designed panels of 1351 and 1278 SNVs, respectively. Furthermore, this study confirmed that using the number of genetic variants with identical coordinates and ref/alt alleles, or identical genotypes could not correctly tag WGBS data.

CONCLUSION

This study proposed an optimized pipeline, applicable fingerprint panels, and a lower boundary for the number of fingerprint genetic variants needed for correct sample tagging of WGBS data, which are valuable for tagging WGBS data and integrating multi-omics data for biobanks.

SNP analysis of challenging bone DNA samples using the HID-Ion AmpliSeq™ Identity Panel: facts and artefacts

PCR-MPS is an emerging tool for the analysis of low-quality DNA samples. In this study, we used PCR-MPS to analyse 32 challenging bone DNA samples from three Second World War victims, which previously yielded no results in conventional STR PCR-CE typing. The Identity Panel was used with 27 cycles of PCR. Despite that we only had an average of 6.8 pg of degraded DNA as template, 30 out of 32 libraries (93.8%) produced sequencing data for about 63/90 autosomal markers per sample. Out of the 30 libraries, 14 (46.7%) yielded single source genetic profiles in agreement with the biological identity of the donor, whereas 12 cases (40.0%) resulted in SNP profiles that did not match or were mixed. The misleading outcomes for those 12 cases were likely due to hidden exogenous human contamination, as shown by the higher frequencies of allelic imbalance, unusual high frequencies of allelic drop-ins, high heterozygosity levels in the consensus profiles generated from challenging samples, and traces of amplified molecular products in four out of eight extraction negative controls. Even if the source and the time of the contamination were not identified, it is likely that it occurred along the multi-step bone processing workflow. Our results suggest that only positive identification by statistical tools (e.g. likelihood ratio) should be accepted as reliable; oppositely, the results leading to exclusion should be treated as inconclusive because of potential contamination issues. Finally, strategies are discussed for monitoring the workflow of extremely challenging bone samples in PCR-MPS experiments with an increased number of PCR cycles.

A transcriptome atlas of leg muscles from healthy human volunteers reveals molecular and cellular signatures associated with muscle location

Skeletal muscles support the stability and mobility of the skeleton but differ in biomechanical properties and physiological functions. The intrinsic factors that regulate muscle-specific characteristics are poorly understood. To study these, we constructed a large atlas of RNA-seq profiles from six leg muscles and two locations from one muscle, using biopsies from 20 healthy young males. We identified differential expression patterns and cellular composition across the seven tissues using three bioinformatics approaches confirmed by large-scale newly developed quantitative immune-histology procedures. With all three procedures, the muscle samples clustered into three groups congruent with their anatomical location. Concomitant with genes marking oxidative metabolism, genes marking fast- or slow-twitch myofibers differed between the three groups. The groups of muscles with higher expression of slow-twitch genes were enriched in endothelial cells and showed higher capillary content. In addition, expression profiles of Homeobox (HOX) transcription factors differed between the three groups and were confirmed by spatial RNA hybridization. We created an open-source graphical interface to explore and visualize the leg muscle atlas (https://tabbassidaloii.shinyapps.io/muscleAtlasShinyApp/). Our study reveals the molecular specialization of human leg muscles, and provides a novel resource to study muscle-specific molecular features, which could be linked with (patho)physiological processes.

Whole exome sequencing identifies two novel variants in PHEX and DMP1 in Malaysian children with hypophosphatemic rickets

BACKGROUND

Hypophosphatemic rickets (HR) is a genetic disease of phosphate wasting that is characterized by defective bone mineralization. The most common cause of the disease is mutations in the phosphate regulating gene with homologies to endopeptidases on the X chromosome (PHEX) gene. The aims of this study were to identify the gene variants responsible for HR in three cases of Malaysian origin from three independent families and to describe their clinical, biochemical, and radiological features.

METHODS

Whole exome sequencing (WES) was performed on all patients and their parents, followed by Sanger sequencing validation. Bioinformatics tools were used to provide supporting evidence for pathogenicity of variants. To confirm that a mutation is de novo, paternity test was carried out. High resolution melting curve analysis was performed to assess the allele frequency in normal controls for mutations that were found in the patients.

RESULTS

The patients showed typical characteristics of HR including lower limb deformity, hypophosphatemia, and elevated alkaline phosphatase. WES revealed two variants in the PHEX gene and one variant in the dentin matrix protein 1 (DMP1) gene. Two of the three variants were novel, including c.1946_1954del (p.Gly649_Arg651del) in PHEX and c.54 + 1G > A in DMP1. Our data suggests that the novel p.Gly649_Arg651del variant is likely pathogenic for HR disease.

CONCLUSIONS

This study extends the variant spectrum of the PHEX and DMP1 genes. Our findings indicate that WES is an advantageous approach for diagnosis of genetic diseases which are heterogeneous.

Community-led risk analysis of direct-to-consumer whole-genome sequencing

Direct-to-consumer (DTC) genetic testing is cheaper and more accessible than ever before; however, the intention to combine, reuse, and resell this genetic information as powerful data sets is generally hidden from the consumer. This financial gain is creating a competitive DTC market, reducing the price of whole-genome sequencing (WGS) to under 300 USD. Entering this transition from single-nucleotide polymorphism-based DTC testing to WGS DTC testing, individuals looking for access to their whole-genomic information face new privacy and security risks. Differences between WGS and other methods of consumer genetic tests are left unexplored by regulation, leading to the application of legal data anonymization methods on whole-genome data, and questionable consent methods. Large representative genomic data sets are important for research and improve the standard of medicine and personalized care. However, these data can also be used by market players, law enforcement, and governments for surveillance, population analyses, marketing purposes, and discrimination. Here, we present a summary of the state of WGS DTC genetic testing and its current regulation, through a community-based lens to expose dual-use risks in consumer-facing biotechnologies.

Identifying individuals using proteomics: are we there yet?

Multi-omics approaches including proteomics analyses are becoming an integral component of precision medicine. As clinical proteomics studies gain momentum and their sensitivity increases, research on identifying individuals based on their proteomics data is here examined for risks and ethics-related issues. A great deal of work has already been done on this topic for DNA/RNA sequencing data, but it has yet to be widely studied in other omics fields. The current state-of-the-art for the identification of individuals based solely on proteomics data is explained. Protein sequence variation analysis approaches are covered in more detail, including the available analysis workflows and their limitations. We also outline some previous forensic and omics proteomics studies that are relevant for the identification of individuals. Following that, we discuss the risks of patient reidentification using other proteomics data types such as protein expression abundance and post-translational modification (PTM) profiles. In light of the potential identification of individuals through proteomics data, possible legal and ethical implications are becoming increasingly important in the field.

Privacy-aware estimation of relatedness in admixed populations

BACKGROUND

Estimation of genetic relatedness, or kinship, is used occasionally for recreational purposes and in forensic applications. While numerous methods were developed to estimate kinship, they suffer from high computational requirements and often make an untenable assumption of homogeneous population ancestry of the samples. Moreover, genetic privacy is generally overlooked in the usage of kinship estimation methods. There can be ethical concerns about finding unknown familial relationships in third-party databases. Similar ethical concerns may arise while estimating and reporting sensitive population-level statistics such as inbreeding coefficients for the concerns around marginalization and stigmatization.

RESULTS

Here, we present SIGFRIED, which makes use of existing reference panels with a projection-based approach that simplifies kinship estimation in the admixed populations. We use simulated and real datasets to demonstrate the accuracy and efficiency of kinship estimation. We present a secure federated kinship estimation framework and implement a secure kinship estimator using homomorphic encryption-based primitives for computing relatedness between samples in two different sites while genotype data are kept confidential. Source code and documentation for our methods can be found at https://doi.org/10.5281/zenodo.7053352.

CONCLUSIONS

Analysis of relatedness is fundamentally important for identifying relatives, in association studies, and for estimation of population-level estimates of inbreeding. As the awareness of individual and group genomic privacy is growing, privacy-preserving methods for the estimation of relatedness are needed. Presented methods alleviate the ethical and privacy concerns in the analysis of relatedness in admixed, historically isolated and underrepresented populations.

SHORT ABSTRACT

Genetic relatedness is a central quantity used for finding relatives in databases, correcting biases in genome wide association studies and for estimating population-level statistics. Methods for estimating genetic relatedness have high computational requirements, and occasionally do not consider individuals from admixed ancestries. Furthermore, the ethical concerns around using genetic data and calculating relatedness are not considered. We present a projection-based approach that can efficiently and accurately estimate kinship. We implement our method using encryption-based techniques that provide provable security guarantees to protect genetic data while kinship statistics are computed among multiple sites.

SVAT: Secure outsourcing of variant annotation and genotype aggregation

Background

Sequencing of thousands of samples provides genetic variants with allele frequencies spanning a very large spectrum and gives invaluable insight into genetic determinants of diseases. Protecting the genetic privacy of participants is challenging as only a few rare variants can easily re-identify an individual among millions. In certain cases, there are policy barriers against sharing genetic data from indigenous populations and stigmatizing conditions.

Results

We present SVAT, a method for secure outsourcing of variant annotation and aggregation, which are two basic steps in variant interpretation and detection of causal variants. SVAT uses homomorphic encryption to encrypt the data at the client-side. The data always stays encrypted while it is stored, in-transit, and most importantly while it is analyzed. SVAT makes use of a vectorized data representation to convert annotation and aggregation into efficient vectorized operations in a single framework. Also, SVAT utilizes a secure re-encryption approach so that multiple disparate genotype datasets can be combined for federated aggregation and secure computation of allele frequencies on the aggregated dataset.

Conclusions

Overall, SVAT provides a secure, flexible, and practical framework for privacy-aware outsourcing of annotation, filtering, and aggregation of genetic variants. SVAT is publicly available for download from https://github.com/harmancilab/SVAT.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04959-6.

Forensic Feature Exploration and Comprehensive Genetic Insights Into Yugu Ethnic Minority and Northern Han Population via a Novel NGS-Based Marker Set

The MPS technology has expanded the potential applications of DNA markers and increased the discrimination power of the targeted loci by taking variations in their flanking regions into consideration. Here, a collection of nuclear and extranuclear DNA markers (totally six kinds of nuclear genetic markers and mtDNA hypervariable region variations) were comprehensively and systematically assessed for polymorphism detections, further employed to dissect the population backgrounds in the Yugu ethnic group from Gansu province (Yugu) and Han population from the Inner Mongolia Autonomous Region (NMH) of China. The elevated efficiencies of the marker set in separating full sibling and challenging half sibling determination cases in parentage tests (iiSNPs), as well as predicting ancestry origins of unknown individuals from at least four continental populations (aiSNPs) and providing informative characteristic-related clues for Chinese populations (piSNPs) are highlighted in the present study. To sum up, different sets of DNA markers revealed sufficient effciencies to serve as promising tools in forensic applications. Genetic insights from the perspectives of autosomal DNA, Y chromosomal DNA, and mtDNA variations yielded that the Yugu ethnic group was genetically close related to the Han populations of the northern region. But we admit that more reference populations (like Mongolian, Tibetan, Hui, and Tu) should be incorporated to gain a refined genetic background landscape of the Yugu group in future studies.

Forensic characterization of 124 SNPs in the central Indian population using precision ID Identity Panel through next-generation sequencing

With the advent of next-generation sequencing technology, SNP markers are being explored as a useful alternative to conventional capillary electrophoresis-based STR typing. Low mutation rate and short-sized amplicons are added advantages of SNP markers over the STRs. However, to achieve a sufficient level of discrimination among individuals, a higher number of SNPs need to be characterized simultaneously. Hence, the NGS technique is highly useful to analyze a sufficiently higher number of SNPs simultaneously. Though the technique is in its nascent stage, an attempt has been made to assess its usability in the central Indian population by analyzing 124 SNPs (90 autosomal and 34 Y-chromosome) in 95 individuals. Various quality parameters such as locus balance, locus strand balance, heterozygosity balance, and noise level showed a good quality sequence obtained from the Ion GeneStudio S5 instrument. Obtained frequency of SNP alleles ranged from 0.001 to 0.377 in autosomal SNPs. rs9951171 was found to be the most informative SNP in the studied population with the highest PD and lowest MP value. The cumulative MP of 90 SNPs was found to be 4.76698 × 10^-37. Analysis of 34 Y-chromosome SNPs reveals 11 unique haplogroups in 54 male samples with R1a1 as the most frequent haplogroup found in 22.22% of samples. Interpopulation comparison by FST analysis, PCA plot, and STRUCTURE analysis showed genetic stratification of the studied population suggesting the utility of SNP markers present in the Precision ID Identity Panel for forensic demands of the Indian population.

Comprehensive Insights Into Forensic Features and Genetic Background of Chinese Northwest Hui Group Using Six Distinct Categories of 231 Molecular Markers

The Hui minority is predominantly composed of Chinese-speaking Islamic adherents distributed throughout China, of which the individuals are mainly concentrated in Northwest China. In the present study, we employed the length and sequence polymorphisms-based typing system of 231 molecular markers, i.e., amelogenin, 22 phenotypic-informative single nucleotide polymorphisms (PISNPs), 94 identity-informative single nucleotide polymorphisms (IISNPs), 24 Y-chromosomal short tandem repeats (Y-STRs), 56 ancestry-informative single nucleotide polymorphisms (AISNPs), 7 X-chromosomal short tandem repeats (X-STRs), and 27 autosomal short tandem repeats (A-STRs), into 90 unrelated male individuals from the Chinese Northwest Hui group to comprehensively explore its forensic characteristics and genetic background. Total of 451 length-based and 652 sequence-based distinct alleles were identified from 58 short tandem repeats (STRs) in 90 unrelated Northwest Hui individuals, denoting that the sequence-based genetic markers could pronouncedly provide more genetic information than length-based markers. The forensic characteristics and efficiencies of STRs and IISNPs were estimated, both of which externalized high polymorphisms in the Northwest Hui group and could be further utilized in forensic investigations. No significant departure from the Hardy-Weinberg equilibrium (HWE) expectation was observed after the Bonferroni correction. Additionally, four group sets of reference population data were exploited to dissect the genetic background of the Northwest Hui group separately from different perspectives, which contained 26 populations for 93 IISNPs, 58 populations for 17 Y-STRs, 26 populations for 55 AISNPs (raw data), and 109 populations for 55 AISNPs (allele frequencies). As a result, the analyses based on the Y-STRs indicated that the Northwest Hui group primarily exhibited intimate genetic relationships with reference Hui groups from Chinese different regions except for the Sichuan Hui group and secondarily displayed close genetic relationships with populations from Central and West Asia, as well as several Chinese groups. However, the AISNP analyses demonstrated that the Northwest Hui group shared more intimate relationships with current East Asian populations apart from reference Hui group, harboring the large proportion of ancestral component contributed by East Asia.

A novel computational strategy to predict the value of the evidence in the SNP-based forensic mixtures

This study introduces a methodology for inferring the weight of the evidence (WoE) in the single nucleotide polymorphism (SNP)-typed DNA mixtures of forensic interest. First, we redefined some algebraic formulae to approach the semi-continuous calculation of likelihoods and likelihood ratios (LRs). To address the allelic dropouts, a peak height ratio index (“h,” an index of heterozygous state plausibility) was incorporated into semi-continuous formulae to act as a proxy for the “split-drop” model of calculation. Second, the original ratio at which a person of interest (POI) has entered into the mixture was inferred by evaluating the DNA amounts conferred by unique genotypes to any possible permutation of any locus of the typing protocol (unique genotypes are genotypes that appear just once in the relevant permutation). We compared this expected ratio (MR_ex) to all the mixing ratios emerging at all other permutations of the mixture (MR_obs) using several (1 - χ²) tests to evaluate the probability of each permutation to exist in the mixture according to quantitative criteria. At the level of each permutation state, we multiplied the (1 - χ²) value to the genotype frequencies and the h index. All the products of all the permutation states were finally summed to give a likelihood value that accounts for three independent properties of the mixtures. Owing to the (1 - χ²) index and the h index, this approach qualifies as a fully continuous methodology of LR calculation. We compared the MRs and LRs emerging from our methodology to those generated by the EuroForMix software ver. 3.0.3. When the true contributors were tested as POIs, our procedure generated highly discriminant LRs that, unlike EuroForMix, never overcame the corresponding single-source LRs. When false contributors were tested as POIs, we obtained a much lower LR value than that from EuroForMix. These two findings indicate that our computational method is more reliable and realistic than EuroForMix.

Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia

BACKGROUND

Considering the clinical and genetic characteristics, acute lymphoblastic leukemia (ALL) is a rather heterogeneous hematological neoplasm for which current standard diagnostics require various analyses encompassing morphology, immunophenotyping, cytogenetics, and molecular analysis of gene fusions and mutations. Hence, it would be desirable to rely on a technique and an analytical workflow that allows the simultaneous analysis and identification of all the genetic alterations in a single approach. Moreover, based on the results with standard methods, a significant amount of patients have no established abnormalities and hence, cannot further be stratified.

METHODS

We performed WTS and WGS in 279 acute lymphoblastic leukemia (ALL) patients (B-cell: n = 211; T-cell: n = 68) to assess the accuracy of WTS, to detect relevant genetic markers, and to classify ALL patients.

RESULTS

DNA and RNA-based genotyping was used to ensure correct WTS-WGS pairing. Gene expression analysis reliably assigned samples to the B Cell Precursor (BCP)-ALL or the T-ALL group. Subclassification of BCP-ALL samples was done progressively, assessing first the presence of chromosomal rearrangements by the means of fusion detection. Compared to the standard methods, 97% of the recurrent risk-stratifying fusions could be identified by WTS, assigning 76 samples to their respective entities. Additionally, read-through fusions (indicative of CDKN2A and RB1 gene deletions) were recurrently detected in the cohort along with 57 putative novel fusions, with yet untouched diagnostic potentials. Next, copy number variations were inferred from WTS data to identify relevant ploidy groups, classifying an additional of 31 samples. Lastly, gene expression profiling detected a BCR-ABL1-like signature in 27% of the remaining samples.

CONCLUSION

As a single assay, WTS allowed a precise genetic classification for the majority of BCP-ALL patients, and is superior to conventional methods in the cases which lack entity defining genetic abnormalities.

Elucidation of familial relationships using hair shaft proteomics

This study examines the potential of hair shaft proteomic analysis to delineate genetic relatedness. Proteomic profiling and amino acid sequence analysis provide information for quantitative and statistically-based analysis of individualization and sample similarity. Protein expression levels are a function of cell-specific transcriptional and translational programs. These programs are greatly influenced by an individual's genetic background, and are therefore influenced by familial relatedness as well as ancestry and genetic disease. Proteomic profiles should therefore be more similar among related individuals than unrelated individuals. Likewise, profiles of genetically variant peptides that contain single amino acid polymorphisms, the result of non-synonymous SNP alleles, should behave similarly. The proteomically-inferred SNP alleles should also provide a basis for calculation of combined paternity and sibship indices. We test these hypotheses using matching proteomic and genetic datasets from a family of two adults and four siblings, one of which has a genetic condition that perturbs hair structure and properties. We demonstrate that related individuals, compared to those who are unrelated, have more similar proteomic profiles, profiles of genetically variant peptides and higher combined paternity indices and combined sibship indices. This study builds on previous analyses of hair shaft protein profiling and genetically variant peptide profiles in different real-world scenarios including different human hair shaft body locations and pigmentation status. It also validates the inclusion of proteomic information with other biomolecular substrates in forensic hair shaft analysis, including mitochondrial and nuclear DNA.

Establishment and application of a novel method based on single nucleotide polymorphism analysis for detecting β-globin gene cluster deletions

β-Globin gene mutations reduce or terminate the production of beta globin chains, of which approximately 10% are large deletions within the β-globin gene cluster. Because gene deletion leads to loss of heterozygosity at single nucleotide polymorphism (SNP), a novel method for detecting β-globin gene cluster deletions based on SNP heterozygosity analysis was established in this study. The location range of SNPs was selected according to the breakpoint of β-globin gene cluster deletions. SNPs were screened using bioinformatics analysis and population sequencing data. A novel method which enables genotyping of multiplex SNPs based on tetra-primer ARMS-PCR was designed and optimized. Forty clinical samples were tested in parallel by this method and MLPA to verify the performance of this method for detecting β-globin gene cluster deletion. Six informative SNPs were obtained, achieving heterozygote coverage of 93.3% in normal individuals. Genotyping of six SNPs were successfully integrated into two multiplex tetra-primer ARMS-PCR reactions. The sensitivity, specificity, positive predictive value and negative predictive value of the method for detecting β-globin gene cluster deletion were 100%, 96.30%, 92.86%, and 100%, respectively. This is a simple, cost-effective and novel method for detecting β-globin gene cluster deletions, which may be suitable for use in combination with MLPA for thalassemia molecular testing.

Authentication, characterization and contamination detection of cell lines, xenografts and organoids by barcode deep NGS sequencing

Misidentification and contamination of biobank samples (e.g. cell lines) have plagued biomedical research. Short tandem repeat (STR) and single-nucleotide polymorphism assays are widely used to authenticate biosamples and detect contamination, but with insufficient sensitivity at 5–10% and 3–5%, respectively. Here, we describe a deep NGS-based method with significantly higher sensitivity (≤1%). It can be used to authenticate human and mouse cell lines, xenografts and organoids. It can also reliably identify and quantify contamination of human cell line samples, contaminated with only small amount of other cell samples; detect and quantify species-specific components in human–mouse mixed samples (e.g. xenografts) with 0.1% sensitivity; detect mycoplasma contamination; and infer population structure and gender of human samples. By adopting DNA barcoding technology, we are able to profile 100–200 samples in a single run at per-sample cost comparable to conventional STR assays, providing a truly high-throughput and low-cost assay for building and maintaining high-quality biobanks.

Comparative analysis of five different methods to design a breed-specific SNP panel for cattle

Single nucleotide polymorphisms (SNPs) have now replaced microsatellite markers in several species for various genetic investigations like parentage assignment, genetic breed composition, assessment for individuality and, most popularly, as a useful tool in genomic selection. However, such a resource, which can offer to assist breed identification in a cost-effective manner is still not explored in cattle breeding programs. In our study, we have tried to describe methods for reducing the number of SNPs to develop a breed-specific panel. We have used SNP data from Dryad open public access repository. Starting from a global dataset of 178 animals belonging to 10 different breeds, we selected five panels each comprising of similar number of SNPs using different methods i.e., Delta, Pairwise Wright's F_ST, informativeness for assignment, frequent item feature selection (FIFS) and minor allele frequency-linkage disequilibrium (MAF-LD) based method. MAF-LD based method has been recently developed by us for construction of breed-specific SNP panels. The STRUCTURE software analysis of MAF-LD based method showed appropriate clustering in comparison to other panels. Later, the panel of 591 breed-specific SNPs was called to their respective breeds using Venny 2.1.0 and UGent web tools software. Breed-specific SNPs were later annotated by using various Bioinformatics softwares.

Identity determination in diagnostic surgical pathology

From a technical perspective, specimen identity determination in surgical pathology over the last several decades has primarily focused on analysis of repetitive DNA sequences, specifically microsatellite repeats. However, a number of techniques have recently been developed that have similar, if not greater, utility in surgical pathology, most notably analysis of single nucleotide polymorphism (SNPs) and gene panels by next generation sequencing (NGS). For cases with an extremely limited sample or a degraded sample, sequence analysis of mitochondrial DNA continues to be the method of choice. From a diagnostic perspective, interest in identity determination in surgical pathology is usually centered on resolving issues of specimen provenance due to specimen labeling/accessioning deficiencies and possible contamination, but is also frequently performed in cases for which the patient's clinical course following definitive therapy is remarkably atypical, in cases of an unexpected diagnosis, and by patient request for "peace of mind". However, the methods used for identity determination have a much broader range of applications in surgical pathology beyond tissue provenance analysis. The methods can be used to provide ancillary information for cases in which the histomorphology is not definitively diagnostic, as for example for tumors that have a virtually identical microscopic appearance but for which the differential diagnosis includes synchronous/metachronous tumors versus a metastasis, and for the diagnosis of hydropic early gestations versus hydatidiform molar pregnancies. The methods also have utility in several other clinical settings, for example to rule out a donor-transmitted malignancy in a transplant recipient, to monitor bone marrow transplant engraftment, and to evaluate natural chimerism.

Big data in forensic genetics

The potential and difficulties of the application of genome wide data in forensics are analyzed. We argue that, besides statistical, computational, ethical, economic and technical validation problems, the state of the art of population genetics theory is insufficient to deal with the forensic use of this type of data. In order to keep the current standards of quantifying and reporting genetic evidence, namely in kinship analyses and identification, substantial improvement in the theoretical framework should be reached, since to obtain genome-wide results is to provide the experts with data that they cannot quantify the corresponding evidentiary value. Therefore, while a satisfactory, generalized theoretical and biostatistical modelling is not achieved, it may well be wiser to improve the already established approaches to a limited, pre-defined number of validated genetic markers, amenable to a consensual handling and reporting. Whole genome population analyses will prove extremely useful in selecting the best suited and most efficient of those markers.