Chimeric Reads Research Articles

Abstract 2185: MicroSEC: Sequence error filter for formalin-fixed and paraffin-embedded samples

Abstract Background: DNAs extracted from formalin-fixed and paraffin-embedded (FFPE) tissues are fragmented and contain a significant amount of single-stranded DNA (ssDNA). We found that most of the false-positive mutations in clinical sequencing with FFPE samples are ssDNA-derived artifacts. During the end-repair step of library preparation, chimeric reads are generated by mis-annealing of ssDNA molecules comprising homologous sequences with a mismatched base. The mismatched base is called as a false-positive mutation, and the position of the base is biased towards the effective ends in the individual reads because either side of the chimeric read should be soft-clipped by the mapping pipeline. Based on this theory, we developed a post hoc filter, MicroSEC, to predict such artifacts in FFPE samples. Methods: Fifty-three fresh frozen (FF) and 190 FFPE normal breast tissue samples and 23 FF and 33 FFPE breast cancer samples were obtained from 26 patients, and subjected to capture-based panel sequencing (Todai OncoPanel, TOP). We also obtained TOP data from 54 FFPE various tumor samples. MicroSEC was developed to predict artifacts with BAM files based on the positional bias of mutations within each read. The predictions were validated with amplicon-based sequencing of 97 mutations. We also developed a model which predicts artifacts only from the mutated base information without corresponding BAM files, by using 5,034 MicroSEC predictions as the supervised data with the LightGBM technique. A total of 742,030 mutations from the AACR Project GENIE were examined with the model. Results: Among the normal breast tissues, we identified 0.3 and 11.7 somatic mutations per sample in FF and FFPE specimens, and 0 (0%) and 10.1 (86.0%) were filtered out by MicroSEC, respectively. Two unique mutations with variant allele frequency of >50% in FFPE samples were eliminated. From the breast cancer specimens, we identified 4.0 and 10.7 mutations per sample in FF and FFPE, and 0 (0%) and 3.2 (30.2%) were filtered out, respectively. In the clinical sequencing data of 54 FFPE tumor samples, we identified 21.6 mutations per sample and 3.6 (16.6%) including five unique pathogenic mutations were filtered out. The validation study showed that the sensitivity and specificity for artifacts of MicroSEC were 97% (95% confidence interval (CI): 82%-100%) and 96% (95% CI: 88%-99%), respectively. Further, the prediction model reproduced the MicroSEC predictions with an area under the ROC curve of 0.995. The model detected 2,512 mutations (0.34%) as artifacts from Project GENIE data. There was a difference in the artifact detection rate between institutions, and 815 (1.45%) of the 56,100 mutations reported by UCSF were predicted as artifacts. Conclusions: MicroSEC removes only FFPE artifacts without eliminating true mutations found in FF samples. Our pipeline will increase the reliability of the clinical sequencing and advance cancer research using FFPE samples. Citation Format: Masachika Ikegami, Shinji Kohsaka, Takeshi Hirose, Toshihide Ueno, Satoshi Inoue, Naoki Kanomata, Hideko Yamauchi, Taisuke Mori, Shigeki Sekine, Yoshihiro Inamoto, Yasushi Yatabe, Hiroshi Kobayashi, Sakae Tanaka, Toru Akiyama, Tomotake Okuma, Hiroyuki Mano. MicroSEC: Sequence error filter for formalin-fixed and paraffin-embedded samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2185.

Abstract 2288: A novel enzymatic fragmentation library preparation chemistry that greatly reduces sequencing artifacts

Abstract After a decade of NGS technology and workflow innovation, personalized medicine is starting to become a reality. DNA fragmentation is still a critical bottleneck during library preparation. Sonication methods have been the gold standard for consistent fragmentation and uniform GC coverage, but are associated with a high upfront investment, expensive consumables, and are prone to oxidative DNA damage. On the other hand, enzymatic fragmentation methods hold the potential to be scalable, automation-friendly workflows that minimize DNA damage. Yet, typical enzymatic fragmentation methods have been shown to introduce systematic hairpin artifacts, exhibit suboptimal uniformity, and have a narrow range of input mass compatibility. We have developed a novel enzymatic fragmentation-based library preparation technology which, together with our high-fidelity library amplification module, effectively overcomes many of the key limitations of related chemistries. Libraries generated using our workflow reduced chimeric reads and terminal hairpin artifacts 10-fold compared to other enzymatic methods, and reached comparable levels of mechanically sheared DNA controls. Furthermore, we observed consistently even coverage uniformity and low sequence-specific bias for human whole genome sequencing. Fragmentation was tested across a broad sample input range from 100 pg to 500 ng. Library insert sizes were highly tunable from 150 bp to 550 bp and consistent across the input titration. High quality libraries with minimal adapter dimer were prepared from as little as 1 picogram of gDNA by adjusting the post amplification clean up conditions. Taken together, this enzymatic fragmentation and library preparation workflow avoids library preparation artifacts that convolute variant calling, is highly scalable, and suitable for ultra-low input samples. Citation Format: Zane Jaafar, Josh Haimes, Thomas Harrison, Lindsay Peterkin, Martin Ranik, Kristin Scott, Brian A. Kudlow. A novel enzymatic fragmentation library preparation chemistry that greatly reduces sequencing artifacts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2288.

Generation of hypoimmunogenic induced pluripotent stem cells by CRISPR-Cas9 system and detailed evaluation for clinical application

In order to expand the promise of regenerative medicine using allogeneic induced pluripotent stem cells (iPSCs), precise and efficient genome editing of human leukocyte antigen (HLA) genes would be advantageous to minimize the immune rejection caused by mismatches of HLA type. However, clinical-grade genome editing of multiple HLA genes in human iPSC lines remains unexplored. Here, we optimized the protocol for good manufacturing practice (GMP)-compatible CRISPR-Cas9 genome editing to deplete the three gene locus (HLA-A, HLA-B, and CIITA genes) simultaneously in HLA homozygous iPSCs. The use of HLA homozygous iPSCs has one main advantage over heterozygous iPSCs for inducing biallelic knockout by a single gRNA. RNA-seq and flow cytometry analyses confirmed the successful depletion of HLAs, and lineage-specific differentiation into cardiomyocytes was verified. We also confirmed that the pluripotency of genome-edited iPSCs was successfully maintained by the three germ layers of differentiation. Moreover, whole-genome sequencing, karyotyping, and optical genome mapping analyses revealed no evident genomic abnormalities detected in some clones, whereas unexpected copy number losses, chromosomal translocations, and complex genomic rearrangements were observed in other clones. Our results indicate the importance of multidimensional analyses to ensure the safety and quality of the genome-edited cells. The manufacturing and assessment pipelines presented here will be the basis for clinical-grade genome editing of iPSCs.

ViroCapt: A Bioinformatics Pipeline for Identifying Viral Insertion in Human Host Genome.

The implication of viruses in human cancers, as well as the emergence of next generation sequencing has permitted to investigate further their role and pathophysiology in the development of this disease. One such mechanism is the integration of portions of viral genomes in the human genome, as well as the specific action of viral oncogenes.inding integration sites and preserved oncogenes is still relying on heavy manual intervention. We developed an analysis and interpretation pipeline to determine viral insertions. Using data from directed viral capture, the pipeline conducts a crude genotyping phase to select reference viral genomes, identifies chimeric reads, extracts the putative human sequences to locate in the human reference genome, scores and ranks candidate junctions, and exports tabular and visual results. We leverage common bioinformatics tools (bowtie2, samtools, blat), and a dedicated filtering and ranking algorithm, implemented in R, to infer candidate junctions and insertions. Static results (tables, figures) are produced, as well as an interactive interpretation tool developed as a shiny web app. We validated this pipeline against published results of HPV, HBV, and AAV2 insertions and show good information retrieval.

Global mapping of RNA homodimers in living cells.

RNA homodimerization is important for various physiological processes, including the assembly of membraneless organelles, RNA subcellular localization, and packaging of viral genomes. However, understanding RNA dimerization has been hampered by the lack of systematic in vivo detection methods. Here, we show that CLASH, PARIS, and other RNA proximity ligation methods detect RNA homodimers transcriptome-wide as “overlapping” chimeric reads that contain more than one copy of the same sequence. Analyzing published proximity ligation data sets, we show that RNA:RNA homodimers mediated by direct base-pairing are rare across the human transcriptome, but highly enriched in specific transcripts, including U8 snoRNA, U2 snRNA, and a subset of tRNAs. Mutations in the homodimerization domain of U8 snoRNA impede dimerization in vitro and disrupt zebrafish development in vivo, suggesting an evolutionarily conserved role of this domain. Analysis of virus-infected cells reveals homodimerization of SARS-CoV-2 and Zika genomes, mediated by specific palindromic sequences located within protein-coding regions of N gene in SARS-CoV-2 and NS2A gene in Zika. We speculate that regions of viral genomes involved in homodimerization may constitute effective targets for antiviral therapies.

TC-hunter: identification of the insertion site of a transgenic gene within the host genome

BackgroundTransgenic animal models are crucial for the study of gene function and disease, and are widely utilized in basic biological research, agriculture and pharma industries. Since the current methods for generating transgenic animals result in the random integration of the transgene under study, the phenotype may be compromised due to disruption of known genes or regulatory regions. Unfortunately, most of the tools that predict transgene insertion sites from high-throughput data are not publicly available or not properly maintained.ResultsWe implemented TC-hunter, Transgene-Construct hunter, an open tool that identifies transgene insertion sites and provides simple reports and visualization aids. It relies on common tools used in the analysis of high-throughput data and makes use of chimeric reads and discordant read pairs to identify and support the transgenic insertion site. To demonstrate its applicability, we applied TC-hunter to four transgenic mice samples harboring the human PPM1D gene, a model used in the study of malignant tumor development. We identified the transgenic insertion site in each sample and experimentally validated them with Touchdown-polymerase chain reaction followed by Sanger sequencing.ConclusionsTC-hunter is an accessible bioinformatics tool that can automatically identify transgene insertion sites from DNA sequencing data with high sensitivity (98%) and precision (92.45%). TC-hunter is a valuable tool that can aid in evaluating any potential phenotypic complications due to the random integration of the transgene and can be accessed at https://github.com/bcfgothenburg/SSF.

CLASH Analyst: A Web Server to Identify In Vivo RNA-RNA Interactions from CLASH Data.

Non-coding RNAs, such as miRNAs and piRNAs, play critical roles in gene regulation through base-pairing interactions with their target molecules. The recent development of the crosslinking, ligation, and sequencing of hybrids (CLASH) method has allowed scientists to map transcriptome-wide RNA–RNA interactions by identifying chimeric reads consisting of fragments from regulatory RNAs and their targets. However, analyzing CLASH data requires scientists to use advanced bioinformatics, and currently available tools are limited for users with little bioinformatic experience. In addition, many published CLASH studies do not show the full scope of RNA–RNA interactions that were captured, highlighting the importance of reanalyzing published data. Here, we present CLASH Analyst, a web server that can analyze raw CLASH data within a fully customizable and easy-to-use interface. CLASH Analyst accepts raw CLASH data as input and identifies the RNA chimeras containing the regulatory and target RNAs according to the user’s interest. Detailed annotation of the captured RNA–RNA interactions is then presented for the user to visualize within the server or download for further analysis. We demonstrate that CLASH Analyst can identify miRNA- and piRNA-targeting sites reported from published CLASH data and should be applicable to analyze other RNA–RNA interactions. CLASH Analyst is freely available for academic use.

Inhibition of Viral Replication Reduces Transcriptionally Active Distinct Hepatitis B Virus Integrations With Implications on Host Gene Dysregulation

Hepatocellular carcinogenesis of hepatitis B virus (HBV) infection may arise from integration of viral DNA into the host genome. We aimed to gauge the effect of viral inhibition on transcriptionally active HBV-host integration events and explore the correlation of viral integrations with host gene dysregulation. We leveraged data and biospecimens from an interventional trial, in which patients with HBV viremia above 2000 IU/mL and minimally raised serum liver enzyme were randomized to receive tenofovir disoproxil fumarate (TDF) or placebo for 3 years. Total RNA-sequencing was performed on paired liver biopsies taken before and after the 3-year intervention in 119 patients. Virus-host chimeric reads were captured to quantify the number of distinct viral integrations. Dysregulation of a host gene disrupted by viral integration was defined by aberrant expression >2 standard deviations away from samples without viral integration. The TDF (n= 64) and placebo groups (n= 55) were comparable at baseline. Expressed viral integrations were detected in all pre- and posttreatment samples. The number of distinct viral integrations significantly correlated with circulatory biomarkers indicative of viral activities including HBV DNA, RNA, and viral antigens (P < .0003 for all correlations). Moreover, TDF vs placebo achieved a significantly greater reduction in distinct viral integrations, with 3.28-fold and 1.81-fold decreases in the expressed integrations per million reads, respectively (analysis of covariance, P= .037). Besides, viral integrations significantly correlated with host gene dysregulation. Inhibition of viral replication reduces the number of transcriptionally active distinct HBV-host DNA integrations in patients with substantial viremia. Given the mutagenic potentials of viral integrations, such treatment effects should be considered in patient management.

MicroSEC filters sequence errors for formalin-fixed and paraffin-embedded samples

The clinical sequencing of tumors is usually performed on formalin-fixed, paraffin-embedded samples and results in many sequencing errors. We identified that most of these errors are detected in chimeric reads caused by single-strand DNA molecules with microhomology. During the end-repair step of library preparation, mutations are introduced by the mis-annealing of two single-strand DNA molecules comprising homologous sequences. The mutated bases are distributed unevenly near the ends in the individual reads. Our filtering pipeline, MicroSEC, focuses on the uneven distribution of mutations in each read and removes the sequencing errors in formalin-fixed, paraffin-embedded samples without over-eliminating the mutations detected also in fresh frozen samples. Amplicon-based sequencing using 97 mutations confirmed that the sensitivity and specificity of MicroSEC were 97% (95% confidence interval: 82–100%) and 96% (95% confidence interval: 88–99%), respectively. Our pipeline will increase the reliability of the clinical sequencing and advance the cancer research using formalin-fixed, paraffin-embedded samples.

Sequences of SARS-CoV-2 “Hybrids” with the Human Genome: Signs of Non-coding RNA?

Controversial reports of human-virus chimeric reads (HVCRs) suggested a possible integration of SARS-CoV-2 sequences into human DNA (1-3).…

ChiTaH: a fast and accurate tool for identifying known human chimeric sequences from high-throughput sequencing data.

Fusion genes or chimeras typically comprise sequences from two different genes. The chimeric RNAs of such joined sequences often serve as cancer drivers. Identifying such driver fusions in a given cancer or complex disease is important for diagnosis and treatment. The advent of next-generation sequencing technologies, such as DNA-Seq or RNA-Seq, together with the development of suitable computational tools, has made the global identification of chimeras in tumors possible. However, the testing of over 20 computational methods showed these to be limited in terms of chimera prediction sensitivity, specificity, and accurate quantification of junction reads. These shortcomings motivated us to develop the first ‘reference-based’ approach termed ChiTaH (Chimeric Transcripts from High–throughput sequencing data). ChiTaH uses 43,466 non–redundant known human chimeras as a reference database to map sequencing reads and to accurately identify chimeric reads. We benchmarked ChiTaH and four other methods to identify human chimeras, leveraging both simulated and real sequencing datasets. ChiTaH was found to be the most accurate and fastest method for identifying known human chimeras from simulated and sequencing datasets. Moreover, especially ChiTaH uncovered heterogeneity of the BCR-ABL1 chimera in both bulk and single-cells of the K-562 cell line, which was confirmed experimentally.

Long-read metagenomics of multiple displacement amplified DNA of low-biomass human gut phageomes by SACRA pre-processing chimeric reads.

The human gut bacteriophage community (phageome) plays an important role in the host's health and disease; however, the entire structure is poorly understood, partly owing to the generation of many incomplete genomes in conventional short-read metagenomics. Here, we show long-read metagenomics of amplified DNA of low-biomass phageomes with multiple displacement amplification (MDA), involving the development of a novel bioinformatics tool, split amplified chimeric read algorithm (SACRA), that efficiently pre-processed numerous chimeric reads generated through MDA. Using five samples, SACRA markedly reduced the average chimera ratio from 72% to 1.5% in PacBio reads with an average length of 1.8 kb. De novo assembly of chimera-less PacBio long reads reconstructed contigs of ≥5 kb with an average proportion of 27%, which was 1% in contigs from MiSeq short reads, thereby dramatically improving contig length and genome completeness. Comparison of PacBio and MiSeq contigs found MiSeq contig fragmentations frequently near local repeats and hypervariable regions in the phage genomes, and those caused by multiple homologous phage genomes coexisting in the community. We also developed a reference-independent method to assess the completeness of the linear phage genomes. Overall, we established a SACRA-coupled long-read metagenomics robust to highly diverse gut phageomes, identifying high-quality circular and linear phage genomes with adequate sequence quantity.

SimFFPE and FilterFFPE: improving structural variant calling in FFPE samples.

BackgroundArtifact chimeric reads are enriched in next-generation sequencing data generated from formalin-fixed paraffin-embedded (FFPE) samples. Previous work indicated that these reads are characterized by erroneous split-read support that is interpreted as evidence of structural variants. Thus, a large number of false-positive structural variants are detected. To our knowledge, no tool is currently available to specifically call or filter structural variants in FFPE samples. To overcome this gap, we developed 2 R packages: SimFFPE and FilterFFPE.ResultsSimFFPE is a read simulator, specifically designed for next-generation sequencing data from FFPE samples. A mixture of characteristic artifact chimeric reads, as well as normal reads, is generated. FilterFFPE is a filtration algorithm, removing artifact chimeric reads from sequencing data while keeping real chimeric reads. To evaluate the performance of FilterFFPE, we performed structural variant calling with 3 common tools (Delly, Lumpy, and Manta) with and without prior filtration with FilterFFPE. After applying FilterFFPE, the mean positive predictive value improved from 0.27 to 0.48 in simulated samples and from 0.11 to 0.27 in real samples, while sensitivity remained basically unchanged or even slightly increased.ConclusionsFilterFFPE improves the performance of SV calling in FFPE samples. It was validated by analysis of simulated and real data.

ZWA: Viral genome assembly and characterization hindrances from virus-host chimeric reads; a refining approach.

Viral metagenomics, also known as virome studies, have yielded an unprecedented number of novel sequences, essential in recognizing and characterizing the etiological agent and the origin of emerging infectious diseases. Several tools and pipelines have been developed, to date, for the identification and assembly of viral genomes. Assembly pipelines often result in viral genomes contaminated with host genetic material, some of which are currently deposited into public databases. In the current report, we present a group of deposited sequences that encompass ribosomal RNA (rRNA) contamination. We highlight the detrimental role of chimeric next generation sequencing reads, between host rRNA sequences and viral sequences, in virus genome assembly and we present the hindrances these reads may pose to current methodologies. We have further developed a refining pipeline, the Zero Waste Algorithm (ZWA) that assists in the assembly of low abundance viral genomes. ZWA performs context-depended trimming of chimeric reads, precisely removing their rRNA moiety. These, otherwise discarded, reads were fed to the assembly pipeline and assisted in the construction of larger and cleaner contigs making a substantial impact on current assembly methodologies. ZWA pipeline may significantly enhance virus genome assembly from low abundance samples and virus metagenomics approaches in which a small number of reads determine genome quality and integrity.

Mouse papillomavirus type 1 (MmuPV1) DNA is frequently integrated in benign tumors by microhomology-mediated end-joining.

MmuPV1 is a useful model for studying papillomavirus-induced tumorigenesis. We used RNA-seq to look for chimeric RNAs that map to both MmuPV1 and host genomes. In tumor tissues, a higher proportion of total viral reads were virus-host chimeric junction reads (CJRs) (1.9‰ - 7‰) than in tumor-free tissues (0.6‰ - 1.3‰): most CJRs mapped to the viral E2/E4 region. Although most of the MmuPV1 integration sites were mapped to intergenic regions and introns throughout the mouse genome, integrations were seen more than once in several genes: Malat1, Krt1, Krt10, Fabp5, Pard3, and Grip1; these data were confirmed by rapid amplification of cDNA ends (RACE)-Single Molecule Real-Time (SMRT)-seq or targeted DNA-seq. Microhomology sequences were frequently seen at host-virus DNA junctions. MmuPV1 infection and integration affected the expression of host genes. We found that factors for DNA double-stranded break repair and microhomology-mediated end-joining (MMEJ), such as H2ax, Fen1, DNA polymerase Polθ, Cdk1, and Plk1, exhibited a step-wise increase and Mdc1 a decrease in expression in MmuPV1-infected tissues and MmuPV1 tumors relative to normal tissues. Increased expression of mitotic kinases CDK1 and PLK1 appears to be correlated with CtIP phosphorylation in MmuPV1 tumors, suggesting a role for MMEJ-mediated DNA joining in the MmuPV1 integration events that are associated with MmuPV1-induced progression of tumors.

Large-Scale Computational Discovery of Binding Motifs in tRNA Fragments.

Accumulating evidence has suggested that tRNA-derived fragments (tRFs) could be loaded to Argonaute proteins and function as regulatory small RNAs. However, their mode of action remains largely unknown, and investigations of their binding mechanisms have been limited, revealing little more than microRNA-like seed regions in a handful of tRFs and a few targets. Here, we identified such regions of potential interaction on a larger scale, using in vivo formed hybrids of guides and targets in crosslinked chimeric reads in two orientations. We considered “forward pairs” (with guides located on the 5′ ends and targets on the 3′ ends of hybrids) and “reverse pairs” (opposite orientation) and compared them as independent sets of biological constructs. We observed intriguing differences between the two chimera orientations, including the paucity of tRNA halves and abundance of polyT-containing targets in forward pairs. We found a total of 197 quality-ranked motifs supported by ∼120,000 tRF–mRNA chimeras, with 103 interacting motifs common in forward and reverse pairs. By analyzing T→C conversions in human and mouse PAR-CLIP datasets, we detected Argonaute crosslinking sites in tRFs, conserved across species. We proposed a novel model connecting the formation of asymmetric pairs in two sets to the potential binding mechanisms of tRFs, involving the identified interaction motifs and crosslinking sites to Argonaute proteins. Our results suggest the way forward for further experimental elucidation of tRF-binding mechanisms.

SARS-CoV-2-Host Chimeric RNA-Sequencing Reads Do Not Necessarily Arise From Virus Integration Into the Host DNA.

The human genome bears evidence of extensive invasion by retroviruses and other retroelements, as well as by diverse RNA and DNA viruses. High frequency of somatic integration of the RNA virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into the DNA of infected cells was recently suggested, based on a number of observations. One key observation was the presence of chimeric RNA-sequencing (RNA-seq) reads between SARS-CoV-2 RNA and RNA transcribed from human host DNA. Here, we examined the possible origin specifically of human-SARS-CoV-2 chimeric reads in RNA-seq libraries and provide alternative explanations for their origin. Chimeric reads were frequently detected also between SARS-CoV-2 RNA and RNA transcribed from mitochondrial DNA or episomal adenoviral DNA present in transfected cell lines, which was unlikely the result of SARS-CoV-2 integration. Furthermore, chimeric reads between SARS-CoV-2 RNA and RNA transcribed from nuclear DNA were highly enriched for host exonic, rather than intronic or intergenic sequences and often involved the same, highly expressed host genes. Although these findings do not rule out SARS-CoV-2 somatic integration, they nevertheless suggest that human-SARS-CoV-2 chimeric reads found in RNA-seq data may arise during library preparation and do not necessarily signify SARS-CoV-2 reverse transcription, integration in to host DNA and further transcription.

Comparison of long-read sequencing technologies in interrogating bacteria and fly genomes.

The newest generation of DNA sequencing technology is highlighted by the ability to generate sequence reads hundreds of kilobases in length. Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) have pioneered competitive long read platforms, with more recent work focused on improving sequencing throughput and per-base accuracy. We used whole-genome sequencing data produced by three PacBio protocols (Sequel II CLR, Sequel II HiFi, RS II) and two ONT protocols (Rapid Sequencing and Ligation Sequencing) to compare assemblies of the bacteria Escherichia coli and the fruit fly Drosophila ananassae. In both organisms tested, Sequel II assemblies had the highest consensus accuracy, even after accounting for differences in sequencing throughput. ONT and PacBio CLR had the longest reads sequenced compared to PacBio RS II and HiFi, and genome contiguity was highest when assembling these datasets. ONT Rapid Sequencing libraries had the fewest chimeric reads in addition to superior quantification of E. coli plasmids versus ligation-based libraries. The quality of assemblies can be enhanced by adopting hybrid approaches using Illumina libraries for bacterial genome assembly or polishing eukaryotic genome assemblies, and an ONT-Illumina hybrid approach would be more cost-effective for many users. Genome-wide DNA methylation could be detected using both technologies, however ONT libraries enabled the identification of a broader range of known E. coli methyltransferase recognition motifs in addition to undocumented D. ananassae motifs. The ideal choice of long read technology may depend on several factors including the question or hypothesis under examination. No single technology outperformed others in all metrics examined.

Presence of complete murine viral genome sequences in patient-derived xenografts

Patient-derived xenografts are crucial for drug development but their use is challenged by issues such as murine viral infection. We evaluate the scope of viral infection and its impact on patient-derived xenografts by taking an unbiased data-driven approach to analyze unmapped RNA-Seq reads from 184 experiments. We find and experimentally validate the extensive presence of murine viral sequence reads covering entire viral genomes in patient-derived xenografts. The existence of viral sequences inside tumor cells is further confirmed by single cell sequencing data. Extensive chimeric reads containing both viral and human sequences are also observed. Furthermore, we find significantly changed expression levels of many cancer-, immune-, and drug metabolism-related genes in samples with high virus load. Our analyses indicate a need to carefully evaluate the impact of viral infection on patient-derived xenografts for drug development. They also point to a need for attention to quality control of patient-derived xenograft experiments.

Alvis: a tool for contig and read ALignment VISualisation and chimera detection

BackgroundThe analysis of long reads or the assessment of assembly or target capture data often necessitates running alignments against reference genomes or gene sets. The aligner outputs are often parsed automatically by scripts, but many kinds of analysis can benefit from the understanding that can follow human inspection of individual alignments. Additionally, diagrams are a useful means of communicating assembly results to others.ResultsWe developed Alvis, a simple command line tool that can generate visualisations for a number of common alignment analysis tasks. Alvis is a fast and portable tool that accepts input in a variety of alignment formats and will output production ready vector images. Additionally, Alvis will highlight potentially chimeric reads or contigs, a common source of misassemblies.ConclusionAlvis diagrams facilitate improved understanding of assembly quality, enable read coverage to be visualised and potential errors to be identified. Additionally, we found that splitting chimeric reads using the output provided by Alvis can improve the contiguity of assemblies, while maintaining correctness.