Identification of Torquetenovirus Species in Patients with Kawasaki Disease Using a Newly Developed Species-Specific PCR Method.

A next-generation sequencing (NGS) study identified a very high viral load of Torquetenovirus (TTV) in KD patients. We aimed to evaluate the feasibility of a newly developed quantitative species-specific TTV-PCR (ssTTV-PCR) method to identify the etiology of KD. We applied ssTTV-PCR to samples collected from 11 KD patients and 22 matched control subjects who participated in our previous prospective study. We used the NGS dataset from the previous study to validate ssTTV-PCR. The TTV loads in whole blood and nasopharyngeal aspirates correlated highly (Spearman's R = 0.8931, p < 0.0001, n = 33), supporting the validity of ssTTV-PCR. The ssTTV-PCR and NGS results were largely consistent. However, inconsistencies occurred when ssTTV-PCR was more sensitive than NGS, when the PCR primer sequences mismatched the viral sequences in the participants, and when the NGS quality score was low. Interpretation of NGS requires complex procedures. ssTTV-PCR is more sensitive than NGS but may fail to detect a fast-evolving TTV species. It would be prudent to update primer sets using NGS data. With this precaution, ssTTV-PCR can be used reliably in a future large-scale etiological study for KD.

Advances in developmental biology using next-generation sequencing (NGS): Workshop for next-generation researchers.

This is a meeting report of "The workshop of research and techniques using next-generation sequencing (NGS) for developmental biology 2022." About 20 researchers attended the workshop. We discuss their NGS studies and techniques.

Metagenomics characterization of respiratory viral RNA pathogens in children under five years with severe acute respiratory infection in the Free State, South Africa.

Prompt detection of viral respiratory pathogens is crucial in managing respiratory infection including severe acute respiratory infection (SARI). Metagenomics next-generation sequencing (mNGS) and bioinformatics analyses remain reliable strategies for diagnostic and surveillance purposes. This study evaluated the diagnostic utility of mNGS using multiple analysis tools compared with multiplex real-time PCR for the detection of viral respiratory pathogens in children under 5 years with SARI. Nasopharyngeal swabs collected in viral transport media from 84 children admitted with SARI as per the World Health Organization definition between December 2020 and August 2021 in the Free State Province, South Africa, were used in this study. The obtained specimens were subjected to mNGS using the Illumina MiSeq system, and bioinformatics analysis was performed using three web-based analysis tools; Genome Detective, One Codex and Twist Respiratory Viral Research Panel. With average reads of 211323, mNGS detected viral pathogens in 82 (97.6%) of the 84 patients. Viral aetiologies were established in nine previously undetected/missed cases with an additional bacterial aetiology (Neisseria meningitidis) detected in one patient. Furthermore, mNGS enabled the much needed viral genotypic and subtype differentiation and provided significant information on bacterial co-infection despite enrichment for RNA viruses. Sequences of nonhuman viruses, bacteriophages, and endogenous retrovirus K113 (constituting the respiratory virome) were also uncovered. Notably, mNGS had lower detectability rate for severe acute respiratory syndrome coronavirus 2 (missing 18/32 cases). This study suggests that mNGS, combined with multiple/improved bioinformatics tools, is practically feasible for increased viral and bacterial pathogen detection in SARI, especially in cases where no aetiological agent could be identified by available traditional methods.

Minimal requirements for ISO15189 validation and accreditation of three next generation sequencing procedures for SARS-CoV-2 surveillance in clinical setting.

Rapid and recurrent breakthroughs of new SARS-CoV-2 strains (variants) have prompted public health authorities worldwide to set up surveillance networks to monitor the circulation of variants of concern. The use of next-generation sequencing technologies has raised the need for quality control assessment as required in clinical laboratories. The present study is the first to propose a validation guide for SARS-CoV-2 typing using three different NGS methods fulfilling ISO15189 standards. These include the assessment of the risk, specificity, accuracy, reproducibility, and repeatability of the methods. Among the three methods used, two are amplicon-based involving reverse transcription polymerase chain reaction (Artic v3 and Midnight v1) on Oxford Nanopore Technologies while the third one is amplicon-based using reverse complement polymerase chain reaction (Nimagen) on Illumina technology. We found that all methods met the quality requirement (e.g., 100% concordant typing results for accuracy, reproducibility, and repeatability) for SARS-CoV-2 typing in clinical setting. Additionally, the typing results emerging from each of the three sequencing methods were compared using three widely known nomenclatures (WHO, Pangolineage, and Nextclade). They were also compared regarding single nucleotide variations. The outcomes showed that Artic v3 and Nimagen should be privileged for outbreak investigation as they provide higher quality results for samples that do not meet inclusion criteria for analysis in a clinical setting. This study is a first step towards validation of laboratory developed NGS tests in the context of the new European regulation for medical devices and in vitro diagnostics.

SARS-CoV-2 Sequencing for Variant Surveillance.

In this chapter, next-generation sequencing of the entire viral genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is described. Successful sequencing of the SARS-CoV-2 virus is dependent upon quality of the specimen, adequate coverage of the entire genome, and up-to-date annotation. Some of the advantages of performing SARS-CoV-2 surveillance using next-generation sequencing are scalability, high-throughput, cost, and full genome analysis. Some of the disadvantages can be expensive instrumentation, large upfront reagent and supply costs, increased time-to-result, computational needs, and complicated bioinformatics. This chapter will provide an overview of a modified FDA Emergency Use Authorization procedure for the genomic sequencing of SARS-CoV-2. The procedure is also referred to as the research use only (RUO) version.

Evaluation of miniaturized Illumina DNA preparation protocols for SARS-CoV-2 whole genome sequencing.

The global pandemic caused by SARS-CoV-2 has increased the demand for scalable sequencing and diagnostic methods, especially for genomic surveillance. Although next-generation sequencing has enabled large-scale genomic surveillance, the ability to sequence SARS-CoV-2 in some settings has been limited by the cost of sequencing kits and the time-consuming preparations of sequencing libraries. We compared the sequencing outcomes, cost and turn-around times obtained using the standard Illumina DNA Prep kit protocol to three modified protocols with fewer clean-up steps and different reagent volumes (full volume, half volume, one-tenth volume). We processed a single run of 47 samples under each protocol and compared the yield and mean sequence coverage. The sequencing success rate and quality for the four different reactions were as follows: the full reaction was 98.2%, the one-tenth reaction was 98.0%, the full rapid reaction was 97.5% and the half-reaction, was 97.1%. As a result, uniformity of sequence quality indicated that libraries were not affected by the change in protocol. The cost of sequencing was reduced approximately seven-fold and the time taken to prepare the library was reduced from 6.5 hours to 3 hours. The sequencing results obtained using the miniaturised volumes showed comparability to the results obtained using full volumes as described by the manufacturer. The adaptation of the protocol represents a lower-cost, streamlined approach for SARS-CoV-2 sequencing, which can be used to produce genomic data quickly and more affordably, especially in resource-constrained settings.

TaME-seq2: tagmentation-assisted multiplex PCR enrichment sequencing for viral genomic profiling.

BACKGROUND: Previously developed TaME-seq method for deep sequencing of HPV, allowed simultaneous identification of the human papillomavirus (HPV) DNA consensus sequence, low-frequency variable sites, and chromosomal integration events. The method has been successfully validated and applied to the study of five carcinogenic high-risk (HR) HPV types (HPV16, 18, 31, 33, and 45). Here, we present TaME-seq2 with an updated laboratory workflow and bioinformatics pipeline. The HR-HPV type repertoire was expanded with HPV51, 52, and 59. As a proof-of-concept, TaME-seq2 was applied on SARS-CoV-2 positive samples showing the method's flexibility to a broader range of viruses, both DNA and RNA. RESULTS: Compared to TaME-seq version 1, the bioinformatics pipeline of TaME-seq2 is approximately 40× faster. In total, 23 HPV-positive samples and seven SARS-CoV-2 clinical samples passed the threshold of 300× mean depth and were submitted to further analysis. The mean number of variable sites per 1 kb was ~ 1.5× higher in SARS-CoV-2 than in HPV-positive samples. Reproducibility and repeatability of the method were tested on a subset of samples. A viral integration breakpoint followed by a partial genomic deletion was found in within-run replicates of HPV59-positive sample. Identified viral consensus sequence in two separate runs was > 99.9% identical between replicates, differing by a couple of nucleotides identified in only one of the replicates. Conversely, the number of identical minor nucleotide variants (MNVs) differed greatly between replicates, probably caused by PCR-introduced bias. The total number of detected MNVs, calculated gene variability and mutational signature analysis, were unaffected by the sequencing run. CONCLUSION: TaME-seq2 proved well suited for consensus sequence identification, and the detection of low-frequency viral genome variation and viral-chromosomal integrations. The repertoire of TaME-seq2 now encompasses seven HR-HPV types. Our goal is to further include all HR-HPV types in the TaME-seq2 repertoire. Moreover, with a minor modification of previously developed primers, the same method was successfully applied for the analysis of SARS-CoV-2 positive samples, implying the ease of adapting TaME-seq2 to other viruses.

Reads2Vec: Efficient Embedding of Raw High-Throughput Sequencing Reads Data.

The massive amount of genomic data appearing for SARS-CoV-2 since the beginning of the COVID-19 pandemic has challenged traditional methods for studying its dynamics. As a result, new methods such as Pangolin, which can scale to the millions of samples of SARS-CoV-2 currently available, have appeared. Such a tool is tailored to take as input assembled, aligned, and curated full-length sequences, such as those found in the GISAID database. As high-throughput sequencing technologies continue to advance, such assembly, alignment, and curation may become a bottleneck, creating a need for methods that can process raw sequencing reads directly. In this article, we propose Reads2Vec, an alignment-free embedding approach that can generate a fixed-length feature vector representation directly from the raw sequencing reads without requiring assembly. Furthermore, since such an embedding is a numerical representation, it may be applied to highly optimized classification and clustering algorithms. Experiments on simulated data show that our proposed embedding obtains better classification results and better clustering properties contrary to existing alignment-free baselines. In a study on real data, we show that alignment-free embeddings have better clustering properties than the Pangolin tool and that the spike region of the SARS-CoV-2 genome heavily informs the alignment-free clusterings, which is consistent with current biological knowledge of SARS-CoV-2.

A comparison of five Illumina, Ion Torrent, and nanopore sequencing technology-based approaches for whole genome sequencing of SARS-CoV-2.

Rapid identification of the rise and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern remains critical for monitoring of the efficacy of diagnostics, therapeutics, vaccines, and control strategies. A wide range of SARS-CoV-2 next-generation sequencing (NGS) methods have been developed over the last years, but cross-sequence technology benchmarking studies have been scarce. In the current study, 26 clinical samples were sequenced using five protocols: AmpliSeq SARS-CoV-2 (Illumina), EasySeq RC-PCR SARS-CoV-2 (Illumina/NimaGen), Ion AmpliSeq SARS-CoV-2 (Thermo Fisher), custom primer sets (Oxford Nanopore Technologies (ONT)), and capture probe-based viral metagenomics (Roche/Illumina). Studied parameters included genome coverage, depth of coverage, amplicon distribution, and variant calling. The median SARS-CoV-2 genome coverage of samples with cycle threshold (Ct) values of 30 and lower ranged from 81.6 to 99.8% for, respectively, the ONT protocol and Illumina AmpliSeq protocol. Correlation of coverage with PCR Ct values varied per protocol. Amplicon distribution signatures differed across the methods, with peak differences of up to 4 log10 at disbalanced positions in samples with high viral loads (Ct values ≤ 23). Phylogenetic analyses of consensus sequences showed clustering independent of the workflow used. The proportion of SARS-CoV-2 reads in relation to background sequences, as a (cost-)efficiency metric, was the highest for the EasySeq protocol. The hands-on time was the lowest when using EasySeq and ONT protocols, with the latter additionally having the shortest sequence runtime. In conclusion, the studied protocols differed on a variety of the studied metrics. This study provides data that assist laboratories when selecting protocols for their specific setting.

Magnetic hydrogel particles improve nanopore sequencing of SARS-CoV-2 and other respiratory viruses.

Presented here is a magnetic hydrogel particle enabled workflow for capturing and concentrating SARS-CoV-2 from diagnostic remnant swab samples that significantly improves sequencing results using the Oxford Nanopore Technologies MinION sequencing platform. Our approach utilizes a novel affinity-based magnetic hydrogel particle, circumventing low input sample volumes and allowing for both rapid manual and automated high throughput workflows that are compatible with Nanopore sequencing. This approach enhances standard RNA extraction protocols, providing up to 40 × improvements in viral mapped reads, and improves sequencing coverage by 20-80% from lower titer diagnostic remnant samples. Furthermore, we demonstrate that this approach works for contrived influenza virus and respiratory syncytial virus samples, suggesting that it can be used to identify and improve sequencing results of multiple viruses in VTM samples. These methods can be performed manually or on a KingFisher automation platform.

Targeted Sequencing Approach and Its Clinical Applications for the Molecular Diagnosis of Human Diseases.

The outbreak of COVID-19 has positively impacted the NGS market recently. Targeted sequencing (TS) has become an important routine technique in both clinical and research settings, with advantages including high confidence and accuracy, a reasonable turnaround time, relatively low cost, and fewer data burdens with the level of bioinformatics or computational demand. Since there are no clear consensus guidelines on the wide range of next-generation sequencing (NGS) platforms and techniques, there is a vital need for researchers and clinicians to develop efficient approaches, especially for the molecular diagnosis of diseases in the emergency of the disease and the global pandemic outbreak of COVID-19. In this review, we aim to summarize different methods of TS, demonstrate parameters for TS assay designs, illustrate different TS panels, discuss their limitations, and present the challenges of TS concerning their clinical application for the molecular diagnosis of human diseases.

AccuVIR: an ACCUrate VIRal genome assembly tool for third-generation sequencing data.

MOTIVATION: RNA viruses tend to mutate constantly. While many of the variants are neutral, some can lead to higher transmissibility or virulence. Accurate assembly of complete viral genomes enables the identification of underlying variants, which are essential for studying virus evolution and elucidating the relationship between genotypes and virus properties. Recently, third-generation sequencing platforms such as Nanopore sequencers have been used for real-time virus sequencing for Ebola, Zika, coronavirus disease 2019, etc. However, their high per-base error rate prevents the accurate reconstruction of the viral genome. RESULTS: In this work, we introduce a new tool, AccuVIR, for viral genome assembly and polishing using error-prone long reads. It can better distinguish sequencing errors from true variants based on the key observation that sequencing errors can disrupt the gene structures of viruses, which usually have a high density of coding regions. Our experimental results on both simulated and real third-generation sequencing data demonstrated its superior performance on generating more accurate viral genomes than generic assembly or polish tools. AVAILABILITY AND IMPLEMENTATION: The source code and the documentation of AccuVIR are available at https://github.com/rainyrubyzhou/AccuVIR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PredictION: a predictive model to establish the performance of Oxford sequencing reads of SARS-CoV-2.

The optimization of resources for research in developing countries forces us to consider strategies in the wet lab that allow the reuse of molecular biology reagents to reduce costs. In this study, we used linear regression as a method for predictive modeling of coverage depth given the number of MinION reads sequenced to define the optimum number of reads necessary to obtain >200X coverage depth with a good lineage-clade assignment of SARS-CoV-2 genomes. The research aimed to create and implement a model based on machine learning algorithms to predict different variables (e.g., coverage depth) given the number of MinION reads produced by Nanopore sequencing to maximize the yield of high-quality SARS-CoV-2 genomes, determine the best sequencing runtime, and to be able to reuse the flow cell with the remaining nanopores available for sequencing in a new run. The best accuracy was -0.98 according to the R squared performance metric of the models. A demo version is available at https://genomicdashboard.herokuapp.com/.

Screening for differentially expressed microRNAs in BALF and blood samples of infected COVID-19 ARDS patients by small RNA deep sequencing.

BACKGROUND: The pandemic COVID-19 has caused a high mortality rate and poses a significant threat to the population of the entire world. Due to the novelty of this disease, the pathogenic mechanism of the disease and the host cell's response are not yet fully known, so lack of evidence prevents a definitive conclusion about treatment strategies. The current study employed a small RNA deep-sequencing approach for screening differentially expressed microRNA (miRNA) in blood and bronchoalveolar fluid (BALF) samples of acute respiratory distress syndrome (ARDS) patients. METHODS: In this study, BALF and blood samples were taken from patients with ARDS (n = 5). Control samples were those with suspected lung cancer candidates for lung biopsy (n = 3). Illumina high-throughput (HiSeq 2000) sequencing was performed to identify known and novel miRNAs differentially expressed in the blood and BALFs of ARDS patients compared with controls. RESULTS: Results showed 2234 and 8324 miRNAs were differentially expressed in blood and BALF samples, respectively. In BALF samples, miR-282, miR-15-5p, miR-4485-3p, miR-483-3p, miR-6891-5p, miR-200c, miR-4463, miR-483-5p, and miR-98-5p were upregulated and miR-15a-5p, miR-548c-5p, miR-548d-3p, miR-365a-3p, miR-3939, miR-514-b-5p, miR-513a-3p, miR-513a-5p, miR-664a-3p, and miR-766-3p were downregulated. On the contrary, in blood samples miR-15b-5p, miR-18a-3p, miR-486-3p, miR-486-5p, miR-146a-5p, miR-16-2-3p, miR-6501-5p, miR-365-3p, miR-618, and miR-623 were top upregulated miRNAs and miR-21-5p, miR-142a-3p, miR-181-a, miR-31-5p, miR-99-5p, miR-342-5p, miR-183-5p, miR-627-5p, and miR-144-3p were downregulated miRNAs. Network functional analysis for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), in ARDS patients' blood and BALF samples, showed that the target genes were more involved in activating inflammatory and apoptosis process. CONCLUSION: Based on our results, the transcriptome profile of ARDS patients would be a valuable source for understanding molecular mechanisms of host response and developing clinical guidance on anti-inflammatory medication.

Simultaneous SARS-CoV-2 Genome Sequencing of 384 Samples on an Illumina MiSeq Instrument through Protocol Optimization.

In the present study, we propose a high-throughput sequencing protocol using aNextera XT Library DNA kit on an Illumina MiSeq instrument. We made major modifications to this library preparation in order to multiplex 384 samples in a single Illumina flow cell. To validate our protocol, we compared the sequences obtained with the modified Illumina protocol to those obtained with the GridION Nanopore protocol. For the modified Illumina protocol, our results showed that 94.9% (357/376) of the sequences were interpretable, with a viral genome coverage between 50.5% and 99.9% and an average depth of 421×. For the GridION Nanopore protocol, 94.6% (356/376) of the sequences were interpretable, with a viral genome coverage between 7.0% and 98.6% and an average depth of 2123×. The modified Illumina protocol allows for gaining EUR 4744 and returning results of 384 samples in 53.5 h versus four times 55.5 h with the standard Illumina protocol. Our modified MiSeq protocol yields similar genome sequence data as the GridION Nanopore protocol and has the advantage of being able to handle four times more samples simultaneously and hence is much less expensive.

Genomic surveillance of SARS-CoV-2 by sequencing the RBD region using Sanger sequencing from North Kerala.

Next Generation Sequencing (NGS) is the gold standard for the detection of new variants of SARS-CoV-2 including those which have immune escape properties, high infectivity, and variable severity. This test is helpful in genomic surveillance, for planning appropriate and timely public health interventions. But labs with NGS facilities are not available in small or medium research settings due to the high cost of setting up such a facility. Transportation of samples from many places to few centers for NGS testing also produces delays due to transportation and sample overload leading in turn to delays in patient management and community interventions. This becomes more important for patients traveling from hotspot regions or those suspected of harboring a new variant. Another major issue is the high cost of NGS-based tests. Thus, it may not be a good option for an economically viable surveillance program requiring immediate result generation and patient follow-up. The current study used a cost-effective facility which can be set up in a common research lab and which is replicable in similar centers with expertise in Sanger nucleotide sequencing. More samples can be processed at a time and can generate the results in a maximum of 2 days (1 day for a 24 h working lab). We analyzed the nucleotide sequence of the Receptor Binding Domain (RBD) region of SARS-CoV-2 by the Sanger sequencing using in-house developed methods. The SARS-CoV-2 variant surveillance was done during the period of March 2021 to May 2022 in the Northern region of Kerala, a state in India with a population of 36.4 million, for implementing appropriate timely interventions. Our findings broadly agree with those from elsewhere in India and other countries during the period.

Confirming Multiplex RT-qPCR Use in COVID-19 with Next-Generation Sequencing: Strategies for Epidemiological Advantage.

Rapid identification and tracking of emerging SARS-CoV-2 variants are critical for understanding the transmission dynamics and developing strategies for interrupting the transmission chain. Next-Generation Sequencing (NGS) is an exceptional tool for whole-genome analysis and deciphering new mutations. The technique has been instrumental in identifying the variants of concern (VOC) and tracking this pandemic. However, NGS is complex and expensive for large-scale adoption, and epidemiological monitoring with NGS alone could be unattainable in limited-resource settings. In this study, we explored the application of RT-qPCR-based detection of the variant identified by NGS. We analyzed a total of 78 deidentified samples that screened positive for SARS-CoV-2 from two timeframes, August 2020 and July 2021. All 78 samples were classified into WHO lineages by whole-genome sequencing and then compared with two commercially available RT-qPCR assays for spike protein mutation(s). The data showed good concordance between RT-qPCR and NGS analysis for specific SARS-CoV-2 lineages and characteristic mutations. RT-qPCR assays are quick and cost-effective and thus can be implemented in synergy with NGS for screening NGS-identified mutations of SARS-CoV-2 for clinical and epidemiological interest. Strategic use of NGS and RT-qPCR can offer several COVID-19 epidemiological advantages.

Evaluation of EPISEQ SARS-CoV-2 and a Fully Integrated Application to Identify SARS-CoV-2 Variants from Several Next-Generation Sequencing Approaches.

Whole-genome sequencing has become an essential tool for real-time genomic surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide. The handling of raw next-generation sequencing (NGS) data is a major challenge for sequencing laboratories. We developed an easy-to-use web-based application (EPISEQ SARS-CoV-2) to analyse SARS-CoV-2 NGS data generated on common sequencing platforms using a variety of commercially available reagents. This application performs in one click a quality check, a reference-based genome assembly, and the analysis of the generated consensus sequence as to coverage of the reference genome, mutation screening and variant identification according to the up-to-date Nextstrain clade and Pango lineage. In this study, we validated the EPISEQ SARS-CoV-2 pipeline against a reference pipeline and compared the performance of NGS data generated by different sequencing protocols using EPISEQ SARS-CoV-2. We showed a strong agreement in SARS-CoV-2 clade and lineage identification (>99%) and in spike mutation detection (>99%) between EPISEQ SARS-CoV-2 and the reference pipeline. The comparison of several sequencing approaches using EPISEQ SARS-CoV-2 revealed 100% concordance in clade and lineage classification. It also uncovered reagent-related sequencing issues with a potential impact on SARS-CoV-2 mutation reporting. Altogether, EPISEQ SARS-CoV-2 allows an easy, rapid and reliable analysis of raw NGS data to support the sequencing efforts of laboratories with limited bioinformatics capacity and those willing to accelerate genomic surveillance of SARS-CoV-2.

Optimization of peripheral blood volume for in silico reconstitution of the human B-cell receptor repertoire.

B cells recognize antigens via membrane-expressed B-cell receptors (BCR) and antibodies. Similar human BCR sequences are frequently found at a significantly higher frequency than that theoretically calculated. Patients infected with SARS-CoV2 and HIV or with autoimmune diseases share very similar BCRs. Therefore, in silico reconstitution of BCR repertoires and identification of stereotypical BCR sequences related to human pathology have diagnostic potential. Furthermore, monitoring changes of clinically significant BCR sequences and isotype conversion has prognostic potential. For BCR repertoire analysis, peripheral blood (PB) is the most convenient source. However, the optimal human PB volume for in silico reconstitution of the BCR repertoire has not been studied in detail. Here, we sampled 5, 10, and 20 mL PB from the left arm and 40 mL PB from the right arm of two volunteers, reconstituted in silico PB BCR repertoires, and compared their composition. In both volunteers, PB sampling over 20 mL resulted in slight increases in functional unique sequences (FUSs) or almost no increase in repertoire diversity. All FUSs with a frequency above 0.08% or 0.03% in the 40 mL PB BCR repertoire were detected even in the 5 mL PB BCR repertoire from each volunteer. FUSs with a higher frequency were more likely to be found in BCR repertoires from reduced PB volume, and those coexisting in two repertoires showed a statistically significant correlation in frequency irrespective of sampled anatomical site. The correlation was more significant in higher-frequency FUSs. These observations support the potential of BCR repertoire analysis for diagnosis.

A Comparison of Bioinformatics Pipelines for Enrichment Illumina Next Generation Sequencing Systems in Detecting SARS-CoV-2 Virus Strains.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a newly emerging virus well known as the major cause of the worldwide pandemic due to Coronavirus Disease 2019 (COVID-19). Major breakthroughs in the Next Generation Sequencing (NGS) field were elucidated following the first release of a full-length SARS-CoV-2 genome on the 10 January 2020, with the hope of turning the table against the worsening pandemic situation. Previous studies in respiratory virus characterization require mapping of raw sequences to the human genome in the downstream bioinformatics pipeline as part of metagenomic principles. Illumina, as the major player in the NGS arena, took action by releasing guidelines for improved enrichment kits called the Respiratory Virus Oligo Panel (RVOP) based on a hybridization capture method capable of capturing targeted respiratory viruses, including SARS-CoV-2; therefore, allowing a direct map of raw sequences data to SARS-CoV-2 genome in downstream bioinformatics pipeline. Consequently, two bioinformatics pipelines emerged with no previous studies benchmarking the pipelines. This study focuses on gaining insight and understanding of target enrichment workflow by Illumina through the utilization of different bioinformatics pipelines named as 'Fast Pipeline' and 'Normal Pipeline' to SARS-CoV-2 strains isolated from Yogyakarta and Central Java, Indonesia. Overall, both pipelines work well in the characterization of SARS-CoV-2 samples, including in the identification of major studied nucleotide substitutions and amino acid mutations. A higher number of reads mapped to the SARS-CoV-2 genome in Fast Pipeline and merely were discovered as a contributing factor in a higher number of coverage depth and identified variations (SNPs, insertion, and deletion). Fast Pipeline ultimately works well in a situation where time is a critical factor. On the other hand, Normal Pipeline would require a longer time as it mapped reads to the human genome. Certain limitations were identified in terms of pipeline algorithm, whereas it is highly recommended in future studies to design a pipeline in an integrated framework, for instance, by using NextFlow, a workflow framework to combine all scripts into one fully integrated pipeline.