Efficient discovery of regulatory genes and elements is essential for understanding cell identity, differentiation, and disease mechanisms. The TRIAGE methods are a set of well-established computational approaches that identify context-specific regulatory genes and prioritize regulatory elements across the genome. Previous publications have described the development of these algorithms, their benchmarking, and biological applications. Here, we provide step-by-step protocols for applying the TRIAGE methods to identify regulatory drivers from diverse input types, including gene expression matrices, gene lists, and genomic loci. It covers analyses of both bulk and single-cell RNA-seq datasets and enables genome-wide interrogation of regulatory elements at single-base resolution. The analysis is efficient, typically requiring <30 min of computation time on a personal computer. In addition to the step-by-step description of the TRIAGE analysis workflow, we provide the TRIAGE toolkit, available as both an R package and a Python implementation, to support flexible and scalable regulatory analysis across platforms. © 2026 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Prioritization of regulatory genes from bulk RNA-seq data Basic Protocol 2: Identification of cell populations and regulatory genes in single-cell RNA-seq data Basic Protocol 3: Prioritization of regulatory long noncoding RNAs Basic Protocol 4: Prioritization of functional genetic variants from eQTL data Alternate Protocol: Python-based implementation of the TRIAGE workflow for regulatory gene and element prioritization Support Protocol: Preparing a normalized expression matrix from bulk RNA-seq count data.

Advancing risk gene discovery across the allele frequency spectrum.

Discovery of novel antimicrobial resistance genes: Integrons as a high-throughput gene capture and functional screening platform.

Fibroblast growth factors (FGFs) are crucial for animal development, growth and physiological regulation. Early vertebrate evolution was shaped by complex whole-genome duplications (WGDs); after a shared first event (1RV), jawed vertebrates underwent a second distinct WGD (2RJV), while cyclostomes (lampreys and hagfishes) experienced a different, lineage-specific genome expansion (2RCY). Despite their key evolutionary position, the FGF gene family in cyclostomes has remained largely uncharacterized, contrasting with extensive research in jawed vertebrates and their invertebrate chordate relatives. To illuminate this knowledge gap, we conducted a comprehensive genomic survey of FGF genes across four cyclostome species, five jawed vertebrates, and an amphioxus outgroup, leveraging newly available cyclostome genomes. Our analysis surprisingly reveals a significantly reduced FGF repertoire in lampreys (17 genes) and hagfishes (12 genes) compared to jawed vertebrates (22-32 genes). This finding suggests extensive FGF gene loss in cyclostomes following their unique genome duplication history. Phylogenetic and synteny analyses confirm that all eight ancestral FGF subfamilies were first established in the common ancestor of vertebrates. Significantly, we report the discovery of a novel FGF gene, Fgf25, within the FGF4/5/6/25 subfamily, uniquely retained in actinopterygians but lost in sarcopterygians. We also propose a new evolutionary model for Fgf3, suggesting its origin via tandem duplication of an unknown Fgf gene after the 1RV but before the second genome duplication, ultimately leading to the conserved Fgf3-Fgf4-Fgf19 gene linkage in jawed vertebrates. This detailed characterization of the cyclostome FGF repertoire provides insights into early vertebrate FGF evolution and a valuable resource for future investigations into cyclostome evolution and development.

Polyethylene Terephthalate (PET) is an extensively used plastic whose durability and resistance to degradation contribute to growing environmental pollution and concerns. Enzymatic PET degradation, particularly via PETase from Ideonella sakaiensis, has emerged as a sustainable approach due to its ability to depolymerize PET under mild conditions. While research has largely focused on enhancing the enzyme's thermal stability through distal mutations, less attention has been given to active-site engineering aimed at directly improving catalytic efficiency. Here, we used an automated in silico protein engineering platform called Gene Discovery and Enzyme Engineering (GDEE), designed to exhaustively explore mutations at the active site in a hight-throughput manner. By leveraging the highly active FAST-PETase (FP) as scaffold, we perform a high throughput generation of thousands of variants, evaluated them via docking studies with a PET substrate analogue, and ranked candidates based on binding affinity and catalytic geometry. We identified S238Y as a key mutation that further enhanced PET film degrading performance at 40°C when inserted in two of the most active PETase variants reported to date: 2.2-fold increase in the FP scaffold and 3.4-fold increase in the ThermoStable-PETase (TSP) background. Compared to wild type PETase, FP S238Y showed a 14.8-fold increase in bulk activity, translating into 9.4-fold more TPA and 20-fold more MHET by UPLC, while TSP S238Y reached a 25.8-fold increase (14.4-fold more TPA and 42.6-fold more MHET). This mutation also enhanced catalytic efficiency and resistance to enzyme concentration inhibition, especially in the TSP scaffold. Molecular dynamics highlight position 238 as a relevant modulator of ligand stabilisation. These findings underscore the potential of targeted active-site engineering, combined with structure-guided prediction, to accelerate the development of efficient mesophilic biocatalysts for plastic waste remediation. Additionally, the GDEE platform provides an automation-ready workflow for active site engineering that is applicable beyond PETase.

Scleric acid is a natural product that was discovered by heterologous expression of the silent scl gene cluster from Streptomyces sclerotialus in Streptomyces albidoflavus and rational de-repression of the biosynthetic genes through deletion of the ArpA-like regulator SclM4. It is a weak inhibitor of the cancer-associated enzyme nicotinamide N-methyltransferase (NNMT). In this work we aimed to improve understanding of scleric acid biosynthesis and of gene regulation of the scl gene cluster. We performed CRISPR/Cas9-mediated deletion of the biosynthetic gene sclG, which confirmed the essential role of the corresponding ATP-grasp family enzyme in the biosynthesis of scleric acid. We also carried out whole-genome Nanopore long-read sequencing of S. sclerotialus to investigate the borders of the scl gene cluster, which led us to discover two additional genes, sclC and sclK, proposed to be involved in biosynthetic precursor supply. Transcriptomics analyses were performed to investigate the effect of the deletion of the ArpA-like gene sclM4 on the expression of the scl biosynthetic genes, shedding light on the role of the corresponding transcriptional repressor. The present work improves understanding of scleric acid biosynthesis and provides new insights into the ArpA-like mediated regulation of biosynthetic gene expression in Streptomyces bacteria.

The discovery of genes encoding the volume-regulated anion channel (VRAC) has enabled detailed exploration of its cell type-specific roles in the brain. LRRC8A (SWELL1) is the essential VRAC subunit. We observed seizure-induced, subunit-specific changes in microglial VRAC expression and investigated its function using conditional KO (cKO) of LRRC8A in microglia. SWELL1 cKO mice exhibited a male-specific increase in kainate-induced seizure severity, yet showed paradoxical neuroprotection against seizure-associated neuronal loss. Mechanistically, SWELL1 deletion led to a cell-autonomous reduction in microglial density and decreased release of VRAC-permeable neuroactive metabolites, including taurine, GABA, and glutamate in culture. Additionally, impaired phagocytic kinetics and reduced lysosomal biogenesis contributed to the observed neuroprotection. These findings reveal potentially novel roles for microglial VRAC in regulating seizure outcomes and microglia-neuron interactions.

A framework beyond single‐reference genomes is needed to understand transcription factor evolution. This study employed an integrated haplotype‑resolved genomes–transcriptome atlas–machine learning to characterize the transcription factors of autotetraploid green jujube (Ziziphus mauritiana). The first haplotype‑resolved comparison of transcription factor superfamilies from eight haplotype genomes (HapGenome) representing a specific wild and a specific cultivated green jujube accession, encompassing 42 superfamilies and 12,123 gene copies. Evolutionary analyses revealed high structural conservation with minimal copy number variation, gene presence/absence variations, and strong purifying selection (Ka/Ks < 1). Dispersed duplication (47.24%), not whole‐genome duplication (36.10%), was the most frequently observed duplication event in the expansion of transcription factor superfamily. A haplotype‑resolved transcriptome atlas demonstrated that tissue‐specific expression divergence occurred at the superfamily level and between the core/dispensable genes. Integrating transcriptomic and metabolomic data, support vector machine classification with leave‑one‑out cross‑validated distinguished three wild fruits from six cultivated fruits with the accuracy of 89% using orthologous gene groups (OGGs) expression profiles. The eXtreme gradient boosting was employed as an exploratory tool to prioritize OGGs related to metabolite changes. Finally, OGG‐95, a Lesion Simulating Disease Zn finger transcription factor, was screened out, which was significantly upregulated in cultivated fruits, and its expression was significantly correlated with differential accumulation of nucleotides and organic acids that need further functional validation. This integrative study provided novel insights into the genomic architecture and regulatory evolution of transcription factors in a polyploid fruit crop, highlighting the power of multi‐dimensional analyses for gene discovery.

Systems-level multi-omics dissection of syndromic and idiopathic autism reveals distinct regulatory architectures, candidate molecular signatures, and potential therapeutic targets.

Protocol for applying a network-enabled gene discovery pipeline to non-model plant species.

BMI-genome interactions regulate global gene expression with emphasis in brain and gut.

Amyotrophic lateral sclerosis (ALS) is a rare, progressive neurodegenerative disorder, with a substantial proportion of cases attributed to genetic factors. Recent advances in gene discovery and genomic technologies have transformed ALS care by enabling genomic testing to inform prognosis, assess familial risk, and facilitate access to novel therapies. However, guidance on the delivery of genetic testing and counselling in ALS remains limited, leading to variability in clinical practice. In response, the Manchester Motor Neuron Disease (MND) Care Centre and the Manchester Centre for Genomic Medicine co-developed a structured genetic care pathway for ALS, drawing on real-world data, patient engagement, and multidisciplinary collaboration. A retrospective evaluation of 326 ALS patients at the Manchester MND Care Centre identified significant variability in genetic testing uptake, counselling practices, and record-keeping. Patient survey and engagement sessions revealed uncertainty regarding key genetic concepts and inconsistent recall of pre- and post-test discussions. Priorities for improvement included clearer communication, standardised discussions, and enhanced support for families following genetic findings. Consequently, the Greater Manchester ALS Genetic Testing Pathway was developed by a multidisciplinary team, incorporating consensus-based steps for patient identification, pre-test conversations, consent, testing, results disclosure, and post-test support. This pathway integrates genetic testing into routine ALS care, clarifies team responsibilities, and establishes a framework for ongoing evaluation using key performance indicators. Patient and staff feedback is used to support continuous improvement. The co-developed ALS genetic testing pathway provides a scalable model for standardising genomic care in mainstream clinical settings. By establishing clear processes for genetics discussions, consent, and follow-up, the pathway seeks to improve equity, transparency, and person-centred care. Ongoing evaluation and collaboration with patients, clinicians, and genetic services are essential to ensure the pathway remains responsive to scientific advances and evolving patient needs. Wider adoption of structured genetic pathways may facilitate the integration of genomics into care for rare diseases across healthcare systems.

Clonal selection drives cancer development, but quantifying selection on noncoding somatic mutations remains largely unexplored. Here, we introduce dNdS-Fun, an extension of the dN/dS framework to quantify selection of both coding and noncoding somatic mutations, thereby enhancing the discovery of driver genes. Applying dNdS-Fun to whole-genome sequencing data from 14,886 cancer patients across 31 cancer types, we identify 175 genes under positive selection across multiple cancer types or datasets, as well as 20 previously known driver genes detected through noncoding mutations. Of these, 69 are previously unrecognized as drivers, and 30 are identified solely through noncoding mutations. Furthermore, we observe evidence of negative selection throughout the genome, with significant enrichment in essential and cancer-dependent genes. Sixteen genes exhibit an overall signature of negative selection but show positive selection in noncoding elements, indicating both their conserved functions and adaptive regulatory roles in tumorigenesis. Our study reveals evidence consistent with negative selection of noncoding mutations, providing important insights for future research on their roles in cancer progression.

Antibiotic tolerance paves the way for acquired resistance in bacterial pathogens. However, the mechanisms of tolerance and its evolutionary role in acquired resistance in pathogenic fungi, and particularly in filamentous fungi, remain elusive. Here, we identified an Inhibitor of Growth domain-containing protein (IngB) as a novel epigenetic regulator of azole tolerance in Aspergillus fumigatus. The loss of ingB promotes supra-MIC growth on agar surfaces despite susceptible MICs in standardized assays. Moreover, established ΔingB biofilms are also less susceptible to azoles in vitro. In a murine model of invasive pulmonary aspergillosis, loss of ingB results in higher pulmonary fungal levels when animals are treated with voriconazole compared to the wild-type control. Subsequent exposure of the ΔingB-tolerant strain to high azole concentrations in vitro resulted in rapid acquired resistance, most notably driven by a frameshift mutation in a putative 20S proteasome maturation protein-encoding gene, umpA, while the susceptible wild-type strain failed to acquire adaptive mutations. The data suggest that loss of IngB provides an epistatic background for the emergence of azole resistance. Our work shows that drug tolerance in a critical fungal pathogen can facilitate azole resistance emergence.IMPORTANCEWhile antimicrobial drug resistance causes adverse effects on human health, drug tolerance can also lead to insufficient pathogen clearance, resulting in infection relapse. However, the mechanisms of antifungal drug tolerance and its evolutionary role in acquired drug resistance in pathogenic fungi, particularly the molds, remain elusive. We identified IngB as a novel regulator of azole tolerance in Aspergillus fumigatus. In a murine model of invasive pulmonary aspergillosis treated with voriconazole, loss of ingB facilitated higher fungal burden levels than the wild-type control, suggesting the observed in vitro tolerance translates to the murine pulmonary environment. Importantly, loss of IngB leads to rapid azole drug resistance under azole-selective pressure in vitro and led to the discovery of a new gene associated with azole resistance, umpA. Our work identifies a novel regulator of antifungal tolerance in a critical human fungal pathogen and suggests that drug tolerance can pave the way for resistance emergence.

The discovery of the SMN1 gene on chromosome 5q in 1995, and later, identification of SMN2 as a modifier gene was the breakthrough in the history of spinal muscular atrophy (SMA). It was the discovery of this gene that led to the discovery of 3 disease-modifying drugs that were approved for use by the US Food and Drug Administration and the European Medicines Agency. This brings to one's mind the fact that the earliest description of this disease happened a century ago. The persistent efforts of a few scientists have rewritten the destiny of children with SMA. With the discovery of the new drugs came new challenges: the need for intense supportive care and the exorbitant cost of the drugs. A long-term global plan for the equitable distribution of these drugs-that are beyond doubt beneficial to improve motor power in children with SMA-is the need of the hour.

Functional genomics have been hampered by the paucity of efficient methods that connect genotype and metabolic phenotype at single-cell resolution. Using the industrial microalga Nannochloropsis oceanica as a model, we introduced a platform that comprises a genome-wide single-gene-edited mutant library and high-throughput Raman-activated cell sorting (RACS). The CRISPR/Cas-generated library consisted of 3567 microalgal mutants derived from 2397 effective guide RNAs. Label-free sorting of the library for high carotenoid content by RACS unraveled mutations in the violaxanthin de-epoxidase (noVDE) or in the proteasome assembly chaperone 4 (noPAC4) genes. Knocking out all five known noVDEs revealed that the high carotenoid content is due to violaxanthin increase, whilst noPAC4 knockout boosted carotenoid content with elevations in violaxanthin, zeaxanthin, and β-carotene. Genetic and transcriptomic evidence suggested two previously unknown modes of carotenogenesis regulation mediated by noPAC4: epigenetic mechanisms via histone deacetylase (HDAC) and post-translational controls by the 26S proteasome. Therefore, by label-freely sorting single-cell metabolic phenotype and rapidly yet unambiguously tracing it to a genotype, this forward-genetics approach can greatly accelerate the discovery of genes and pathways.

Brain disorders characterized by progressive neurodegeneration, such as Alzheimer's disease (AD) and frontotemporal dementia (FTD), represent an increasing medical and societal challenge. While genome‑wide studies have uncovered numerous susceptibility loci, these efforts have largely focused on common variants and leave a substantial portion of genetic liability unresolved. Variants of low frequency, often associated with stronger biological effects, remain insufficiently characterized, particularly in heterogeneous populations. Genetically isolated populations offer an effective strategy to overcome these limitations. Finland, shaped by historical demographic events, harbors a distinctive spectrum of enriched rare variants that can facilitate gene discovery. The FinnGen initiative capitalizes on this setting by combining extensive genotyping with nationwide health registry data through a coordinated network of Finnish biobanks. With half a million participants analyzed, FinnGen supports highly powered analyses across a broad array of clinical outcomes and registry data. Recent comprehensive analyses have reported thousands of significant genotype-phenotype associations, including novel protein‑altering variants. Importantly, the FinnGen cohort structure favors older individuals and hospital‑derived samples, increasing representation of brain disorders, such as AD and idiopathic normal pressure hydrocephalus (iNPH), a disorder frequently accompanied by AD‑like pathological features. In this expert review, we summarize FinnGen‑based investigations relevant to neurodegenerative diseases and iNPH, highlighting insights into genetic susceptibility, disease overlap, and protective factors, and discuss how integration with recall studies as well as biomarker and clinical data accelerates translational applications in brain disorders.

Kidney disease in patients with two APOL1 risk variants.

Covering 1982 to 2026Some of the most prominent natural products originate from plants. Discovering their biosynthetic genes has been a slow process. In contrast to microbial systems, co-expression analysis rather than genome mining has been the main strategy to elucidate biosynthetic pathways in plants. However, traditional co-expression analyses are limited in efficiency and often not as successful as desired. In this review, we describe emerging technologies to improve or replace traditional co-expression analyses, for example based on genome or protein data. Furthermore, we critically discuss the current state and impact of artificial intelligence and machine learning in the field. Our review will help to select the most efficient approaches for elucidation of biosynthetic pathways in plants for future work. Additionally, we highlight areas that require further methodological improvements to guide future research.

The microbial cycling of dimethylsulfoniopropionate (DMSP) and dimethyl sulfide (DMS) constitutes a crucial component of the global sulfur cycle, influencing climate regulation through the release of climate-active gases. Since DMSP production has historically been attributed to planktonic algae, research on its cycling has consequently centered on the surface ocean. However, the continuous discovery of bacterial DMSP synthesis genes (dsyB, mmtN, and dsyGD) has confirmed that the DMSP/DMS cycling process may also exist in the aphotic deep-sea environment. Further supporting this, the recently identified hydrogen sulfide (H2S)/methanethiol (MeSH)-dependent DMS-producing enzyme MddH, widespread among marine bacteria, may represent a significant source of DMS. This review integrates emerging insights into the ecological roles, environmental distribution, and microbial metabolism of these organic sulfur compounds, with a specific emphasis on deep-sea environments. We further discuss the distribution of key microbial taxa and functional genes involved in the biosynthesis and degradation of DMSP and DMS across deep-sea water columns and sediments. Collectively, this review highlights the existence of an active microbial DMSP/DMS cycling network in the deep ocean that remained overlooked until recently, with profound implications for global biogeochemical cycles and climate.