Next-generation Sequencing For Identification Research Articles

Combined Use of RT-qPCR and NGS for Identification and Surveillance of SARS-CoV-2 Variants of Concern in Residual Clinical Laboratory Samples in Miami-Dade County, Florida

Over the course of the COVID-19 pandemic, SARS-CoV-2 variants of concern (VOCs) with increased transmissibility and immune escape capabilities, such as Delta and Omicron, have triggered waves of new COVID-19 infections worldwide, and Omicron subvariants continue to represent a global health concern. Tracking the prevalence and dynamics of VOCs has clinical and epidemiological significance and is essential for modeling the progression and evolution of the COVID-19 pandemic. Next generation sequencing (NGS) is recognized as the gold standard for genomic characterization of SARS-CoV-2 variants, but it is labor and cost intensive and not amenable to rapid lineage identification. Here we describe a two-pronged approach for rapid, cost-effective surveillance of SARS-CoV-2 VOCs by combining reverse-transcriptase quantitative polymerase chain reaction (RT-qPCR) and periodic NGS with the ARTIC sequencing method. Variant surveillance by RT-qPCR included the commercially available TaqPath COVID-19 Combo Kit to track S-gene target failure (SGTF) associated with the spike protein deletion H69-V70, as well as two internally designed and validated RT-qPCR assays targeting two N-terminal-domain (NTD) spike gene deletions, NTD156-7 and NTD25-7. The NTD156-7 RT-qPCR assay facilitated tracking of the Delta variant, while the NTD25-7 RT-qPCR assay was used for tracking Omicron variants, including the BA.2, BA.4, and BA.5 lineages. In silico validation of the NTD156-7 and NTD25-7 primers and probes compared with publicly available SARS-CoV-2 genome databases showed low variability in regions corresponding to oligonucleotide binding sites. Similarly, in vitro validation with NGS-confirmed samples showed excellent correlation. RT-qPCR assays allow for near-real-time monitoring of circulating and emerging variants allowing for ongoing surveillance of variant dynamics in a local population. By performing periodic sequencing of variant surveillance by RT-qPCR methods, we were able to provide ongoing validation of the results obtained by RT-qPCR screening. Rapid SARS-CoV-2 variant identification and surveillance by this combined approach served to inform clinical decisions in a timely manner and permitted better utilization of sequencing resources.

Microbial Community Diversity as a Potential Bioindicator of AMD and Steel Plant Effluent in a Channelled Valley Bottom Wetland

Freshwater resources in semi-arid countries are under constant threat from pollution. One of the major pollutants is acid mine drainage (AMD), which not only lowers the pH of the water, but contains high sulphuric acid and high metal concentrations. Bacteria and algae are the first organisms to respond to stressors such as reduced pH and high metal concentrations. The bacterial community in a natural freshwater wetland impacted by AMD and steel plant effluent was identified, with the objective to include bacterial indicator communities in an ecotoxicological screening tool for wetland ecosystem health estimation. Five study sites at the Grootspruit canal valley bottom wetland in Mpumalanga, South Africa, were identified as case study areas which include a reference site and four AMD-impacted sites displaying various degrees of degradation. Physical, chemical and microbiological parameters were measured at each site. The bacterial community was sampled from both the water column and bottom sediment and subjected to next-generation sequencing for identification. The bacterial diversity was high, even at the most impacted sites. The phyla that were predominant in all the samples were the alpha-, beta- and gamma-Proteobacteria and Bacteriodetes. The bacterial based bio-assessment tool scored the reference site as mostly unaffected by anthropogenic impacts, while the AMD and steel plant effluent-impacted sites were classified as modified to severely modify. The outcome of the study showed that the proposed bacterial bioindicators can potentially be employed as part of the ecotoxicological screening tool to determine wetland ecosystem health.

Nextgeneration sequencing for identification of candidate genes for Fusarium wilt and sterility mosaic disease in pigeonpea Cajanus cajan

Nextgeneration sequencing for identification of candidate genes for Fusarium wilt and sterility mosaic disease in pigeonpea Cajanus cajan

Next-generation sequencing for identification of candidate genes for Fusarium wilt and sterility mosaic disease in pigeonpea (Cajanus cajan)

Next-generation sequencing for identification of candidate genes for Fusarium wilt and sterility mosaic disease in pigeonpea (Cajanus cajan)

Aarskog-Scott syndrome: phenotypic and genetic heterogeneity

AbstractAarskog-Scott syndrome (AAS) is a rare developmental disorder which primarily affects males and has a relative prevalence of 1 in 25,000 in the general population. AAS patients usually present with developmental complications including short stature and facial, skeletal and urogenital anomalies. The spectrum of genotype-phenotype correlations in AAS is unclear and mutations of the FGD1 gene on the proximal short arm of chromosome X account for only 20% of the incidence of the disorder. Failure to identify pathogenic variants in patients referred for FGD1 screening suggests heterogeneity underlying pathophysiology of the condition. Furthermore, overlapping features of AAS with several other developmental disorders increase the complexity of diagnosis. Cytoskeletal signaling may be involved in the pathophysiology of AAS. The FGD1 protein family has a role in activation of CDC42 (Cell Division Control protein 42 homolog) which has a core function in remodeling of extracellular matrix and the transcriptional activation of many modulators of development. Therefore, mutations in components in the EGFR1 (Epidermal Growth Factor Receptor 1) signaling pathway, to which CDC42 belongs, may contribute to pathophysiology. Parallel sequencing strategies (so-called next generation sequencing or high throughput sequencing) enables simultaneous production of millions of sequencing reads that enormously facilitate cost-effective identification of cryptic mutations in heterogeneous monogenic disorders. Here we review the source of phenotypic and genetic heterogeneity in the context of AAS and discuss the applicability of next generation sequencing for identification of novel mutations underlying AAS.

Abstract 12257: Calmodulin Interacting Genes as a Novel Candidate for Pathogenesis of Long-QT Syndrome

Background: Approximately 30% of long-QT syndrome (LQTS) cases remains genetically elusive. Here, we investigated usefulness of the whole exon sequencing (WES) by next-generation sequencing for identification of novel pathogenic candidates which directly or indirectly interact with proteins encoded by known LQTS genes. Methods: Of 1815 Japanese LQTS cohort patients, WES was performed in 59 LQTS patients and 61 unaffected individuals from 35 families and 138 unrelated LQTS cases, all were screened major LQTS genes such as KCNQ1, KCNH2, SCN5A, KCNE1, KCNE2 and KCNJ2. After WES, the genes known as inherited arrhythmias were screened by the Human Gene Mutation Database, and the Sanger sequencing was also referred for validation of the mutations and common variants were excluded by the public (1000G, ESP6500 and dbSNP) and Riken database. Results: Total 92 candidate mutations including 11 de novo, 5 recessive (2 homozygous and 3 compound heterozygous) and 73 dominant mutations in 88 genes were identified in 23 of the 35 families. Protein-protein interaction network analyses revealed ten new pathogenic candidates (WDR26, RYR2, UBR5, UBR4, KIF21B, CIT, SIRT6, PIK3CG, PI4KA and RIMS1) that directly or indirectly interact with proteins encoded by known LQTS genes. Furthermore, gene based association studies identified an additional novel candidate; SLC2A5. Taken together, mutations in these new candidates or known LQTS genes were identified in 13 of the 35(37%) genotype-unknown LQTS families. Moreover, 5 of the 11 newly identified candidates directly interact with calmodulin (CaM). Subsequent variant analysis in the independent set of 138 cases identified 16 variants in the 11 genes, of which, 14 (87.5%) were in the CaM-interacting genes and 8 of them were in RYR2. Many of the patients with RyR2 mutation had similar exercise-induced cardiac events (3 syncope, 2 VF) as LQTS patients, while the QTc interval was shorter in patients with RyR2 mutation than those with genotype-negative LQTS (441±32 vs. 487±47ms; p=0.01). Conclusions: These findings suggest that CaM interacting genes have an important role on the pathogenesis of LQTS. In particular, RYR2 mutations may cause an overlap syndrome between catecholaminergic polymorphic ventricular tachycardia and LQTS.

Marker Assisted Selection-Applications and Evaluation for Commercial Poultry Breeding

Poultry industry is abounding day by day as it engrosses less cost of investment per bird as compared to large animals. Poultry have the most copious genomic tool box amongst domestic animals for the detection of quantitative trait loci (QTL) and marker assisted selection (MAS). Use of multiple markers and least square techniques for mapping of QTL affecting quality and production traits in poultry is in vogue. Examples of genetic tests that are available to or used in industry programs are documented and classified into causative mutations (direct markers), linked markers in population-wide linkage disequilibrium (LD) with the QTL (LD markers), and linked markers in population wide equilibrium with the QTL (LE markers). Development of genome-wide SNP assays, role of 42 K, 60 K (Illumina) and 600 K (Affymetrix<TEX>$^{(R)}$</TEX> Axim<TEX>$^{(R)}$</TEX>) SNP chip with next generation sequencing for identification of single nucleotide polymorphism (SNP) has been documented. Hybridization based, PCR based, DNA chip and sequencing based are the major segments of DNA markers which help in conducting of MAS in poultry. Economic index-marker assisted selection (EI-MAS) provides platform for simultaneous selection for production traits while giving due weightage to their marginal economic values by calculating predicted breeding value, using information on DNA markers which are normally associated with relevant QTL. Understanding of linkage equilibrium, linkage dis-equilibrium, relation between the markers and gene of interest are quite important for success of MAS. This kind of selection is the most useful tool in enhancing disease resistance by identifying candidate genes to improve the immune response. The application of marker assisted selection in selection procedures would help in improvement of economic traits in poultry.

Coupled high-throughput functional screening and next generation sequencing for identification of plant polymer decomposing enzymes in metagenomic libraries

Recent advances in sequencing technologies generate new predictions and hypotheses about the functional roles of environmental microorganisms. Yet, until we can test these predictions at a scale that matches our ability to generate them, most of them will remain as hypotheses. Function-based mining of metagenomic libraries can provide direct linkages between genes, metabolic traits and microbial taxa and thus bridge this gap between sequence data generation and functional predictions. Here we developed high-throughput screening assays for function-based characterization of activities involved in plant polymer decomposition from environmental metagenomic libraries. The multiplexed assays use fluorogenic and chromogenic substrates, combine automated liquid handling and use a genetically modified expression host to enable simultaneous screening of 12,160 clones for 14 activities in a total of 170,240 reactions. Using this platform we identified 374 (0.26%) cellulose, hemicellulose, chitin, starch, phosphate and protein hydrolyzing clones from fosmid libraries prepared from decomposing leaf litter. Sequencing on the Illumina MiSeq platform, followed by assembly and gene prediction of a subset of 95 fosmid clones, identified a broad range of bacterial phyla, including Actinobacteria, Bacteroidetes, multiple Proteobacteria sub-phyla in addition to some Fungi. Carbohydrate-active enzyme genes from 20 different glycoside hydrolase (GH) families were detected. Using tetranucleotide frequency (TNF) binning of fosmid sequences, multiple enzyme activities from distinct fosmids were linked, demonstrating how biochemically-confirmed functional traits in environmental metagenomes may be attributed to groups of specific organisms. Overall, our results demonstrate how functional screening of metagenomic libraries can be used to connect microbial functionality to community composition and, as a result, complement large-scale metagenomic sequencing efforts.