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Results for “high-throughput functional genomics”

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PubMed2026

A streamlined protocol for small-scale protoplast generation and CRISPR/Cpf1-mediated genome editing in Fusarium oxysporum.

Fusarium oxysporum is a significant threat to agriculture and One Health, requiring advanced molecular tools for functional genomic analyses and biological control agent development. Existing gene-editing methods are hampered by costly protoplast preparation protocols and by CRISPR-Cas9 limitations, such as restricted protospacer adjacent motif (PAM) sequences and complex guide RNA requirements. We engineered an efficient CRISPR/Cpf1 system that overcomes these issues through three main innovations: small-scale protoplast generation using filter column-based methods that greatly reduce enzyme consumption while simplifying workflows, a CRISPR/Cpf1 system with shorter guide RNA design and staggered DNA cleavage to promote homologous recombination, and minimal homology arm strategies that significantly decrease cloning complexity. Extensive validation confirms successful gene targeting with molecular verification and functional analysis via standardized pathogenicity assays. This integrated platform offers affordable, accessible tools for systematic F. oxysporum research, enhancing fundamental understanding of plant-pathogen interactions and supporting high-throughput screening vital for agricultural biotechnology and biological agent development.

CRISPR/Cpf1↗

PubMed2026

Transcriptomic Changes Associated with Electroacupuncture in a DMCAO Model of Delayed Cognitive Impairment.

INTRODUCTION: Delayed Cognitive Impairment (DCIS) occurs in approximately 31% to 77% of individuals following stroke. Clinical findings have indicated that electroacupuncture may alleviate post-stroke DCIS. However, insights derived from animal models remain limited. The present study utilized a Distal Middle Cerebral Artery Occlusion (DMCAO) mouse model to investigate the potential mechanisms of electroacupuncture through hippocampal transcriptomic analysis. MATERIALS AND METHODS: Adult male BALB/c mice were subjected to DMCAO and received electroacupuncture treatment. High-throughput RNA sequencing of hippocampal tissue was performed to identify Differentially Expressed Genes (DEGs). Enrichment analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, hierarchical clustering, and Protein-Protein Interaction (PPI) network analysis, were performed to elucidate potential biological mechanisms. RESULTS: The DMCAO model exhibited features consistent with DCIS. Electroacupuncture treatment was associated with improved cognitive performance and enhanced hippocampal neuroplasticity. A total of 116 DEGs were identified in the DMCAO group compared with the sham group, while 69 DEGs were identified in the DMCAO + electroacupuncture group compared with the untreated DMCAO group. DISCUSSION: GO enrichment analysis indicated that electroacupuncture modulated biological processes related to nerve fibers, axonal development, neuronal regulation, cellular processes, and cardiovascular protection. KEGG pathway analysis indicated involvement in pathways associated with neuronal recovery and axonal function. The PPI network comprised 28 nodes and 33 interactions, with hub genes such as Gna13, Hipk2, and Stambp playing key roles. Quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) results were consistent with RNA sequencing findings. CONCLUSION: Electroacupuncture improved DCIS in the DMCAO mouse model. Transcriptomic analysis of the hippocampus provided preliminary evidence of the potential mechanisms underlying the therapeutic effects of electroacupuncture treatment following ischemic stroke.

Animals↗

PubMed2026

Engineering bubble structures as Cas12a activators for highly sensitive monitoring of WRN helicase function.

The Werner syndrome helicase (WRN) is a critical synthetic lethal target in microsatellite instability cancers, essential for resolving complex genomic structures like replication bubbles and R-loops. However, strategies to simultaneously discriminate WRN activity on DNA versus DNA-RNA substrates in living cells are lacking. Here, we developed a structure-specific CRISPR/Cas12a biosensing strategy to visualize WRN functional activity by engineering bubble-structure probes. These probes were rationally designed to structurally mimic DNA replication bubbles and R-loop associated DNA-RNA hybrids. Upon specific unwinding by WRN, the probes release a sequestered activator strand that triggers Cas12a trans-cleavage, effectively converting the unwinding event into an amplified fluorescent signal. This assay achieves low picomolar sensitivity (LODs: 5.6-6.0 pM) and exceptional selectivity against homologous RecQ helicases. Uniquely, this strategy enables the parallel quantification of WRN activity on both substrate types, providing insights into distinct WRN-mediated pathways for resolving genomic stress. We further demonstrated the strategy's utility by visualizing endogenous WRN dynamics in living cells and profiling the efficacy of small-molecule inhibitors. This work offers a powerful molecular toolkit for dissecting WRN biology and facilitating high-throughput drug screening in targeted cancer therapy.

Werner Syndrome Helicase↗

PubMed2026

ALPAR: automated learning pipeline for antimicrobial resistance.

SUMMARY: The field of machine learning in antimicrobial resistance (AMR) research has experienced rapid growth, fueled by advancements in high-throughput genome sequencing and the growing capacity of computational resources. However, the complexity and lack of standardized data preparation and bioinformatic analyses present significant challenges, especially for newcomers to the domain. In response to these challenges, we introduce ALPAR (Automated Learning Pipeline for Antimicrobial Resistance), a comprehensive AMR data analysis tool covering the entire process from processing of raw genomic data to training machine learning models to interpretation of results. Our method relies on a reproducible pipeline that integrates widely used bioinformatics tools, presenting a simplified, automatic workflow specifically tailored for single-reference AMR analysis. Accepting genomic data in the form of FASTA files as input, ALPAR facilitates the generation of machine learning-ready data tables and both the training of machine learning and the execution of genome-wide association studies (GWAS) experiments. Additionally, our tool offers supplementary functionalities such as phylogeny-based analysis of the distribution of mutations, enhancing its utility for researchers. The tool has also proven its performance in competitive benchmarks, winning the 2024 CAMDA Anti-Microbial Resistance Prediction Challenge and placing third in the 2025 edition. AVAILABILITY AND IMPLEMENTATION: ALPAR is open-source and freely accessible via GitHub (https://github.com/kalininalab/ALPAR). The pipeline is fully reproducible and can be easily installed as a Conda package (https://anaconda.org/kalininalab/ALPAR).

Machine Learning↗

PubMed2026

Exome sequencing and large-scale analysis of electronic medical record-linked biobank data identify candidate deafness genes.

INTRODUCTION: Rapid advances in whole-exome sequencing (WES) have enabled large-scale detection of pathogenic variants. Although hundreds of genes are implicated in hearing loss, up to half of inherited cases remain unsolved, limiting eligibility for gene therapy trials that require genetic diagnosis. Biobanks and electronic medical records (EMRs) offer opportunities to integrate genomic and clinical data at scale and expand the spectrum of hearing loss genes. Despite clinical value, EMRs often lack key information such as inheritance patterns, posing challenges for accurate interpretation. METHODS: WES was performed on DNA samples from 1038 hearing-impaired patients enrolled in the Maccabi Research and Innovation Center Tipa Biobank. Clinical data were extracted from EMRs. Audiograms were available for all cases, although data on age of onset, family history and mode of inheritance were mostly unavailable. We applied a scalable bioinformatics analysis strategy for high-throughput annotation, filtering and prioritisation of WES variants across more than 1000 patients, designed to accommodate incomplete and heterogeneous clinical records. RESULTS: Using this approach, 15% of cases were solved or potentially solved through known or novel variants in established deafness genes. Homozygous variants in novel candidate genes were identified in 3% of cases. Functional characterisation was performed for promising candidate genes to validate their role in the ear. CONCLUSION: These findings demonstrate that WES can determine disease aetiology in large, genetically heterogeneous populations, even in the context of incomplete clinical data. This approach supports large-scale genetic screening and provides a framework for identifying patients who may benefit from emerging gene-based therapies.

Genetic Testing↗

PubMed2026

Clinically actionable stratification of uncommon MET fusions: a precision oncology framework.

BACKGROUND: MET fusions represent emerging therapeutic targets in solid tumors; however, functional interpretation of non-canonical variants remains poorly understood, posing a major challenge for precision oncology. METHODS: We conducted a multicenter, pan-cancer study analyzing 23,299 clinical samples using DNA-based next-generation sequencing (NGS) to profile MET fusions. Transcriptional validation was performed using RNA-based NGS on available samples. Preliminary clinical outcomes were assessed in four patients with advanced malignancies harboring uncommon MET fusions who received MET tyrosine kinase inhibitor therapy. RESULTS: We identified 116 MET fusions (incidence: 0.5%), with 55.2% (64/116) classified as uncommon fusions. These uncommon fusions were stratified into: Group A (5’-retained, n = 12), Group B (intergenic/exonic breakpoints, n = 19), Group C (rare partners, n = 23), and Group D (dual fusions, n = 10). RNA validation revealed an overall low transcriptional consistency of 43.8% (14/32) for uncommon fusions, versus 100% for canonical fusions (PTPRZ1::MET, CAPZA2::MET). Notably, most 5’-retained fusions were transcriptionally silent, while some intergenic fusions resolved into expressed canonical partners (e.g. PTPRZ1::MET). Therapeutically, all four MET inhibitor-treated patients achieved partial responses, including pediatric diffuse midline gliomas (DMG) (median OS: 11.2 months) and lung adenocarcinoma (median OS: 34 months), demonstrating preliminary clinical activity. CONCLUSIONS: uncommon MET fusions are heterogeneous at genomic and transcriptional levels. DNA-level findings often do not predict functional transcripts, underscoring the necessity of RNA-based confirmation for clinical interpretation. Despite low overall consistency, a subset retains therapeutic potential. We propose a refined diagnostic framework integrating DNA-based stratification and RNA validation to guide the management of MET-altered cancers in precision oncology workflows.

Humans↗

PubMed2026

Analysis of deep-resequencing data of 984 soybean accessions reveals structural variations underlying agronomic traits.

Genomic structural variants (SVs) are major sources of genetic variation and have profound impacts on phenotypic traits. However, their functional effects remain largely unexplored in soybean. Here, we resequence 940 soybean accessions. Together with 44 publicly available datasets, we identify 602,281 SVs. Using a graph-based genome, we detect an additional 58,760 presence/absence variations (PAVs) that broadly affect gene expression. Population genomic analyses reveal that SVs serve as a core driving force for soybean domestication and improvement. Integrating SVs with QTLs for oil and protein content, and performing GWAS on 27 traits, we identify key functional SVs. These include transposable element insertions altering seed coat color, multiple insertions within a cytochrome P450 gene modifying flower and hypocotyl color, and a GmMATE1 deletion enhancing seed size. Together, our study establishes a comprehensive SV map of soybean, offering a valuable resource for dissecting the genetic basis of complex traits to accelerate molecular breeding.

Glycine max↗

PubMed2026

A de novo algorithm for allele reconstruction from Oxford nanopore amplicon reads, with application to CYP2D6.

MOTIVATION: The Oxford Nanopore Technologies' sequencing platform offers a path towards bedside genomics, producing long reads that can completely cover a gene of interest, and detect any known or novel variant the gene contains. However, the analysis of these long reads to identify actionable genotypes remains challenging and typically requires customization depending on the target gene. RESULTS: Here, we describe a generic algorithm to accurately reconstruct allele sequences derived from long-reads of amplicon-based data. Rather than calling variants directly from these long-reads, our method takes a "sequence-first" approach, performing an unbiased reconstruction of the underlying amplicon sequences to generate high-confidence reconstructed allele sequences. This is done without user input of the target gene, allowing for any source amplicon to be reconstructed. These high-confidence reconstructed allele sequences are then compared to the genomic reference sequence of the gene to infer the specific diplotype present in the sample. This approach is agnostic towards the number of genes and alleles present and readily detects novel variants. We demonstrate our approach using three independent data sets for CYP2D6, a diverse and complex gene with over 175 known alleles of clinical significance. We show how our approach can accurately recover validated CYP2D6 diplotypes from 20 Coriell samples covering 14 distinct alleles, using different amplicons, flow cell versions, and depths. This includes inferring occurrences of allele duplication events from relative abundances of each allele, a critical factor for ascribing functional effects to a diplotype. Further, we demonstrate our approach's utility for other genomic regions, including HLA. AVAILABILITY: Custom code is available at the following GitHub repository, along with instructions for use and test data: https://github.com/scottdbrown/allele-reconstruction-long-read-amplicon-data. A snapshot of the code at the time of publication is available on Zenodo.org; doi 10.5281/zenodo.19716004. Raw .fastq sequence data for our three sequencing runs is available at the SRA under Bioproject PRJNA1357883 (https://www.ncbi.nlm.nih.gov/bioproject/1357883).

Alleles↗

PubMed2026

Functional Prediction of Epitranscriptome.

N6-methyladenosine (m6A) is one of the most prevalent and well-studied RNA modifications, playing a pivotal role in many biological processes. With the recent advances in high-throughput sequencing technologies, tens of thousands of m6A sites have been reported. However, not all m6A sites are important or functionally significant, highlighting the need to distinguish biologically relevant m6As from non-functional or technically artefactual ones. Here, we describe ConsRM, which is a web-based resource that was designed to evaluate the importance of m6As from an evolutionary perspective. It introduced a novel scoring framework for quantifying the conservation degree of m6As in humans. Its web interface includes a database of 177998 distinct human m6A sites along with their calculated conservation score, and allows users to analyze their own data via the web server. ConsRM is freely accessible at: http://180.208.58.19/conservation/browser.html .

Humans↗

PubMed2026

A novel peptide encoded by circTLL1 drives osimertinib resistance in lung cancer by modulating the NT5C2/Ras/PI3K axis.

BACKGROUND: Acquired resistance to osimertinib, a third-generation EGFR tyrosine kinase inhibitor, remains a major clinical challenge in the treatment of non-small cell lung cancer (NSCLC). Although circular RNAs (circRNAs) have been increasingly implicated in drug resistance, most studies have focused on their canonical role as microRNA sponges, while their capacity to encode functional micropeptides remains largely unexplored. This study aimed to identify novel circRNAs involved in osimertinib resistance and to characterize their regulatory functions at the protein level. METHODS: Osimertinib-resistant (OR) NSCLC cell lines were established and validated. High-throughput RNA sequencing was performed to compare the circRNA expression profiles between parental and OR cells. The function of the candidate circRNA was assessed through a series of in vitro and in vivo experiments, including cell viability assays, apoptosis analysis, and xenograft mouse models. Mechanistic investigations involved mass spectrometry, co-immunoprecipitation and western blotting to explore its protein-coding potential and downstream signaling pathways. RESULTS: We identified a novel circRNA, termed circTLL1, that was stably and significantly upregulated in OR-NSCLC cells. Functionally, overexpression of circTLL1 promoted osimertinib resistance, whereas its knockdown restored drug sensitivity both in vitro and in vivo. Mechanistically, we discovered that circTLL1 harbors an open reading frame (ORF) that is translated into a novel 90-amino-acid protein, which we designated circTLL1-90aa. Further investigation revealed that circTLL1-90aa directly interacts with and promotes the degradation of 5'-nucleotidase, cytosolic II (NT5C2), thereby uncoupling nucleotide metabolism from its normal regulatory constraints. The consequent downregulation of NT5C2 leads to elevated GTP levels and leading to the sustained activation of the downstream Ras/PI3K/AKT signaling pathway. CONCLUSION: Our findings unveil a previously unrecognized circRNA/micropeptide/metabolism cascade underlying osimertinib resistance. The identification of the circTLL1-90aa/NT5C2/Ras/PI3K axis not only expands the functional repertoire of the non-coding genome but also provides new insights into the complexity of drug resistance. Given its selective upregulation in resistant cells, circTLL1-90aa holds promise both as a predictive biomarker for treatment stratification and as an actionable therapeutic target, offering a novel strategy to overcome osimertinib resistance in NSCLC patients.

Pyrimidines↗

PubMed2026

esloco: simulation-based estimation of local coverage in long-read DNA sequencing.

SUMMARY: Long-read DNA sequencing is increasingly applied for whole-genome studies, yet experimental planning often lacks reliable estimates of target region coverage, leading to costly and time-consuming pilot studies and replicates. We present esloco, a Monte Carlo-based simulation framework for estimating local coverage in long-read sequencing experiments, including scenarios with unknown target regions (e.g. viral integration, CRISPR-Cas9) or PCR-free designs (e.g. base modifications). By modeling coverage as a function of sequencing depth and read length distribution, esloco enables informed predictions of local sequencing outcomes. Benchmarking across a 45-gene panel demonstrated close agreement with empirical data, underscoring the framework's reliability. AVAILABILITY AND IMPLEMENTATION: esloco is a Python package available on PyPI (https://pypi.org/project/esloco/), GitHub (https://github.com/aweich/esloco), and Zenodo (https://doi.org/10.5281/zenodo.17776161).

Sequence Analysis, DNA↗

PubMed2025

Decipher RNA isoform combinations from minigene splicing assays and massive parallel sequencing with MAGIC.

SUMMARY: Functional testing of RNA using minigene splicing assays is increasingly being realized to demonstrate the effects of variants on splicing. In complex cases, variant pathogenicity is assessed by Sanger sequencing, which can be time consuming and may be replaced by short read sequencing. Moreover, strategies based on long read sequencing of the amplified minigene construct are promising and allow the isoforms to be fully characterized. We introduce MAGIC, a user-friendly tool that first generates the artificial construction genome files required to then perform alignment, assembly and annotation of the isoforms obtained by either short or long read minigene splicing assay sequencing. AVAILABILITY AND IMPLEMENTATION: MAGIC is available at https://github.com/LBGC-CFB/MAGIC. Zenodo DOI: 10.5281/zenodo.17052752.

High-Throughput Nucleotide Sequencing↗

PubMed2025

Evaluation of sequencing reads at scale using rdeval.

MOTIVATION: Large sequencing datasets are being produced and deposited into public archives at unprecedented rates. The availability of tools that can reliably and efficiently generate and store sequencing read summary statistics has become critical. RESULTS: As part of the effort by the Vertebrate Genomes Project (VGP) to generate high-quality reference genomes at scale, we sought to address the community's need for efficient sequence data evaluation by developing rdeval, a standalone tool to quickly compute and interactively display sequencing read metrics. Rdeval can either run on the fly or store key sequence data metrics in tiny read 'snapshot' files. Statistics can then be efficiently recalled from snapshots for additional processing. Rdeval can convert fa*[.gz] files to and from other popular formats including BAM and CRAM for better compression. Overall, while CRAM achieves the best compression, the gain compared to BAM is marginal, and BAM achieves the best compromise between data compression and access speed. Rdeval also generates a detailed visual report with multiple data analytics that can be exported in various formats. We showcase rdeval's functionalities using long-read data from different sequencing platforms and species, including human. For PacBio long-read sequencing, our analysis shows dramatic improvements in both read length and quality over time, as well as the benefit of increased coverage for genome assembly, though the magnitude varies by taxa. AVAILABILITY AND IMPLEMENTATION: Rdeval is implemented in C++ for data processing and in R for data visualization. Precompiled releases (Linux, MacOS, Windows) and commented source code for rdeval are available under MIT license at https://github.com/vgl-hub/rdeval. Documentation is available on ReadTheDocs (https://rdeval-documentation.readthedocs.io). Rdeval is also available in Bioconda and in Galaxy (https://usegalaxy.org). An automated test workflow ensures the consistency of software updates.

Software↗

PubMed2026

Utilization of long-read sequencing for the detection of structural rearrangements with AgileStructure.

MOTIVATION: Changes in genome organisation contribute to genetic disease when they disrupt gene function or regulation. Structural rearrangements may interrupt coding sequence or alter expression through promoter loss or gain, chromatin changes, copy-number variation, or disruption of short-range regulatory elements. Although short-read sequencing excels at detecting small variants, it performs poorly at resolving breakpoints of large rearrangements, especially in repetitive or low-complexity regions. Long-read sequencing overcomes these limitations, but analytical tools have not kept pace, making accurate identification and annotation of large structural variants challenging. RESULTS: We developed AgileStructure, a desktop application for locating and annotating large‑scale genomic rearrangements using aligned long‑read data. The software enables user‑guided exploration of breakpoint‑spanning reads, supporting accurate interpretation of complex events and filling a key gap in current structural variant analysis workflows. AVAILABILITY AND IMPLEMENTATION: Source code, binaries, user guide, and example aligned read data, are available on GitHub: https://github.com/msjimc/AgileStructure. An archived version is also available on Zenodo at https://doi.org/10.5281/zenodo.18610110.

Software↗

PubMed2026

Comparison of paralog identification methods and their impact on species tree topologies in target capture phylogenomics within the Sindora clade (Detarioideae: Leguminosae).

Target capture is a common method of generating high throughput DNA sequencing data for phylogenetic reconstruction of species relationships, for which single copy genes are usually most informative. However, a pervasive problem with target capture is that putatively single copy genes may in fact be paralogs resulting from gene duplication, which are problematic for phylogenetic inference because their evolutionary history may differ from the divergence history of species. Here, we use as a case study a target enrichment dataset of 88 species of Detarioideae (Leguminosae) with a focus on the Sindora clade to examine approaches for handling paralogs, including the built-in paralog handling functions in HybPiper and CAPTUS, plus subsequent steps using Putative Paralog Detection and the tree-based Yang & Smith orthology inference approach. We compare the paralogs flagged using these methods and verify their performance with BLAST mapping against a reference genome sequence of Sindora glabra, and then subsequently compare the species tree topologies produced across these methods. Our comparisons of paralogs flagged across the Sindora clade show that the Putative Paralog Detection pipeline was the most accurate in identifying paralogs in terms of its similarity to the BLAST mapping, followed by the built-in paralog identification function of CAPTUS. However, the results we recovered for the Detarioideae subfamily suggest that the largest differences in species tree topology resulted from the use of paralog-filtered alignments (such as with the Putative Paralog Detection pipeline and the Yang & Smith orthology inference approaches) rather than just by removing the sequences of identified paralogous genes. This was the true for HybPiper-assembled datasets but was not seen in CAPTUS-assembled datasets. In all comparisons, the topological differences caused by different paralog handling methods tended to be confined to clades where processes such as hybridisation and introgression are prevalent. Our study provides a roadmap to establish the best approach to identify, eliminate or separate paralogs in the absence of a chromosomally contiguous reference genome for a study group, and highlights the importance of careful data inspection and processing in addition to understanding the extent of paralogy and paralog characteristics (e.g. sequence divergence between copies) for their study group.

Phylogeny↗

PubMed2026

Obtaining a Diagnostic Yield via Scan findings prior to the introduction of SEquencing retrospectivelY (ODYSSEY): a cohort study.

OBJECTIVE: To determine the retrospective yield of prenatal exome sequencing (PES) by establishing the proportion of children with a postnatal monogenic diagnosis that could have been diagnosed prenatally if PES had been available. METHODS: The study cohort comprised a sample of children in Northern Ireland, born between January 2010 and January 2018 (predating routine availability of PES), who received a monogenic diagnosis postnatally via next generation sequencing as part of either of two UK-wide studies (the 100 000 Genomes Project (2015-2018) or the Deciphering Developmental Disorders study (2011-2015)). Clinical data were collected retrospectively and correlated with the current UK National Health Service PES protocol, including the phenotypic eligibility criteria for PES and the associated fetal anomalies gene panel. Cases were considered retrospective diagnoses if the fetal phenotype would have been eligible for PES and the diagnostic gene was included on the test panel, meaning prenatal diagnosis in this current era could have been feasible. RESULTS: Of 101 children, 17.8% (95% CI, 10.3-25.3%) had both an eligible fetal structural anomaly (FSA) (i.e. high-risk FSA) and a diagnostic gene on the associated test panel, meaning that they could have been diagnosed prenatally in the current clinical landscape. The median length of the diagnostic odyssey for this subgroup of children was 3.7 years (1354 (range, 822-2450) days). Moreover, 58.4% (n = 59) of cases had no anomalies detected prenatally and 19.8% (n = 20) had a FSA that would not meet the eligibility criteria for PES (low-risk FSA). Although these cases would have been ineligible for PES under the current clinical pathway, 89.9% (n = 71/79) were affected by severe or profound syndromes. Postnatally, the most common functional anomalies were neurodevelopmental delay/intellectual disability and/or behavioral abnormality, which were observed in 80.2% (n = 81) of the included children. However, 80.2% (n = 65/81) of these affected children did not present with fetal anomalies eligible for PES. CONCLUSIONS: Almost one-fifth of children with a monogenic condition included in this study could have received a diagnosis via modern PES, avoiding a diagnostic odyssey lasting almost 4 years. However, despite having a monogenic condition, over half of the children did not present with any structural anomalies in utero. This demonstrates the degree to which fetal imaging is limited in its ability to reassure parents of the absence of a fetal genetic syndrome. © 2026 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Humans↗

PubMed2026

Bilateral Conversion Risk in Unilateral Retinoblastoma Using Age and Genetic Testing.

IMPORTANCE: Metachronous bilateral conversion in initially unilateral retinoblastoma is uncommon but clinically consequential, potentially requiring intensified treatment and carrying worse prognosis. Clarifying how age at diagnosis refines genetic-risk stratification could enable safer, more efficient surveillance protocols. OBJECTIVE: To estimate the incidence and timing of metachronous bilateral conversion in unilateral retinoblastoma and assess whether age at diagnosis and RB1 testing are associated with bilateral conversion risk. DESIGN, SETTING AND PARTICIPANTS: This was a retrospective cohort study at a tertiary center in Shanghai, China, including 1108 consecutive children with initially unilateral retinoblastoma diagnosed from July 2010 to October 2024 (after exclusions for short follow-up [n = 139], missing data [n = 53], or synchronous bilateral disease [n = 10]). The median (IQR) follow-up was 43.4 (24.2-67.6) months. EXPOSURES: Age at diagnosis and RB1 genetic status/subtypes assessed by next-generation sequencing and multiplex ligation-dependent probe amplification, including penetrance class (high vs low) and mosaic vs germline categorization. MAIN OUTCOMES AND MEASURES: Time to metachronous bilateral conversion; cumulative incidence functions with death as a competing risk; spatial distribution of fellow-eye tumors. RESULTS: Among 1108 patients (median [IQR] age at diagnosis, 22.2 [12.0-31.4] months; 591 [53.3%] male), 24 (2.2%) developed metachronous bilateral disease. At 24 months, cumulative incidence was 2.2% (95% CI, 1.3-3.1) overall. By genetic status, the 24-month cumulative incidence was 24.8% (95% CI, 13.8-35.9) in RB1 variant-positive vs 1.6% (95% CI, 0.0-3.1) in RB1 variant-negative patients. Among RB1 variant-positive patients, risk clustered among those diagnosed before 9 months, whereas no conversions were observed among those diagnosed at older than 9 months. Four RB1 variant-negative patients who were initially diagnosed at notably late ages (20.9, 42.7, 79.6, and 118 months) subsequently converted; these cases likely represent undetected low-level mosaicism, somatic variants below detection thresholds, or rare genomic events not captured by standard sequencing panels. Fellow-eye tumors did not involve macula and showed a nasal-predominant distribution. CONCLUSIONS AND RELEVANCE: The findings in this study suggest that age at diagnosis may refine genetic risk stratification for metachronous bilateral conversion. RB1 variant-positive patients diagnosed at 9 months or later represent a very low-risk subgroup that may warrant surveillance deescalation, while rare late conversions in RB1 variant-negative patients necessitate continued long-term monitoring.

Humans↗

PubMed2026

Discovery and Engineering of a Rat Endogenous Retrovirus Reverse Transcriptase for Efficient Prime Editing.

CRISPR-based prime editors (PEs) install precise edits into genomic DNA without generating double-strand breaks. Their editing efficiency is highly dependent on reverse transcriptases (RTs), but efficient RT candidates remain limited. Here, we identified 19 novel active RTs by screening 558 candidates. Among them, RERV-RT, derived from Rattus norvegicus, exhibited the highest activity. Through structure-guided engineering and deep mutational scanning, we developed an optimized variant, enRERV-RT, which outperforms conventional M-MLV-RT-based PE systems by 1.20-fold in mammalian and plant cells, and by 1.88-fold at hard-to-edit loci, while enabling precise multiplex editing of functionally relevant genes. Additionally, we developed a high-throughput platform, TRAP-seq-PE, to systematically evaluate prime editor performance. Across diverse mutation types, we found that PE systems based on enRERV-RT exhibited higher editing efficiencies than those based on M-MLV-RT. Collectively, our work establishes a versatile, high-efficiency PE system, thereby facilitating advances in clinical gene therapy and precise crop breeding.

Animals↗