KnockoffTrio: A knockoff framework for the identification of putative causal variants in genome-wide association studies with trio design.

Family-based designs can eliminate confounding due to population substructure and can distinguish direct from indirect genetic effects, but these designs are underpowered due to limited sample sizes. Here, we propose KnockoffTrio, a statistical method to identify putative causal genetic variants for father-mother-child trio design built upon a recently developed knockoff framework in statistics. KnockoffTrio controls the false discovery rate (FDR) in the presence of arbitrary correlations among tests and is less conservative and thus more powerful than the conventional methods that control the family-wise error rate via Bonferroni correction. Furthermore, KnockoffTrio is not restricted to family-based association tests and can be used in conjunction with more powerful, potentially nonlinear models to improve the power of standard family-based tests. We show, using empirical simulations, that KnockoffTrio can prioritize causal variants over associations due to linkage disequilibrium and can provide protection against confounding due to population stratification. In applications to 14,200 trios from three study cohorts for autism spectrum disorders (ASDs), including AGP, SPARK, and SSC, we show that KnockoffTrio can identify multiple significant associations that are missed by conventional tests applied to the same data. In particular, we replicate known ASD association signals with variants in several genes such as MACROD2, NRXN1, PRKAR1B, CADM2, PCDH9, and DOCK4 and identify additional associations with variants in other genes including ARHGEF10, SLC28A1, ZNF589, and HINT1 at FDR 10%.

Fast and accurate variant identification tool for sequencing-based studies.

BACKGROUND: Accurate identification of genetic variants, such as point mutations and insertions/deletions (indels), is crucial for various genetic studies into epidemic tracking, population genetics, and disease diagnosis. Genetic studies into microbiomes often require processing numerous sequencing datasets, necessitating variant identifiers with high speed, accuracy, and robustness. RESULTS: We present QuickVariants, a bioinformatics tool that effectively summarizes variant information from read alignments and identifies variants. When tested on diverse bacterial sequencing data, QuickVariants demonstrates a ninefold higher median speed than bcftools, a widely used variant identifier, with higher accuracy in identifying both point mutations and indels. This accuracy extends to variant identification in virus samples, including SARS-CoV-2, particularly with significantly fewer false negative indels than bcftools. The high accuracy of QuickVariants is further demonstrated by its detection of a greater number of Omicron-specific indels (5 versus 0) and point mutations (61 versus 48-54) than bcftools in sewage metagenomes predominated by Omicron variants. Much of the reduced accuracy of bcftools was attributable to its misinterpretation of indels, often producing false negative indels and false positive point mutations at the same locations. CONCLUSIONS: We introduce QuickVariants, a fast, accurate, and robust bioinformatics tool designed for identifying genetic variants for microbial studies. QuickVariants is available at https://github.com/caozhichongchong/QuickVariants .

Reinvestigation of unidentified causative variants in FXI-deficient patients: Focus on gene segment deletions.

INTRODUCTION: Data on failure to identify the molecular mechanism underlying FXI deficiency by Sanger analysis and the contribution of gene segment deletions are almost inexistent. AIMS AND METHODS: Prospective and retrospective analysis was conducted on FXI-deficient patients' DNA via Next Generation Sequencing (NGS), or Sanger sequencing and Multiplex Probe Ligation-dependent Assay (MLPA) to detect cryptic causative gene variants or gene segment deletions. RESULTS: Sanger analysis or NGS enabled us to identify six severe and one partial (median activity 41 IU/dl) FXI deficient index cases with deletions encompassing exons 11-15, the whole gene, or both. After Sanger sequencing, retrospective evaluation using MLPA detected seven additional deletion cases in apparently homozygous cases in non-consanguineous families, or in previously unsolved FXI-deficiency cases. Among the 504 index cases with a complete genetic investigation (Sanger/MLPA, or NGS), 23 remained unsolved (no abnormality found [n = 14] or rare intronic variants currently under investigation, [n = 9]). In the 481 solved cases (95% efficiency), we identified F11 gene-deleted patients (14 cases; 2.9%). Among these, whole gene deletion accounted for four heterozygous cases, exons 11-15 deletion for five heterozygous and three homozygous ones, while compound heterozygous deletion and isolated exon 12 deletion accounted for one case each. CONCLUSION: Given the high incidence of deletions in our population (2.9%), MLPA (or NGS with a reliable bioinformatic pipeline) should be systematically performed for unsolved FXI deficiencies or apparently homozygous cases in non-consanguineous families.

Fruit transcriptional profiling of the contrasting genotypes for shelf life reveals the key candidate genes and molecular pathways regulating post-harvest biology in cucumber.

Cucumber fruits are perishable in nature and become unfit for market within 2-3 days of harvesting. A natural variant, DC-48 with exceptionally high shelf life was developed and used to dissect the genetic architecture and molecular mechanism for extended shelf life through RNA-seq for first time. A total of 1364 DEGs were identified and cell wall degradation, chlorophyll and ethylene metabolism related genes played key role. Polygalacturunase (PG), Expansin (EXP) and xyloglucan were down regulated determining fruit firmness and retention of fresh green colour was mainly attributed to the low expression level of the chlorophyll catalytic enzymes (CCEs). Gene regulatory networks revealed the hub genes and cross-talk associated with wide variety of the biological processes. Large number of SSRs (21524), SNPs (545173) and InDels (126252) identified will be instrumental in cucumber improvement. A web genomic resource, CsExSLDb developed will provide a platform for future investigation on cucumber post-harvest biology.

Defining the mutation sites in chickpea nodulation mutants PM233 and PM405.

BACKGROUND: Like most legumes, chickpeas form specialized organs called root nodules. These nodules allow for a symbiotic relationship with rhizobium bacteria. The rhizobia provide fixed atmospheric nitrogen to the plant in a usable form. It is of both basic and practical interest to understand the host plant genetics of legume root nodulation. Chickpea lines PM233 and PM405, which harbor the mutationally identified nodulation genes rn1 and rn4, respectively, both display nodulation-deficient phenotypes. Previous investigators identified the rn1 mutation with the chickpea homolog of Medicago truncatula nodulation gene NSP2, but were unable to define the mutant rn1 allele. We used Illumina and Nanopore sequencing reads to attempt to identify and characterize candidate mutation sites responsible for the PM233 and PM405 phenotypes. RESULTS: We aligned Illumina reads to the available desi chickpea reference genome, and did a de novo contig assembly of Nanopore reads. In mutant PM233, the Nanopore contigs allowed us to identify the breakpoints of a ~ 35 kb deleted region containing the CaNSP2 gene, the Medicago truncatula homolog of which is involved in nodulation. In mutant PM405, we performed variant calling in read alignments and identified 10 candidate mutations. Genotyping of a segregating progeny population narrowed that pool down to a single candidate gene which displayed homology to M. truncatula nodulation gene NIN. CONCLUSIONS: We have characterized the nodulation mutation sites in chickpea mutants PM233 and PM405. In mutant PM233, the rn1 mutation was shown to be due to deletion of the entire CaNSP2 nodulation gene, while in mutant PM405 the rn4 mutation was due to a single base deletion resulting in a frameshift mutation between the predicted RWP-RK and PB1 domains of the NIN nodulation gene. Critical to characterization of the rn1 allele was the generation of Nanopore contigs for mutant PM233 and its wild type parent ICC 640, without which the deletional boundaries could not be defined. Our results suggest that efforts of prior investigators were hampered by genomic misassemblies in the CaNSP2 region of both the desi and kabuli reference genomes.

Highly Sensitive Lineage Discrimination of SARS-CoV-2 Variants through Allele-Specific Probe PCR.

Tools to detect SARS-CoV-2 variants of concern and track the ongoing evolution of the virus are necessary to support public health efforts and the design and evaluation of novel COVID-19 therapeutics and vaccines. Although next-generation sequencing (NGS) has been adopted as the gold standard method for discriminating SARS-CoV-2 lineages, alternative methods may be required when processing samples with low viral loads or low RNA quality. To this aim, an allele-specific probe PCR (ASP-PCR) targeting lineage-specific single nucleotide polymorphisms (SNPs) was developed and used to screen 1,082 samples from two clinical trials in the United Kingdom and Brazil. Probit regression models were developed to compare ASP-PCR performance against 1,771 NGS results for the same cohorts. Individual SNPs were shown to readily identify specific variants of concern. ASP-PCR was shown to discriminate SARS-CoV-2 lineages with a higher likelihood than NGS over a wide range of viral loads. The comparative advantage for ASP-PCR over NGS was most pronounced in samples with cycle threshold (CT) values between 26 and 30 and in samples that showed evidence of degradation. Results for samples screened by ASP-PCR and NGS showed 99% concordant results. ASP-PCR is well suited to augment but not replace NGS. The method can differentiate SARS-CoV-2 lineages with high accuracy and would be best deployed to screen samples with lower viral loads or that may suffer from degradation. Future work should investigate further destabilization from primer-target base mismatch through altered oligonucleotide chemistry or chemical additives.

An Upgrade on the Surveillance System of SARS-CoV-2: Deployment of New Methods for Genetic Inspection.

SARS-CoV-2 variants surveillance is a worldwide task that has been approached with techniques such as Next Generation Sequencing (NGS); however, this technology is not widely available in developing countries because of the lack of equipment and limited funding in science. An option is to deploy a RT-qPCR screening test which aids in the analysis of a higher number of samples, in a shorter time and at a lower cost. In this study, variants present in samples positive for SARS-CoV-2 were identified with a RT-qPCR mutation screening kit and were later confirmed by NGS. A sample with an abnormal result was found with the screening test, suggesting the simultaneous presence of two viral populations with different mutations. The DRAGEN Lineage analysis identified the Delta variant, but there was no information about the other three mutations previously detected. When the sequenced data was deeply analyzed, there were reads with differential mutation patterns, that could be identified and classified in terms of relative abundance, whereas only the dominant population was reported by DRAGEN software. Since most of the software developed to analyze SARS-CoV-2 sequences was aimed at obtaining the consensus sequence quickly, the information about viral populations within a sample is scarce. Here, we present a faster and deeper SARS-CoV-2 surveillance method, from RT-qPCR screening to NGS analysis.

Optimization and Identification of Single Mutation in Hemoglobin Variants with 2,2,2 Trifluoroethanol Modified Digestion Method and Nano-LC Coupled MALDI MS/MS.

Background: Hemoglobin (Hb) variants arise due to point mutations in globin chains and their pathological treatments rely heavily on the identification of the nature and location of the mutation in the globin chains. Traditional methods for diagnosis such as HPLC and electrophoresis have their own limitations. Therefore, the present study aims to develop and optimize a specific method of sample processing that could lead to improved sequence coverage and analysis of Hb variants by nano LC-MALDI MS/MS. Methods: In our study, we primarily standardized various sample processing methods such as conventional digestion with trypsin followed by 10% acetonitrile treatment, digestion with multiple proteases like trypsin, Glu-C, Lys-C, and trypsin digestion subsequent to 2,2,2 trifluoroethanol (TFE) treatment. Finally, the peptides were identified by LC-MALDI MS/MS. All of these sample processing steps were primarily tested with recombinant Hb samples. After initial optimization, we found that the TFE method was the most suitable one and the efficiency of this method was applied in Hb variant identification based on high sequence coverage. Results: We developed and optimized a method using an organic solvent TFE and heat denaturation prior to digestion, resulting in 100% sequence coverage in the ß-chains and 95% sequence coverage in the α-chains, which further helped in the identification of Hb mutations. A Hb variant protein sequence database was created to specify the search and reduce the search time. Conclusion: All of the mutations were identified using a bottom-up non-target approach. Therefore, a sensitive, robust and reproducible method was developed to identify single substitution mutations in the Hb variants from the sequence of the entire globin chains. Biological Significance: Over 330,000 infants are born annually with hemoglobinopathies and it is the major cause of morbidity and mortality in early childhood. Hb variants generally arise due to point mutation in the globin chains. There is high sequence homology between normal Hb and Hb variant chains. Due to this high homology between the two forms, identification of variants by mass spectrometry is very difficult and requires the full sequence coverage of α- and ß-chains. As such, there is a need for a suitable method that provides 100% sequence coverage of globin chains for variant analysis by mass spectrometry. Our study provides a simple, robust, and reproducible method that is suitable for LC-MALDI and provides nearly complete sequence coverage in the globin chains. This method may be used in the near future in routine diagnosis for Hb variant analysis.

[Exome diagnostics in neurology]. / Exomdiagnostik in der Neurologie.

After an impressively successful application as a research instrument, whole-exome sequencing (WES) now enters the clinical practice due to its high diagnostic, time, and economic efficiency. WES is the diagnostic method of choice for symptoms that may be due to many different monogenic causes. Neurological indications include movement disorders, especially in cases of early symptom onset, familial clustering and complex manifestation. Starting from a blood sample, enrichment and sequencing of the exome enable the examination of all coding DNA regions for point mutations and small insertions/deletions. The identification of variants as the cause of a disease requires a professional evaluation pipeline, variant prioritization schemes and variant classification databases. Whereas many variants can be reliably classified as pathogenic or benign, variants of unclear significance (VUS) remain a challenge for the clinical evaluation and necessitate a periodic reanalysis of WES data. As a genetic examination WES requires adequate patient informed consent which in particular should address possible secondary findings as well as data security. A positive molecular result ends diagnostic odysseys, enables accurate genetic counseling and can point to targeted preventive measures and treatment. A WES significantly contributes to the understanding of the genetic architecture and pathophysiology of neurological diseases, enriching and enabling precision medicine.

Robust identification of deletions in exome and genome sequence data based on clustering of Mendelian errors.

Multiple tools have been developed to identify copy number variants (CNVs) from whole exome (WES) and whole genome sequencing (WGS) data. Current tools such as XHMM for WES and CNVnator for WGS identify CNVs based on changes in read depth. For WGS, other methods to identify CNVs include utilizing discordant read pairs and split reads and genome-wide local assembly with tools such as Lumpy and SvABA, respectively. Here, we introduce a new method to identify deletion CNVs from WES and WGS trio data based on the clustering of Mendelian errors (MEs). Using our Mendelian Error Method (MEM), we identified 127 deletions (inherited and de novo) in 2,601 WES trios from the Pediatric Cardiac Genomics Consortium, with a validation rate of 88% by digital droplet PCR. MEM identified additional de novo deletions compared with XHMM, and a significant enrichment of 15q11.2 deletions compared with controls. In addition, MEM identified eight cases of uniparental disomy, sample switches, and DNA contamination. We applied MEM to WGS data from the Genome In A Bottle Ashkenazi trio and identified deletions with 97% specificity. MEM provides a robust, computationally inexpensive method for identifying deletions, and an orthogonal approach for verifying deletions called by other tools.

Autosomal-dominant biventricular arrhythmogenic cardiomyopathy in a large family with a novel in-frame DSP nonsense mutation.

A novel autosomal-dominant in-frame deletion resulting in a nonsense mutation in the desmoplakin (DSP) gene was identified in association with biventricular arrhythmogenic cardiomyopathy across three generations of a large Caucasian family. Mutations that disrupt the function and structure of desmosomal proteins, including desmoplakin, have been extensively linked to familial arrhythmogenic right ventricular cardiomyopathy (ARVC). Analysis of data from 51 individuals demonstrated the previously undescribed variant p.Cys81Stop (c.243_251delCTTGATGCG) in DSP segregates with a pathogenic phenotype exhibiting variable penetrance and expressivity. The mutation's pathogenicity was first established due to two sudden cardiac deaths (SCDs), each with a biventricular cardiomyopathy identified on autopsy. Of the individuals who underwent genetic screening, 27 of 51 were heterozygous for the DSP mutation (29 total with two obligate carriers). Six of these were subsequently diagnosed with arrhythmogenic cardiomyopathy. An additional nine family members have a conduction disorder and/or myocardial structural changes characteristic of an evolving condition. Previous reports from both human patients and mouse studies proposed DSP mutations with a premature stop codon impart mild to no clinical symptoms. Loss of expression from the abnormal allele via the nonsense-mediated mRNA decay pathway has been implicated to explain these findings. We identified an autosomal-dominant DSP nonsense mutation in a large family that led to SCD and phenotypic expression of arrhythmogenic cardiomyopathy involving both ventricles. This evidence demonstrates the pathogenic significance of this type of desmosomal mutation and provides insight into potential clinical manifestations.

Wastewater surveillance of severe acute respiratory syndrome coronavirus-2 in open drains of two Indian megacities captures evolutionary lineage transitions: a zonation approach.

Wastewater-based environmental surveillance (WBES) has been proven as proxy tool for monitoring nucleic acids of pathogens shed by infected population before clinical outcomes. The poor sewershed network of low to middle-income countries (LMICs) leads to most of the wastewater flow through open drains. We studied the effectiveness of WBES using open drain samples to monitor the emergence of the SARS-CoV-2 variants in 2 megacities of India having dense population through zonation approach. Samples from 28 locations spanned into 5 zones of Pune region, Maharashtra, India, were collected on a weekly basis during October 2021 to July 2022. Out of 1115 total processed samples, 303 (~ 27%) tested positive for SARS-CoV-2. The periodical rise and fall in the percentage positivity of the samples was found to be in sync with the abundance of SARS-CoV-2 RNA and the reported COVID-19 active cases for Pune city. Sequencing of the RNA obtained from wastewater samples confirmed the presence of SARS-CoV-2. Of 337 sequences, lineage identification for 242 samples revealed 265 distinct SARS-CoV-2 variants including 10 highly transmissible ones. Importantly, transition from Delta to Omicron variant could be detected in wastewater samples 2 weeks prior to any clinically reported Omicron cases in India. Thus, this study demonstrates the usefulness of open drain samples for real-time monitoring of a viral pathogen's evolutionary dynamics and could be implemented in LMICs.

Evaluation of an identification method for the SARS-CoV-2 Delta variant based on the amplification-refractory mutation system.

The Delta variant of SARS-CoV-2 dominated the COVID-19 pandemic due to its high viral replication capacity and immune evasion, causing massive outbreaks of cases, hospitalizations, and deaths. Currently, variant identification is performed mainly by sequencing. However, the high requirements for equipment and operators as well as its high cost have limited its application in underdeveloped regions. To achieve an economical and rapid method of variant identification suitable for undeveloped areas, we applied an amplification-refractory mutation system (ARMS) based on PCR for the detection of novel coronavirus variants. The results showed that this method could be finished in 90 min and detect as few as 500 copies/mL and not react with SARS-Coronavirus, influenza A H1N1(2009), and other cross-pathogens or be influenced by fresh human blood, α- interferon, and other interfering substances. In a set of double-blind trials, tests of 262 samples obtained from patients confirmed with Delta variant infection revealed that our method was able to accurately identify the Delta variant with high sensitivity and specificity. In conclusion, the ARMS-PCR method applied in Delta variant identification is rapid, sensitive, specific, economical, and suitable for undeveloped areas. In our future study, ARMS-PCR will be further applied in the identification of other variants, such as Omicron.

Drug Target Elucidation Through Isolation and Analysis of Drug-Resistant Mutants in Cryptococcus neoformans.

Drug target identification is an essential component to antifungal drug development. Many methods, including large chemical library screening, natural product screening, and drug repurposing efforts, can identify compounds with favorable in vitro antifungal activity. However, these approaches will often identify compounds with no known mechanism of action. Herein, we describe a method utilizing the human fungal pathogen Cryptococcus neoformans to identify antifungal drug targets through the isolation of spontaneous resistant mutants, antifungal testing, whole-genome sequencing, and variant analysis.

Rapid identification of SARS-CoV-2 variants: Validation of the simplexa SARS-CoV-2 variant direct assay.

The circulation of certain SARS-CoV-2 variants may have a great impact on the epidemiological status of a geographical area; therefore, it is important that their presence is monitored. Currently, the gold standard method used to identify newly emerged variants is sequencing of either genes or whole genomes. However, since this method is relatively expensive and has a long turnaround time, other rapid strategies should also be employed. The current study aimed to evaluate the performance of the Simplexa® SARS-CoV-2 Variants Direct assay, which is a RT-PCR that determines the variant present in a nasopharyngeal swab sample in approximately two hours. Totally, 527 positive samples for SARS-CoV-2 were analyzed from January until December 2022 and next-generation sequencing (NGS) was used as the reference method. The assay showed high sensitivity, ranging from 94.12 % to 100 %, depending on the variant. The assay also showed high specificity, reaching 100 % for Delta and BA.1 variants, and 99.74 % and 98.67 % for BA.2 and BA.4/BA.5 variants, respectively. Moreover, the assay was able to identify the correct variant category in the presence of any subvariant in the sample. We conclude that the assay can be used to facilitate faster monitoring of circulating SARS-CoV-2 variants, however sequencing cannot be completely replaced, since new variants always emerge, and constant updates are needed, so that the user is able to interpret the melting curve patterns.

PipeCoV: a pipeline for SARS-CoV-2 genome assembly, annotation and variant identification.

Motivation: Since the identification of the novel coronavirus (SARS-CoV-2), the scientific community has made a huge effort to understand the virus biology and to develop vaccines. Next-generation sequencing strategies have been successful in understanding the evolution of infectious diseases as well as facilitating the development of molecular diagnostics and treatments. Thousands of genomes are being generated weekly to understand the genetic characteristics of this virus. Efficient pipelines are needed to analyze the vast amount of data generated. Here we present a new pipeline designed for genomic analysis and variant identification of the SARS-CoV-2 virus. Results: PipeCoV shows better performance when compared to well-established SARS-CoV-2 pipelines, with a lower content of Ns and higher genome coverage when compared to the Wuhan reference. It also provides a variant report not offered by other tested pipelines. Availability: https://github.com/alvesrco/pipecov.

Complete CFTR gene sequencing in 5,058 individuals with cystic fibrosis informs variant-specific treatment.

BACKGROUND: Cystic fibrosis (CF) is a recessive condition caused by variants in each CF transmembrane conductance regulator (CFTR) allele. Clinically affected individuals without two identified causal variants typically have no further interrogation of CFTR beyond examination of coding regions, but the development of variant-specific CFTR-targeted treatments necessitates complete understanding of CFTR genotype. METHODS: Whole genome sequences were analyzed on 5,058 individuals with CF. We focused on the full CFTR gene sequence and identified disease-causing variants in three phases: screening for known and structural variants; discovery of novel loss-of-function variants; and investigation of remaining variants. RESULTS: All variants identified in the first two phases and coding region variants found in the third phase were interpreted according to CFTR2 or ACMG criteria (n = 371; 16 [4.3%] previously unreported). Full gene sequencing enabled delineation of 18 structural variants (large insertions or deletions), of which two were novel. Additional CFTR variants of uncertain effect were found in 76 F508del homozygotes and in 21 individuals with other combinations of CF-causing variants. Both causative variants were identified in 98.1% (n = 4,960) of subjects, an increase of 2.3 percentage points from the 95.8% (n = 4,847) who had a registry- or chart-reported disease-causing CFTR genotype. Of the remaining 98 individuals, 78 carried one variant that has been associated with CF (CF-causing [n = 70] or resulting in varying clinical consequences n = 8]). CONCLUSIONS: Complete CFTR gene sequencing in 5,058 individuals with CF identified at least one DNA variant in 99.6% of the cohort that is targetable by current molecular or emerging gene-based therapeutic technologies.

Efficient multiplexing and variant discrimination in reverse-transcription loop-mediated isothermal amplification with sequence-specific hybridization probes.

Loop-mediated isothermal amplification (LAMP) has proven a robust and reliable nucleic acid amplification method that is well suited for simplified and rapid molecular diagnostics. Various approaches have emerged for sequence-specific detection of LAMP products, but with limitations to their widespread utility or applicability for single-nucleotide polymorphism detection and multiplexing. Here we demonstrate the use of simple hybridization probes (as used for qPCR) that enable simple multiplexing and SARS-CoV-2 variant typing in reverse-transcription LAMP. This approach requires no modification to the LAMP primers and is amenable to the detection of single-nucleotide polymorphisms and small sequence changes, which is usually difficult in LAMP. By extending LAMP's ability to be utilized for multitarget and single-base change detection, we hope to increase its potential to enable more and better molecular diagnostic testing.

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.

High-Throughput Adaptable SARS-CoV-2 Screening for Rapid Identification of Dominant and Emerging Regional Variants.

OBJECTIVES: Emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant strains can be associated with increased transmissibility, more severe disease, and reduced effectiveness of treatments. To improve the availability of regional variant surveillance, we describe a variant genotyping system that is rapid, accurate, adaptable, and able to detect new low-level variants built with existing hospital infrastructure. METHODS: We used a tiered high-throughput SARS-CoV-2 screening program to characterize variants in a supraregional health system over 76 days. Combining targeted reverse transcription-polymerase chain reaction (RT-PCR) and selective sequencing, we screened SARS-CoV-2 reactive samples from all hospitals within our health care system for genotyping dominant and emerging variants. RESULTS: The median turnaround for genotyping was 2 days using the high-throughput RT-PCR-based screen, allowing us to rapidly characterize the emerging Delta variant. In our population, the Delta variant is associated with a lower cycle threshold value, lower age at infection, and increased vaccine-breakthrough cases. Detection of low-level and potentially emerging variants highlights the utility of a tiered approach. CONCLUSIONS: These findings underscore the need for fast, low-cost, high-throughput monitoring of regional viral sequences as the pandemic unfolds and the emergence of SARS-CoV-2 variants increases. Combining RT-PCR-based screening with selective sequencing allows for rapid genotyping of variants and dynamic system improvement.