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The cancer genome plays an increasingly large role in the care of patients with breast cancer. Commercially available gene-expression profiling assays are now a part of staging and treatment guidelines, and their use continues to be examined in large-scale studies. With the advent of next-generation sequencing, the cancer genome can now be examined more quickly, less invasively, and in much greater detail. These technologies have led to a more nuanced understanding of molecular pathways, allowing providers to better match patients to clinical trials. Furthermore, a new era of diagnostics based on liquid biopsies is expected to revolutionize disease detection and clinical care.

Detection of insertions and deletions (InDels) by short-read next-generation sequencing (NGS) technology can be challenging because of frequent misaligned reads. A systematic analysis of short InDels (1 to 30 bases) and fms-related receptor tyrosine kinase 3 (FLT3) internal tandem duplications (ITDs; 6 to 183 bases) from 46 clinical cases of solid or hematologic malignancy processed with a clinical NGS assay identified misaligned reads in every case, ranging from 3% to 100% of reads with the InDel showing mismapped bases. Mismaps also increased with InDel size. As a consequence, the clinical NGS bioinformatics pipeline undercalled the variant allele frequency by 1% to 84%, incorrectly called simultaneous single-base substitutions along with InDels, or did not report an FLT3 ITD that had been detected by capillary electrophoresis. To improve the ability of the pipeline to better detect and quantify InDels, we utilized a software program called Assembly-Based ReAligner (ABRA2) to more accurately remap reads. ABRA2 was able to correct 41% to 100% of the reads with mismapped bases and led to absolute increases in the variant allele frequency from 1% to 61% along with correction of all of the single-base substitutions except for two cases. ABRA2 could also detect multiple FLT3 ITD clones except for one 183-base ITD. Our analysis has found that ABRA2 performs well on short InDels as well as FLT3 ITDs that are100 bases.

Cancer remains the second leading cause of death worldwide and newly diagnosed cases have increased at an alarming rate. One in every four people has a lifetime risk of being afflicted with cancer. Early diagnosis, which is essential in reducing morbidity and mortality, requires the development of highly sensitive and specific techniques to identify and monitor molecular changes for cancer-specific genetic and epigenetic markers. Among these, fluorescent in situ hybridization (FISH), Polymerase Chain Reaction (PCR), DNA microarray and NanoString technologies are notable. Recent advances in the development of efficient and cost-effective next-generation sequencing (NGS) has enabled whole genome, exome and transcriptome analysis. This review focuses on the features and applications of important molecular techniques to detect various genetic mutations thus enabling improved diagnosis, treatment and outcome.

Rapid, cost-effective genomic stratification of structural rearrangements in cancer is often of vital importance when determining treatment; however, existing diagnostic cytogenetic and molecular testing fails to deliver the required speed when deployed at scale. Next-generation sequencing-based methods are widely used, but these can lack sensitivity and require batching of samples to be cost-effective, with long turnaround times. Here we present a novel method for rearrangement detection from genomic DNA based on third-generation long-read sequencing that overcomes these time and cost issues. The utility of this approach for the genomic stratification of patients with acute myeloid leukemia is shown based on detection of four of the most prevalent structural rearrangements. The method not only determines the precise genomic breakpoint for each expected rearrangement but also discovers and validates novel translocations in one-third of the tested samples, 80% of which involve known oncogenes. This method may prove to be a powerful tool for the diagnosis, genomic stratification, and characterization of cancers.

Targeted therapies have transformed clinical management of advanced biliary tract cancer (BTC). Cell-free DNA (cfDNA) analysis is an attractive approach for cancer genomic profiling that overcomes many limitations of traditional tissue-based analysis. We examined cfDNA as a tool to inform clinical management of patients with advanced BTC and generate novel insights into BTC tumor biology.We analyzed next-generation sequencing data of 2068 cfDNA samples from 1671 patients with advanced BTC generated with Guardant360. We carried out clinical annotation on a multi-institutional subset (n = 225) to assess intra-patient cfDNA-tumor concordance and the association of cfDNA variant allele fraction (VAF) with clinical outcomes.Genetic alterations were detected in cfDNA in 84% of patients, with targetable alterations detected in 44% of patients. Fibroblast growth factor receptor 2 (FGFR2) fusions, isocitrate dehydrogenase 1 (IDH1) mutations, and BRAF V600E were clonal in the majority of cases, affirming these targetable alterations as early driver events in BTC. Concordance between cfDNA and tissue for mutation detection was high for IDH1 mutations (87%) and BRAF V600E (100%), and low for FGFR2 fusions (18%). cfDNA analysis uncovered novel putative mechanisms of resistance to targeted therapies, including mutation of the cysteine residue (FGFR2 C492F) to which covalent FGFR inhibitors bind. High pre-treatment cfDNA VAF was associated with poor prognosis and shorter response to chemotherapy and targeted therapy. Finally, we report the frequency of promising targets in advanced BTC currently under investigation in other advanced solid tumors, including KRAS G12C (1.0%), KRAS G12D (5.1%), PIK3CA mutations (6.8%), and ERBB2 amplifications (4.9%).These findings from the largest and most comprehensive study to date of cfDNA from patients with advanced BTC highlight the utility of cfDNA analysis in current management of this disease. Characterization of oncogenic drivers and mechanisms of therapeutic resistance in this study will inform drug development efforts to reduce mortality for patients with BTC.

Age-related changes in human vaginal microbiota composition have been reported, and such changes might be influenced by humidity, external stimuli, hormone levels, drug to use, and other factors. However, there is no report about the vaginal microbiota composition of female beagles at different ages. To investigate the effects of aging on the vaginal microbiota independent of other effects, we analyzed the vaginal microbiomes of 23 beagles at a wide range of ages from 1 year to 7 years old (except the 3rd year), 1-2 y were categorized into youth stage (YS), 4-5 y were categorized into middle stage (MS), and 6-7 y were categorized into elderly stage (ES) based on age. Samples were collected by scraping the vaginal mucosa of YS (n = 8), MS (n = 5) and ES (n = 10), and analyzed by 16S-rRNA gene high-throughput-sequencing. The diversity of the vaginal microbiome in female beagles was found to continuously change with age. We also found associations between age and specific members and functions of the vaginal microbiome. The metabolism of terpenoids and polyketide and the cell motility are significantly enhanced with age. Our results suggest that the proportion of Tenericutes might be a biomarker which could distinguish between YS and others.

Genomic profiling using short-read sequencing has utility in detecting disease-associated variation in both DNA and RNA. However, given the frequent occurrence of structural variation in cancer, molecular profiling using long-read sequencing improves the resolution of such events. For example, the Pacific Biosciences long-read RNA-sequencing (Iso-Seq) transcriptome protocol provides full-length isoform characterization, discernment of allelic phasing, and isoform discovery, and identifies expressed fusion partners. The Pacific Biosciences Fusion and Long Isoform Pipeline (PB_FLIP) incorporates a suite of RNA-sequencing software analysis tools and scripts to identify expressed fusion partners and isoforms. In addition, sequencing of a commercial reference (Spike-In RNA Variants) with known isoform complexity was performed and demonstrated high recall of the Iso-Seq and PB_FLIP workflow to benchmark our protocol and analysis performance. This study describes the utility of Iso-Seq and PB_FLIP analysis in improving deconvolution of complex structural variants and isoform detection within an institutional pediatric and adolescent/young adult translational cancer research cohort. The exemplar case studies demonstrate that Iso-Seq and PB_FLIP discover novel expressed fusion partners, resolve complex intragenic alterations, and discriminate between allele-specific expression profiles.

Medium-chain acyl-coenzyme A dehydrogenase deficiency (MCADD) is a rare inherited metabolic disorder of fatty acid β-oxidation and one of the most common inborn errors of metabolism. The incidence of MCADD varies among regions and ethnic groups. To date, few cases of MCADD have been documented in China.The present study aimed to find out the novel genetic pathogenic variants in the Chinese patients and evaluate the detection rate of the disease of high-frequency ACADM pathogenic variants in different regions of China.6 cases of MCADD were screened by tandem mass spectrometric (MS/MS) among 245 054 newborns. We performed next-generation sequencing on 6 families of infants with MCADD. We used the REVEL method to predict the protein function of the detected missense variants and used SPDBV 4.10 to predict the protein 3D structure model. We identified pathogenic variants of ACADM gene in 6 cases of MCADD, and then assessed these variants through Sanger sequencing and association analysis.The incidence of neonatal MCADD was 1/40,842 in Henan province. Among the 6 patients, five cases were compound heterozygous variants, one case was homozygous variants. DNA sequencing revealed 4 known (c.449_452del, c.1085G A, c.1229 T C, c.589A G) and 3 novel mutations (c.849 + 5_849 + 8del, c.427A G, c.1181C T) in the ACADM gene. Mutation c.1085G A (p.G362E) was most frequent among Henan people and shows obvious differences between North and South of China.MCADD is relatively rare in China, and c.1085G A (p.G362E) is a common mutation in Henan population. Our findings, especially novel variants, will help improve the understanding of the genetic background and have facilitated clinical diagnosis and genetic counseling for the affected families.

IDH1-mutated intrahepatic cholangiocarcinomas (IDH1m iCCAs) could be treated with anti-IDH1 drugs, although the high heterogeneity in this class of tumours could limit treatment efficacy.We selected 125 IDH1m iCCAs that were treated as resectable, locally advanced, or metastatic and were screened by the NGS-based FoundationOne gene panel. We conducted a mutation-based clustering of tumours and survival analysis.Three main clusters were identified. The most altered pathways in cluster 1 were cell cycle and apoptosis, RTK/RAS, PI3K, and chromatin modification. Of note, CDKN2A/2B were mutated in 41/44 patients of this cluster. In cluster 2, the most affected pathways were as follows: Chromatin modification, DNA damage control, PI3K, and RTK/RAS. In this cluster, the most frequently mutated genes were ARID1A and PBRM1. The most altered pathways in cluster 3 were as follows: Cell cycle and apoptosis, DNA damage control, TP53, and chromatin modification. Importantly, TP53 was mutated only in cluster 3 patients. In the cohort of patients treated with surgery, cluster 2 showed statistically significant better disease-free survival (DFS) and overall survival (OS) compared with patients in cluster 3 and cluster 1 (p = 0.0014 and p = 0.0003, respectively). In the advanced setting, cluster 2 experienced a statistically significant better PFS (p = 0.0012), a tendency toward a better OS from first-line treatment, and a better OS from first-line progression compared with patients in cluster 1 and cluster 3 (p = 0.0017). We proposed an easy-to-use algorithm able to stratify patients in the three clusters on the basis of the genomic profile.We highlighted three different mutation-based clusters with prognostic significance in a cohort of IDH1m iCCAs.

iTHER is a Dutch prospective national precision oncology program aiming to define tumour molecular profiles in children and adolescents with primary very high-risk, relapsed, or refractory paediatric tumours. Between April 2017 and April 2021, 302 samples from 253 patients were included. Comprehensive molecular profiling including low-coverage whole genome sequencing (lcWGS), whole exome sequencing (WES), RNA sequencing (RNA-seq), Affymetrix, and/or 850k methylation profiling was successfully performed for 226 samples with at least 20% tumour content. Germline pathogenic variants were identified in 16% of patients (35/219), of which 22 variants were judged causative for a cancer predisposition syndrome. At least one somatic alteration was detected in 204 (90.3%), and 185 (81.9%) were considered druggable, with clinical priority very high (6.1%), high (21.3%), moderate (26.0%), intermediate (36.1%), and borderline (10.5%) priority. iTHER led to revision or refinement of diagnosis in 8 patients (3.5%). Temporal heterogeneity was observed in paired samples of 15 patients, indicating the value of sequential analyses. Of 137 patients with follow-up beyond twelve months, 21 molecularly matched treatments were applied in 19 patients (13.9%), with clinical benefit in few. Most relevant barriers to not applying targeted therapies included poor performance status, as well as limited access to drugs within clinical trial. iTHER demonstrates the feasibility of comprehensive molecular profiling across all ages, tumour types and stages in paediatric cancers, informing of diagnostic, prognostic, and targetable alterations as well as reportable germline variants. Therefore, WES and RNA-seq is nowadays standard clinical care at the Princess Máxima Center for all children with cancer, including patients at primary diagnosis. Improved access to innovative treatments within biology-driven combination trials is required to ultimately improve survival.

With rare genetic variations having been increasingly recognized at a preclinical stage, a variety of early-phase clinical trials have been launched. Due to the low incidence rate of these variations, although the sample size of trials are small, it still needs a large number of patients for screening. With the advent of next-generation sequencing (NGS), multiple genetic variations can be detected simultaneously. Multiple biomarkers and agents can be evaluated using umbrella clinical trials, which rapidly and effectively screen and enroll patients for parallel sub-studies using NGS.We designed an open-label, multi-center, phase II clinical trial CTONG1702. This is an adaptive umbrella trial that will evaluate the efficacy and safety of several biomarker-driven agents, including tyrosine kinase inhibitors (TKIs) and a PD-1 inhibitor, in stage IIIB to IV patients (eighth AJCC) with non-small-cell lung cancer (NSCLC) patients. Patients will be enrolled in parallel sub-studies based on the results of NGS and PD-L1 IHC analysis. Patients who are not eligible for CTONG1702 will be enrolled in the observational real-world study CTONG1705. This study aims to develop a large-scale genomic database and explore the relationship between genetic variations in NSCLC patients and clinical outcomes.The adaptive umbrella trial will evaluate multi-targets and multi-drugs in advanced NSCLC patients (CTONG1702). In addition, the simultaneously initiated real-world study will provide additional data for clinical practice (CTONG1705).

RNA therapeutics is an emerging field that widens the range of treatable targets and would improve disease outcome through bypassing the antibiotic bactericidal targets to kill Mycobacterium tuberculosis (M.tb).We screened for microRNA with immune-regulatory functions against M.tb by next generation sequencing of peripheral blood mononuclear cells, followed by validation in an independent cohort.Twenty three differentially expressed microRNAs were identified between 12 active pulmonary TB patients and 4 healthy subjects, and 35 microRNAs before and after 6-month anti-TB therapy. Enriched predicted target pathways included proteoglycan, HIF-1 signaling, longevity-regulating, central carbon metabolism, and autophagy. We validated miR-431-3p down-regulation and miR-1303 up-regulation accompanied with corresponding changes in their predicted target genes in an independent validation cohort of 46 active TB patients, 30 latent TB infection subjects, and 24 non-infected healthy subjects. In vitro experiments of transfections with miR-431-3p mimic/miR-1303 short interfering RNA in THP-1 cells under ESAT-6 stimuli showed that miR-431-3p and miR-1303 were capable to augment and suppress autophagy/apoptosis/phagocytosis of macrophage via targeting MDR1/MMP16/RIPOR2 and ATG5, respectively.This study provides a proof of concept for microRNA-based host-directed immunotherapy for active TB disease. The combined miR-431-3p over-expression and miR-1303 knock-down revealed new vulnerabilities of treatment-refractory TB disease.

Metagenomic next-generation sequencing (mNGS) is increasingly used for the clinical diagnosis of infectious diseases, but there is a paucity of data regarding the application of mNGS in the early diagnosis of infected pancreatic necrosis (IPN).To investigate the clinical application value of mNGS in the pathogenic diagnosis of IPN.Forty-two patients with suspected IPN were prospectively and consecutively enrolled from August 2019 to August 2021. Blood samples were collected for mNGS and microbial culture simultaneously during fever (T ≥ 38.5 °C). For patients who had indications of surgical interventions, peri-pancreatic specimens were collected for mNGS and microbial culture simultaneously during the first surgical intervention to confirm IPN. The clinical performance of mNGS and microbial culture were compared.A total of 21 patients (50.0%) were confirmed to have IPN during hospitalization. The sensitivity of blood mNGS was significantly higher than blood culture (95.2% vs. 23.8%, P 0.001) in diagnosing IPN. The negative predictive value of blood mNGS was 90.0%. The turnaround time of mNGS was significantly shorter than that of microbial culture [(37.70 ± 1.44) vs. (115.23 ± 8.79) h, P 0.01] and the average costs of mNGS accounted for 1.7% of the average total cost of hospitalization. The survival analysis demonstrates that the positive blood mNGS result was not associated with increased mortality (P = 0.119).With more valuable diagnostic performance and shorter turnaround time, clinical mNGS represents a potential step forward in the early diagnosis of IPN.

Recent advances have led to the emergence of highly comprehensive and analytical approaches, such as omics analysis and high-resolution, time-resolved bioimaging analysis. These technologies have made it possible to obtain vast data from a single measurement. Subsequently, large datasets have pioneered the data-driven approach, an alternative to the traditional hypothesis-testing system, for researchers. However, processing, interpreting, and elucidating enormous datasets is no longer possible without computation. Bioinformatics is a field that has developed over long periods, intending to understand biological phenomena using methods collected from information science and statistics, thus solving this proposed research challenge. This review presents the latest methodologies and applications in sequencing, imaging, and mass spectrometry that were developed using bioinformatics. We presented the features of individual techniques and outlines in each part, avoiding the use of complex algorithms and formulas to allow beginning researchers to understand an overview. In the section on sequencing, we focused on comparative genomic, transcriptomic, and bacterial microbiome analyses, which are frequently used as applications of next-generation sequencing. Bioinformatic methods for handling sequence data and case studies were described. In the section on imaging, we introduced the analytical methods and microscopy imaging informatics techniques used in animal cell biology and plant physiology. We introduce informatics technologies for maximizing the value of measured data, including predicting the structure of unknown molecules and untargeted analysis in the section on mass spectrometry. Finally, we discuss the future outlook of this field. We anticipate that this review will assist biologists in using bioinformatics more effectively.

Placental dysfunction is one of the most common causes of Intrauterine Fetal Demise (IUFD). Due to its characteristics, the placenta may be the target of molecular research aimed to investigate potential causes of IUFD. In the literature, there are no studies on human placentas that have investigated possible associations between somatic mutations and the occurrence of IUFD. The aim of this study was to identify the presence of gene mutations in placental tissues in a series of cases of IUFD and to evaluate potential correlations with placental microscopic findings.Thirty-seven samples of formalin-fixed and paraffin-embedded placental tissues were retrospectively selected from pregnancies ending in IUFD between 23rd to 40th week. Six control placentas of physiological pregnancies were included as controls. After sampling, made according to standardized protocol and conventional histopathological examination, placental tissues were subjected to DNA extraction and sequencing by means of Next Generation Sequencing with a 56-gene panel.The most frequent mutation observed in 32/37 IUFD cases (86.5%) and absent in any of the 6 control placentas was in c-KIT gene, which is implicated in placental tissue differentiation. However, no significant correlation was found between the presence of individual gene mutations and placental histopatological findings.As the present study found an elevated frequency of c-KIT mutation in IUFD, it further supports the hypothesis that c-KIT is involved in abnormal tissue differentiation leading to altered placental vascularization and function.

Pancreatic cancer remains one of the most devastating malignancies due to the absence of techniques for early diagnosis and the lack of target therapeutic options for advanced disease. Next Generation Sequencing (NGS) generates high throughput and valuable genetic information when evaluating circulating tumor DNA (ctDNA); however clinical utility of liquid biopsy in pancreatic cancer has not been demonstrated yet. The aim of this study was to evaluate whether results from a Next Generation Sequencing panel on plasma samples from pancreatic cancer patients could have a clinical significance.From December 2016 to January 2020, plasma samples from 27 patients with pancreatic ductal adenocarcinoma at two different tertiary Spanish Hospitals underwent ctDNA testing using a commercial NGS panel of 65 genes. Clinical data were available for these patients. VarsSome Clinical software was used to analyse NGS data and establish pathogenicity.Evaluable NGS results were obtained in 18 out of the 27 plasma samples. Somatic pathogenic mutations were found mainly in KRAS, BRCA2, FLT3 and HNF1A, genes. Pathogenic mutations were detected in 50% of plasma samples from patient diagnosed at stages III-IV samples. FLT3 mutations were observed in 22.22% of samples which constitute a novel result in the field.Liquid biopsy using NGS is a valuable tool but still not sensitive or specific enough to provide clinical utility in pancreatic cancer patients.

Tumor purity, or the relative contribution of tumor cells out of all cells in a pathological specimen, influences mutation identification and clinical interpretation of cancer panel next generation sequencing results. Here, we describe a method of calculating tumor purity using pathologist-guided copy number analysis from sequencing data. Molecular calculation of tumor purity showed strong linear correlation with purity derived from driver KRAS or BRAF variant allele fractions in colorectal cancers (R

Thalassemia is one of the most common genetic diseases and a major health threat worldwide. Accurate, efficient, and scalable analysis of next-generation sequencing (NGS) data is much needed for its molecular diagnosis and carrier screening. We developed NGS4THAL, a bioinformatics analysis pipeline analyzing NGS data to detect pathogenic variants for thalassemia and other hemoglobinopathies. NGS4THAL realigns ambiguously mapped NGS reads derived from the homologous Hb gene clusters for accurate detection of point mutations and small insertions/deletions. It uses a combination of complementary structural variant (SV) detection tools and an in-house database of control data containing specific SVs to achieve accurate detection of the complex SV types. Detected variants are matched with those in HbVar (A Database of Human Hemoglobin Variants and Thalassemia Mutations), allowing recognition of known pathogenic variants, including disease modifiers. Tested on simulation data, NGS4THAL achieved high sensitivity and specificity. For targeted NGS sequencing data from samples with laboratory-confirmed pathogenic Hb variants, it achieved 100% detection accuracy. Application of NGS4THAL on whole genome sequencing data from unrelated studies revealed thalassemia mutation carrier rates for Hong Kong Chinese and Northern Vietnamese that were consistent with previous reports. NGS4THAL is a highly accurate and efficient molecular diagnosis tool for thalassemia and other hemoglobinopathies based on tailored analysis of NGS data and may be scaled for population carrier screening.

Recent advances in next-generation sequencing (NGS) have resulted in the identification of tens of thousands of rare pharmacogenetic variations with unknown functional effects. However, although such pharmacogenetic variations have been estimated to account for a considerable amount of the heritable variability in drug response and toxicity, accurate interpretation at the level of the individual patient remains challenging. We discuss emerging strategies and concepts to close this translational gap. We illustrate how massively parallel experimental assays, artificial intelligence (AI), and machine learning can synergize with population-scale biobank projects to facilitate the interpretation of NGS data to individualize clinical decision-making and personalized medicine.

Molecular testing is now considered the standard of care to screen for disease, confirm the diagnosis, guide management, and use target therapy. Currently, several testing strategies are being used. One of the most common strategies is single-gene testing, which is often conducted for known mutations, such as BRAF in melanoma and EGFR in lung cancer. Subsequently, next-generation sequencing (NGS), which tests many genes simultaneously, was developed using targeted gene panels, whole-exome, or whole-genome sequencing. Ordering the best diagnostic tool and choosing between single-gene testing and NGS depends on several factors. In this review, we discuss different single-gene testing methodologies and the impact of using them in comparison to NGS/multigene panel.

Trigeminal neuropathic pain (TNP) arises due to peripheral nerve injury, the mechanisms underlying which are little known. The altered gene expression profile in sensory ganglia is critical for neuropathic pain generation and maintenance. We, therefore, assessed the transcriptome of the trigeminal ganglion (TG) from mice at different periods of pain progression. Trigeminal neuropathic pain was established by partial infraorbital nerve transection (pIONT). High-throughput RNA sequencing was applied to detect the mRNA profiles of TG collected at 3 and 10 days after modeling. Injured TG displayed dramatically altered mRNA expression profiles compared to Sham. Different gene expression profiles were obtained at 3 and 10 days after pIONT. Moreover, 314 genes were significantly upregulated, and 81 were significantly downregulated at both 3 and 10 days post-pIONT. Meanwhile, enrichment analysis of these persistent differentially expressed genes (DEGs) showed that the MAPK pathway was the most significantly enriched pathway for upregulated DEGs, validated by immunostaining. In addition, TG cell populations defined by single-nuclei RNA sequencing displayed cellular localization of DEGs at a single-cell resolution. Protein-protein interaction (PPI) and sub-PPI network analyses constructed networks and identified the top 10 hub genes for DEGs at different time points. The present data provide novel information on the gene expression signatures of TG during the development and maintenance phases of TNP, and the identified hub genes and pathways may serve as potential targets for treatment.

Cancer is characterized by an extremely complex biological background, which hinders personalized therapeutic interventions. Precision medicine promises to overcome this obstacle through integrating information from different ‘subsystems’, including the host, the external environment, the tumor itself and the tumor micro-environment. Immunogenetics is an essential tool that allows dissecting both lymphoid cancer ontogeny at both a cell-intrinsic and a cell-extrinsic level, i.e. through characterizing micro-environmental interactions, with a view to precision medicine. This is particularly thanks to the introduction of powerful, high-throughput approaches i.e. next generation sequencing, which allow the comprehensive characterization of immune repertoires. Indeed, NGS immunogenetic analysis (Immune-seq) has emerged as key to both understanding cancer pathogenesis and improving the accuracy of clinical decision making in oncology. Immune-seq has applications in lymphoid malignancies, assisting in the diagnosis e.g. through differentiating from reactive conditions, as well as in disease monitoring through accurate assessment of minimal residual disease. Moreover, Immune-seq facilitates the study of T cell receptor clonal dynamics in critical clinical contexts, including transplantation as well as innovative immunotherapy for solid cancers. The clinical utility of Immune-seq represents the focus of the present contribution, where we highlight what can be achieved but also what must be addressed in order to maximally realize the promise of Immune-seq in precision medicine in cancer.

This study aimed to evaluate the clinical value of metagenomic next-generation sequencing (mNGS) in patients with suspected lower respiratory tract infections.This retrospective study reviewed patients with suspected lower respiratory tract infections at the Wuhan Union Hospital. Data including demographic, laboratory, and radiological profiles; treatment; and outcomes were recorded and analyzed.mNGS identified pathogenic microbes in 100/140 (71.4%) patients, although 135 (96.4%) had received empiric antibiotic treatment before the mNGS tests. Single bacterial infection (35/100, 35%) was the most common type of infection in patients with positive mNGS results, followed by single fungal infection (14/100, 14%), bacterial-viral coinfection (14/100, 14%), single viral infection (12/100, 12%), bacterial-fungal coinfection (9/100, 9%), fungal-viral coinfection (9/100, 9%), and bacterial-fungal-viral coinfection (7/100, 7%). Moreover, compared with culture test, mNGS showed higher sensitivity (63/85, 74.1% vs 22/85, 25.9% P = 0.001) and lower processing time (24 hours vs 48 hours). Antibiotic treatment was adjusted or confirmed based on the mNGS results in 123 (87.9%) patients, including five (3.6%), 33 (23.6%), and 85 (60.7%) patients, in whom treatment was downgraded, upgraded, and unchanged, respectively. Almost all patients, regardless of escalation, de-escalation, or no change in treatment, showed significant improvement in clinical symptoms and inflammatory indicators. In addition, 17 (12.1%) patients were referred to Wuhan Pulmonary Hospital for further treatment because of confirmed or suspected tuberculosis.mNGS could be a promising technique for microbiological diagnosis and antibiotic management, potentially improving outcomes for patients.

Because the clinical impact of cancer genomics is being increasingly recognized, tumor sequencing will likely continue to expand in breadth and scope. Therefore, it is vital for laboratory professionals to adopt the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists guidelines and create a standardized system of classification and nomenclature for somatic variants. Combining robust bioinformatics pipelines with thorough data analysis is necessary to efficiently and reproducibly identify and assess the impact of clinically relevant variants.

This article covers analytical principles of cancer next generation sequencing (NGS). Cancer samples require special considerations due to the cancer-specific applications of testing, as well as cancer sample specific issues, including low input, low tumor purity, or fixation-related artifacts. Laboratories typically use a combination of approaches around specimen processing, assay design, and bioinformatics analysis to allow for successful detection of actionable biomarkers. Examples of these approaches for cancer NGS testing are discussed and reviewed here.

Understanding the genetic basis of human diseases and traits is dependent on the identification and accurate genotyping of genetic variants. Deep whole-genome sequencing (WGS), the gold standard technology for SNP and indel identification and genotyping, remains very expensive for most large studies. Here, we quantify the extent to which array genotyping followed by genotype imputation can approximate WGS in studies of individuals of African, Hispanic/Latino, and European ancestry in the US and of Finnish ancestry in Finland (a population isolate). For each study, we performed genotype imputation by using the genetic variants present on the Illumina Core, OmniExpress, MEGA, and Omni 2.5M arrays with the 1000G, HRC, and TOPMed imputation reference panels. Using the Omni 2.5M array and the TOPMed panel, ≥90% of bi-allelic single-nucleotide variants (SNVs) are well imputed (r(2) > 0.8) down to minor-allele frequencies (MAFs) of 0.14% in African, 0.11% in Hispanic/Latino, 0.35% in European, and 0.85% in Finnish ancestries. There was little difference in TOPMed-based imputation quality among the arrays with >700k variants. Individual-level imputation quality varied widely between and within the three US studies. Imputation quality also varied across genomic regions, producing regions where even common (MAF > 5%) variants were consistently not well imputed across ancestries. The extent to which array genotyping and imputation can approximate WGS therefore depends on reference panel, genotype array, sample ancestry, and genomic location. Imputation quality by variant or genomic region can be queried with our new tool, RsqBrowser, now deployed on the Michigan Imputation Server.

Can preimplantation genetic testing for structural rearrangement (PGT-SR) based on low-coverage next-generation sequencing (NGS) accurately discriminate between normal and carrier embryos of reciprocal translocation (RecT) and Robertsonian translocation (RobT)?A total of 109 couples with RecT or RobT were included in this study. The ages, bad obsteric histories (BOH), blood karyotype and IVF cycle information, including the number of cumulus-oocyte complexes, metaphase II oocytes, two pronuclei oocytes and blastocysts were recorded. 0.1 × whole genome sequencing (WGS) of embryos followed by copy number variation (identifying unbalanced/balanced) and 2 × WGS of parents and embryos followed by haplotype analysis (discriminating between normal and carrier) were carried out in PGT-SR cycles. The embryos without translocation were transferred and clinical outcomes evaluated.Among all the couples in this study, 67 patients had RecT and 42 had RobT. After unbalanced and balanced detection, 103 balanced embryos underwent a further normal and carrier discrimination procedure, and 53 normal embryos were identified. Finally, 32 normal embryos were transferred, with an ongoing pregnancy rate of 46.88% (15/32). All ongoing pregnancies underwent amniocentesis, and the amninocentesis karyotyping results showed 100% concordance with PGT-SR diagnosis.Our low-coverage NGS-based PGT-SR method can accurately discriminate between normal and carrier status of balanced embryos. The method is cost-effective and has broad clinical applicability.

Rationale In 2016, Belgium launched the Next Generation Sequencing (NGS) Roadbook, consisting in 10 Actions, across the health care system, to facilitate the uptake of NGS in routine clinical practice. We compiled feedback on deployment of the NGS Roadbook from governmental stakeholders and beneficiaries: health policy makers, insurance providers, pathologists, geneticists, and oncologists. Main findings The Roadbook ensured the establishment of a Commission on Personalized Medicine and NGS testing guidelines. A national benchmarking trial ensued, and 10 networks of hospitals and laboratories adopted a reimbursement convention with the Belgian Health Insurance Agency. The Healthdata.be platform centralizes the collection of NGS metrics, and citizens were consulted on their views about NGS and genomics. Conclusion The Roadbook facilitated the implementation of NGS in routine (hemato-)oncology care in Belgium. Some challenges remain linked to data sharing and access by a wider range of stakeholders. Next steps include continuous monitoring of health outcomes and the budgetary impact.

Identifying pathogens in patients with pulmonary infection (PI) has always been a major challenge in medicine. Compared with sputum and throat swabs, bronchoalveolar lavage fluid (BALF) can better reflect the actual state of the lungs. However, there has not been a meta-analysis of the diagnostic efficacy of metagenomic next-generation sequencing (mNGS) in detecting pathogens in BALF from patients with PIs.Data sources were PubMed, Web of Science, Embase, and the China National Knowledge Infrastructure. The pooled sensitivity and specificity were estimated using random-effects or fixed-effect models. Subgroup analysis was performed to reveal the effect of potential explanatory factors on the diagnostic performance measures.The pooled sensitivity was 78% (95% confidence interval [CI]: 67-87%; ImNGS has high diagnostic performance for BALF pathogens in patients with PIs, especially in critically ill or immunocompromised patients.

Mosaicism results from postzygotic alterations during embryogenesis leading to genetically distinct populations of cells within individuals and has been historically recognized by phenotypes with visible, often patterned manifestations. Before the advent of molecular profiling assays and high-throughput sequencing, it was challenging to study mosaicism in human disease; however, the study of mosaic disorders has recently revealed unexpected and novel pathways for disease pathogenesis. In this paper, we will review the techniques for discovery of disease-causing alleles using Proteus syndrome; phakomatosis pigmentokeratotica; linear porokeratosis; and vacuoles, E1 enzyme, X-linked, autoinflammatory somatic syndrome as models. These tools represent powerful approaches for dissecting the genetic basis for human disorders.

High-throughput molecular profiling of tumors is a fundamental aspect of precision oncology, enabling the identification of genomic alterations that can be targeted therapeutically. In this context, a patient is matched to a specific drug or therapy based on the tumor's underlying genetic driver events rather than the histologic classification. This approach requires extensive bioinformatics methodology and workflows, including raw sequencing data processing and quality control, variant calling and annotation, integration of different molecular data types, visualization and finally reporting the data to physicians, cancer researchers and pharmacologists in a format that is readily interpretable for clinical decision making. This review comprises a broad overview of these bioinformatics aspects and discusses the multiple analytical, technical and interpretational challenges that remain to efficiently translate molecular findings into personalized treatment recommendations.

To identify dysregulated microRNAs (miRNAs) derived from urinary small Extracellular Vesicles (sEVs) and to explore the potential roles sEVs miRNAs play in nephrolithiasis.First morning voids were collected from participants. Urinary exosomes were isolated via sequential differential centrifugation and ultracentrifugation. Next-generation sequencing was conducted to analyze the transcriptome of urine sEVs from three Calcium oxalate (CaOx) stone patients and three age-/sex-matched healthy controls. Bioinformatics analysis was performed to explore how dysregulated miRNAs were associated with stone formation. The miRNA sequencing results of sEVs derived from epithelial cells (GSE110509) were compared with the dysregulated miRNAs of our study, and finally we found three common miRNAs.54 dysregulated miRNAs were found between control and stone groups, among which 14 miRNAs were down-regulated and 40 miRNAs were up-regulated in stone groups compared to control groups. Gene ontology (GO) analysis indicated that dysregulated miRNAs were enriched in oxidative stress (Biological Process), focal adhesion (Cellular Component), and cell adhesion molecule binding (Molecular Function). Kyoto Encyclopedia of Genes and Genomes pathways analysis demonstrated that dysregulated miRNAs were common enriched in MAPK signaling pathway, focal adhesion and AGE-RAGE signaling pathway. The expression of miR-223-3p, miR-127-3p, and miR-214-5p were significantly different in either the sEVs derived from cells (GSE110509) or the sEVs derived from urine. QPCR confirmed that the expression of miR-223-3p was higher in urinary sEVs derived from CaOx stone patients.The expression of miR-223-3p is significantly higher in urinary sEVs derived from CaOx stone patients and may affect stone formation via regulating oxidative stress, focal adhesion and inflammation process.

The study aimed to determine the diagnostic yield, optimal timing, and methodology of next generation sequencing data reanalysis in suspected Mendelian disorders.We conducted a systematic review and meta-analysis of studies that conducted data reanalysis in patients with suspected Mendelian disorders. Random effects model was used to pool the estimated outcome with subgroup analysis stratified by timing, sequencing methodology, sample size, segregation, use of research validation, and artificial intelligence (AI) variant curation tools.A search of PubMed, Embase, Scopus, and Web of Science between 2007 and 2021 yielded 9327 articles, of which 29 were selected. Significant heterogeneity was noted between studies. Reanalysis had an overall diagnostic yield of 0.10 (95% CI = 0.06-0.13). Literature updates accounted for most new diagnoses. Diagnostic yield was higher after 24 months, although this was not statistically significant. Increased diagnoses were obtained with research validation and data sharing. AI-based tools did not adversely affect reanalysis diagnostic rate.Next generation sequencing data reanalysis can improve diagnostic yield. Owing to the heterogeneity of the studies, the optimal time to reanalysis and the impact of AI-based tools could not be determined with confidence. We propose standardized guidelines for future studies to reduce heterogeneity and improve the quality of the conclusions.

Accurate human leucocyte antigen (HLA) typing is essential for solid organ transplantation (SOT) and hematopoietic stem cell transplantation (HSCT). Next-generation sequencing (NGS) is increasingly adopted by clinical laboratories performing HLA typing. To ensure reliable NGS-based HLA typing throughout China, a HLA-NGS proficiency testing (PT) scheme was set up.A panel of 10 DNA reference materials for 11 HLA loci were distributed to 24 participants. They were asked to submit NGS typing results for at least six loci including HLA-A, HLA-B, HLA-C, HLA-DRB1, HLA-DQB1, and HLA-DPB1. Information regarding individual laboratory's sample preparation method, NGS platform, and genotyping software was also collected.Thirteen participants correctly identified HLA alleles in all samples. The total concordance rate for all HLA alleles typed was 99.2% (3390/3420). The overall discordance was 0.2% (3/1440) for Class I, and 1.4% (27/1980) for Class II loci. Further investigation of the typing mistakes pointed to poor sequencing coverage and wrong allele calls. The errors identified reflect the deficient aspect of NGS in HLA typing, which may have implications for quality improvement for relevant laboratories.The results of this PT underscore the necessity of regular participation in external quality assessment for clinical laboratories that perform HLA-NGS typing.

Infectious hypodermal and haematopoietic necrosis virus (IHHNV) is the smallest known virus in shrimp, which causes runt-deformity syndrome (RDS) and leads to huge economic loss every year in penaeid shrimp farming. Previous studies have shown that the juvenile Penaeus vannamei is more susceptible to IHHNV infection than the adults, but the mechanism is still unclear. In order to investigate the mechanism of pathogenic differences in IHHNV infection of P. vannamei at different developmental stages, the juvenile and adult P. vannamei were studied by transcriptome high-throughput sequencing to analyze their response to IHHNV infection. GO and KEGG enrichment were analyzed to search for differentially expressed genes (DEGs) related to immunity, growth and metabolism. The results showed that many immune-related genes of the juvenile and adult P. vannamei responded differently to IHHNV infection. For the adult P. vannamei, the expression of most immune-related genes was significantly up-regulated, which means that a cellular defense response was triggered after IHHNV infection. However, most immune-related genes in juvenile P. vannamei were inhibited, indicating that the immune system of juvenile the P. vannamei is imperfect and makes it to be more susceptible to IHHNV. Similarly, the growth-related genes of P. vannamei were changed during IHHNV infection. For the juvenile P. vannamei, the growth-related genes were significantly down-regulated, which resulted in a growth hormone disorder and prevented the juvenile P. vannamei from growth. In the adult P. vannamei, most molting-related genes were significantly up-regulated, indicating that IHHNV infection leads the adult P. vannamei to early molting to eliminate pathogen in the body. Metabolic process data showed that energy metabolism pathway was affected when P. vannamei infected with IHHNV. The adult P. vannamei infected with IHHNV can cause energetically costly and lead to the disturbance of the metabolism, activate complex immune systems to resist the invasion of pathogens. The results of this study clarified the response mechanism of P. vannamei at different developmental stages to IHHNV infection, which can provide new insights to IHHNV effective control and a reference for the study of sensitive period of different shrimp virus to host infection.

The purpose of this study is to investigate whether the mitochondrial DNA (mtDNA) content can reflect the state of mosaic embryos.The study included 1669 blastocysts derived from 394 PGT-A cycles between January 2018 and December 2020, in which preimplantation genetic testing for aneuploidy was performed and mtDNA content was determined. The standard deviation (SD) of whole genomic sequencing data was calculated for quality control. mtDNA content was measured as the proportion of mtDNA to genomic DNA. 1558 blastocysts with SD values less than 4.0 and mtDNA values less than 0.4% were selected for statistical analysis.The mtDNA content of the PGT mosaic group was significantly higher than that of the PGT normal group (P 0.001). Twenty-six mosaic embryos were transferred, and the results were as follows: 2 out of 26 had undergone a spontaneous miscarriage, 15 were not pregnant, and 9 resulted in a live birth. There were significant differences in the mtDNA content between the miscarriage/non-pregnancy group and the live birth group (**P 0.01; ***P 0.001). There was no mosaic embryo with more than 0.157% mtDNA content found in the live birth group.This study demonstrates that mtDNA analysis has the ability to identify mosaic embryos with high developmental potential. It can be a valuable supplementary index for the selection of mosaic embryos for transfer. Larger studies with a greater sample size will further our understanding of the relationships between metabolic activity and mosaicism.

This study evaluated two DNA-based next-generation sequencing approaches for detection of single-nucleotide variants (SNVs) and fusions in formalin-fixed, paraffin-embedded (FFPE) tissue specimens and liquid biopsies (AVENIO Targeted and Surveillance Panels). Reference standards (n = 7 with SNVs and structural variants) and real-world FFPE tissue specimens (n = 26 lung, colorectal, pancreas, ovary, breast, prostate, melanoma, and soft tissue cancer cases with n = 27 samples), liquid biopsies [n = 29 cases with n = 40 plasma/cell-free DNA (cfDNA) samples], and one pleural effusion (lung cancer) were analyzed by the AVENIO workflow for known SNVs (BRAF, BRCA1/2, CTNNB1, EGFR, KRAS, MET exon 14 skipping, NRAS, PIK3CA, and TP53), insertions and deletions (ERBB2 and KIT), and fusions (ALK and ROS1). Detection of SNVs, insertions and deletions, and fusions was reliable in 24 of 26 FFPE tissue specimen cases and at 1% allele frequency in 5 of 5 cfDNA reference standards and 37 of 40 plasma/cfDNA samples. Pitfalls were identified for the AVENIO workflow in calling and listing of clinically relevant variants, requiring additional manual inspection. Moreover, laboratory workflows are distinct for FFPE tissue specimens and liquid biopsies as well as time-consuming for sample quality control assays. In summary, the DNA-based next-generation sequencing approaches may be suitable for routine molecular pathology diagnostics on careful data interpretation and further optimization of the technical and laboratory workflows.

To date, over 150 different RNA modifications have been identified, playing crucial roles in biological processes and disease pathogenesis. Thanks to the advancement of high-throughput sequencing technologies employed for transcriptome-wide mapping, a bunch of RNA modification databases have emerged as an exciting area, which promotes further investigation of the mechanisms and functions of these modified ribonucleotides. This article introduces the high-throughput sequencing technique developed for transcriptome-wide mapping of RNA modifications, as well as the procedures and main techniques of building these databases from the developers' perspective. It also reviews existing RNA modification databases in terms of their main functions, species, the number of sites they collected, the annotations, and the tools they provided. From the view of users, we further analyze and compare these databases in terms of their functions. For instance, these databases can be applied to record chemical structures and biosynthetic pathways, or unravel the epi-transcriptome comprehensively, or only investigate specific features of RNA modifications. Additionally, the limitations of the existing approaches are discussed, and some future suggestions are offered.

BackgroundThe prevalence, association with disease status, and public health impact of infection with mixtures of M. tuberculosis strains is unclear, in part due to limitations of existing methods for detecting mixed infections.MethodsWe developed an algorithm to identify mixtures of M. tuberculosis strains using next generation sequencing data, assessing performance using simulated sequences. We identified mixed M. tuberculosis strains when there was at least one mixed nucleotide position, and where both the mixture’s components were present in similar isolates from other individuals. We determined risk factors for mixed infection among isolations of M. tuberculosis in England using logistic regression. We used survival analyses to assess the association between mixed infection and putative transmission.Findings6,560 isolations of TB were successfully sequenced in England 2016-2018. Of 3,691 (56%) specimens for which similar sequences had been isolated from at least two other individuals, 341 (9.2%) were mixed. Infection with lineages other than Lineage 4 were associated with mixed infection. Among the 1,823 individuals with pulmonary infection with Lineage 4 M. tuberculosis, mixed infection was associated with significantly increased risk of subsequent isolation of closely related organisms from a different individual (HR 1.43, 95% CI 1.05,1.94), indicative of transmission.InterpretationMixtures of transmissible strains occur in at least 5% of tuberculosis infections in England; when present in pulmonary disease, such mixtures are associated with an increased risk of tuberculosis transmission.FundingPublic Health England; NIHR Health Protection Research Unit Oxford; European Union.Research in ContextEvidence Before This StudyWe searched Pubmed using the search terms ‘tuberculosis’ and ‘mixed’ or ‘mixture’ for English Language articles published up to 1 April 2019. Studies, most performed without the benefit of genomic sequencing, report mixed TB infection from a range of medium and high prevalence areas and show it to be associated with delayed treatment response. Modelling suggests detection and treatment of mixed TB infection is an important goal for TB eradication campaigns. Although routine DNA sequencing of M. tuberculosis isolates is becoming widespread, efficient methods for detecting mixed infection from such data are underdeveloped, and the true prevalence of mixed infection and its association with transmission is unclear.Added Value of This StudyThis study investigated a large series of TB isolations obtained as part of a routine Mycobacterial sequencing program by two reference laboratories, in a low incidence area, England. We developed an efficient generalisable approach to identify transmitted mixed M. tuberculosis infection; our approach is capable of sensitive and specific detection of a single mixed nucleotide position. We identified mixed infection of similar strains (‘microvariation’) in about 9.2% of the M. tuberculosis samples which we were able to assess, and found evidence of increased transmission from individuals with mixed infection.Implications of All the Available EvidenceTB microvariation is a risk factor for TB transmission, even in the low incidence area studied. Although an efficient and highly specific technique identifying microvariation exists, it relies on comparison with similar sequences isolated from other patients. Sharing of sequence data from the many TB sequencing programs being deployed globally will increase the sensitivity of microvariation detection, and may assist targeted public health interventions.

Hepatocarcinogenesis involves complex genetic and cellular dysregulations which drive the formation of hepatocellular carcinoma (HCC), the predominant form of primary liver cancer, with extensive heterogeneity. In contrast to the broad spectrum of molecularly driven therapies available for defined patient groups in certain cancer types, unfortunately the treatment options for HCC are highly limited. The lack of representative molecular and cellular signatures in the heterogeneous HCC tumors that can effectively guide the choice of the most appropriate treatment among the patients unavoidably limits the treatment outcome. Advancement and wide availability of the next-generation sequencing technologies have empowered us to examine and capture not only the detailed genetic alterations of the HCC cells but also the precise composition of different cell types within the tumor microenvironment and their interactions with the HCC cells at an unprecedented level. The information generated has provided new insight and better defined the inter-patient intertumoral heterogeneity, intra-patient intratumoral heterogeneity as well as the plasticity of HCC cells. These collectively provide a robust scientific basis in guiding the development and use of targeted therapy and immunotherapy. To complement, liquid biopsy coupled with high-sensitivity sequencing could potentially be adopted as a more practical and safer approach to detect and reflect the tumor heterogeneity in HCC patients in guiding the choice of treatment and monitoring disease progression.

Mutation detection is increasingly used for the management of hematological malignancies. Prior whole transcriptome and whole exome sequencing studies using total RNA and DNA identified diverse mu-tation types in cancer-related genes associated with treatment failure in patients with chronic myeloid leukemia. Variants included single-nucleotide variants and small insertions/deletions, plus fusion transcripts and partial or whole gene deletions. The hypothesis that all of these mutation types could be detected by a single cost-effective hybridization capture next-generation sequencing method using total RNA was assessed. A method was developed that targeted 130 genes relevant for myeloid and lymphoid leukemia. Retrospective samples with 121 precharacterized variants were tested using total RNA and/or DNA. Concordance of detection of precharacterized variants using RNA or DNA was 96%, whereas the enhanced sensitivity identified additional variants. Comparison between 24 matched DNA and RNA samples demonstrated 95.3% of 170 variants detectable using DNA were detected using RNA, including all but one variant predicted to activate nonsense-mediated decay. RNA identified an addi-tional 10 variants, including fusion transcripts. Furthermore, the true effect of splice variants on RNA splicing was only evident using RNA. In conclusion, capture sequencing using total RNA alone is suitable for detecting a range of variants relevant in chronic myeloid leukemia and may be more broadly applied to other hematological malignancies where diverse variant types define risk groups. Refereed/Peer-reviewed

Somatic copy number alterations (SCNAs) in tumors are clinically significant diagnostic, prognostic, and predictive biomarkers. SCNA detection from targeted next-generation sequencing panels is increasingly common in clinical practice; however, detailed descriptions of optimization and validation of SCNA pipelines for small targeted panels are limited. This study describes the validation and implementation of a tumor-only SCNA pipeline using CNVkit, augmented with custom modules and optimized for clinical implementation by testing reference materials and clinical tumor samples with different classes of copy number variation (CNV; amplification, single copy loss, and biallelic loss). Using wet-bench and in silico methods, various parameters impacting CNV calling, including assay-intrinsic variables (establishment of normal reference and sequencing coverage), sample-intrinsic variables (tumor purity and sample quality), and CNV algorithm-intrinsic variables (bin size), were optimized. The pipeline was trained and tested on an optimization cohort and validated using an independent cohort with a sensitivity and specificity of 100% and 93%, respectively. Using custom modules, intragenic CNVs with breakpoints within tumor suppressor genes were uncovered. Using the validated pipeline, re-analysis of 28 pediatric solid tumors that had been previously profiled for mutations identified SCNAs in 86% (24/28) samples, with 46% (13/28) samples harboring findings of potential clinical relevance. Our report highlights the importance of rigorous establishment of performance characteristics of SCNA pipelines and presents a detailed validation framework for optimal SCNA detection in targeted sequencing panels.

We analyzed 131 human brains (44 neurotypical, 19 with Tourette syndrome, 9 with schizophrenia, and 59 with autism) for somatic mutations after whole genome sequencing to over 200X depth. Typically, brains had 20 to 60 detectable single nucleotide mutations but ~6% of brains harbored hundreds of somatic mutations. Hypermutability was associated with age and damaging mutations in genes implicated in cancers and in some brains reflected in vivo clonal expansions. Somatic duplications, likely arising during development, were found in ~5% of normal and diseased brains, reflecting background mutagenesis. Brains with autism were associated with mutations creating putative transcription factor binding motifs in enhancer-like regions in the developing brain. The top-ranked affected motifs corresponded to MEIS transcription factors, suggesting a potential link between their involvement in gene regulation and autism.

Cell-free (cf)DNA-based testing has undergone increasingly wide adoption, including assays for the detection of circulating tumor DNA. Due to nucleosome protection, cfDNA has a distinctive fragment size of 160 to 180 bp. However, cfDNA can be contaminated with high molecular weight genomic DNA from blood cells released in plasma during sample collection. Such contamination can lead to decreased sensitivity or inconsistent results in cfDNA next-generation sequencing assays. This article describes a technical advancement in which a quantitative PCR method is used for high molecular weight contamination assessment and input mass adjustment, and has been demonstrated to improve consistency of performance in a circulating tumor DNA next-generation sequencing workflow.

This study aimed to provide comprehensive diagnostic and candidate analyses in a pediatric rare disease cohort through the Genomic Answers for Kids program.Extensive analyses of 960 families with suspected genetic disorders included short-read exome sequencing and short-read genome sequencing (srGS); PacBio HiFi long-read genome sequencing (HiFi-GS); variant calling for single nucleotide variants (SNV), structural variant (SV), and repeat variants; and machine-learning variant prioritization. Structured phenotypes, prioritized variants, and pedigrees were stored in PhenoTips database, with data sharing through controlled access the database of Genotypes and Phenotypes.Diagnostic rates ranged from 11% in patients with prior negative genetic testing to 34.5% in naive patients. Incorporating SVs from genome sequencing added up to 13% of new diagnoses in previously unsolved cases. HiFi-GS yielded increased discovery rate with4-fold more rare coding SVs compared with srGS. Variants and genes of unknown significance remain the most common finding (58% of nondiagnostic cases).Computational prioritization is efficient for diagnostic SNVs. Thorough identification of non-SNVs remains challenging and is partly mitigated using HiFi-GS sequencing. Importantly, community research is supported by sharing real-time data to accelerate gene validation and by providing HiFi variant (SNV/SV) resources from1000 human alleles to facilitate implementation of new sequencing platforms for rare disease diagnoses.