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Tandem repeats are frequent across the human genome, and variation in repeat length has been linked to a variety of traits. Recent improvements in long read sequencing technologies have the potential to greatly improve tandem repeat analysis, especially for long or complex repeats. Here, we introduce LongTR, which accurately genotypes tandem repeats from high-fidelity long reads available from both PacBio and Oxford Nanopore Technologies. LongTR is freely available at https://github.com/gymrek-lab/longtr and https://zenodo.org/doi/10.5281/zenodo.11403979 .

BACKGROUND: Infectious conjunctivitis is common in Nepal. MATERIALS AND METHODS: This prospective study recruited 60 patients with presumed acute infectious conjunctivitis from the B.P. Koirala Lions Center for Ophthalmic Studies in Kathmandu, Nepal. Swabs from the conjunctiva and anterior nares were processed for metagenomic RNA deep sequencing (RNA-seq). RESULTS: Pathogens were identified in 55% of cases. RNA viruses were the most common pathogen class identified. Severe acute respiratory syndrome coronavirus 2 was the most common RNA virus identified. CONCLUSIONS: Acute infectious conjunctivitis varies by location. Contrary to expectations, RNA viruses predominated. Repeat surveillance may be useful and RNA-seq allows for detection of the unexpected pathogen including RNA viruses.

Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the performance of eight scATAC-seq methods across 47 experiments using human peripheral blood mononuclear cells (PBMCs) as a reference sample and develop PUMATAC, a universal preprocessing pipeline, to handle the various sequencing data formats. Our analyses reveal significant differences in sequencing library complexity and tagmentation specificity, which impact cell-type annotation, genotype demultiplexing, peak calling, differential region accessibility and transcription factor motif enrichment. Our findings underscore the importance of sample extraction, method selection, data processing and total cost of experiments, offering valuable guidance for future research. Finally, our data and analysis pipeline encompasses 169,000 PBMC scATAC-seq profiles and a best practices code repository for scATAC-seq data analysis, which are freely available to extend this benchmarking effort to future protocols.

Whitebark pine (WBP, Pinus albicaulis) is a white pine of subalpine regions in the Western contiguous United States and Canada. WBP has become critically threatened throughout a significant part of its natural range due to mortality from the introduced fungal pathogen white pine blister rust (WPBR, Cronartium ribicola) and additional threats from mountain pine beetle (Dendroctonus ponderosae), wildfire, and maladaptation due to changing climate. Vast acreages of WBP have suffered nearly complete mortality. Genomic technologies can contribute to a faster, more cost-effective approach to the traditional practices of identifying disease-resistant, climate-adapted seed sources for restoration. With deep-coverage Illumina short reads of haploid megagametophyte tissue and Oxford Nanopore long reads of diploid needle tissue, followed by a hybrid, multistep assembly approach, we produced a final assembly containing 27.6 Gb of sequence in 92,740 contigs (N50 537,007 bp) and 34,716 scaffolds (N50 2.0 Gb). Approximately 87.2% (24.0 Gb) of total sequence was placed on the 12 WBP chromosomes. Annotation yielded 25,362 protein-coding genes, and over 77% of the genome was characterized as repeats. WBP has demonstrated the greatest variation in resistance to WPBR among the North American white pines. Candidate genes for quantitative resistance include disease resistance genes known as nucleotide-binding leucine-rich repeat receptors (NLRs). A combination of protein domain alignments and direct genome scanning was employed to fully describe the 3 subclasses of NLRs. Our high-quality reference sequence and annotation provide a marked improvement in NLR identification compared to previous assessments that leveraged de novo-assembled transcriptomes.

Myelodysplastic neoplasm (MDS) is a heterogeneous group of clonal hematological disorders that originate from the hematopoietic and progenitor cells and present with cytopenias and morphologic dysplasia with a propensity to progress to bone marrow failure or acute myeloid leukemia (AML). Genetic evolution plays a critical role in the pathogenesis, progression, and clinical outcomes of MDS. This process involves the acquisition of genetic mutations in stem cells that confer a selective growth advantage, leading to clonal expansion and the eventual development of MDS. With the advent of next-generation sequencing (NGS) assays, an increasing number of molecular aberrations have been discovered in recent years. The knowledge of molecular events in MDS has led to an improved understanding of the disease process, including the evolution of the disease and prognosis, and has paved the way for targeted therapy. The 2022 World Health Organization (WHO) Classification and the International Consensus Classification (ICC) have incorporated the molecular signature into the classification system for MDS. In addition, specific germline mutations are associated with MDS development, especially in pediatrics and young adults. This article reviews the genetic abnormalities of MDS in adults with a brief review of germline predisposition syndromes.

In the human genome, heterozygous sites refer to genomic positions with a different allele or nucleotide variant on the maternal and paternal chromosomes. Resolving these allelic differences by chromosomal copy, also known as phasing, is achievable on a short-read sequencer when using a library preparation method that captures long-range genomic information. TELL-Seq is a library preparation that captures long-range genomic information with the aid of molecular identifiers (barcodes). The same barcode is used to tag the reads derived from the same long DNA fragment within a range of up to 200 kilobases (kb), generating linked-reads. This strategy can be used to phase an entire genome. Here, we introduce a TELL-Seq protocol developed for targeted applications, enabling the phasing of enriched loci of varying sizes, purity levels, and heterozygosity. To validate this protocol, we phased 2-200 kb loci enriched with different methods: CRISPR/Cas9-mediated excision coupled with pulse-field electrophoresis for the longest fragments, CRISPR/Cas9-mediated protection from exonuclease digestion for mid-size fragments, and long PCR for the shortest fragments. All selected loci have known clinical relevance: BRCA1, BRCA2, MLH1, MSH2, MSH6, APC, PMS2, SCN5A-SCN10A, and PKI3CA. Collectively, the analyses show that TELL-Seq can accurately phase 2-200 kb targets using a short-read sequencer.

Pangenome references address biases of reference genomes by storing a representative set of diverse haplotypes and their alignment, usually as a graph. Alternate alleles determined by variant callers can be used to construct pangenome graphs, but advances in long-read sequencing are leading to widely available, high-quality phased assemblies. Constructing a pangenome graph directly from assemblies, as opposed to variant calls, leverages the graph's ability to represent variation at different scales. Here we present the Minigraph-Cactus pangenome pipeline, which creates pangenomes directly from whole-genome alignments, and demonstrate its ability to scale to 90 human haplotypes from the Human Pangenome Reference Consortium. The method builds graphs containing all forms of genetic variation while allowing use of current mapping and genotyping tools. We measure the effect of the quality and completeness of reference genomes used for analysis within the pangenomes and show that using the CHM13 reference from the Telomere-to-Telomere Consortium improves the accuracy of our methods. We also demonstrate construction of a Drosophila melanogaster pangenome.

Penstemon is the most speciose flowering plant genus endemic to North America. Penstemon species diverse morphology and adaptation to various environments have made them a valuable model system for studying evolution. Here, we report the first full reference genome assembly and annotation for Penstemon davidsonii. Using PacBio long-read sequencing and Hi-C scaffolding technology, we constructed a de novo reference genome of 437,568,744 bases, with a contig N50 of 40 Mb and L50 of 5. The annotation includes 18,199 gene models, and both the genome and transcriptome assembly contain over 95% complete eudicot BUSCOs. This genome assembly will serve as a valuable reference for studying the evolutionary history and genetic diversity of the Penstemon genus.

The maintenance of DNA sequence integrity is critical to avoid accumulation of cancer-causing mutations. Inactivation of DNA Mismatch Repair (MMR) genes (e.g., MLH1 and MSH2) is common among many cancers, including colorectal cancer (CRC) and is the driver of classic microsatellite instability (MSI) in tumors. Somatic MSH3 alterations have been linked to a specific form of MSI called elevated microsatellite alterations at selected tetranucleotide repeats (EMAST) that is associated with patient poor prognosis and elevated among African American (AA) rectal cancer patients. Genetic variants of MSH3 and their pathogenicity vary among different populations, such as among AA, which are not well-represented in publicly available databases. Targeted exome sequencing of MSH3 among AA CRC samples followed by computational bioinformatic pipeline and molecular dynamic simulation analysis approach confirmed six identified MSH3 variants (c.G1237A, c.C2759T, c.G1397A, c.G2926A, c.C3028T, c.G3241A) that corresponded to MSH3 amino-acid changes (p.E413K; p.S466N; p.S920F; p.E976K; p.H1010Y; p.E1081K). All identified MSH3 variants were non-synonymous, novel, pathogenic, and show loss or gain of hydrogen bonding, ionic bonding, hydrophobic bonding, and disulfide bonding and have a deleterious effect on the structure of MSH3 protein. Some variants were located within the ATPase site of MSH3, affecting ATP hydrolysis that is critical for MSH3's function. Other variants were in the MSH3-MSH2 interacting domain, important for MSH3's binding to MSH2. Overall, our data suggest that these variants among AA CRC patients affect the function of MSH3 making them pathogenic and likely contributing to the development or advancement of CRC among AA. Further clarifying functional studies will be necessary to fully understand the impact of these variants on MSH3 function and CRC development in AA patients.

Long-read sequencing is driving rapid progress in genome assembly across all major groups of life, including species of the family Drosophilidae, a longtime model system for genetics, genomics, and evolution. We previously developed a cost-effective hybrid Oxford Nanopore (ONT) long-read and Illumina short-read sequencing approach and used it to assemble 101 drosophilid genomes from laboratory cultures, greatly increasing the number of genome assemblies for this taxonomic group. The next major challenge is to address the laboratory culture bias in taxon sampling by sequencing genomes of species that cannot easily be reared in the lab. Here, we build upon our previous methods to perform amplification-free ONT sequencing of single wild flies obtained either directly from the field or from ethanol-preserved specimens in museum collections, greatly improving the representation of lesser studied drosophilid taxa in whole-genome data. Using Illumina Novaseq X Plus and ONT P2 sequencers with R10.4.1 chemistry, we set a new benchmark for inexpensive hybrid genome assembly at US $150 per genome while assembling genomes from as little as 35 ng of genomic DNA from a single fly. We present 183 new genome assemblies for 179 species as a resource for drosophilid systematics, phylogenetics, and comparative genomics. Of these genomes, 62 are from pooled lab strains and 121 from single adult flies. Despite the sample limitations of working with small insects, most single-fly diploid assemblies are comparable in contiguity (>1 Mb contig N50), completeness (>98% complete dipteran BUSCOs), and accuracy (>QV40 genome-wide with ONT R10.4.1) to assemblies from inbred lines. We present a well-resolved multi-locus phylogeny for 360 drosophilid and 4 outgroup species encompassing all publicly available (as of August 2023) genomes for this group. Finally, we present a Progressive Cactus whole-genome, reference-free alignment built from a subset of 298 suitably high-quality drosophilid genomes. The new assemblies and alignment, along with updated laboratory protocols and computational pipelines, are released as an open resource and as a tool for studying evolution at the scale of an entire insect family.

Randomly barcoded transposon mutant libraries are powerful tools for studying gene function and organization, assessing gene essentiality and pathways, discovering potential therapeutic targets, and understanding the physiology of gut bacteria and their interactions with the host. However, construction of high-quality libraries with uniform representation can be challenging. In this review, we survey various strategies for barcoded library construction, including transposition systems, methods of transposon delivery, optimal library size, and transconjugant selection schemes. We discuss the advantages and limitations of each approach, as well as factors to consider when selecting a strategy. In addition, we highlight experimental and computational advances in arraying condensed libraries from mutant pools. We focus on examples of successful library construction in gut bacteria and their application to gene function studies and drug discovery. Given the need for understanding gene function and organization in gut bacteria, we provide a comprehensive guide for researchers to construct randomly barcoded transposon mutant libraries.

Sample multiplexing enables pooled analysis during single-cell RNA sequencing workflows, thereby increasing throughput and reducing batch effects. A challenge for all multiplexing techniques is to link sample-specific barcodes with cell-specific barcodes, then demultiplex sample identity post-sequencing. However, existing demultiplexing tools fail under many real-world conditions where barcode cross-contamination is an issue. We therefore developed deMULTIplex2, an algorithm inspired by a mechanistic model of barcode cross-contamination. deMULTIplex2 employs generalized linear models and expectation-maximization to probabilistically determine the sample identity of each cell. Benchmarking reveals superior performance across various experimental conditions, particularly on large or noisy datasets with unbalanced sample compositions.

Protein display systems are powerful techniques used to identify protein molecules that bind with high affinity to target proteins of interest. The initial challenge in implementing a display system is the construction of a high-diversity naïve library. Here, we describe the methods to generate a designed ankyrin repeat protein (DARPin) display library using degenerate oligonucleotides. Specifically described is the construction of a single DARPin repeat module by overlap extension PCR, concatenation of the module by restriction enzyme digestion and ligation, and incorporation of the concatenated modules into a full-length DARPin sequence in a bacterial cloning or display vector containing the hydrophilic N- and C-terminal capping domains. Protocols for PCR amplification of DARPin sequences to estimate diversity of naïve and enriched libraries via next-generation sequencing are included, as is a simple Linux-based program for analysis of naïve and enriched sequences. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Generation of a single DARPin repeat by overlap extension PCR Basic Protocol 2: Concatenation of DARPin repeats Basic Protocol 3: Ligation of internal repeats into cloning/display vector containing N- and C-terminal capping repeats Basic Protocol 4: Estimation of library size and diversity by next-generation sequencing (NGS) Basic Protocol 5: NGS analysis of naïve and enriched libraries.

Background: Brugada syndrome (BrS) and arrhythmogenic cardiomyopathy (ACM) are inherited cardiac diseases that may predispose to ventricular arrhythmia. Although overlapping features between BrS and ACM have been demonstrated previously, it remains to be determined whether genetic testing for ACM-related genes is needed in BrS probands. Method: Based on a single-center, retrospective registry of BrS, we aimed to verify genetic profiles of BrS using a next-generation sequencing panel, and further analyzed genetic testing of ACM-related variants in Brugada phenotypes. Results: Among a total of 119 Brugada phenotypes, 114 patients (95.8%) were male and the mean age of onset was 43.6 years. Genetic variants were identified in 25 of the 42 patients who underwent genetic testing. Fifteen patients had BrS-related genotypes, including SCN5A in 6 patients, and non-SCN5A genes in 9 patients (SCN10A, HCN4, SCN3B, and KCNE3). Nineteen patients underwent additional genetic testing with cardiomyopathy panel, which revealed ACM-related genotypes (2 PKP2, 1 DSG2, 1 TMEM43, 1 JUP, and 1 DSP) present in 6 patients (31.5%). None of the patients had structural or electrocardiographic features that fulfilled the diagnostic criteria for ACM. Conclusions: In clinical setting, ACM-related genes were identified in a significant proportion of Brugada phenotypes, supporting the argument that genetic testing of ACM overlapping is needed. Follow-up imaging studies should be considered to monitor if the disease progresses to ACM. [ABSTRACT FROM AUTHOR]

Simple Summary: Germline and somatic deficiencies of mismatch repair proteins (MMRd) are related to colorectal and endometrial cancers, but the survival impact in Asian patients remains unclear. We investigated the prevalence and outcomes of patients with germline and/or somatic MMRd. Germline and somatic MMRd were determined by gene sequencing and protein staining of tumor samples, respectively. We found that colorectal and endometrial cancer patients with germline MMRd have favorable survival outcomes compared to those without, regardless of somatic MMRd status. These findings highlight the importance of germline genetic testing when tumor MMRd is detected. Germline (Lynch syndrome, LS) and somatic deficiencies of mismatch repair proteins (MMRd) are linked to colorectal and endometrial cancer; however, their prognostic impact in Asian populations remains unclear. This prospective cohort study aimed to determine the prevalence and outcome of germline and somatic MMRd in cancer patients suspected of LS. Patients with colorectal or endometrial cancer suspected of LS were enrolled and underwent gene sequencing for germline MMRd (gMMRd) and immunohistochemistry staining of MMR proteins in a subset of the pathological samples (pMMRd). Among the 451 enrolled patients, 36 patients were gMMRd (+). Compared with gMMRd (−) patients, the 10-year relapse-free survival in gMMRd (+) patients was significantly higher (100% vs. 77.9%; p = 0.006), whereas the 10-year overall survival was similar (100% vs. 90.9%; p = 0.12). Among the 102 gMMRd (−) patients with available pMMR status, 13.7% were pMMRd (+). The 5-year relapse-free survival was 62.9% in gMMRd (−) pMMRd (+) patients and 35.0% in gMMRd (−) pMMRd (−) patients, both lower than gMMRd (+) patients (100%; p < 0.001). This study showed that having LS confers a favorable outcome in colorectal and endometrial cancer patients and highlights the importance of germline genetic testing following the detection of somatic MMRd. [ABSTRACT FROM AUTHOR]

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Measurable residual disease (MRD) testing, a standard procedure in B-lymphoblastic leukemia (B-ALL) diagnostics, is assessed using multiparametric flow cytometry (MFC) and next-generation sequencing (NGS) analysis of immunoglobulin gene rearrangements. We evaluated the concordance between eight-color, two-tube MFC-MRD the LymphoTrack NGS-MRD assays using 139 follow-up samples from 54 pediatric patients with B-ALL. We also assessed the effect of hemodilution in MFC-MRD assays. The MRD-concordance rate was 79.9% (N=111), with 25 (18.0%) and 3 (2.2%) samples testing positive only by NGSMRD (MFC-NGS+MRD) and MFC-MRD (MFC+NGS-MRD), respectively. We found a significant correlation in MRD values from total nucleated cells between the two methods (r=0.736 [0.647-0.806], P <0.001). The median MRD value of MFC-NGS+MRD samples was estimated to be 0.0012% (0.0001%-0.0263%) using the NGS-MRD assays. Notably, 14.3% of MFC-NGS+MRD samples showed NGS-MRD values below the limit of detection in the MFC-MRD assays. The percentages of hematogones detected in MFC-MRD assays significantly differed between the discordant and concordant cases (P <0.001). MFC and NGS-MRD assays showed relatively high concordance and correlation in MRD assessment, whereas the NGS-MRD assay detected MRD more frequently than the MFC-MRD assay in pediatric B-ALL. Evaluating the hematogone percentages can aid in assessing the impact of sample hemodilution. [ABSTRACT FROM AUTHOR]

Background: The three best-known NUP214 rearrangements found in leukemia (SET:: NUP214, NUP214::ABL1, and DEK::NUP214) are associated with treatment resistance and poor prognosis. Mouse experiments have shown that NUP214 rearrangements alone are insufficient for leukemogenesis; therefore, the identification of concurrent mutations is important for accurate assessment and tailored patient management. Here, we characterized the demographic characteristics and concurrent mutations in patients harboring NUP214 rearrangements. Methods: To identify patients with NUP214 rearrangements, RNA-sequencing results of diagnostic bone marrow aspirates were retrospectively studied. Concurrent targeted nextgeneration sequencing results, patient demographics, karyotypes, and flow cytometry information were also reviewed. Results: In total, 11 patients harboring NUP214 rearrangements were identified, among whom four had SET::NUP214, three had DEK::NUP214, and four had NUP214::ABL1. All DEK::NUP214-positive patients were diagnosed as having AML. In patients carrying SET::NUP214 and NUP214::ABL1, T-lymphoblastic leukemia was the most common diagnosis (50%, 4/8). Concurrent gene mutations were found in all cases. PFH6 mutations were the most common (45.5%, 5/11), followed by WT1 (27.3%, 3/11), NOTCH1 (27.3%, 3/11), FLT3-internal tandem duplication (27.3%, 3/11), NRAS (18.2%, 2/11), and EZH2 (18.2%, 2/11) mutations. Two patients represented the second and third reported cases of NUP214::ABL1-positive AML. Conclusions: We examined the characteristics and concurrent test results, including gene mutations, of 11 leukemia patients with NUP214 rearrangement. We hope that the elucidation of the context in which they occurred will aid future research on tailored monitoring and treatment. [ABSTRACT FROM AUTHOR]

In the last decade, an incredible improvement has been made in elucidating the genetic bases of cardiomyopathies. Here we report the impact of either the European Society of Cardiology (ESC) guidelines or the use of whole exome sequencing (WES) in terms of a number of variants of uncertain significance (VUS) and missed diagnoses in a series of 260 patients affected by inherited cardiac disorders. Samples were analyzed using a targeted gene panel of 128 cardiac‐related genes and/or WES in a subset of patients, with a three‐tier approach. Analyzing (i) only a subset of genes related to the clinical presentation, strictly following the ESC guidelines, 20.77% positive test were assessed. The incremental diagnostic rate for (ii) the whole gene panel, and (iii) the WES was 4.71% and 11.67%, respectively. The diverse analytical approaches increased the number of VUSs and incidental findings. Indeed, the use of WES highlights that there is a small percentage of syndromic conditions that standard analysis would not have detected. Moreover, the use of targeted sequencing coupled with “narrow” analytical approach prevents the detection of variants in actionable genes that could allow for preventive treatment. Our data suggest that genetic testing might aid clinicians in the diagnosis of inheritable cardiac disorders. [ABSTRACT FROM AUTHOR]

Infertility is a complex disease characterized by extreme genetic heterogeneity, compounded by various environmental factors. While there are exceptions, individual genetic and genomic variations related to infertility are typically rare, often family-specific, and may serve as susceptibility factors rather than direct causes of the disease. Consequently, identifying the cause of infertility and developing prevention and treatment strategies based on these factors remain challenging tasks, even in the modern genomic era. In this review, we first examine the genetic and genomic variations associated with infertility, and subsequently summarize the concepts and methods of preimplantation genetic testing in light of advances in genome analysis technology. [ABSTRACT FROM AUTHOR]

This document is a letter published in the journal Clinical Chemistry & Laboratory Medicine. It discusses a clinical pilot study on the automation of library preparation for next-generation sequencing (NGS) using microfluidics. The study focuses on the screening of somatic rearrangements of Immunoglobulin (IG) genes in patients with acute lymphoblastic leukemia (ALL). The researchers used a centrifugal microfluidic cartridge and a modified commercially available player for the automation process. The results showed that the automated library preparation using microfluidics was comparable to manual library preparation in terms of coverage and detection of IGH-VJ rearrangements. The study suggests that centrifugal microfluidic automation can reduce complexity and staff hands-on time in a clinical setup for library preparation. However, the choice of automation system depends on the throughput numbers of the laboratory. The researchers also mention the possibility of manufacturing cartridges for other lymphoid malignancies and the potential for MRD quantification by NGS. [Extracted from the article]

Background Melanoma incidence is on the rise in East Asia, yet studies of the molecular landscape are lacking in this population. We examined patients with melanoma who underwent next-generation sequencing (NGS) at a single tertiary center in South Korea, focusing on patients harboring NRAS or RAF alterations who received belvarafenib, a pan-RAF dimer inhibitor, through the Expanded Access Program (EAP). Patients and Methods Data were collected from 192 patients with melanoma who underwent NGS between November 2017 and May 2023. Variant call format data were obtained and annotated. Patients in the EAP received 450 mg twice daily doses of belvarafenib. Results Alterations in the RAS/RTK pathway were the most prevalent, with BRAF and NRAS alteration rates of 22.4% and 17.7%, respectively. NGS enabled additional detection of fusion mutations, including 6 BRAF and 1 RAF1 fusion. Sixteen patients with NRAS or RAF alterations received belvarafenib through the EAP, and disease control was observed in 50%, with 2 patients demonstrating remarkable responses. Conclusions Our study highlights the value of NGS in detecting BRAF , NRAS mutations and RAF fusions, expanding possibilities for targeted therapies in malignant melanoma. Belvarafenib showed clinical benefit in patients harboring these alterations. Ongoing trials will provide further insights into the safety and efficacy of belvarafenib. [ABSTRACT FROM AUTHOR]

Ribosome profiling has unveiled diverse regulation and perturbations of translation through a transcriptome-wide survey of ribosome occupancy, read out by sequencing of ribosome-protected messenger RNA fragments. Generation of ribosome footprints and their conversion into sequencing libraries is technically demanding and sensitive to biases that distort the representation of physiological ribosome occupancy. We address these challenges by producing ribosome footprints with P1 nuclease rather than RNase I and replacing RNA ligation with ordered two-template relay, a single-tube protocol for sequencing library preparation that incorporates adaptors by reverse transcription. Our streamlined approach reduced sequence bias and enhanced enrichment of ribosome footprints relative to ribosomal RNA. Furthermore, P1 nuclease preserved distinct juxtaposed ribosome complexes informative about yeast and human ribosome fates during translation initiation, stalling and termination. Our optimized methods for mRNA footprint generation and capture provide a richer translatome profile with low input and fewer technical challenges.

Advances in long-read sequencing and assembly now mean that individual labs can generate phased genomes that are more accurate and more contiguous than the original human reference genome. With declining costs and increasing democratization of technology, we suggest that complete genome assemblies, where both parental haplotypes are phased telomere to telomere, will become standard in human genetics. Soon, even in clinical settings where rigorous sample-handling standards must be met, affected individuals could have reference-grade genomes fully sequenced and assembled in just a few hours given advances in technology, computational processing, and annotation. Complete genetic variant discovery will transform how we map, catalog, and associate variation with human disease and fundamentally change our understanding of the genetic diversity of all humans.

Current single-cell RNA-sequencing approaches have limitations that stem from the microfluidic devices or fluid handling steps required for sample processing. We develop a method that does not require specialized microfluidic devices, expertise or hardware. Our approach is based on particle-templated emulsification, which allows single-cell encapsulation and barcoding of cDNA in uniform droplet emulsions with only a vortexer. Particle-templated instant partition sequencing (PIP-seq) accommodates a wide range of emulsification formats, including microwell plates and large-volume conical tubes, enabling thousands of samples or millions of cells to be processed in minutes. We demonstrate that PIP-seq produces high-purity transcriptomes in mouse-human mixing studies, is compatible with multiomics measurements and can accurately characterize cell types in human breast tissue compared to a commercial microfluidic platform. Single-cell transcriptional profiling of mixed phenotype acute leukemia using PIP-seq reveals the emergence of heterogeneity within chemotherapy-resistant cell subsets that were hidden by standard immunophenotyping. PIP-seq is a simple, flexible and scalable next-generation workflow that extends single-cell sequencing to new applications.

Next-generation sequencing (NGS) to identify pathogenic mutations is an integral part of acute myeloid leukemia (AML) therapeutic decision-making. The concordance in identifying pathogenic mutations among different NGS platforms at different diagnostic laboratories has been studied in solid tumors but not in myeloid malignancies to date. To determine this interlaboratory concordance, we collected a total of 194 AML bone marrow or peripheral blood samples from newly diagnosed patients with AML enrolled in the Beat AML Master Trial (BAMT) at 2 academic institutions. We analyzed the diagnostic samples from patients with AML for the detection of pathogenic myeloid mutations in 8 genes (DNMT3A, FLT3, IDH1, IDH2, NPM1, TET2, TP53, and WT1) locally using the Hematologic Neoplasm Mutation Panel (50-gene myeloid indication filter) (site 1) or the GeneTrails Comprehensive Heme Panel (site 2) at the 2 institutions and compared them with the central results from the diagnostic laboratory for the BAMT, Foundation Medicine, Inc. The overall percent agreement was over 95% each in all 8 genes, with almost perfect agreement (κ > 0.906) in all but WT1, which had substantial agreement (κ = 0.848) when controlling for site. The minimal discrepancies were due to reporting variants of unknown significance (VUS) for the WT1 and TP53 genes. These results indicate that the various NGS methods used to analyze samples from patients with AML enrolled in the BAMT show high concordance, a reassuring finding given the wide use of NGS for therapeutic decision-making in AML.

Long-read sequencing technologies substantially overcome the limitations of short-reads but have not been considered as a feasible replacement for population-scale projects, being a combination of too expensive, not scalable enough or too error-prone. Here we develop an efficient and scalable wet lab and computational protocol, Napu, for Oxford Nanopore Technologies long-read sequencing that seeks to address those limitations. We applied our protocol to cell lines and brain tissue samples as part of a pilot project for the National Institutes of Health Center for Alzheimer's and Related Dementias. Using a single PromethION flow cell, we can detect single nucleotide polymorphisms with F1-score comparable to Illumina short-read sequencing. Small indel calling remains difficult within homopolymers and tandem repeats, but achieves good concordance to Illumina indel calls elsewhere. Further, we can discover structural variants with F1-score on par with state-of-the-art de novo assembly methods. Our protocol phases small and structural variants at megabase scales and produces highly accurate, haplotype-specific methylation calls.

The accurate determination of allele frequencies is crucially important across a wide range of problems in genetics, such as developing population genetic models, making inferences from genome-wide association studies, determining genetic risk for diseases, as well as other scientific and medical applications. Furthermore, understanding how allele frequencies change over time in populations is central to ascertaining their evolutionary dynamics. We present a precise, efficient, and economical method (FREQ-Seq2) for quantifying the relative frequencies of different alleles at loci of interest in mixed population samples. Through the creative use of paired barcode sequences, we exponentially increased the throughput of the original FREQ-Seq method from 48 to 2,304 samples. FREQ-Seq2 can be targeted to specific genomic regions of interest, which are amplified using universal barcoded adapters to generate Illumina sequencing libraries. Our enhanced method, available as a kit along with open-source software for analyzing sequenced libraries, enables the detection and removal of errors that are undetectable in the original FREQ-Seq method as well as other conventional methods for allele frequency quantification. Finally, we validated the performance of our sequencing-based approach with a highly multiplexed set of control samples as well as a competitive evolution experiment in Escherichia coli and compare the latter to estimates derived from manual colony counting. Our analyses demonstrate that FREQ-Seq2 is flexible, inexpensive, and produces large amounts of data with low error, low noise, and desirable statistical properties. In summary, FREQ-Seq2 is a powerful method for quantifying allele frequency that provides a versatile approach for profiling mixed populations.

BACKGROUND: Ossifying fibroma (OF) of the craniofacial skeleton is a fibro-osseous lesion characterized by various patterns of bone formation in a cellular fibroblastic stroma. The molecular landscape of OF remains mostly unknown. There are a few known pathogenic abnormalities in OF, including HRPT2 mutations in conventional OF and SATB2 translocations in juvenile psammomatoid OF. On the other hand, conflicting reports exist regarding MDM2 gene amplification and chromosomal copy number alterations (CNA) in OF. METHODS: Surgically removed biopsies and curettage specimens from OF patients were obtained. Clinical, radiographic, and pathologic features of tumors were reviewed. Genomic DNA was extracted from formalin-fixed, paraffin-embedded blocks of tumor tissue. Capture-based DNA next-generation sequencing targeting the coding regions 529 cancer genes and select introns was performed. RESULTS: We identified 17 OF cases from 8 male and 8 female patients with mean age of 22 years (range 1-58 years). Nine case occurred in the gnathic bones and 8 in the extragnathic craniofacial bones. These cases included 3 juvenile psammomatoid OF, 6 conventional OF and 8 juvenile trabecular OF. Large-scale CNAs were present in 6 of 17 cases. Seven cases (41%) had focal amplifications including FOSB (n = 2, 11%), FOS (n = 4, 23%), COL1A1 (n = 4, 23%) and TBX3 (n = 5, 29%). Three cases (17%) had pathogenic CDC73 mutations. No cases showed focal MDM2 amplification. CONCLUSIONS: Here, we provided a comprehensive molecular characterization of OF that reveals a heterogeneous genetic profile with occasional large-scale CNAs (n = 6, 35%). FOS, FOSB, and TBX3 genes that regulate AP-1 transcriptional complex are frequently altered in OF (n = 7, 41%), chiefly in juvenile trabecular OF. These genes encode transcription factors that act as downstream effectors of the MAP kinase signaling pathway. MDM2 amplification is an exceedingly rare event in OF, if present at all, so identification of this event should continue to raise concern for low-grade gnathic osteosarcoma. In summary, our findings suggest that OF represents a heterogeneous group of tumors at the genetic level but dysregulation of the AP-1 pathway may play a role in pathogenesis of juvenile trabecular OF.

Abstract Background Brugada syndrome (BrS) and arrhythmogenic cardiomyopathy (ACM) are inherited cardiac diseases that may predispose to ventricular arrhythmia. Although overlapping features between BrS and ACM have been demonstrated previously, it remains to be determined whether genetic testing for ACM-related genes is needed in BrS probands. Method Based on a single-center, retrospective registry of BrS, we aimed to verify genetic profiles of BrS using a next-generation sequencing panel, and further analyzed genetic testing of ACM-related variants in Brugada phenotypes. Results Among a total of 119 Brugada phenotypes, 114 patients (95.8%) were male and the mean age of onset was 43.6 years. Genetic variants were identified in 25 of the 42 patients who underwent genetic testing. Fifteen patients had BrS-related genotypes, including SCN5A in 6 patients, and non-SCN5A genes in 9 patients (SCN10A, HCN4, SCN3B, and KCNE3). Nineteen patients underwent additional genetic testing with cardiomyopathy panel, which revealed ACM-related genotypes (2 PKP2, 1 DSG2, 1 TMEM43, 1 JUP, and 1 DSP) present in 6 patients (31.5%). None of the patients had structural or electrocardiographic features that fulfilled the diagnostic criteria for ACM. Conclusions In clinical setting, ACM-related genes were identified in a significant proportion of Brugada phenotypes, supporting the argument that genetic testing of ACM overlapping is needed. Follow-up imaging studies should be considered to monitor if the disease progresses to ACM.

Next-generation sequencing technologies have enabled many advances across diverse areas of biology, with many benefiting from increased sample size. Although the cost of running next-generation sequencing instruments has dropped substantially over time, the cost of sample preparation methods has lagged behind. To counter this, researchers have adapted library miniaturization protocols and large sample pools to maximize the number of samples that can be prepared by a certain amount of reagents and sequenced in a single run. However, due to high variability of sample quality, over and underrepresentation of samples in a sequencing run has become a major issue in high-throughput sequencing. This leads to misinterpretation of results due to increased noise, and additional time and cost rerunning underrepresented samples. To overcome this problem, we present a normalization method that uses shallow iSeq sequencing to accurately inform pooling volumes based on read distribution. This method is superior to the widely used fluorometry methods, which cannot specifically target adapter-ligated molecules that contribute to sequencing output. Our normalization method not only quantifies adapter-ligated molecules but also allows normalization of feature space; for example, we can normalize to reads of interest such as non-ribosomal reads. As a result, this normalization method improves the efficiency of high-throughput next-generation sequencing by reducing noise and producing higher average reads per sample with more even sequencing depth. IMPORTANCE High-throughput next generation sequencing (NGS) has significantly contributed to the field of genomics; however, further improvements can maximize the potential of this important tool. Uneven sequencing of samples in a multiplexed run is a common issue that leads to unexpected extra costs or low-quality data. To mitigate this problem, we introduce a normalization method based on read counts rather than library concentration. This method allows for an even distribution of features of interest across samples, improving the statistical power of data sets and preventing the financial loss associated with resequencing libraries. This method optimizes NGS, which already has huge importance across many areas of biology.

Cis-regulatory elements (CREs) can be classified by the shapes of their transcription start site (TSS) profiles, which are indicative of distinct regulatory mechanisms. Massively parallel reporter assays (MPRAs) are increasingly being used to study CRE regulatory mechanisms, yet the degree to which MPRAs replicate individual endogenous TSS profiles has not been determined. Here, we present a new low-input MPRA protocol (TSS-MPRA) that enables measuring TSS profiles of episomal reporters as well as after lentiviral reporter chromatinization. To sensitively compare MPRA and endogenous TSS profiles, we developed a novel dissimilarity scoring algorithm (WIP score) that outperforms the frequently used earth mover's distance on experimental data. Using TSS-MPRA and WIP scoring on 500 unique reporter inserts, we found that short (153 bp) MPRA promoter inserts replicate the endogenous TSS patterns of ∼60% of promoters. Lentiviral reporter chromatinization did not improve fidelity of TSS-MPRA initiation patterns, and increasing insert size frequently led to activation of extraneous TSS in the MPRA that are not active in vivo. We discuss the implications of our findings, which highlight important caveats when using MPRAs to study transcription mechanisms. Finally, we illustrate how TSS-MPRA and WIP scoring can provide novel insights into the impact of transcription factor motif mutations and genetic variants on TSS patterns and transcription levels.

Several methods exist for detecting genetic relatedness or identity by comparing DNA information. These methods generally require genotype calls, either single-nucleotide polymorphisms or short tandem repeats, at the sites used for comparison. For some DNA samples, like those obtained from bone fragments or single rootless hairs, there is often not enough DNA present to generate genotype calls that are accurate and complete enough for these comparisons. Here, we describe IBDGem, a fast and robust computational procedure for detecting genomic regions of identity-by-descent by comparing low-coverage shotgun sequence data against genotype calls from a known query individual. At less than 1× genome coverage, IBDGem reliably detects segments of relatedness and can make high-confidence identity detections with as little as 0.01× genome coverage.

While molecular testing of hematologic malignancies is now standard of care, there is variability in practice and testing capabilities between different academic laboratories, with common questions arising on how to best meet clinical expectations. A survey was sent to hematopathology subgroup members of the Genomics Organization for Academic Laboratories consortium to assess current and future practice and potentially establish a reference for peer institutions. Responses were received from 18 academic tertiary-care laboratories regarding next-generation sequencing (NGS) panel design, sequencing protocols and metrics, assay characteristics, laboratory operations, case reimbursement, and development plans. Differences in NGS panel size, use, and gene content were reported. Gene content for myeloid processes was reported to be generally excellent, while genes for lymphoid processes were less well covered. The turnaround time (TAT) for acute cases, including acute myeloid leukemia, was reported to range from 2 to 7 calendar days to 15 to 21 calendar days, with different approaches to achieving rapid TAT described. To help guide NGS panel design and standardize gene content, consensus gene lists based on current and future NGS panels in development were generated. Most survey respondents expected molecular testing at academic laboratories to continue to be viable in the future, with rapid TAT for acute cases likely to remain an important factor. Molecular testing reimbursement was reported to be a major concern. The results of this survey and subsequent discussions improve the shared understanding of differences in testing practices for hematologic malignancies between institutions and will help provide a more consistent level of patient care.

Although plastid genome (plastome) structure is highly conserved across most seed plants, investigations during the past two decades have revealed several disparately related lineages that experienced substantial rearrangements. Most plastomes contain a large inverted repeat and two single-copy regions, and a few dispersed repeats; however, the plastomes of some taxa harbour long repeat sequences (>300 bp). These long repeats make it challenging to assemble complete plastomes using short-read data, leading to misassemblies and consensus sequences with spurious rearrangements. Single-molecule, long-read sequencing has the potential to overcome these challenges, yet there is no consensus on the most effective method for accurately assembling plastomes using long-read data. We generated a pipeline, plastid Genome Assembly Using Long-read data (ptGAUL), to address the problem of plastome assembly using long-read data from Oxford Nanopore Technologies (ONT) or Pacific Biosciences platforms. We demonstrated the efficacy of the ptGAUL pipeline using 16 published long-read data sets. We showed that ptGAUL quickly produces accurate and unbiased assemblies using only ~50× coverage of plastome data. Additionally, we deployed ptGAUL to assemble four new Juncus (Juncaceae) plastomes using ONT long reads. Our results revealed many long repeats and rearrangements in Juncus plastomes compared with basal lineages of Poales. The ptGAUL pipeline is available on GitHub: https://github.com/Bean061/ptgaul.

RT-PCR and northern blots have long been used to study RNA isoforms usage for single genes. Recent advancements in long-read sequencing have yielded unprecedented information about the usage and abundance of these RNA isoforms. However, visualization of long-read sequencing data remains challenging due to the high information density. To alleviate these issues, we have developed NanoBlot, an open-source R-package that generates northern blot and RT-PCR-like images from long-read sequencing data. NanoBlot requires aligned, positionally sorted and indexed BAM files. Plotting is based around ggplot2 and is easily customizable. Advantages of NanoBlot include a robust system for designing probes to visualize isoforms including excluding reads based on the presence or absence of a specified region, an elegant solution to representing isoforms with continuous variations in length, and the ability to overlay multiple genes in the same plot using different colors. We present examples of nanoblots compared to actual northern blot data. In addition to traditional gel-like images, the NanoBlot package can also output other visualizations such as violin plots and 3-RACE-like plots focused on 3-end isoforms visualization. The use of the NanoBlot package should provide a simple answer to some of the challenges of visualizing long-read RNA-sequencing data.

Hybridization capture approaches allow targeted high-throughput sequencing analysis at reduced costs compared to shotgun sequencing. Hybridization capture is particularly useful in analyses of genomic data from ancient, environmental, and forensic samples, where target content is low, DNA is fragmented and multiplex PCR or other targeted approaches often fail. Here, we describe a DNA bait synthesis approach for hybridization capture that we call Circular Nucleic acid Enrichment Reagent, or CNER (pronounced 'snare'). The CNER method uses rolling-circle amplification followed by restriction digestion to discretize microgram quantities of hybridization probes. We demonstrate the utility of the CNER method by generating probes for a panel of 23 771 known sites of single nucleotide polymorphism in the horse genome. Using these probes, we capture and sequence from a panel of ten ancient horse DNA libraries, comparing CNER capture efficiency to a commercially available approach. With about one million read pairs per sample, CNERs captured more targets (90.5% versus 66.5%) at greater mean depth than an alternative commercial approach.

This is the first viral metagenomic analysis of grapevine conducted in Mexico. During the summer of 2021, 48 plants displaying virus-like symptoms were sampled in Queretaro, an important grapevine-producing area of Mexico, and analyzed for the presence of viruses via high-throughput sequencing (HTS). The results of HTS were verified by real-time RT-PCR following a standardized testing scheme (Protocol 2010). Fourteen different viruses were identified, including grapevine asteroid mosaic-associated virus (GAMaV), grapevine Cabernet Sauvignon reovirus (GCSV), grapevine fanleaf virus (GFLV), grapevine fleck virus (GFkV), grapevine Pinot gris virus (GPGV), grapevine red globe virus (GRGV), grapevine rupestris stem pitting-associated virus (GRSPaV), grapevine rupestris vein feathering virus (GRVFV), grapevine Syrah virus 1 (GSyV-1), grapevine virus B (GVB), and grapevine leafroll-associated viruses 1, 2, 3, 4 (GLRaV1, 2, 3, 4). Additionally, divergent variants of GLRaV4 and GFkV, and a novel Enamovirus-like virus were discovered. This is the first report of GAMaV, GCSV, GLRaV4, GPGV, GRGV, GRVFV, and GSyV-1 infecting grapevines in Mexico; the impact of these pathogens on production is unknown.

Sequencing has revealed hundreds of millions of human genetic variants, and continued efforts will only add to this variant avalanche. Insufficient information exists to interpret the effects of most variants, limiting opportunities for precision medicine and comprehension of genome function. A solution lies in experimental assessment of the functional effect of variants, which can reveal their biological and clinical impact. However, variant effect assays have generally been undertaken reactively for individual variants only after and, in most cases long after, their first observation. Now, multiplexed assays of variant effect can characterise massive numbers of variants simultaneously, yielding variant effect maps that reveal the function of every possible single nucleotide change in a gene or regulatory element. Generating maps for every protein encoding gene and regulatory element in the human genome would create an Atlas of variant effect maps and transform our understanding of genetics and usher in a new era of nucleotide-resolution functional knowledge of the genome. An Atlas would reveal the fundamental biology of the human genome, inform human evolution, empower the development and use of therapeutics and maximize the utility of genomics for diagnosing and treating disease. The Atlas of Variant Effects Alliance is an international collaborative group comprising hundreds of researchers, technologists and clinicians dedicated to realising an Atlas of Variant Effects to help deliver on the promise of genomics.

MOTIVATION: In recent years, high-throughput sequencing technologies have made large-scale protein sequences accessible. However, their functional annotations usually rely on low-throughput and pricey experimental studies. Computational prediction models offer a promising alternative to accelerate this process. Graph neural networks have shown significant progress in protein research, but capturing long-distance structural correlations and identifying key residues in protein graphs remains challenging. RESULTS: In the present study, we propose a novel deep learning model named Hierarchical graph transformEr with contrAstive Learning (HEAL) for protein function prediction. The core feature of HEAL is its ability to capture structural semantics using a hierarchical graph Transformer, which introduces a range of super-nodes mimicking functional motifs to interact with nodes in the protein graph. These semantic-aware super-node embeddings are then aggregated with varying emphasis to produce a graph representation. To optimize the network, we utilized graph contrastive learning as a regularization technique to maximize the similarity between different views of the graph representation. Evaluation of the PDBch test set shows that HEAL-PDB, trained on fewer data, achieves comparable performance to the recent state-of-the-art methods, such as DeepFRI. Moreover, HEAL, with the added benefit of unresolved protein structures predicted by AlphaFold2, outperforms DeepFRI by a significant margin on Fmax, AUPR, and Smin metrics on PDBch test set. Additionally, when there are no experimentally resolved structures available for the proteins of interest, HEAL can still achieve better performance on AFch test set than DeepFRI and DeepGOPlus by taking advantage of AlphaFold2 predicted structures. Finally, HEAL is capable of finding functional sites through class activation mapping. AVAILABILITY AND IMPLEMENTATION: Implementations of our HEAL can be found at https://github.com/ZhonghuiGu/HEAL.

Killer cell immunoglobulin like receptor (KIR) genes and human leukocyte antigen (HLA) genes play important roles in innate and adaptive immunity. They are highly polymorphic and cannot be genotyped with standard variant calling pipelines. Compared with HLA genes, many KIR genes are similar to each other in sequences and may be absent in the chromosomes. Therefore, although many tools have been developed to genotype HLA genes using common sequencing data, none of them work for KIR genes. Even specialized KIR genotypers could not resolve all the KIR genes. Here we describe T1K, a novel computational method for the efficient and accurate inference of KIR or HLA alleles from RNA-seq, whole-genome sequencing, or whole-exome sequencing data. T1K jointly considers alleles across all genotyped genes, so it can reliably identify present genes and distinguish homologous genes, including the challenging KIR2DL5A/KIR2DL5B genes. This model also benefits HLA genotyping, where T1K achieves high accuracy in benchmarks. Moreover, T1K can call novel single-nucleotide variants and process single-cell data. Applying T1K to tumor single-cell RNA-seq data, we found that KIR2DL4 expression was enriched in tumor-specific CD8+ T cells. T1K may open the opportunity for HLA and KIR genotyping across various sequencing applications.

Approximately 13% of the human genome at certain motifs have the potential to form noncanonical (non-B) DNA structures (e.g., G-quadruplexes, cruciforms, and Z-DNA), which regulate many cellular processes but also affect the activity of polymerases and helicases. Because sequencing technologies use these enzymes, they might possess increased errors at non-B structures. To evaluate this, we analyzed error rates, read depth, and base quality of Illumina, Pacific Biosciences (PacBio) HiFi, and Oxford Nanopore Technologies (ONT) sequencing at non-B motifs. All technologies showed altered sequencing success for most non-B motif types, although this could be owing to several factors, including structure formation, biased GC content, and the presence of homopolymers. Single-nucleotide mismatch errors had low biases in HiFi and ONT for all non-B motif types but were increased for G-quadruplexes and Z-DNA in all three technologies. Deletion errors were increased for all non-B types but Z-DNA in Illumina and HiFi, as well as only for G-quadruplexes in ONT. Insertion errors for non-B motifs were highly, moderately, and slightly elevated in Illumina, HiFi, and ONT, respectively. Additionally, we developed a probabilistic approach to determine the number of false positives at non-B motifs depending on sample size and variant frequency, and applied it to publicly available data sets (1000 Genomes, Simons Genome Diversity Project, and gnomAD). We conclude that elevated sequencing errors at non-B DNA motifs should be considered in low-read-depth studies (single-cell, ancient DNA, and pooled-sample population sequencing) and in scoring rare variants. Combining technologies should maximize sequencing accuracy in future studies of non-B DNA.

Mosaic variants (MVs) reflect mutagenic processes during embryonic development and environmental exposure, accumulate with aging and underlie diseases such as cancer and autism. The detection of noncancer MVs has been computationally challenging due to the sparse representation of nonclonally expanded MVs. Here we present DeepMosaic, combining an image-based visualization module for single nucleotide MVs and a convolutional neural network-based classification module for control-independent MV detection. DeepMosaic was trained on 180,000 simulated or experimentally assessed MVs, and was benchmarked on 619,740 simulated MVs and 530 independent biologically tested MVs from 16 genomes and 181 exomes. DeepMosaic achieved higher accuracy compared with existing methods on biological data, with a sensitivity of 0.78, specificity of 0.83 and positive predictive value of 0.96 on noncancer whole-genome sequencing data, as well as doubling the validation rate over previous best-practice methods on noncancer whole-exome sequencing data (0.43 versus 0.18). DeepMosaic represents an accurate MV classifier for noncancer samples that can be implemented as an alternative or complement to existing methods.

Random DNA barcodes are a versatile tool for tracking cell lineages, with applications ranging from development to cancer to evolution. Here, we review and critically evaluate barcode designs as well as methods of barcode sequencing and initial processing of barcode data. We first demonstrate how various barcode design decisions affect data quality and propose a new design that balances all considerations that we are currently aware of. We then discuss various options for the preparation of barcode sequencing libraries, including inline indices and Unique Molecular Identifiers (UMIs). Finally, we test the performance of several established and new bioinformatic pipelines for the extraction of barcodes from raw sequencing reads and for error correction. We find that both alignment and regular expression-based approaches work well for barcode extraction, and that error-correction pipelines designed specifically for barcode data are superior to generic ones. Overall, this review will help researchers to approach their barcoding experiments in a deliberate and systematic way.

The term "multiple primary (MP) cancers" refers to the existence of more than one cancer in the same patient. The combination of MP cancers with hematological malignancies is relatively uncommon. In this study, we present five patients diagnosed with MP cancers concomitant with hematological malignancies. We comprehensively analyzed their clinical characteristics, cytogenetic profiles, and germline and somatic variants. As first primaries, two patients had solid cancer not followed by cytotoxic therapy and three had hematologic cancer, followed by cytotoxic therapy. The second primaries were all hematologic malignancies that did not meet the criteria for therapy-related myeloid neoplasm. Notably, two (40%) out of the five patients harbored pathogenic potential/presumed germline variants in cancer predisposition genes. Therefore, germline variant testing should be considered when MP cancers with hematological malignancies require consideration for related donor stem cell transplantation. [ABSTRACT FROM AUTHOR]

Abstract Background Normalization, as a pre-processing step, can significantly affect the resolution of machine learning analysis for microbiome studies. There are countless options for normalization scheme selection. In this study, we examined compositionally aware algorithms including the additive log ratio (alr), the centered log ratio (clr), and a recent evolution of the isometric log ratio (ilr) in the form of balance trees made with the PhILR R package. We also looked at compositionally naïve transformations such as raw counts tables and several transformations that are based on relative abundance, such as proportions, the Hellinger transformation, and a transformation based on the logarithm of proportions (which we call “lognorm”). Results In our evaluation, we used 65 metadata variables culled from four publicly available datasets at the amplicon sequence variant (ASV) level with a random forest machine learning algorithm. We found that different common pre-processing steps in the creation of the balance trees made very little difference in overall performance. Overall, we found that the compositionally aware data transformations such as alr, clr, and ilr (PhILR) performed generally slightly worse or only as well as compositionally naïve transformations. However, relative abundance-based transformations outperformed most other transformations by a small but reliably statistically significant margin. Conclusions Our results suggest that minimizing the complexity of transformations while correcting for read depth may be a generally preferable strategy in preparing data for machine learning compared to more sophisticated, but more complex, transformations that attempt to better correct for compositionality. Video Abstract

Objectives A combination of immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) is the current standard of care for HER2 evaluation in breast cancer. Here, we investigate the potential clinical utility of next-generation sequencing (NGS)–derived HER2/ERBB2 copy number (CN) data for predicting HER2 status as defined by American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guidelines. Methods In total, 294 locally recurrent and metastatic breast cancers previously tested by targeted hybrid capture–based NGS and by HER2 IHC/FISH were included. Analyses focused on the ERBB2 median log2 ratios and start-end genomic coordinates from NGS, average HER2 CN and HER2/ CEP17 ratios from FISH, and the HER2 IHC scores. We also determined a more stringent log2 ratio cutoff to predict HER2-positive status with 100% specificity. Results Sixty-four (22%) cases were HER2 positive and 230 (78%) were HER2 negative by ASCO/CAP guidelines. The ERBB2 median log2 ratios from NGS strongly correlated with HER2 status by IHC/FISH (area under receiver operator characteristic curve = 0.951). ERBB2 log2 ratio more than 1.7 was 100% specific for HER2-positive results by IHC/FISH. Start and end genomic coordinates for regions of gain near ERBB2 by NGS also predicted HER2 status. Conclusions Copy number data from our NGS panel strongly correlate with HER2 status. Using a stringent cutoff, ERBB2 log2 ratio accurately predicts HER2 positivity with high specificity. The NGS CN assessment may have utility in determining HER2 status in certain clinical settings. [ABSTRACT FROM AUTHOR]

Background: The mechanism and medical treatment target for degenerative aortic valve disease, including aortic stenosis, is not well studied. In this study, we investigated the effect of clonal hematopoiesis of indeterminate potential (CHIP) on the development of aortic valve sclerosis (AVS), a calcified aortic valve without significant stenosis. Methods: Participants with AVS (valves ≥2 mm thick, high echogenicity, and a peak transaortic velocity of <2.5 m/sec) and an age- and sex-matched control group were enrolled. Twenty-four CHIP genes with common variants in cardiovascular disease were used to generate a next-generation sequencing panel. The primary endpoint was the CHIP detection rate between the AVS and control groups. Inverse-probability treatment weighting (IPTW) analysis was performed to adjust for differences in baseline characteristics. Results: From April 2020 to April 2022, 187 participants (125 with AVS and 62 controls) were enrolled; the mean age was 72.6±8.5 yrs, and 54.5% were male. An average of 1.3 CHIP variants was observed. CHIP detection, defined by a variant allele frequency (VAF) of ≥0.5%, was similar between the groups. However, the AVS group had larger CHIP clones: 49 (39.2%) participants had a VAF of ≥1% (vs. 13 [21.0%] in the control group; P=0.020), and 25 (20.0%) had a VAF of ≥2% (vs. 4 [6.5%]; P=0.028). AVS is independently associated with a VAF of ≥1% (adjusted odds ratio: 2.44, 95% confidence interval: 1.11-5.36; P=0.027). This trend was concordant and clearer in the IPTW cohort. Conclusions: Participants with AVS more commonly had larger CHIP clones than age- and sex-matched controls. Further studies are warranted to identify causality between AVS and CHIP. [ABSTRACT FROM AUTHOR]

Circulating tumor DNA (ctDNA) has emerged as a promising tool for various clinical applications, including early diagnosis, therapeutic target identification, treatment response monitoring, prognosis evaluation, and minimal residual disease detection. Consequently, ctDNA assays have been incorporated into clinical practice. In this review, we offer an indepth exploration of the clinical implementation of ctDNA assays. Notably, we examined existing evidence related to pre-analytical procedures, analytical components in current technologies, and result interpretation and reporting processes. The primary objective of this guidelines is to provide recommendations for the clinical utilization of ctDNA assays. [ABSTRACT FROM AUTHOR]

The Ataxia Global Initiative (AGI) is a worldwide multi-stakeholder research platform to systematically enhance trial-readiness in degenerative ataxias. The next-generation sequencing (NGS) working group of the AGI aims to improve methods, platforms, and international standards for ataxia NGS analysis and data sharing, ultimately allowing to increase the number of genetically ataxia patients amenable for natural history and treatment trials. Despite extensive implementation of NGS for ataxia patients in clinical and research settings, the diagnostic gap remains sizeable, as approximately 50% of patients with hereditary ataxia remain genetically undiagnosed. One current shortcoming is the fragmentation of patients and NGS datasets on different analysis platforms and databases around the world. The AGI NGS working group in collaboration with the AGI associated research platforms—CAGC, GENESIS, and RD-Connect GPAP—provides clinicians and scientists access to user-friendly and adaptable interfaces to analyze genome-scale patient data. These platforms also foster collaboration within the ataxia community. These efforts and tools have led to the diagnosis of > 500 ataxia patients and the discovery of > 30 novel ataxia genes. Here, the AGI NGS working group presents their consensus recommendations for NGS data sharing initiatives in the ataxia field, focusing on harmonized NGS variant analysis and standardized clinical and metadata collection, combined with collaborative data and analysis tool sharing across platforms. [ABSTRACT FROM AUTHOR]