SVDF: enhancing structural variation detect from long-read sequencing via automatic filtering strategies.

Structural variation (SV) is an important form of genomic variation that influences gene function and expression by altering the structure of the genome. Although long-read data have been proven to better characterize SVs, SVs detected from noisy long-read data still include a considerable portion of false-positive calls. To accurately detect SVs in long-read data, we present SVDF, a method that employs a learning-based noise filtering strategy and an SV signature-adaptive clustering algorithm, for effectively reducing the likelihood of false-positive events. Benchmarking results from multiple orthogonal experiments demonstrate that, across different sequencing platforms and depths, SVDF achieves higher calling accuracy for each sample compared to several existing general SV calling tools. We believe that, with its meticulous and sensitive SV detection capability, SVDF can bring new opportunities and advancements to cutting-edge genomic research.

A foundational large language model for edible plant genomes.

Significant progress has been made in the field of plant genomics, as demonstrated by the increased use of high-throughput methodologies that enable the characterization of multiple genome-wide molecular phenotypes. These findings have provided valuable insights into plant traits and their underlying genetic mechanisms, particularly in model plant species. Nonetheless, effectively leveraging them to make accurate predictions represents a critical step in crop genomic improvement. We present AgroNT, a foundational large language model trained on genomes from 48 plant species with a predominant focus on crop species. We show that AgroNT can obtain state-of-the-art predictions for regulatory annotations, promoter/terminator strength, tissue-specific gene expression, and prioritize functional variants. We conduct a large-scale in silico saturation mutagenesis analysis on cassava to evaluate the regulatory impact of over 10 million mutations and provide their predicted effects as a resource for variant characterization. Finally, we propose the use of the diverse datasets compiled here as the Plants Genomic Benchmark (PGB), providing a comprehensive benchmark for deep learning-based methods in plant genomic research. The pre-trained AgroNT model is publicly available on HuggingFace at https://huggingface.co/InstaDeepAI/agro-nucleotide-transformer-1b  for future research purposes.

Unbiasedly decoding the tumor microenvironment with single-cell multiomics analysis in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a poor prognosis and limited therapeutic options. Research on the tumor microenvironment (TME) of PDAC has propelled the development of immunotherapeutic and targeted therapeutic strategies with a promising future. The emergence of single-cell sequencing and mass spectrometry technologies, coupled with spatial omics, has collectively revealed the heterogeneity of the TME from a multiomics perspective, outlined the development trajectories of cell lineages, and revealed important functions of previously underrated myeloid cells and tumor stroma cells. Concurrently, these findings necessitated more refined annotations of biological functions at the cell cluster or single-cell level. Precise identification of all cell clusters is urgently needed to determine whether they have been investigated adequately and to identify target cell clusters with antitumor potential, design compatible treatment strategies, and determine treatment resistance. Here, we summarize recent research on the PDAC TME at the single-cell multiomics level, with an unbiased focus on the functions and potential classification bases of every cellular component within the TME, and look forward to the prospects of integrating single-cell multiomics data and retrospectively reusing bulk sequencing data, hoping to provide new insights into the PDAC TME.

Clinical and genomic features of Mycobacterium avium complex: a multi-national European study.

BACKGROUND: The Mycobacterium avium complex (MAC) comprises the most frequent non-tuberculous mycobacteria (NTM) in Central Europe and currently includes twelve species. M. avium (MAV), M. intracellulare subsp. intracellulare (MINT), and M. intracellulare subsp. chimaera (MCH) are clinically most relevant. However, the population structure and genomic landscape of MAC linked with potential pathobiological differences remain little investigated. METHODS: Whole genome sequencing (WGS) was performed on a multi-national set of MAC isolates from Germany, France, and Switzerland. Phylogenetic analysis was conducted, as well as plasmids, resistance, and virulence genes predicted from WGS data. Data was set into a global context with publicly available sequences. Finally, detailed clinical characteristics were associated with genomic data in a subset of the cohort. RESULTS: Overall, 610 isolates from 465 patients were included. The majority could be assigned to MAV (n = 386), MCH (n = 111), and MINT (n = 77). We demonstrate clustering with less than 12 SNPs distance of isolates obtained from different patients in all major MAC species and the identification of trans-European or even trans-continental clusters when set into relation with 1307 public sequences. However, none of our MCH isolates clustered closely with the heater-cooler unit outbreak strain Zuerich-1. Known plasmids were detected in MAV (325/1076, 30.2%), MINT (62/327, 19.0%), and almost all MCH-isolates (457/463, 98.7%). Predicted resistance to aminoglycosides or macrolides was rare. Overall, there was no direct link between phylogenomic grouping and clinical manifestations, but MCH and MINT were rarely found in patients with extra-pulmonary disease (OR 0.12 95% CI 0.04-0.28, p < 0.001 and OR 0.11 95% CI 0.02-0.4, p = 0.004, respectively) and MCH was negatively associated with fulfillment of the ATS criteria when isolated from respiratory samples (OR 0.28 95% CI 0.09-0.7, p = 0.011). With 14 out of 43 patients with available serial isolates, co-infections or co-colonizations with different strains or even species of the MAC were frequent (32.6%). CONCLUSIONS: This study demonstrates clustering and the presence of plasmids in a large proportion of MAC isolates in Europe and in a global context. Future studies need to urgently define potential ways of transmission of MAC isolates and the potential involvement of plasmids in virulence.

Easing genomic surveillance: A comprehensive performance evaluation of long-read assemblers across multi-strain mixture data of HIV-1 and Other pathogenic viruses for constructing a user-friendly bioinformatic pipeline.

Background: Determining the appropriate computational requirements and software performance is essential for efficient genomic surveillance. The lack of standardized benchmarking complicates software selection, especially with limited resources. Methods: We developed a containerized benchmarking pipeline to evaluate seven long-read assemblers-Canu, GoldRush, MetaFlye, Strainline, HaploDMF, iGDA, and RVHaplo-for viral haplotype reconstruction, using both simulated and experimental Oxford Nanopore sequencing data of HIV-1 and other viruses. Benchmarking was conducted on three computational systems to assess each assembler's performance, utilizing QUAST and BLASTN for quality assessment. Results: Our findings show that assembler choice significantly impacts assembly time, with CPU and memory usage having minimal effect. Assembler selection also influences the size of the contigs, with a minimum read length of 2,000 nucleotides required for quality assembly. A 4,000-nucleotide read length improves quality further. Canu was efficient among de novo assemblers but not suitable for multi-strain mixtures, while GoldRush produced only consensus assemblies. Strainline and MetaFlye were suitable for metagenomic sequencing data, with Strainline requiring high memory and MetaFlye operable on low-specification machines. Among reference-based assemblers, iGDA had high error rates, RVHaplo showed the best runtime and accuracy but became ineffective with similar sequences, and HaploDMF, utilizing machine learning, had fewer errors with a slightly longer runtime. Conclusions: The HIV-64148 pipeline, containerized using Docker, facilitates easy deployment and offers flexibility to select from a range of assemblers to match computational systems or study requirements. This tool aids in genome assembly and provides valuable information on HIV-1 sequences, enhancing viral evolution monitoring and understanding.

The "Investigating and translating genomic evidence for public health response to SARS-CoV-2 (INSIDE SARS-CoV-2)" project - Network of excellence. Commentary.

The "Investigating and translating genomic evidence for public health response to SARS-CoV-2 (INSIDE SARS-CoV-2)" project is part of the initiative "Joint science and technology cooperation call for joint project proposals for the years 2021-2023" promoted by the Italian Ministry of Foreign Affairs and International Cooperation (MAECI) and the Republic of India. To start the project activities, the pandemic response and the epidemiological situation in Italy and in India, together with the genomic surveillance strategies for SARS-CoV-2 virus in the two countries, are here described.

Pangenome graph layout by Path-Guided Stochastic Gradient Descent.

MOTIVATION: The increasing availability of complete genomes demands for models to study genomic variability within entire populations. Pangenome graphs capture the full genomic similarity and diversity between multiple genomes. In order to understand them, we need to see them. For visualization, we need a human-readable graph layout: a graph embedding in low (e.g. two) dimensional depictions. Due to a pangenome graph's potential excessive size, this is a significant challenge. RESULTS: In response, we introduce a novel graph layout algorithm: the Path-Guided Stochastic Gradient Descent (PG-SGD). PG-SGD uses the genomes, represented in the pangenome graph as paths, as an embedded positional system to sample genomic distances between pairs of nodes. This avoids the quadratic cost seen in previous versions of graph drawing by SGD. We show that our implementation efficiently computes the low-dimensional layouts of gigabase-scale pangenome graphs, unveiling their biological features. AVAILABILITY AND IMPLEMENTATION: We integrated PG-SGD in ODGI which is released as free software under the MIT open source license. Source code is available at https://github.com/pangenome/odgi.

Low-input PacBio sequencing generates high-quality individual fly genomes and characterizes mutational processes.

Long-read sequencing, exemplified by PacBio, revolutionizes genomics, overcoming challenges like repetitive sequences. However, the high DNA requirement ( > 1 µg) is prohibitive for small organisms. We develop a low-input (100 ng), low-cost, and amplification-free library-generation method for PacBio sequencing (LILAP) using Tn5-based tagmentation and DNA circularization within one tube. We test LILAP with two Drosophila melanogaster individuals, and generate near-complete genomes, surpassing preexisting single-fly genomes. By analyzing variations in these two genomes, we characterize mutational processes: complex transpositions (transposon insertions together with extra duplications and/or deletions) prefer regions characterized by non-B DNA structures, and gene conversion of transposons occurs on both DNA and RNA levels. Concurrently, we generate two complete assemblies for the endosymbiotic bacterium Wolbachia in these flies and similarly detect transposon conversion. Thus, LILAP promises a broad PacBio sequencing adoption for not only mutational studies of flies and their symbionts but also explorations of other small organisms or precious samples.

Unveiling the microevolution of antimicrobial resistance in selected Pseudomonas aeruginosa isolates from Egyptian healthcare settings: A genomic approach.

The incidence of Pseudomonas aeruginosa infections in healthcare environments, particularly in low-and middle-income countries, is on the rise. The purpose of this study was to provide comprehensive genomic insights into thirteen P. aeruginosa isolates obtained from Egyptian healthcare settings. Phenotypic analysis of the antimicrobial resistance profile and biofilm formation were performed using minimum inhibitory concentration and microtiter plate assay, respectively. Whole genome sequencing was employed to identify sequence typing, resistome, virulome, and mobile genetic elements. Our findings indicate that 92.3% of the isolates were classified as extensively drug-resistant, with 53.85% of these demonstrating strong biofilm production capabilities. The predominant clone observed in the study was ST773, followed by ST235, both of which were associated with the O11 serotype. Core genome multi-locus sequence typing comparison of these clones with global isolates suggested their potential global expansion and adaptation. A significant portion of the isolates harbored Col plasmids and various MGEs, all of which were linked to antimicrobial resistance genes. Single nucleotide polymorphisms in different genes were associated with the development of antimicrobial resistance in these isolates. In conclusion, this pilot study underscores the prevalence of extensively drug-resistant P. aeruginosa isolates and emphasizes the role of horizontal gene transfer facilitated by a diverse array of mobile genetic elements within various clones. Furthermore, specific insertion sequences and mutations were found to be associated with antibiotic resistance.

Genetic and genomic analysis of Belgian Blue's susceptibility for psoroptic mange.

BACKGROUND: Psoroptic mange, caused by Psoroptes ovis mites, is affecting Belgian Blue cattle's welfare and production potential. The Belgian Blue cattle-known for its high degree of muscling, low feed conversion ratio and high beef quality-is highly susceptible for this disease. RESULTS: In this study, we phenotyped 1975 Belgian Blue cattle from more than 100 different groups on commercial beef farms for their psoroptic mange susceptibility. Substantial individual differences were observed within these management groups, with lesion extent differences up to ± 15%. Animal models showed that estimated heritabilities were low for lesion extent and severe lesion extent (0.07 and 0.09, respectively) and 0.12 for the number of mites. A genome wide association study for mange susceptibility revealed signals on BTA6, BTA11, BTA15 and BTA24. In these regions, candidate genes GBA3, RAG2, and TRAF6 were identified. CONCLUSIONS: Despite the challenges in phenotyping for psoroptic mange due to the timing of screening, the continuous evolution of lesions and different management conditions, we successfully conducted a study on the genetic susceptibility to psoroptic mange in Belgian Blue cattle. Our results clearly indicate that psoroptic mange is under polygenic control and the underlying candidate genes should be studied more thoroughly. This is the first study providing candidate genes for this complex disease. These results are already valuable for Belgian Blue breeding, however, further research is needed to unravel the architecture of this disease and to identify causal mutations.

Unraveling the genomic secrets of Tritonibacter mobilis AK171: a plant growth-promoting bacterium isolated from Avicennia marina.

The scarcity of freshwater resources resulting in a significant yield loss presents a pressing challenge in agriculture. To address this issue, utilizing abundantly available saline water could offer a smart solution. In this study, we demonstrate that the genome sequence rhizosphere bacterium Tritonibacter mobilis AK171, a halophilic marine bacterium recognized for its ability to thrive in saline and waterlogged environments, isolated from mangroves, has the remarkable ability to enable plant growth using saline irrigation. AK171 is characterized as rod-shaped cells, displays agile movement in free-living conditions, and adopts a rosette arrangement in static media. Moreover, The qualitative evaluation of PGP traits showed that AK171 could produce siderophores and IAA but could not solubilize phosphate nor produce hydrolytic enzymes it exhibits a remarkable tolerance to high temperatures and salinity. In this study, we conducted a comprehensive genome sequence analysis of T. mobilis AK171 to unravel the genetic mechanisms underlying its plant growth-promoting abilities in such challenging conditions. Our analysis revealed diverse genes and pathways involved in the bacterium's adaptation to salinity and waterlogging stress. Notably, T. mobilis AK171 exhibited a high level of tolerance to salinity and waterlogging through the activation of stress-responsive genes and the production of specific enzymes and metabolites. Additionally, we identified genes associated with biofilm formation, indicating its potential role in establishing symbiotic relationships with host plants. Furthermore, our analysis unveiled the presence of genes responsible for synthesizing antimicrobial compounds, including tropodithietic acid (TDA), which can effectively control phytopathogens. This genomic insight into T. mobilis AK171 provides valuable information for understanding the molecular basis of plant-microbial interactions in saline and waterlogged environments. It offers potential applications for sustainable agriculture in challenging conditions.

Impact of genomic and epigenomic alterations of multigene on a multicancer pedigree.

BACKGROUND: Germline mutations have been identified in a small number of hereditary cancers, but the genetic predisposition for many familial cancers remains to be elucidated. METHODS: This study identified a Chinese pedigree that presented different cancers (breast cancer, BRCA; adenocarcinoma of the esophagogastric junction, AEG; and B-cell acute lymphoblastic leukemia, B-ALL) in each of the three generations. Whole-genome sequencing and whole-exome sequencing were performed on peripheral blood or bone marrow and cancer biopsy samples. Whole-genome bisulfite sequencing was conducted on the monozygotic twin brothers, one of whom developed B-ALL. RESULTS: According to the ACMG guidelines, bioinformatic analysis of the genome sequencing revealed 20 germline mutations, particularly mutations in the DNAH11 (c.9463G > A) and CFH (c.2314G > A) genes that were documented in the COSMIC database and validated by Sanger sequencing. Forty-one common somatic mutated genes were identified in the cancer samples, displaying the same type of single nucleotide substitution Signature 5. Meanwhile, hypomethylation of PLEK2, MRAS, and RXRA as well as hypermethylation of CpG island associated with WT1 was shown in the twin with B-ALL. CONCLUSIONS: These findings reveal genomic alterations in a pedigree with multiple cancers. Mutations found in the DNAH11, CFH genes, and other genes predispose to malignancies in this family. Dysregulated methylation of WT1, PLEK2, MRAS, and RXRA in the twin with B-ALL increases cancer susceptibility. The similarity of the somatic genetic changes among the three cancers indicates a hereditary impact on the pedigree. These familial cancers with germline and somatic mutations, as well as epigenomic alterations, represent a common molecular basis for many multiple cancer pedigrees.

Comparative genomics of quinolone-resistant Escherichia coli from broilers and humans in Norway.

BACKGROUND: The usage of fluoroquinolones in Norwegian livestock production is very low, including in broiler production. Historically, quinolone-resistant Escherichia coli (QREC) isolated from Norwegian production animals rarely occur. However, with the introduction of a selective screening method for QREC in the Norwegian monitoring programme for antimicrobial resistance in the veterinary sector in 2014; 89.5% of broiler caecal samples and 70.7% of broiler meat samples were positive. This triggered the concern if there could be possible links between broiler and human reservoirs of QREC. We are addressing this by characterizing genomes of QREC from humans (healthy carriers and patients) and broiler isolates (meat and caecum). RESULTS: The most frequent mechanism for quinolone resistance in both broiler and human E. coli isolates were mutations in the chromosomally located gyrA and parC genes, although plasmid mediated quinolone resistance (PMQR) was also identified. There was some relatedness of the isolates within human and broiler groups, but little between these two groups. Further, some overlap was seen for isolates with the same sequence type isolated from broiler and humans, but overall, the SNP distance was high. CONCLUSION: Based on data from this study, QREC from broiler makes a limited contribution to the incidence of QREC in humans in Norway.

Directional integration and pathway enrichment analysis for multi-omics data.

Omics techniques generate comprehensive profiles of biomolecules in cells and tissues. However, a holistic understanding of underlying systems requires joint analyses of multiple data modalities. We present DPM, a data fusion method for integrating omics datasets using directionality and significance estimates of genes, transcripts, or proteins. DPM allows users to define how the input datasets are expected to interact directionally given the experimental design or biological relationships between the datasets. DPM prioritises genes and pathways that change consistently across the datasets and penalises those with inconsistent directionality. To demonstrate our approach, we characterise gene and pathway regulation in IDH-mutant gliomas by jointly analysing transcriptomic, proteomic, and DNA methylation datasets. Directional integration of survival information in ovarian cancer reveals candidate biomarkers with consistent prognostic signals in transcript and protein expression. DPM is a general and adaptable framework for gene prioritisation and pathway analysis in multi-omics datasets.

Genomic sequencing reveals convergent adaptation during experimental evolution in two budding yeast species.

Convergent evolution is central in the origins of multicellularity. Identifying the basis for convergent multicellular evolution is challenging because of the diverse evolutionary origins and environments involved. Haploid Kluyveromyces lactis populations evolve multicellularity during selection for increased settling in liquid media. Strong genomic and phenotypic convergence is observed between K. lactis and previously selected S. cerevisiae populations under similar selection, despite their >100-million-year divergence. We find K. lactis multicellularity is conferred by mutations in genes ACE2 or AIM44, with ACE2 being predominant. They are a subset of the six genes involved in the S. cerevisiae multicellularity. Both ACE2 and AIM44 regulate cell division, indicating that the genetic convergence is likely due to conserved cellular replication mechanisms. Complex population dynamics involving multiple ACE2/AIM44 genotypes are found in most K. lactis lineages. The results show common ancestry and natural selection shape convergence while chance and contingency determine the degree of divergence.

Integrative analysis of genomic and epigenomic regulation reveals miRNA mediated tumor heterogeneity and immune evasion in lower grade glioma.

The expression dysregulation of microRNAs (miRNA) has been widely reported during cancer development, however, the underling mechanism remains largely unanswered. In the present work, we performed a systematic integrative study for genome-wide DNA methylation, copy number variation and miRNA expression data to identify mechanisms underlying miRNA dysregulation in lower grade glioma. We identify 719 miRNAs whose expression was associated with alterations of copy number variation or promoter methylation. Integrative multi-omics analysis revealed four subtypes with differing prognoses. These glioma subtypes exhibited distinct immune-related characteristics as well as clinical and genetic features. By construction of a miRNA regulatory network, we identified candidate miRNAs associated with immune evasion and response to immunotherapy. Finally, eight prognosis related miRNAs were validated to promote cell migration, invasion and proliferation through in vitro experiments. Our study reveals the crosstalk among DNA methylation, copy number variation and miRNA expression for immune regulation in glioma, and could have important implications for patient stratification and development of biomarkers for immunotherapy approaches.

Genomic and phenotypic inconsistencies in Pseudomonas aeruginosa resistome among intensive care patients.

Objective: Pseudomonas aeruginosa, a difficult-to-manage nosocomial pathogen, poses a serious threat to clinical outcomes in intensive care (ICU) patients due to its high antimicrobial resistance (AMR). To promote effective management, it is essential to investigate the genomic and phenotypic differences in AMR expression of the isolates. Methods: A prospective observational study was conducted from July 2022 to April 2023 at Liepaja Regional Hospital in Latvia. The study included all adult patients who were admitted to the ICU and had a documented infection with P. aeruginosa, as confirmed by standard laboratory microbiological testing and short-read sequencing. Since ResFinder is the only sequencing-based database offering antibacterial susceptibility testing (AST) data for each antibiotic, we conducted a comparison of the resistance profile with the results of phenotypic testing, evaluating if ResFinder met the US Food and Drug Administration (FDA) requirements for approval as a new AMR diagnostic test. Next, to improve precision, AST data from ResFinder was compared with two other databases - AMRFinderPlus and RGI. Additionally, data was gathered from environmental samples to inform the implementation of appropriate infection control measures in real time. Results: Our cohort consisted of 33 samples from 29 ICU patients and 34 environmental samples. The presence of P. aeruginosa infection was found to be associated with unfavourable clinical outcomes. A third of the patient samples were identified as multi-drug resistant isolates. Apart from resistance against colistin, significant discrepancies were observed when phenotypic data were compared to genotypic data. For example, the aminoglycoside resistance prediction of ResFinder yielded a major errors value of 3.03% for amikacin, which was marginally above the FDA threshold. Among the three positive environmental samples, one sample exhibited multiple AMR genes similar to the patient samples in its cluster. Conclusion: Our findings underscore the importance of utilizing a combination of diagnostic methods for the identification of resistance mechanisms, clusters, and environmental reservoirs in ICUs.

Real-world comprehensive genomic and immune profiling reveals distinct age- and sex-based genomic and immune landscapes in tumors of patients with non-small cell lung cancer.

Introduction: Younger patients with non-small cell lung cancer (NSCLC) (<50 years) represent a significant patient population with distinct clinicopathological features and enriched targetable genomic alterations compared to older patients. However, previous studies of younger NSCLC suffer from inconsistent findings, few studies have incorporated sex into their analyses, and studies targeting age-related differences in the tumor immune microenvironment are lacking. Methods: We performed a retrospective analysis of 8,230 patients with NSCLC, comparing genomic alterations and immunogenic markers of younger and older patients while also considering differences between male and female patients. We defined older patients as those ≥65 years and used a 5-year sliding threshold from <45 to <65 years to define various groups of younger patients. Additionally, in an independent cohort of patients with NSCLC, we use our observations to inform testing of the combinatorial effect of age and sex on survival of patients given immunotherapy with or without chemotherapy. Results: We observed distinct genomic and immune microenvironment profiles for tumors of younger patients compared to tumors of older patients. Younger patient tumors were enriched in clinically relevant genomic alterations and had gene expression patterns indicative of reduced immune system activation, which was most evident when analyzing male patients. Further, we found younger male patients treated with immunotherapy alone had significantly worse survival compared to male patients ≥65 years, while the addition of chemotherapy reduced this disparity. Contrarily, we found younger female patients had significantly better survival compared to female patients ≥65 years when treated with immunotherapy plus chemotherapy, while treatment with immunotherapy alone resulted in similar outcomes. Discussion: These results show the value of comprehensive genomic and immune profiling (CGIP) for informing clinical treatment of younger patients with NSCLC and provides support for broader coverage of CGIP for younger patients with advanced NSCLC.

Inherited Germline Variants in Urinary Tract Cancer: A Multicenter Whole-Exome Sequencing Analysis and Correlation With Clinical Features and Tumor Genomics.

PURPOSE: This study investigates a real-world multicenter cohort of patients with urinary tract cancer (UTC), with primary disease sites including the bladder, urethra, and upper tract, who enrolled for research molecular testing of their germline and tumor. The purpose of this study was to evaluate factors that could affect the likelihood of identifying a clinically actionable germline pathogenic variant (PV). METHODS: Patients with UTC were identified from 10 cancer institutes of the Oncology Research Information Exchange Network consortium. The data set comprised abstracted clinical data with germline and tumor genomic data, and comparative analyses were conducted. RESULTS: Clinically actionable germline PVs in cancer predisposition genes were identified in 16 (4.5%) of 354 patients. A higher proportion of patients with the urethra and the upper tract as the primary sites of disease had PVs with a prevalence of 11% (5/45), compared with only 3.6% (11/308) in those with the bladder as the primary site of disease (P = .04). There were no significant differences in markers of genomic instability (such as tumor mutational burden, microsatellite instability [MSI], and loss of heterozygosity, copy number, and chromosomal instability) between those with PVs and those without (P > .05). Of the PVs identified, 10 (62%) were in homologous recombination repair (HRR) genes, three (19%) in mismatch repair (MMR) genes, and three (19%) in genes associated with other pathways. CONCLUSION: Tissue-based assessment of genomic instability, such as MSI, does not reliably indicate germline PV. A comprehensive clinical germline testing approach that includes HRR genes in addition to MMR genes is likely to yield PVs in approximately one of 10 patients with nonbladder primary disease sites such as the upper tract and the urethra.