AQME: A forensic mitochondrial DNA analysis tool for next-generation sequencing data

Mitochondrial point heteroplasmy: insights from deep-sequencing of human replicate samples

BACKGROUND

Human mitochondrial heteroplasmy is an extensively investigated phenomenon in the context of medical diagnostics, forensic identification and molecular evolution. However, technical limitations of high-throughput sequencing hinder reliable determination of point heteroplasmies (PHPs) with minor allele frequencies (MAFs) within the noise threshold.

RESULTS

To investigate the PHP landscape at an MAF threshold down to 0.1%, we sequenced whole mitochondrial genomes at approximately 7.700x coverage, in multiple technical and biological replicates of longitudinal blood and buccal swab samples from 11 human donors (159 libraries in total). The results obtained by two independent sequencing platforms and bioinformatics pipelines indicate distinctive PHP patterns below and above the 1% MAF cut-off. We found a high inter-individual prevalence of low-level PHPs (MAF < 1%) at polymorphic positions of the mitochondrial DNA control region (CR), their tissue preference, and a tissue-specific minor allele linkage. We also established the position-dependent potential of minor allele expansion in PHPs, and short-term PHP instability in a mitotically active tissue. We demonstrate that the increase in sensitivity of PHP detection to minor allele frequencies below 1% within a robust experimental and analytical pipeline, provides new information with potential applicative value.

CONCLUSIONS

Our findings reliably show different mutational loads between tissues at sub-1% allele frequencies, which may serve as an informative medical biomarker of time-dependent, tissue-specific mutational burden, or help discriminate forensically relevant tissues in a single person, close maternal relatives or unrelated individuals of similar phylogenetic background.

Review: Computational analysis of human skeletal remains in ancient DNA and forensic genetics

Degraded DNA is used to answer questions in the fields of ancient DNA (aDNA) and forensic genetics. While aDNA studies typically center around human evolution and past history, and forensic genetics is often more concerned with identifying a specific individual, scientists in both fields face similar challenges. The overlap in source material has prompted periodic discussions and studies on the advantages of collaboration between fields toward mutually beneficial methodological advancements. However, most have been centered around wet laboratory methods (sampling, DNA extraction, library preparation, etc.). In this review, we focus on the computational side of the analytical workflow. We discuss limitations and considerations to consider when working with degraded DNA. We hope this review provides a framework to researchers new to computational workflows for how to think about analyzing highly degraded DNA and prompts an increase of collaboration between the forensic genetics and aDNA fields.

Complete Mitochondrial DNA Genome Variation in the Swedish Population

The development of complete mitochondrial genome (mitogenome) reference data for inclusion in publicly available population databases is currently underway, and the generation of more high-quality mitogenomes will only enhance the statistical power of this forensically useful locus. To characterize mitogenome variation in Sweden, the mitochondrial DNA (mtDNA) reads from the SweGen whole genome sequencing (WGS) dataset were analyzed. To overcome the interference from low-frequency nuclear mtDNA segments (NUMTs), a 10% variant frequency threshold was applied for the analysis. In total, 934 forensic-quality mitogenome haplotypes were characterized. Almost 45% of the SweGen haplotypes belonged to haplogroup H. Nearly all mitogenome haplotypes (99.1%) were assigned to European haplogroups, which was expected based on previous mtDNA studies of the Swedish population. There were signature northern Swedish and Finnish haplogroups observed in the dataset (e.g., U5b1, W1a), consistent with the nuclear DNA analyses of the SweGen data. The complete mitogenome analysis resulted in high haplotype diversity (0.9996) with a random match probability of 0.15%. Overall, the SweGen mitogenomes provide a large mtDNA reference dataset for the Swedish population and also contribute to the effort to estimate global mitogenome haplotype frequencies.

Evaluating the Usefulness of Human DNA Quantification to Predict DNA Profiling Success of Historical Bone Samples

This study assessed the usefulness of DNA quantification to predict the success of historical samples when analyzing SNPs, mtDNA, and STR targets. Thirty burials from six historical contexts were utilized, ranging in age from 80 to 800 years postmortem. Samples underwent library preparation and hybridization capture with two bait panels (FORCE and mitogenome), and STR typing (autosomal STR and Y-STR). All 30 samples generated small (~80 bp) autosomal DNA target qPCR results, despite mean mappable fragments ranging from 55-125 bp. The qPCR results were positively correlated with DNA profiling success. Samples with human DNA inputs as low as 100 pg resulted in ≥80% FORCE SNPs at 10X coverage. All 30 samples resulted in mitogenome coverage ≥100X despite low human DNA input (as low as 1 pg). With PowerPlex Fusion, ≥30 pg human DNA input resulted in >40% of auSTR loci. At least 59% of Y-STR loci were recovered with Y-target qPCR-based inputs of ≥24 pg. The results also indicate that human DNA quantity is a better predictor of success than the ratio of human to exogenous DNA. Accurate quantification with qPCR is feasible for historical bone samples, allowing for the screening of extracts to predict the success of DNA profiling.

Bioinformatics approaches and big data analytics opportunities in improving fisheries and aquaculture

Aquaculture has witnessed an excellent growth rate during the last two decades and offers huge potential to provide nutritional as well as livelihood security. Genomic research has contributed significantly toward the development of beneficial technologies for aquaculture. The existing high throughput technologies like next-generation technologies generate oceanic data which requires extensive analysis using appropriate tools. Bioinformatics is a rapidly evolving science that involves integrating gene based information and computational technology to produce new knowledge for the benefit of aquaculture. Bioinformatics provides new opportunities as well as challenges for information and data processing in new generation aquaculture. Rapid technical advancements have opened up a world of possibilities for using current genomics to improve aquaculture performance. Understanding the genes that govern economically relevant characteristics, necessitates a significant amount of additional research. The various dimensions of data sources includes next-generation DNA sequencing, protein sequencing, RNA sequencing gene expression profiles, metabolic pathways, molecular markers, and so on. Appropriate bioinformatics tools are developed to mine the biologically relevant and commercially useful results. The purpose of this scoping review is to present various arms of diverse bioinformatics tools with special emphasis on practical translation to the aquaculture industry.

The Value of Whole-Genome Sequencing for Mitochondrial DNA Population Studies: Strategies and Criteria for Extracting High-Quality Mitogenome Haplotypes

Whole-genome sequencing (WGS) data present a readily available resource for mitochondrial genome (mitogenome) haplotypes that can be utilized for genetics research including population studies. However, the reconstruction of the mitogenome is complicated by nuclear mitochondrial DNA (mtDNA) segments (NUMTs) that co-align with the mtDNA sequences and mimic authentic heteroplasmy. Two minimum variant detection thresholds, 5% and 10%, were assessed for the ability to produce authentic mitogenome haplotypes from a previously generated WGS dataset. Variants associated with NUMTs were detected in the mtDNA alignments for 91 of 917 (~8%) Swedish samples when the 5% frequency threshold was applied. The 413 observed NUMT variants were predominantly detected in two regions (nps 12,612–13,105 and 16,390–16,527), which were consistent with previously documented NUMTs. The number of NUMT variants was reduced by ~97% (400) using a 10% frequency threshold. Furthermore, the 5% frequency data were inconsistent with a platinum-quality mitogenome dataset with respect to observed heteroplasmy. These analyses illustrate that a 10% variant detection threshold may be necessary to ensure the generation of reliable mitogenome haplotypes from WGS data resources.

Ancient DNA Methods Improve Forensic DNA Profiling of Korean War and World War II Unknowns

The integration of massively parallel sequencing (MPS) technology into forensic casework has been of particular benefit to the identification of unknown military service members. However, highly degraded or chemically treated skeletal remains often fail to provide usable DNA profiles, even with sensitive mitochondrial (mt) DNA capture and MPS methods. In parallel, the ancient DNA field has developed workflows specifically for degraded DNA, resulting in the successful recovery of nuclear DNA and mtDNA from skeletal remains as well as sediment over 100,000 years old. In this study we use a set of disinterred skeletal remains from the Korean War and World War II to test if ancient DNA extraction and library preparation methods improve forensic DNA profiling. We identified an ancient DNA extraction protocol that resulted in the recovery of significantly more human mtDNA fragments than protocols previously used in casework. In addition, utilizing single-stranded rather than double-stranded library preparation resulted in increased attainment of reportable mtDNA profiles. This study emphasizes that the combination of ancient DNA extraction and library preparation methods evaluated here increases the success rate of DNA profiling, and likelihood of identifying historical remains.

An Introductory Overview of Open-Source and Commercial Software Options for the Analysis of Forensic Sequencing Data

The top challenges of adopting new methods to forensic DNA analysis in routine laboratories are often the capital investment and the expertise required to implement and validate such methods locally. In the case of next-generation sequencing, in the last decade, several specifically forensic commercial options became available, offering reliable and validated solutions. Despite this, the readily available expertise to analyze, interpret and understand such data is still perceived to be lagging behind. This review gives an introductory overview for the forensic scientists who are at the beginning of their journey with implementing next-generation sequencing locally and because most in the field do not have a bioinformatics background may find it difficult to navigate the new terms and analysis options available. The currently available open-source and commercial software for forensic sequencing data analysis are summarized here to provide an accessible starting point for those fairly new to the forensic application of massively parallel sequencing.

Platinum-Quality Mitogenome Haplotypes from United States Populations

A total of 1327 platinum-quality mitochondrial DNA haplotypes from United States (U.S.) populations were generated using a robust, semi-automated next-generation sequencing (NGS) workflow with rigorous quality control (QC). The laboratory workflow involved long-range PCR to minimize the co-amplification of nuclear mitochondrial DNA segments (NUMTs), PCR-free library preparation to reduce amplification bias, and high-coverage Illumina MiSeq sequencing to produce an average per-sample read depth of 1000 × for low-frequency (5%) variant detection. Point heteroplasmies below 10% frequency were confirmed through replicate amplification, and length heteroplasmy was quantitatively assessed using a custom read count analysis tool. Data analysis involved a redundant, dual-analyst review to minimize errors in haplotype reporting with additional QC checks performed by EMPOP. Applying these methods, eight sample sets were processed from five U.S. metapopulations (African American, Caucasian, Hispanic, Asian American, and Native American) corresponding to self-reported identity at the time of sample collection. Population analyses (e.g., haplotype frequencies, random match probabilities, and genetic distance estimates) were performed to evaluate the eight datasets, with over 95% of haplotypes unique per dataset. The platinum-quality mitogenome haplotypes presented in this study will enable forensic statistical calculations and thereby support the usage of mitogenome sequencing in forensic laboratories.

Searching the undetected mtDNA variants in forensic MPS data

The efficiency of MPS in forensic mtDNA analysis has been thoroughly proven, although a reliable and well established data evaluation still remains a critical point. Numerous bioinformatics tools have been developed, but most of them require specific operating systems and high costs, while free open-source programs with user-friendly interfaces are few. In this study, 43 full mtGenomes were sequenced using the Ion Personal Genome Machine™ (PGM™) System and analyzed utilizing the plug-in Variant Caller (TVC) of the Ion Torrent Software Suite and the mtDNA-Server (mDS), a free web-based mitochondrial analysis tool for MPS data. The outcomes of these two different analysis tools were compared to variants noted after manual inspection of the aligned reads performed using Integrative Genomics Viewer (IGV). The comparison highlighted the presence of thirty-nine discordant variant calls, which were resolved by Sanger sequencing that confirmed the presence of all variants, except for 7 deletions. The combined adoption of IGV and Sanger type sequencing confirmatory steps, in addition of TVC and mDS analysis, resulted in a more accurate variants assignment with the detection of 32 additional true polymorphisms, which were noted in the final dataset. Regarding the heteroplasmy issue, out of a total of thirty heteroplasmic variants, twenty-eight were detected by the TVC, while the mDS detected twenty-two. Overall, none of the used bioinformatics tools were the perfect choice and a secondary analysis with an expert's opinion in complete mtGenome MPS data evaluation is still required in forensic genetic analysis.

Pathogenic Variant Filtering for Mitochondrial Genome Haplotype Reporting

Given the enhanced discriminatory power of the mitochondrial DNA (mtDNA) genome (mitogenome) over the commonly sequenced control region (CR) portion, the scientific merit of mitogenome sequencing is generally accepted. However, many laboratories remain beholden to CR sequencing due to privacy policies and legal requirements restricting the use of disease information or coding region (codR) information. In this report, we present an approach to obviate the reporting of sensitive codR data in forensic haplotypes. We consulted the MitoMap database to identify 92 mtDNA codR variants with confirmed pathogenicity. We determined the frequencies of these pathogenic variants in literature-quality and forensic-quality databases to be very low, at 1.2% and 0.36%, respectively. The observed effect of pathogenic variant filtering on random match statistics in 2488 forensic-quality mitogenome haplotypes from four populations was nil. We propose that pathogenic variant filtering should be incorporated into variant calling algorithms for mitogenome haplotype reporting to maximize the discriminatory power of the locus while minimizing the reveal of sensitive genetic information.

A Forensic Genomics Approach for the Identification of Sister Marija Crucifiksa Kozulić

Sister Marija Krucifiksa Kozulić (1852–1922) was a Croatian nun who is in consideration for beatification by the Vatican, which is facilitated by the identification of her 20th-century remains. Sister Marija was buried in a tomb in Rijeka, Croatia, along with other nuns including her biological sister, Tereza Kozulić (1861–1933). When the remains were exhumed in 2011, they were found in a deteriorated state and commingled with several other sets of remains. Thus, mitochondrial genome sequencing of the long bones was performed to sort the remains by mitochondrial haplotype. Two similar but unique haplotypes belonging to haplogroup H1bu were identified, and samples from these bones were subjected to autosomal short tandem repeat (STR) and single nucleotide polymorphism (SNP) sequencing. Although only partial profiles were obtained, the data were sufficient for kinship analysis with the profile of a paternal niece of Sister Marija (Fides Kozulić). The data indicate that it is 574,195-fold more likely that the two sets of skeletal remains represent 2nd-degree relatives of Fides than sisters who are unrelated to Fides. Although it is impossible to discern which set of remains belongs to Marija and which belongs to Tereza, forensic genomics methods have enabled identification of the sisters.

The lot-to-lot variability in the mitochondrial genome of controls

Current research in the biomedical field has illustrated how cell lines used as reference standards can change over time and, more importantly, can affect research and diagnostic results obtained from these cell lines. With the use of increasingly sensitive and highly resolving technologies (e.g., massively parallel sequencing), forensic scientists must be aware of and account for potential variability in the cell lines used as controls in their validation studies and day-to-day casework. In this study, multiple lot numbers from four commonly-used control cell line DNAs were sequenced with massively parallel sequencing on the Ion S5. The variability among these different lots was evaluated, and the effect on forensic laboratory work discussed.

Validation of NGS for mitochondrial DNA casework at the FBI Laboratory

As a first step towards integrating next generation sequencing (NGS) technology into the FBI Laboratory's operational casework, the PowerSeq™ CRM Nested System, an NGS-based mitochondrial DNA (mtDNA) control region assay, was developmentally and internally validated. The validation studies were conducted in accordance with the Scientific Working Group on DNA Analysis Methods (SWGDAM) Validation Guidelines for Forensic DNA Analysis Methods, and the FBI's Quality Assurance Standards (QAS) for Forensic DNA Testing Laboratories. The assay was shown to be highly reproducible, with variant frequencies across intra and inter-run replicates of the same sample differing, on average, by just 0.3% for substitutions and point heteroplasmies and 1.5% for insertions and deletions. The assay was also shown to be extremely sensitive, yielding complete control region sequence data from as few as 2000 copies of mtDNA. This is a more than 20-fold increase in sensitivity when compared to the FBI Laboratory's current Sanger sequencing-based protocols and, based on mtDNA quantitation values of samples routinely encountered in mtDNA casework, suggests that the percentage of questioned samples from which full control region data can be recovered will increase from our current 20% to approximately 90% success with NGS technology. In addition, the assay requires on average only 30% of the extract volume typically required to develop control region profiles from degraded samples via Sanger sequencing. Overall, these studies establish the reliability of the PowerSeq™ CRM Nested System for accurate mtDNA control region typing and can serve as a model for laboratories seeking to validate NGS protocols for forensic mtDNA analysis.

Developmental validation of a Nextera XT mitogenome Illumina MiSeq sequencing method for high-quality samples

Generating mitochondrial genome (mitogenome) data from reference samples in a rapid and efficient manner is critical to harnessing the greater power of discrimination of the entire mitochondrial DNA (mtDNA) marker. The method of long-range target enrichment, Nextera XT library preparation, and Illumina sequencing on the MiSeq is a well-established technique for generating mitogenome data from high-quality samples. To this end, a validation was conducted for this mitogenome method processing up to 24 samples simultaneously along with analysis in the CLC Genomics Workbench and utilizing the AQME (AFDIL-QIAGEN mtDNA Expert) tool to generate forensic profiles. This validation followed the Federal Bureau of Investigation's Quality Assurance Standards (QAS) for forensic DNA testing laboratories and the Scientific Working Group on DNA Analysis Methods (SWGDAM) validation guidelines. The evaluation of control DNA, non-probative samples, blank controls, mixtures, and nonhuman samples demonstrated the validity of this method. Specifically, the sensitivity was established at ≥25 pg of nuclear DNA input for accurate mitogenome profile generation. Unreproducible low-level variants were observed in samples with low amplicon yields. Further, variant quality was shown to be a useful metric for identifying sequencing error and crosstalk. Success of this method was demonstrated with a variety of reference sample substrates and extract types. These studies further demonstrate the advantages of using NGS techniques by highlighting the quantitative nature of heteroplasmy detection. The results presented herein from more than 175 samples processed in ten sequencing runs, show this mitogenome sequencing method and analysis strategy to be valid for the generation of reference data.

A review of bioinformatic methods for forensic DNA analyses

Short tandem repeats, single nucleotide polymorphisms, and whole mitochondrial analyses are three classes of markers which will play an important role in the future of forensic DNA typing. The arrival of massively parallel sequencing platforms in forensic science reveals new information such as insights into the complexity and variability of the markers that were previously unseen, along with amounts of data too immense for analyses by manual means. Along with the sequencing chemistries employed, bioinformatic methods are required to process and interpret this new and extensive data. As more is learnt about the use of these new technologies for forensic applications, development and standardization of efficient, favourable tools for each stage of data processing is being carried out, and faster, more accurate methods that improve on the original approaches have been developed. As forensic laboratories search for the optimal pipeline of tools, sequencer manufacturers have incorporated pipelines into sequencer software to make analyses convenient. This review explores the current state of bioinformatic methods and tools used for the analyses of forensic markers sequenced on the massively parallel sequencing (MPS) platforms currently most widely used.