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Supplementary Table 4 from Detection of Redundant Fusion Transcripts as Biomarkers or Disease-Specific Therapeutic Targets in Breast Cancer

Supplementary Table 2 from Detection of Redundant Fusion Transcripts as Biomarkers or Disease-Specific Therapeutic Targets in Breast Cancer

Supplementary Figure 1 from Detection of Redundant Fusion Transcripts as Biomarkers or Disease-Specific Therapeutic Targets in Breast Cancer

Supplementary Table 3 from Detection of Redundant Fusion Transcripts as Biomarkers or Disease-Specific Therapeutic Targets in Breast Cancer

Supplementary Table 1 from Detection of Redundant Fusion Transcripts as Biomarkers or Disease-Specific Therapeutic Targets in Breast Cancer

While amyloid-β (Aβ) plaques are considered a hallmark of Alzheimer's disease, clinical trials focused on targeting gamma secretase, an enzyme involved in aberrant Aβ peptide production, have not led to amelioration of AD symptoms or synaptic dysregulation. Screening strategies based on mechanistic, multi-omics approaches that go beyond pathological readouts can aid in the evaluation of therapeutics. Using early-onset Alzheimer's (EOFAD) disease patient lineage PSEN1A246E iPSC-derived neurons, we performed RNA-seq to characterize AD-associated endotypes, which are in turn used as a screening evaluation metric for two gamma secretase drugs, the inhibitor Semagacestat and the modulator BPN-15606. We demonstrate that drug treatment partially restores the neuronal state while concomitantly inhibiting cell cycle re-entry and dedifferentiation endotypes to different degrees depending on the mechanism of gamma secretase engagement. Our endotype-centric screening approach offers a new paradigm by which candidate AD therapeutics can be evaluated for their overall ability to reverse disease endotypes.

The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor–normal genomic DNA (gDNA) samples derived from a breast cancer cell line—which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations—and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking ‘tumor-only’ or ‘matched tumor–normal’ analyses.

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor–normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.

We assess the performance of mRNA capture sequencing to identify fusion transcripts in FFPE tissue of different sarcoma types, followed by RT-qPCR confirmation. To validate our workflow, six positive control tumors with a specific chromosomal rearrangement were analyzed using the TruSight RNA Pan-Cancer Panel. Fusion transcript calling by FusionCatcher confirmed these aberrations and enabled the identification of both fusion gene partners and breakpoints. Next, whole-transcriptome TruSeq RNA Exome sequencing was applied to 17 fusion gene-negative alveolar rhabdomyosarcoma (ARMS) or undifferentiated round cell sarcoma (URCS) tumors, for whom fluorescence in situ hybridization (FISH) did not identify the classical pathognomonic rearrangements. For six patients, a pathognomonic fusion transcript was readily detected, i.e., PAX3-FOXO1 in two ARMS patients, and EWSR1-FLI1, EWSR1-ERG, or EWSR1-NFATC2 in four URCS patients. For the 11 remaining patients, 11 newly identified fusion transcripts were confirmed by RT-qPCR, including COPS3-TOM1L2, NCOA1-DTNB, WWTR1-LINC01986, PLAA-MOB3B, AP1B1-CHEK2, and BRD4-LEUTX fusion transcripts in ARMS patients. Additionally, recurrently detected secondary fusion transcripts in patients diagnosed with EWSR1-NFATC2-positive sarcoma were confirmed (COPS4-TBC1D9, PICALM-SYTL2, SMG6-VPS53, and UBE2F-ALS2). In conclusion, this study shows that mRNA capture sequencing enhances the detection rate of pathognomonic fusions and enables the identification of novel and secondary fusion transcripts in sarcomas.

Sensitive and specific diagnostic and prognostic biomarkers for prostate cancer (PCa) are urgently needed. Urine samples are a non-invasive means to obtain abundant and readily accessible “liquid biopsies”. Herein we used urine liquid biopsies to identify and characterize a novel group of urine-enriched RNAs and metabolites in patients with PCa and normal individuals with or without benign prostatic disease. Differentially expressed RNAs were identified in urine samples by deep sequencing and metabolites in urine were measured by mass spectrometry. mRNA and metabolite profiles were distinct in patients with benign and malignant disease. Integrated analysis of urinary gene expression and metabolite signatures unveiled an aberrant glutamate metabolism and tricarboxylic acid (TCA) cycle node in prostate cancer-derived cells. Functional validation supported a role for glutamate metabolism and glutamate oxaloacetate transaminase 1 (GOT1)-dependent redox balance in PCa, which could be exploited for novel biomarkers and therapies. In this study, we discovered cancer-specific changes in urinary RNAs and metabolites, paving the way for the development of sensitive and specific urinary PCa diagnostic biomarkers either alone or in combination. Our methodology was based on single void urine samples (i.e., without prostatic massage). The integrated analysis of metabolomic and transcriptomic data from these liquid biopsies revealed a glutamate metabolism and tricarboxylic acid cycle node that was specific to prostate-derived cancer cells and cancer-specific metabolic changes in urine.

Next-Generation Sequencing based genomic surveillance has been widely implemented for identification and tracking of emerging SARS-CoV-2 variants to guide the Public Health response to the COVID-19 pandemic. Amplicon-based assays, such as the Illumina® COVIDSeq™ Test (RUO) and COVIDSeq Assay (RUO), enable scalable sequencing of SARS-CoV-2, leveraging V3 and V4 primer designs from the ARTIC community and DRAGEN™ COVID Lineage App analysis available on Illumina BaseSpace™. We report here a comparison of COVIDSeq performance for SARS-CoV-2 genome reporting using the ARTIC V3 based primer pool (including primers for human control genes) that is provided with the COVIDSeq kit versus the ARTIC V4 based Illumina COVIDSeq V4 primer pool, using an optimized protocol and DRAGEN COVID Lineage App analysis. The data indicates that both primer pools enable robust reporting of SARS-CoV-2 variants. The Illumina COVIDSeq V4 primer pool has superior performance for SARS-CoV-2 genome reporting, particularly in samples with low virus load, and is therefore the recommended primer pool for genomic surveillance of SARS-CoV-2 for research use using COVIDSeq.

The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to examine risk across multi-ancestry genomes. We leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from nasopharyngeal swabs of 1049 individuals (736 SARS-CoV-2 positive and 313 SARS-CoV-2 negative) and integrate them with digital phenotypes from electronic health records from a diverse catchment area in Northern California. Genome-wide association disaggregated by admixture mapping reveals novel COVID-19-severity-associated regions containing previously reported markers of neurologic, pulmonary and viral disease susceptibility. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. Summary data from multiomic investigation reveals metagenomic and HLA associations with severe COVID-19. The wealth of data available from residual nasopharyngeal swabs in combination with clinical data abstracted automatically at scale highlights a powerful strategy for pandemic tracking, and reveals distinct epidemiologic, genetic, and biological associations for those at the highest risk.

The SARS-CoV-2 pandemic has differentially impacted populations of varied race, ethnicity and socioeconomic status. Admixture mapping and local ancestry inference represent powerful tools to examine genetic risk within multi-ancestry genomes independent of these confounding social constructs. Here, we leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from 1,327 nasopharyngeal swab residuals and integrate them with digital phenotypes from electronic health records. We demonstrate over-representation of individuals possessing Oceanian and Indigenous American ancestry in SARS-CoV-2 positive populations. Genome-wide-association disaggregated by admixture mapping reveals regions of chromosomes 5 and 14 associated with COVID19 severity within African and Oceanic local ancestries, respectively, independent of overall ancestry fraction. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. We further present summary data from a multi-omic investigation of human-leukocyte-antigen (HLA) typing, nasopharyngeal microbiome and human transcriptomics that reveal metagenomic and HLA associations with severe COVID19 infection. This work demonstrates the power of multi-omic pandemic tracking and genomic analyses to reveal distinct epidemiologic, genetic and biological associations for those at the highest risk.

Summary Background The 2018 Ebola virus disease (EVD) outbreak in Equateur Province, Democratic Republic of the Congo, began on May 8, and was declared over on July 24; it resulted in 54 documented cases and 33 deaths. We did a retrospective genomic characterisation of the outbreak and assessed potential therapeutic agents and vaccine (medical countermeasures). Methods We used target-enrichment sequencing to produce Ebola virus genomes from samples obtained in the 2018 Equateur Province outbreak. Combining these genomes with genomes associated with known outbreaks from GenBank, we constructed a maximum-likelihood phylogenetic tree. In-silico analyses were used to assess potential mismatches between the outbreak strain and the probes and primers of diagnostic assays and the antigenic sites of the experimental rVSVΔG-ZEBOV-GP vaccine and therapeutics. An in-vitro flow cytometry assay was used to assess the binding capability of the individual components of the monoclonal antibody cocktail ZMapp. Findings A targeted sequencing approach produced 16 near-complete genomes. Phylogenetic analysis of these genomes and 1011 genomes from GenBank revealed a distinct cluster, confirming a new Ebola virus variant, for which we propose the name “Tumba”. This new variant appears to have evolved at a slower rate than other Ebola virus variants (0·69 × 10−3 substitutions per site per year with “Tumba” vs 1·06 × 10−3 substitutions per site per year without “Tumba”). We found few sequence mismatches in the assessed assay target regions and antigenic sites. We identified nine amino acid changes in the Ebola virus surface glycoprotein, of which one resulted in reduced binding of the 13C6 antibody within the ZMapp cocktail. Interpretation Retrospectively, we show the feasibility of using genomics to rapidly characterise a new Ebola virus variant within the timeframe of an outbreak. Phylogenetic analysis provides further indications that these variants are evolving at differing rates. Rapid in-silico analyses can direct in-vitro experiments to quickly assess medical countermeasures. Funding Defense Biological Product Assurance Office .

BackgroundIn the current phase of COVID-19 pandemic, we are facing two serious public health challenges that include deficits in SARS-CoV-2 variant monitoring, and neglect of other co-circulating respiratory viruses. Additionally, accurate assessment of the evolution, extent and dynamics of the outbreak are required to understand the transmission of the virus amongst seemingly unrelated cases and provide critical epidemiological information. To address these challenges, we evaluated a new high-throughput next-generation sequencing (NGS), respiratory viral panel (RVP) that includes 40 viral pathogens with the aim of analyzing viral subtypes, mutational variants of SARS-CoV-2, model to understand the spread of the virus in the state of Georgia, USA, and to assess other circulating viruses in the same population.MethodsThis study evaluated a total of 522 samples that included 483 patient samples and 42 synthetic positive control material. The performance metrics were calculated for both clinical and reference control samples by comparing detection results with the RT-PCR assay. The limit of detection (LoD) studies were conducted as per the FDA guidelines. Inference and visualization of the phylogeny of the SARS-CoV-2 sequences were performed through the Nextstrain Command-Line Interface (CLI) tool, utilizing the associated augur and auspice toolkits.ResultsThe performance metrics calculated using both the clinical samples and the reference controls revealed a PPA, NPA and accuracy of 95.98%, 85.96% and 94.4%, respectively. The LoD was determined to be 10 copies/ml with all 25 replicates detected across two different runs. The clade for pangolin lineage B that contains certain distant variants, including P4715L in ORF1ab, Q57H in ORF 3a and, S84L in ORF8 covarying with the D614G spike protein mutation were the most prevalent, early in the pandemic, in Georgia, USA. In our analysis, isolates from the same county formed paraphyletic groups, which indicated virus transmission between counties.ConclusionThe study demonstrates the clinical and public health utility of the NGS-RVP to identify novel variants that can provide actionable information to prevent or mitigate emerging viral threats, models that provide insights into viral transmission patterns and predict transmission/ resurgence of regional outbreaks and provide critical information on co-circulating respiratory viruses that might be independent factors contributing to the global disease burden.

Existing compendia of non-coding RNA (ncRNA) are incomplete, in part because they are derived almost exclusively from small and polyadenylated RNAs. Here we present a more comprehensive atlas of the human transcriptome, which includes small and polyA RNA as well as total RNA from 300 human tissues and cell lines. We report thousands of previously uncharacterized RNAs, increasing the number of documented ncRNAs by approximately 8%. To infer functional regulation by known and newly characterized ncRNAs, we exploited pre-mRNA abundance estimates from total RNA sequencing, revealing 316 microRNAs and 3,310 long non-coding RNAs with multiple lines of evidence for roles in regulating protein-coding genes and pathways. Our study both refines and expands the current catalog of human ncRNAs and their regulatory interactions. All data, analyses and results are available for download and interrogation in the R2 web portal, serving as a basis for future exploration of RNA biology and function.

The use of blood-based extracellular RNA (cell-free RNA; exRNA) as clinical biomarker requires the implementation of a validated procedure for sample collection, processing, and profiling. So far, no study has systematically addressed the pre-analytical variables affecting transcriptome analysis of exRNAs. In the exRNAQC study, we evaluated ten blood collection tubes, three time intervals between blood draw and downstream processing, and eight RNA purification methods using the supplier-specified minimum and maximum biofluid input volumes. The impact of these pre-analytics on deep transcriptome profiling of both small and messenger RNA from healthy donors’ plasma or serum was assessed for each pre-analytical variable separately and for interactions between a selected set of pre-analytics, resulting in 456 extracellular transcriptomes. Making use of 189 synthetic spike-in RNAs, the processing and analysis workflow was controlled. When comparing blood collection tubes, so-called preservation tubes do not stabilize exRNA well, and result in variable RNA concentration and sensitivity (i.e., the number of detected RNAs) over time, as well as compromised reproducibility. We also document large differences in RNA purification kit performance in terms of sensitivity, reproducibility, and observed transcriptome complexity, and demonstrate interactions between specific blood collection tubes, purification kits and time intervals. Our results are summarized in 11 performance metrics that enable an informed selection of the most optimal sample processing workflow for a given experiment. In conclusion, we put forward robust quality control metrics for exRNA quantification methods with validated standard operating procedures (SOPs), representing paramount groundwork for future exRNA-based precision medicine applications.

Summary Comprehensive transcriptome analysis of extracellular RNA (exRNA) purified from human biofluids is challenging because of the low RNA concentration and compromised RNA integrity. Here, we describe an optimized workflow to (1) isolate exRNA from different types of biofluids and (2) to prepare messenger RNA (mRNA)-enriched sequencing libraries using complementary hybridization probes. Importantly, the workflow includes 2 sets of synthetic spike-in RNA molecules as processing controls for RNA purification and sequencing library preparation and as an alternative data normalization strategy. For complete details on the use and execution of this protocol, please refer to Hulstaert et al. (2020)., Graphical abstract, Highlights • Extracellular RNA from biofluids has a low concentration and a compromised integrity • An optimized workflow for mRNA capture sequencing of human biofluids is provided • Synthetic spike-in RNA molecules serve as processing controls • Spike-in RNAs allow for data normalization and calculation of mRNA concentration, Comprehensive transcriptome analysis of extracellular RNA (exRNA) purified from human biofluids is challenging because of the low RNA concentration and compromised RNA integrity. Here, we describe an optimized workflow to (1) isolate exRNA from different types of biofluids and (2) to prepare messenger RNA (mRNA)-enriched sequencing libraries using complementary hybridization probes. Importantly, the workflow includes 2 sets of synthetic spike-in RNA molecules as processing controls for RNA purification and sequencing library preparation and as an alternative data normalization strategy.

Viral genome sequencing has guided our understanding of the spread and extent of genetic diversity of SARS-CoV-2 during the COVID-19 pandemic. SARS-CoV-2 viral genomes are usually sequenced from nasopharyngeal swabs of individual patients to track viral spread., Viral genome sequencing has guided our understanding of the spread and extent of genetic diversity of SARS-CoV-2 during the COVID-19 pandemic. SARS-CoV-2 viral genomes are usually sequenced from nasopharyngeal swabs of individual patients to track viral spread. Recently, RT-qPCR of municipal wastewater has been used to quantify the abundance of SARS-CoV-2 in several regions globally. However, metatranscriptomic sequencing of wastewater can be used to profile the viral genetic diversity across infected communities. Here, we sequenced RNA directly from sewage collected by municipal utility districts in the San Francisco Bay Area to generate complete and nearly complete SARS-CoV-2 genomes. The major consensus SARS-CoV-2 genotypes detected in the sewage were identical to clinical genomes from the region. Using a pipeline for single nucleotide variant calling in a metagenomic context, we characterized minor SARS-CoV-2 alleles in the wastewater and detected viral genotypes which were also found within clinical genomes throughout California. Observed wastewater variants were more similar to local California patient-derived genotypes than they were to those from other regions within the United States or globally. Additional variants detected in wastewater have only been identified in genomes from patients sampled outside California, indicating that wastewater sequencing can provide evidence for recent introductions of viral lineages before they are detected by local clinical sequencing. These results demonstrate that epidemiological surveillance through wastewater sequencing can aid in tracking exact viral strains in an epidemic context.

Assessing the reproducibility, accuracy and utility of massively parallel DNA sequencing platforms remains an ongoing challenge. Here the Association of Biomolecular Resource Facilities (ABRF) Next-Generation Sequencing Study benchmarks the performance of a set of sequencing instruments (HiSeq/NovaSeq/paired-end 2 × 250-bp chemistry, Ion S5/Proton, PacBio circular consensus sequencing (CCS), Oxford Nanopore Technologies PromethION/MinION, BGISEQ-500/MGISEQ-2000 and GS111) on human and bacterial reference DNA samples. Among short-read instruments, HiSeq 4000 and X10 provided the most consistent, highest genome coverage, while BGI/MGISEQ provided the lowest sequencing error rates. The long-read instrument PacBio CCS had the highest reference-based mapping rate and lowest non-mapping rate. The two long-read platforms PacBio CCS and PromethION/MinION showed the best sequence mapping in repeat-rich areas and across homopolymers. NovaSeq 6000 using 2 × 250-bp read chemistry was the most robust instrument for capturing known insertion/deletion events. This study serves as a benchmark for current genomics technologies, as well as a resource to inform experimental design and next-generation sequencing variant calling. Next-generation sequencing platforms are benchmarked using human, bacterial and metagenomics reference materials.

During COVID19 and other viral pandemics, rapid generation of host and pathogen genomic data is critical to tracking infection and informing therapies. There is an urgent need for efficient approaches to this data generation at scale. We have developed a scalable, high throughput approach to generate high fidelity low pass whole genome and HLA sequencing, viral genomes, and representation of human transcriptome from single nasopharyngeal swabs of COVID19 patients.

Massively parallel DNA sequencing is a critical tool for genomics research and clinical diagnostics. Here, we describe the Association of Biomolecular Resource Facilities (ABRF) Next-Generation Sequencing Phase II Study to measure quality and reproducibility of DNA sequencing. Replicates of human and bacterial reference DNA samples were generated across multiple sequencing platforms, including well-established technologies such as Illumina, ThermoFisher Ion Torrent, and Pacific Biosciences, as well as emerging technologies such as BGI, Genapsys, and Oxford Nanopore. A total of 202 datasets were generated to investigate the performance of a total of 16 sequencing platforms, including mappability of reads, coverage and error rates in difficult genomic regions, and detection of small-scale polymorphisms and large-scale structural variants. This study provides a comprehensive baseline resource for continual benchmarking as chemistries, methods, and platforms evolve for DNA sequencing.

BACKGROUND Studies of chromosomal rearrangements and fusion transcripts have elucidated mechanisms of tumorigenesis and led to targeted cancer therapies. This study was aimed at identifying novel fusion transcripts in esophageal adenocarcinoma (EAC). METHODS To identify new fusion transcripts associated with EAC, targeted RNA sequencing and polymerase chain reaction (PCR) verification were performed in 40 EACs and matched nonmalignant specimens from the same patients. Genomic PCR and Sanger sequencing were performed to find the breakpoint of fusion genes. RESULTS Five novel in-frame fusion transcripts were identified and verified in 40 EACs and in a validation cohort of 15 additional EACs (55 patients in all): fibroblast growth factor receptor 2 (FGFR2)–GRB2-associated binding protein 2 (GAB2) in 2 of 55 or 3.6%, Niemann-Pick C1 (NPC1)–maternal embryonic leucine zipper kinase (MELK) in 2 of 55 or 3.6%, ubiquitin-specific peptidase 54 (USP54)–calcium/calmodulin dependent protein kinase II γ (CAMK2G) in 2 of 55 or 3.6%, megakaryoblastic leukemia (translocation) 1 (MKL1)–fibulin 1 (FBLN1) in 1 of 55 or 1.8%, and CCR4-NOT transcription complex subunit 2 (CNOT2)–chromosome 12 open reading frame 49 (C12orf49) in 1 of 55 or 1.8%. A genomic analysis indicated that NPC1-MELK arose from a complex interchromosomal translocation event involving chromosomes 18, 3, and 9 with 3 rearrangement points, and this was consistent with chromoplexy. CONCLUSIONS These data indicate that fusion transcripts occur at a stable frequency in EAC. Furthermore, our results indicate that chromoplexy is an underlying mechanism that generates fusion transcripts in EAC. These and other fusion transcripts merit further study as diagnostic markers and potential therapeutic targets in EAC. Cancer 2017;123:3916-24. © 2017 American Cancer Society.

Neurons in familial Alzheimer’s disease undergo dedifferentiation, resulting in loss of lineage state and degeneration., Identifying the systems-level mechanisms that lead to Alzheimer’s disease, an unmet need, is an essential step toward the development of therapeutics. In this work, we report that the key disease-causative mechanisms, including dedifferentiation and repression of neuronal identity, are triggered by changes in chromatin topology. Here, we generated human induced pluripotent stem cell (hiPSC)–derived neurons from donor patients with early-onset familial Alzheimer’s disease (EOFAD) and used a multiomics approach to mechanistically characterize the modulation of disease-associated gene regulatory programs. We demonstrate that EOFAD neurons dedifferentiate to a precursor-like state with signatures of ectoderm and nonectoderm lineages. RNA-seq, ATAC-seq, and ChIP-seq analysis reveals that transcriptional alterations in the cellular state are orchestrated by changes in histone methylation and chromatin topology. Furthermore, we demonstrate that these mechanisms are observed in EOFAD-patient brains, validating our hiPSC-derived neuron models. The mechanistic endotypes of Alzheimer’s disease uncovered here offer key insights for therapeutic interventions.

The human transcriptome consists of various RNA biotypes including multiple types of non-coding RNAs (ncRNAs). Current ncRNA compendia remain incomplete partially because they are almost exclusively derived from the interrogation of small- and polyadenylated RNAs. Here, we present a more comprehensive atlas of the human transcriptome that is derived from matching polyA-, total-, and small-RNA profiles of a heterogeneous collection of nearly 300 human tissues and cell lines. We report on thousands of novel RNA species across all major RNA biotypes, including a hitherto poorly-cataloged class of non-polyadenylated single-exon long non-coding RNAs. In addition, we exploit intron abundance estimates from total RNA-sequencing to test and verify functional regulation by novel non-coding RNAs. Our study represents a substantial expansion of the current catalogue of human ncRNAs and their regulatory interactions. All data, analyses, and results are available in the R2 web portal and serve as a basis to further explore RNA biology and function.

Summary Background The real-time generation of information about pathogen genomes has become a vital goal for transmission analysis and characterisation in rapid outbreak responses. In response to the recently established genomic capacity in the Democratic Republic of the Congo, we explored the real-time generation of genomic information at the start of the 2018 Ebola virus disease (EVD) outbreak in North Kivu Province. Methods We used targeted-enrichment sequencing to produce two coding-complete Ebola virus genomes 5 days after declaration of the EVD outbreak in North Kivu. Subsequent sequencing efforts yielded an additional 46 genomes. Genomic information was used to assess early transmission, medical countermeasures, and evolution of Ebola virus. Findings The genomic information demonstrated that the EVD outbreak in the North Kivu and Ituri Provinces was distinct from the 2018 EVD outbreak in Equateur Province of the Democratic Republic of the Congo. Primer and probe mismatches to Ebola virus were identified in silico for all deployed diagnostic PCR assays, with the exception of the Cepheid GeneXpert GP assay. Interpretation The first two coding-complete genomes provided actionable information in real-time for the deployment of the rVSVΔG-ZEBOV-GP Ebola virus envelope glycoprotein vaccine, available therapeutics, and sequence-based diagnostic assays. Based on the mutations identified in the Ebola virus surface glycoprotein (GP12) observed in all 48 genomes, deployed monoclonal antibody therapeutics (mAb114 and ZMapp) should be efficacious against the circulating Ebola virus variant. Rapid Ebola virus genomic characterisation should be included in routine EVD outbreak response procedures to ascertain efficacy of medical countermeasures. Funding Defense Biological Product Assurance Office.

We characterized two reference samples for NGS technologies: a human triple-negative breast cancer cell line and a matched normal cell line. Leveraging several whole-genome sequencing (WGS) platforms, multiple sequencing replicates, and orthogonal mutation detection bioinformatics pipelines, we minimized the potential biases from sequencing technologies, assays, and informatics. Thus, our “truth sets” were defined using evidence from 21 repeats of WGS runs with coverages ranging from 50X to 100X (a total of 140 billion reads). These “truth sets” present many relevant variants/mutations including 193 COSMIC mutations and 9,016 germline variants from the ClinVar database, nonsense mutations inBRCA1/2and missense mutations inTP53andFGFR1.Independent validation in three orthogonal experiments demonstrated a successful stress test of the truth set. We expect these reference materials and “truth sets” to facilitate assay development, qualification, validation, and proficiency testing. In addition, our methods can be extended to establish new fully characterized reference samples for the community.

Background Sequencing-based detection and characterization of viruses in complex samples can suffer from lack of sensitivity due to a variety of factors including, but not limited to, low titer, small genome size, and contribution of host or environmental nucleic acids. Hybridization-based target enrichment is one potential method for increasing the sensitivity of viral detection via high-throughput sequencing. Results This study expands upon two previously developed panels of virus enrichment probes (for filoviruses and for respiratory viruses) to include other viruses of biodefense and/or biosurveillance concern to the U.S. Department of Defense and various international public health agencies. The newly expanded and combined panel is tested using carefully constructed synthetic metagenomic samples that contain clinically relevant amounts of viral genetic material. Target enrichment results in a dramatic increase in sensitivity for virus detection as compared to shotgun sequencing, yielding full, deeply covered viral genomes from materials with Ct values suggesting that amplicon sequencing would be likely to fail. Increased pooling to improve cost- and time-effectiveness does not negatively affect the ability to obtain full-length viral genomes, even in the case of co-infections, although as expected, it does decrease depth of coverage. Conclusions Hybridization-based target enrichment is an effective solution to obtain full-length viral genomes for samples from which virus detection would fail via unbiased, shotgun sequencing or even via amplicon sequencing. As the development and testing of probe sets for viral target enrichment expands and continues, the application of this technique, in conjunction with deeper pooling strategies, could make high-throughput sequencing more economical for routine use in biosurveillance, biodefense and outbreak investigations. Electronic supplementary material The online version of this article (10.1186/s12864-019-5543-2) contains supplementary material, which is available to authorized users.

Unbiased, deep sequencing of a nasal specimen from an otherwise healthy 13 month-old boy hospitalized in intensive care revealed high gene expression and the complete genome of a novel isolate of KI polyomavirus (KIPyV). Further investigation detected minimal gene expression of additional viruses, suggesting that KIPyV was potentially the causal agent. Analysis of the complete genome of isolate NMKI001 revealed it is different from all previously reported genomes and contains two amino acid differences as compared to the closest virus isolate, Stockholm 380 (EF127908). This article is protected by copyright. All rights reserved

Vascular and haematopoietic cells organize into specialized tissues during early embryogenesis to supply essential nutrients to all organs and thus play critical roles in development and disease. At the top of the haemato-vascular specification cascade lies cloche, a gene that when mutated in zebrafish leads to the striking phenotype of loss of most endothelial and haematopoietic cells and a significant increase in cardiomyocyte numbers. Although this mutant has been analysed extensively to investigate mesoderm diversification and differentiation and continues to be broadly used as a unique avascular model, the isolation of the cloche gene has been challenging due to its telomeric location. Here we used a deletion allele of cloche to identify several new cloche candidate genes within this genomic region, and systematically genome-edited each candidate. Through this comprehensive interrogation, we succeeded in isolating the cloche gene and discovered that it encodes a PAS-domain-containing bHLH transcription factor, and that it is expressed in a highly specific spatiotemporal pattern starting during late gastrulation. Gain-of-function experiments show that it can potently induce endothelial gene expression. Epistasis experiments reveal that it functions upstream of etv2 and tal1, the earliest expressed endothelial and haematopoietic transcription factor genes identified to date. A mammalian cloche orthologue can also rescue blood vessel formation in zebrafish cloche mutants, indicating a highly conserved role in vertebrate vasculogenesis and haematopoiesis. The identification of this master regulator of endothelial and haematopoietic fate enhances our understanding of early mesoderm diversification and may lead to improved protocols for the generation of endothelial and haematopoietic cells in vivo and in vitro.

Extracellular RNAs present in biofluids have emerged as potential biomarkers for disease. Where most studies focus on plasma or serum, other biofluids may contain more informative RNA molecules, depending on the type of disease. Here, we present an unprecedented atlas of messenger, circular and small RNA transcriptomes of a comprehensive collection of 20 different human biofluids. By means of synthetic spike-in controls, we compared RNA content across biofluids, revealing a more than 10 000-fold difference in RNA concentration. The circular RNA fraction is increased in nearly all biofluids compared to tissues. Each biofluid transcriptome is enriched for RNA molecules derived from specific tissues and cell types. In addition, a subset of biofluids, including stool, sweat, saliva and sputum, contains high levels of bacterial RNAs. Our atlas enables a more informed selection of the most relevant biofluid to monitor particular diseases. To verify the biomarker potential in these biofluids, four validation cohorts representing a broad spectrum of diseases were profiled, revealing numerous differential RNAs between case and control subjects. Taken together, our results reveal novel insights in the RNA content of human biofluids and may serve as a valuable resource for future biomarker studies. All spike-normalized data is publicly available in the R2 web portal and serve as a basis to further explore the RNA content in biofluids.

Cancer biomarker studies require procedures that provide accurate and precise test results with high analytical sensitivity. Consequently, the growing use of extracellular RNA from human biofluids as clinically relevant biomarker requires the implementation of benchmarked methods for sample collection, processing, and profiling. While several small-scale studies have pointed at the impact of individual preanalytical factors, no comprehensive study has addressed the many preanalytical variables affecting downstream sequencing of blood-derived exRNAs. In the Extracellular RNA Quality Control study, we have systematically evaluated the type of blood collection tube (n=10, including 5 so-called preservation tubes), the time between blood draw and plasma preparation (n=3), different plasma types (n=3, i.e., platelet-free, -poor, and -rich plasma), and RNA purification methods using the supplier-specified minimum and maximum plasma input volumes (n=15). The impact of these preanalytical factors is assessed by deep transcriptome profiling of all small and messenger RNAs from healthy donors’ plasma, using TruSeq Small RNA sequencing and TruSeq RNA Exome sequencing, respectively. All experiments are conducted in triplicate (for a total of 270 transcriptomes) using 191 synthetic RNA spike-in molecules as processing controls over a relevant dynamic range. When comparing blood collection tubes, serum mRNA seems very similar to EDTA plasma mRNA, but serum-derived small RNAs are markedly different in biotype composition compared to their plasma counterparts. Furthermore, several plasma tubes with preservation reagents do not stabilize RNA very well, as is reflected by increasing RNA concentrations and number of detected genes over time. Also, their reproducibility is generally compromised. In addition, we demonstrate large differences in RNA purification kit performance in terms of reproducibility, sensitivity, and observed transcriptome complexity. Among others, we note a 50-fold difference in mRNA yield and a 5-fold difference in the number of detected mRNAs. We summarized the results in 12 performance parameters that enable an informed selection of the most optimal sample processing workflow. In conclusion, using a systematic approach, we put forward robust quality control metrics for exRNA quantification methods with validated SOPs for sample collection, processing, and profiling. Our results are crucially important for all future RNA-based liquid biopsy-guided precision oncology applications. Authors in random order; abstract submitted on behalf of the exRNAQC Consortium. Citation Format: Anneleen Decock, Jasper Anckaert, Celine Everaert, Justine Nuytens, Scott Kuersten, An Hendrix, Jo Vandesompele, Pieter Mestdagh, Bert Dhondt, Ruben Van Paemel, Kimberly Verniers, Gary Schroth, Carolina Fierro, Nurten Yigit, Kathleen Schoofs, Annelien Morlion, Jill Deleu, Eva Hulstaert, Francisco Avila Cobos, Nele Nijs, Eveline Vanden Eynde, Hetty Hilde Helsmoortel, Olivier De Wever, Annouck Philippron. Substantial performance differences among RNA purification kits and blood collection tubes in the Extracellular RNA Quality Control study—important considerations for liquid biopsies [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr B49.

Liquid biopsies offer a minimally invasive alternative to tissue biopsies for both diagnosis and monitoring of treatment response. Extracellular RNAs present in biofluids have emerged as potential biomarkers in health and disease, including cancer. While current studies typically focus on plasma or serum, other biofluids may contain more informative RNA molecules for particular disease types. Here, we present an unprecedented atlas of messenger, circular, and small RNA transcriptomes of a comprehensive collection of 20 different human biofluids (amniotic fluid, aqueous humor, ascites, bile, bronchial lavage fluid, breast milk, cerebrospinal fluid, colostrum, gastric fluid, pancreatic cyst fluid, plasma, saliva, seminal fluid, serum, sputum, stool, synovial fluid, sweat, tear fluid, and urine). By means of 173 synthetic RNA spike-in controls, we compared RNA content across biofluids, revealing a more than 10,000-fold difference in RNA concentration. Of interest, the circular RNA fraction is significantly increased in nearly all biofluids compared to various solid tissues. Each biofluid transcriptome is enriched for RNA molecules derived from specific tissues and cell types. In addition, a subset of biofluids, including stool, sweat, saliva, and sputum, contain high levels of bacterial RNAs. These findings enable a more informed selection of the most relevant biofluid to monitor individual cancer types. To verify the biomarker potential in these biofluids, four validation cohorts representing a broad spectrum of diseases, including urine from bladder cancer patients and CSF from glioblastoma patients, were profiled, revealing differential RNAs between case and control subjects. Taken together, our results reveal novel insights in the RNA content of human biofluids and may serve as a valuable resource for future biomarker studies. This abstract is also being presented as Poster B01. Citation Format: Eva Hulstaert, Annelien Morlion, Francisco Avila Cobos, Kimberly Verniers, Justine Nuytens, Eveline Vanden Eynde, Nurten Yigit, Jasper Anckaert, Anja Geerts, Pieter Hindryckx, Peggy Jacques, Guy Brusselle, Ken Bracke, Tania Maes, Thomas Malfait, Thierry Derveaux, Virginie Ninclaus, Caroline Van Cauwenbergh, Kristien Roelens, Ellen Roets, Dimitri Hemelsoet, Kelly Tilleman, Lieve Brochez, Scott Kuersten, Lukas Simon, Sebastian Karg, Christa Nöhammer, Alexandra Kautzky-Willers, Michael Leutner, Ondrej Slaby, Gary Schroth, Jo Vandesompele, Pieter Mestdagh. Charting extracellular transcriptomes in The Human Biofluid RNA Atlas [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr PR15.

Early-Onset Familial Alzheimer’s Disease (EOFAD) is a dominantly inherited neurodegenerative disorder elicited by mutations in the PSEN1, PSEN2, and APP genes1. Hallmark pathological changes and symptoms observed, namely the accumulation of misfolded Amyloid-β (Aβ) in plaques and Tau aggregates in neurofibrillary tangles associated with memory loss and cognitive decline, are understood to be temporally accelerated manifestations of the more common sporadic Late-Onset Alzheimer’s Disease. The complete penetrance of EOFAD-causing mutations has allowed for experimental models which have proven integral to the overall understanding of AD2. However, the failure of pathology-targeting therapeutic development suggests that the formation of plaques and tangles may be symptomatic and not describe the etiology of the disease3,4. Here, we use an integrative, multi-omics approach and systems-level analysis in hiPSC-derived neurons to generate a mechanistic disease model for EOFAD. Using patient-specific cells from donors harboring mutations in PSEN1 differentiated into neurons, we characterize the disease-related gene expression and chromatin accessibility changes by RNA- Seq, ATAC-Seq, and histone methylation ChIP-Seq. We show that the defining disease-causing mechanism of EOFAD is dedifferentiation, primarily through the REST-mediated repression of neuronal lineage specification gene programs and the activation of non-specific germ layer precursor gene programs concomitant with modifications in chromatin accessibility. These gene signature profiles and changes in chromatin topology illustrate that EOFAD neurons traverse the chromatin landscape from an ectodermal origin to a mixed germ lineage state. Further, a reanalysis of existing transcriptomic data from PSEN1 patient brain samples demonstrates that the mechanisms identified in our experimental system recapitulate EOFAD in the human brain. Our results comprise a disease model which describes the mechanisms culminating in dedifferentiation that precede amyloid and tau pathology formation and engender neurodegeneration.

Next generation sequencing (NGS) technologies have revolutionized the genomics field and are becoming more commonplace for identification of human infectious diseases. However, due to the low abundance of viral nucleic acids (NAs) in relation to host, viral identification using direct NGS technologies often lacks sufficient sensitivity. Here, we describe an approach based on two complementary enrichment strategies that significantly improves the sensitivity of NGS-based virus identification. To start, we developed two sets of DNA probes to enrich virus NAs associated with respiratory diseases. The first set of probes spans the genomes, allowing for identification of known viruses and full genome sequencing, while the second set targets regions conserved among viral families or genera, providing the ability to detect both known and potentially novel members of those virus groups. Efficiency of enrichment was assessed by NGS testing reference virus and clinical samples with known infection. We show significant improvement in viral identification using enriched NGS compared to unenriched NGS. Without enrichment, we observed an average of 0.3% targeted viral reads per sample. However, after enrichment, 50%–99% of the reads per sample were the targeted viral reads for both the reference isolates and clinical specimens using both probe sets. Importantly, dramatic improvements on genome coverage were also observed following virus-specific probe enrichment. The methods described here provide improved sensitivity for virus identification by NGS, allowing for a more comprehensive analysis of disease etiology.

A suspected case of sexual transmission from a male survivor of Ebola virus disease (EVD) to his female partner (the patient in this report) occurred in Liberia in March 2015. Ebola virus (EBOV) genomes assembled from blood samples from the patient and a semen sample from the survivor were consistent with direct transmission. The genomes shared three substitutions that were absent from all other Western African EBOV sequences and that were distinct from the last documented transmission chain in Liberia before this case. Combined with epidemiologic data, the genomic analysis provides evidence of sexual transmission of EBOV and evidence of the persistence of infective EBOV in semen for 179 days or more after the onset of EVD. (Funded by the Defense Threat Reduction Agency and others.).

Because RNA-protein interactions have a central role in a wide array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the high-throughput sequencing-RNA affinity profiling (HiTS-RAP) assay that couples sequencing on an Illumina GAIIx genome analyzer with the quantitative assessment of protein-RNA interactions. This assay is able to analyze interactions between one or possibly several proteins with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of the EGFP and negative elongation factor subunit E (NELF-E) proteins with their corresponding canonical and mutant RNA aptamers. Here we provide a detailed protocol for HiTS-RAP that can be completed in about a month (8 d hands-on time). This includes the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, HiTS and protein binding with a GAIIx instrument, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, quantitative analysis of RNA on a massively parallel array (RNA-MaP) and RNA Bind-n-Seq (RBNS), for quantitative analysis of RNA-protein interactions.

A large number of viruses can individually and concurrently cause various respiratory illnesses. Metagenomic sequencing using next-generation sequencing (NGS) technology is capable of identifying a variety of pathogens. Here, we describe a method using a large panel of oligo probes to enrich sequence targets of 34 respiratory DNA and RNA viruses that reduces non-viral reads in NGS data and achieves high performance of sequencing-based pathogen identification. The approach can be applied to total nucleic acids purified from respiratory swabs stored in viral transport medium. Illumina TruSeq RNA Access Library procedure is used in targeted sequencing of respiratory viruses. The samples are subjected to RNA fragmentation, random reverse transcription, random PCR amplification, and ligation with barcoded library adaptors. The libraries are pooled and subjected to two rounds of enrichments by using a large panel of oligos designed to capture whole genomes of 34 respiratory viruses. The enriched libraries are amplified and sequenced using Illumina MiSeq sequencing system and reagents. This method can achieve viral detection sensitivity comparable with molecular assay and obtain partial to complete genome sequences for each virus to allow accurate genotyping and variant analysis.

The response of the peripheral nervous system (PNS) to injury may go together with alterations in epigenetics, a conjecture that has not been subjected to a comprehensive, genome-wide test. Using reduced representation bisulfite sequencing, we report widespread remodeling of DNA methylation in the rat dorsal root ganglion (DRG) occurring within 24 h of peripheral nerve ligation, a neuropathy model of allodynia. Significant (P < 10−4) cytosine hyper- and hypo-methylation was found at thousands of CpG sites. Remodeling occurred outside of CpG islands. Changes affected genes with known roles in the PNS, yet methylome remodeling also involved genes that were not linked to neuroplasticity by prior evidence. Consistent with emerging models relying on genome-wide methylation and RNA-seq analysis of promoter regions and gene bodies, variation of methylation was not tightly linked with variation of gene expression. Furthermore, approximately 44% of the dynamically changed CpGs were located outside of genes. We compared their positions with the intergenic, tissue-specific differentially methylated CpGs (tDMCs) of an independent experimental set consisting of liver, spleen, L4 control DRG, and muscle. Dynamic changes affected those intergenic CpGs that were different between tissues (P < 10−15) and almost never the invariant portion of the methylome (those CpGs that were identical across all tissues). Our findings—obtained in mixed tissue—show that peripheral nerve injury leads to methylome remodeling in the DRG. Future studies may address which of the cell types found in the DRG, such as specific groups of neurons or non-neuronal cells are affected by which aspect of the observed methylome remodeling.