Benefits of applying molecular barcoding systems are not uniform across different genomic applications.

BACKGROUND: Despite the wide variety of Next Generation Sequencing (NGS)-based methods, it remains challenging to detect mutations present at very low frequencies. This problem is particularly relevant in oncology, where the limiting amount of input material, and its low quality, often limit the performance of the assays. Unique Molecular Identifiers (UMIs) are a molecular barcoding system often coupled with computational methods of noise suppression to improve the reliability of detection of rare variants. Although widely adopted, UMI inclusion imposes additional technical complexity and sequencing cost. Currently, there are no guidelines on UMI usage nor a comprehensive evaluation of their advantage across different applications. METHODS: We used DNA sequencing data generated by molecular barcoding and hybridization-based enrichment, from various types and quantities of input material (fresh frozen, formaldehyde-treated and cell-free DNA), to evaluate the performance of variant calling in different clinically relevant contexts. RESULTS: Noise suppression achieved by read grouping based on fragment mapping positions ensures reliable variant calling for many experimental designs even without exogenous UMIs. Exogenous barcodes significantly improve performance only when mapping position collisions occur, which is common in cell-free DNA. CONCLUSIONS: We demonstrate that UMI usage is not universally beneficial across experimental designs and that it is worthwhile to critically consider the comparative advantage of UMI usage for a given NGS application prior to experimental design.

High-Throughput Nucleotide Resolution Predictions of Assay Limitations Increase the Reliability and Concordance of Clinical Tests.

PURPOSE: The ability of next-generation sequencing (NGS) assays to interrogate thousands of genomic loci has revolutionized genetic testing. However, translation to the clinic is impeded by false-negative results that pose a risk to patients. In response, regulatory bodies are calling for reliability measures to be reported alongside NGS results. Existing methods to estimate reliability do not account for sample- and position-specific variability, which can be significant. Here, we report an approach that computes reliability metrics for every genomic position and sample interrogated by an NGS assay. METHODS: Our approach predicts the limit of detection (LOD), the lowest reliably detectable variant fraction, by taking technical factors into account. We initially explored how LOD is affected by input material amount, library conversion rate, sequencing coverage, and sequencing error rate. This revealed that LOD depends heavily on genomic context and sample properties. Using these insights, we developed a computational approach to predict LOD on the basis of a biophysical model of the NGS workflow. We focused on targeted assays for cell-free DNA, but, in principle, this approach applies to any NGS assay. RESULTS: We validated our approach by showing that it accurately predicts LOD and distinguishes reliable from unreliable results when screening 580 lung cancer samples for actionable mutations. Compared with a standard variant calling workflow, our approach avoided most false negatives and improved interassay concordance from 94% to 99%. CONCLUSION: Our approach, which we name LAVA (LOD-aware variant analysis), reports the LOD for every position and sample interrogated by an NGS assay. This enables reliable results to be identified and improves the transparency and safety of genetic tests.

Recommendations for accurate genotyping of SARS-CoV-2 using amplicon-based sequencing of clinical samples.

OBJECTIVES: Genotyping of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been instrumental in monitoring viral evolution and transmission during the pandemic. The quality of the sequence data obtained from these genotyping efforts depends on several factors, including the quantity/integrity of the input material, the technology, and laboratory-specific implementation. The current lack of guidelines for SARS-CoV-2 genotyping leads to inclusion of error-containing genome sequences in genomic epidemiology studies. We aimed to establish clear and broadly applicable recommendations for reliable virus genotyping. METHODS: We established and used a sequencing data analysis workflow that reliably identifies and removes technical artefacts; such artefacts can result in miscalls when using alternative pipelines to process clinical samples and synthetic viral genomes with an amplicon-based genotyping approach. We evaluated the impact of experimental factors, including viral load and sequencing depth, on correct sequence determination. RESULTS: We found that at least 1000 viral genomes are necessary to confidently detect variants in the SARS-CoV-2 genome at frequencies of ≥10%. The broad applicability of our recommendations was validated in over 200 clinical samples from six independent laboratories. The genotypes we determined for clinical isolates with sufficient quality cluster by sampling location and period. Our analysis also supports the rise in frequencies of 20A.EU1 and 20A.EU2, two recently reported European strains whose dissemination was facilitated by travel during the summer of 2020. CONCLUSIONS: We present much-needed recommendations for the reliable determination of SARS-CoV-2 genome sequences and demonstrate their broad applicability in a large cohort of clinical samples.

High-resolution mapping of mitotic DNA synthesis regions and common fragile sites in the human genome through direct sequencing.

DNA replication stress, a feature of human cancers, often leads to instability at specific genomic loci, such as the common fragile sites (CFSs). Cells experiencing DNA replication stress may also exhibit mitotic DNA synthesis (MiDAS). To understand the physiological function of MiDAS and its relationship to CFSs, we mapped, at high resolution, the genomic sites of MiDAS in cells treated with the DNA polymerase inhibitor aphidicolin. Sites of MiDAS were evident as well-defined peaks that were largely conserved between cell lines and encompassed all known CFSs. The MiDAS peaks mapped within large, transcribed, origin-poor genomic regions. In cells that had been treated with aphidicolin, these regions remained unreplicated even in late S phase; MiDAS then served to complete their replication after the cells entered mitosis. Interestingly, leading and lagging strand synthesis were uncoupled in MiDAS, consistent with MiDAS being a form of break-induced replication, a repair mechanism for collapsed DNA replication forks. Our results provide a better understanding of the mechanisms leading to genomic instability at CFSs and in cancer cells.

Monitoring early S-phase origin firing and replication fork movement by sequencing nascent DNA from synchronized cells.

A better understanding of DNA replication initiation in human cells and how this process is altered upon DNA replication stress requires the ability to study origin firing genome wide. Previously described methods of mapping DNA replication origins in higher eukaryotes rely principally on fractionation of DNA fragments based on their size and, optionally, on the presence of ribonucleotides at their 5' end. Here, we describe a protocol for EdUseq-HU, a method for mapping early S-phase replication origins. Cells, synchronized by mitotic shake-off, are released in medium containing 5-ethynyl-2'-deoxyuridine (EdU; to label nascent DNA) and hydroxyurea (HU; to limit fork progression after origin firing). After using click chemistry to tag the EdU label with a biotin conjugate that is cleavable under mild conditions, the nascent DNA is captured on streptavidin beads. One variant of EdUseq-HU allows mapping of DNA replication origins on the genome at a resolution of 10 kb, and a second variant monitors progression of replication forks. Using EdUseq-HU, the spatiotemporal program of DNA replication in human cell lines can be interrogated in <2 weeks. The protocol requires basic cell culture and molecular biology skills, as well as familiarity with the Perl programming language and the Linux operating system.

Intragenic origins due to short G1 phases underlie oncogene-induced DNA replication stress.

Oncogene-induced DNA replication stress contributes critically to the genomic instability that is present in cancer. However, elucidating how oncogenes deregulate DNA replication has been impeded by difficulty in mapping replication initiation sites on the human genome. Here, using a sensitive assay to monitor nascent DNA synthesis in early S phase, we identified thousands of replication initiation sites in cells before and after induction of the oncogenes CCNE1 and MYC. Remarkably, both oncogenes induced firing of a novel set of DNA replication origins that mapped within highly transcribed genes. These ectopic origins were normally suppressed by transcription during G1, but precocious entry into S phase, before all genic regions had been transcribed, allowed firing of origins within genes in cells with activated oncogenes. Forks from oncogene-induced origins were prone to collapse, as a result of conflicts between replication and transcription, and were associated with DNA double-stranded break formation and chromosomal rearrangement breakpoints both in our experimental system and in a large cohort of human cancers. Thus, firing of intragenic origins caused by premature S phase entry represents a mechanism of oncogene-induced DNA replication stress that is relevant for genomic instability in human cancer.

DNA replication stress as a hallmark of cancer.

Human cancers share properties referred to as hallmarks, among which sustained proliferation, escape from apoptosis, and genomic instability are the most pervasive. The sustained proliferation hallmark can be explained by mutations in oncogenes and tumor suppressors that regulate cell growth, whereas the escape from apoptosis hallmark can be explained by mutations in the TP53, ATM, or MDM2 genes. A model to explain the presence of the three hallmarks listed above, as well as the patterns of genomic instability observed in human cancers, proposes that the genes driving cell proliferation induce DNA replication stress, which, in turn, generates genomic instability and selects for escape from apoptosis. Here, we review the data that support this model, as well as the mechanisms by which oncogenes induce replication stress. Further, we argue that DNA replication stress should be considered as a hallmark of cancer because it likely drives cancer development and is very prevalent.