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Detection of RNA targets is typically achieved through RT-qPCR or RNAseq. RT-qPCR is rapid but limited in number and complexity of targets detected, while RNAseq is high-throughput but takes multiple days. We demonstrate simultaneous amplification and detection of 28 distinct RNA targets from a single unsplit purified RNA sample in under 40 minutes using our convective array PCR (caPCR) technology. We integrate tunable strand displacement probes into caPCR to allow detection of RNA species with programmable sequence selectivity for either a single, perfectly matched target sequence or for targets with up to 2 single-nucleotide variants within the probe-binding regions. Tunable probes allow for robust detection of desired RNA species against high homology background sequences and robust detection of RNA species with significant sequence diversity due to community-acquired mutations. As a proof-of-concept, we experimentally demonstrated detection of 7 human coronaviruses and 7 key variants of concern of SARS-CoV-2 in a single assay. Integrating tunable strand displacement probes into a convective array PCR platform allows simultaneous amplification and detection of 28 distinct RNA targets from a single sample in under 40 minutes. [ABSTRACT FROM AUTHOR]

One major challenge in the design of highly multiplexed PCR primer sets is the large number of potential primer dimer species that grows quadratically with the number of primers to be designed. Simultaneously, there are exponentially many choices for multiplex primer sequence selection, resulting in systematic evaluation approaches being computationally intractable. Here, we present and experimentally validate Simulated Annealing Design using Dimer Likelihood Estimation (SADDLE), a stochastic algorithm for design of multiplex PCR primer sets that minimize primer dimer formation. In a 96-plex PCR primer set (192 primers), the fraction of primer dimers decreases from 90.7% in a naively designed primer set to 4.9% in our optimized primer set. Even when scaling to 384-plex (768 primers), the optimized primer set maintains low dimer fraction. In addition to NGS, SADDLE-designed primer sets can also be used in qPCR settings to allow highly multiplexed detection of gene fusions in cDNA, with a single-tube assay comprising 60 primers detecting 56 distinct gene fusions recurrently observed in lung cancer. The design of highly multiplex PCR primers to amplify and enrich many different DNA sequences is increasing in biomedical importance as new mutations and pathogens are identified. The authors present and experimentally validate Simulated Annealing Design using Dimer Likelihood Estimation (SADDLE), a stochastic algorithm for design of highly multiplex PCR primer sets that minimize primer dimer formation. [ABSTRACT FROM AUTHOR]

Current gold standard for absolute quantitation of a specific DNA sequence is droplet digital PCR (ddPCR), which has been applied to copy number variation (CNV) detection. However, the number of quantitation modules in ddPCR is limited by fluorescence channels, which thus limits the CNV sensitivity due to sampling error following Poisson distribution. Here we develop a PCR-based molecular barcoding NGS approach, quantitative amplicon sequencing (QASeq), for accurate absolute quantitation scalable to over 200 quantitation modules. By attaching barcodes to individual target molecules with high efficiency, 2-plex QASeq exhibits higher and more consistent conversion yield than ddPCR in absolute molecule count quantitation. Multiplexed QASeq improves CNV sensitivity allowing confident distinguishment of 2.05 ploidy from normal 2.00 ploidy. We apply multiplexed QASeq to serial longitudinal plasma cfDNA samples from patients with metastatic ERBB2+ (HER2+) breast cancer seeking association with tumor progression. We further show an RNA QASeq panel for targeted expression profiling. Highly multiplexed ddPCR for sensitive nucleic acid quantitation remains challenging due to limited fluorescence channels. Here the authors report quantitative amplicon sequencing (QASeq), a PCR-based molecular barcoding NGS approach which is compatible with high multiplexing. [ABSTRACT FROM AUTHOR]

Quantitation of rare somatic mutations is essential for basic research and translational clinical applications including minimal residual disease (MRD) detection. Though unique molecular identifier (UMI) has suppressed errors for rare mutation detection, the sequencing depth requirement is high. Here, we present Quantitative Blocker Displacement Amplification (QBDA) which integrates sequence-selective variant enrichment into UMI quantitation for accurate quantitation of mutations below 0.01% VAF at only 23,000X depth. Using a panel of 20 genes recurrently altered in acute myeloid leukemia, we demonstrate quantitation of various mutations including single base substitutions and indels down to 0.001% VAF at a single locus with less than 4 million sequencing reads, allowing sensitive MRD detection in patients during complete remission. In a pan-cancer panel and a melanoma hotspot panel, we detect mutations down to 0.1% VAF using only 1 million reads. QBDA provides a convenient and versatile method for sensitive mutation quantitation using low-depth sequencing. Quantification of rare somatic mutations is essential for basic research and translational applications. Here the authors present Quantitative Blocker Displacement Amplification allowing for accurate detection of mutations below 0.01% VAF. [ABSTRACT FROM AUTHOR]

Targeted high-throughput DNA sequencing is a primary approach for genomics and molecular diagnostics, and more recently as a readout for DNA information storage. Oligonucleotide probes used to enrich gene loci of interest have different hybridization kinetics, resulting in non-uniform coverage that increases sequencing costs and decreases sequencing sensitivities. Here, we present a deep learning model (DLM) for predicting Next-Generation Sequencing (NGS) depth from DNA probe sequences. Our DLM includes a bidirectional recurrent neural network that takes as input both DNA nucleotide identities as well as the calculated probability of the nucleotide being unpaired. We apply our DLM to three different NGS panels: a 39,145-plex panel for human single nucleotide polymorphisms (SNP), a 2000-plex panel for human long non-coding RNA (lncRNA), and a 7373-plex panel targeting non-human sequences for DNA information storage. In cross-validation, our DLM predicts sequencing depth to within a factor of 3 with 93% accuracy for the SNP panel, and 99% accuracy for the non-human panel. In independent testing, the DLM predicts the lncRNA panel with 89% accuracy when trained on the SNP panel. The same model is also effective at predicting the measured single-plex kinetic rate constants of DNA hybridization and strand displacement. DNA probes used in next generation sequencing (NGS) have variable hybridisation kinetics, resulting in non-uniform coverage. Here, the authors develop a deep learning model to predict NGS depth using DNA probe sequences and apply to human and non-human sequencing panels. [ABSTRACT FROM AUTHOR]

Whole exome sequencing (WES) is used to identify mutations in a patient's tumor DNA that are predictive of tumor behavior, including the likelihood of response or resistance to cancer therapy. WES has a mutation limit of detection (LoD) at variant allele frequencies (VAF) of 5%. Putative mutations called at ≤ 5% VAF are frequently due to sequencing errors, therefore reporting these subclonal mutations incurs risk of significant false positives. Here we performed ~ 1000 × WES on fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tissue biopsy samples from a non-small cell lung cancer patient, and identified 226 putative mutations at between 0.5 and 5% VAF. Each variant was then tested using NuProbe NGSure, to confirm the original WES calls. NGSure utilizes Blocker Displacement Amplification to first enrich the allelic fraction of the mutation and then uses Sanger sequencing to determine mutation identity. Results showed that 52% of the 226 (117) putative variants were disconfirmed, among which 2% (5) putative variants were found to be misidentified in WES. In the 66 cancer-related variants, the disconfirmed rate was 82% (54/66). This data demonstrates Blocker Displacement Amplification allelic enrichment coupled with Sanger sequencing can be used to confirm putative mutations ≤ 5% VAF. By implementing this method, next-generation sequencing can reliably report low-level variants at a high sensitivity, without the cost of high sequencing depth. [ABSTRACT FROM AUTHOR]

Mutations in the BRAF gene at or near the p. V600 locus are informative for therapy selection, but current methods for analyzing FFPE tissue DNA generally have a limit of detection of 5% variant allele frequency (VAF), or are limited to the single variant (V600E). These can result in false negatives for samples with low VAFs due to low tumor content or subclonal heterogeneity, or harbor non-V600 mutations. Here, we show that Sanger sequencing using the NuProbe VarTrace BRAF assay, based on the Blocker Displacement Amplification (BDA) technology, is capable of detecting BRAF V600 mutations down to 0.20% VAF from FFPE lymph node tissue samples. Comparison experiments on adjacent tissue sections using BDA Sanger, immunohistochemistry (IHC), digital droplet PCR (ddPCR), and NGS showed 100% concordance among all 4 methods for samples with BRAF mutations at ≥ 1% VAF, though ddPCR did not distinguish the V600K mutation from the V600E mutation. BDA Sanger, ddPCR, and NGS (with orthogonal confirmation) were also pairwise concordant for lower VAF mutations down to 0.26% VAF, but IHC produced a false negative. Thus, we have shown that Sanger sequencing can be effective for rapid detection and quantitation of multiple low VAF BRAF mutations from FFPE samples. BDA Sanger method also enabled detection and quantitation of less frequent, potentially actionable non-V600 mutations as demonstrated by synthetic samples. [ABSTRACT FROM AUTHOR]

Hybridization of complementary sequences is one of the central tenets of nucleic acid chemistry; however, the unintended binding of closely related sequences limits the accuracy of hybridization-based approaches to analysing nucleic acids. Thermodynamics-guided probe design and empirical optimization of the reaction conditions have been used to enable the discrimination of single-nucleotide variants, but typically these approaches provide only an approximately 25-fold difference in binding affinity. Here we show that simulations of the binding kinetics are both necessary and sufficient to design nucleic acid probe systems with consistently high specificity as they enable the discovery of an optimal combination of thermodynamic parameters. Simulation-guided probe systems designed against 44 sequences of different target single-nucleotide variants showed between a 200- and 3,000-fold (median 890) higher binding affinity than their corresponding wild-type sequences. As a demonstration of the usefulness of this simulation-guided design approach, we developed probes that, in combination with PCR amplification, detect low concentrations of variant alleles (1%) in human genomic DNA. [ABSTRACT FROM AUTHOR]

Small variations in nucleic acid sequences can have far-reaching phenotypic consequences. Reliably distinguishing closely related sequences is therefore important for research and clinical applications. Here, we demonstrate that conditionally fluorescent DNA probes are capable of distinguishing variations of a single base in a stretch of target DNA. These probes use a novel programmable mechanism in which each single nucleotide polymorphism generates two thermodynamically destabilizing mismatch bubbles rather than the single mismatch formed during typical hybridization-based assays. Up to a 12,000-fold excess of a target that contains a single nucleotide polymorphism is required to generate the same fluorescence as one equivalent of the intended target, and detection works reliably over a wide range of conditions. Using these probes we detected point mutations in a 198 base-pair subsequence of the Escherichia coli rpoB gene. That our probes are constructed from multiple oligonucleotides circumvents synthesis limitations and enables long continuous DNA sequences to be probed. [ABSTRACT FROM AUTHOR]

The specific hybridization of complementary sequences is an essential property of nucleic acids, enabling diverse biological and biotechnological reactions and functions. However, the specificity of nucleic acid hybridization is compromised for long strands, except near the melting temperature. Here, we analytically derived the thermodynamic properties of a hybridization probe that would enable near-optimal single-base discrimination and perform robustly across diverse temperature, salt and concentration conditions. We rationally designed 'toehold exchange' probes that approximate these properties, and comprehensively tested them against five different DNA targets and 55 spurious analogues with energetically representative single-base changes (replacements, deletions and insertions). These probes produced discrimination factors between 3 and 100+ (median, 26). Without retuning, our probes function robustly from 10 °C to 37 °C, from 1 mM Mg2+ to 47 mM Mg2+, and with nucleic acid concentrations from 1 nM to 5 µM. Experiments with RNA also showed effective single-base change discrimination. [ABSTRACT FROM AUTHOR]

The potential of DNA as an information storage medium is rapidly growing due to advances in DNA synthesis and sequencing. However, the chemical stability of DNA challenges the complete erasure of information encoded in DNA sequences. Here, we encode information in a DNA information solution, a mixture of true message- and false message-encoded oligonucleotides, and enables rapid and permanent erasure of information. True messages are differentiated by their hybridization to a "truth marker" oligonucleotide, and only true messages can be read; binding of the truth marker can be effectively randomized even with a brief exposure to the elevated temperature. We show 8 separate bitmap images can be stably encoded and read after storage at 25 °C for 65 days with an average of over 99% correct information recall, which extrapolates to a half-life of over 15 years at 25 °C. Heating to 95 °C for 5 minutes, however, permanently erases the message. The chemical stability of DNA makes complete erasure of DNA-encoded data difficult. Here the authors mix true and false messages, differentiated by whether a truth marker oligo is bound to it, and show that brief exposure to elevated temperatures randomizes the binding of truth markers preventing data recovery. [ABSTRACT FROM AUTHOR]

In the version of this Article originally published, owing to a technical error, the Life Sciences Reporting Summary was not included; this summary is now available.

Rare DNA-sequence variants hold important clinical and biological information, but existing detection techniques are expensive, complex, allele-specific, or don't allow for significant multiplexing. Here, we report a temperature-robust polymerase-chain-reaction method, which we term blocker displacement amplification (BDA), that selectively amplifies all sequence variants, including single-nucleotide variants (SNVs), within a roughly 20-nucleotide window by 1,000-fold over wild-type sequences. This allows for easy detection and quantitation of hundreds of potential variants originally at ≤0.1% in allele frequency. BDA is compatible with inexpensive thermocycler instrumentation and employs a rationally designed competitive hybridization reaction to achieve comparable enrichment performance across annealing temperatures ranging from 56 °C to 64 °C. To show the sequence generality of BDA, we demonstrate enrichment of 156 SNVs and the reliable detection of single-digit copies. We also show that the BDA detection of rare driver mutations in cell-free DNA samples extracted from the blood plasma of lung-cancer patients is highly consistent with deep sequencing using molecular lineage tags, with a receiver operator characteristic accuracy of 95%.