Targeted single molecule mutation detection with massively parallel sequencing

MADDD-seq, a novel massively parallel sequencing tool for simultaneous detection of DNA damage and mutations

Our genome is exposed to a wide variety of DNA-damaging agents. If left unrepaired, this damage can be converted into mutations that promote carcinogenesis or the development of genetically inherited diseases. As a result, researchers and clinicians require tools that can detect DNA damage and mutations with exceptional sensitivity. In this study, we describe a massively parallel sequencing tool termed Mutation And DNA Damage Detection-seq (MADDD-seq) that is capable of detecting O6-methyl guanine lesions and mutations simultaneously, with a single assay. To illustrate the dual capabilities of MADDD-seq, we treated WT and DNA repair deficient yeast cells with the DNA-damaging agent MNNG and tracked DNA lesions and mutations over a 24-h time period. This approach allowed us to identify thousands of DNA adducts and mutations in a single sequencing run and gain deep insight into the kinetics of DNA repair and mutagenesis.

Chasing Sequencing Perfection: Marching Toward Higher Accuracy and Lower Costs

Next-generation sequencing (NGS), represented by Illumina platforms, has been an essential cornerstone of basic and applied research. However, the sequencing error rate of 1 per 1000 bp (10-3) represents a serious hurdle for research areas focusing on rare mutations, such as somatic mosaicism or microbe heterogeneity. By examining the high-fidelity sequencing methods developed in the past decade, we summarized three major factors underlying errors and the corresponding 12 strategies mitigating these errors. We then proposed a novel framework to classify 11 preexisting representative methods according to the corresponding combinatory strategies and identified three trends that emerged during methodological developments. We further extended this analysis to eight long-read sequencing methods, emphasizing error reduction strategies. Finally, we suggest two promising future directions that could achieve comparable or even higher accuracy with lower costs in both NGS and long-read sequencing.

Principles of digital sequencing using unique molecular identifiers

Massively parallel sequencing technologies have long been used in both basic research and clinical routine. The recent introduction of digital sequencing has made previously challenging applications possible by significantly improving sensitivity and specificity to now allow detection of rare sequence variants, even at single molecule level. Digital sequencing utilizes unique molecular identifiers (UMIs) to minimize sequencing-induced errors and quantification biases. Here, we discuss the principles of UMIs and how they are used in digital sequencing. We outline the properties of different UMI types and the consequences of various UMI approaches in relation to experimental protocols and bioinformatics. Finally, we describe how digital sequencing can be applied in specific research fields, focusing on cancer management where it can be used in screening of asymptomatic individuals, diagnosis, treatment prediction, prognostication, monitoring treatment efficacy and early detection of treatment resistance as well as relapse.

A critical spotlight on the paradigms of FFPE-DNA sequencing

In the late 19th century, formalin fixation with paraffin-embedding (FFPE) of tissues was developed as a fixation and conservation method and is still used to this day in routine clinical and pathological practice. The implementation of state-of-the-art nucleic acid sequencing technologies has sparked much interest for using historical FFPE samples stored in biobanks as they hold promise in extracting new information from these valuable samples. However, formalin fixation chemically modifies DNA, which potentially leads to incorrect sequences or misinterpretations in downstream processing and data analysis. Many publications have concentrated on one type of DNA damage, but few have addressed the complete spectrum of FFPE-DNA damage. Here, we review mitigation strategies in (I) pre-analytical sample quality control, (II) DNA repair treatments, (III) analytical sample preparation and (IV) bioinformatic analysis of FFPE-DNA. We then provide recommendations that are tested and illustrated with DNA from 13-year-old liver specimens, one FFPE preserved and one fresh frozen, applying target-enriched sequencing. Thus, we show how DNA damage can be compensated, even when using low quantities (50 ng) of fragmented FFPE-DNA (DNA integrity number 2.0) that cannot be amplified well (Q129 bp/Q41 bp = 5%). Finally, we provide a checklist called 'ERROR-FFPE-DNA' that summarises recommendations for the minimal information in publications required for assessing fitness-for-purpose and inter-study comparison when using FFPE samples.

Simultaneous analysis of mutations and methylations in circulating cell-free DNA for hepatocellular carcinoma detection

Cell-free DNA (cfDNA)-based liquid biopsy is a promising approach for the early detection of cancer. A major hurdle is the limited yield of cfDNA from one blood draw, limiting the use of most samples to one test of either mutation or methylation. Here, we develop a technology, Mutation Capsule Plus (MCP), which enables multiplex profiling of one cfDNA sample, including simultaneous detection of genetic and epigenetic alterations and genome-wide discovery of methylation markers. With this technology, we performed de novo screening of methylation markers on cfDNA samples from 30 hepatocellular carcinoma (HCC) cases and 30 non-HCC controls. The methylation markers enriched in HCC cfDNA were further profiled in parallel with a panel of mutations on a training cohort of 60 HCC and 60 non-HCC cases, resulting in an HCC detection model. We validated the model in an independent retrospective cohort with 58 HCC and 198 non-HCC cases and got 90% sensitivity with 94% specificity. Furthermore, we applied the model to a prospective cohort of 311 asymptomatic hepatitis B virus carriers with normal liver ultrasonography and serum AFP concentration. The model detected four of the five HCC cases in the cohort, showing 80% sensitivity and 94% specificity. These findings demonstrate that the MCP technology has potential for the discovery and validation of multiomics biomarkers for the noninvasive detection of cancer. This study also provides a comprehensive database of genetic and epigenetic alterations in the cfDNA of a large cohort of HCC cases and high-risk non-HCC individuals.

Pre-PCR Mutation-Enrichment Methods for Liquid Biopsy Applications

Liquid biopsy is having a remarkable impact on healthcare- and disease-management in the context of personalized medicine. Circulating free DNA (cfDNA) is one of the most instructive liquid-biopsy-based biomarkers and harbors valuable information for diagnostic, predictive, and prognostic purposes. When it comes to cancer, circulating DNA from the tumor (ctDNA) has a wide range of applications, from early cancer detection to the early detection of relapse or drug resistance, and the tracking of the dynamic genomic make-up of tumor cells. However, the detection of ctDNA remains technically challenging, due, in part, to the low frequency of ctDNA among excessive circulating cfDNA originating from normal tissues. During the past three decades, mutation-enrichment methods have emerged to boost sensitivity and enable facile detection of low-level mutations. Although most developed techniques apply mutation enrichment during or following initial PCR, there are a few techniques that allow mutation selection prior to PCR, which provides advantages. Pre-PCR enrichment techniques can be directly applied to genomic DNA and diminish the influence of PCR errors that can take place during amplification. Moreover, they have the capability for high multiplexity and can be followed by established mutation detection and enrichment technologies without changes to their established procedures. The first approaches for pre-PCR enrichment were developed by employing restriction endonucleases directly on genomic DNA in the early 1990s. However, newly developed pre-PCR enrichment methods provide higher sensitivity and versatility. This review describes the available pre-PCR enrichment methods and focuses on the most recently developed techniques (NaME-PrO, UVME, and DEASH/MAESTRO), emphasizing their applications in liquid biopsies.

Nuclease-Assisted, Multiplexed Minor-Allele Enrichment: Application in Liquid Biopsy of Cancer

The use of next-generation sequencing (NGS) to profile genomic variation of individual cancer species is revolutionizing the practice of clinical oncology. In liquid biopsy of cancer, sequencing of circulating-free DNA (cfDNA) is gradually applied to all stages of cancer diagnosis and treatment, serving as complement or replacement of tissue biopsies. However, analysis of cfDNA obtained from blood draws still faces technical obstacles due in part to an excess of wild-type DNA originating from normal tissues and hematopoietic cells. The resulting low-level mutation abundance often falls below routine NGS detection sensitivity and limits reliable mutation identification that meets clinical sensitivity and specificity standards. Despite sample preparation advances that reduce sequencing error rates via use of unique molecular identifiers (molecular barcodes) and error-suppression algorithms, excessive amounts of sequencing are still required to detect mutations at allelic frequency levels below 1%. This requirement reduces throughput and increases cost.In this chapter, we describe a sensitive multiplex mutation detection method that enriches mutation-containing DNA during sample preparation, prior to sequencing, thereby increasing signal-to-noise ratios and providing low-level mutation detection without excessive sequencing depth. We couple targeted next-generation sequencing with wild-type DNA removal using Nuclease-assisted Minor-allele Enrichment using Probe Overlap, NaME-PrO, a recently developed method to eliminate wild-type sequences from multiple targets simultaneously. A step by step guide to library preparation and data analysis are provided as well as some precautions during the sample handling.

Exploring ALDH2 expression and immune infiltration in HNSC and its correlation of prognosis with gender or alcohol intake

The aldehyde dehydrogenase 2 point mutation (ALDH2*2) is a common frequent human gene variant, especially in East Asians. However, the expression and mechanism of action of ALDH2 in HNSC remain unknown. The present study explored the clinical significance and immune characteristics of ALDH2 in HNSC. The receiver operating characteristic curve was analysed to assess the diagnostic value of ALDH2 expression. ALDH2 expression in normal tissues and HNSC tissues was evaluated by IHC, and we also analysed ALDH2 gene expression in 4 HNSC cell lines. ALDH2 expression was significantly reduced in HNSC tissues compared to normal tissues (p < 0.05). HNSC patients with high ALDH2 expression had a better prognosis compared to patients with low ALDH2 expression (p < 0.05). GSEA indicated that these gene sets were correlated with signalling pathways, including the JAK-STAT signalling pathway. Unexpectedly, we found a significant prognostic effect of ALDH2 for HNSC based on alcohol consumption and the male sex. The correlation between ALDH2 expression and immune inhibitors showed an effect for ALDH2 in modifying tumour immunology in HNSC, and there may be a possible mechanism by which ALDH2 regulates the functions of T cells in HNSC. In addition, we developed a prognostic nomogram for HNSC patients, which suggested that low ALDH2 expression indicated poor prognosis in HNSC patients who were males and alcoholics.

MuA-based Molecular Indexing for Rare Mutation Detection by Next-Generation Sequencing

Detection of low-frequency mutations in cancer genomes or other heterogeneous cell populations requires high-fidelity sequencing. Molecular barcoding is one of the key technologies that enables the differentiation of true mutations from errors, which can be caused by sequencing or library preparation processes. However, current approaches where barcodes are introduced via primer extension or adaptor ligation do not utilize the full power of barcoding, due to complicated library preparation workflows and biases. Here we demonstrate the remarkable tolerance of MuA transposase to the presence of multiple replacements in transposon sequence, and explore this unique feature to engineer the MuA transposome complex with randomised nucleotides in 12 transposon positions, which can be introduced as a barcode into the target molecule after transposition event. We applied the approach of Unique MuA-based Molecular Indexing (UMAMI) to assess the power of rare mutation detection by shortgun sequencing on the Illumina platform. Our results show that UMAMI allows detection of rare mutations readily and reliably, and in this paper we report error rate values for the number of thermophilic DNA polymerases measured by using UMAMI.

Assessment of Circulating Nucleic Acids in Cancer: From Current Status to Future Perspectives and Potential Clinical Applications

Current approaches for cancer detection and characterization are based on radiological procedures coupled with tissue biopsies, despite relevant limitations in terms of overall accuracy and feasibility, including relevant patients' discomfort. Liquid biopsies enable the minimally invasive collection and analysis of circulating biomarkers released from cancer cells and stroma, representing therefore a promising candidate for the substitution or integration in the current standard of care. Despite the potential, the current clinical applications of liquid biopsies are limited to a few specific purposes. The lack of standardized procedures for the pre-analytical management of body fluids samples and the detection of circulating biomarkers is one of the main factors impacting the effective advancement in the applicability of liquid biopsies to clinical practice. The aim of this work, besides depicting current methods for samples collection, storage, quality check and biomarker extraction, is to review the current techniques aimed at analyzing one of the main circulating biomarkers assessed through liquid biopsy, namely cell-free nucleic acids, with particular regard to circulating tumor DNA (ctDNA). ctDNA current and potential applications are reviewed as well.

Accurate Detection of Rare Mutant Alleles by Target Base-Specific Cleavage with the CRISPR/Cas9 System

The detection of low-frequency somatic mutations enables early diagnosis of disease; however, base-substitution errors that arise during genomic library preparation and high-throughput sequencing can lead to false diagnostic information. To discriminate true genomic alterations from technical errors, we developed spCas9-assisted true variant labeling sequencing (CARVE-seq), which detects low-frequency mutant alleles with high accuracy. CARVE-seq utilizes single-base discrimination during spCas9 cleavage reactions to exclude technical errors. Ten single nucleotide variants that recurrently occur in tumors were assayed by CARVE-seq using 20 ng reference samples, and 100% positive predictive value and specificity was observed, which proved the highly accurate performance of CARVE-seq.

Hawk-Seq™ differentiates between various mutations in Salmonella typhimurium TA100 strain caused by exposure to Ames test-positive mutagens

A precise understanding of differences in genomic mutations according to the mutagenic mechanisms detected in mutagenicity data is required to evaluate the carcinogenicity of environmental mutagens. Recently, we developed a highly accurate genome sequencing method, ‘Hawk-Seq™’, that enables the detection of mutagen-induced genome-wide mutations. However, its applicability to detect various mutagens and identify differences in mutational profiles is not well understood. Thus, we evaluated DNA samples from Salmonella typhimurium TA100 exposed to 11 mutagens, including alkylating agents, aldehydes, an aromatic nitro compound, epoxides, aromatic amines and polycyclic aromatic hydrocarbons (PAHs). We extensively analysed mutagen-induced mutational profiles and studied their association with the mechanisms of mutagens. Hawk-Seq™ sensitively detected mutations induced by all 11 mutagens, including one that increased the number of revertants by approximately 2-fold in the Ames test. Although the sensitivity for less water-soluble mutagens was relatively low, we increased the sensitivity to obtain high-resolution spectra by modifying the exposure protocol. Moreover, two epoxides indicated similar 6- or 96-dimensional mutational patterns; likewise, three S_N1-type alkylating agents indicated similar mutational patterns, suggesting that the mutational patterns are compound category specific. Meanwhile, an S_N2 type alkylating agent exhibited unique mutational patterns compared to those of the S_N1 type alkylating agents. Although the mutational patterns induced by aldehydes, the aromatic nitro compound, aromatic amines and PAHs did not differ substantially from each other, the maximum total base substitution frequencies (MTSFs) were similar among mutagens in the same structural groups. Furthermore, the MTSF was found to be associated with the carcinogenic potency of some direct-acting mutagens. These results indicate that our method can generate high-resolution mutational profiles to identify characteristic features of each mutagen. The detailed mutational data obtained by Hawk-Seq™ can provide useful information regarding mutagenic mechanisms and help identify its association with the carcinogenicity of mutagens without requiring carcinogenicity data.

Absence of hydroxyurea-induced mutational effects supports higher utilisation for the treatment of sickle cell anaemia

Hydroxyurea (hydroxycarbamide) is approved for treating both children and adults with sickle cell anaemia (SCA). Fetal haemoglobin (HbF) induction is the primary treatment response, along with improved anaemia, reduced haemolysis, myelosuppression and decreased endothelial inflammation. Hydroxyurea has proven clinical efficacy for SCA - treatment significantly reduces disease manifestations and prolongs survival. Despite these recognised benefits, long-standing concerns regarding the risks of mutagenic and potentially carcinogenic drug exposure have hampered efforts for broad hydroxyurea use in SCA, although these are based largely on outdated experimental models and treatment experiences with myeloproliferative neoplasms. Consequently, many patients with SCA are not receiving this highly effective disease-modifying therapy. In this review, we describe the concept of genotoxicity and its laboratory measurements, summarise hydroxyurea-associated data from both preclinical and clinical studies, and discuss carcinogenic potential. The genotoxicity results clearly demonstrate that hydroxyurea does not directly bind DNA and is not mutagenic. Rather, its genotoxic effects are limited to indirect clastogenicity occurring in select cell types, and only when high dose and time thresholds are exceeded. This absence of mutagenic activity is consistent with the observed lack of any compelling carcinogenic potential. Since hydroxyurea therapy for SCA carries minimal carcinogenic risks, the current drug labelling should be modified accordingly, and prescribing practices should be broadened to allow better access and increased utilisation of this highly effective drug.

Quantification of cancer driver mutations in human breast and lung DNA using targeted, error-corrected CarcSeq

There is a need for scientifically-sound, practical approaches to improve carcinogenicity testing. Advances in DNA sequencing technology and knowledge of events underlying cancer development have created an opportunity for progress in this area. The long-term goal of this work is to develop variation in cancer driver mutation (CDM) levels as a metric of clonal expansion of cells carrying CDMs because these important early events could inform carcinogenicity testing. The first step toward this goal was to develop and validate an error-corrected next-generation sequencing method to analyze panels of hotspot cancer driver mutations (hCDMs). The "CarcSeq" method that was developed uses unique molecular identifier sequences to construct single-strand consensus sequences for error correction. CarcSeq was used for mutational analysis of 13 amplicons encompassing >20 hotspot CDMs in normal breast, normal lung, ductal carcinomas, and lung adenocarcinomas. The approach was validated by detecting expected differences related to tissue type (normal vs. tumor and breast vs. lung) and mutation spectra. CarcSeq mutant fractions (MFs) correlated strongly with previously obtained ACB-PCR mutant fraction (MF) measurements from the same samples. A reconstruction experiment, in conjunction with other analyses, showed CarcSeq accurately quantifies MFs ≥10-4 . CarcSeq MF measurements were correlated with tissue donor age and breast cancer risk. CarcSeq MF measurements were correlated with deviation from median MFs analyzed to assess clonal expansion. Thus, CarcSeq is a promising approach to advance cancer risk assessment and carcinogenicity testing practices. Paradigms that should be investigated to advance this strategy for carcinogenicity testing are proposed.

Identification of unique and shared mitochondrial DNA mutations in neurodegeneration and cancer by single-cell mitochondrial DNA structural variation sequencing (MitoSV-seq)

Background

Point mutations and structural variations (SVs) in mitochondrial DNA (mtDNA) contribute to many neurodegenerative diseases. Technical limitations and heteroplasmy, however, have impeded their identification, preventing these changes from being examined in neurons in healthy and disease states.

Methods

We have developed a high-resolution technique—Mitochondrial DNA Structural Variation Sequencing (MitoSV-seq)—that identifies all types of mtDNA SVs and single-nucleotide variations (SNVs) in single neurons and novel variations that have been undetectable with conventional techniques.

Findings

Using MitoSV-seq, we discovered SVs/SNVs in dopaminergic neurons in the Ifnar1^−/− murine model of Parkinson disease. Further, MitoSV-seq was found to have broad applicability, delivering high-quality, full-length mtDNA sequences in a species-independent manner from human PBMCs, haematological cancers, and tumour cell lines, regardless of heteroplasmy. We characterised several common SVs in haematological cancers (AML and MDS) that were linked to the same mtDNA region, MT-ND5, using only 10 cells, indicating the power of MitoSV-seq in determining single-cancer-cell ontologies. Notably, the MT-ND5 hotspot, shared between all examined cancers and Ifnar1^−/− dopaminergic neurons, suggests that its mutations have clinical value as disease biomarkers.

Interpretation

MitoSV-seq identifies disease-relevant mtDNA mutations in single cells with high resolution, rendering it a potential drug screening platform in neurodegenerative diseases and cancers.

Funding

The Lundbeck Foundation, Danish Council for Independent Research-Medicine, and European Union Horizon 2020 Research and Innovation Programme.

Chasing ctDNA in Patients With Sarcoma

Liquid biopsies are new technologies that allow cancer profiling of tumor fragments found in body fluids, such as peripheral blood, collected noninvasively from patients with malignancies. These assays are increasingly valuable in clinical oncology practice as prognostic biomarkers, as guides for therapy selection, for treatment monitoring, and for early detection of disease progression and relapse. However, application of these assays to rare cancers, such as pediatric and adult sarcomas, have lagged. In this article, we review the technical challenges of applying liquid biopsy technologies to sarcomas, provide an update on progress in the field, describe common pitfalls in interpreting liquid biopsy data, and discuss the intersection of sarcoma clinical care and commercial assays emerging on the horizon.

Detection of Circulating Tumor DNA with a Single-Molecule Sequencing Analysis Validated for Targeted and Immunotherapy Selection

INTRODUCTION

Comprehensive genetic cancer profiling using circulating tumor DNA has enabled the detection of National Comprehensive Cancer Network (NCCN) guideline-recommended somatic alterations from a single, non-invasive blood draw. However, reliably detecting somatic variants at low variant allele fractions (VAFs) remains a challenge for next-generation sequencing (NGS)-based tests. We have developed the single-molecule sequencing (SMSEQ) platform to address these challenges.

METHODS

The OncoLBx assay utilizes the SMSEQ platform to optimize cell-free DNA extraction and library preparation with variant type-specific calling algorithms to improve sensitivity and specificity. OncoLBx is a pan-cancer panel for solid tumors targeting 75 genes and five microsatellite sites analyzing five classes of NCCN-recommended somatic variants: single-nucleotide variants (SNVs), insertions and deletions (indels), copy number variants (CNVs), fusions and microsatellite instability (MSI). Circulating DNA was extracted from plasma, followed by library preparation using SMSEQ. Analytical validation was performed according to recently published American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) guidelines and established the limit of detection (LOD), sensitivity, specificity, accuracy and reproducibility using 126 gold-standard reference samples, healthy donor samples verified by whole-exome sequencing by an external College of American Pathologists (CAP) reference lab and cell lines with known variants. Results were analyzed using a locus-specific modeling algorithm.

RESULTS

We have demonstrated that OncoLBx detects VAFs of ≥ 0.1% for SNVs and indels, ≥ 0.5% for fusions, ≥ 4.5 copies for CNVs and ≥ 2% for MSI, with all variant types having specificity ≥ 99.999%. Diagnostic performance of paired samples displays 80% sensitivity and > 99.999% clinical specificity. Clinical utility and performance were assessed in 416 solid tumor samples. Variants were detected in 79% of samples, for which 87.34% of positive samples had available targeted therapy.

Rationale and Roadmap for Developing Panels of Hotspot Cancer Driver Gene Mutations as Biomarkers of Cancer Risk

Cancer driver mutations (CDMs) are necessary and causal for carcinogenesis and have advantages as reporters of carcinogenic risk. However, little progress has been made toward developing measurements of CDMs as biomarkers for use in cancer risk assessment. Impediments for using a CDM-based metric to inform cancer risk include the complexity and stochastic nature of carcinogenesis, technical difficulty in quantifying low-frequency CDMs, and lack of established relationships between cancer driver mutant fractions and tumor incidence. Through literature review and database analyses, this review identifies the most promising targets to investigate as biomarkers of cancer risk. Mutational hotspots were discerned within the 20 most mutated genes across the 10 deadliest cancers. Forty genes were identified that encompass 108 mutational hotspot codons overrepresented in the COSMIC database; 424 different mutations within these hotspot codons account for approximately 63,000 tumors and their prevalence across tumor types is described. The review summarizes literature on the prevalence of CDMs in normal tissues and suggests such mutations are direct and indirect substrates for chemical carcinogenesis, which occurs in a spatially stochastic manner. Evidence that hotspot CDMs (hCDMs) frequently occur as tumor subpopulations is presented, indicating COSMIC data may underestimate mutation prevalence. Analyses of online databases show that genes containing hCDMs are enriched in functions related to intercellular communication. In its totality, the review provides a roadmap for the development of tissue-specific, CDM-based biomarkers of carcinogenic potential, comprised of batteries of hCDMs and can be measured by error-correct next-generation sequencing. Environ. Mol. Mutagen. 61:152-175, 2020. Published 2019. This article is a U.S. Government work and is in the public domain in the USA. Environmental and Molecular Mutagenesis published by Wiley Periodicals, Inc. on behalf of Environmental Mutagen Society.

Next-Generation Genotoxicology: Using Modern Sequencing Technologies to Assess Somatic Mutagenesis and Cancer Risk

Mutations have a profound effect on human health, particularly through an increased risk of carcinogenesis and genetic disease. The strong correlation between mutagenesis and carcinogenesis has been a driving force behind genotoxicity research for more than 50 years. The stochastic and infrequent nature of mutagenesis makes it challenging to observe and to study. Indeed, decades have been spent developing increasingly sophisticated assays and methods to study these low-frequency genetic errors, in hopes of better predicting which chemicals may be carcinogens, understanding their mode of action, and informing guidelines to prevent undue human exposure. While effective, widely used genetic selection-based technologies have a number of limitations that have hampered major advancements in the field of genotoxicity. Emerging new tools, in the form of enhanced next-generation sequencing platforms and methods, are changing this paradigm. In this review, we discuss rapidly evolving sequencing tools and technologies, such as error-corrected sequencing and single cell analysis, which we anticipate will fundamentally reshape the field. In addition, we consider a variety emerging applications for these new technologies, including the detection of DNA adducts, inference of mutational processes based on genomic site and local sequence contexts, and evaluation of genome engineering fidelity, as well as other cutting-edge challenges for the next 50 years of environmental and molecular mutagenesis research. Environ. Mol. Mutagen. 61:135-151, 2020. © 2019 The Authors. Environmental and Molecular Mutagenesis published by Wiley Periodicals, Inc. on behalf of Environmental Mutagen Society.

Somatic mutations - Evolution within the individual

With the rapid advancement of sequencing technologies over the last two decades, it is becoming feasible to detect rare variants from somatic tissue samples. Studying such somatic mutations can provide deep insights into various senescence-related diseases, including cancer, inflammation, and sporadic psychiatric disorders. While it is still a difficult task to identify true somatic mutations, relentless efforts to combine experimental and computational methods have made it possible to obtain reliable data. Furthermore, state-of-the-art machine learning approaches have drastically improved the efficiency and sensitivity of these methods. Meanwhile, we can regard somatic mutations as a counterpart of germline mutations, and it is possible to apply well-formulated mathematical frameworks developed for population genetics and molecular evolution to analyze this 'somatic evolution'. For example, retrospective cell lineage tracing is a promising technique to elucidate the mechanism of pre-diseases using single-cell RNA-sequencing (scRNA-seq) data.

Genome-wide somatic mutation analysis via Hawk-Seq™ reveals mutation profiles associated with chemical mutagens

It is difficult to identify mutagen-induced genome-wide somatic mutations using next generation sequencing; hence, mutagenic features of each mutagen and their roles in cancer development require further elucidation. We described Hawk-Seq™, a highly accurate genome sequencing method and the optimal conditions, for using it to construct libraries that would enable the accurate (c.a. 1 error/10⁷-10⁸ bp) and efficient survey of genome-wide mutations. Genomic mutations in gpt delta mice or Salmonella typhimurium TA100 exposed to methylnitrosourea (MNU), ethylnitrosourea (ENU), diethylnitrosamine (DEN), benzo[a]pyrene (BP), and aristolochic acid (AA) were profiled using Hawk-Seq™ to analyse positions, substitution patterns, or frequencies. The resultant vast mutation data provided high-resolution mutational signatures, including for minor mutational fractions (e.g. G:C>A:T by AA), which enabled the clarification of the mutagenic features of all mutagens. The 96-type mutational signatures of MNU, AA, and BP indicate their partial similarity to signature 11, 22, and 4 or 29, respectively. Meanwhile, signatures attributable to ENU and DEN were highly similar to each other, but not to signature 11, suggesting that the mechanisms of these agents differed from those of typical alkylating agents. Thus, Hawk-Seq™ can clarify genome-wide chemical mutagenicity profiles at extraordinary resolutions, thereby providing insight into mutagen mechanisms and their roles in cancer development.

High-resolution mapping of DNA polymerase fidelity using nucleotide imbalances and next-generation sequencing

DNA polymerase fidelity is affected by both intrinsic properties and environmental conditions. Current strategies for measuring DNA polymerase error rate in vitro are constrained by low error subtype sensitivity, poor scalability, and lack of flexibility in types of sequence contexts that can be tested. We have developed the Magnification via Nucleotide Imbalance Fidelity (MagNIFi) assay, a scalable next-generation sequencing assay that uses a biased deoxynucleotide pool to quantitatively shift error rates into a range where errors are frequent and hence measurement is robust, while still allowing for accurate mapping to error rates under typical conditions. This assay is compatible with a wide range of fidelity-modulating conditions, and enables high-throughput analysis of sequence context effects on base substitution and single nucleotide deletion fidelity using a built-in template library. We validate this assay by comparing to previously established fidelity metrics, and use it to investigate neighboring sequence-mediated effects on fidelity for several DNA polymerases. Through these demonstrations, we establish the MagNIFi assay for robust, high-throughput analysis of DNA polymerase fidelity.

Single-cell whole-genome sequencing reveals the functional landscape of somatic mutations in B lymphocytes across the human lifespan

Accumulation of mutations in somatic cells has been implicated as a cause of aging since the 1950s. However, attempts to establish a causal relationship between somatic mutations and aging have been constrained by the lack of methods to directly identify mutational events in primary human tissues. Here we provide genome-wide mutation frequencies and spectra of human B lymphocytes from healthy individuals across the entire human lifespan using a highly accurate single-cell whole-genome sequencing method. We found that the number of somatic mutations increases from <500 per cell in newborns to >3,000 per cell in centenarians. We discovered mutational hotspot regions, some of which, as expected, were located at Ig genes associated with somatic hypermutation (SHM). B cell-specific mutation signatures associated with development, aging, or SHM were found. The SHM signature strongly correlated with the signature found in human B cell tumors, indicating that potential cancer-causing events are already present even in B cells of healthy individuals. We also identified multiple mutations in sequence features relevant to cellular function (i.e., transcribed genes and gene regulatory regions). Such mutations increased significantly during aging, but only at approximately one-half the rate of the genome average, indicating selection against mutations that impact B cell function. This full characterization of the landscape of somatic mutations in human B lymphocytes indicates that spontaneous somatic mutations accumulating with age can be deleterious and may contribute to both the increased risk for leukemia and the functional decline of B lymphocytes in the elderly.

Molecular Profiling of Liquid Biopsy Samples for Precision Medicine

In the context of oncology, liquid biopsies consist of harvesting cancer biomarkers, such as circulating tumor cells, tumor-derived cell-free DNA, and extracellular vesicles, from bodily fluids. These biomarkers provide a source of clinically actionable molecular information that can enable precision medicine. Herein, we review technologies for the molecular profiling of liquid biopsy markers with special emphasis on the analysis of low abundant markers from mixed populations.

Considerations and quality controls when analyzing cell-free tumor DNA

Circulating cell-free tumor DNA (ctDNA) is a promising biomarker in cancer. Ultrasensitive technologies enable detection of low (< 0.1%) mutant allele frequencies, a pre-requisite to fully utilize the potential of ctDNA in cancer diagnostics. In addition, the entire liquid biopsy workflow needs to be carefully optimized to enable reliable ctDNA analysis. Here, we discuss important considerations for ctDNA detection in plasma. We show how each experimental step can easily be evaluated using simple quantitative PCR assays, including detection of cellular DNA contamination and PCR inhibition. Furthermore, ctDNA assay performance is also demonstrated to be affected by both DNA fragmentation and target sequence. Finally, we show that quantitative PCR is useful to estimate the required sequencing depth and to monitor DNA losses throughout the workflow. The use of quality control assays enables the development of robust and standardized workflows that facilitate the implementation of ctDNA analysis into clinical routine.

Targeted Next Generation Sequencing to study insert stability in genetically modified plants

The EU directive 2001/18/EC requires any genetically modified (GM) event to be stable. In the present work, a targeted Next-Generation Sequencing (NGS) approach using barcodes to specifically tag each individual DNA molecules during library preparation was implemented to detect mutations taking into account the background noise due to amplification and sequencing errors. The method was first showed to be efficient in detecting the mutations in synthetic samples prepared with custom-synthesized mutated or non-mutated P35S sequences mixed in different proportions. The genetic stability of a portion of the P35S promoter targeted for GM detection was then analyzed in GM flour samples. Several low frequency mutations were detected in the P35S sequences. Some mutated nucleotides were located within the primers and probes used in the P35S diagnostic test. If present not as somatic mutations but as the consensus sequence of some individuals, these mutations could influence the efficiency of the P35S real time PCR diagnostic test. This methodology could be implemented in genetic stability studies of GM inserts but also to detect single nucleotide mutant GM plants produced using "new breeding techniques".

Rare haplotype load as marker for lethal mutagenesis

RNA viruses replicate with a template-copying fidelity, which lies close to an extinction threshold. Increases of mutation rate by nucleotide analogues can drive viruses towards extinction. This transition is the basis of an antiviral strategy termed lethal mutagenesis. We have introduced a new diversity index, the rare haplotype load (RHL), to describe NS5B (polymerase) mutant spectra of hepatitis C virus (HCV) populations passaged in absence or presence of the mutagenic agents favipiravir or ribavirin. The increase in RHL is more prominent in mutant spectra whose expansions were due to nucleotide analogues than to multiple passages in absence of mutagens. Statistical tests for paired mutagenized versus non-mutagenized samples with 14 diversity indices show that RHL provides consistently the highest standardized effect of mutagenic treatment difference for ribavirin and favipiravir. The results indicate that the enrichment of viral quasispecies in very low frequency minority genomes can serve as a robust marker for lethal mutagenesis. The diagnostic value of RHL from deep sequencing data is relevant to experimental studies on enhanced mutagenesis of viruses, and to pharmacological evaluations of inhibitors suspected to have a mutagenic activity.

Duplex Proximity Sequencing (Pro-Seq): A method to improve DNA sequencing accuracy without the cost of molecular barcoding redundancy

A challenge in the clinical adoption of cell-free DNA (cfDNA) liquid biopsies for cancer care is their high cost compared to potential reimbursement. The most common approach used in liquid biopsies to achieve high specificity detection of circulating tumor DNA (ctDNA) among a large background of normal cfDNA is to attach molecular barcodes to each DNA template, amplify it, and then sequence it many times to reach a low-error consensus. In applications where the highest possible specificity is required, error rate can be lowered further by independently detecting the sequences of both strands of the starting cfDNA. While effective in error reduction, the additional sequencing redundancy required by such barcoding methods can increase the cost of sequencing up to 100-fold over standard next-generation sequencing (NGS) of equivalent depth. We present a novel library construction and analysis method for NGS that achieves comparable performance to the best barcoding methods, but without the increase in sequencing and subsequent sequencing cost. Named Proximity-Sequencing (Pro-Seq), the method merges multiple copies of each template into a single sequencing read by physically linking the molecular copies so they seed a single sequencing cluster. Since multiple DNA copies of the same template are compared for consensus within the same cluster, sequencing accuracy is improved without the use of redundant reads. Additionally, it is possible to represent both senses of the starting duplex in a single cluster. The resulting workflow is simple, and can be completed by a single technician in a work day with minimal hands on time. Using both cfDNA and cell line DNA, we report the average per-mutation detection threshold and per-base analytical specificity to be 0.003% and >99.9997% respectively, demonstrating that Pro-Seq is among the highest performing liquid biopsy technologies in terms of both sensitivity and specificity, but with greatly reduced sequencing costs compared to existing methods of comparable accuracy.

Somatic mutation load and spectra: A record of DNA damage and repair in healthy human cells

Somatic genome instability is a hallmark of cancer genomes and has been linked to aging and a variety of other pathologies. Large-scale cancer genome and exome sequencing have revealed that mutation load and spectra in cancers can be influenced by environmental exposures, the anatomical site of exposures, and tissue type. There is now an abundance of data favoring the hypothesis that a substantial portion of the mutations in cancers originate prior to carcinogenesis in stem cells of the healthy individual. Rapid advances in sequencing of noncancer cells from healthy humans have shown that their mutation loads and spectra resemble cancer data. Similar to cancer genomes, mutation profiles of healthy cells show marked intra-individual variation, thus providing a metric of the various factors-environmental and endogenous-involved in mutagenesis in these individuals. This review focuses on the current methodologies to measure mutation loads and to determine mutation signatures for evaluating the environmental and endogenous sources of DNA damage in human somatic cells. We anticipate that in future, such large-scale studies aimed at exploring the landscapes of somatic mutations across different cell types in healthy people would provide a valuable resource for designing personalized preventative strategies against diseases associated with somatic genome instability. Environ. Mol. Mutagen. 59:672-686, 2018. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

Methods of Detection of Measurable Residual Disease in AML

The presence of measurable ("minimal") residual disease (MRD) after induction and/or consolidation chemotherapy is a significant risk factor for relapse in patients with acute myeloid leukemia (AML). In recognition of the clinical significance of AML MRD, the European LeukemiaNet (ELN) recently recommended the establishment of CR-MRD^Negative as a separate category of treatment response. This recommendation represents a major milestone in the integration of AML MRD testing in standard clinical practice. This review article summarizes the methodologies employed in AML MRD detection and their application in clinical studies that provide evidence supporting the clinical utility of AML MRD testing. Future MRD evaluations in AML likely will require an integrated approach combining multi-parameter flow cytometry and high-sensitivity molecular techniques applied to time points during and after completion of therapy in order to provide the most accurate and comprehensive assessment of treatment response.

Detecting Rare Mutations and DNA Damage with Sequencing-Based Methods

There is a great need in biomedical and genetic research to detect DNA damage and de novo mutations, but doing so is inherently challenging because of the rarity of these events. The enormous capacity of current DNA sequencing technologies has opened the door for quantifying sequence variants present at low frequencies in vivo, such as within cancerous tissues. However, these sequencing technologies are error prone, resulting in high noise thresholds. Most DNA sequencing methods are also generally incapable of identifying chemically modified bases arising from DNA damage. In recent years, numerous specialized modifications to sequencing methods have been developed to address these shortcomings. Here, we review this landscape of emerging techniques, highlighting their respective strengths, weaknesses, and target applications.

MERIT reveals the impact of genomic context on sequencing error rate in ultra-deep applications

BACKGROUND

Rapid progress in high-throughput sequencing (HTS) and the development of novel library preparation methods have improved the sensitivity of detecting mutations in heterogeneous samples, specifically in high-depth (> 500×) clinical applications. However, HTS methods are bounded by their technical and theoretical limitations and sequencing errors cannot be completely eliminated. Comprehensive quantification of the background noise can highlight both the efficiency and the limitations of any HTS methodology, and help differentiate true mutations at low abundance from artifacts.

RESULTS

We introduce MERIT (Mutation Error Rate Inference Toolkit), designed for in-depth quantification of erroneous substitutions and small insertions and deletions. MERIT incorporates an all-inclusive variant caller and considers genomic context, including the nucleotides immediately at 5 'and 3 ', thereby establishing error rates for 96 possible substitutions as well as four single-base and 16 double-base indels. We applied MERIT to ultra-deep sequencing data (1,300,000 ×) obtained from the amplification of multiple clinically relevant loci, and showed a significant relationship between error rates and genomic contexts. In addition to observing significant difference between transversion and transition rates, we identified variations of more than 100-fold within each error type at high sequencing depths. For instance, T >G transversions in trinucleotide GTCs occurred 133.5 ± 65.9 more often than those in ATAs. Similarly, C >T transitions in GCGs were observed at 73.8 ± 10.5 higher rate than those in TCTs. We also devised an in silico approach to determine the optimal sequencing depth, where errors occur at rates similar to those of expected true mutations. Our analyses showed that increasing sequencing depth might improve sensitivity for detecting some mutations based on their genomic context. For example, T >G rate of error in GTCs did not change when sequenced beyond 10,000 ×; in contrast, T >G rate in TTAs consistently improved even at above 500,000 ×.

CONCLUSIONS

Our results demonstrate significant variation in nucleotide misincorporation rates, and suggest that genomic context should be considered for comprehensive profiling of specimen-specific and sequencing artifacts in high-depth assays. This data provide strong evidence against assigning a single allele frequency threshold to call mutations, for it can result in substantial false positive as well as false negative variants, with important clinical consequences.

Somatic mutations in neurons during aging and neurodegeneration

The nervous system is composed of a large variety of neurons with a diverse array of morphological and functional properties. This heterogeneity is essential for the construction and maintenance of a distinct set of neural networks with unique characteristics. Accumulating evidence now indicates that neurons do not only differ at a functional level, but also at the genomic level. These genomic discrepancies seem to be the result of somatic mutations that emerge in nervous tissue during development and aging. Ultimately, these mutations bring about a genetically heterogeneous population of neurons, a phenomenon that is commonly referred to as "somatic brain mosaicism". Improved understanding of the development and consequences of somatic brain mosaicism is crucial to understand the impact of somatic mutations on neuronal function in human aging and disease. Here, we highlight a number of topics related to somatic brain mosaicism, including some early experimental evidence for somatic mutations in post-mitotic neurons of the hypothalamo-neurohypophyseal system. We propose that age-related somatic mutations are particularly interesting, because aging is a major risk factor for a variety of neuronal diseases, including Alzheimer's disease. We highlight potential links between somatic mutations and the development of these diseases and argue that recent advances in single-cell genomics and in vivo physiology have now finally made it possible to dissect the origins and consequences of neuronal mutations in unprecedented detail.

Enhancing the accuracy of next-generation sequencing for detecting rare and subclonal mutations

Mutations, the fuel of evolution, are first manifested as rare DNA changes within a population of cells. Although next-generation sequencing (NGS) technologies have revolutionized the study of genomic variation between species and individual organisms, most have limited ability to accurately detect and quantify rare variants among the different genome copies in heterogeneous mixtures of cells or molecules. We describe the technical challenges in characterizing subclonal variants using conventional NGS protocols and the recent development of error correction strategies, both computational and experimental, including consensus sequencing of single DNA molecules. We also highlight major applications for low-frequency mutation detection in science and medicine, describe emerging methodologies and provide our vision for the future of DNA sequencing.

Extending Circulating Tumor DNA Analysis to Ultralow Abundance Mutations: Techniques and Challenges

Liquid biopsies that analyze circulating tumor DNA (ctDNA) hold great promise in the guidance of clinical treatment for various cancers. However, the innate characteristics of ctDNA make it a difficult target: ctDNA is highly fragmented, and found at very low concentrations, both in absolute terms and relative to wildtype species. Clinically relevant target sequences often differ from the wildtype species by a single DNA base pair. These characteristics make analyzing mutant ctDNA a uniquely difficult process. Despite this, techniques have recently emerged for analyzing ctDNA, and have been used in pilot studies that showed promising results. These techniques each have various drawbacks, either in their analytical capabilities or in practical considerations, which restrict their application to many clinical situations. Many of the most promising potential applications of ctDNA require assay characteristics that are not currently available, and new techniques with these properties could have benefits in companion diagnostics, monitoring response to treatment and early detection. Here we review the current state of the art in ctDNA detection, with critical comparison of the analytical techniques themselves. We also examine the improvements required to expand ctDNA diagnostics to more advanced applications and discuss the most likely pathways for these improvements.

COLD-PCR Technologies in the Area of Personalized Medicine: Methodology and Applications

Somatic mutations bear great promise for use as biomarkers for personalized medicine, but are often present only in low abundance in biological material and are therefore difficult to detect. Many assays for mutation analysis in cancer-related genes (hotspots) have been developed to improve diagnosis, prognosis, prediction of drug resistance, and monitoring of the response to treatment. Two major approaches have been developed: mutation-specific amplification methods and methods that enrich and detect mutations without prior knowledge on the exact location and identity of the mutation. CO-amplification at Lower Denaturation temperature Polymerase Chain Reaction (COLD-PCR) methods such as full-, fast-, ice- (improved and complete enrichment), enhanced-ice, and temperature-tolerant COLD-PCR make use of a critical temperature in the polymerase chain reaction to selectively denature wild-type-mutant heteroduplexes, allowing the enrichment of rare mutations. Mutations can subsequently be identified using a variety of laboratory technologies such as high-resolution melting, digital polymerase chain reaction, pyrosequencing, Sanger sequencing, or next-generation sequencing. COLD-PCR methods are sensitive, specific, and accurate if appropriately optimized and have a short time to results. A large variety of clinical samples (tumor DNA, circulating cell-free DNA, circulating cell-free fetal DNA, and circulating tumor cells) have been studied using COLD-PCR in many different applications including the detection of genetic changes in cancer and infectious diseases, non-invasive prenatal diagnosis, detection of microorganisms, or DNA methylation analysis. In this review, we describe in detail the different COLD-PCR approaches, highlighting their specificities, advantages, and inconveniences and demonstrating their use in different fields of biological and biomedical research.

Performance evaluation method for read mapping tool in clinical panel sequencing

In addition to the rapid advancement in Next-Generation Sequencing (NGS) technology, clinical panel sequencing is being used increasingly in clinical studies and tests. However, tools that are used in NGS data analysis have not been comparatively evaluated in performance for panel sequencing. This study aimed to evaluate the tools used in the alignment process, the first procedure in bioinformatics analysis, by comparing tools that have been widely used with ones that have been introduced recently. With the accumulated panel sequencing data, detected variant lists were cataloged and inserted into simulated reads produced from the reference genome (h19). The amount of unmapped reads and misaligned reads, mapping quality distribution, and runtime were measured as standards for comparison. As the most widely used tools, Bowtie2 and BWA–MEM each showed explicit performance with AUC of 0.9984 and 0.9970 respectively. Kart, maintaining superior runtime and less number of misaligned read, also similarly possessed high level of AUC (0.9723). Such selection and optimization method of tools appropriate for panel sequencing can be utilized for fields requiring error minimization, such as clinical application and liquid biopsy studies.

Targeted error-suppressed quantification of circulating tumor DNA using semi-degenerate barcoded adapters and biotinylated baits

Ultrasensitive methods for rare allele detection are critical to leverage the full potential offered by liquid biopsies. Here, we describe a novel molecular barcoding method for the precise detection and quantification of circulating tumor DNA (ctDNA). The major benefits of our design include straightforward and cost-effective production of barcoded adapters to tag individual DNA molecules before PCR and sequencing, and better control over cross-contamination between experiments. We validated our approach in a cohort of 24 patients with a broad spectrum of cancer diagnoses by targeting and quantifying single-nucleotide variants (SNVs), indels and genomic rearrangements in plasma samples. By using personalized panels targeting a priori known mutations, we demonstrate comprehensive error-suppression capabilities for SNVs and detection thresholds for ctDNA below 0.1%. We also show that our semi-degenerate barcoded adapters hold promise for noninvasive genotyping in the absence of tumor biopsies and monitoring of minimal residual disease in longitudinal plasma samples. The benefits demonstrated here include broad applicability, flexibility, affordability and reproducibility in the research and clinical settings.

Targeted sequencing of both DNA strands barcoded and captured individually by RNA probes to identify genome-wide ultra-rare mutations

Next Generation Sequencing (NGS) has been widely implemented in biological research and has made a profound impact on patient care. One of the essential NGS applications is to identify disease-causing sequence variants, where high coverage and accuracy are needed. Here, we reported a novel NGS pipeline, termed a Sequencing System of Digitalized Barcode Encrypted Single-stranded Library from Extremely Low (quality and quantity) DNA Input with Probe-based DNA Enrichment by RNA probes targeting DNA duplex (DEEPER-Seq). This method combines an ultra-sensitive single-stranded library construction with barcoding error correction, termed DEEPER-Library; and a DNA capture approach using RNA probes targeting both DNA strands, termed DEEPER-Capture. DEEPER-Seq can create NGS libraries from as little as 20 pg DNA with PCR error correcting capabilities, and capture target sequences at an average ratio of 29.2% by targeting both DNA strands simultaneously with an over 98.6% coverage. Our method tags and sequences each of the two strands of a DNA duplex independently and only scores mutations that are found at the same position in both strands, which allows us to identify mutations with allelic fractions down to 0.03% in a whole exome sequencing (WES) study with a background error rate of one artificial error per 4.8 × 10⁹ nucleotides.

A high-throughput assay for quantitative measurement of PCR errors

The accuracy with which DNA polymerase can replicate a template DNA sequence is an extremely important property that can vary by an order of magnitude from one enzyme to another. The rate of nucleotide misincorporation is shaped by multiple factors, including PCR conditions and proofreading capabilities, and proper assessment of polymerase error rate is essential for a wide range of sensitive PCR-based assays. In this paper, we describe a method for studying polymerase errors with exceptional resolution, which combines unique molecular identifier tagging and high-throughput sequencing. Our protocol is less laborious than commonly-used methods, and is also scalable, robust and accurate. In a series of nine PCR assays, we have measured a range of polymerase accuracies that is in line with previous observations. However, we were also able to comprehensively describe individual errors introduced by each polymerase after either 20 PCR cycles or a linear amplification, revealing specific substitution preferences and the diversity of PCR error frequency profiles. We also demonstrate that the detected high-frequency PCR errors are highly recurrent and that the position in the template sequence and polymerase-specific substitution preferences are among the major factors influencing the observed PCR error rate.

Single-Strand Consensus Sequencing Reveals that HIV Type but not Subtype Significantly Impacts Viral Mutation Frequencies and Spectra

A long-standing question of human immunodeficiency virus (HIV) genetic variation and evolution has been whether differences exist in mutation rate and/or mutation spectra among HIV types (i.e., HIV-1 versus HIV-2) and among HIV groups (i.e., HIV-1 groups M-P and HIV-2 groups A-H) and HIV-1 Group M subtypes (i.e., subtypes A-D, F-H, and J-K). To address this, we developed a new single-strand consensus sequencing assay for the determination of HIV mutation frequencies and spectra using the Illumina sequencing platform. This assay enables parallel and standardized comparison of HIV mutagenesis among various viral vectors with lower background error than traditional methods of Illumina library preparation. We found significant differences in viral mutagenesis between HIV types but intriguingly no significant differences among HIV-1 Group M subtypes. More specifically, HIV-1 exhibited higher transition frequencies than HIV-2, due mostly to single G-to-A mutations and (to a lesser extent) G-to-A hypermutation. These data suggest that HIV-2 RT exhibits higher fidelity during viral replication, and taken together, these findings demonstrate that HIV type but not subtype significantly affects viral mutation frequencies and spectra. These differences may inform antiviral and vaccine strategies.

Asymmetrical barcode adapter-assisted recovery of duplicate reads and error correction strategy to detect rare mutations in circulating tumor DNA

Deep sequencing is required for the highly sensitive detection of rare variants in circulating tumor DNA (ctDNA). However, there remains a challenge for improved sensitivity and specificity. Maximum-depth sequencing is crucial to detect minority mutations that contribute to cancer progression. The associated costs become prohibitive as the numbers of targets and samples increase. We describe the targeted sequencing of KRAS in plasma samples using an efficient barcoding approach to recover discarded reads marked as duplicates. Combined with an error-removal strategy, we anticipate that our method could improve the accuracy of genotype calling, especially to detect rare mutations in the monitoring of ctDNA.

Towards precision prevention: Technologies for identifying healthy individuals with high risk of disease

The rise of advanced technologies for characterizing human populations at the molecular level, from sequence to function, is shifting disease prevention paradigms toward personalized strategies. Because minimization of adverse outcomes is a key driver for treatment decisions for diseased populations, developing personalized therapy strategies represent an important dimension of both precision medicine and personalized prevention. In this commentary, we highlight recently developed enabling technologies in the field of DNA damage, DNA repair, and mutagenesis. We propose that omics approaches and functional assays can be integrated into population studies that fuse basic, translational and clinical research with commercial expertise in order to accelerate personalized prevention and treatment of cancer and other diseases linked to aberrant responses to DNA damage. This collaborative approach is generally applicable to efforts to develop data-driven, individualized prevention and treatment strategies for other diseases. We also recommend strategies for maximizing the use of biological samples for epidemiological studies, and for applying emerging technologies to clinical applications.

Simple multiplexed PCR-based barcoding of DNA for ultrasensitive mutation detection by next-generation sequencing

Detection of extremely rare variant alleles within a complex mixture of DNA molecules is becoming increasingly relevant in many areas of clinical and basic research, such as the detection of circulating tumor DNA in the plasma of cancer patients. Barcoding of DNA template molecules early in next-generation sequencing (NGS) library construction provides a way to identify and bioinformatically remove polymerase errors that otherwise make detection of these rare variants very difficult. Several barcoding strategies have been reported, but all require long and complex library preparation protocols. Simple, multiplexed, PCR-based barcoding of DNA for sensitive mutation detection using sequencing (SiMSen-seq) was developed to generate targeted barcoded libraries with minimal DNA input, flexible target selection and a very simple, short (∼4 h) library construction protocol. The protocol comprises a three-cycle barcoding PCR step followed directly by adaptor PCR to generate the library and then bead purification before sequencing. Thus, SiMSen-seq allows detection of variant alleles at <0.1% frequency with easy customization of library content (from 1 to 40+ PCR amplicons) and a protocol that can be implemented in any molecular biology laboratory. Here, we provide a detailed protocol for assay development and describe software to process the barcoded sequence reads.

Advances in Circulating Tumor DNA Analysis

The analysis of cell-free circulating tumor DNA (ctDNA) is a very promising tool and might revolutionize cancer care with respect to early detection, identification of minimal residual disease, assessment of treatment response, and monitoring tumor evolution. ctDNA analysis, often referred to as "liquid biopsy" offers what tissue biopsies cannot-a continuous monitoring of tumor-specific changes during the entire course of the disease. Owing to technological improvements, efforts for the establishment of preanalytical and analytical benchmark, and the inclusion of ctDNA analyses in clinical trial, an actual clinical implementation has come within easy reach. In this chapter, recent advances of the analysis of ctDNA are summarized starting from the discovery of cell-free DNA, to methodological approaches and the clinical applicability.