Best practices for variant calling in clinical sequencing

Expanding the Molecular-genetic Spectrum of Canalicular Adenoma-like Subtype of Pleomorphic Adenoma of Salivary Glands

Canalicular tumors of the salivary glands have recently emerged as an entity characterized by distinct morphology and recurrent HMGA2 gene rearrangement. In this study, we analyzed 40 cases intending to elucidate their features further. The monophasic or biphasic tumors exhibited a growth pattern of interconnected anastomosing trabeculae and canaliculi, accompanied by a classical pleomorphic adenoma in one-third of the cases. Invasive growth into surrounding adipose tissue was revealed in one case which was, therefore, diagnosed as epithelial-myoepithelial carcinoma. Although the tumor cells uniformly expressed HMGA2 protein in all cases, cytokeratin 7, S100 protein, and SOX10 displayed either diffuse positivity or highlighted the luminal and abluminal cell populations, respectively. Areas with morphological oncocytoid change and AR-immunopositivity of luminal cells were seen in 13/14 (93%) of tested biphasic cases. HMGA2 rearrangement was detected by RNA-sequencing in 30 cases. The most common alteration was an HMGA1::WIF1 fusion, but several novel or rare fusion partners were identified, including ARID2 , FHIT , MSRB3 and its antisense variant MSRB3-AS1 , IFNG-AS1 , and the long intergenic region LINC02389 . In addition, FISH revealed HGMA2 break-apart in the remaining 10 cases where targeted sequencing failed to detect any alteration or where RNA sequencing could not be performed. Notably, the loss of the 3'-untranslated region of HMGA2 emerges as the common denominator for the described rearrangements, possibly disrupting its negative regulation by small regulatory RNAs. Awareness of this lesion ensures appropriate diagnosis and clinical management, especially with regard to the possibility of malignant transformation described in this and previous studies.

Cytomegalovirus infection and drug resistance emergence during letermovir salvage therapy in a pediatric SCID patient

Cytomegalovirus (CMV) infection is a common complication in newborns with severe combined immunodeficiency (SCID). Prolonged antiviral treatment in immunocompromised patients increases the risk of the emergence of drug resistance. We analyzed drug resistance in a newborn with SCID who developed neonatal CMV infection. Sequencing of viral DNA polymerase (DP; UL54), protein kinase (UL97), and terminase (UL51, UL56, UL89) genes identified ganciclovir (GCV) and foscarnet (PFA) resistance mutations in blood, but not cerebrospinal fluid. After treatment was shifted to cidofovir and letermovir (LMV), a LMV resistance mutation rapidly emerged in UL56 (C325F). Eventually, a multidrug-resistant genotype was established (DP-V781I and UL56-C325F). Whole-genome sequencing of CMV in clinical blood samples showed an otherwise stable genotype. This case describes a CMV infection complicated by compartmentalization and the emergence of resistance to GCV, PFA, and LMV. It highlights the need for further investigation into alternative antiviral strategies for the prevention and treatment of CMV.

Dynamics and Evolution of Donor-derived Cytomegalovirus Infection in 3 Solid Organ Transplant Recipients With the Same Multiorgan Donor

BACKGROUND

Cytomegalovirus (CMV) infection poses a significant risk to immunosuppressed transplant recipients, manifesting through primary infection, reinfection, or reactivation.

METHODS

We analyzed the emergence of drug resistance in CMV infection in 3 patients who were later found to have received an allograft from a shared, deceased donor. The seronegative transplant recipients developed symptomatic CMV infections after bowel/pancreas, kidney, or lung transplantation. Prospective Sanger sequencing was used to identify mutations in the viral DNA polymerase (DP) and protein kinase (PK). DP and PK variants were retrospectively quantified by targeted next-generation sequencing. The impact of the novel DP-A505G substitution on drug susceptibility was assessed using a recombinant virus. Whole-genome sequencing of clinical CMV samples was enabled through target DNA enrichment.

RESULTS

The DP-A505G substitution was found in all patient samples and could be associated with a natural polymorphism. A subsequent review of the patients' clinical histories revealed that they had all received organs from a single donor. The CMV infection exhibited divergent evolution among the patients: patient 1 developed resistance to ganciclovir and foscarnet because of 2 DP mutations (V715M and V781I), patient 2 showed no genotypic resistance, and patient 3 developed ganciclovir (PK-L595S) and maribavir resistance (PK-T409M). Interpatient variation across the entire CMV genome was minimal, with viral samples clustering in phylogenetic analysis.

CONCLUSIONS

All 3 transplant recipients were infected with the same donor-derived CMV strain and readily developed different drug susceptibility profiles. This underscores the importance of judicious antiviral drug use and surveillance in preventing antiviral resistance emergence.

Genomic and transcriptomic sequencing in prostate cancer

PURPOSE OF REVIEW

Genomic and transcriptomic sequencing technologies have revolutionized our ability to characterize prostate cancer at the molecular level. The underlying premise of next-generation sequencing technologies and their current and evolving applications in prostate cancer management are provided in the review.

RECENT FINDINGS

Improved methodologies are allowing timely sequencing of the coding regions or both the coding and noncoding regions of the genome to help identify potential mutations and structural variations in the prostate cancer genome, some of which are currently also targetable therapeutically. DNA microarray- based differential gene expression has been supplanted by RNA sequencing (RNA-seq), which not only allows for more accurate quantitation but also nucleotide-level resolution to investigate the entire transcriptome, including alternative gene spliced transcripts and noncoding RNA transcripts, whose full clinical implications have yet to be fully understood and realized. Gene classifier platforms that predict risk of recurrence or metastasis are being incorporated into prostate cancer management algorithms. In the appropriate clinical context, not only somatic but also germline mutation testing is being recommended.

SUMMARY

Continued clinical integration of sequencing technologies and ongoing research will lead to improved understanding of prostate cancer biology and prostate cancer treatment.

Rapid, Reliable, and Interpretable Copy Number Variant Curation Visualizations for Diagnostic Settings with SeeNV

Copy number variants (CNVs), structural alterations in the genome involving duplication or deletion of DNA segments, are implicated in various health conditions. Despite their clinical significance, accurate identification and interpretation of CNVs remain challenging, especially in the context of whole-exome sequencing (WES), which is commonly used in clinical diagnostic laboratories. Although WES offers economic advantages over whole-genome sequencing, it struggles with CNV detection because of technical noise introduced by laboratory and analytic processes. Manual curation of CNV calls generated by these tools is labor intensive and error prone. To address this, SeeNV, a command-line tool, is introduced to aid manual curation of CNVs at scale. SeeNV is one solution to these issues, developed in collaboration with and used by the Precision Diagnostics Laboratory at Children's Hospital Colorado. SeeNV generates static infographics for each CNV, incorporating sample and cohort sequencing coverage statistics, CNV population frequency, and, more, facilitating rapid and precise assessment. Using CNV calls identified in publicly available WES and whole-genome sequencing samples, users can rapidly and reliably curate CNV calls, needing only 4.3 seconds to curate a call, achieving 0.95 recall (analytical sensitivity) and 0.74 precision (positive predictive value). SeeNV is freely available for download on GitHub.

Advancing precision oncology with AI-powered genomic analysis

Multiomics data integration approaches offer a comprehensive functional understanding of biological systems, with significant applications in disease therapeutics. However, the quantitative integration of multiomics data presents a complex challenge, requiring highly specialized computational methods. By providing deep insights into disease-associated molecular mechanisms, multiomics facilitates precision medicine by accounting for individual omics profiles, enabling early disease detection and prevention, aiding biomarker discovery for diagnosis, prognosis, and treatment monitoring, and identifying molecular targets for innovative drug development or the repurposing of existing therapies. AI-driven bioinformatics plays a crucial role in multiomics by computing scores to prioritize available drugs, assisting clinicians in selecting optimal treatments. This review will explain the potential of AI and multiomics data integration for disease understanding and therapeutics. It highlight the challenges in quantitative integration of diverse omics data and clinical workflows involving AI in cancer genomics, addressing the ethical and privacy concerns related to AI-driven applications in oncology. The scope of this text is broad yet focused, providing readers with a comprehensive overview of how AI-powered bioinformatics and integrative multiomics approaches are transforming precision oncology. Understanding bioinformatics in Genomics, it explore the integrative multiomics strategies for drug selection, genome profiling and tumor clonality analysis with clinical application of drug prioritization tools, addressing the technical, ethical, and practical hurdles in deploying AI-driven genomics tools.

Artificial intelligence in variant calling: a review

Artificial intelligence (AI) has revolutionized numerous fields, including genomics, where it has significantly impacted variant calling, a crucial process in genomic analysis. Variant calling involves the detection of genetic variants such as single nucleotide polymorphisms (SNPs), insertions/deletions (InDels), and structural variants from high-throughput sequencing data. Traditionally, statistical approaches have dominated this task, but the advent of AI led to the development of sophisticated tools that promise higher accuracy, efficiency, and scalability. This review explores the state-of-the-art AI-based variant calling tools, including DeepVariant, DNAscope, DeepTrio, Clair, Clairvoyante, Medaka, and HELLO. We discuss their underlying methodologies, strengths, limitations, and performance metrics across different sequencing technologies, alongside their computational requirements, focusing primarily on SNP and InDel detection. By comparing these AI-driven techniques with conventional methods, we highlight the transformative advancements AI has introduced and its potential to further enhance genomic research.

Benchmarking of variant calling software for whole-exome sequencing using gold standard datasets

Accurate variant calling from whole-exome sequencing (WES) data is vital for understanding genetic diseases. Recently, commercial variant calling software have emerged that do not require bioinformatics or programming expertise, hence enabling independent analysis of WES data by smaller laboratories and clinics and circumventing the need for dedicated and expensive computers and bioinformatics staff. This study benchmarks four non-programming variant calling software namely, Illumina BaseSpace Sequence Hub (Illumina), CLC Genomics Workbench (CLC), Partek Flow, and Varsome Clinical, for the variant calling of three Genome in a Bottle (GIAB) whole-exome sequencing datasets (HG001, HG002 and HG003). Following alignment of sequence reads to the human reference genome GRCh38, variants were compared against high-confidence regions from GIAB datasets and assessed using the Variant Calling Assessment Tool (VCAT). Illumina's DRAGEN Enrichment achieved the highest precision and recall scores for single nucleotide variant (SNV) and insertions/deletion (indel) calling at over 99% for SNVs and 96% for indels while Partek Flow using unionised variant calls from Freebayes and Samtools had the lowest indel calling performance. Illumina had the highest true positives (TP) variant counts for all samples and all four software shared 98-99% similarity of TP variants. Run times were shortest for CLC and Illumina ranging from 6 to 25 min and 29 to 36 min respectively, while Partek Flow took the longest (3.6 to 29.7 h). This study provides information for clinicians and biologists without programming expertise in their selection of software for variant analysis that balance accuracy, sensitivity, and runtime.

Multiomic profiling of T cell lymphoma after therapy with anti-BCMA CAR T cells and GPRC5D-directed bispecific antibody

Chimeric antigen receptor (CAR) T cells and bispecific T cell engagers have become integral components in the treatment of relapsed/refractory multiple myeloma. We report a 63-year-old male who received ciltacabtagene autoleucel CAR T cells and the GPRC5D × CD3 bispecific talquetamab for early relapse of his multiple myeloma. Nine months after CAR T therapy, he developed a symptomatic leukemic peripheral T cell lymphoma with cutaneous and intestinal involvement. Longitudinal single-cell RNA and T cell receptor sequencing of peripheral blood and bone marrow revealed two hyperexpanded CAR-carrying T cell clones. These expanded clones exhibited an exhausted effector-memory T cell transcriptional signature, and the neoplasm itself was sensitive to dexamethasone treatment. The immunophenotypic and transcriptional alterations of these abnormal T cells resembled those of T-large granular lymphocytic leukemia. Spatial transcriptomes of skin lesions confirmed the aberrant CAR-expressing T cells. Whole-genome sequencing revealed three distinct integration sites, within the introns of ZGPAT, KPNA4 and polycomb-associated noncoding RNAs. Before and after CAR T whole-genome analyses implicated clonal outgrowth of a TET2-mutated precursor propelled by additional subclone-specific loss of heterozygosity and other secondary mechanisms. This case highlights the evolution of a CAR-carrying peripheral T cell lymphoma following CAR T cell and bispecific T cell engager therapy, offering critical insights into the clonal evolution from a predisposed hematopoietic precursor to a mature neoplasm.

Diagnostic and Prognostic/Therapeutic Significance of Comprehensive Analysis of Bone and Soft Tissue Tumors Using Optical Genome Mapping and Next-Generation Sequencing

Detecting somatic structural variants (SVs), copy number variants (CNVs), and mutations in bone and soft tissue tumors is essential for accurately diagnosing, treating, and prognosticating outcomes. Optical genome mapping (OGM) holds promise to yield useful data on SVs and CNVs but requires fresh or snap-frozen tissues. This study aimed to evaluate the clinical utility of data from OGM compared with current standard-of-care cytogenetic testing. We evaluated 60 consecutive specimens from bone and soft tissue tumors using OGM and karyotyping, fluorescence in situ hybridization, gene fusion assays, and deep next-generation sequencing. OGM accurately identified diagnostic SVs/CNVs previously detected by karyotyping and fluorescence in situ hybridization (specificity = 100%). OGM identified diagnostic and pathogenic SVs/CNVs (∼23% of cases) undetected by karyotyping (cryptic/submicroscopic). OGM allowed the detection and further characterization of complex structural rearrangements including chromoanagenesis (27% of cases) and complex 3- to 6-way translocations (15% of cases). In addition to identifying 321 SVs and CNVs among cases with chromoanagenesis events, OGM identified approximately 9 SVs and 12 CNVs per sample. A combination of OGM and deep next-generation sequencing data identified diagnostic, disease-associated, and pathogenic SVs, CNVs, and mutations in ∼98% of the cases. Our cohort contained the most extensive collection of bone and soft tissue tumors profiled by OGM. OGM had excellent concordance with standard-of-care cytogenetic testing, detecting and assigning high-resolution genome-wide genomic abnormalities with higher sensitivity than routine testing. This is the first and largest study to provide insights into the clinical utility of combined OGM and deep sequencing for the pathologic diagnosis and potential prognostication of bone and soft tissue tumors in routine clinical practice.

Breaking the Bone Marrow Barrier: Peripheral Blood as a Gateway to Measurable Residual Disease Detection in Acute Myelogenous Leukemia

Acute myeloid leukemia (AML) is a genetically heterogeneous disease with high rates of relapse after initial treatment. Identifying measurable residual disease (MRD) following initial therapy is essential to assess response, predict patient outcomes, and identify those in need of additional intervention. Currently, MRD analysis relies on invasive, serial bone marrow (BM) biopsies, which complicate sample availability and processing time and negatively impact patient experience. Additionally, finding a positive result can generate more questions than answers, causing anxiety for both the patient and the provider. Peripheral blood (PB) evaluation has shown promise in detecting MRD and is now recommended by the European Leukemia Net for AML for certain genetic abnormalities. PB-based sampling allows for more frequent testing intervals and better temporal resolution of malignant expansion while sparing patients additional invasive procedures. In this review, we will discuss the current state of PB testing for MRD evaluation with a focus on next-generation sequencing methodologies that are capable of MRD detection across AML subtypes.

Molecular Profiling of Sinonasal Adenoid Cystic Carcinoma: Canonical and Noncanonical Gene Fusions and Mutation

Adenoid cystic carcinomas (AdCC) of salivary gland origin have long been categorized as fusion-defined carcinomas owing to the almost universal presence of the gene fusion MYB::NFIB , or less commonly MYBL1::NFIB. Sinonasal AdCC is an aggressive salivary gland malignancy with no effective systemic therapy. Therefore, it is urgent to search for potentially targetable genetic alterations associated with AdCC. We have searched the authors' registries and selected all AdCCs arising in the sinonasal tract. The tumors were examined histologically, immunohistochemically, by next generation sequencing (NGS) and/or fluorescence in situ hybridization (FISH) looking for MYB/MYBL1 and/or NFIB gene fusions or any novel gene fusions and/or mutations. In addition, all tumors were tested for HPV by genotyping using (q)PCR. Our cohort comprised 88 cases of sinonasal AdCC, predominantly characterized by canonical MYB::NFIB (49 cases) and MYBL1::NFIB (9 cases) fusions. In addition, noncanonical fusions EWSR1::MYB ; ACTB::MYB; ESRRG::DNM3 , and ACTN4::MYB were identified by NGS, each of them in 1 case. Among nine fusion-negative AdCCs, FISH detected rearrangements in MYB (7 cases) , NFIB (1 case), and EWSR1 (1 case). Six AdCCs lacked fusions or gene rearrangements, while 11 cases were unanalyzable. Mutational analysis was performed by NGS in 31/88 (35%) AdCCs. Mutations in genes with established roles in oncogenesis were identified in 21/31 tumors (68%), including BCOR (4/21; 19%), NOTCH1 (3/21; 14%), EP300 (3/21; 14%), SMARCA4 (2/21; 9%), RUNX1 (2/21; 9%), KDM6A (2/21; 9%), SPEN (2/21; 9%), and RIT1, MGA, RB1, PHF6, PTEN, CREBBP, DDX41, CHD2, ROS1, TAF1, CCD1, NF1, PALB2, AVCR1B, ARID1A, PPM1D, LZTR1, GEN1 , PDGFRA , each in 1 case (1/21; 5%). Additional 24 cases exhibited a spectrum of gene mutations of uncertain pathogenetic significance. No morphologic differences were observed between AdCCs with MYBL1::NFIB and MYB::NFIB fusions. Interestingly, mutations in the NOTCH genes were seen in connection with both canonical and noncanonical fusions, and often associated with high-grade histology or metatypical phenotype, as well as with poorer clinical outcome. Noncanonical fusions were predominantly observed in metatypical AdCCs. These findings emphasize the value of comprehensive molecular profiling in correlating morphologic characteristics, genetic landscape, and clinical behavior in AdCC.

Diagnostic next-generation sequencing to detect MYD88 L265P in Lymphoplasmacytic lymphoma compared to ddPCR

Lymphoplasmacytic lymphoma (LPL) is a B-cell lymphoproliferative disorder typically involving the bone marrow with infiltration by small lymphocytes and plasma cells. Studies have identified MYD88 L265P mutation as a diagnostic marker to distinguish LPL from other small B-cell lymphomas. Detection rates for this mutation have varied depending on the analytic methodology, with previous data suggesting that routine next-generation sequencing (NGS) does not demonstrate the required sensitivity to reliably detect MYD88 L265P. NGS has become part of routine clinical testing because it allows detection of variants across multiple genes. To study the utility of NGS in the detection of MYD88 L265P, we performed droplet digital PCR (ddPCR) and routine NGS on a cohort of 34 cases of lymphoid neoplasms (22 LPL, 4 CLL, 1 MCL, 1 MGUS, 2 plasma cell myeloma, and 4 negative bone marrow cases). We utilized manual review and BAMtools to assess MYD88 L265P in NGS cases. Limit of detection for ddPCR was determined to be 0.4 % variant allele frequency (VAF) with 10 ng DNA input. MYD88 L265P VAF detection by NGS and ddPCR was comparable down to 0.5 % VAF (R2 = 0.968). Setting an appropriate threshold for detection based on ddPCR results resulted in zero NGS false positives. We found that low tumor content did not impact the detection of MYD88 L265P by NGS. This study demonstrates that NGS can be a sensitive and reliable method for detection of MYD88 L265P with adequate coverage and specific assessment parameters.

Genome-wide DNA polymorphisms in two peatland adapted Coffea liberica varieties

OBJECTIVES

Coffea liberica is one of the species within the Coffea genus known for its distinctive flavor and resistance to leaf rust disease. Through breeding approaches, two superior varieties of C. liberica, designated as Liberoid Meranti 1 (Lim 1) and Liberoid Meranti 2 (Lim 2), were introduced in 2015. These varieties are known for their high adaptability in peatlands. The genetic basis of plant adaptability to peatlands remains largely unknown. It is therefore essential to identify genome-wide DNA polymorphisms in Lim 1 and 2 in order to gain insights into its capacity for adaptation in peatlands.

DATA DESCRIPTION

Whole genome sequencing was performed on three plants from each variety (Lim 1 and 2), resulting in 430 million sequencing reads. The mean depth of sequencing for each sample was 36.90x. The reads were mapped to the Coffea canephora genome, with an average mapping rate of 96.34%. The sequencing data revealed the presence of 3,766,805 single-nucleotide polymorphisms (SNPs) and 1,123,683 insertion-deletions (indels) in all six plants. Among the SNPs, there was a notable prevalence of transitions, with a ratio of approximately twofold compared to transversions. The generated data offers invaluable genomic resources for marker development, with significant implications for understanding peatlands adaptability.

De novo and somatic structural variant discovery with SVision-pro

Long-read-based de novo and somatic structural variant (SV) discovery remains challenging, necessitating genomic comparison between samples. We developed SVision-pro, a neural-network-based instance segmentation framework that represents genome-to-genome-level sequencing differences visually and discovers SV comparatively between genomes without any prerequisite for inference models. SVision-pro outperforms state-of-the-art approaches, in particular, the resolving of complex SVs is improved, with low Mendelian error rates, high sensitivity of low-frequency SVs and reduced false-positive rates compared with SV merging approaches.

Comprehensive study of gene fusions in sarcomas

Sarcomas, including bone sarcomas and soft tissue sarcomas (STSs), are a heterogeneous group of mesenchymal malignancies. Recent advancements in next-generation sequencing (NGS) have enabled the identification of novel chromosomal translocations and fusion genes, which play a critical role in sarcoma subtypes. Our study focuses on gene fusions in sarcomas among Chinese patients, comparing their genomic profiles to those of Western populations. We analyzed 1048 sarcoma samples from Chinese patients using a panel of over 500 genes, identifying 481 gene fusions in 329 patients. The most common fusions included EWSR1, HMGA2, and SS18, with notable subtype-specific fusions such as EWSR1-FLI1 in Ewing sarcoma and NAB2-STAT6 in solitary fibrous tumors. In comparison to Chinese and Western populations, variations in fusion spectrum exist, potentially necessitating distinct treatment strategies; however, further validation of these fusions is warranted. Our findings highlight the importance of gene fusions as diagnostic markers and potential therapeutic targets. Actionable fusions, including kinase-related fusions like ALK, NTRK3, and BRAF, were detected in 67 patients (6.4%) and may guide precision therapies. Additionally, we observed the frequent co-occurrence of genomic alterations, particularly in cell cycle regulators such as CDK4 and MDM2. Genomic profiling of sarcomas offers valuable insights into their molecular drivers and can support personalized therapeutic approaches. Further research is needed to validate these findings and optimize treatment strategies for sarcoma patients.

Common Ancestry of the Id Locus: Chromosomal Rearrangement and Polygenic Possibilities

The diversity in dermal pigmentation and plumage color among domestic chickens is striking, with Black Bone Chickens (BBC) particularly notable for their intense melanin hyperpigmentation. This unique trait is driven by a complex chromosomal rearrangement on chromosome 20 at the Fm locus, resulting in the overexpression of the EDN3 (a gene central to melanocyte regulation). In contrast, the inhibition of dermal pigmentation is regulated by the Id locus. Although prior studies using genetic crosses, GWAS, and gene expression analysis have investigated the genetic underpinnings of the Id locus, its precise location and functional details remain elusive. Our study aims to precisely locate the Id locus, identify associated chromosomal rearrangements and candidate genes influencing dermal pigmentation, and examine the ancestral status of the Id locus in BBC breeds. Using public genomic data from BBC and non-BBC breeds, we refined the Id locus to a ~1.6 Mb region that co-localizes with Z amplicon repeat units at the distal end of the q-arm of chromosome Z within a 10.36 Mb inversion in Silkie BBC. Phylogenetic and population structure analyses reveal that the Id locus shares a common ancestry across all BBC breeds, much like the Fm locus. Selection signatures and highly differentiated BBC-specific SNPs within the MTAP gene position it as the prime candidate for the Id locus with CCDC112 and additional genes, suggesting a possible polygenic nature. Our results suggest that the Id locus is shared among BBC breeds and may function as a supergene cluster in shank and dermal pigmentation variation.

Statistical Distributions of Genome Assemblies Reveal Random Effects in Ancient Viral DNA Reconstructions

Ancient human viruses have been detected in ancient DNA (aDNA) samples of both Anatomically Modern Humans and Neanderthals. Reconstructing genomes from aDNA using reference mapping presents numerous problems due to the unique nature of ancient samples, their degraded state, smaller read sizes and the limitations of current methodologies. The spurious alignments of reads to reference sequences (mapping) are a main source of false positives in aDNA assemblies and the assessment of signal-to-noise ratios is essential to differentiate bona fide reconstructions from random, noisy assemblies. Here, we analyzed the statistical distributions of viral genome assemblies, ancient and modern, and their respective random "mock" controls used to evaluate the signal-to-noise ratio. We tested if differences between real and random assemblies could be detected from their statistical distributions. Our analysis shows that the coverage distributions of (1) real viral aDNA assemblies of adenovirus (ADV), herpesvirus (HSV) and papillomavirus (HPV) do not follow power laws nor log-normal laws, (2) (ADV) and control aDNA assemblies are well approximated by log-normal laws, (3) negative control parvovirus B19 (real and random) follow a power law with infinite variance and (4) the mapDamage negative control with non-ancient DNA (modern ADV) and the mapDamage positive control (human mtDNA) are well approximated by the negative binomial distribution, consistent with the Lander-Waterman model. Our results show that the tails of the distributions of aDNA and their controls reveal the weight of random effects and can differentiate spurious assemblies, or false positives, from bona fide assemblies.

Virus Evolution in Prolonged Infections of Immunocompromised Individuals

BACKGROUND

Many viruses can cause persistent infection and/or viral shedding in immunocompromised hosts. This is a well-described occurrence not only with SARS-CoV-2 but for many other viruses as well. Understanding how viruses evolve and mutate in these patients and the global impact of this phenomenon is critical as the immunocompromised population expands.

CONTENT

In this review, we provide an overview of populations at risk for prolonged viral shedding, clinical manifestations of persistent viral infection, and methods of assessing viral evolution. We then review the literature on viral evolution in immunocompromised patients across an array of RNA viruses, including SARS-CoV-2, norovirus, influenza, and poliovirus, and discuss the global implications of persistent viral infections in these hosts.

SUMMARY

There is significant evidence for accelerated viral evolution and accumulation of mutations in antigenic sites in immunocompromised hosts across many viral pathogens. However, the implications of this phenomenon are not clear; while there are rare reports of transmission of these variants, they have not clearly been shown to predict disease outbreaks or have significant global relevance. Emerging methods including wastewater monitoring may provide a more sophisticated understanding of the impact of variants that evolve in immunocompromised hosts on the wider host population.

Lossless and reference-free compression of FASTQ/A files using GeneSqueeze

As sequencing becomes more accessible, there is an acute need for novel compression methods to efficiently store sequencing files. Omics analytics can leverage sequencing technologies to enhance biomedical research and individualize patient care, but sequencing files demand immense storage capabilities, particularly when sequencing is utilized for longitudinal studies. Addressing the storage challenges posed by these technologies is crucial for omics analytics to achieve their full potential. We present a novel lossless, reference-free compression algorithm, GeneSqueeze, that leverages the patterns inherent in the underlying components of FASTQ files to solve this need. GeneSqueeze's benefits include an auto-tuning compression protocol based on each file's distribution, lossless preservation of IUPAC nucleotides and read identifiers, and unrestricted FASTQ/A file attributes (i.e., read length, number of reads, or read identifier format). We compared GeneSqueeze to the general-purpose compressor, gzip, and to a domain-specific compressor, SPRING, to assess performance. Due to GeneSqueeze's current Python implementation, GeneSqueeze underperformed as compared to gzip and SPRING in the time domain. GeneSqueeze and gzip achieved 100% lossless compression across all elements of the FASTQ files (i.e. the read identifier, sequence, quality score and ' + ' lines). GeneSqueeze and gzip compressed all files losslessly, while both SPRING's traditional and lossless modes exhibited data loss of non-ACGTN IUPAC nucleotides and of metadata following the ' + ' on the separator line. GeneSqueeze showed up to three times higher compression ratios as compared to gzip, regardless of read length, number of reads, or file size, and had comparable compression ratios to SPRING across a variety of factors. Overall, GeneSqueeze represents a competitive and specialized compression method for FASTQ/A files containing nucleotide sequences. As such, GeneSqueeze has the potential to significantly reduce the storage and transmission costs associated with large omics datasets without sacrificing data integrity.

Establishing a Variant Allele Frequency Cutoff for Manual Curation of Medical Exome Sequencing Data

Medical exome sequencing pipelines consist of various preprocessing steps to prioritize credible causal variants before a pathologist or variant curation scientist manually interprets potential findings that are then reported to patients. The variant allele frequency (VAF), reported as the fraction of sequencing reads supporting a variant call, can be used to screen for technical artifacts, yet a specific filtering threshold has yet to be established. A total of 13,122 manually curated variants, sequenced from 289 patients using the Agilent SureSelect Focused Exome enrichment kit at the University of Kentucky Clinical Genomics laboratory from October 2019 to May 2023, were evaluated. Totals of 278 single-nucleotide polymorphisms (SNPs) and 3340 SNPs as technical artifacts are clinically reported. All reported variants had a VAF between 0.33 and 0.63, and 82% (2725/3340) of sequencing artifacts had a VAF of <0.33. It is proposed that removing SNPs in which the VAF is less than approximately 0.30 reduces manual curation time by approximately 20% while capturing all medically relevant variants in medical exome sequencing data sets.

Detection of single nucleotide variants in the mitochondrial genome of healthy mice and humans

Single nucleotide mutations in the mitochondrial genome are linked to aging in humans, primates, and rodents and cause neuromuscular diseases in humans. Load of mitochondrial variants in healthy tissues, however, is little known. Employing an unbiased detection method with no prior enzymatic amplification, we observed that the mitochondrial genome of embryonic, adult, and aged mouse brain from two different strains contains a diversity of single nucleotide variants with no age-related increase in abundance. We also observed de novo variants in single oocytes and adult liver arising at 5x10-5 and 8x10-6 substitutions per base pair per generation, respectively. Moreover, we found variants in human placenta of healthy donors that may reach up to 66% of all mitochondrial genome copies. Increase in the heteroplasmy of the variants observed in healthy mouse and human tissues and of those arisen de novo at high frequency in mice may lead to mitochondrial dysfunction and disease.

Spectrum and genotyping strategies of "dark" genetic matter in germline susceptibility genes of tumor syndromes

PURPOSE

Despite the widespread use of high-throughput genotyping strategies, certain mutation types remain understudied. We provide an overview of these often overlooked mutation types, with representative examples from common hereditary cancer syndromes.

METHODS

We conducted a comprehensive review of the literature and locus-specific variant databases to summarize the germline pathogenic variants discovered through non-routine genotyping methods. We evaluated appropriate detection and analysis methods tailored for these specific genetic aberrations. Additionally, we performed in silico splice predictions on deep intronic variants registered in the ClinVar database.

RESULTS

Our study suggests that, aside from founder mutations, most cases are sporadic. However, we anticipate a relatively high likelihood of splice effects for deep intronic variants. The findings underscore the significant clinical utility of genome sequencing techniques and the importance of applying relevant analysis methods.

Genetic Characterization of Kidney Failure of Unknown Etiology in Spain: Findings From the GENSEN Study

RATIONALE & OBJECTIVE

Chronic kidney disease of unknown etiology (CKDUE) is one of the main global causes of kidney failure. Genetic studies may identify an etiology in these patients, but few studies have implemented genetic testing of CKDUE in a population-based series of patients, which was the focus of the GENSEN Study.

STUDY DESIGN

Case series.

SETTINGS & PARTICIPANTS

818 patients aged≤45 years at 51 Spanish centers with CKDUE, and either an estimated glomerular filtration rate of<15mL/min/1.73m2 or treatment with maintenance dialysis or transplantation.

OBSERVATIONS

Genetic testing for 529 genes associated with inherited nephropathies using high-throughput sequencing (HTS). Pathogenic and/or likely pathogenic (P/LP) gene variants concordant with the inheritance pattern were detected in 203 patients (24.8%). Variants in type IV collagen genes were the most frequent (COL4A5, COL4A4, COL4A3; 35% of total gene variants), followed by NPHP1, PAX2, UMOD, MUC1, and INF2 (7.3%, 5.9%, 2.5%, 2.5%, and 2.5%, respectively). Overall, 87 novel variants classified as P/LP were identified. The top 5 most common previously undiagnosed diseases were Alport syndrome spectrum (35% of total positive reports), genetic podocytopathies (19%), nephronophthisis (11%), autosomal dominant tubulointerstitial kidney disease (7%), and congenital anomalies of the kidney and urinary tract (CAKUT, 5%). A family history of kidney disease was reported by 191 participants (23.3%) and by 65 of 203 patients (32.0%) with P/LP variants.

LIMITATIONS

Missing data, and selection bias resulting from voluntary enrollment.

CONCLUSIONS

Genomic testing with HTS identified a genetic cause of kidney disease in approximately one quarter of young patients with CKDUE and advanced kidney disease. These findings suggest that genetic studies are a potentially useful tool for the evaluation of people with CKDUE.

PLAIN-LANGUAGE SUMMARY

The cause of kidney disease is unknown for 1 in 5 patients requiring kidney replacement therapy, reflecting possible prior missed treatment opportunities. We assessed the diagnostic utility of genetic testing in children and adults aged≤45 years with either an estimated glomerular filtration rate of<15mL/min/1.73m2 or treatment with maintenance dialysis or transplantation. Genetic testing identified the cause of kidney disease in approximately 1 in 4 patients without a previously known cause of kidney disease, suggesting that genetic studies are a potentially useful tool for the evaluation of these patients.

Identification of molecular biomarkers associated with non-small-cell lung carcinoma (NSCLC) using whole-exome sequencing

ObjectivesSignificant progress has been made in the treatment of patients with pulmonary adenocarcinoma (ADCA) based on molecular profiling. However, no such molecular target exists for squamous cell carcinoma (SQCC). An exome sequence may provide new markers for personalized medicine for lung cancer patients of all subtypes. The current study aims to discover new genetic markers that can be used as universal biomarkers for non-small cell lung cancer (NSCLC).MethodsWES of 19 advanced NSCLC patients (10 ADCA and 9 SQCC) was performed using Illumina HiSeq 2000. Variant calling was performed using GATK HaplotypeCaller and then the impacts of variants on protein structure or function were predicted using SnpEff and ANNOVAR. The clinical impact of somatic variants in cancer was assessed using cancer archives. Somatic variants were further prioritized using a knowledge-driven variant interpretation approach. Sanger sequencing was used to validate functionally important variants.ResultsWe identified 24 rare single-nucleotide variants (SNVs) including 17 non-synonymous SNVs, and 7 INDELs in 18 genes possibly linked to lung carcinoma. Variants were classified as known somatic (n = 10), deleterious (n = 8), and variant of uncertain significance (n = 6). We found TBP and MPRIP genes exclusively associated with ADCA subtypes, FBOX6 with SQCC subtypes and GPRIN2, KCNJ18 and TEKT4 genes mutated in all the patients. The Sanger sequencing of 10 high-confidence somatic SNVs showed 100% concordance in 7 genes, and 80% concordance in the remaining 3 genes.ConclusionsOur bioinformatics analysis identified KCNJ18, GPRIN2, TEKT4, HRNR, FOLR3, ESSRA, CTBP2, MPRIP, TBP, and FBXO6 may contribute to progression in NSCLC and could be used as new biomarkers for the treatment. The mechanism by which GPRIN2, KCNJ12, and TEKT4 contribute to tumorigenesis is unclear, but our results suggest they may play an important role in NSCLC and it is worth investigating in future.

The potential clinical utility of Whole Genome Sequencing for patients with cancer: evaluation of a regional implementation of the 100,000 Genomes Project

BACKGROUND

The 100,000 Genomes Project established infrastructure for Whole Genome Sequencing (WGS) in the United Kingdom.

METHODS

A retrospective study of cancer patients recruited to the 100,000 Genomes Project by the West Midlands Genomics Medicine Centre, evaluating clinical relevance of results.

RESULTS

After excluding samples with no sequencing data (1678/4851; 34.6%), 3166 sample sets (germline and somatic) from 3067 participants were sequenced. Results of 1256 participants (41.0%) were interpreted (excluding participants who died (308/3067; 10.0%) or were clinically excluded (1503/3067; 49.0%)). Of these, 323 (25.7%) had no variants in genes which may alter management (Domain 1 genes). Of the remaining 933 participants, 552 (59.2%) had clinical recommendations made (718 recommendations in total). These included therapeutic recommendations (377/933; 40.4%), such as clinical trial, unlicensed or licensed therapies or high TMB recommendations, and germline variants warranting clinical genetics review (85/933; 9.1%). At the last follow up, 20.2% of all recommendations were followed (145/718). However, only a small proportion of therapeutic recommendations were followed (5.1%, 25/491).

CONCLUSIONS

The 100,000 Genomes Project has established infrastructure and regional experience to support personalised cancer care. The majority of those with successful sequencing had actionable variants. Ensuring GTAB recommendations are followed will maximise benefits for patients.

Targeted Variant Assessments of Human Endogenous Retroviral Regions in Whole Genome Sequencing Data Reveal Retroviral Variants Associated with Papillary Thyroid Cancer

Papillary thyroid cancer (PTC) is one of the fastest-growing cancers worldwide, lacking established causal factors or validated early diagnostics. Human endogenous retroviruses (HERVs), comprising 8% of human genomes, have potential as PTC biomarkers due to their comparably high baseline expression in healthy thyroid tissues, indicating homeostatic roles. However, HERV regions are often overlooked in genome-wide association studies because of their highly repetitive nature, low sequence coverage, and decreased sequencing quality. Using targeted whole-genome sequence analysis in conjunction with high sequencing depth to overcome methodological limitations, we identified associations of specific HERV variants with PTC. Analyzing WGS data from 138 patients with PTC generated through The Cancer Genome Atlas project and 2015 control samples from the 1000 Genomes Project, we examined the mutational variation in HERVs within a 20 kb radius of known cancer predisposition genes (CPGs) differentially expressed in PTC. We discovered 15 common and 13 rare germline HERV variants near or within 20 CPGs that distinguish patients with PTC from healthy controls. We identified intragenic-intronic HERV variants within RYR2, LRP1B, FN1, MET, TCRVB, UNC5D, TRPM3, CNTN5, CD70, RYR1, RUNX1, CRLF2, and PCDH1X, and three variants downstream of SERPINA1 and RUNX1T1. Sanger sequencing analyses of 20 thyroid and 5 non-thyroid cancer cell lines confirmed associations with PTC, particularly for MSTA HERV-L variant rs200077102 within the FN1 gene and HERV-L MLT1A LTR variant rs78588384 within the CNTN5 gene. Variant rs78588384, in particular, was shown in our analyses to be located within a POL2 binding site regulating an alternative transcript of CNTN5. In addition, we identified 16 variants that modified the poly(A) region in Alu elements, potentially altering the potential to retrotranspose. In conclusion, this study serves as a proof-of-concept for targeted variant analysis of HERV regions and establishes a basis for further exploration of HERVs in thyroid cancer development.

Genetic insights from a Brazilian cohort of aortopathies through targeted next-generation sequencing and FBN1 direct sequencing

Thoracic aortic diseases (or aortopathies) result from complex interactions between genetic and hemodynamic factors. Often clinically silent, these diseases can lead to lethal complications such as aortic dissection or rupture. This study focused on a Brazilian cohort of 79 individuals with thoracic aortic diseases and explored genetic factors through targeted next-generation sequencing (tNGS) of 15 priority genes and FBN1 direct sequencing. The majority of individuals had nonsyndromic aortopathy, with eight diagnosed with Marfan syndrome (MFS). Pathogenic or likely pathogenic variants (PV/LPV) were found in five genes, namely, FBN1, ACTA2, TGFBR2, MYLK, and SMAD3. Notably, novel variants in FBN1 were identified that contributed to Marfan-like phenotypes. The diagnostic yield for isolated aortopathies was 7.1%, which increased to 55.5% for syndromic cases. Variants of uncertain significance (VUS) were identified, emphasizing the need for further research and familial investigations to refine variant classifications. This study provides valuable insights into the genetic landscape of aortopathies in Brazil, aiding early diagnosis and personalized management.

Best practices for germline variant and DNA methylation analysis of second- and third-generation sequencing data

This comprehensive review provides insights and suggested strategies for the analysis of germline variants using second- and third-generation sequencing technologies (SGS and TGS). It addresses the critical stages of data processing, starting from alignment and preprocessing to quality control, variant calling, and the removal of artifacts. The document emphasized the importance of meticulous data handling, highlighting advanced methodologies for annotating variants and identifying structural variations and methylated DNA sites. Special attention is given to the inspection of problematic variants, a step that is crucial for ensuring the accuracy of the analysis, particularly in clinical settings where genetic diagnostics can inform patient care. Additionally, the document covers the use of various bioinformatics tools and software that enhance the precision and reliability of these analyses. It outlines best practices for the annotation of variants, including considerations for problematic genetic alterations such as those in the human leukocyte antigen region, runs of homozygosity, and mitochondrial DNA alterations. The document also explores the complexities associated with identifying structural variants and copy number variations, underscoring the challenges posed by these large-scale genomic alterations. The objective is to offer a comprehensive framework for researchers and clinicians, ensuring that genetic analyses conducted with SGS and TGS are both accurate and reproducible. By following these best practices, the document aims to increase the diagnostic accuracy for hereditary diseases, facilitating early diagnosis, prevention, and personalized treatment strategies. This review serves as a valuable resource for both novices and experts in the field, providing insights into the latest advancements and methodologies in genetic analysis. It also aims to encourage the adoption of these practices in diverse research and clinical contexts, promoting consistency and reliability across studies.

Actionable Structural Variant Detection via RNA-NGS and DNA-NGS in Patients With Advanced Non-Small Cell Lung Cancer

Importance

The National Comprehensive Cancer Network (NCCN) guidelines for non-small cell lung cancer suggest that RNA next-generation sequencing (NGS) may improve the detection of fusions and splicing variants compared with DNA-NGS alone. However, there is limited adoption of RNA-NGS in routine oncology clinical care today.

Objective

To analyze clinical evidence from a diverse cohort of patients with advanced lung adenocarcinoma and compare the detection of NCCN-recommended actionable structural variants (aSVs; fusions and splicing variants) via concurrent DNA and RNA-NGS vs DNA-NGS alone.

Design, Setting, and Participants

This multisite, retrospective cohort study examined patients sequenced between February 2021 and October 2023 within the deidentified, Tempus multimodal database, consisting of linked molecular and clinical data. Participants included patients with advanced lung adenocarcinoma and sufficient tissue sample quantities for both RNA-NGS and DNA-NGS testing.

Exposures

Received results from RNA-NGS and DNA-NGS solid-tissue profiling assays.

Main Outcomes and Measures

Detection rates of NCCN guideline-based structural variants (ALK, ROS1, RET and NTRK1/2/3 fusions, as well as MET exon 14 skipping splicing alterations) found uniquely by RNA-NGS.

Results

In the evaluable cohort of 5570 patients, median (IQR) age was 67.8 (61.3-75.4) years, and 2989 patients (53.7%) were female. The prevalence of actionable structural variants detected by either RNA-NGS or DNA-NGS was 8.8% (n = 491), with 86.7% (n = 426) of these detected by DNA-NGS. Concurrent RNA-NGS and DNA-NGS identified 15.3% more patients harboring aSVs compared with DNA-NGS alone (491 vs 426 patients, respectively), including 14.3% more patients harboring actionable fusions (376 vs 329 patients) and 18.6% more patients harboring MET exon 14 skipping alterations (115 vs 97 patients). There was no significant association between the assay used for aSV detection and aSV-targeted therapeutic adoption or clinical outcome. Emerging structural variants (eSVs) were found to have a combined prevalence to be 0.7%, with only 47.5% of eSVs detected by DNA-NGS.

Conclusions and Relevance

In this cohort study, the detection of structural variants via concurrent RNA-NGS and DNA-NGS was higher across multiple NCCN-guideline recommended biomarkers compared with DNA-NGS alone, suggesting that RNA-NGS should be routinely implemented in the care of patients with advanced NSCLC.

Next-generation data filtering in the genomics era

Genomic data are ubiquitous across disciplines, from agriculture to biodiversity, ecology, evolution and human health. However, these datasets often contain noise or errors and are missing information that can affect the accuracy and reliability of subsequent computational analyses and conclusions. A key step in genomic data analysis is filtering - removing sequencing bases, reads, genetic variants and/or individuals from a dataset - to improve data quality for downstream analyses. Researchers are confronted with a multitude of choices when filtering genomic data; they must choose which filters to apply and select appropriate thresholds. To help usher in the next generation of genomic data filtering, we review and suggest best practices to improve the implementation, reproducibility and reporting standards for filter types and thresholds commonly applied to genomic datasets. We focus mainly on filters for minor allele frequency, missing data per individual or per locus, linkage disequilibrium and Hardy-Weinberg deviations. Using simulated and empirical datasets, we illustrate the large effects of different filtering thresholds on common population genetics statistics, such as Tajima's D value, population differentiation (FST), nucleotide diversity (π) and effective population size (Ne).

A validated heart-specific model for splice-disrupting variants in childhood heart disease

BACKGROUND

Congenital heart disease (CHD) is the most common congenital anomaly. Almost 90% of isolated cases have an unexplained genetic etiology after clinical testing. Non-canonical splice variants that disrupt mRNA splicing through the loss or creation of exon boundaries are not routinely captured and/or evaluated by standard clinical genetic tests. Recent computational algorithms such as SpliceAI have shown an ability to predict such variants, but are not specific to cardiac-expressed genes and transcriptional isoforms.

METHODS

We used genome sequencing (GS) (n = 1101 CHD probands) and myocardial RNA-Sequencing (RNA-Seq) (n = 154 CHD and n = 43 cardiomyopathy probands) to identify and validate splice disrupting variants, and to develop a heart-specific model for canonical and non-canonical splice variants that can be applied to patients with CHD and cardiomyopathy. Two thousand five hundred seventy GS samples from the Medical Genome Reference Bank were analyzed as healthy controls.

RESULTS

Of 8583 rare DNA splice-disrupting variants initially identified using SpliceAI, 100 were associated with altered splice junctions in the corresponding patient myocardium affecting 95 genes. Using strength of myocardial gene expression and genome-wide DNA variant features that were confirmed to affect splicing in myocardial RNA, we trained a machine learning model for predicting cardiac-specific splice-disrupting variants (AUC 0.86 on internal validation). In a validation set of 48 CHD probands, the cardiac-specific model outperformed a SpliceAI model alone (AUC 0.94 vs 0.67 respectively). Application of this model to an additional 947 CHD probands with only GS data identified 1% patients with canonical and 11% patients with non-canonical splice-disrupting variants in CHD genes. Forty-nine percent of predicted splice-disrupting variants were intronic and > 10 bp from existing splice junctions. The burden of high-confidence splice-disrupting variants in CHD genes was 1.28-fold higher in CHD cases compared with healthy controls.

CONCLUSIONS

A new cardiac-specific in silico model was developed using complementary GS and RNA-Seq data that improved genetic yield by identifying a significant burden of non-canonical splice variants associated with CHD that would not be detectable through panel or exome sequencing.

Widespread mutagenesis and chromosomal instability shape somatic genomes in systemic sclerosis

Systemic sclerosis is a connective tissue disorder characterized by excessive fibrosis that primarily affects women, and can present as a multisystem pathology. Roughly 4-22% of patients with systemic sclerosis develop cancer, which drastically worsens prognosis. However, the mechanisms underlying systemic sclerosis initiation, propagation, and cancer development are poorly understood. We hypothesize that the inflammation and immune response associated with systemic sclerosis can trigger DNA damage, leading to elevated somatic mutagenesis, a hallmark of pre-cancerous tissues. To test our hypothesis, we culture clonal lineages of fibroblasts from the lung tissues of controls and systemic sclerosis patients and compare their mutation burdens and spectra. We find an overall increase in all major mutation types in systemic sclerosis samples compared to control lung samples, from small-scale events such as single base substitutions and insertions/deletions, to chromosome-level changes, including copy-number changes and structural variants. In the genomes of patients with systemic sclerosis, we find evidence of somatic hypermutation or kategis (typically only seen in cancer genomes), we identify mutation signatures closely resembling the error-prone translesion polymerase Polη activity, and observe an activation-induced deaminase-like mutation signature, which overlaps with genomic regions displaying kataegis.

Reversion of KPC-114 to KPC-2 in ceftazidime-avibactam- resistant/meropenem-susceptible Klebsiella pneumoniae ST11 is related to low mutation rates

Klebsiella pneumoniae strains that produce Klebsiella pneumoniae Carbapenemase (KPC) variants displaying resistance to ceftazidime-avibactam (CZA) often remain susceptible to meropenem (MEM), suggesting a potential therapeutic use of this carbapenem antibiotic. However, in vitro studies indicate that these sorts of strains can mutate becoming MEM-resistant, raising concerns about the effectiveness of carbapenems as treatment option. We have studied mutation rates occurring from the reversion of MEM-susceptible KPC-114 to MEM-resistant KPC-2, in CZA-resistant K. pneumoniae belonging to ST11. Two-step fluctuation assays (FAs) were conducted. In brief, initial cultures of KPC-114-producing K. pneumoniae showing 1 µg/mL MEM MIC were spread on Mueller-Hinton agar plates containing 2-8 µg/mL MEM. A second step of FA, at 4-16 µg/mL MEM was performed from a mutant colony obtained at 2 µg/mL MEM. Mutation rates were calculated using maximum likelihood estimation. Parental and mutant strains were sequenced by Illumina NextSeq, and mutations were predicted by variant-calling analysis. At 8 µg/mL MEM, mutants derived from parental CZA-resistant (MIC ≥ 64 µg/mL)/MEM-susceptible (MIC = 1 µg/mL) KPC-114-positive K. pneumoniae exhibited an accumulative mutation rate of 3.05 × 10-19 mutations/cell/generation, whereas at 16 µg/mL MEM an accumulative mutation rate of 1.33 × 10-19 mutations/cell/generation resulted in the reversion of KPC-114 (S181_P182 deletion) to KPC-2. These findings highlight that the reversion of MEM-susceptible KPC-114 to MEM-resistant KPC-2, in CZA-resistant K. pneumoniae ST11 is related to low mutation rates suggesting a low risk of therapeutic failure. In vivo investigations are necessary to confirm the clinical potential of MEM against CZA-resistant KPC variants.IMPORTANCEThe emergence of ceftazidime-avibactam (CZA) resistance among carbapenem-resistant Klebsiella pneumoniae is a major concern due to the limited therapeutic options. Strikingly, KPC mutations mediating CZA resistance are generally associated with meropenem susceptibility, suggesting a potential therapeutic use of this carbapenem antibiotic. However, the reversion of meropenem-susceptible to meropenem-resistant could be expected. Therefore, knowing the mutation rate related to this genetic event is essential to estimate the potential use of meropenem against CZA-resistant KPC-producing K. pneumoniae. In this study, we demonstrate, in vitro, that under high concentrations of meropenem, reversion of KPC-114 to KPC-2 in CZA-resistant/meropenem-susceptible K. pneumoniae belonging to the global high-risk ST11 is related to low mutation rates.

Human embryonic genetic mosaicism and its effects on development and disease

Nearly every mammalian cell division is accompanied by a mutational event that becomes fixed in a daughter cell. When carried forward to additional cell progeny, a clone of variant cells can emerge. As a result, mammals are complex mosaics of clones that are genetically distinct from one another. Recent high-throughput sequencing studies have revealed that mosaicism is common, clone sizes often increase with age and specific variants can affect tissue function and disease development. Variants that are acquired during early embryogenesis are shared by multiple cell types and can affect numerous tissues. Within tissues, variant clones compete, which can result in their expansion or elimination. Embryonic mosaicism has clinical implications for genetic disease severity and transmission but is likely an under-recognized phenomenon. To better understand its implications for mosaic individuals, it is essential to leverage research tools that can elucidate the mechanisms by which expanded embryonic variants influence development and disease.

Cancer associated variant enrichment CAVE, a gene agnostic approach to identify low burden variants in chronic lymphocytic leukemia

Intratumoral heterogeneity is an important clinical challenge because low burden clones expressing specific genetic alterations drive therapeutic resistance mechanisms. We have developed CAVE (cancer-associated variant enrichment), a gene-agnostic computational tool to identify specific enrichment of low-burden cancer driver variants in next-generation sequencing (NGS) data. For this study, CAVE was applied to TP53 in chronic lymphocytic leukemia (CLL) as a cancer model. Indeed, as TP53 mutations are part of treatment decision-making algorithms and low-burden variants are frequent, there is a need to distinguish true variants from background noise. Recommendations have been published for reliable calling of low-VAF variants of TP53 in CLL and the assessment of the background noise for each platform is essential for the quality of the testing. CAVE is able to detect specific enrichment of low-burden variants starting at variant allele frequencies (VAFs) as low as 0.3%. In silico TP53 dependent and independent analyses confirmed the true driver nature of all these variants. Orthogonal validation using either ddPCR or NGS analyses of follow-up samples confirmed variant identification. CAVE can be easily deployed in any cancer-related NGS workflow to detect the enrichment of low-burden variants of clinical interest.

Whole-exome sequencing to identify causative variants in juvenile sudden cardiac death

BACKGROUND

Juvenile sudden cardiac death (SCD) remains unexplained in approximately 40% of cases, leading to a significant emotional burden for the victims' families and society. Comprehensive investigations are essential to uncover its elusive causes and enable cascade family screening. This study aimed to enhance the identification of likely causative variants in juvenile SCD cases (age ≤ 50 years), particularly when autopsy findings are inconclusive.

RESULTS

Autopsy revealed diagnostic structural abnormalities in 46%, non-diagnostic findings in 23%, and structurally normal hearts in 31% of cases. Whole-exome sequencing (WES), refined through a customized virtual gene panel was used to identify variants. These variants were then evaluated using a multidisciplinary approach and a structured variant prioritization scheme. Our extended approach identified likely causative variants in 69% of cases, outperforming the diagnostic yields of both the cardio panel and standard susceptibility gene analysis (50% and 16%, respectively). The extended cardio panel achieved an 80% diagnostic yield in cases with structurally normal hearts, demonstrating its efficacy in challenging scenarios. Notably, half of the positive cases harboured a single variant, while the remainder had two or more variants.

CONCLUSION

This study highlights the efficacy of a multidisciplinary approach employing WES and a tailored virtual gene panel to elucidate the aetiology of juvenile SCD. The findings support the expansion of genetic testing using tailored gene panels and prioritization schemes as part of routine autopsy evaluations to improve the identification of causative variants and potentially facilitate early diagnosis in first-degree relatives.

Discovery of Novel TULP4/ACTN4/EWSR1/ACTB::MYB and ESRRG::DNM3 Fusions Expands Molecular Landscape of Adenoid Cystic Carcinoma Beyond Fusions Between MYB/MYBL1 and NFIB Genes

Adenoid cystic carcinoma (AdCC) is one of the most common salivary gland malignancies and occurs in all major and minor salivary gland and seromucous gland sites. AdCCs of salivary gland origin have long been categorized as fusion-defined carcinomas owing to the almost consistent presence of fusion genes MYB::NFIB, or less commonly MYBL1::NFIB. We collected a cohort of 95 cases of AdCC, which were largely characterized by canonical fusions MYB::NFIB (49 cases) or MYBL1::NFIB (9 cases). In additional 11 cases of AdCC, rearrangements in MYB or NFIB genes were detected by FISH. In addition, NGS revealed novel noncanonical fusion transcripts EWSR1::MYB; ACTB::MYB; ESRRG::DNM3, MYB::TULP4, and ACTN4::MYB, each of them in 1 case. The tumors that showed noncanonical fusions had features of metatypical AdCC with a diverse architecture, lobulated multinodular growth pattern, and hypercellular peripheral palisading of nuclei (2 cases), tubular hypereosinophilia (2 cases), and pale eosinophilic to vacuolated (bubbly) cytoplasm (3 cases). Our study documented 3 cases of AdCC of salivary glands harboring novel gene fusions TULP4::MYB, ACTN4::MYB, and ACTB::MYB, in 1 case each, which have not been described before. A rare EWSR1::MYB fusion was detected in 1 case. Moreover, 1 case of sinonasal metatypical AdCC showed EWSR1 rearrangement detected by FISH. Also, 1 case with an ESRRG::DNM3 fusion of unknown significance is described in this study. These discoveries illustrate how broad molecular profiling will expand understanding of changes in known entities.

Low-grade parental gonosomal mosaicism in CHD2 siblings with Smith-Magenis-like syndrome

Loss-of-function CHD2 (chromodomain helicase DNA-binding protein 2) mutations are associated with a spectrum of neurodevelopmental disorders often including early-onset generalized seizures, photosensitivity, and epileptic encephalopathies. Patients show psychomotor delay/intellectual disability (ID), autistic features, and behavior disorders, such as aggression and impulsivity. Most reported cases are sporadic with description of germline mosaicism only in two families. We detect the first case of parental gonosomal CHD2 mosaicism disclosed by two brothers showing mild ID, born to healthy parents. The eldest brother has a history of drug-controlled generalized tonic-clonic seizures and displays sleep disorder and aggressive behavior suggestive of Smith-Magenis syndrome (SMS). Analysis of brothers' DNAs by next-generation sequencing (NGS) custom gene panel for pediatric epilepsy and/or ID disclosed in both the same pathogenic CHD2 variant. Additional NGS experiment on genomic DNA from parents' peripheral blood and from buccal swab raised the suspicion of low-grade gonosomal mosaicism in the unaffected mother subsequently confirmed by digital polymerase chain reaction (dPCR). This report underlines as worthwhile CHD2 screening in individuals presenting ID/developmental delay, with/without epilepsy, and behavior and sleep disorders suggestive of SMS. Detecting a CHD2 variant should prime testing probands' parents by NGS coupled to dPCR on different tissues to exclude/confirm gonosomal mosaicism and define the recurrence risk.

Temporal evolution and inter-patient heterogeneity in primary and recurrent head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinomas (HNSCCs) are heterogeneous in terms of origin and aetiology. In addition, there is uncertainty about the genetic evolution from initial diagnosis to recurrence after primary treatments and further disease progression following systemic treatment. Changes in the genetic profile have implications on the selection of appropriate treatments for patients, especially in the era of targeted therapies and immunotherapies.

METHODS

We analysed a cohort of nine HNSCC patients with metachronous recurrence. All patients had paired primary and recurrent samples suitable for whole-exome sequencing, while transcriptomic data from seven patients could be analysed (multiple recurrent samples collected at different time points were available for three patients).

RESULTS

At the genomic level, the recurrences shared a fraction of the somatic single nucleotide variants (SNVs) with the index primary tumours, but they also acquired many additional mutations, while losing only a few others. A similar behaviour was also observed when examining the changes of mutational signatures between primary and recurrent samples. Overall, recurrences appeared thus more genetically diverse than the respective primary tumours. The transcriptomic analysis showed that recurrent samples had lower immune cell presence, which was also confirmed by the multiplex immunofluorescence (IF) histology assays performed on the PhenoCycler platform. Several genes related to immune response were significantly downregulated compared to the primary samples.

CONCLUSIONS

Our results underline the importance of analysing multiple samples per patient to obtain a more complete picture of the patient's tumour and advocate a re-biopsy in the event of recurrence and treatment failure, in order to select the most appropriate therapeutic strategy.

Genomic Insights into Idiopathic Granulomatous Mastitis through Whole-Exome Sequencing: A Case Report of Eight Patients

Idiopathic granulomatous mastitis (IGM) is a rare condition characterised by chronic inflammation and granuloma formation in the breast. The aetiology of IGM is unclear. By focusing on the protein-coding regions of the genome, where most disease-related mutations often occur, whole-exome sequencing (WES) is a powerful approach for investigating rare and complex conditions, like IGM. We report WES results on paired blood and tissue samples from eight IGM patients. Samples were processed using standard genomic protocols. Somatic variants were called with two analytical pipelines: nf-core/sarek with Strelka2 and GATK4 with Mutect2. Our WES study of eight patients did not find evidence supporting a clear genetic component. The discrepancies between variant calling algorithms, along with the considerable genetic heterogeneity observed amongst the eight IGM cases, indicate that common genetic drivers are not readily identifiable. With only three genes, CHIT1, CEP170, and CTR9, recurrently altering in multiple cases, the genetic basis of IGM remains uncertain. The absence of validation for somatic variants by Sanger sequencing raises further questions about the role of genetic mutations in the disease. Other potential contributors to the disease should be explored.

DeepSomatic: Accurate somatic small variant discovery for multiple sequencing technologies

Somatic variant detection is an integral part of cancer genomics analysis. While most methods have focused on short-read sequencing, long-read technologies now offer potential advantages in terms of repeat mapping and variant phasing. We present DeepSomatic, a deep learning method for detecting somatic SNVs and insertions and deletions (indels) from both short-read and long-read data, with modes for whole-genome and exome sequencing, and able to run on tumor-normal, tumor-only, and with FFPE-prepared samples. To help address the dearth of publicly available training and benchmarking data for somatic variant detection, we generated and make openly available a dataset of five matched tumor-normal cell line pairs sequenced with Illumina, PacBio HiFi, and Oxford Nanopore Technologies, along with benchmark variant sets. Across samples and technologies (short-read and long-read), DeepSomatic consistently outperforms existing callers, particularly for indels.

Mutational Landscapes of Normal Skin and Their Potential Implications in the Development of Skin Cancer: A Comprehensive Narrative Review

Recent evidence suggests that physiologically normal skin harbors pervasive mutant clones with cancer drivers. Normal skin has the highest burden of somatic mutations due to persistent ultraviolet exposure throughout life. The mutation burden exponentially increases with age and is further modified by skin site, sun-damage history, and skin phototype. Driver gene profiles in normal skin are similar to those in cutaneous squamous cell carcinoma where NOTCH family, FAT family, and TP53 are consistently reported, while other reported profiles include PPM1D, KMT2D, ASXL1, and RBM10. Normal skin seldom harbors canonical hotspot mutations with therapeutic relevance. The pathologic role of mutant clones with cancer drivers in normal skin is classically considered precursors for skin cancer; however, recent evidence also suggests their putative cancer-protective role. Copy number alterations and other structural variants are rare in normal skin with loss in 9q region encompassing NOTCH1 being the most common. Study methodologies should be carefully designed to obtain an adequate number of cells for sequencing, and a comparable number of cells and read depth across samples. In conclusion, this review provides mutational landscapes of normal skin and discusses their potential implications in the development of skin cancer, highlighting the role of driver genes in early malignant progression.

Utility analyses of AVITI sequencing chemistry

BACKGROUND

DNA sequencing is a critical tool in modern biology. Over the last two decades, it has been revolutionized by the advent of massively parallel sequencing, leading to significant advances in the genome and transcriptome sequencing of various organisms. Nevertheless, challenges with accuracy, lack of competitive options and prohibitive costs associated with high throughput parallel short-read sequencing persist.

RESULTS

Here, we conduct a comparative analysis using matched DNA and RNA short-reads assays between Element Biosciences' AVITI and Illumina's NextSeq 550 chemistries. Similar comparisons were evaluated for synthetic long-read sequencing for RNA and targeted single-cell transcripts between the AVITI and Illumina's NovaSeq 6000. For both DNA and RNA short-read applications, the study found that the AVITI produced significantly higher per sequence quality scores. For PCR-free DNA libraries, we observed an average 89.7% lower experimentally determined error rate when using the AVITI chemistry, compared to the NextSeq 550. For short-read RNA quantification, AVITI platform had an average of 32.5% lower error rate than that for NextSeq 550. With regards to synthetic long-read mRNA and targeted synthetic long read single cell mRNA sequencing, both platforms' respective chemistries performed comparably in quantification of genes and isoforms. The AVITI displayed a marginally lower error rate for long reads, with fewer chemistry-specific errors and a higher mutation detection rate.

CONCLUSION

These results point to the potential of the AVITI platform as a competitive candidate in high-throughput short read sequencing analyses when juxtaposed with the Illumina NextSeq 550.

Tumor Neoepitope-Based Vaccines: A Scoping Review on Current Predictive Computational Strategies

Therapeutic cancer vaccines have been considered in recent decades as important immunotherapeutic strategies capable of leading to tumor regression. In the development of these vaccines, the identification of neoepitopes plays a critical role, and different computational methods have been proposed and employed to direct and accelerate this process. In this context, this review identified and systematically analyzed the most recent studies published in the literature on the computational prediction of epitopes for the development of therapeutic vaccines, outlining critical steps, along with the associated program's strengths and limitations. A scoping review was conducted following the PRISMA extension (PRISMA-ScR). Searches were performed in databases (Scopus, PubMed, Web of Science, Science Direct) using the keywords: neoepitope, epitope, vaccine, prediction, algorithm, cancer, and tumor. Forty-nine articles published from 2012 to 2024 were synthesized and analyzed. Most of the identified studies focus on the prediction of epitopes with an affinity for MHC I molecules in solid tumors, such as lung carcinoma. Predicting epitopes with class II MHC affinity has been relatively underexplored. Besides neoepitope prediction from high-throughput sequencing data, additional steps were identified, such as the prioritization of neoepitopes and validation. Mutect2 is the most used tool for variant calling, while NetMHCpan is favored for neoepitope prediction. Artificial/convolutional neural networks are the preferred methods for neoepitope prediction. For prioritizing immunogenic epitopes, the random forest algorithm is the most used for classification. The performance values related to the computational models for the prediction and prioritization of neoepitopes are high; however, a large part of the studies still use microbiome databases for training. The in vitro/in vivo validations of the predicted neoepitopes were verified in 55% of the analyzed studies. Clinical trials that led to successful tumor remission were identified, highlighting that this immunotherapeutic approach can benefit these patients. Integrating high-throughput sequencing, sophisticated bioinformatics tools, and rigorous validation methods through in vitro/in vivo assays as well as clinical trials, the tumor neoepitope-based vaccine approach holds promise for developing personalized therapeutic vaccines that target specific tumor cancers.

Utility Analyses of AVITI Sequencing Chemistry

Background

DNA sequencing is a critical tool in modern biology. Over the last two decades, it has been revolutionized by the advent of massively parallel sequencing, leading to significant advances in the genome and transcriptome sequencing of various organisms. Nevertheless, challenges with accuracy, lack of competitive options and prohibitive costs associated with high throughput parallel short-read sequencing persist.

Results

Here, we conduct a comparative analysis using matched DNA and RNA short-reads assays between Element Biosciences' AVITI and Illumina's NextSeq 550 chemistries. Similar comparisons were evaluated for synthetic long-read sequencing for RNA and targeted single-cell transcripts between the AVITI and Illumina's NovaSeq 6000. For both DNA and RNA short-read applications, the study found that the AVITI produced significantly higher per sequence quality scores. For PCR-free DNA libraries, we observed an average 89.7% lower experimentally determined error rate when using the AVITI chemistry, compared to the NextSeq 550. For short-read RNA quantification, AVITI platform had an average of 32.5% lower error rate than that for NextSeq 550. With regards to synthetic long-read mRNA and targeted synthetic long read single cell mRNA sequencing, both platforms' respective chemistries performed comparably in quantification of genes and isoforms. The AVITI displayed a marginally lower error rate for long reads, with fewer chemistry-specific errors and a higher mutation detection rate.

Conclusion

These results point to the potential of the AVITI platform as a competitive candidate in high-throughput short read sequencing analyses when juxtaposed with the Illumina NextSeq 550.

Genomic Mosaicism of the Brain: Origin, Impact, and Utility

Genomic mosaicism describes the phenomenon where some but not all cells within a tissue harbor unique genetic mutations. Traditionally, research focused on the impact of genomic mosaicism on clinical phenotype-motivated by its involvement in cancers and overgrowth syndromes. More recently, we increasingly shifted towards the plethora of neutral mosaic variants that can act as recorders of cellular lineage and environmental exposures. Here, we summarize the current state of the field of genomic mosaicism research with a special emphasis on our current understanding of this phenomenon in brain development and homeostasis. Although the field of genomic mosaicism has a rich history, technological advances in the last decade have changed our approaches and greatly improved our knowledge. We will provide current definitions and an overview of contemporary detection approaches for genomic mosaicism. Finally, we will discuss the impact and utility of genomic mosaicism.

Skeletal abnormalities, pediatric-onset severe osteoporosis, and multiple fragility fractures in a patient with a novel CTNNB1 de novo variant

We report a case of a patient with a de novo germline heterozygous truncating variant of CTNNB1 gene (c.2172del, p.Tyr724Ter) causing neurodevelopmental disorder with spastic diplegia and visual defects syndrome (NEDSDV) associated with a new clinical feature - severe pediatric-onset osteoporosis and multiple fractures. A functional effect of the identified variant was demonstrated using adipose-tissue derived primary mesenchymal stem cells, where we detected the alteration of CTNNB1mRNA and β-catenin protein levels using real-time PCR and Western blot analysis.

Analysis of somatic mutations in whole blood from 200,618 individuals identifies pervasive positive selection and novel drivers of clonal hematopoiesis

Human aging is marked by the emergence of a tapestry of clonal expansions in dividing tissues, particularly evident in blood as clonal hematopoiesis (CH). CH, linked to cancer risk and aging-related phenotypes, often stems from somatic mutations in a set of established genes. However, the majority of clones lack known drivers. Here we infer gene-level positive selection in whole blood exomes from 200,618 individuals in UK Biobank. We identify 17 additional genes, ZBTB33, ZNF318, ZNF234, SPRED2, SH2B3, SRCAP, SIK3, SRSF1, CHEK2, CCDC115, CCL22, BAX, YLPM1, MYD88, MTA2, MAGEC3 and IGLL5, under positive selection at a population level, and validate this selection pattern in 10,837 whole genomes from single-cell-derived hematopoietic colonies. Clones with mutations in these genes grow in frequency and size with age, comparable to classical CH drivers. They correlate with heightened risk of infection, death and hematological malignancy, highlighting the significance of these additional genes in the aging process.

Unveiling microbial diversity: harnessing long-read sequencing technology

Long-read sequencing has recently transformed metagenomics, enhancing strain-level pathogen characterization, enabling accurate and complete metagenome-assembled genomes, and improving microbiome taxonomic classification and profiling. These advancements are not only due to improvements in sequencing accuracy, but also happening across rapidly changing analysis methods. In this Review, we explore long-read sequencing's profound impact on metagenomics, focusing on computational pipelines for genome assembly, taxonomic characterization and variant detection, to summarize recent advancements in the field and provide an overview of available analytical methods to fully leverage long reads. We provide insights into the advantages and disadvantages of long reads over short reads and their evolution from the early days of long-read sequencing to their recent impact on metagenomics and clinical diagnostics. We further point out remaining challenges for the field such as the integration of methylation signals in sub-strain analysis and the lack of benchmarks.