Bulk segregant mapping and transcriptome analyses reveal the molecular mechanisms of spinetoram resistance in Spodoptera frugiperda.

The evolution of resistance to insecticides poses a significant threat to pest management programs. Understanding the molecular mechanisms underlying insecticide resistance is essential to design sustainable pest control and resistance management programs. The fall armyworm, Spodoptera frugiperda, is an important insect pest of many crops and has a remarkable ability to evolve resistance to insecticides. In this study, we employed bulk segregant analysis (BSA) combined with DNA and RNA sequencing to characterize the molecular basis of spinetoram resistance in S. frugiperda. Analysis of genomic data derived from spinetoram selected and unselected bulks and the spinetoram-resistant and susceptible parental strains led to the identification of a three-nucleotide deletion in the gene encoding the nicotinic acetylcholine receptor α6 subunit (nAChR α6). Transcriptome profiling identified the upregulation of few genes encoding detoxification enzymes associated with spinetoram resistance. Thus, spinetoram resistance in S. frugiperda appears to be mediated mainly by target site insensitivity with a minor role of detoxification enzymes. Our findings provide insight into the mechanisms underpinning resistance to spinetoram in S. frugiperda and will inform the development of strategies to control this highly damaging, globally distributed crop pest.

Transcription dosage compensation does not occur in Down syndrome.

BACKGROUND: The increase in DNA copy number in Down syndrome (DS; caused by trisomy 21) has led to the DNA dosage hypothesis, which posits that the level of gene expression is proportional to the gene's DNA copy number. Yet many reports have suggested that a proportion of chromosome 21 genes are dosage compensated back towards typical expression levels (1.0×). In contrast, other reports suggest that dosage compensation is not a common mechanism of gene regulation in trisomy 21, providing support to the DNA dosage hypothesis. RESULTS: In our work, we use both simulated and real data to dissect the elements of differential expression analysis that can lead to the appearance of dosage compensation, even when compensation is demonstrably absent. Using lymphoblastoid cell lines derived from a family with an individual with Down syndrome, we demonstrate that dosage compensation is nearly absent at both nascent transcription (GRO-seq) and steady-state RNA (RNA-seq) levels. Furthermore, we link the limited apparent dosage compensation to expected allelic variation in transcription levels. CONCLUSIONS: Transcription dosage compensation does not occur in Down syndrome. Simulated data containing no dosage compensation can appear to have dosage compensation when analyzed via standard methods. Moreover, some chromosome 21 genes that appear to be dosage compensated are consistent with allele specific expression.

CHTKC: a robust and efficient k-mer counting algorithm based on a lock-free chaining hash table.

MOTIVATION: Calculating the frequency of occurrence of each substring of length k in DNA sequences is a common task in many bioinformatics applications, including genome assembly, error correction, and sequence alignment. Although the problem is simple, efficient counting of datasets with high sequencing depth or large genome size is a challenge. RESULTS: We propose a robust and efficient method, CHTKC, to solve the k-mer counting problem with a lock-free hash table that uses linked lists to resolve collisions. We also design new mechanisms to optimize memory usage and handle situations where memory is not enough to accommodate all k-mers. CHTKC has been thoroughly tested on seven datasets under multiple memory usage scenarios and compared with Jellyfish2 and KMC3. Our work shows that using a hash-table-based method to effectively solve the k-mer counting problem remains a feasible solution.

An effect of large-scale deletions and duplications on transcript expression.

Since copy number variants (CNVs) have been recognized as an important source of genetic and transcriptomic variation, we aimed to characterize the impact of CNVs located within coding, intergenic, upstream, and downstream gene regions on the expression of transcripts. Regions in which deletions occurred most often were introns, while duplications in coding regions. The transcript expression was lower for deleted coding (P = 0.008) and intronic regions (P = 1.355 × 10-10), but it was not changed in the case of upstream and downstream gene regions (P = 0.085). Moreover, the expression was decreased if duplication occurred in the coding region (P = 8.318 × 10-5). Furthermore, a negative correlation (r = - 0.27) between transcript length and its expression was observed. The correlation between the percent of deleted/duplicated transcript and transcript expression level was not significant for all concerned genomic regions in five out of six animals. The exceptions were deletions in coding regions (P = 0.004) and duplications in introns (P = 0.01) in one individual. CNVs in coding (deletions, duplications) and intronic (deletions) regions are important modulators of transcripts by reducing their expression level. We hypothesize that deletions imply severe consequences by interrupting genes. The negative correlation between the size of the transcript and its expression level found in this study is consistent with the hypothesis that selection favours shorter introns and a moderate number of exons in highly expressed genes. This may explain the transcript expression reduction by duplications. We did not find the correlation between the size of deletions/duplications and transcript expression level suggesting that expression is modulated by CNVs regardless of their size.

Identification of imprinted genes in the skeletal muscle of newborn piglets by high-throughput sequencing.

Imprinted genes - exhibiting parent-specific transcription - play essential roles in the process of mammalian development and growth. Skeletal muscle growth is crucial for meat production. To further understand the role of imprinted genes during the porcine skeletal muscle growth, DNA-seq and RNA-seq were used to explore the characteristics of imprinted genes from porcine reciprocal crosses. A total of 584 545 single-nucleotide variations were discovered in the DNA-seq data of F0 parents, heterozygous in two pig breeds (Yorkshire and Min pigs) but homozygous in each breed. These single-nucleotide variations were used to determine the allelic-specific expression in F1 individuals. Finally, eight paternal expression sites and three maternal expression sites were detected, whereas two paternally expressed imprinted genes (NDN and IGF2) and one maternally expressed imprinted gene (H1-3) were validated by Sanger sequencing. DNA methylation regulates the expression of imprinted genes, and all of the identified imprinted genes in this study were predicted to possess CpG islands. PBX1 and YY1 binding motifs were discovered in the promoter regions of all three imprinted genes, which were candidate elements regulating the transcription of imprinted genes. For these identified imprinted genes, IGF2 and NDN promoted muscle growth whereas H1-3 inhibited cell proliferation, corroborating the 'parental conflict' theory that paternally expressed imprinted genes assisted descendants' growth whereas maternally expressed imprinted genes inhibited it. This study discovered porcine imprinted genes in skeletal muscle and was the first to reveal that H1-3 was expressed by the maternal allele to our knowledge. Our findings provided valuable resources for the potential utilization of imprinted genes in pig breeding.

Computational Resources for the Interpretation of Variations in Cancer.

A broad ecosystem of resources, databases, and systems to analyze cancer variations is present in the literature. These are a strategic element in the interpretation of NGS experiments. However, the intrinsic wealth of data from RNA-seq, ChipSeq, and DNA-seq can be fully exploited only with the proper skill and knowledge. In this chapter, we survey relevant literature concerning databases, annotators, and variant prioritization tools.

Mechanisms of responsiveness to and resistance against trabectedin in murine models of human myxoid liposarcoma.

Myxoid liposarcoma (MLPS) is a rare soft-tissue sarcoma characterised by the expression of FUS-DDIT3 chimera. Trabectedin has shown significant clinical anti-tumour activity against MLPS. To characterise the molecular mechanism of trabectedin sensitivity and of resistance against it, we integrated genomic and transcriptomic data from treated mice bearing ML017 or ML017/ET, two patient-derived MLPS xenograft models, sensitive to and resistant against trabectedin, respectively. Longitudinal RNA-Seq analysis of ML017 showed that trabectedin acts mainly as a transcriptional regulator: 15 days after the third dose trabectedin modulates the transcription of 4883 genes involved in processes that sustain adipocyte differentiation. No such differences were observed in ML017/ET. Genomic analysis showed that prolonged treatment causes losses in 4p15.2, 4p16.3 and 17q21.3 cytobands leading to acquired-resistance against the drug. The results dissect the complex mechanism of action of trabectedin and provide the basis for novel combinatorial approaches for the treatment of MLPS that could overcome drug-resistance.

Acquired mutations and transcriptional remodeling in long-term estrogen-deprived locoregional breast cancer recurrences.

BACKGROUND: Endocrine therapy resistance is a hallmark of advanced estrogen receptor (ER)-positive breast cancer. In this study, we aimed to determine acquired genomic changes in endocrine-resistant disease. METHODS: We performed DNA/RNA hybrid-capture sequencing on 12 locoregional recurrences after long-term estrogen deprivation and identified acquired genomic changes versus each tumor's matched primary. RESULTS: Despite being up to 7 years removed from the primary lesion, most recurrences harbored similar intrinsic transcriptional and copy number profiles. Only two genes, AKAP9 and KMT2C, were found to have single nucleotide variant (SNV) enrichments in more than one recurrence. Enriched mutations in single cases included SNVs within transcriptional regulators such as ARID1A, TP53, FOXO1, BRD1, NCOA1, and NCOR2 with one local recurrence gaining three PIK3CA mutations. In contrast to DNA-level changes, we discovered recurrent outlier mRNA expression alterations were common-including outlier gains in TP63 (n = 5 cases [42%]), NTRK3 (n = 5 [42%]), NTRK2 (n = 4 [33%]), PAX3 (n = 4 [33%]), FGFR4 (n = 3 [25%]), and TERT (n = 3 [25%]). Recurrent losses involved ESR1 (n = 5 [42%]), RELN (n = 5 [42%]), SFRP4 (n = 4 [33%]), and FOSB (n = 4 [33%]). ESR1-depleted recurrences harbored shared transcriptional remodeling events including upregulation of PROM1 and other basal cancer markers. CONCLUSIONS: Taken together, this study defines acquired genomic changes in long-term, estrogen-deprived disease; highlights the importance of longitudinal RNA profiling; and identifies a common ESR1-depleted endocrine-resistant breast cancer subtype with basal-like transcriptional reprogramming.

Indel detection from DNA and RNA sequencing data with transIndel.

BACKGROUND: Insertions and deletions (indels) are a major class of genomic variation associated with human disease. Indels are primarily detected from DNA sequencing (DNA-seq) data but their transcriptional consequences remain unexplored due to challenges in discriminating medium-sized and large indels from splicing events in RNA-seq data. RESULTS: Here, we developed transIndel, a splice-aware algorithm that parses the chimeric alignments predicted by a short read aligner and reconstructs the mid-sized insertions and large deletions based on the linear alignments of split reads from DNA-seq or RNA-seq data. TransIndel exhibits competitive or superior performance over eight state-of-the-art indel detection tools on benchmarks using both synthetic and real DNA-seq data. Additionally, we applied transIndel to DNA-seq and RNA-seq datasets from 333 primary prostate cancer patients from The Cancer Genome Atlas (TCGA) and 59 metastatic prostate cancer patients from AACR-PCF Stand-Up- To-Cancer (SU2C) studies. TransIndel enhanced the taxonomy of DNA- and RNA-level alterations in prostate cancer by identifying recurrent FOXA1 indels as well as exitron splicing in genes implicated in disease progression. CONCLUSIONS: Our study demonstrates that transIndel is a robust tool for elucidation of medium- and large-sized indels from DNA-seq and RNA-seq data. Including RNA-seq in indel discovery efforts leads to significant improvements in sensitivity for identification of med-sized and large indels missed by DNA-seq, and reveals non-canonical RNA-splicing events in genes associated with disease pathology.

Muver, a computational framework for accurately calling accumulated mutations.

BACKGROUND: Identification of mutations from next-generation sequencing data typically requires a balance between sensitivity and accuracy. This is particularly true of DNA insertions and deletions (indels), that can impart significant phenotypic consequences on cells but are harder to call than substitution mutations from whole genome mutation accumulation experiments. To overcome these difficulties, we present muver, a computational framework that integrates established bioinformatics tools with novel analytical methods to generate mutation calls with the extremely low false positive rates and high sensitivity required for accurate mutation rate determination and comparison. RESULTS: Muver uses statistical comparison of ancestral and descendant allelic frequencies to identify variant loci and assigns genotypes with models that include per-sample assessments of sequencing errors by mutation type and repeat context. Muver identifies maximally parsimonious mutation pathways that connect these genotypes, differentiating potential allelic conversion events and delineating ambiguities in mutation location, type, and size. Benchmarking with a human gold standard father-son pair demonstrates muver's sensitivity and low false positive rates. In DNA mismatch repair (MMR) deficient Saccharomyces cerevisiae, muver detects multi-base deletions in homopolymers longer than the replicative polymerase footprint at rates greater than predicted for sequential single-base deletions, implying a novel multi-repeat-unit slippage mechanism. CONCLUSIONS: Benchmarking results demonstrate the high accuracy and sensitivity achieved with muver, particularly for indels, relative to available tools. Applied to an MMR-deficient Saccharomyces cerevisiae system, muver mutation calls facilitate mechanistic insights into DNA replication fidelity.

Whole-exome mutational and transcriptional landscapes of combined hepatocellular cholangiocarcinoma and intrahepatic cholangiocarcinoma reveal molecular diversity.

BACKGROUND: Primary liver cancer (PLC) is the third largest contributor to cancer mortality in the world. PLC is a heterogeneous disease that encompasses several biologically distinct subtypes including hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC) and combined hepatocellular-cholangiocarcinoma (CHC). CHC is a distinct, albeit rare, subtype of PLC and is comprised of cells with histopathological features of both HCC and ICC. Several studies have focused on the mutation and expression landscapes of HCC and ICC. However, studies of CHC were rare. OBJECTIVE: The aim of the current study was to identify genetic and gene expression alterations in the carcinogenesis and development of CHC and ICC in the Chinese population. Unraveling both similar and differing patterns among these subtypes may help to identify personalized medicine approaches that could improve patient survival. METHODS: Whole genome sequencing (WGS), whole exome sequencing (WES) and RNA-seq were performed on 10 ICC and 10 CHC samples, matched with adjacent non-tumor liver tissue specimens. Comparative analysis was performed using HCC datasets from The Cancer Genome Atlas (TCGA). RESULTS: Mutational and transcriptional landscapes of CHC and ICC were clearly delineated. TP53 and CTNNB1 were identified as exhibiting mutations in CHC. ARID1A, PBRM1, and IDH1 were frequently mutated in ICC. RYR3, FBN2, and KCNN3 are associated with cell migration and metastasis and might be driver genes in CHC. KCNN3 was identified as also exhibiting mutations in ICC. The ECM-receptor interaction pathway associated fibrogenic hepatic progenitor cell differentiation and liver fibrosis may play an important role in carcinogenesis of PLC. Chromatin remodeling and chromosome organization are key processes in carcinogenesis and development in PLC. P53 related pathways showed alterations in CHC and HCC. Inflammation may be a key factor involved in ICC carcinogenesis. CONCLUSION: CHC and ICC are different subtypes of PLC. This study discusses predominantly the molecular genetic details of PLC subtypes and highlights the need for an accurate diagnosis and treatment of specific PLC subtypes to optimize patient management.

Genome sequencing and protein domain annotations of Korean Hanwoo cattle identify Hanwoo-specific immunity-related and other novel genes.

BACKGROUND: Identification of genetic mechanisms and idiosyncrasies at the breed-level can provide valuable information for potential use in evolutionary studies, medical applications, and breeding of selective traits. Here, we analyzed genomic data collected from 136 Korean Native cattle, known as Hanwoo, using advanced statistical methods. RESULTS: Results revealed Hanwoo-specific protein domains which were largely characterized by immunoglobulin function. Furthermore, domain interactions of novel Hanwoo-specific genes reveal additional links to immunity. Novel Hanwoo-specific genes linked to muscle and other functions were identified, including protein domains with functions related to energy, fat storage, and muscle function that may provide insight into the mechanisms behind Hanwoo cattle's uniquely high percentage of intramuscular fat and fat marbling. CONCLUSION: The identification of Hanwoo-specific genes linked to immunity are potentially useful for future medical research and selective breeding. The significant genomic variations identified here can crucially identify genetic novelties that are arising from useful adaptations. These results will allow future researchers to compare and classify breeds, identify important genetic markers, and develop breeding strategies to further improve significant traits.

Ten years of next-generation sequencing technology.

Ten years ago next-generation sequencing (NGS) technologies appeared on the market. During the past decade, tremendous progress has been made in terms of speed, read length, and throughput, along with a sharp reduction in per-base cost. Together, these advances democratized NGS and paved the way for the development of a large number of novel NGS applications in basic science as well as in translational research areas such as clinical diagnostics, agrigenomics, and forensic science. Here we provide an overview of the evolution of NGS and discuss the most significant improvements in sequencing technologies and library preparation protocols. We also explore the current landscape of NGS applications and provide a perspective for future developments.

Genetic and Genomic Response to Selection for Food Consumption in Drosophila melanogaster.

Food consumption is an essential component of animal fitness; however, excessive food intake in humans increases risk for many diseases. The roles of neuroendocrine feedback loops, food sensing modalities, and physiological state in regulating food intake are well understood, but not the genetic basis underlying variation in food consumption. Here, we applied ten generations of artificial selection for high and low food consumption in replicate populations of Drosophila melanogaster. The phenotypic response to selection was highly asymmetric, with significant responses only for increased food consumption and minimal correlated responses in body mass and composition. We assessed the molecular correlates of selection responses by DNA and RNA sequencing of the selection lines. The high and low selection lines had variants with significantly divergent allele frequencies within or near 2081 genes and 3526 differentially expressed genes in one or both sexes. A total of 519 genes were both genetically divergent and differentially expressed between the divergent selection lines. We performed functional analyses of the effects of RNAi suppression of gene expression and induced mutations for 27 of these candidate genes that have human orthologs and the strongest statistical support, and confirmed that 25 (93 %) affected the mean and/or variance of food consumption.

Molecular methods resolve the bacterial composition of natural marine biofilms on galvanically coupled stainless steel cathodes.

Navy vessels consist of various metal alloys and biofilm accumulation at the metal surface is thought to play a role in influencing metal deterioration. To develop better strategies to monitor and control metallic biofilms, it is necessary to resolve the bacterial composition within the biofilm. This study aimed to determine if differences in electrochemical current could influence the composition of dominant bacteria in a metallic biofilm, and if so, determine the level of resolution using metagenomic amplicon sequencing. Current was generated by creating galvanic couples between cathodes made from stainless steel and anodes made from carbon steel, aluminum, or copper nickel and exposing them in the Delaware Bay. Stainless steel cathodes (SSCs) coupled to aluminum or carbon steel generated a higher mean current (0.39 mA) than that coupled to copper nickel (0.17 mA). Following 3 months of exposure, the bacterial composition of biofilms collected from the SSCs was determined and compared. Dominant bacterial taxa from the two higher current SSCs were different from that of the low-current SSC as determined by DGGE and verified by Illumina DNA-seq analysis. These results demonstrate that electrochemical current could influence the composition of dominant bacteria in metallic biofilms and that amplicon sequencing is sufficient to complement current methods used to study metallic biofilms in marine environments.

Bulked sample analysis in genetics, genomics and crop improvement.

Biological assay has been based on analysis of all individuals collected from sample populations. Bulked sample analysis (BSA), which works with selected and pooled individuals, has been extensively used in gene mapping through bulked segregant analysis with biparental populations, mapping by sequencing with major gene mutants and pooled genomewide association study using extreme variants. Compared to conventional entire population analysis, BSA significantly reduces the scale and cost by simplifying the procedure. The bulks can be built by selection of extremes or representative samples from any populations and all types of segregants and variants that represent wide ranges of phenotypic variation for the target trait. Methods and procedures for sampling, bulking and multiplexing are described. The samples can be analysed using individual markers, microarrays and high-throughput sequencing at all levels of DNA, RNA and protein. The power of BSA is affected by population size, selection of extreme individuals, sequencing strategies, genetic architecture of the trait and marker density. BSA will facilitate plant breeding through development of diagnostic and constitutive markers, agronomic genomics, marker-assisted selection and selective phenotyping. Applications of BSA in genetics, genomics and crop improvement are discussed with their future perspectives.

Library preparation methods for next-generation sequencing: tone down the bias.

Next-generation sequencing (NGS) has caused a revolution in biology. NGS requires the preparation of libraries in which (fragments of) DNA or RNA molecules are fused with adapters followed by PCR amplification and sequencing. It is evident that robust library preparation methods that produce a representative, non-biased source of nucleic acid material from the genome under investigation are of crucial importance. Nevertheless, it has become clear that NGS libraries for all types of applications contain biases that compromise the quality of NGS datasets and can lead to their erroneous interpretation. A detailed knowledge of the nature of these biases will be essential for a careful interpretation of NGS data on the one hand and will help to find ways to improve library quality or to develop bioinformatics tools to compensate for the bias on the other hand. In this review we discuss the literature on bias in the most common NGS library preparation protocols, both for DNA sequencing (DNA-seq) as well as for RNA sequencing (RNA-seq). Strikingly, almost all steps of the various protocols have been reported to introduce bias, especially in the case of RNA-seq, which is technically more challenging than DNA-seq. For each type of bias we discuss methods for improvement with a view to providing some useful advice to the researcher who wishes to convert any kind of raw nucleic acid into an NGS library.

ToxCodAn-Genome: an automated pipeline for toxin-gene annotation in genome assembly of venomous lineages.

BACKGROUND: The rapid development of sequencing technologies resulted in a wide expansion of genomics studies using venomous lineages. This facilitated research focusing on understanding the evolution of adaptive traits and the search for novel compounds that can be applied in agriculture and medicine. However, the toxin annotation of genomes is a laborious and time-consuming task, and no consensus pipeline is currently available. No computational tool currently exists to address the challenges specific to toxin annotation and to ensure the reproducibility of the process. RESULTS: Here, we present ToxCodAn-Genome, the first software designed to perform automated toxin annotation in genomes of venomous lineages. This pipeline was designed to retrieve the full-length coding sequences of toxins and to allow the detection of novel truncated paralogs and pseudogenes. We tested ToxCodAn-Genome using 12 genomes of venomous lineages and achieved high performance on recovering their current toxin annotations. This tool can be easily customized to allow improvements in the final toxin annotation set and can be expanded to virtually any venomous lineage. ToxCodAn-Genome is fast, allowing it to run on any personal computer, but it can also be executed in multicore mode, taking advantage of large high-performance servers. In addition, we provide a guide to direct future research in the venomics field to ensure a confident toxin annotation in the genome being studied. As a case study, we sequenced and annotated the toxin repertoire of Bothrops alternatus, which may facilitate future evolutionary and biomedical studies using vipers as models. CONCLUSIONS: ToxCodAn-Genome is suitable to perform toxin annotation in the genome of venomous species and may help to improve the reproducibility of further studies. ToxCodAn-Genome and the guide are freely available at https://github.com/pedronachtigall/ToxCodAn-Genome.

TMBcalc: a computational pipeline for identifying pan-cancer Tumor Mutational Burden gene signatures.

Background: In the precision medicine era, identifying predictive factors to select patients most likely to benefit from treatment with immunological agents is a crucial and open challenge in oncology. Methods: This paper presents a pan-cancer analysis of Tumor Mutational Burden (TMB). We developed a novel computational pipeline, TMBcalc, to calculate the TMB. Our methodology can identify small and reliable gene signatures to estimate TMB from custom targeted-sequencing panels. For this purpose, our pipeline has been trained on top of 17 cancer types data obtained from TCGA. Results: Our results show that TMB, computed through the identified signature, strongly correlates with TMB obtained from whole-exome sequencing (WES). Conclusion: We have rigorously analyzed the effectiveness of our methodology on top of several independent datasets. In particular we conducted a comprehensive testing on: (i) 126 samples sourced from the TCGA database; few independent whole-exome sequencing (WES) datasets linked to colon, breast, and liver cancers, all acquired from the EGA and the ICGC Data Portal. This rigorous evaluation clearly highlights the robustness and practicality of our approach, positioning it as a promising avenue for driving substantial progress within the realm of clinical practice.

CDKN2A copy number alteration in bladder cancer: Integrative analysis in patient-derived xenografts and cancer patients.

Bladder cancer (BlCa) is an extensively heterogeneous disease that leads to great variability in tumor evolution scenarios and lifelong patient surveillance, emphasizing the need for modern, minimally invasive precision medicine. Here, we explored the clinical significance of copy number alterations (CNAs) in BlCa. CNA profiling was performed in 15 patient-derived xenografts (PDXs) and validated in The Cancer Genome Atlas BlCa (TCGA-BLCA; n = 408) and Lindgren et al. (n = 143) cohorts. CDKN2A copy number loss was identified as the most frequent CNA in bladder tumors, associated with reduced CDKN2A expression, tumors of a papillary phenotype, and prolonged PDX survival. The study's screening cohort consisted of 243 BlCa patients, and CDKN2A copy number was assessed in genomic DNA and cell-free DNA (cfDNA) from 217 tumors and 189 pre-treatment serum samples, respectively. CDKN2A copy number loss was correlated with superior disease-free and progression-free survival of non-muscle-invasive BlCa (NMIBC) patients. Moreover, a higher CDKN2A index (CDKN2A/LEP ratio) in pre-treatment cfDNA was associated with advanced tumor stage and grade and short-term NMIBC progression to invasive disease, while multivariate models fitted for CDKN2A index in pre-treatment cfDNA offered superior risk stratification of T1/high-grade and EORTC high-risk patients, enhancing prediction of treatment outcome. CDKN2A copy number status could serve as a minimally invasive tool to improve risk stratification and support personalized prognosis in BlCa.