A high-throughput assay for quantitative measurement of PCR errors

Correcting PCR amplification errors in unique molecular identifiers to generate accurate numbers of sequencing molecules

Unique molecular identifiers are random oligonucleotide sequences that remove PCR amplification biases. However, the impact that PCR associated sequencing errors have on the accuracy of generating absolute counts of RNA molecules is underappreciated. We show that PCR errors are a source of inaccuracy in both bulk and single-cell sequencing data, and synthesizing unique molecular identifiers using homotrimeric nucleotide blocks provides an error-correcting solution that allows absolute counting of sequenced molecules.

Foldback-crRNA-Enhanced CRISPR/Cas13a System (FCECas13a) Enables Direct Detection of Ultrashort sncRNA

The CRISPR/Cas13a system has promising applications in clinical small noncoding RNA (sncRNA) detection because it is free from the interference of genomic DNA. However, detecting ultrashort sncRNAs (less than 20 nucleotides) has been challenging because the Cas13a nuclease requires longer crRNA-target RNA hybrids to be activated. Here, we report the development of a foldback-crRNA-enhanced CRISPR/Cas13a (FCECas13a) system that overcomes the limitations of the current CRISPR/Cas13a system in detecting ultrashort sncRNAs. The FCECas13a system employs a 3'-terminal foldback crRNA that hybridizes with the target ultrashort sncRNA, forming a double strand that "tricks" the Cas13a nuclease into activating the HEPN structural domain and generating trans-cleavage activity. The FCECas13a system can accurately detect miRNA720 (a sncRNA currently known as tRNA-derived small RNA), which is only 17 nucleotides long and has a concentration as low as 15 fM within 20 min. This FCECas13a system opens new avenues for ultrashort sncRNA detection with significant implications for basic biological research, disease prognosis, and molecular diagnosis.

A digital twin for DNA data storage based on comprehensive quantification of errors and biases

Archiving data in synthetic DNA offers unprecedented storage density and longevity. Handling and storage introduce errors and biases into DNA-based storage systems, necessitating the use of Error Correction Coding (ECC) which comes at the cost of added redundancy. However, insufficient data on these errors and biases, as well as a lack of modeling tools, limit data-driven ECC development and experimental design. In this study, we present a comprehensive characterisation of the error sources and biases present in the most common DNA data storage workflows, including commercial DNA synthesis, PCR, decay by accelerated aging, and sequencing-by-synthesis. Using the data from 40 sequencing experiments, we build a digital twin of the DNA data storage process, capable of simulating state-of-the-art workflows and reproducing their experimental results. We showcase the digital twin's ability to replace experiments and rationalize the design of redundancy in two case studies, highlighting opportunities for tangible cost savings and data-driven ECC development.

Liquid Biopsies in Lung Cancer

As lung cancer has the highest cancer-specific mortality rates worldwide, there is an urgent need for new therapeutic and diagnostic approaches to detect early-stage tumors and to monitor their response to the therapy. In addition to the well-established tissue biopsy analysis, liquid-biopsy-based assays may evolve as an important diagnostic tool. The analysis of circulating tumor DNA (ctDNA) is the most established method, followed by other methods such as the analysis of circulating tumor cells (CTCs), microRNAs (miRNAs), and extracellular vesicles (EVs). Both PCR- and NGS-based assays are used for the mutational assessment of lung cancer, including the most frequent driver mutations. However, ctDNA analysis might also play a role in monitoring the efficacy of immunotherapy and its recent accomplishments in the landscape of state-of-the-art lung cancer therapy. Despite the promising aspects of liquid-biopsy-based assays, there are some limitations regarding their sensitivity (risk of false-negative results) and specificity (interpretation of false-positive results). Hence, further studies are needed to evaluate the usefulness of liquid biopsies for lung cancer. Liquid-biopsy-based assays might be integrated into the diagnostic guidelines for lung cancer as a tool to complement conventional tissue sampling.

Phasing of de novo mutations using a scaled-up multiple amplicon long-read sequencing approach

De novo mutations (DNMs) play an important role in severe genetic disorders that reduce fitness. To better understand their role in disease, it is important to determine the parent-of-origin and timing of mutational events that give rise to these mutations, especially in sex-specific developmental disorders such as male infertility. However, currently available short-read sequencing approaches are not ideally suited for phasing, as this requires long continuous DNA strands that span both the DNM and one or more informative single-nucleotide polymorphisms. To overcome these challenges, we optimized and implemented a multiplexed long-read sequencing approach using Oxford Nanopore technologies MinION platform. We focused on improving target amplification, integrating long-read sequenced data with high-quality short-read sequence data, and developing an anchored phasing computational method. This approach handled the inherent phasing challenges of long-range target amplification and the normal accumulation of sequencing error associated with long-read sequencing. In total, 77 of 109 DNMs (71%) were successfully phased and parent-of-origin identified. The majority of phased DNMs were prezygotic (90%), the accuracy of which is highlighted by an average mutant allele frequency of 49.6% and standard error of 0.84%. This study demonstrates the benefits of employing an integrated short-read and long-read sequencing approach for large-scale DNM phasing.

Prognostic Value of Circulating Tumor DNA (ctDNA) in Oncogene-Driven NSCLC: Current Knowledge and Future Perspectives

Simple Summary

Personalized medicine has significantly changed the clinical outcome of oncogene-driven non-small cell lung cancer (NSCLC) due to the efficacy of molecular targeted therapies. Despite the advances in the management of this group of patients, the need for powerful biomarkers with the potential for a real-time assessment of the tumor genomic profile as well as for detecting and monitoring minimal residual disease (MRD) remains unmet. The aim of this article is to present the current knowledge and the future perspectives regarding the prognostic value of ctDNA in NSCLC, focusing on the most common druggable driver mutations, including those in epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), c-ros oncogene 1 (ROS1), rearranged during transfection (RET), kirsten rat sarcoma virus (KRAS), B-Raf proto-oncogene (BRAF), and mesenchymal epithelial transition factor receptor (MET) genes.

Abstract

As we enter an unprecedented era of personalized medicine, molecular targeted therapies have the potential to induce improved survival outcome in patients with non-small cell lung cancer (NSCLC). However, a significant percentage of oncogene-driven NSCLC patients will relapse even after definitive treatment, whereas chronic and durable response to targeted therapies is a less common event in advanced-stage lung cancer. This phenomenon could be attributed to minimal residual disease (MRD), defined as a population of disseminated tumor cells that survive during the course or after treatment, eventually leading to recurrence and limiting patient survival. Circulating tumor DNA (ctDNA) is a powerful biomarker for MRD detection and monitoring and is a non-invasive approach of treating cancer, and especially NSCLC, based on a real-time assessment of the tumor genomic landscape. In this review, we present the key findings of studies that have used ctDNA with regard to its prognostic value and in respect to the most common druggable driver mutations of genes in NSCLC, such as epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), c-ros oncogene 1 (ROS1), rearranged during transfection (RET), Kirsten rat sarcoma virus (KRAS), B-Raf proto-oncogene (BRAF), and mesenchymal epithelial transition factor receptor (MET).

Benchmarking and optimization of a high-throughput sequencing based method for transgene sequence variant analysis in biotherapeutic cell line development

In recent years, High-Throughput Sequencing (HTS) based methods to detect mutations in biotherapeutic transgene products have become a key quality step deployed during the development of manufacturing cell line clones. Previously we reported on a higher throughput, rapid mutation detection method based on amplicon sequencing (targeting transgene RNA) and detailed its implementation to facilitate cell line clone selection. By gaining experience with our assay in a diverse set of cell line development programs, we improved the computational analysis as well as experimental protocols. Here we report on these improvements as well as on a comprehensive benchmarking of our assay. We evaluated assay performance by mixing amplicon samples of a verified mutated antibody clone with a non-mutated antibody clone to generate spike-in mutations from ∼60% down to ∼0.3% frequencies. We subsequently tested the effect of 16 different sample and HTS library preparation protocols on the assay's ability to quantify mutations and on the occurrence of false-positive background error mutations (artifacts). Our evaluation confirmed assay robustness, established a high confidence limit of detection of ∼0.6%, and identified protocols that reduce error levels thereby significantly reducing a source of false positives that bottlenecked the identification of low-level true mutations.

Genotypic Characterization of Clinical Klebsiella spp. Isolates Collected From Patients With Suspected Community-Onset Sepsis, Sweden

Klebsiella is a genus of Gram-negative bacteria known to be opportunistic pathogens that may cause a variety of infections in humans. Highly drug-resistant Klebsiella species, especially K. pneumoniae, have emerged rapidly and are becoming a major concern in clinical management. Although K. pneumoniae is considered the most important pathogen within the genus, the true clinical significance of the other species is likely underrecognized due to the inability of conventional microbiological methods to distinguish between the species leading to high rates of misidentification. Bacterial whole-genome sequencing (WGS) enables precise species identification and characterization that other technologies do not allow. Herein, we have characterized the diversity and traits of Klebsiella spp. in community-onset infections by WGS of clinical isolates (n = 105) collected during a prospective sepsis study in Sweden. The sequencing revealed that 32 of the 82 isolates (39.0%) initially identified as K. pneumoniae with routine microbiological methods based on cultures followed by matrix-assisted laser desorption-time of flight mass spectrometry (MALDI-TOF MS) had been misidentified. Of these, 23 were identified as Klebsiella variicola and nine as other members of the K. pneumoniae complex. Comparisons of the number of resistance genes showed that significantly fewer resistance genes were detected in Klebsiella oxytoca compared to K. pneumoniae and K. variicola (both values of p < 0.001). Moreover, a high proportion of the isolates within the K. pneumoniae complex were predicted to be genotypically multidrug-resistant (MDR; 79/84, 94.0%) in contrast to K. oxytoca (3/16, 18.8%) and Klebsiella michiganensis (0/4, 0.0%). All isolates predicted as genotypically MDR were found to harbor the combination of β-lactam, fosfomycin, and quinolone resistance markers. Multi-locus sequence typing (MLST) revealed a high diversity of sequence types among the Klebsiella spp. with ST14 (10.0%) and ST5429 (10.0%) as the most prevalent ones for K. pneumoniae, ST146 for K. variicola (12.0%), and ST176 for K. oxytoca (25.0%). In conclusion, the results from this study highlight the importance of using high-resolution genotypic methods for identification and characterization of clinical Klebsiella spp. isolates. Our findings indicate that infections caused by other members of the K. pneumoniae complex than K. pneumoniae are a more common clinical problem than previously described, mainly due to high rates of misidentifications.

An ultra-sensitive T-cell receptor detection method for TCR-Seq and RNA-Seq data

MOTIVATION

T-cell receptors (TCRs) function to recognize antigens and play vital roles in T-cell immunology. Surveying TCR repertoires by characterizing complementarity-determining region 3 (CDR3) is a key issue. Due to the high diversity of CDR3 and technological limitation, accurate characterization of CDR3 repertoires remains a great challenge.

RESULTS

We propose a computational method named CATT for ultra-sensitive and precise TCR CDR3 sequences detection. CATT can be applied on TCR sequencing, RNA-Seq and single-cell TCR(RNA)-Seq data to characterize CDR3 repertoires. CATT integrated de Bruijn graph-based micro-assembly algorithm, data-driven error correction model and Bayesian inference algorithm, to self-adaptively and ultra-sensitively characterize CDR3 repertoires with high performance. Benchmark results of datasets from in silico and experimental data demonstrated that CATT showed superior recall and precision compared with existing tools, especially for data with short read length and small size and single-cell sequencing data. Thus, CATT will be a useful tool for TCR analysis in researches of cancer and immunology.

AVAILABILITY AND IMPLEMENTATION

http://bioinfo.life.hust.edu.cn/CATT or https://github.com/GuoBioinfoLab/CATT.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Liquid Biopsies Using Circulating Tumor DNA in Non-Small Cell Lung Cancer

Liquid biopsies for the diagnosis and treatment of lung cancer have developed rapidly, driven primarily by technical advances in sensitivity to detect circulating tumor DNA (ctDNA). Still, technical limitations such as the challenge of detecting low-level ctDNA variants and distinguishing tumor-related variants from clonal hematopoiesis remain. With further technical advancements, new applications for ctDNA analysis are emerging including detection of post-treatment molecular residual disease (MRD), clinical trial selection, and early cancer detection. This chapter reviews the current state of ctDNA testing in NSCLC, the underlying technological advances enabling ctDNA detection, and the potential to expand ctDNA analysis to new applications.

A novel virtual barcode strategy for accurate panel-wide variant calling in circulating tumor DNA

Background

Hybrid capture-based next-generation sequencing of DNA has been widely applied in the detection of circulating tumor DNA (ctDNA). Various methods have been proposed for ctDNA detection, but low-allelic-fraction (AF) variants are still a great challenge. In addition, no panel-wide calling algorithm is available, which hiders the full usage of ctDNA based ‘liquid biopsy’. Thus, we developed the VBCALAVD (Virtual Barcode-based Calling Algorithm for Low Allelic Variant Detection) in silico to overcome these limitations.

Results

Based on the understanding of the nature of ctDNA fragmentation, a novel platform-independent virtual barcode strategy was established to eliminate random sequencing errors by clustering sequencing reads into virtual families. Stereotypical mutant-family-level background artifacts were polished by constructing AF distributions. Three additional robust fine-tuning filters were obtained to eliminate stochastic mutant-family-level noises. The performance of our algorithm was validated using cell-free DNA reference standard samples (cfDNA RSDs) and normal healthy cfDNA samples (cfDNA controls). For the RSDs with AFs of 0.1, 0.2, 0.5, 1 and 5%, the mean F1 scores were 0.43 (0.25~0.56), 0.77, 0.92, 0.926 (0.86~1.0) and 0.89 (0.75~1.0), respectively, which indicates that the proposed approach significantly outperforms the published algorithms. Among controls, no false positives were detected. Meanwhile, characteristics of mutant-family-level noise and quantitative determinants of divergence between mutant-family-level noises from controls and RSDs were clearly depicted.

Conclusions

Due to its good performance in the detection of low-AF variants, our algorithm will greatly facilitate the noninvasive panel-wide detection of ctDNA in research and clinical settings. The whole pipeline is available at https://github.com/zhaodalv/VBCALAVD.

smCounter2: an accurate low-frequency variant caller for targeted sequencing data with unique molecular identifiers

MOTIVATION

Low-frequency DNA mutations are often confounded with technical artifacts from sample preparation and sequencing. With unique molecular identifiers (UMIs), most of the sequencing errors can be corrected. However, errors before UMI tagging, such as DNA polymerase errors during end repair and the first PCR cycle, cannot be corrected with single-strand UMIs and impose fundamental limits to UMI-based variant calling.

RESULTS

We developed smCounter2, a UMI-based variant caller for targeted sequencing data and an upgrade from the current version of smCounter. Compared to smCounter, smCounter2 features lower detection limit that decreases from 1 to 0.5%, better overall accuracy (particularly in non-coding regions), a consistent threshold that can be applied to both deep and shallow sequencing runs, and easier use via a Docker image and code for read pre-processing. We benchmarked smCounter2 against several state-of-the-art UMI-based variant calling methods using multiple datasets and demonstrated smCounter2's superior performance in detecting somatic variants. At the core of smCounter2 is a statistical test to determine whether the allele frequency of the putative variant is significantly above the background error rate, which was carefully modeled using an independent dataset. The improved accuracy in non-coding regions was mainly achieved using novel repetitive region filters that were specifically designed for UMI data.

AVAILABILITY AND IMPLEMENTATION

The entire pipeline is available at https://github.com/qiaseq/qiaseq-dna under MIT license.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

TILLING by Sequencing: A Successful Approach to Identify Rare Alleles in Soybean Populations

Soybean seeds produce valuable protein that is a major component of livestock feed. However, soybean seeds also contain the anti-nutritional raffinose family oligosaccharides (RFOs) raffinose and stachyose, which are not digestible by non-ruminant animals. This requires the proportion of soybean meal in the feed to be limited, or risk affecting animal growth rate or overall health. While reducing RFOs in soybean seed has been a goal of soybean breeding, efforts are constrained by low genetic variability for carbohydrate traits and the difficulty in identifying these within the soybean germplasm. We used reverse genetics Targeting Induced Local Lesions in Genomes (TILLING)-by-sequencing approach to identify a damaging polymorphism that results in a missense mutation in a conserved region of the RAFFINOSE SYNTHASE3 gene. We demonstrate that this mutation, when combined as a double mutant with a previously characterized mutation in the RAFFINOSE SYNTHASE2 gene, eliminates nearly 90% of the RFOs in soybean seed as a proportion of the total seeds carbohydrates, and results in increased levels of sucrose. This represents a proof of concept for TILLING by sequencing in soybean.

Deep sequencing of B cell receptor repertoire

Immune repertoire is a collection of enormously diverse adaptive immune cells within an individual. As the repertoire shapes and represents immunological conditions, identification of clones and characterization of diversity are critical for understanding how to protect ourselves against various illness such as infectious diseases and cancers. Over the past several years, fast growing technologies for high throughput sequencing have facilitated rapid advancement of repertoire research, enabling us to observe the diversity of repertoire at an unprecedented level. Here, we focus on B cell receptor (BCR) repertoire and review approaches to B cell isolation and sequencing library construction. These experiments should be carefully designed according to BCR regions to be interrogated, such as heavy chain full length, complementarity determining regions, and isotypes. We also highlight preprocessing steps to remove sequencing and PCR errors with unique molecular index and bioinformatics techniques. Due to the nature of massive sequence variation in BCR, caution is warranted when interpreting repertoire diversity from error-prone sequencing data. Furthermore, we provide a summary of statistical frameworks and bioinformatics tools for clonal evolution and diversity. Finally, we discuss limitations of current BCR-seq technologies and future perspectives on advances in repertoire sequencing.

dCas9-mediated Nanoelectrokinetic Direct Detection of Target Gene for Liquid Biopsy

The-state-of-the-art bio- and nanotechnology have opened up an avenue to noninvasive liquid biopsy for identifying diseases from biomolecules in bloodstream, especially DNA. In this work, we combined sequence-specific-labeling scheme using mutated clustered regularly interspaced short palindromic repeats associated protein 9 without endonuclease activity (CRISPR/dCas9) and ion concentration polarization (ICP) phenomenon as a mechanism to selectively preconcentrate targeted DNA molecules for rapid and direct detection. Theoretical analysis on ICP phenomenon figured out a critical mobility, elucidating two distinguishable concentrating behaviors near a nanojunction, a stacking and a propagating behavior. Through the modulation of the critical mobility to shift those behaviors, the C-C chemokine receptor type 5 ( CCR5) sequences were optically detected without PCR amplification. Conclusively, the proposed dCas9-mediated genetic detection methodology based on ICP would provide rapid and accurate micro/nanofluidic platform of liquid biopsies for disease diagnostics.

A droplet microfluidic platform for efficient enzymatic chromatin digestion enables robust determination of nucleosome positioning

The first step in chromatin-based epigenetic assays involves the fragmentation of chromatin to facilitate precise genomic localization of the associated DNA. Here, we report the development of a droplet microfluidic device that can rapidly and efficiently digest chromatin into single nucleosomes starting from whole-cell input material offering simplified and automated processing compared to conventional manual preparation. We demonstrate the digestion of chromatin from 2500-125 000 Jurkat cells using micrococcal nuclease for enzymatic processing. We show that the yield of mononucleosomal DNA can be optimized by controlling enzyme concentration and incubation time, with resulting mononucleosome yields exceeding 80%. Bioinformatic analysis of sequenced mononucleosomal DNA (MNase-seq) indicated a high degree of reproducibility and concordance (97-99%) compared with conventionally processed preparations. Our results demonstrate the feasibility of robust and automated nucleosome preparation using a droplet microfluidic platform for nucleosome positioning and downstream epigenomic assays.

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.

Next-generation sequencing-based analysis of reverse transcriptase fidelity

In this study, we devised a simple and rapid method to analyze fidelity of reverse transcriptase (RT) using next-generation sequencing (NGS). The method comprises a cDNA synthesis reaction from standard RNA with a primer containing a tag of 14 randomized bases and the RT to be tested, PCR using high-fidelity DNA polymerase, and NGS. By comparing the sequence of each read with the reference sequence, mutations were identified. The mutation can be identified to be due to an error introduced by either cDNA synthesis, PCR, or NGS based on whether the sequence reads with the same tag contain the same mutation or not. The error rates in cDNA synthesis with Moloney murine leukemia virus (MMLV) RT thermostable variant MM4 or the recently developed 16-tuple variant of family B DNA polymerase with RT activity, RTX, from Thermococcus kodakarensis, were 0.75-1.0 × 10^-4 errors/base, while that in the reaction with the wild-type human immunodeficiency virus type 1 (HIV-1) RT was 2.6 × 10^-4 errors/base. Overall, our method could precisely evaluate the fidelity of various RTs with different reaction conditions in a high-throughput manner without the use of expensive optics and troublesome adaptor ligation.