Sequencing Artifacts Research Articles

Identification of genetic variants controlling RNA editing and their effect on RNA structure stabilization.

Post-transcriptional modification of RNA (RNA editing, RNAe) results in differences between the RNA transcript and the genomic DNA sequence (RDD). Enzymatic modification of adenosine to inosine (A2I) by ADAR is the most studied type of RNAe. However, few genetic association studies with A2I RNAe events have been conducted. Some studies have analyzed the inter-population RNAe-QTL diversity in humans, but the sample size of these studies was limited. Other types of RNA and DNA differences have been reported but are largely understudied. Here, we report a comprehensive analysis of all types of RDD, based on two independent datasets. We found that A2I was by far the most observed type of RDD. Moreover, manual curation suggests that A2I is likely the only enzymatically driven RNAe type observed in blood derived DNA, all other non-A2I RDD could either be attributed to sequencing and processing artifacts, or are a result of somatic DNA rearrangements. We then conducted an in-cis genetic association study and identified 472 genetic associations (RNAe-QTL), that were replicated in both datasets. We confirm the potential effect of the RNAe-QTL on RNA structure by showing that allele specific RNAe occurs in heterozygotes. Although the generally assumed function of RNAe is to destabilize double stranded RNA structure, we found clear evidence for the potential additional involvement of RNAe in maintaining RNA hairpin that has been altered by the RNAe-QTL. Our study confirms, in two independent datasets, the potential role of RNAe in maintaining RNA structure in the presence of genetic variation.

A fully-automated method discovers loss of mouse-lethal and human-monogenic disease genes in 58 mammals.

Gene losses provide an insightful route for studying the morphological and physiological adaptations of species, but their discovery is challenging. Existing genome annotation tools focus on annotating intact genes and do not attempt to distinguish nonfunctional genes from genes missing annotation due to sequencing and assembly artifacts. Previous attempts to annotate gene losses have required significant manual curation, which hampers their scalability for the ever-increasing deluge of newly sequenced genomes. Using extreme sequence erosion (amino acid deletions and substitutions) and sister species support as an unambiguous signature of loss, we developed an automated approach for detecting high-confidence gene loss events across a species tree. Our approach relies solely on gene annotation in a single reference genome, raw assemblies for the remaining species to analyze, and the associated phylogenetic tree for all organisms involved. Using human as reference, we discovered over 400 unique human ortholog erosion events across 58 mammals. This includes dozens of clade-specific losses of genes that result in early mouse lethality or are associated with severe human congenital diseases. Our discoveries yield intriguing potential for translational medical genetics and evolutionary biology, and our approach is readily applicable to large-scale genome sequencing efforts across the tree of life.

54. Tool for filtering FFPE sequence artifacts from paired-end sequencing data

54. Tool for filtering FFPE sequence artifacts from paired-end sequencing data

Needlestack: an ultra-sensitive variant caller for multi-sample next generation sequencing data.

The emergence of next-generation sequencing (NGS) has revolutionized the way of reaching a genome sequence, with the promise of potentially providing a comprehensive characterization of DNA variations. Nevertheless, detecting somatic mutations is still a difficult problem, in particular when trying to identify low abundance mutations, such as subclonal mutations, tumour-derived alterations in body fluids or somatic mutations from histological normal tissue. The main challenge is to precisely distinguish between sequencing artefacts and true mutations, particularly when the latter are so rare they reach similar abundance levels as artefacts. Here, we present needlestack, a highly sensitive variant caller, which directly learns from the data the level of systematic sequencing errors to accurately call mutations. Needlestack is based on the idea that the sequencing error rate can be dynamically estimated from analysing multiple samples together. We show that the sequencing error rate varies across alterations, illustrating the need to precisely estimate it. We evaluate the performance of needlestack for various types of variations, and we show that needlestack is robust among positions and outperforms existing state-of-the-art method for low abundance mutations. Needlestack, along with its source code is freely available on the GitHub platform: https://github.com/IARCbioinfo/needlestack.

Development of a massively parallel, genotyping-by-sequencing assay in American badger (Taxidea taxus) highlights the need for careful validation when working with low template DNA

Non-invasive DNA sampling to identify and enumerate species is critical to population monitoring and for developing effective management strategies. However, individual DNA identification is often limited by degraded and low template DNA (LT-DNA) that routinely yields partial profiles prone to technical artifacts, thus limiting their utility/reliability. Massively parallel, genotyping-by-sequencing (GBS) assays present an opportunity to amplify not only a large suite of molecular markers simultaneously, providing higher resolution to identify individuals, but also higher levels of sequence redundancy to enable quality metric evaluations of profiles from LT-DNA. Taxidea taxus jacksoni is an endangered badger subspecies in Canada, with low levels of genetic diversity, complicating individual identifications from closely related DNA sequences. Challenges arise from the small number of hairs collected from snag traps set in badger burrows that rarely provide full profiles. We designed a GBS assay to obtain microsatellite profiles compatible with pre-existing databases generated with conventional capillary electrophoresis (CE) genotyping. We assessed the assay’s reproducibility via a dilution series to mimic LT-DNA and tested if the assay produced similar CE-generated results. While GBS offers the potential to genotype large numbers of individuals and markers at the same time, we found low concordance between GBS- and CE-based genotypes from DNA templates < 250 pg. We recommend existing wildlife genetic databases focus on tetra-nucleotide microsatellite or SNP markers to reduce or eliminate sequencing artifacts (i.e., stutter) that present challenges for GBS genotypes from degraded and LT-DNA, and the use of sample replicates to form consensus genotypes.

Family reunion via error correction: an efficient analysis of duplex sequencing data

BackgroundDuplex sequencing is the most accurate approach for identification of sequence variants present at very low frequencies. Its power comes from pooling together multiple descendants of both strands of original DNA molecules, which allows distinguishing true nucleotide substitutions from PCR amplification and sequencing artifacts. This strategy comes at a cost—sequencing the same molecule multiple times increases dynamic range but significantly diminishes coverage, making whole genome duplex sequencing prohibitively expensive. Furthermore, every duplex experiment produces a substantial proportion of singleton reads that cannot be used in the analysis and are thrown away.ResultsIn this paper we demonstrate that a significant fraction of these reads contains PCR or sequencing errors within duplex tags. Correction of such errors allows “reuniting” these reads with their respective families increasing the output of the method and making it more cost effective.ConclusionsWe combine an error correction strategy with a number of algorithmic improvements in a new version of the duplex analysis software, Du Novo 2.0. It is written in Python, C, AWK, and Bash. It is open source and readily available through Galaxy, Bioconda, and Github: https://github.com/galaxyproject/dunovo.

The potential of combined mutation sequencing of plasma circulating cell-free DNA and matched white blood cells for treatment response prediction.

Highly sensitive mutation detection methods enable the application of circulating cell-free DNA for molecular tumor profiling. Recent studies revealed that sequencing artifacts, germline variants, and clonal hematopoiesis confound the interpretation of sequencing results and complicate subsequent treatment decision making and disease monitoring. Parallel sequencing of matched white blood cells promises to overcome these issues and enables appropriate variant calling. Comment on: https://doi.org/10.1002/1878-0261.12617.

The stochastic nature of errors in next-generation sequencing of circulating cell-free DNA.

Challenges with distinguishing circulating tumor DNA (ctDNA) from next-generation sequencing (NGS) artifacts limits variant searches to established solid tumor mutations. Here we show early and random PCR errors are a principal source of NGS noise that persist despite duplex molecular barcoding, removal of artifacts due to clonal hematopoiesis of indeterminate potential, and suppression of patterned errors. We also demonstrate sample duplicates are necessary to eliminate the stochastic noise associated with NGS. Integration of sample duplicates into NGS analytics may broaden ctDNA applications by removing NGS-related errors that confound identification of true very low frequency variants during searches for ctDNA without a priori knowledge of specific mutations to target.

Systematic Nucleotide Exchange Analysis of ESTs From the Human Cancer Genome Project Report: Origins of 347 Unknown ESTs Indicate Putative Transcription of Non-Coding Genomic Regions.

Expressed sequence tags (ESTs) provide an imprint of cellular RNA diversity irrespectively of sequence homology with template genomes. NCBI databases include many unknown RNAs from various normal and cancer cells. These are usually ignored assuming sequencing artefacts or contamination due to their lack of sequence homology with template DNA. Here, we report genomic origins of 347 ESTs previously assumed artefacts/unknown, from the FAPESP/LICR Human Cancer Genome Project. EST template detection uses systematic nucleotide exchange analyses called swinger transformations. Systematic nucleotide exchanges replace systematically particular nucleotides with different nucleotides. Among 347 unknown ESTs, 51 ESTs match mitogenome transcription, 17 and 2 ESTs are from nuclear chromosome non-coding regions, and uncharacterized nuclear genes. Identified ESTs mapped on 205 protein-coding genes, 10 genes had swinger RNAs in several biosamples. Whole cell transcriptome searches for 17 ESTs mapping on non-coding regions confirmed their transcription. The 10 swinger-transcribed genes identified more than once associate with cancer induction and progression, suggesting swinger transformation occurs mainly in highly transcribed genes. Swinger transformation is a unique method to identify noncanonical RNAs obtained from NGS, which identifies putative ncRNA transcribed regions. Results suggest that swinger transcription occurs in highly active genes in normal and genetically unstable cancer cells.

Targeted sequencing analysis of cell-free DNA from metastatic non-small-cell lung cancer patients: clinical and biological implications.

BackgroundSequencing artifacts, clonal hematopoietic mutations of indeterminate potential (CHIP) and tumor heterogeneity have been hypothesized to contribute to the low concordance between tissue and cell-free DNA (cfDNA) molecular profiling with targeted sequencing.MethodsWe analyzed by targeted sequencing cfDNA from 30 healthy individuals, and cfDNA and matched tumor samples from 30 EGFR-mutant and 77 EGFR wild-type metastatic non-small-cell lung cancer (mNSCLC) patients. Discordant cases were solved by droplet digital PCR (ddPCR).ResultsBy testing cfDNA from healthy donors, we developed an algorithm to recognize sequencing artifacts. Applying this method to cfDNA from mNSCLC patients, EGFR mutations were detected with a good sensitivity (76.7%) and specificity (97.4%). In contrast, sensitivity and specificity for KRAS variants were 61.5% and 93.8%, respectively. All EGFR and KRAS variants detected in plasma but not in tissue were confirmed by ddPCR, thus excluding sequencing artifacts. In a fraction of cases, KRAS mutations found in plasma samples were confirmed in tumor tissue suggesting tumor heterogeneity. KRAS variants were found to be more likely sub-clonal as compared with EGFR mutations, and a correlation between clonal origin and frequency of detection in plasma was found. In a case with both EGFR and KRAS variants in cfDNA, we could demonstrate the presence of the KRAS variant in tumor tissue associated with lack of response to tyrosine kinase inhibitors (TKIs).ConclusionsAlthough sequencing artifacts can be identified in targeted sequencing of cfDNA, tumor heterogeneity and CHIP are likely to influence the concordance between plasma and tissue testing.

Sequencing artifacts derived from a library preparation method using enzymatic fragmentation.

DNA fragmentation is a fundamental step during library preparation in hybridization capture-based, short-read sequencing. Ultra-sonication has been used thus far to prepare DNA of an appropriate size, but this method is associated with a considerable loss of DNA sample. More recently, studies have employed library preparation methods that rely on enzymatic fragmentation with DNA endonucleases to minimize DNA loss, particularly in nano-quantity samples. Yet, despite their wide use, the effect of enzymatic fragmentation on the resultant sequences has not been carefully assessed. Here, we used pairwise comparisons of somatic variants of the same tumor DNA samples prepared using ultrasonic and enzymatic fragmentation methods. Our analysis revealed a substantially larger number of recurrent artifactual SNVs/indels in endonuclease-treated libraries as compared with those created through ultrasonication. These artifacts were marked by palindromic structure in the genomic context, positional bias in sequenced reads, and multi-nucleotide substitutions. Taking advantage of these distinctive features, we developed a filtering algorithm to distinguish genuine somatic mutations from artifactual noise with high specificity and sensitivity. Noise cancelling recovered the composition of the mutational signatures in the tumor samples. Thus, we provide an informatics algorithm as a solution to the sequencing errors produced as a consequence of endonuclease-mediated fragmentation, highlighted for the first time in this study.

Characterization of FFPE-induced bacterial DNA damage and development of a repair method.

Formalin-fixed, paraffin-embedded (FFPE) specimens have huge potential as source material in the field of human microbiome research. However, the effects of FFPE processing on bacterial DNA remain uncharacterized. Any effects are relevant for microbiome studies, where DNA template is often minimal and sequences studied are not limited to one genome. As such, we aimed to both characterize this FFPE-induced bacterial DNA damage and develop strategies to reduce and repair this damage. Our analyses indicate that bacterial FFPE DNA is highly fragmented, a poor template for PCR, crosslinked and bears sequence artefacts derived predominantly from oxidative DNA damage. Two strategies to reduce this damage were devised – an optimized decrosslinking procedure reducing sequence artefacts generated by high-temperature incubation, and secondly, an in vitro reconstitution of the base excision repair pathway. As evidenced by whole genome sequencing, treatment with these strategies significantly increased fragment length, reduced the appearance of sequence artefacts and improved the sequencing readability of bacterial and mammalian FFPE DNA. This study provides a new understanding of the condition of bacterial DNA in FFPE specimens and how this impacts downstream analyses, in addition to a strategy to improve the sequencing quality of bacterial and possibly mammalian FFPE DNA.

An optimized BRCA1/2 next-generation sequencing for different clinical sample types.

ObjectiveA simultaneous detection of germline and somatic mutations in ovarian cancer (OC) using tumor materials is considered to be cost-effective for BRCA1/2 testing. However, there are limited studies of the analytical performances according to various sample types. The aim of this study is to propose a strategy for routine BRCA1/2 next-generation sequencing (NGS) screening based on analytical performance according to different sample types.MethodsWe compared BRCA1/2 NGS screening assay using buffy coat, fresh-frozen (FF) and formalin-fixed paraffin-embedded (FFPE) from 130 samples.ResultsThe rate of repeated tests in a total of buffy coat, FF and FFPE was 0%, 8%, and 34%, respectively. The accuracy of BRCA1/2 NGS testing was 100.0%, 99.9% and 99.9% in buffy coat, FFPE and FF, respectively. However, due to the presence of variant allele frequency (VAF) shifted heterozygous variants, tumor materials (FFPE and FF) showed lower sensitivity (95.5%–99.0%) than buffy coat (100%). Furthermore, FFPE showed 51.4% of the positive predictive value (PPV) on account of sequence artifacts. When performed in the post-filtration process, PPV was increased by approximately 20% in FFPE. Buffy coat showed 100% of sensitivity, specificity and accuracy in BRCA1/2 NGS test.ConclusionsOn the comparison of the analytical performance according to different sample types, the buffy coat was not affected by sequencing artifacts and VAF shifted variants. Therefore, the blood test should be given priority in detecting germline BRCA1/2 mutation, and tumor materials could be suitable to detect somatic mutations in OC patients without identifying germline BRCA1/2 mutation.

UMI-Gen: A UMI-based read simulator for variant calling evaluation in paired-end sequencing NGS libraries

MotivationWith Next Generation Sequencing becoming more affordable every year, NGS technologies asserted themselves as the fastest and most reliable way to detect Single Nucleotide Variants (SNV) and Copy Number Variations (CNV) in cancer patients. These technologies can be used to sequence DNA at very high depths thus allowing to detect abnormalities in tumor cells with very low frequencies. Multiple variant callers are publicly available and are usually efficient at calling out variants. However, when frequencies begin to drop under 1%, the specificity of these tools suffers greatly as true variants at very low frequencies can be easily confused with sequencing or PCR artifacts. The recent use of Unique Molecular Identifiers (UMI) in NGS experiments has offered a way to accurately separate true variants from artifacts. UMI-based variant callers are slowly replacing raw-read based variant callers as the standard method for an accurate detection of variants at very low frequencies. However, benchmarking done in the tools publication are usually realized on real biological data in which real variants are not known, making it difficult to assess their accuracy. ResultsWe present UMI-Gen, a UMI-based read simulator for targeted sequencing paired-end data. UMI-Gen generates reference reads covering the targeted regions at a user customizable depth. After that, using a number of control files, it estimates the background error rate at each position and then modifies the generated reads to mimic real biological data. Finally, it will insert real variants in the reads from a list provided by the user. AvailabilityThe entire pipeline is available at https://gitlab.com/vincent-sater/umigen under MIT license.

FIREVAT: finding reliable variants without artifacts in human cancer samples using etiologically relevant mutational signatures

BackgroundAccurate identification of real somatic variants is a primary part of cancer genome studies and precision oncology. However, artifacts introduced in various steps of sequencing obfuscate confidence in variant calling. Current computational approaches to variant filtering involve intensive interrogation of Binary Alignment Map (BAM) files and require massive computing power, data storage, and manual labor. Recently, mutational signatures associated with sequencing artifacts have been extracted by the Pan-cancer Analysis of Whole Genomes (PCAWG) study. These spectrums can be used to evaluate refinement quality of a given set of somatic mutations.ResultsHere we introduce a novel variant refinement software, FIREVAT (FInding REliable Variants without ArTifacts), which uses known spectrums of sequencing artifacts extracted from one of the largest publicly available catalogs of human tumor samples. FIREVAT performs a quick and efficient variant refinement that accurately removes artifacts and greatly improves the precision and specificity of somatic calls. We validated FIREVAT refinement performance using orthogonal sequencing datasets totaling 384 tumor samples with respect to ground truth. Our novel method achieved the highest level of performance compared to existing filtering approaches. Application of FIREVAT on additional 308 The Cancer Genome Atlas (TCGA) samples demonstrated that FIREVAT refinement leads to identification of more biologically and clinically relevant mutational signatures as well as enrichment of sequence contexts associated with experimental errors. FIREVAT only requires a Variant Call Format file (VCF) and generates a comprehensive report of the variant refinement processes and outcomes for the user.ConclusionsIn summary, FIREVAT facilitates a novel refinement strategy using mutational signatures to distinguish artifactual point mutations called in human cancer samples. We anticipate that FIREVAT results will further contribute to precision oncology efforts that rely on accurate identification of variants, especially in the context of analyzing mutational signatures that bear prognostic and therapeutic significance. FIREVAT is freely available at https://github.com/cgab-ncc/FIREVAT

Location and Volume of MRI Artifacts in Patients With Implanted Sphenopalatine Ganglion Neurostimulators for Treatment of Chronic Cluster Headache

Sphenopalatine ganglion stimulation (SPG-S) is an invasive form of neuromodulation by which a neurostimulator is implanted into the pterygopalatine fossa to treat refractory chronic cluster headache. The implant is MRI conditional, up to 3 T, however there is no clinical data on the shape, size, and location of the artifact produced by the implant. Records of patients with SPG-S were analyzed for postoperative cranial MRI scans. MRI and intraoperative CT scans for visualization of the implant were fused and volumetry was performed for both the implant and the MRI artifact in different MRI sequences. In total, n = 3 patients with postoperative MRI scans were identified. The mean CT artifact volume was 0.73 cm3 (±0.15 cm3 ). MRI artifact volume differed between sequences (range: 25.2-220.7 cm3 ). The intracranial space was largely unaffected besides the pole of the ipsilateral temporal lobe and the basal frontal gyrus. MRI artifacts affected the extracranial space (orbit, maxillary and ethmoid sinuses, and parts of the parotid gland). No adverse events occurred during or after MRI scans. Cranial MRI scans with SPG-S implants were safely performed in three patients following the manufacturer's MRI conditions. MRI artifacts were mostly located in the extracranial space. Brain MRI imaging is largely unaffected. The authors declare no potential conflicts of interest with respect to research, authorship, and/or publication of this article.

Analyzing degraded DNA and challenging samples using the ForenSeq™ DNA Signature Prep kit

Typing short tandem repeats (STRs) is the basis for human identification in current forensic testing. The standard method uses capillary electrophoresis (CE) to separate amplicons by length and fluorescent labeling. In recent years new methods, including massively parallel sequencing (MPS), have been developed which increased the discriminative power of STRs through sequencing. MPS also offers the opportunity to test more genetic markers in a run than is possible with standard CE technology. Verogen’s ForenSeq™ DNA Signature Prep kit includes over 150 genetic markers [STRs and single nucleotide polymorphisms (SNPs)]. Further, MPS separation depends on sequences rather than lengths; therefore, amplicons can be small or even of the same lengths. These improvements are advantageous when testing challenging forensic samples that could be severely degraded.This study tested the ForenSeq™ DNA Signature Prep kit in repeated experimental runs on series of degraded DNA samples, ranging from mild to severe degradation, as well as 24 mock case-type samples, derived from bones, blood cards, and teeth. Despite passing the quality metrics, positive controls (2800 M) showed drop-outs at some loci, mostly SNPs. Sequencing DNA samples repeatedly in two experimental runs as well as sequencing one pooled library in triplicate led to the assumption that spurious alleles of the Y-STRs in this study were not a result of sequencing artifacts but could be due to sequence structures (e.g. duplications, palindromes) of the Y-chromosome and/or might be accumulated during library preparation.Two sets of serially degraded DNA samples revealed that dropped-out loci were primarily loci with long amplicons as well as low read numbers (coverage), e.g. PentaE, DXS8378, and rs1736442. STRs started to drop out at degradation indices (DIs) > 4. However, severely degraded DNA (DI: 44) still resulted in 90% of the 20 CODIS loci, while only 35% were obtained using Promega’s PowerPlex® Fusion kit, a current standard CE kit. Mock case-type samples confirmed these results. ForenSeq™ DNA Signature Prep kit demonstrated that it can be successfully used on degraded DNA samples. This study may be helpful for other laboratories assessing and validating MPS technologies.

Usefulness of Radio Frequency Identification Device in Diagnosing Rotation of Motiva SmoothSilk Implants after Augmentation Mammoplasty.

Breast implant displacement has been described as a significant risk following augmentation mammoplasty. Magnetic resonance imaging (MRI) is considered the method of choice for diagnosing implant complications, but it has its limits in assessing correct implant position and displacement. Motiva SmoothSilk/SilkSurface® Implants (MSS) are the first to incorporate a radio frequency identification device (RFID), which produces an imaging artifact in MRI sequences. Given the frequency of breast augmentation procedures and the recent US Food and Drug Administration prospective trial involving SS with RFID, further analysis of implant stability and diagnostic imaging methods to evaluate implant positioning is necessary. The objective of this study was to assess the use of MRI with this new RFID-containing implant as a new tool to assess correct implant positioning. The authors performed this technique in 5 patients (10 implants) undergoing primary breast augmentation or revision surgery with MSS implants (255-385 cc, mean = 325 cc). The average area and volume of the artifact were 15.7 cm2 and 31.75 cm3, respectively. All cases presented satisfactory results, with 1 case of implant displacement. Our clinical and radiological outcome demonstrated that RFID technology is a useful tool for correct visualization of the implant position and diagnosis of complications such as slight displacements or rotation. To our knowledge, this is the first RFID breast implant that has been objectively evaluated for MRI issues.

Musculoskeletal MRI Pulse Sequences: A Review for Residents and Fellows.

Understanding the basic principles and physics of common musculoskeletal MRI pulse sequences is fundamental for appropriate sequence selection, protocol troubleshooting, artifact reduction, and int...

Insights into tissue microstructure using a double diffusion encoding sequence on a clinical scanner: Validation and application to experimental tumor models.

To present a double diffusion encoding MRI sequence on a clinical scanner to analyze micro-structure and micro-vasculature of tumors. The sequence was tested on phantoms, asparaguses, and 2 tumors allografts in a rodent. Results were analyzed using an adapted VERDICT model to estimate microstructural parameters. The technical feasibility of the sequence on a 3T clinical system was assessed on a water phantom. The accuracy of cell size estimation was assessed on asparaguses by comparison with light microscopy. Cell size estimations were also validated when limiting relative angles of diffusion encodings to 0 and 180°. Sensitivities to restricted diffusion and incoherent flow from the vasculature were investigated in experimental tumor models. Values of microstructural parameters in viable and decaying tumor tissue were compared with those obtained from histological analysis. Measurements on the water phantom revealed no significant sequence artifacts and accurate apparent diffusion coefficient values within a 4% relative error. In asparaguses, quartiles and medians of pore size distributions typically deviated less than 6% from light microscopy regardless of whether the full or reduced set of relative angles was used. Signal analyses in tumors showed mixed effects of both blood flow and diffusion restriction. Microstructural parameter estimations in tumors were consistent with histology and allowed clear and histology-proven distinctions between decaying and viable tumor tissue. Double diffusion encoding with clinical gradients and scan times allows characterization of restricted diffusion and micro-circulation flow in tumors. Our estimated microstructural parameters are promising for further investigations in assessing microstructural evolutions in tumors.