Input RNA Research Articles

High-Throughput NanoString Analysis of Oncogenic Human Papillomavirus and Tumor Microenvironment Transcription in Head and Neck Squamous Cell Carcinoma.

Human papillomaviruses (HPVs), specifically high-risk HPVs, are responsible for up to 3% of all cancers in women and up to 2% of all cancers in men. They have been identified as the etiological agent of cervical cancer and have been increasingly found to be the driver behind head and neck cancers of the oropharynx. A system in which we can simultaneously observe transcriptional changes to both a host's tumor microenvironment and its associated oncogenic driver (e.g., HPV) would be highly valuable for understanding HPV's role in tumorigenesis. This article describes a detailed methodology for utilizing high-throughput RNA analysis to study viral transcription in formalin-fixed, paraffin-embedded clinical tumor samples. Although our lab utilizes these methods for the study of head and neck cancer, the principles contained within are widely applicable to all fields of HPV study. © 2021 Wiley Periodicals LLC. Basic Protocol: HPV16 transcript analysis using NanoString Support Protocol 1: Preparation of RNA from formalin-fixed, paraffin-embedded slides Support Protocol 2: Preparation of RNA from cell lysates Support Protocol 3: Fluorometric RNA concentration and RNA integrity analysis Support Protocol 4: Determination of input RNA based on DV300 calculation.

Overcoming the Challenges of High Quality RNA Extraction from Core Needle Biopsy.

The use of gene expression profiling (GEP) in cancer management is rising, as GEP can be used for disease classification and diagnosis, tailoring treatment to underlying genetic determinants of pharmacological response, monitoring of therapy response, and prognosis. However, the reliability of GEP heavily depends on the input of RNA in sufficient quantity and quality. This highlights the need for standard procedures to ensure best practices for RNA extraction from often small tumor biopsies with variable tissue handling. We optimized an RNA extraction protocol from fresh-frozen (FF) core needle biopsies (CNB) from breast cancer patients and from formalin-fixed paraffin-embedded (FFPE) tissue when FF CNB did not yield sufficient RNA. Methods to avoid ribonucleases andto homogenize or to deparaffinize tissues and the impact of tissue composition on RNA extraction were studied. Additionally, RNA’s compatibility with the nanoString nCounter® technology was studied. This technology platform enables GEP using small RNA fragments. After optimization of the protocol, RNA of high quality and sufficient quantity was obtained from FF CNB in 92% of samples. For the remaining 8% of cases, FFPE material prepared by the pathology department was used for RNA extraction. Both resulting RNA end products are compatible with the nanoString nCounter® technology.

Analytical validation of the Percepta genomic sequencing classifier; an RNA next generation sequencing assay for the assessment of Lung Cancer risk of suspicious pulmonary nodules

BackgroundBronchoscopy is a common procedure used for evaluation of suspicious lung nodules, but the low diagnostic sensitivity of bronchoscopy often results in inconclusive results and delays in treatment. Percepta Genomic Sequencing Classifier (GSC) was developed to assist with patient management in cases where bronchoscopy is inconclusive. Studies have shown that exposure to tobacco smoke alters gene expression in airway epithelial cells in a way that indicates an increased risk of developing lung cancer. Percepta GSC leverages this idea of a molecular “field of injury” from smoking and was developed using RNA sequencing data generated from lung bronchial brushings of the upper airway. A Percepta GSC score is calculated from an ensemble of machine learning algorithms utilizing clinical and genomic features and is used to refine a patient’s risk stratification.MethodsThe objective of the analysis described and reported here is to validate the analytical performance of Percepta GSC. Analytical performance studies characterized the sensitivity of Percepta GSC test results to input RNA quantity, the potentially interfering agents of blood and genomic DNA, and the reproducibility of test results within and between processing runs and between laboratories.ResultsVarying the amount of input RNA into the assay across a nominal range had no significant impact on Percepta GSC classifier results. Bronchial brushing RNA contaminated with up to 10% genomic DNA by nucleic acid mass also showed no significant difference on classifier results. The addition of blood RNA, a potential contaminant in the bronchial brushing sample, caused no change to classifier results at up to 11% contamination by RNA proportion. Percepta GSC scores were reproducible between runs, within runs, and between laboratories, varying within less than 4% of the total score range (standard deviation of 0.169 for scores on 4.57 scale).ConclusionsThe analytical sensitivity, analytical specificity, and reproducibility of Percepta GSC laboratory results were successfully demonstrated under conditions of expected day to day variation in testing. Percepta GSC test results are analytically robust and suitable for routine clinical use.

Defining stable reference genes in HIV latency reversal experiments.

Quantification of cell associated HIV RNA (ca-RNA) is one of the most important and commonly used methods to evaluate the performance of latency-reversing agents (LRAs). Copies of HIV RNA measured by qPCR, are often normalized to the input RNA or cell number. However, these could be affected by biological variability and/or technical errors, which can be avoided by using an internal reference gene. To obtain reliable data, it is essential to select stable reference genes (RGs) of which the expression is not influenced by biological variability, the type of cells, or the LRAs used. However, to date, no study has carefully evaluated RG stability following LRA exposure. We analyzed the stability of six widely used RGs (GAPDH, TBP, YWHAZ, UBE2D2, HPRT1 and RPL27A) in human PBMC and CD4+ T cells. LRA exposure significantly influenced the stability of these RGs. Overall, TBP, UBE2D2, and RPL27A were the most stable RGs in all tested conditions. TBP was generally the most stable RG whereas GAPDH varied the most. Finally, we evaluated the impact of applying different RG normalizers to host genes and HIV ca-RNA data. Altered results were observed both in host and HIV gene expression when unstable RGs were used. Our data underline the importance of testing the stability of RGs utilized to evaluate LRA-induced HIV ca-RNA expression. To our knowledge, this is the first careful evaluation of the stability of RGs after LRA exposure and will significantly contribute to the quality of data analysis in regard to gene expression.IMPORTANCELatency-reversing agents (LRAs) are ubiquitously used in the "shock-and-kill" HIV cure strategy and their performance is often evaluated by ex-vivo quantification of cell associated HIV RNA. HIV RNA, measured by qPCR, is often normalized to internal reference genes, but the expression of these genes should not be influenced by the experimental settings. We found that treatment of human PBMC and CD4+ T cells with LRAs significantly altered the expression of several commonly used reference genes, such as GAPDH. Finally, we evaluate the impact of different reference genes on normalization of host genes and HIV cell associated RNA expression and demonstrated that using unstable reference genes dramatically altered experimental outcome. Our data highlight the importance of using reference genes that are unaffected by LRAs under study to correctly evaluate host gene and cell associated HIV RNA expression induced by latency-reversing agents.

NGS and NanoString Platforms Play Complementary Role in Bedside Advanced Heart Failure Outcome Prediction Test Development

<h3>Purpose</h3> In order to create a clinical assay that preoperatively predicts 1-year survival status of AdHF patients following surgical/interventional therapies and to select the appropriate commercial platform, we compared the properties of Next Generation Sequencing (NGS) to NanoString (NS). <h3>Methods</h3> 8ml of blood was collected in CPT tubes from 25 AdHF patients (11 heart failure control, 4 mechanical circulatory support surgery, and 10 heart transplant surgery) at UCLA Medical Center 2015-2016. Purified RNA samples were aliquoted in two sets: one was processed using NGS transcriptome analysis (Illumina HiSeq 2500) and compared to 770 genes represented on NS pre-existing PanCancer IO 360 Gene Expression research panel. Prior to statistical analysis, expression values were log transformed. Pearson correlation coefficients were computed for each sample. Gene expression values were compared between NS and NGS across the set of matched genes and for each of the matched genes across the set of samples. Genes were grouped by average NGS expression, and the NS-NGS correlation for each group was computed. <h3>Results</h3> Out of 770 genes, 734 overlapped between both platforms and showed high intrasample correlation (R^2 = 0.82). Genes with higher expression demonstrated higher correlation across both platforms (Figure). NS demonstrated high <b>robustness:</b> Gene signature scores were similar across different RNA input concentrations, cartridges, and outcomes; <b>sensitivity:</b> Probe counts between 100 and 500 detected and quantified. The RNA input of 100 ng yielded the most precise result and were used for downstream analysis; and <b>reproducibility:</b> Technical replicates with equal concentration (100ng input) showed extremely high correlation (R^2 > 0.99), thus demonstrating high reproducibility. <h3>Conclusion</h3> Both platforms have meaningful, complementary roles, NGS for discovery and NanoString for commercialization and can be used for AdHF-biomarker test development.

Meiocyte Isolation by INTACT and Meiotic Transcriptome Analysis in Arabidopsis

Isolation of nuclei tagged in specific cell types (INTACT) is a method developed to isolate cell-type-specific nuclei that are tagged through in vivo biotin labeling of a nuclear targeting fusion (NTF) protein. In our work, INTACT was used to capture nuclei of meiocytes and to generate a meiotic transcriptome in Arabidopsis. Using the promoter of AtDMC1 recombinase to label meiotic nuclei, we generated transgenic plants carrying AtDMC1:NTF along with biotin ligase enzyme (BirA) under the constitutive ACTIN2 (ACT2) promoter. AtDMC1-driven expression of biotin-labeled NTF allowed us to collect nuclei of meiocytes by streptavidin-coated magnetic beads. The nuclear meiotic transcriptome was obtained by RNA-seq using low-quantity input RNA. Transcripts grouped into different categories according to their expression levels were investigated by gene ontology enrichment analysis (GOEA). The most enriched GO term “DNA demethylation” in mid/high-expression classes suggests that this biological process is particularly relevant to meiosis onset. The majority of genes with established roles in meiosis were distributed in the classes of mid/high and high expression. Meiotic transcriptome was compared with public available transcriptomes from other tissues in Arabidopsis. Bioinformatics analysis by expression network identified a core of more than 1,500 genes related to meiosis landmarks.

A suitable RNA preparation methodology for whole transcriptome shotgun sequencing harvested from Plasmodium vivax-infected patients

Plasmodium vivax is a world-threatening human malaria parasite, whose biology remains elusive. The unavailability of in vitro culture, and the difficulties in getting a high number of pure parasites makes RNA isolation in quantity and quality a challenge. Here, a methodological outline for RNA-seq from P. vivax isolates with low parasitemia is presented, combining parasite maturation and enrichment with efficient RNA extraction, yielding ~ 100 pg.µL−1 of RNA, suitable for SMART-Seq Ultra-Low Input RNA library and Illumina sequencing. Unbiased coding transcriptome of ~ 4 M reads was achieved for four patient isolates with ~ 51% of transcripts mapped to the P. vivax P01 reference genome, presenting heterogeneous profiles of expression among individual isolates. Amongst the most transcribed genes in all isolates, a parasite-staged mixed repertoire of conserved parasite metabolic, membrane and exported proteins was observed. Still, a quarter of transcribed genes remain functionally uncharacterized. In parallel, a P. falciparum Brazilian isolate was also analyzed and 57% of its transcripts mapped against IT genome. Comparison of transcriptomes of the two species revealed a common trophozoite-staged expression profile, with several homologous genes being expressed. Collectively, these results will positively impact vivax research improving knowledge of P. vivax biology.

High-Throughput Simultaneous mRNA Profiling Using nCounter Technology Demonstrates That Extracellular Vesicles Contain Different mRNA Transcripts Than Their Parental Prostate Cancer Cells.

Extracellular vesicles (EVs) are nano-sized lipid bilayer encapsulated particles with a molecular cargo that appears to play important roles within the human body, such as in cell-to-cell communication. Unraveling the composition of EV cargos remains one of the most fundamental steps toward understanding the role of EVs in intercellular communication and the discovery of new biomarkers. One of the unmet needs in this field is the lack of a robust, sensitive, and multiplexed method for EV mRNA profiling. We established a new protocol using the NanoString low RNA input nCounter assay by which the targeted mRNA transcripts in EVs can be efficiently and specifically amplified and then assayed for 770 mRNAs in one reaction. Prostate cancer cells with epithelial (PC3-Epi) or mesenchymal (PC3-EMT) phenotypes and their progeny EVs were analyzed by the same panel. Among these mRNAs, 157 were detected in PC3-Epi EVs and 564 were detected in PC3-EMT EVs. NOTCH1 was the most significantly abundant mRNA transcripts in PC3-EMT EVs compared to PC3-Epi EVs. Our results demonstrated that when cells undergo epithelial-to-mesenchymal transition (EMT), a more active loading of cancer progression-related mRNA transcripts may occur. The mRNA cargos of EVs derived from mesenchymal prostate cancer cells may contribute to the pro-EMT function. We found that mRNA transcripts are different in progeny EVs compared to parental cells. EV cargos are not completely reflective of their cell origin, and the underlying mechanism of cargo sorting is complicated and needs to be further elucidated.

Gene Fusion Identification Using Anchor-Based Multiplex PCR and Next-Generation Sequencing

Methods for identifying gene fusion events, such as fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), and transcriptome analysis, are either single gene approaches or require bioinformatics expertise not generally available in clinical laboratories. We analytically validated a customized next-generation sequencing (NGS) panel targeting fusion events in 34 genes involving soft-tissue sarcomas. Specimens included 87 formalin-fixed paraffin-embedded (FFPE) tissues with known gene fusion status. Isolated total nucleic acid was used to identify fusion events at the RNA level. The potential fusions were targeted by gene-specific primers, followed by primer extension and nested PCR to enrich for fusion candidates with subsequent bioinformatics analysis. The study generated results using the following quality metrics for fusion detection: (a) ≥100 ng total nucleic acid, (b) RNA average unique start sites per gene-specific primer control ≥10, (c) quantitative PCR assessing input RNA quality had a crossing point <30, (d) total RNA percentage ≥30%, and (e) total sequencing fragments ≥500 000. The test validation study demonstrated analytical sensitivity of 98.7% and analytical specificity of 90.0%. The NGS-based panel generated highly concordant results compared to alternative testing methods.

PAS-seq 2: A fast and sensitive method for global profiling of polyadenylated RNAs.

Alternative polyadenylation (APA) is a widespread phenomenon in eukaryotes that contributes to regulating gene expression and generating proteomic diversity. APA plays critical roles in development and its mis-regulation has been implicated in a wide variety of human diseases, including cancer. To study APA on the transcriptome-wide level, numerous deep sequencing methods that capture 3' end of mRNAs have been developed in the past decade, but they generally require a large amount of hands-on time and/or high RNA input. Here, we introduce PAS-seq 2, a fast and sensitive method for global and quantitative profiling of polyadenylated RNAs. Compared to our original PAS-seq, this method takes less time and requires much lower total RNA input due to improvement in the reverse transcription process. PAS-seq 2 can be applied to both APA and differential gene expression analyses.

COVID-19 laboratory diagnosis: comparative analysis of different RNA extraction methods for SARS-CoV-2 detection by two amplification protocols.

ABSTRACTThe gold standard for the laboratory diagnosis of COVID-19 is the reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) assay, which searches for SARS-CoV-2 target genes in nasopharyngeal/oropharyngeal (NP/OP) samples, and its performance depends on the quantity and quality of the RNA input. This study compared the performance and cost-effectiveness of three different kits/reagents for RNA extraction used in COVID-19 diagnosis in Sao Paulo, Brazil. A total of 300 NP/OP samples belonging to suspected cases of COVID-19 stored in a biorepository were randomly selected, and RNA was extracted using (i) automated extraction (Loccus, Extracta Kit FAST), (ii) manual extraction (BioGene Kit, Bioclin, Quibasa), and (iii) quick extraction methods (Lucigen, Quick DNA Extract Kit). Next, the samples were tested using RT-qPCR for SARS-CoV-2 with the Allplex 2019-nCoV modified assay and the Charité-Berlin protocol. All assays/kits were used according to the manufacturer’s instructions. For the Allplex kit, the sensitivity in detecting SARS-CoV-2 with previously extracted RNA by different procedures was 100.0% for Loccus, 100.0% for BioGene and 91.9% for Quick. Using the Charité-Berlin protocol, the sensitivities were 81.4% for Loccus, 81.2% for BioGene and 60.7% for Quick. The least sensitive target gene and the gene most affected by RNA extraction procedures was the RNA-dependent RNA polymerase gene (Charité-Berlin protocol). No false-positive SARS-CoV-2 results were detected using RNA obtained from any of the different protocols. In conclusion, Loccus and BioGene RNA extractions were efficient for RT-qPCR assays, and although the BioGene procedure is less expensive, Loccus is the best choice because it allows the rapid handling of hundreds or thousands of samples, a desirable feature during pandemics. Although less sensitive, the Quick extraction is useful during outbreaks coupled with the Allplex amplification kit for SARS-CoV-2 diagnosis (κ = 0.925).

RBPsuite: RNA-protein binding sites prediction suite based on deep learning

BackgroundRNA-binding proteins (RBPs) play crucial roles in various biological processes. Deep learning-based methods have been demonstrated powerful on predicting RBP sites on RNAs. However, the training of deep learning models is very time-intensive and computationally intensive.ResultsHere we present a deep learning-based RBPsuite, an easy-to-use webserver for predicting RBP binding sites on linear and circular RNAs. For linear RNAs, RBPsuite predicts the RBP binding scores with them using our updated iDeepS. For circular RNAs (circRNAs), RBPsuite predicts the RBP binding scores with them using our developed CRIP. RBPsuite first breaks the input RNA sequence into segments of 101 nucleotides and scores the interaction between the segments and the RBPs. RBPsuite further detects the verified motifs on the binding segments gives the binding scores distribution along the full-length sequence.ConclusionsRBPsuite is an easy-to-use online webserver for predicting RBP binding sites and freely available at http://www.csbio.sjtu.edu.cn/bioinf/RBPsuite/.

RNA‐based approaches for body fluid identification in forensic science

AbstractIn forensic science, the identification of body fluids present in a stain can aid in the reconstruction of crime scenes and support activity‐level information in some cases. RNA‐based methods for body fluid identification address some limitations associated with conventional testing, including a lack of specificity and sample destruction. mRNA profiling by endpoint reverse transcription polymerase chain reaction (RT‐PCR) is a confirmatory RNA method currently used by some forensic laboratories in casework due to the availability of capillary electrophoresis instruments. This method is highly specific and reliable when the RNA input is within the optimal range. When RNA input is below the limit of detection or too high, then false negatives and false positives/cross reactivity can occur, respectively. Real‐time quantitative PCR (qPCR) is quantitative, more sensitive, and efficient than endpoint PCR, and does not require post‐PCR processing. A reverse transcription (RT) step may also be included in qPCR (RT‐qPCR), enabling mRNA quantification. However, there are concerns regarding the lack of consistency and standardization of RT‐qPCR methodology and reporting of results. Additionally, the number of currently available fluorophores somewhat reduces multiplexing ability. More recently, approaches involving Piwi‐interacting biomarkers, NanoString barcodes, and RNA sequencing have been developed. This review will cover the current and developing RNA‐based techniques for forensic body fluid identification, focusing on endpoint and quantitative RT‐PCR using mRNA. The advantages and limitations of these along with alternative methods will be discussed, and how they may be further developed to advance forensic body fluid identification.This article is categorized under: Forensic Biology &gt; Body Fluid Identification Forensic Biology &gt; Applications of RNA

Detection of RNA viruses in Solanum quitoense by high-throughput sequencing (HTS) using total and double stranded RNA inputs

Solanum quitoense Lam. is a solanaceous fruit shrub native to South America that produces a tomato-sized fruit popular in the preparation of fresh juice, fermented beverages, nectars, ice cream and fruit concentrates. Unfortunately, this crop is highly susceptible to insects, nematodes, fungi, oomycetes, bacteria, and a wide range of viral diseases. With the arrival of High-Throughput Sequencing (HTS) methods, our understanding of the viruses affecting this crop has increased at a steady pace. In this work, we investigate the virome of S. quitoense in Antioquia (Colombia) using the Illumina HTS platform and analyze the effect of using ribosomal RNA depleted total RNA and dsRNA templates. Our results suggest that total RNA outputs a larger amount of viral sequences but fails to detect viruses present at lower loads. Both templates allowed detection and assembly of Potato leafroll virus (PLRV), Potato yellow vein virus (PYVV), and Potato mop-top virus (PMTV); however, the dsRNA input was more sensitive for detection of Potato virus Y (PVY), Potato virus X (PVX), Potato virus S (PVS), and Bell pepper alphaendornavirus (BPEV). These results suggest that the combination of different RNA inputs in HTS studies of plant viromes can give a more complete picture of the real virus diversity.

Additional Evidence of Mismatch Repair Pathway As Relapse-Specific Alteration in B-Cell Precursor Acute Lymphoblastic Leukemia: Discovery of Novel Somatic Mutation in MLH1 and Establishment of New Cell Line with MLH1 Mutation

&amp;lt;Introduction&amp;gt;Extensive molecular analysis revealed genetic alterations related to relapse such as mutations of CREEB, MSH2, or NT5C2 in B-cell precursor acute lymphoblastic leukemia (BCP-ALL). Recently Li B, et al. have established relationship between relapse-specific somatic alterations and timing of relapse (Blood 2020;135:41-55). They identified close link between alterations of DNA mismatch repair genes, including MSH2, MSH6, and PMS2 and early relapse of BCP-ALL as a result of alteration of thiopurine response and resistance to treatment. However, it remains to be clarified which subtype of BCP-ALL is prone to acquisition of particular type of relapse-specific molecular alteration. To further elucidate mechanism of recurrence we have analyzed childhood BCP-ALL cases, particularly focusing on DNA mismatch repair pathway. &amp;lt;Procedure&amp;gt; We analyzed diagnosis-relapse pair samples of recurrent 16 BCP-ALL cases, who had been treated in our institution to find single nucleotide variant (SNV), small Indel, and copy number variation in the coding exons, particularly focusing on mismatch repair pathway using the data captured by Ion AmpliSeq Exome kit and Ion Proton (Thermo Fisher Scientific, MA, USA). The identified variants were confirmed by Sanger sequence. Additionally, we performed RNA-seq using SMART-Seq Ultra Low Input RNA Kit (Clontech Laboratories, Inc, CA, USA), Ion Plus Fragment Library Kit, and Ion Proton, and in vitro cell culture of the leukemic blasts for several cases. &amp;lt;Result&amp;gt; Of several DNA mismatch repair pathway genes, we have identified somatic SNV of MLH1 in a case. The index case, three years old male had diploid BCP-ALL with t(7;9) and PAX5 alteration at diagnosis, who developed early relapse (11 months from diagnosis) and died of the disease. From the sample at 1st and 2nd relapse we have identified somatic MLH1 variant (NM_000249.4:c.901C&amp;gt;T;p.Gln301*). This SNV was detected in small fraction of the diagnostic sample. Furthermore, we have established permanently growing cell line, ICH-BCP-1 from the sample obtained at 2nd relapse. The doubling time is approximately 37 hours and the karyotype was, 46,XY. The same MLH1 variant was identified in the cell line. Of note is that the number of detected SNV increased rapidly at 1st relapse and 2nd relapse as suggested by function of MLH1 product. No other alteration of DNA mismatch repair pathway was observed in the cohort. As previously discovered relapse-specific alterations, we identified somatic SNV of NT5C2 in one hyperdiploid BCP-ALL case and somatic SNV of CREBBP in one hyperdiploid BCP-ALL case. The former case with SNV of NT5C2 gained deletion of IKZF1 and formation of P2RY8-CRLF2 fusion gene at recurrence. Throughout the cohort, hyperdiploid BCP-ALL cases had tendency to have RAS pathway somatic SNVs (KRAS, NRAS, FLT3, and PTPN11). In addition, one low hypodiploid BCP-ALL case had germline small Indel of TP53 and somatic SNV of RB. &amp;lt;Discussion&amp;gt; We add MLH1 alteration to the list of DNA repair pathway relapse-specific somatic alterations, further supporting the particular significance of DNA repair pathway as mechanism of BCP-ALL recurrence, probably related to massive acquisition of complex genetic alteration as a result of loss of DNA repair. In our cohort, the prevalence of previously reported relapse-specific mutation is relatively low, which may be caused by detection method and different ethnicity. Our novel cell line is useful staff for investigation to identify the role of DNA mismatch repair pathway in BCP-ALL leukemogenesis. Disclosures No relevant conflicts of interest to declare.

A Systematic Evaluation of High-Throughput Sequencing Approaches to Identify Low-Frequency Single Nucleotide Variants in Viral Populations.

High-throughput sequencing such as those provided by Illumina are an efficient way to understand sequence variation within viral populations. However, challenges exist in distinguishing process-introduced error from biological variance, which significantly impacts our ability to identify sub-consensus single-nucleotide variants (SNVs). Here we have taken a systematic approach to evaluate laboratory and bioinformatic pipelines to accurately identify low-frequency SNVs in viral populations. Artificial DNA and RNA “populations” were created by introducing known SNVs at predetermined frequencies into template nucleic acid before being sequenced on an Illumina MiSeq platform. These were used to assess the effects of abundance and starting input material type, technical replicates, read length and quality, short-read aligner, and percentage frequency thresholds on the ability to accurately call variants. Analyses revealed that the abundance and type of input nucleic acid had the greatest impact on the accuracy of SNV calling as measured by a micro-averaged Matthews correlation coefficient score, with DNA and high RNA inputs (107 copies) allowing for variants to be called at a 0.2% frequency. Reduced input RNA (105 copies) required more technical replicates to maintain accuracy, while low RNA inputs (103 copies) suffered from consensus-level errors. Base errors identified at specific motifs identified in all technical replicates were also identified which can be excluded to further increase SNV calling accuracy. These findings indicate that samples with low RNA inputs should be excluded for SNV calling and reinforce the importance of optimising the technical and bioinformatics steps in pipelines that are used to accurately identify sequence variants.

Clinical laboratory validation of the MCL35 assay for molecular risk stratification of mantle cell lymphoma

Mantle cell lymphoma (MCL) is a clinically heterogeneous B cell malignancy for which a variety of prognostic factors have been proposed. Previously, a digital gene expression profiling “proliferation signature” capable of risk stratifying MCL was identified and subsequently developed into a multi-analyte prognostic assay, known as the “MCL35” assay. In this study, we sought to explore the performance characteristics of the MCL35 assay in a clinical laboratory and compare results with the Ki67 proliferation marker. The results describe the clinical validation of the MCL35 assay for molecular risk stratification of MCL including accuracy, sensitivity, specificity, use in acid-decalcified bone marrow core biopsies, fixatives, lower limit of RNA input, quality metrics, and other laboratory parameters. The resulting data indicate that this is a robust technique with outstanding reproducibility. Overall, the data support the concept of molecular signatures, as assessed with digital gene expression profiling, for improved standardization and reproducibility for proliferation assessment in MCL.

A comprehensive RNA handling and transcriptomics guide for high-throughput processing of Plasmodium blood-stage samples

BackgroundSequencing technology advancements opened new opportunities to use transcriptomics for studying malaria pathology and epidemiology. Even though in recent years the study of whole parasite transcriptome proved to be essential in understanding parasite biology there is no compiled up-to-date reference protocol for the efficient generation of transcriptome data from growing number of samples. Here, a comprehensive methodology on how to preserve, extract, amplify, and sequence full-length mRNA transcripts from Plasmodium-infected blood samples is presented that can be fully streamlined for high-throughput studies.ResultsThe utility of various commercially available RNA-preserving reagents in a range of storage conditions was evaluated. Similarly, several RNA extraction protocols were compared and the one most suitable method for the extraction of high-quality total RNA from low-parasitaemia and low-volume blood samples was established. Furthermore, the criteria needed to evaluate the quality and integrity of Plasmodium RNA in the presence of human RNA was updated. Optimization of SMART-seq2 amplification method to better suit AT-rich Plasmodium falciparum RNA samples allowed us to generate high-quality transcriptomes from as little as 10 ng of total RNA and a lower parasitaemia limit of 0.05%. Finally, a modified method for depletion of unwanted human haemoglobin transcripts using in vitro CRISPR-Cas9 treatment was designed, thus improving parasite transcriptome coverage in low parasitaemia samples. To prove the functionality of the pipeline for both laboratory and field strains, the highest 2-hour resolution RNA-seq transcriptome for P. falciparum 3D7 intraerythrocytic life cycle available to date was generated, and the entire protocol was applied to create the largest transcriptome data from Southeast Asian field isolates.ConclusionsOverall, the presented methodology is an inclusive pipeline for generation of good quality transcriptomic data from a diverse range of Plasmodium-infected blood samples with varying parasitaemia and RNA inputs. The flexibility of this pipeline to be adapted to robotic handling will facilitate both small and large-scale future transcriptomic studies in the field of malaria.

Characterization of Emerging Swine Viral Diseases through Oxford Nanopore Sequencing Using Senecavirus A as a Model.

Emerging viral infectious diseases present a major threat to the global swine industry. Since 2015, Senecavirus A (SVA) has been identified as a cause of vesicular disease in different countries and is considered an emerging disease. Despite the growing concern about SVA, there is a lack of preventive and diagnostic strategies, which is also a problem for all emerging infectious diseases. Using SVA as a model, we demonstrated that Oxford Nanopore MinION sequencing could be used as a robust tool for the investigation and surveillance of emerging viral diseases. Our results identified that MinION sequencing allowed for rapid, unbiased pathogen detection at the species and strain level for clinical cases. SVA whole genome sequences were generated using both direct RNA sequencing and PCR-cDNA sequencing methods, with an optimized consensus accuracy of 94% and 99%, respectively. The advantages of direct RNA sequencing lie in its shorter turnaround time, higher analytical sensitivity and its quantitative relationship between input RNA and output sequencing reads, while PCR-cDNA sequencing excelled at creating highly accurate sequences. This study developed whole genome sequencing methods to facilitate the control of SVA and provide a reference for the timely detection and prevention of other emerging infectious diseases.

Transcriptome of airway neutrophils reveals an interferon response in life-threatening respiratory syncytial virus infection

BackgroundNeutrophils are the most abundant cell type infiltrating the airways during severe respiratory syncytial virus (RSV) infection. Their exact role in disease pathophysiology remains enigmatic. Therefore, we determined genome-wide RNA expression profiles of local and systemic neutrophils in RSV bronchiolitis to provide further insight into local neutrophil biology. MethodsWe performed a single-center analysis, in 16 infants, admitted to the pediatric intensive care unit with severe RSV bronchiolitis. Neutrophils were isolated from blood and tracheobronchial aspirates (sputum). After low input RNA sequencing, differential expression of genes was determined followed by gene set analysis. ResultsPaired transcriptomic analysis of airway versus blood neutrophils showed an inflammatory phenotype, characterized by NF-kB signaling and upregulated expression of IL-6 and interferon pathways. We observed distinct expression of neutrophil activation genes (TNFSF13B, FCER1G). DiscussionOur data indicate that airway neutrophils regulate their function at the transcriptional level in response to viral infection. It also suggests that local interferon drives the neutrophil response of severe RSV bronchiolitis.