Era Of Next-generation Sequencing Research Articles

Assessing the Relevance of Non-molecular Prognostic Systems for Myelodysplastic Syndrome in the Era of Next-Generation Sequencing.

The Molecular International Prognostic Scoring System (IPSS-M) has improved the prediction of clinical outcomes for myelodysplastic syndromes (MDS). The Artificial Intelligence Prognostic Scoring System for MDS (AIPSS-MDS), based on classical clinical parameters, has outperformed the IPSS, revised version (IPSS-R). For the first time, we validated the IPSS-M and other molecular prognostic models and compared them with the established IPSS-R and AIPSS-MDS models using data from South American patients. Molecular and clinical data from 145 patients with MDS and 37 patients with MDS/myeloproliferative neoplasms were retrospectively analyzed. Prognostic power evaluation revealed that the IPSS-M (Harrell's concordance [C]-index: 0.75, area under the receiver operating characteristic curve [AUC]: 0.68) predicted overall survival better than the European MDS (EuroMDS; C-index: 0.72, AUC: 0.68) and Munich Leukemia Laboratory (MLL) (C-index: 0.70, AUC: 0.64) models. The IPSS-M prognostic discrimination was similar to that of the AIPSS-MDS model (C-index: 0.74, AUC: 0.66) and outperformed the IPSS-R model (C-index: 0.70, AUC: 0.61). Considering simplified low- and high-risk groups for clinical management, after restratifying from IPSS-R (57% and 32%, respectively, hazard ratio [HR]: 2.8; P=0.002) to IPSS-M, 12.6% of patients were upstaged, and 5% were downstaged (HR: 2.9; P=0.001). The AIPSS-MDS recategorized 51% of the low-risk cohort as high-risk, with no patients being downstaged (HR: 5.6; P<0.001), consistent with most patients requiring disease-modifying therapy. The IPSS-M and AIPSS-MDS models provide more accurate survival prognoses than the IPSS-R, EuroMDS, and MLL models. The AIPSS-MDS model is a valid option for assessing risks for all patients with MDS, especially in resource-limited centers where molecular testing is not currently a standard clinical practice.

Short Tandem Repeats in the era of next-generation sequencing: from historical loci to population databases.

In this study, we explore the landscape of short tandem repeats (STRs) within the human genome through the lens of evolving technologies to detect genomic variations. STRs, which encompass approximately 3% of our genomic DNA, are crucial for understanding human genetic diversity, disease mechanisms, and evolutionary biology. The advent of high-throughput sequencing methods has revolutionized our ability to accurately map and analyze STRs, highlighting their significance in genetic disorders, forensic science, and population genetics. We review the current available methodologies for STR analysis, the challenges in interpreting STR variations across different populations, and the implications of STRs in medical genetics. Our findings underscore the urgent need for comprehensive STR databases that reflect the genetic diversity of global populations, facilitating the interpretation of STR data in clinical diagnostics, genetic research, and forensic applications. This work sets the stage for future studies aimed at harnessing STR variations to elucidate complex genetic traits and diseases, reinforcing the importance of integrating STRs into genetic research and clinical practice.

Short Tandem Repeats in the era of next-generation sequencing: from historical loci to population databases.

In this study, we explore the landscape of short tandem repeats (STRs) within the human genome through the lens of evolving technologies to detect genomic variations. STRs, which encompass approximately 3% of our genomic DNA, are crucial for understanding human genetic diversity, disease mechanisms, and evolutionary biology. The advent of high-throughput sequencing methods has revolutionized our ability to accurately map and analyze STRs, highlighting their significance in genetic disorders, forensic science, and population genetics. We review the current available methodologies for STR analysis, the challenges in interpreting STR variations across different populations, and the implications of STRs in medical genetics. Our findings underscore the urgent need for comprehensive STR databases that reflect the genetic diversity of global populations, facilitating the interpretation of STR data in clinical diagnostics, genetic research, and forensic applications. This work sets the stage for future studies aimed at harnessing STR variations to elucidate complex genetic traits and diseases, reinforcing the importance of integrating STRs into genetic research and clinical practice.

Optimization of Fluorescence In Situ Hybridization Protocols in the Era of Precision Medicine.

Fluorescence in situ hybridization (FISH) is a cytogenetic assay that is widely used in both clinical and research settings to validate genetic aberrations. Simple in principle, it is based on denaturation and hybridization of a DNA probe and its complementary sequence; however, it is subject to continuous optimization. Here we share how in-house FISH can be optimized using different control tissues to visualize and ultimately validate common and novel genetic abnormalities unearthed by next-generation sequencing (NGS). Seven specific FISH probes were designed and labeled, and conditions for eight tissue types and one patient-derived tumor organoid were optimized. Formalin-fixed paraffin-embedded (FFPE) tissue slides were used for each experiment. Slides were first deparaffinized, then placed in a pretreatment solution followed by a digestion step. In-house FISH probes were then added to the tissue to be denatured and hybridized, and then washed twice. To obtain optimal results, probe concentration, pepsin incubation time, denaturation, and the two post-hybridization washes were optimized for each sample. By modifying the above conditions, all FISH experiments were optimized in separate tissue types to investigate specific genomic alterations in tumors arising in those tissues. Signals were clear and distinct, allowing for visualization of the selected probes. Following this protocol, our lab has quickly optimized 11 directly labeled in-house FISH probes to support genetic aberrations nominated by NGS, including most recent discoveries through whole-genome sequencing analyses. We describe a robust approach of how to advance in-house labeled FISH probes. By following these guidelines, reliable and reproducible FISH results can be obtained to interrogate FFPE slides from benign, tumor tissues, and patient-derived tumor organoid specimens. This is of most relevance in the era of NGS and precision oncology. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Metaphase FISH optimization Support Protocol 1: In-house probe labeling and preparation Support Protocol 2: Metaphase spread preparation Basic Protocol 2: Optimization of FISH on formalin-fixed paraffin-embedded tissue.

The Utility of Genetic Testing in Infantile Epileptic Spasms Syndrome: A Step-Based Approach in the Next-Generation Sequencing Era

BackgroundTo evaluate the utility of genetic testing for etiology-specific diagnosis (ESD) in infantile epileptic spasms syndrome (IESS) with a step-based diagnostic approach in the next-generation sequencing (NGS) era. MethodsThe study cohort consisted of 314 patients with IESS, followed by the Pediatric Neurology Division of Ege University Hospital between 2005 and 2021. The ESD was evaluated using a step-based approach: step I (clinical phenomenology), step II (neuroimaging), step III (metabolic screening), and step IV (genetic testing). The diagnostic utility of genetic testing was evaluated to compare the early-NGS period (2005 to 2013, n = 183) and the NGS era (2014 to 2021, n = 131). ResultsAn ESD was established in 221 of 314 (70.4%) infants with IESS: structural, 40.8%; genetic, 17.2%; metabolic, 8.3%; immune-infectious, 4.1%. The diagnostic yield of genetic testing increased from 8.9% to 41.7% in the cohort during the four follow-up periods. The rate of unknown etiology decreased from 34.9% to 22.1% during the follow-up periods. The genetic ESD was established as 27.4% with genetic testing in the NGS era. The genetic testing in the NGS era increased dramatically in subgroups with unknown and structural etiologies. The diagnostic yields of the epilepsy panels increased from 7.6% to 19.2%. However, the diagnostic yield of whole exome sequencing remained at similar levels during the early-NGS period at 54.5% and in the NGS era at 59%. ConclusionsThe more genetic ESD (27.4%) was defined for IESS in the NGS era with the implication of precision therapy (37.7%).

Variants of Unknown Significance in Maturity-Onset Diabetes of the Young: High Rate of Conundrum Resolution via Variants of Unknown Significance Reanalysis

Introduction: In the era of next-generation sequencing, clinicians frequently encounter variants of unknown significance (VUS) in genetic testing. VUS may be reclassified over time as genetic knowledge grows. We know little about how best to approach VUS in the maturity-onset diabetes of the young (MODY). Therefore, our study aimed to determine the utility of reanalysis of previous VUS results in genetic confirmation of MODY. Methods: A single-center retrospective chart review identified 85 subjects with a MODY clinical diagnosis. We reanalyzed genetic testing in 10 subjects with 14 unique VUS on MODY genes that was performed >3 years before the study. Demographic, clinical, and biochemical data was collected for those individuals. Results: After reanalysis, 43% (6/14) of the gene variants were reclassified to a different category: 7% (1/14) were “likely pathogenic” and 36% (5/14) were “benign” or “likely benign.” The reclassified pathogenic variant was in HNF1A and all reclassified benign variants were in HNF1A, HNF1B and PDX1. The median time between MODY testing and reclassification was 8 years (range: 4–10 years). Conclusion: In sum, iterative reanalyzing the genetic data from VUS found during MODY testing may provide high-yield diagnostic information. Further studies are warranted to identify the optimal time and frequency for such analyses.

The utility of electrodiagnostic testing in unprovoked rhabdomyolysis in the era of next-generation sequencing.

Rhabdomyolysis is an etiologically heterogeneous, acute necrosis of myofibers characterized by transient marked creatine kinase (CK) elevation associated with myalgia, muscle edema, and/or weakness. The study aimed to determine the role of electrodiagnostic (EDX) testing relative to genetic testing and muscle biopsy in patients with unprovoked rhabdomyolysis in identifying an underlying myopathy. EDX database was reviewed to identify unprovoked rhabdomyolysis patients who underwent EDX testing between January 2012 and January 2022. Each patient's clinical profile, EDX findings, muscle pathology, laboratory, and genetic testing results were analyzed. Of 66 patients identified, 32 had myopathic electromyography (EMG). Muscle biopsy and genetic testing were performed in 41 and 37 patients, respectively. A definitive diagnosis was achieved in 15 patients (11 myopathic EMG and 4 nonmyopathic EMG; p = .04) based on abnormal muscle biopsy (4/11 patients) or genetic testing (12/12 patients, encompassing 5 patients with normal muscle biopsy and 3 patients with nonmyopathic EMG). These included seven metabolic and eight nonmetabolic myopathies (five muscular dystrophies and three ryanodine receptor 1 [RYR1]-myopathies). Patients were more likely to have baseline weakness (p < .01), elevated baseline CK (p < .01), and nonmetabolic myopathies (p = .03) when myopathic EMG was identified. Myopathic EMG occurred in approximately half of patients with unprovoked rhabdomyolysis, more likely in patients with weakness and elevated CK at baseline. Although patients with myopathic EMG were more likely to have nonmetabolic myopathies, nonmyopathic EMG did not exclude myopathy, and genetic testing was primarily helpful to identify an underlying myopathy. Genetic testing should likely be first-tier diagnostic testing following unprovoked rhabdomyolysis.

Digital counting of tissue cells for molecular analysis: the QuANTUM pipeline.

The estimation of tumor cellular fraction (TCF) is a crucial step in predictive molecular pathology, representing an entry adequacy criterion also in the next-generation sequencing (NGS) era. However, heterogeneity of quantification practices and inter-pathologist variability hamper the robustness of its evaluation, stressing the need for more reliable results. Here, 121 routine histological samples from non-small cell lung cancer (NSCLC) cases with complete NGS profiling were used to evaluate TCF interobserver variability among three different pathologists (pTCF), developing a computational tool (cTCF) and assessing its reliability vs ground truth (GT) tumor cellularity and potential impact on the final molecular results. Inter-pathologist reproducibility was fair to good, with overall Wk ranging between 0.46 and 0.83 (avg. 0.59). The obtained cTCF was comparable to the GT (p = 0.129, 0.502, and 0.130 for surgical, biopsies, and cell block, respectively) and demonstrated good reliability if elaborated by different pathologists (Wk = 0.9). Overall cTCF was lower as compared to pTCF (30 ± 10 vs 52 ± 19, p < 0.001), with more cases < 20% (17, 14%, p = 0.690), but none containing < 100 cells for the algorithm. Similarities were noted between tumor area estimation and pTCF (36 ± 29, p < 0.001), partly explaining variability in the human assessment of tumor cellularity. Finally, the cTCF allowed a reduction of the copy number variations (CNVs) called (27 vs 29, - 6.9%) with an increase of effective CNVs detection (13 vs 7, + 85.7%), some with potential clinical impact previously undetected with pTCF. An automated computational pipeline (Qupath Analysis of Nuclei from Tumor to Uniform Molecular tests, QuANTUM) has been created and is freely available as a QuPath extension. The computational method used in this study has the potential to improve efficacy and reliability of TCF estimation in NSCLC, with demonstrated impact on the final molecular results.

The genetic landscape of mitochondrial diseases in the next-generation sequencing era: a Portuguese cohort study.

Introduction: Rare disorders that are genetically and clinically heterogeneous, such as mitochondrial diseases (MDs), have a challenging diagnosis. Nuclear genes codify most proteins involved in mitochondrial biogenesis, despite all mitochondria having their own DNA. The development of next-generation sequencing (NGS) technologies has revolutionized the understanding of many genes involved in the pathogenesis of MDs. In this new genetic era, using the NGS approach, we aimed to identify the genetic etiology for a suspected MD in a cohort of 450 Portuguese patients. Methods: We examined 450 patients using a combined NGS strategy, starting with the analysis of a targeted mitochondrial panel of 213 nuclear genes, and then proceeding to analyze the whole mitochondrial DNA. Results and Discussion: In this study, we identified disease-related variants in 134 (30%) analyzed patients, 88 with nuclear DNA (nDNA) and 46 with mitochondrial DNA (mtDNA) variants, most of them being pediatric patients (66%), of which 77% were identified in nDNA and 23% in mtDNA. The molecular analysis of this cohort revealed 72 already described pathogenic and 20 novel, probably pathogenic, variants, as well as 62 variants of unknown significance. For this cohort of patients with suspected MDs, the use of a customized gene panel provided a molecular diagnosis in a timely and cost-effective manner. Patients who cannot be diagnosed after this initial approach will be further selected for whole-exome sequencing. Conclusion: As a national laboratory for the study and research of MDs, we demonstrated the power of NGS to achieve a molecular etiology, expanding the mutational spectrum and proposing accurate genetic counseling in this group of heterogeneous diseases without therapeutic options.

Considerations for Familial Chylomicronemia Diagnosis in the Era of Next-Generation Sequencing: A Latin American Perspective

Considerations for Familial Chylomicronemia Diagnosis in the Era of Next-Generation Sequencing: A Latin American Perspective

Does Neonatal Microbiome Research Encompass the Placental Transfer Pathway?

The word “microbiome” is a combination of “microbiota” and “genome,” which represents the genomic concept of microbiota. The bacterial culture method is the mainstay of identifying microbes, while polymerase chain reaction adds diagnostic value. However, in the era of next-generation sequencing, achieving high-throughput microbiota footprints is extremely sensitive. This sensitivity often leads to confusion, as it can detect specific microbes genomes, even in sterile samples, such as blood, placenta, breast milk, skin, vagina, and stool. The neonatal microbiome remarkably influences both fetal and neonatal life related to health status and disease outcome. However, its origins pose a question: does it stem from a direct gateway or through a breakdown of barriers? This review provides a brief overview of evidence and speculative insights.

Statistical learning quantifies transposable element-mediated cis-regulation

BackgroundTransposable elements (TEs) have colonized the genomes of most metazoans, and many TE-embedded sequences function as cis-regulatory elements (CREs) for genes involved in a wide range of biological processes from early embryogenesis to innate immune responses. Because of their repetitive nature, TEs have the potential to form CRE platforms enabling the coordinated and genome-wide regulation of protein-coding genes by only a handful of trans-acting transcription factors (TFs).ResultsHere, we directly test this hypothesis through mathematical modeling and demonstrate that differences in expression at protein-coding genes alone are sufficient to estimate the magnitude and significance of TE-contributed cis-regulatory activities, even in contexts where TE-derived transcription fails to do so. We leverage hundreds of overexpression experiments and estimate that, overall, gene expression is influenced by TE-embedded CREs situated within approximately 500 kb of promoters. Focusing on the cis-regulatory potential of TEs within the gene regulatory network of human embryonic stem cells, we find that pluripotency-specific and evolutionarily young TE subfamilies can be reactivated by TFs involved in post-implantation embryogenesis. Finally, we show that TE subfamilies can be split into truly regulatorily active versus inactive fractions based on additional information such as matched epigenomic data, observing that TF binding may better predict TE cis-regulatory activity than differences in histone marks.ConclusionOur results suggest that TE-embedded CREs contribute to gene regulation during and beyond gastrulation. On a methodological level, we provide a statistical tool that infers TE-dependent cis-regulation from RNA-seq data alone, thus facilitating the study of TEs in the next-generation sequencing era.

Novel alleles in the era of next-generation sequencing-based HLA typing calls for standardization and policy.

Next-Generation Sequencing (NGS) has transformed clinical histocompatibility laboratories through its capacity to provide accurate, high-throughput, high-resolution typing of Human Leukocyte Antigen (HLA) genes, which is critical for transplant safety and success. As this technology becomes widely used for clinical genotyping, histocompatibility laboratories now have an increased capability to identify novel HLA alleles that previously would not be detected using traditional genotyping methods. Standard guidelines for the clinical verification and reporting of novelties in the era of NGS are greatly needed. Here, we describe the experience of a clinical histocompatibility laboratory's use of NGS for HLA genotyping and its management of novel alleles detected in an ethnically-diverse population of British Columbia, Canada. Over a period of 18months, 3,450 clinical samples collected for the purpose of solid organ or hematopoietic stem cell transplantation were sequenced using NGS. Overall, 29 unique novel alleles were identified at a rate of ∼1.6 per month. The majority of novelties (52%) were detected in the alpha chains of class II (HLA-DQA1 and -DPA1). Novelties were found in all 11 HLA classical genes except for HLA-DRB3, -DRB4, and -DQB1. All novelties were single nucleotide polymorphisms, where more than half led to an amino acid change, and one resulted in a premature stop codon. Missense mutations were evaluated for changes in their amino acid properties to assess the potential effect on the novel HLA protein. All novelties identified were confirmed independently at another accredited HLA laboratory using a different NGS assay and platform to ensure validity in the reporting of novelties. The novel alleles were submitted to the Immuno Polymorphism Database-Immunogenetics/HLA (IPD-IMGT/HLA) for official allele name designation and inclusion in future database releases. A nationwide survey involving all Canadian HLA laboratories confirmed the common occurrence of novel allele detection but identified a wide variability in the assessment and reporting of novelties. In summary, a considerable proportion of novel alleles were identified in routine clinical testing. We propose a framework for the standardization of policies on the clinical management of novel alleles and inclusion in proficiency testing programs in the era of NGS-based HLA genotyping.

BCR::ABL1-negative myeloproliferative neoplasms in the era of next-generation sequencing.

The classical BCR::ABL1-negative myeloproliferative neoplasms such as polycythemia vera (PV), essential thrombocythemia (ET), and myelofibrosis (MF) are clonal diseases with the presence of characteristic "driver mutations" in one of the genes: JAK2, CALR, or MPL. The search for mutations in these three genes is required for the diagnosis of MPNs. Nevertheless, the progress that has been made in the field of molecular genetics has opened a new era in medicine. The search for additional mutations in MPNs is helpful in assessing the risk stratification, disease progression, transformation to acute myeloid leukemia (AML), or choosing the right treatment. In some cases, advanced technologies are needed to find a clonal marker of the disease and establish a diagnosis. This review focuses on how the use of new technologies like next-generation sequencing (NGS) helps in the diagnosis of BCR::ABL1-negative myeloproliferative neoplasms.

Pangenome insights into the diversification and disease specificity of worldwide Xanthomonas outbreaks.

The bacterial genus Xanthomonas is responsible for disease outbreaks in several hundred plant species, many of them economically important crops. In the era of next-generation sequencing, thousands of strains from this genus have now been sequenced as part of isolated studies that focus on outbreak characterization, host range, diversity, and virulence factor identification. However, these data have not been synthesized and we lack a comprehensive phylogeny for the genus, with some species designations in public databases still relying on phenotypic similarities and representative sequence typing. The extent of genetic cohesiveness among Xanthomonas strains, the distribution of virulence factors across strains, and the impact of evolutionary history on host range across the genus are also poorly understood. In this study, we present a pangenome analysis of 1,910 diverse Xanthomonas genomes, highlighting their evolutionary relationships, the distribution of virulence-associated genes across strains, and rates of horizontal gene transfer. We find a number of broadly conserved classes of virulence factors and considerable diversity in the Type 3 Secretion Systems (T3SSs) and Type 3 Secreted Effector (T3SE) repertoires of different Xanthomonas species. We also use these data to re-assign incorrectly classified strains to phylogenetically informed species designations and find evidence of both monophyletic host specificity and convergent evolution of phylogenetically distant strains to the same host. Finally, we explore the role of recombination in maintaining genetic cohesion within the Xanthomonas genus as a result of both ancestral and recent recombination events. Understanding the evolutionary history of Xanthomonas species and the relationship of key virulence factors with host-specificity provides valuable insight into the mechanisms through which Xanthomonas species shift between hosts and will enable us to develop more robust resistance strategies against these highly virulent pathogens.

1281-P: Variants of Unknown Significance (VUS) in Maturity-Onset Diabetes of the Young (MODY)—High Rate of Conundrum Resolution via Reanalysis of VUS

In the era of next-generation sequencing, clinicians frequently encounter VUS on genetic tests for MODY. Pathogenicity ascertainment of those variants may have substantial impact on optimal diabetes care. We aimed to determine the usefulness of reanalyzing previous VUS results in MODY. We performed a retrospective chart review to identify subjects with a VUS on a MODY genetic test performed &amp;gt; 3 years before the study and requested reanalysis of their genetic data at Athena Diagnostics. We identified 10 subjects with at least one VUS on MODY genetic testing (mean age at diagnosis: 13.4 ± 3.4 years, 60% female, 60% Hispanic, 20% African American and 20% non-Hispanic White). After reanalysis, 50% were recategorized to a different category: 30% “likely pathogenic” and 20% “benign”. All newly reclassified pathogenic variants were in HNF1A, and benign variants were in HNF1B and PDX1. The median time to reclassification since MODY testing was 8 years (range 4-10 years). The mean random C-peptide at diagnosis was 1.17 ± 0.17, 2.24 ± 0.8 and 2.96 ± 1.4 ng/mL for those with variants reclassified as benign, likely pathogenic and those who remained as VUS, respectively. In sum, periodic reanalysis of the genetic data of cases with a VUS on MODY tests may provide high-yield diagnostic information. Further studies are warranted to identify the optimal time and frequency for such analyses. Disclosure G.Alarcon: None. M.J.Redondo: None. M.Tosur: Advisory Panel; Provention Bio, Inc.

Metabolic Myopathies in the Era of Next-Generation Sequencing

Metabolic myopathies are rare inherited disorders that deserve more attention from neurologists and pediatricians. Pompe disease and McArdle disease represent some of the most common diseases in clinical practice; however, other less common diseases are now better-known. In general the pathophysiology of metabolic myopathies needs to be better understood. Thanks to the advent of next-generation sequencing (NGS), genetic testing has replaced more invasive investigations and sophisticated enzymatic assays to reach a final diagnosis in many cases. The current diagnostic algorithms for metabolic myopathies have integrated this paradigm shift and restrict invasive investigations for complicated cases. Moreover, NGS contributes to the discovery of novel genes and proteins, providing new insights into muscle metabolism and pathophysiology. More importantly, a growing number of these conditions are amenable to therapeutic approaches such as diets of different kinds, exercise training protocols, and enzyme replacement therapy or gene therapy. Prevention and management-notably of rhabdomyolysis-are key to avoiding serious and potentially life-threatening complications and improving patients' quality of life. Although not devoid of limitations, the newborn screening programs that are currently mushrooming across the globe show that early intervention in metabolic myopathies is a key factor for better therapeutic efficacy and long-term prognosis. As a whole NGS has largely increased the diagnostic yield of metabolic myopathies, but more invasive but classical investigations are still critical when the genetic diagnosis is unclear or when it comes to optimizing the follow-up and care of these muscular disorders.

Limitations of using 16S rRNA microbiome sequencing to predict oral squamous cell carcinoma.

A new era of next-generation sequencing has changed our perception of the oral microbiome in health and disease, and with this there is a growing understanding that the oral microbiome is a contributing factor to oral squamous cell carcinoma (OSCC), a malignancy of the oral cavity. This study aimed to analyse the trends and relevant literature based on the 16S rRNA oral microbiome in head and neck cancer using next-generation sequencing technologies, and to conduct a meta-analysis of the studies with OSCC cases and healthy controls. A literature search using the databases Web of Science and PubMed was conducted in a scoping-like review to collect information based on the study design, and plots were generated using RStudio. We selected case-control studies using 16S rRNA oral microbiome sequencing analysis in OSCC cases versus healthy controls for re-analysis. Statistical analyses were conducted using R. Out of 916 original articles, we filtered and selected 58 studies for review, and 11 studies for meta-analysis. Differences between sampling type, DNA extraction methods, next-generation sequencing technology and region of the 16S rRNA were identified. No significant differences in the α- and β-diversity between health and oral squamous cell carcinoma were observed (p < 0.05). Random Forest classification marginally improved predictability of four studies (training set) when split 80/20. We found an increase in Selenomonas, Leptotrichia and Prevotella species to be indicative of disease. A number of technological advances have been accomplished to study oral microbial dysbiosis in oral squamous cell carcinoma. There is a clear need for standardization of study design and methodology to ensure 16S rRNA outputs are comparable across the discipline in the hope of identifying 'biomarker' organisms for designing screening or diagnostic tools.

A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets

In the next-generation sequencing era, RT-qPCR is still widely employed to quantify levels of nucleic acids of interest due to its popularity, versatility, and limited costs. The measurement of transcriptional levels through RT-qPCR critically depends on reference genes used for normalization. Here, we devised a strategy to select appropriate reference genes for a specific clinical/experimental setting based on publicly available transcriptomic datasets and a pipeline for RT-qPCR assay design and validation. As a proof-of-principle, we applied this strategy to identify and validate reference genes for transcriptional studies of bone-marrow plasma cells from patients with AL amyloidosis. We performed a systematic review of published literature to compile a list of 163 candidate reference genes for RT-qPCR experiments employing human samples. Next, we interrogated the Gene Expression Omnibus to assess expression levels of these genes in published transcriptomic studies on bone-marrow plasma cells from patients with different plasma cell dyscrasias and identified the most stably expressed genes as candidate normalizing genes. Experimental validation on bone-marrow plasma cells showed the superiority of candidate reference genes identified through this strategy over commonly employed "housekeeping" genes. The strategy presented here may apply to other clinical and experimental settings for which publicly available transcriptomic datasets are available.

Prevalence of genetically confirmed skeletal muscle channelopathies in the era of next generation sequencing

We provide an up-to-date and accurate minimum point prevalence of genetically defined skeletal muscle channelopathies which is important for understanding the population impact, planning for treatment needs and future clinical trials. Skeletal muscle channelopathies include myotonia congenita (MC), sodium channel myotonia (SCM), paramyotonia congenita (PMC), hyperkalemic periodic paralysis (hyperPP), hypokalemic periodic paralysis (hypoPP) and Andersen- Tawil Syndrome (ATS). Patients referred to the UK national referral centre for skeletal muscle channelopathies and living in UK were included to calculate the minimum point prevalence using the latest data from the Office for National Statistics population estimate. We calculated a minimum point prevalence of all skeletal muscle channelopathies of 1.99/100 000 (95% CI 1.981–1.999). The minimum point prevalence of MC due to CLCN1 variants is 1.13/100 000 (95% CI 1.123–1.137), SCN4A variants which encode for PMC and SCM is 0.35/100 000 (95% CI 0.346 – 0.354) and for periodic paralysis (HyperPP and HypoPP) 0.41/100 000 (95% CI 0.406–0.414). The minimum point prevalence for ATS is 0.1/100 000 (95% CI 0.098–0.102). There has been an overall increase in point prevalence in skeletal muscle channelopathies compared to previous reports, with the biggest increase found to be in MC. This can be attributed to next generation sequencing and advances in clinical, electrophysiological and genetic characterisation of skeletal muscle channelopathies.