A Novel Strategy for the Detection of SARS-CoV-2 Variants Based on Multiplex PCR-Mass Spectrometry Minisequencing Technology

The emergence of SARS-CoV-2 variants is the key factor in the second wave of the COVID-19 pandemic. An all-in-one SARS-CoV-2 variant identification method based on a multiplex PCR-mass spectrometry minisequencing system was developed in this study.

Identification of pathogenic Leptospira species and serovars in New Zealand using metabarcoding

Leptospirosis is a zoonotic disease of global importance. The breadth of Leptospira diversity associated with both human and animal disease poses major logistical challenges to the use of classical diagnostic techniques, and increasingly molecular diagnostic tools are used for their detection. In New Zealand, this has resulted in an increase in positive cases reported nationally that have not been attributed to the infecting serovar or genomospecies. In this study, we used data from all pathogenic Leptospira genomes to identify a partial region of the glmU gene as a suitable locus for the discrimination of the infecting species and serovars of New Zealand-endemic Leptospira. This method can be used in culture and culture-independent scenarios making it flexible for diagnostics in humans, animals, and environmental samples. We explored the use of this locus as a molecular barcoding tool via the Oxford Nanopore Technology (ONT) sequencing platform MinION. Sequences obtained by this method allowed specific identification of Leptospira species in mixed and enriched environmental cultures, however read error inherent in the MinION sequencing system reduced the accuracy of strain/variant identification. Using this approach to characterise Leptospira in enriched environmental cultures, we detected the likely presence of Leptospira genomospecies that have not been reported in New Zealand to date. This included a strain of L. borgpetersenii that has recently been identified in dairy cattle and sequences similar to those of L. mayottensis. L. tipperaryensis, L. dzianensis and L. alstonii.

Multiple Variant Calling Pipelines in Wheat Whole Exome Sequencing

The highly challenging hexaploid wheat (Triticum aestivum) genome is becoming ever more accessible due to the continued development of multiple reference genomes, a factor which aids in the plight to better understand variation in important traits. Although the process of variant calling is relatively straightforward, selection of the best combination of the computational tools for read alignment and variant calling stages of the analysis and efficient filtering of the false variant calls are not always easy tasks. Previous studies have analyzed the impact of methods on the quality metrics in diploid organisms. Given that variant identification in wheat largely relies on accurate mining of exome data, there is a critical need to better understand how different methods affect the analysis of whole exome sequencing (WES) data in polyploid species. This study aims to address this by performing whole exome sequencing of 48 wheat cultivars and assessing the performance of various variant calling pipelines at their suggested settings. The results show that all the pipelines require filtering to eliminate false-positive calls. The high consensus among the reference SNPs called by the best-performing pipelines suggests that filtering provides accurate and reproducible results. This study also provides detailed comparisons for high sensitivity and precision at individual and population levels for the raw and filtered SNP calls.

A Simple and Fast Method to Sequence the Full-Length Spike Gene for SARS-CoV-2 Variant Identification from Patient Samples

Since the beginning of the pandemic, a race has been underway to detect SARS-CoV-2 virus infection (PCR screening, serological diagnostic kits), treat patients (drug repurposing, standard care) and develop a vaccine. After almost a year of active circulation worldwide, SARS-CoV-2 variants have appeared in different countries. Those variants include mutations in multiple regions of the genome, particularly in the spike gene. Because this surface protein is a key player in both the spread of the virus and the efficacy of vaccine strategies, the challenge is to efficiently monitor the appearance of spike mutations in the population. The present work describes a procedure based on the widely available Sanger technology to produce a full-length sequence of the spike gene from patient-derived samples.

Exome sequencing identifies novel and known mutations in families with intellectual disability

Background Intellectual disability (ID) is a phenotypically and genetically heterogeneous disorder. Methods In this study, genome wide SNP microarray and whole exome sequencing are used for the variant identification in eight Pakistani families with ID. Beside ID, most of the affected individuals had speech delay, facial dysmorphism and impaired cognitive abilities. Repetitive behavior was observed in MRID143, while seizures were reported in affected individuals belonging to MRID137 and MRID175. Results In two families (MRID137b and MRID175), we identified variants in the genes CCS and ELFN1, which have not previously been reported to cause ID. In four families, variants were identified in ARX, C5orf42, GNE and METTL4. A copy number variation (CNV) was identified in IL1RAPL1 gene in MRID165. Conclusion These findings expand the existing knowledge of variants and genes implicated in autosomal recessive and X linked ID.

Implementation of Multigene Germline and Parallel Somatic Genetic Testing in Epithelial Ovarian Cancer: SIGNPOST Study

We present findings of a cancer multidisciplinary-team (MDT) coordinated mainstreaming pathway of unselected 5-panel germline BRCA1/BRCA2/RAD51C/RAD51D/BRIP1 and parallel somatic BRCA1/BRCA2 testing in all women with epithelial-OC and highlight the discordance between germline and somatic testing strategies across two cancer centres. Patients were counselled and consented by a cancer MDT member. The uptake of parallel multi-gene germline and somatic testing was 97.7%. Counselling by clinical-nurse-specialist more frequently needed >1 consultation (53.6% (30/56)) compared to a medical (15.0% (21/137)) or surgical oncologist (15.3% (17/110)) (p < 0.001). The median age was 54 (IQR = 51–62) years in germline pathogenic-variant (PV) versus 61 (IQR = 51–71) in BRCA wild-type (p = 0.001). There was no significant difference in distribution of PVs by ethnicity, stage, surgery timing or resection status. A total of 15.5% germline and 7.8% somatic BRCA1/BRCA2 PVs were identified. A total of 2.3% patients had RAD51C/RAD51D/BRIP1 PVs. A total of 11% germline PVs were large-genomic-rearrangements and missed by somatic testing. A total of 20% germline PVs are missed by somatic first BRCA-testing approach and 55.6% germline PVs missed by family history ascertainment. The somatic testing failure rate is higher (23%) for patients undergoing diagnostic biopsies. Our findings favour a prospective parallel somatic and germline panel testing approach as a clinically efficient strategy to maximise variant identification. UK Genomics test-directory criteria should be expanded to include a panel of OC genes.

SARS-CoV-2 variants of concern, Gamma (P.1) and Delta (B.1.617), sensitive detection and quantification in wastewater employing direct RT-qPCR

SARS-CoV-2 variants of concern present a worldwide threat. Demonstrating higher infection rate and durability to antibodies when compared to the original SARS-CoV-2 virus, the variants of concern are responsible for continuing global outbreaks. Prompt identification of the infecting SARS-CoV-2 variant is essential for pandemic assessment and containment. However, variant identification is mainly being performed using expensive, time-consuming next generation sequencing. Rapid identification methodology for variants of concern is of great need and various variant-specific assays are being developed. Amongst the variants of concern that have recently appeared, the Gamma variant (P.1, Brazilian) and Delta variant (B.1.617, Indian) are the most prominent. Here we describe the development of a sensitive RT-qPCR assay for the quick direct detection of the Gamma and Delta variants as part of a methodical characterization and detection in municipal wastewater.

Malware Variant Identification Using Incremental Clustering

Dynamic analysis and pattern matching techniques are widely used in industry, and they provide a straightforward method for the identification of malware samples. Yara is a pattern matching technique that can use sandbox memory dumps for the identification of malware families. However, pattern matching techniques fail silently due to minor code variations, leading to unidentified malware samples. This paper presents a two-layered Malware Variant Identification using Incremental Clustering (MVIIC) process and proposes clustering of unidentified malware samples to enable the identification of malware variants and new malware families. The novel incremental clustering algorithm is used in the identification of new malware variants from the unidentified malware samples. This research shows that clustering can provide a higher level of performance than Yara rules, and that clustering is resistant to small changes introduced by malware variants. This paper proposes a hybrid approach, using Yara scanning to eliminate known malware, followed by clustering, acting in concert, to allow the identification of new malware variants. F1 score and V-Measure clustering metrics are used to evaluate our results.