Duplicate Reads Research Articles

Impact of Mark Duplicate Reads During Variant Calling in Next Generation Sequencing (NGS) Data of Pistacia vera L.

Impact of Mark Duplicate Reads During Variant Calling in Next Generation Sequencing (NGS) Data of Pistacia vera L.

Health-Related Physical Fitness Evaluation in HIV-Diagnosed Children and Adolescents: A Scoping Review.

Health-related physical fitness has been widely used to investigate the adverse effects of HIV infection/ART in children and adolescents. However, methods/protocols and cut-points applied for investigating health-related physical fitness are not clear. The aim of this scoping review was to map the literature to identify gaps in knowledge regarding the methods/protocols and cut-points. A scoping review, following the Joana Briggs Institute (JBI) guidelines, was conducted through ten major databases. Search followed the PCC strategy to construct block of terms related to population (children and adolescents), concept (health-related physical fitness components) and context (HIV infection). The search resulted in 7545 studies. After duplicate removal, titles and abstracts reading and full text assessment, 246 studies were included in the scoping review. Body composition was the most investigated component (n = 244), followed by muscular strength/endurance (n = 23), cardiorespiratory fitness (n = 15) and flexibility (n = 4). The World Health Organization growth curves, and nationals' surveys were the most reference values applied to classify body composition (n = 149), followed by internal cut-points (n = 30) and cut-points developed through small populations (n = 16). Cardiorespiratory fitness was classified through cut-points from three different assessment batteries, as well as cut-points developed through studies with small populations, muscular strength/endurance and flexibility were classified through the same cut-points from five different assessment batteries. The research on muscular strength/endurance, cardiorespiratory fitness and flexibility has been scarcely explored. The lack of studies that investigated method usability as well as reference values was evidenced.

Exploring a Transcriptome-forward Approach for Genetic Evaluation in Thoracic Aortopathy

Background/Objective: Thoracic aortic aneurysm (TAA) is an aortopathy that predisposes to aortic dissection and rupture. Transcriptomic analysis has diagnostic utility in other diseases, but this has not been developed for TAA. We therefore sought to implement the Genome Analysis Toolkit (GATK) as a tool for high-throughput detection of novel variants in RNA sequencing (RNA-seq) data from patients with TAA.
 Methods: Human proximal aortic tissue samples from 63 TAA patients and 15 controls were used to establish primary smooth muscle cell (SMC) lines in culture. Total RNA was extracted at early passage; RNA-seq was performed using 150 base pair paired-end reads. Variants were called from RNA-seq reads using the GATK’s HaplotypeCaller tool. The MarkDuplicates tool tagged duplicate reads, but these were retained for variant analysis. Singletons were defined as heterozygous variants unique to one sample in the overall group.
 Results: The RNA-seq pipeline was validated by confirming known mutations in 2 patients, inspecting reads directly in the Integrative Genomics Viewer (IGV), and genotyping for a common single nucleotide polymorphism. Across all 78 samples, the GATK pipeline identified 4,823,462 variant sites, 236,495 of which were in coding regions. Variant sites were filtered for those located within the coding regions of 31 genes curated for known evidence of aortic disease causality. Among the 511 coding variant sites in these genes, 330 single nucleotide variants and 33 insertions/deletions were identified as singletons. Singleton variant calls were evaluated for quality and annotated in order to predict their likelihood of pathogenicity, thus far identifying strong candidate causal variants in FBN1, TGFBR1, TGFB3, GATA4, and HEY2.
 Conclusion: Application of the GATK RNA-seq pipeline expands our prior IGV analysis, further demonstrating the potential diagnostic utility of transcriptomic analysis of aortic SMCs in TAA.
 Scientific Impact: Identifying novel aortopathy-associated variants could improve future disease detection and prediction of severity.

ScPipe: an extended preprocessing pipeline for comprehensive single-cell ATAC-Seq data integration in R/Bioconductor.

scPipe is a flexible R/Bioconductor package originally developed to analyse platform-independent single-cell RNA-Seq data. To expand its preprocessing capability to accommodate new single-cell technologies, we further developed scPipe to handle single-cell ATAC-Seq and multi-modal (RNA-Seq and ATAC-Seq) data. After executing multiple data cleaning steps to remove duplicated reads, low abundance features and cells of poor quality, a SingleCellExperiment object is created that contains a sparse count matrix with features of interest in the rows and cells in the columns. Quality control information (e.g. counts per cell, features per cell, total number of fragments, fraction of fragments per peak) and any relevant feature annotations are stored as metadata. We demonstrate that scPipe can efficiently identify 'true' cells and provides flexibility for the user to fine-tune the quality control thresholds using various feature and cell-based metrics collected during data preprocessing. Researchers can then take advantage of various downstream single-cell tools available in Bioconductor for further analysis of scATAC-Seq data such as dimensionality reduction, clustering, motif enrichment, differential accessibility and cis-regulatory network analysis. The scPipe package enables a complete beginning-to-end pipeline for single-cell ATAC-Seq and RNA-Seq data analysis in R.

Metagenomic analysis of soybean endosphere microbiome to reveal signatures of microbes for health and disease

BackgroundSoil metagenomics is a cultivation-independent molecular strategy for investigating and exploiting the diversity of soil microbial communities. Soil microbial diversity is essential because it is critical to sustaining soil health for agricultural productivity and protection against harmful organisms. This study aimed to perform a metagenomic analysis of the soybean endosphere (all microbial communities found in plant leaves) to reveal signatures of microbes for health and disease. ResultsThe dataset is based on the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) release “microbial diversity in soybean”. The quality control process rejected 21 of the evaluated sequences (0.03% of the total sequences). Dereplication determined that 68,994 sequences were artificial duplicate readings, and removed them from consideration. Ribosomal Ribonucleic acid (RNA) genes were present in 72,747 sequences that successfully passed quality control (QC). Finally, we found that hierarchical classification for taxonomic assignment was conducted using MG-RAST, and the considered dataset of the metagenome domain of bacteria (99.68%) dominated the other groups. In Eukaryotes (0.31%) and unclassified sequence 2 (0.00%) in the taxonomic classification of bacteria in the genus group, Streptomyces, Chryseobacterium, Ppaenibacillus, Bacillus, and Mitsuaria were found. We also found some biological pathways, such as CMP-KDO biosynthesis II (from D-arabinose 5-phosphate), tricarboxylic acid cycle (TCA) cycle (plant), citrate cycle (TCA cycle), fatty acid biosynthesis, and glyoxylate and dicarboxylate metabolism. Gene prediction uncovered 1,180 sequences, 15,172 of which included gene products, with the shortest sequence being 131 bases and maximum length 3829 base pairs. The gene list was additionally annotated using Integrated Microbial Genomes and Microbiomes. The annotation process yielded a total of 240 genes found in 177 bacterial strains. These gene products were found in the genome of strain 7598. Large volumes of data are generated using modern sequencing technology to sample all genes in all species present in a given complex sample. ConclusionsThese data revealed that it is a rich source of potential biomarkers for soybean plants. The results of this study will help us to understand the role of the endosphere microbiome in plant health and identify the microbial signatures of health and disease. The MG-RAST is a public resource for the automated phylogenetic and functional study of metagenomes. This is a powerful tool for investigating the diversity and function of microbial communities.

RNA Extraction Method Impacts Quality Metrics and Sequencing Results in Formalin-Fixed, Paraffin-Embedded Tissue Samples

Archived formalin-fixed, paraffin-embedded (FFPE) tissue samples are being increasingly used in molecular cancer research. Compared with fresh-frozen tissue, the nucleic acid analysis of FFPE tissue is technically more challenging. This study aimed to compare the impact of 3 different RNA extraction methods on yield, quality, and sequencing-based gene expression results in FFPE samples. RNA extraction was performed in 16 FFPE tumor specimens from patients with diffuse large B-cell lymphoma and in reference FFPE material from microsatellite-stable and microsatellite-instable cell lines (3 replicates each) using 2 silica-based procedures (A, miRNeasy FFPE; C, iCatcher FFPE Tissue RNA) and 1 isotachophoresis-based procedure (B, Ionic FFPE to Pure RNA). The RNA yield; RNA integrity, as reflected by the distribution value 200; and RNA purity, as reflected by the 260/280 and the 260/230 nm absorbance ratios, were determined. The RNA was sequenced on the NovaSeq 6000 instrument using the TruSeq RNA Exome and SMARTer Stranded Total RNA-Seq Pico v3 library preparations kits. Our results highlight the impact of RNA extraction methodology on both preanalytical and sequencing-based gene expression results. Overall, methods B and C outperformed method A because these showed significantly higher fractions of uniquely mapped reads, an increased number of detectable genes, a lower fraction of duplicated reads, and better representation of the B-cell receptor repertoire. Differences among the extraction methods were generally more explicit for the total RNA sequencing method than for the exome-capture sequencing method. Importantly, the predicative value of quality metrics varies among extraction kits, and caution should be applied when comparing and interpreting results obtained using different methods.

ESTABLISHMENT OF A BIOINFORMATICS PIPELINE FOR THE DETECTION OF PATHOGENIC BACTERIA

Next-generation sequencing-based methods using partial 16S rRNA gene amplicons are extensively applied today in studies of the plant metagenomes. NGS sequencing creates huge sets of raw data making analysis a challenging task. Lack of computational and bioinformatics knowledge and tools for analyzing high throughput data to interpret correct biological variations is a major problem. In addition, downstream analysis of NGS data with the available bioinformatics platforms create various challenges in inferring microbial composition. The available commercial software are expensive and individual opensource tools are usually operate stand alone as they are not combined for a user-friendly workflow. Therefore, beginners in bioinformatics might find analysis procedures are complicated, expensive, and timeconsuming with the associated learning. In the present study, a bioinformatics pipeline is developed to analyze the 16S rDNA amplicons of plant metagenome. Microbial DNA was extracted from imported seed potato tubers. Extracted DNA was sequenced using Ion Torrent Next Generation Sequencing technology by amplifying 400 bp V1-V2 region of 16S rRNA gene for the detection of bacterial pathogens. The pipeline was built by stringing together many command line tools; Quality checking of raw fastq data using FastQC, trimming of low-quality data with Trimmomatric, alignment of trimmed data using the BWA-MEM algorithm, removal of duplicate reads with Picard Mark Duplicates tool and finally generation of the phylogenetic tree and taxonomic profile with MEGAN 5. The developed pipeline was used to analyze the 16S rRNA next generation sequences and the reliability of the results has been checked with the use of mock communities for validation. The pipeline often can be executed on laptop sized machines to obtain the output in a couple of hours enabling easy access for the researchers.

Technological and computational advances driving high-throughput oncology.

Engineering and computational advances have opened many new avenues in cancer research, particularly when being exploited in interdisciplinary approaches. For example, the combination of microfluidics, novel sequencing technologies, and computational analyses has been crucial to enable single-cell assays, giving a detailed picture of tumor heterogeneity for the very first time. In a similar way, these 'tech' disciplines have been elementary for generating large data sets in multidimensional cancer 'omics' approaches, cell-cell interaction screens, 3D tumor models, and tissue level analyses. In this review we summarize the most important technology and computational developments that have been or will be instrumental for transitioning classical cancer research to a large data-driven, high-throughput, high-content discipline across all biological scales.

A Case Study for the Recovery of Authentic Microbial Ancient DNA from Soil Samples.

High Throughput DNA Sequencing (HTS) revolutionized the field of paleomicrobiology, leading to an explosive growth of microbial ancient DNA (aDNA) studies, especially from environmental samples. However, aDNA studies that examine environmental microbes routinely fail to authenticate aDNA, examine laboratory and environmental contamination, and control for biases introduced during sample processing. Here, we surveyed the available literature for environmental aDNA projects—from sample collection to data analysis—and assessed previous methodologies and approaches used in the published microbial aDNA studies. We then integrated these concepts into a case study, using shotgun metagenomics to examine methodological, technical, and analytical biases during an environmental aDNA study of soil microbes. Specifically, we compared the impact of five DNA extraction methods and eight bioinformatic pipelines on the recovery of microbial aDNA information in soil cores from extreme environments. Our results show that silica-based methods optimized for aDNA research recovered significantly more damaged and shorter reads (<100 bp) than a commercial kit or a phenol–chloroform method. Additionally, we described a stringent pipeline for data preprocessing, efficiently decreasing the representation of low-complexity and duplicated reads in our datasets and downstream analyses, reducing analytical biases in taxonomic classification.

P989: DYNAMIC CHANGES IN THE HISTONE H3 LYSINE 27 TRIMETHYLATION EPIGENETIC LANDSCAPE FOLLOWING RUXOLITINIB ADMINISTRATION

Background: Dysregulation of normal epigenetic processes is increasingly recognised as a feature of myeloid malignancy generally and implicated in the pathogenesis of MPN. Epigenetic changes may directly result from the mutation of key epigenetic regulators including TET2, ASXL1 and EZH2 or indirectly from the activation of intracellular signalling cascades. We have previously observed that ruxolitinib, a JAK1/2 inhibitor, may alter the epigenetic landscape of histone modifications in MPN. CUT&RUN is a novel experimental approach providing high resolution profiling of epigenetic modifications and transcription factor binding. Aims: To comprehensively profile the H3K27me3 epigenetic landscape of JAK2 V617F positive cells resulting from JAK inhibition and determine the dynamic changes occurring between short term and persistent ruxolitinib therapy to identify potential genetic contributors to pathogenesis and options for future therapeutics. Methods:JAK2 V617F positive UKE1 cells were cultured in duplicate in the presence of 1000nM ruxolitinib or DMSO 0.1% vehicle control continuously for approximately five weeks. Samples were harvested at 37 days for CUT&RUN analysis using H3K27me3, EZH2 and IgG (negative control) antibodies. CUT&RUN performed using Epicypher CUTANA Kit according to manufacturer instructions. Libraries prepared using NEBNext® Ultra™ II DNA Library Prep kit with 50 base pair, paired end sequencing undertaken on Illumina NovaSeq 6000. Resulting FASTQ files were trimmed using Trim Galore! and aligned to reference genome hg38 using Bowtie2. Duplicate reads were removed using SAMtools rmdup and peaks called with MACS2 callpeak on the usegalaxy.eu platform. Differential peak analysis undertaken with Diffbind package in R. Samples were normalised to library size prior to differential analysis with DESeq2 methodology. Bigwig files generated using deepTools bamcoverage for visualisation. Results: UKE1 cells remain sensitive to ruxolitinib after a period of treatment with high dose ruxolitinib lasting over 5 weeks. CUT&RUN libraries were sequenced to a minimum depth of 3.6 million unique reads per sample. Initial comparisons between Day 37 high dose treated cells and vehicle control revealed 1004 differentially enriched H3K27me3 peaks. Of these, 545 (54.2%) peaks were increased in the ruxolitinib treated cells and 459 (45.7%) peaks were increased in the control cells. Analysis of the difference between day 37 and day 1 high dose ruxolitinib treated cells revealed 290 peaks differentially enriched. Of these peaks, 279 (96.2%) were increased and 11 (3.8%) were decreased at day 37. Analysis of the overlap between these results identified 33 peaks increased at D37 in comparison to DMSO control and day 1 treatment samples. Analysis of the differential binding patterns and direct visualisation of the results in a genome browser revealed particular genetic locations of interest including the promoter region of SPRY1, a potential regulator of erythropoiesis and JAK signalling, UGCG and BTBD11. Figure 1 shows an example. Differential H3K27me3 was also noted at regions associated with PLXNA1 and NRP2 genes which act as co-receptors for class III semaphorin signalling. Image:Summary/Conclusion: The dynamic changes in the H3K27me3 epigenetic landscape of JAK2 V617F positive cells following persistent high dose ruxolitinib administration has potential therapeutic implications and may sensitise cells to epigenetic therapies. Specific gene loci identified demonstrating differential H3K27me3 may offer some insight into JAK2 V617F mediated pathology and require further investigation.

The effect of hemolysis on quality control metrics for noninvasive prenatal testing

BackgroundNoninvasive prenatal testing (NIPT) is the testing of blood samples from pregnant women to screen for fetal risk of chromosomal disorders. Even though in vitro hemolysis of blood specimens is common in clinical laboratories, its influence on NIPT has not been well investigated.MethodsPeripheral blood samples were collected from 205 pregnant women and categorized according to the concentration of free hemoglobin in the plasma. After performing NIPT using massively parallel sequencing, the quality control metrics were analyzed and compared with samples that did not undergo hemolysis or samples redrawn from the same women.ResultsThe specimens were divided into four groups based on the concentration of free hemoglobin: Group I (0–1 g/L, n = 53), Group II (1–2 g/L, n = 97), Group III (2–4 g/L, n = 30), and Group IV (> 4 g/L, n = 25). There was no significant difference in the quality control metrics of clinical samples with slight or moderate hemolysis (Group II and III). However, samples with severe hemolysis (Group IV) showed a significantly increased rate of duplicated reads (duplication rate) and fetal fraction, as well as decreased library concentration compared with samples without hemolysis. Moreover, the increase in fetal fraction caused by hemolysis was confirmed by redrawing blood samples in Group IV.ConclusionFor NIPT using massively parallel sequencing, samples with slight or moderate hemolysis (≤ 4 g/L) are acceptable. However, careful consideration should be taken regarding the use of severely hemolyzed samples (> 4 g/L), since they might increase the risk of test failure.

The impact of tobacco smoking and electronic cigarette vaping on salivary biomarkers. A comparative study

ObjectivesThis study aimed to investigate the effect of electronic cigarette vaping and cigarette smoking on the levels of interleukin-1β and transforming growth factor‑β salivary biomarkers compared to non-smokers. MethodsOne hundred and fifty people participated in this study; There were 50 participants who smoked traditional cigarettes, 50 who used electronic cigarettes, and 50 healthy people who had never smoked cigarettes (control group). Furthermore, 5 ml of unstimulated whole saliva was sampled and clarified by centrifugation and frozen until analysis. Interleukin-1β and transforming growth factor‑β concentrations were assessed in saliva samples using ELISA. The duplicate readings average was utilized to interpret the data. ResultsWe found that cigarette smokers had significantly higher levels of interleukin-1β and transforming growth factor‑β than non-smokers and electronic cigarette users (p < 0.05). The difference between control participants and electronic cigarette users, as well as that between control participants and traditional cigarette smokers, was statistically significant (p < 0.05). ConclusionElectronic cigarette users have higher levels of inflammatory and cancer risk biomarker than non-smokers, suggesting that electronic cigarettes can pose a risk of developing systemic diseases but less than conventional cigarettes. In conclusion, our study could be regarded as new evidence supporting the hazardous effects of e-cigs using a cost-effective, non-invasive method.

2022 Guidelines of the Taiwan Society of Cardiology and the Taiwan Hypertension Society for the Management of Hypertension.

Hypertension is the most important modifiable cause of cardiovascular (CV) disease and all-cause mortality worldwide. Despite the positive correlations between blood pressure (BP) levels and later CV events since BP levels as low as 100/60 mmHg have been reported in numerous epidemiological studies, the diagnostic criteria of hypertension and BP thresholds and targets of antihypertensive therapy have largely remained at the level of 140/90 mmHg in the past 30 years. The publication of both the SPRINT and STEP trials (comprising > 8,500 Caucasian/African and Chinese participants, respectively) provided evidence to shake this 140/90 mmHg dogma. Another dogma regarding hypertension management is the dependence on office (or clinic) BP measurements. Although standardized office BP measurements have been widely recommended and adopted in large-scale CV outcome trials, the practice of office BP measurements has never been ideal in real-world practice. Home BP monitoring (HBPM) is easy to perform, more likely to be free of environmental and/or emotional stress, feasible to document long-term BP variations, of good reproducibility and reliability, and more correlated with hypertension-mediated organ damage (HMOD) and CV events, compared to routine office BP measurements. In the 2022 Taiwan Hypertension Guidelines of the Taiwan Society of Cardiology (TSOC) and the Taiwan Hypertension Society (THS), we break these two dogmas by recommending the definition of hypertension as ≥ 130/80 mmHg and a universal BP target of < 130/80 mmHg, based on standardized HBPM obtained according to the 722 protocol. The 722 protocol refers to duplicate BP readings taken per occasion ("2"), twice daily ("2"), over seven consecutive days ("7"). To facilitate implementation of the guidelines, a series of flowcharts encompassing assessment, adjustment, and HBPM-guided hypertension management are provided. Other key messages include that: 1) lifestyle modification, summarized as the mnemonic S-ABCDE, should be applied to people with elevated BP and hypertensive patients to reduce life-time BP burden; 2) all 5 major antihypertensive drugs (angiotensin-converting enzyme inhibitors [A], angiotensin receptor blockers [A], β-blockers [B], calcium-channel blockers [C], and thiazide diuretics [D]) are recommended as first-line antihypertensive drugs; 3) initial combination therapy, preferably in a single-pill combination, is recommended for patients with BP ≥ 20/10 mmHg above targets; 4) a target hierarchy (HBPM-HMOD- ambulatory BP monitoring [ABPM]) should be considered to optimize hypertension management, which indicates reaching the HBPM target first and then keeping HMOD stable or regressed, otherwise ABPM can be arranged to guide treatment adjustment; and 5) renal denervation can be considered as an alternative BP-lowering strategy after careful clinical and imaging evaluation.

Fast-HBR: Fast hash based duplicate read remover.

The Next-Generation Sequencing (NGS) platforms produce massive amounts of data to analyze various features in environmental samples. These data contain multiple duplicate reads which impact the analyzing process efficiency and accuracy. We describe Fast-HBR, a fast and memory-efficient duplicate reads removing tool without a reference genome using de-novo principles. It uses hash tables to represent reads in integer value to minimize memory usage for faster manipulation. Fast-HBR is faster and has less memory footprint when compared with the state of the art De-novo duplicate removing tools. Fast-HBR implemented in Python 3 is available at https://github.com/Sami-Altayyar/Fast-HBR.

Halvade somatic: Somatic variant calling with Apache Spark.

BackgroundThe accurate detection of somatic variants from sequencing data is of key importance for cancer treatment and research. Somatic variant calling requires a high sequencing depth of the tumor sample, especially when the detection of low-frequency variants is also desired. In turn, this leads to large volumes of raw sequencing data to process and hence, large computational requirements. For example, calling the somatic variants according to the GATK best practices guidelines requires days of computing time for a typical whole-genome sequencing sample.FindingsWe introduce Halvade Somatic, a framework for somatic variant calling from DNA sequencing data that takes advantage of multi-node and/or multi-core compute platforms to reduce runtime. It relies on Apache Spark to provide scalable I/O and to create and manage data streams that are processed on different CPU cores in parallel. Halvade Somatic contains all required steps to process the tumor and matched normal sample according to the GATK best practices recommendations: read alignment (BWA), sorting of reads, preprocessing steps such as marking duplicate reads and base quality score recalibration (GATK), and, finally, calling the somatic variants (Mutect2). Our approach reduces the runtime on a single 36-core node to 19.5 h compared to a runtime of 84.5 h for the original pipeline, a speedup of 4.3 times. Runtime can be further decreased by scaling to multiple nodes, e.g., we observe a runtime of 1.36 h using 16 nodes, an additional speedup of 14.4 times. Halvade Somatic supports variant calling from both whole-genome sequencing and whole-exome sequencing data and also supports Strelka2 as an alternative or complementary variant calling tool. We provide a Docker image to facilitate single-node deployment. Halvade Somatic can be executed on a variety of compute platforms, including Amazon EC2 and Google Cloud.ConclusionsTo our knowledge, Halvade Somatic is the first somatic variant calling pipeline that leverages Big Data processing platforms and provides reliable, scalable performance. Source code is freely available.

Abstract 556: Highly complex DNA sequencing library preparation for cfDNA enrichment panels using a single-stranded approach

Abstract DNA sequencing library preparation is a crucial step for next-generation sequencing of cell free DNA of plasma for cancer diagnostics. We present SRSLY, a robust single-stranded DNA library preparation method, that generates libraries with unique molecule identifiers (UMIs), with advantages over traditional double-stranded DNA preparations. Using 5 ng of plasma-derived cfDNA from acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and gastrointestinal cancer cases, we prepared both SRSLY and double-stranded DNA (dsDNA) sequencing libraries with UMIs. The libraries were enriched using a Twist Biosciences custom hybridization probe set for an 800 kilobase cancer mutation panel. We sequenced to a panel depth of 1000x to 2000x, after correcting UMI sequences and removing duplicate reads. With comparable fold enrichment and on-target percentages, we observe complexities of 11-21 million unique molecules with SRSLY. This is approximately four times higher than dsDNA complexity of 2.8-4.9 million unique molecules. Using duplicate reads from the same unique molecule, we perform error correction on template read bases and are able to call low-variant allele frequency mutations. In particular, we show an increase in KRAS p.G12D variant allele fraction during progression from MDS to AML. SRSLY shows increased recovery of small fragments over dsDNA preparations and retains the native lengths and termini of all fragments. Apart from improved library complexity, we show that MDS and AML samples can be distinguished from healthy samples by their disrupted genomic profile of short to long fragments, which has been previously demonstrated in solid tumors but not for MDS or AML. Citation Format: Charles J. Vaske, Chris Troll, Camille Schwartz, Colin Naughton, Abdullah Mahmood Ali, Azra Raza, Varsha Rao, Kelly Harkins-Kincaid, Richard Edward Green. Highly complex DNA sequencing library preparation for cfDNA enrichment panels using a single-stranded approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 556.

MDS Diagnosis Using cfRNA Profiling By Targeted Enrichment Next Generation Sequencing

Introduction: The confirmation of a diagnosis of myelodysplastic syndrome (MDS) can be very difficult based on morphology alone. The detection of cytogenetic abnormalities or the presence of mutations in one or more of the myeloid-related genes can provide significant help in confirming this diagnosis. However, some patients with MDS may lack mutations or cytogenetic abnormalities. Cell free DNA (cfDNA) and microRNA are used extensively in testing for molecular abnormalities in hematologic and solid tumors, but little is known about the value of cell free mRNA (cfRNA) in liquid biopsy. We explored the use of targeted enrichment and Next Generation Sequencing (NGS) of cfRNA in the RNA profiling and diagnosis of MDS.Methods: We used NucliSenS EasyMAG (bioMérieux, Marcy-l'Étoile, France) automated platform for extracting total nucleic acid from peripheral blood plasma collected in EDTA. We used the TruSight RNA Pan-Cancer Panel (Illumina, San Diego, CA) for detecting fusion, expression, and mutations in 1385 genes. The Pan-Cancer Panel is a hybridization based targeted panel, therefore alignments and gene expression are calculated only to the 1385 genes as per manufacturer recommendations. Each sample was deeply sequenced (>55M reads) using Illumina paired-end 75 bp sequencing and duplicate reads were removed before fragment per kilobase of transcript per million mapped reads (FPKMs) were calculated for each gene. Samples from 23 patients were analyzed including 19 patients confirmed by molecular, cytogenetic, and morphologic methods to have MDS or chronic myelomonocytic leukemia (CMML) and 4 individuals who had one or more cytopenia, but MDS was ruled out by molecular mutation analysis, cytogenetics, as well as morphology. Expression levels were first normalized using ABL1 and PAX5 (i.e., regressing each gene on ABL1 and PAX5 jointly and using the residuals instead of the raw data) and models for distinguishing MDS from non-MDS were developed.Results: In this study, only expression levels were considered and not the mutational profile. We used t-tests and examined the statistical significance of each gene separately. Then we selected genes with P-values < 0.05 to filter out non-significant genes, resulting in 49 significant genes. After adjusting for multiple hypothesis testing, only three genes remained significant with false discovery rate set at 0.1. The three genes were: CBFB, RASGRF2, and SP1 . Using a logistic regression model based on these three variables, we were able to obtain accuracy rate of 87.0% and AUC (area under the ROC curve) of 92.1% based on the leave-one-out testing. This model identified all the normal cases correctly, but misclassified 3 MDS cases as normal. Alternatively, using the top 3 principal components based on the selected 49 significant genes in a linear regression model, we can improve prediction and AUC to 95.6% and 96.7%, respectively, based on the leave-one-out testing. In this model, only one MDS case (out of 19) was misclassified as normal, while all the normal cases were classified correctly.Conclusion: Although additional studies and validation are needed, RNA profiling using targeted enrichment NGS of cfRNA is potentially useful in the classification and diagnosis of MDS. This model can be expanded to incorporate an entire mutational profile assessment. This approach has the potential to be used not only for MDS diagnosis, but also in the diagnosis, prognostic prediction and response to therapy of a variety of myeloid and lymphoid neoplasms. [Display omitted] DisclosuresWong:NeoGenomics: Employment. Funari:NeoGenomics: Employment. Ma:NeoGenomics: Employment. De Dios:NeoGenomics: Employment. Blocker:NeoGenomics: Employment. Albitar:NeoGenomics: Employment.

METTL3 regulates viral m6A RNA modification and host cell innate immune responses during SARS-CoV-2 infection.

It is urgent and important to understand the relationship of the widespread severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2) with host immune response and study the underlining molecular mechanism. N6-methylation of adenosine (m6A) in RNA regulates many physiological and disease processes. Here, we investigate m6A modification of the SARS-CoV-2 gene in regulating the host cell innate immune response. Our data show that the SARS-CoV-2 virus has m6A modifications that are enriched in the 3′ end of the viral genome. We find that depletion of the host cell m6A methyltransferase METTL3 decreases m6A levels in SARS-CoV-2 and host genes, and m6A reduction in viral RNA increases RIG-I binding and subsequently enhances the downstream innate immune signaling pathway and inflammatory gene expression. METTL3 expression is reduced and inflammatory genes are induced in patients with severe coronavirus disease 2019 (COVID-19). These findings will aid in the understanding of COVID-19 pathogenesis and the design of future studies regulating innate immunity for COVID-19 treatment.

Flash Glucose Monitoring Compared to Capillary Glucose Levels in Patients With Diabetic Ketoacidosis: Potential Clinical Applications

ObjectiveFrequent, finger-prick capillary blood glucose measurement is standard care, used to drive insulin infusion rates for inpatients being resuscitated from diabetic ketoacidosis (DKA). Over recent years there has been a shift toward continuous interstitial glucose monitoring, allowing monitoring of glucose without repeated invasive testing. While continuous interstitial glucose monitoring has been safely and reliably utilized in the outpatient setting, it has yet to be studied in acutely unwell patients with DKA. The aim of this study, allowing for physiologically lower interstitial compared to capillary glucose, was to determine if interstitial flash glucose monitoring (FGM) would lead to insulin infusion rates that were similar to capillary blood glucose (CapBG) in DKA. MethodsIn this study, 10 patients with diabetes mellitus, assessed to be in DKA, were enrolled. At the same time as standard DKA management commencement, simultaneous FGM measurements were obtained. Duplicate paired glucose readings were then analyzed for agreement. ResultsActual (CapBG-driven) and predicted (FGM determined) insulin infusion rates were similar. Minor differences in predicted insulin infusion rates were noted in 2/10 patients at higher glucose concentrations, which may relate to the lag in change in glucose in the interstitial space. ConclusionBased on our results, a trial of clinical outcomes in patients with DKA treated with insulin infusion rates driven by CapBG versus subcutaneous FGM appears justified. The FGM method of testing may improve patient comfort, obviate fatigue, improve staff time and direct patient contact, and potentially facilitate rapid discharge.

Reproducibility of the creamatocrit technique for the measurement of fat content in human milk

Quantification of human milk (HM) fat is important for determining the energy intake of infants. The simplest and most rapid method is the creamatocrit method. However, the reliability of the creamatocrit has not been comprehensively investigated. The aims of this study were to test the inter- and-intra-rater reliability of: 1) HM sampling after hand- or-machine mixing methods and 2) HM fat measurement by the creamatocrit method. Inter-and-intra rater HM sampling after hand- or-machine mixing methods had high intraclass correlation coefficient (>0.91). Inter-rater reliability of measurement of HM with low fat (<2%) resulted in high variability (median coefficient of variations (CVs) > 15%). Intra- and inter-rater reliability of measurement of HM with higher fat (>3.5%) had low variability (median CVs < 10%). As the greatest variation in the creamatocrit method occurred during the measurement of HM samples with low fat, duplicate readings are necessary to reduce discrepancies in every HM fat determination.