Actinobacteria are a diverse and heterogeneous group of bacteria with complex taxonomy that produce most of the natural products used in medicine. Although comparative genomic studies of Nocardia species have been reported, comprehensive species-level analyses integrating phylogenomics, pangenome structure, and biosynthetic gene cluster distribution in N. brasiliensis remain limited. In this study, we performed phylogenomic orthology inference, analyzed pangenome composition, and evaluated the potential of Nocardia brasiliensis as a source of secondary metabolites using comparative genomics. Four clinical strains from Mexico and 22 publicly accessible genomes were included. Genomic identification was performed, orthologous genes were identified, core genome and pangenome composition were estimated, and phylogenomic orthology inference was assessed. All genomes were searched for known BGCs, secondary metabolites were predicted, and data on reported biological activity were collected. A pangenome comprising 17,715 clusters was calculated, with the core genome accounting for 22.76 % and the cloud genome for 48.17 %. The trend in the gene accumulation curve indicated that the species had an open pangenome, as the continuous increase in gene clusters with the addition of new genomes suggests a high level of genomic diversity and ongoing gene acquisition within the species, reflecting its capacity for environmental adaptation and evolutionary plasticity. Phylogenomic analysis showed that geographical origin and isolation conditions affect evolutionary divergence within N. brasiliensis. Computational BGC prediction detected PKS, NRPS, NAPAA, terpenes, aminopolycarboxylic acids, hybrids, and other clusters coding for secondary metabolites with antimicrobial activity (ε-Poly-L-lysine, brasiliquinones A-B), antitumor activity (rhizomides A-C, anthramycin), antioxidant activity (isorenieratene), and a fertilizer for calcareous soils ([S, S]-EDDS). The results reveal significant genomic diversity and a wide distribution of biosynthetic clusters within the Nocardia brasiliensis pangenome, demonstrating its genomic plasticity and the variability in metabolic potential across strains.
Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype defined by the absence of estrogen receptor, progesterone receptor, and HER2 expression, and is associated with limited targeted treatment options and poor clinical outcomes. Although major genomic studies have characterized TNBC in Western populations, the genomic landscape of TNBC in South Asian populations remains insufficiently understood despite a relatively high disease burden in this region. We conducted a systematic review following PRISMA 2020 guidance to synthesize available genomic evidence on TNBC in South Asian cohorts. Studies reporting genomic alterations in TNBC patients from South Asia were identified through searches of PubMed, Scopus, Web of Science, and ProQuest, supplemented by citation tracking and a ClinicalTrials.gov search. Eight studies from India and Pakistan met the eligibility criteria. Because the evidence base was sparse and clinically and methodologically heterogeneous, and because the number of studies reporting extractable denominators for any single biomarker did not reach our pre-specified threshold for pooling, data were synthesized descriptively rather than by meta-analysis. Across the included studies, recurrent alterations were reported in key tumor-suppressor and DNA-repair genes, particularly BRCA1, BRCA2, and TP53. Germline BRCA1 alterations were reported at a relatively high frequency in several cohorts, most notably in Pakistani TNBC patients, suggesting a contribution of hereditary DNA-repair defects to TNBC pathogenesis in this population. These findings highlight the importance of population-specific genomic analyses and support the growing role of DNA-repair-directed therapies and biomarker-driven precision oncology strategies in TNBC management. We additionally propose, as recommendations for future work, a two-tier framework for ancestry classification and a tiered scheme for harmonizing homologous recombination deficiency (HRD) reporting.
Despite the prevalence of bacterial probiotics, yeast-based preparations offer unique therapeutic benefits that remain a key research priority. Here, we conducted a comparative genomic characterization of the dairy-associated Saccharomyces cerevisiae WUT3 and WUT151 strains, building on previous evidence showing their enhanced probiotic potential relative to the probiotic S. cerevisiae var. boulardii CNCM I-745. The genomes of WUT3 and WUT151 were compared with the reference S. cerevisiae S288C and the probiotic S. boulardii CNCM I-745. At the CDS level, both WUT strains were closer to S288C, suggesting that their probiotic properties stem from unique mechanisms rather than general genetic similarities to the probiotic strain. WUTs shared selected probiotic-related features, including ENA1 deletions, WHI2 alterations, and loss of Ty1/Ty2 regions present in S288C. Together with conserved core stress-response genes, this profile supports their tolerance to low pH, bile salts, and elevated temperature. Gene content analysis revealed redundancy within the hexose transporters and confirmed the absence of the ASP3 cluster. Indels in HSP150 and PIR3 may reflect WUT and S. boulardii cell wall variations. Overall, the probiotic potential of WUT strains does not originate from a single 'probiotic genome', but rather from a unique combination of traits dispersed throughout the S. cerevisiae species. Since no detrimental features were revealed in the analyzed genomes, these strains represent promising candidates for further clinical evaluation. Furthermore, these findings demonstrate that integrative genomic analysis is an effective strategy for the identification, selection, and characterization of candidate probiotic yeast strains.
Cucumber is a globally significant vegetable crop whose production and market value are affected by fruit quality and resilience to diverse environmental stressors. Despite the identification of numerous Quantitative Trait Loci (QTL) over the last two decades, their direct application in breeding has been hindered by inconsistent genomic positions and broad confidence intervals. In this study, we conducted a comprehensive Meta-QTL (mQTL) analysis by integrating 647 initial QTLs from 40 independent studies published between 2003 and 2024. Using a high-density consensus map containing 9,299 markers, we projected 531 QTLs, identifying 38 robust mQTLs associated with fruit quality, biotic and abiotic stress tolerance. The identified mQTLs exhibited a significant reduction in the average confidence interval (CI) by 5.3-fold, compared to the average CI of the original QTLs and phenotypic variance explained values reaching up to 49.81% (mQTL 6.8). Our results identifying specific genomic hotspots on chromosomes 1, 3, 5, and 6 that harbor high-confidence candidate genes responsible for stress tolerance and fruit quality. Comparative analysis with seven independent genome-wide association studies validated 16 mQTL regions, confirming their stability across diverse genetic backgrounds. Biotic stress resilience was linked to immune regulators such as LRK10L2 and MLO-like protein 12, while abiotic stress tolerance was anchored by genes like NCED5 (cold), ClpB1 (heat), and MYB44-like (waterlogging). Furthermore, we identified key drivers of fruit quality, including Expansin-A4 and CNR2 for dimensions, CsWOX9 for epidermal spine initiation, and Hd3a for flowering phenology. Transcriptomic profiling provided robust expression support for these prioritized candidate genes within the target mQTL intervals. The markers linked to these genes serve as robust tools for marker-assisted selection and fine mapping, offering precise targets for the development of climate-resilient, high-quality cucumber cultivars.
The intensification of food production systems highlights the need for poultry gut health strategies aligned with One Health goals. Central to this is a balanced gut microbiota, which supports nutrient absorption, immunity, and disease resilience. We applied integrative multi-omics, combining untargeted LC-MS metabolomics and shotgun metagenomics, to explore the caecal responses of commercial Ross-308 broilers to two widely used gut health interventions: ionophore supplementation (T1) and anticoccidial vaccination (T2). Across 7,554 detected metabolites, we identified candidate metabolic signatures: T1 was marked by trends in prenol lipids, including multiple soyasaponins, and enrichment of cellular stress-related pathways (e.g. glutathione pathway). T2 instead was associated with shifts in aromatic amino acid metabolism, elevating tryptophan-derived indoles such as 5-methoxyindole. While global metabolic profiles did not differ significantly (PERMANOVA p > 0.05), supervised integration (DIABLO algorithm) identified 405 potential metabolite-MAG correlations. Bacteroides fragilis emerged as a dominant associate, correlating positively with a diverse range of metabolites (n = 271). Functional gene analysis suggested a link between Mediterraneibacter spp. and soyasaponin deglycosylation, while Ruminococcaceae UBA3818 showed genomic potential for tryptophan utilisation and indole-linked metabolic steps. Our exploratory findings suggest that prophylactic interventions impact the gut microbiome, resulting in divergent subsets of metabolic features. This highlights the potential of microbiome-informed strategies to improve enteric disease management and advance gut health centred approaches in both veterinary and human contexts.
High-altitude hypoxia presents an extreme environmental pressure that challenges human survival, growth, and reproduction. Despite this challenge, humans have thrived on the Andean Altiplano for millennia, displaying several unique physiological responses to hypoxia such as elevated hemoglobin concentration ([Hb]). This trait closely resembles the acclimatization response observed among high-altitude sojourners but is distinct from the sea-level normative [Hb] that characterizes the Tibetan adaptive response. As recent candidate-gene efforts to understand the role of natural selection in shaping Andean [Hb] have produced conflicting results, it remains unclear what role natural selection may have played in shaping this unique hematopoietic response. Using genome-wide array data from Peruvian Andeans, we identified two genomic regions containing three genes, PDE1B, PPP1R1A, and RASGEF1B, that show evidence of recent positive selection and are associated with [Hb]. Importantly, Andean alleles within these regions are associated with lowered [Hb], suggesting that recent polygenic selection may be acting to reduce [Hb] within this population. We observe the greatest divergence of Andean allele frequencies from other global populations within the PDE1B/PPP1R1A region, and use WGS data and publicly available expression and Hi-C data to more closely identify how natural selection may be acting within this region to impact [Hb]. We identify a selective sweep that favors eleven PDE1B expression-decreasing alleles, and is located at the boundary of a topologically associating domain spanning several hemoglobin-linked genes. In sum, this study provides novel evidence that polygenic natural selection may be acting to lower Andean [Hb] in a manner phenotypically convergent with Tibetan populations.
Genome-wide association studies suffer from two major limitations - reductionist statistics and population-level averaging - both of which hinder actionable insights for precision medicine. To bridge these gaps, we introduce a statistical mechanics model that integrates all genetic variants into informative, dynamic, omnidirectional, and personalized networks (idopNetworks), formalized through quasi-dynamic mixed ordinary differential equations. By synthesizing functional mapping, allometric scaling, evolutionary game theory, and modularity theory, this framework shifts the paradigm from reductionist statistics to an omnigenic interactome reconstructed from multi-omics data. The model translates population statistics into patient-specific genomic maps, empowering clinicians to predict individual drug responses and guide multi-site polygenic editing. Ultimately, idopNetworks move therapeutics beyond population averages, offering a scalable tool to design targeted genetic interventions for personalized medicine.
The genetic architecture of bovine hoof and leg conformation traits remains incompletely understood, particularly in dairy cattle and with respect to non-additive effects. Moreover, the limited genetic resolution of previous studies hampered the identification of candidate variants. This study aimed to investigate traits in Swiss Holstein (HO) and Brown Swiss (BS), comprising bone structure, heel depth, foot angle, locomotion, rear leg rear view, and rear leg set in HO, and heel depth, foot angle, hock quality, and rear leg side view in BS, by (1) estimating trait heritabilities, (2) identifying QTL using additive and non-additive GWAS based on imputed whole-genome sequence (WGS) variants, (3) detecting candidate genes and variants using Bayesian fine-mapping, (4) assessing the effects of the recessive HYAL1 on conformation, longevity, and production traits in French HO, and (5) clinically characterizing HYAL1-homozygous HO. Heritability estimates ranged from 0.10 to 0.28 in HO and from 0.10 to 0.26 in BS. Additive and non-additive GWAS detected 25 significant associated regions (P ≤ 5 × 10-8) for bone structure and locomotion in HO and for heel depth and hock quality in BS. Conditional analyses reduced these to 15 unique QTL and Bayesian fine-mapping prioritised 17 candidate variants (3 in HO, 14 in BS), including 15 additive, one dominant, and one recessive effect. A nonsense variant in HYAL1 (NP_001017941.1:p.(Gln93*)) showed a significant recessive effect on bone structure in HO (P = 1.62 × 10-17). The harmful allele was observed predominantly in HO at 4.4% in Swiss and 8.4% in French HO. Analyses in the French population further showed adverse effects on six-year survival, indicating early culling after the first lactation, and 14 routinely recorded conformation and production traits, most notably locomotion and rear leg rear view. Clinical examination of HYAL1-homozygotes revealed polysynovitis. This study indicates a predominantly polygenic architecture of hoof and leg conformation traits in HO and BS cattle and show that integrating imputed WGS data with non-additive analyses of proxy phenotypes improves the detection and refinement of QTL and candidate variants. In particular, the identification of a recessive HYAL1 nonsense variant associated with bone structure in HO uncovered a hidden Mendelian disorder.
As the two main variety groups in improved rice, IND (indica) and JAP (temperate japonica and tropical japonica), extensive studies have utilized (single-nucleotide polymorphisms) SNPs on 233 selected improved rice cultivars to analyze the genetic basis of agronomic traits during their improvement and to compare their similarities and differences. However, the roles of other types of variations, such as insertions and deletions (INDELs) and structural variations (SVs), remain relatively underexplored. Here, using resequencing data from 233 improved rice accessions (IND: 142, JAP: 91), we identified 811,646 INDELs and 16,231 SVs in IND, and 652,793 INDELs and 10,533 SVs in JAP. The abundance of INDELs and SVs decreased as their length increased in both variety groups. INDELs and SVs also showed an uneven distribution across the chromosomes of the two variety groups. In IND, 38.92% of INDELs and 44.1% of SVs were located within the 2 kb upstream and downstream of genes; in JAP, this proportion was 38.49% for INDELs and 43.22% for SVs. By performing genome wide association studies (GWAS) using phenotypic data of six agronomic traits (heading date, flag leaf length, flag leaf width, panicle number, plant height, and thousand grain weight) along with INDELs and SVs, we identified 3,222 significant IND-INDELs, 537 significant IND-SVs, 1,996 significant JAP-INDELs, and 286 significant JAP-SVs. Comparison of significant loci revealed that IND and JAP shared only one INDEL associated with flag leaf length and one SV associated with panicle number, suggesting distinct genetic architectures determined by INDELs and SVs for these traits in the two groups. Furthermore, haplotype analysis of candidate genes demonstrated that INDELs and SVs influence key functional genes, such as the gene TAD1 (IND-INDELs) in flag leaf length, RCN2 (IND-SVs) in heading date, PLS2 (JAP-INDELs) in plant height, and OsYLC2 (JAP-SVs) in leaf development. This study analyzed the variation patterns of INDELs and SVs during the improvement of IND and JAP varieties, and identified INDELs and SVs associated with agronomic traits. These findings will provide valuable genetic and material resources for rice breeding.
Cattle are important livestock that provide essential meat and milk resources. However, a comprehensive analysis of gene expression, alternative splicing (AS), and RNA editing across various organs and developmental stages in cattle has not been reported. This study aims to create a comprehensive transcriptomic BodyMap across various tissues and developmental stages, integrating this information into genomic predictions of beef production traits. We created a comprehensive transcriptomic BodyMap using 400 samples collected from 52 organs of newborn, young, and adult cattle, and estimated their contributions to genetic variance and genomic predictions for 23 beef production traits in 1476 beef cattle. We cataloged the expression of 25,530 annotated genes, 28,533 novel long non-coding RNAs (lncRNAs), 215,754 AS events, and 3,093,058 A-to-I RNA-editing sites. Integrating transcriptome BodyMap with 23 beef production traits, we found lncRNAs influenced traits like rib-eye area and carcass length, while RNA editing associated with chunk roll weight and daily gain. We observed trait-relevant tissues between different stages, including the differential expressed genes of cerebellum, longissimus muscle, and testis between newborn and adult stages are more relevant to beef production traits. The tissue-specific genes and development-associated genes in several tissues could improve the reliability of genomic prediction in beef production traits. We developed Cattle BodyMap Transcriptome Database (https://cattlegenomics.online/cattle_bodymap) to retrieve, analyze, and visualize gene expression, lncRNA, splicing and RNA editing data. Our results demonstrated the potential of using transcriptome data as a valuable resource for genomic selection and breeding programs in beef cattle. Additionally, our transcriptome BodyMap serves as a valuable resource for biological interpretation, functional validation, and genomic improvement in livestock.
In India, indigenous camel populations have evolved under diverse ecological conditions, leading to the emergence of several distinct breeds with specialised adaptive traits. Understanding the genomic architecture and population structure of such camel populations is essential for their conservation and sustainable utilisation. In the present study, whole-genome sequencing data were generated and analysed for Indian dromedary camels representing nine recognised breeds, along with Indian Bactrian (double-humped) and Arabian Peninsula dromedaries with the primary objective to investigate population structure and to assess the genetic distinctiveness of the geographically isolated Kharai camel, a unique breed adapted to coastal and saline environments. The sequencing depth ranged from 11.3× to 25.4× for Indian dromedaries, with high mapping efficiency to the reference genome (mCamDro1). Population structure analyses consistently revealed limited genetic differentiation among most Indian dromedary populations, reflecting shared ancestry and historical gene flow. However, the Kharai camel exhibited clear genetic distinctiveness across multiple analytical approaches. Principal component analysis separated Kharai from other dromedaries, and admixture analysis at K = 2 demonstrated near-complete clustering of Kharai individuals to a distinct ancestral component. Pairwise genetic distances (FST) further supported moderate differentiation in Kharai (0.07-0.10), compared with the low differentiation observed among other populations. Neighbour-Net and phylogenetic tree analyses corroborated these findings, showing breed-specific clustering with clear separation of Kharai. Genome-wide diversity analysis revealed a predominance of low-frequency alleles (57.7% of SNPs with MAF 0.05-0.10), indicating population subdivision and localised demographic histories. Moderate genetic diversity was observed (Hₒ = 0.303 ± 0.001; Hₑ = 0.319 ± 0.0001), with evidence of a mild heterozygote deficit likely attributable to the Wahlund effect. Linkage disequilibrium (LD) analysis showed strong short-range LD (r² = 0.783 at 0-10 kb) with gradual decay up to 10 Mb, suggesting a moderate historical effective population size. LD-based reconstruction indicated a decline in effective population size from > 2,500 ancestral individuals to approximately 167 individuals in recent generations, highlighting demographic contraction. These findings demonstrate substantial genetic homogeneity among Indian dromedary populations while highlighting the distinct genomic identity of the Kharai camel breed. The results underscore the evolutionary uniqueness of this breed and emphasise the need for targeted conservation and management strategies to preserve its genetic resources.
The increase in cases of infectious diseases related to multidrug-resistant bacteria and the spread of multidrug-resistant genes have driven the search for therapeutic alternatives that can circumvent this global phenomenon. One of these alternatives is the use of bacteriophages, which are viruses capable of infecting and killing specific bacteria. Klebsiella pneumoniae species complex (KpSC) is an important opportunistic group associated with multidrug resistance. This group includes Klebsiella quasipneumoniae subsp. similipneumoniae, a species recognized as a clinically relevant pathogen, and that was used as a host (designated Klebsiella KH1) to isolate the phage characterized in the present study. The characterization of new phages is essential to expand the therapeutic arsenal and to improve our understanding on phage diversity. In this study, we evaluated a Klebsiella bacteriophage named KP47 that was isolated from sewage in the United Kingdom. We performed phage biological and genomic characterization in order to assess its therapeutic attributes. KP47 represents a newly isolated Klebsiella phage, being able to infect both K. pneumoniae and K. quasipneumoniae subsp. similipneumoniae, which also shows evidence of depolymerase activity and an efficient bacteriolytic performance. The phage KP47 showed a typical morphology of the Caudoviricetes class, with a capsid of 48 nm and a tail of 161 nm. Its genome has 47,396 bp, 63 CDSs, and a GC content of 57.52%, which apparently encodes a depolymerase. ViPTree analysis placed KP47 near Drexlerviridae-related phages, while comparative analyses using representative RefSeq genomes revealed low intergenomic similarity. This phage demonstrated strictly lytic behavior and fast adsorption (90% in 6 min). MOI experiments indicated complete inhibition of bacterial growth in MOIs ≥ 1. The phage infected two out of nine tested strains belonging to the strains of KpSC. In this study, we described the Klebsiella phage KP47, likely representing a new viral genus, that exhibits a strictly lytic lifestyle, rapid adsorption (90% within 6 min), and an effective bacterial growth inhibition at MOIs ≥ 1. KP47 was able to infect clinically relevant members of the Klebsiella pneumoniae species complex. Further investigations of its potential to act on biofilms and against Klebsiella species in in vivo models are of interest to evaluate its potential for clinical application.
The Greenland shark (Somniosus microcephalus) is a deep-sea vertebrate inhabiting the cold waters of the North Atlantic and Arctic Ocean and is renowned for its exceptional longevity, with individuals estimated to live for more than 400 years. It has also been proposed as a candidate species exhibiting negligible senescence. This narrative review synthesizes current knowledge on the biological mechanisms that may contribute to this phenotype. Potential contributing factors include its extreme environment, low metabolic rate and remarkably late sexual maturation, all of which may reduce cumulative physiological stress over time. At the molecular level, recent genomic studies have identified distinctive features, including duplications of DNA repair genes and structural variation in the tumour suppressor protein p53, which are consistent with enhanced genome maintenance, although their functional significance remains to be experimentally validated. Additional mechanisms, such as proteostatic resilience, antioxidant defences and immune adaptations, may further support long-term cellular homeostasis. Collectively, these observations suggest that the Greenland shark possesses biological characteristics that could influence multiple hallmarks of ageing, including genomic stability, proteostasis and intercellular communication. Emerging evidence also indicates resistance to age-related functional decline in systems such as vision and cardiac function. Taken together, these characteristics highlight the Greenland shark as a valuable, yet still underexplored, model for investigating the biology of longevity and resistance to ageing. Further research in this species may provide insights into the mechanisms underlying healthy ageing across vertebrates and generate hypotheses for future translational studies.
Atherosclerotic cardiovascular disease (ASCVD) remains a leading cause of mortality worldwide, yet its genetic architecture and underlying mechanistic hypotheses have not been fully elucidated. We applied genomic structural equation modeling (SEM) to five ASCVD-related phenotypes with a total combined sample size of approximately 3.8 million individuals across the five component GWAS. Leveraging these genetic insights, we performed a cross-tissue transcriptome-wide association study (TWAS) using the UTMOST framework by integrating ASCVD genetic data with gene expression from 49 tissues (GTEx v8). Complementary analyses included single-tissue TWAS (FUSION) and gene-level analysis (MAGMA). By triangulating evidence from these multiple convergent statistical approaches, we identified robust candidate genes, which were further prioritized using Mendelian randomization, Bayesian colocalization, phenome-wide association studies (PheWAS), tissue/cell-type enrichment analyses, and AlphaFold-based structural predictions integrated with chemical interaction profiling. We identified 14 genes robustly associated with ASCVD susceptibility, including four genes-ARVCF, GFPT1, NFU1, and USP39-some of which have been previously implicated in coronary artery disease genetics (ARVCF) or are newly prioritized in the composite ASCVD phenotype (USP39), exhibiting broad tissue expression patterns. Mendelian randomization and colocalization provided supportive evidence consistent with potential causal relationships, with pronounced tissue specificity (e.g., ARVCF in artery aorta, GFPT1 in heart atrial appendage, NFU1 in adipose subcutaneous). Cell-type enrichment highlighted erythroid progenitor cells and immune populations. PheWAS revealed potential horizontal pleiotropy, while network and pathway analyses implicated these genes in cell adhesion, amino sugar metabolism, iron-sulfur cluster assembly, and RNA splicing. Structural predictions confirmed protein model reliability, and chemical interaction profiling linked these genes to cardiovascular and metabolic disease pathways. Our integrative statistical genetics approach advances the functional understanding of ASCVD genetics, implicates four genes in disease pathogenesis with tissue-specific mechanisms, and highlights promising candidate genes for future investigation.
Podocytopathies are kidney diseases caused by podocyte injury or dysfunction that drives proteinuria or nephrotic syndrome. A significant expansion in understanding of the complex causes and mechanisms of podocyte injury, as well as potential therapeutic approaches, has been achieved over the past two decades with rapid advances in genomics in both research and clinical practice. Podocytopathies associated with monogenic mechanisms account for approximately 30% of cases with steroid-resistant nephrotic syndrome (SRNS) or focal segmental glomerulosclerosis lesions (FSGS), with even higher proportions in pediatric patients. Podocytopathies related to each gene mutation are rare. However, recent developments in these rare podocytopathies contribute to an optimistic outcome for the future to eventually avoid kidney failure. This review therefore focuses on aspects of new advances of therapies in rare podocytopathies with monogenic causes.
Prior biological knowledge and phenotype information can help identify disease genes from whole genome/exome sequencing studies, but how best to incorporate external knowledge with variant data remains challenging. We developed a machine learning algorithm called RankVar to prioritize causative variants for rare diseases, based on clinical notes and genome/exome sequencing profiles. RankVar uses a random forest classifier trained on ~ 1 million variants from the 1000 Genomes Project with spiked-in pathogenic variants. For testing, we compiled sequencing data and phenotype information from several independent datasets: 260 subjects from the Children's Hospital of Philadelphia (CHOP) with positive genetic diagnosis of various Mendelian diseases, 135 subjects from Birth Defects Biorepository (BDB), as well as 356 and 97 subjects with candidate causal variants for autism spectrum disorders from the Simons Simplex Collection (SSC) and the Simons Foundation Powering Autism Research for Knowledge (SPARK), respectively. RankVar achieves a top 10 variant accuracy of 90.0%, 81.5%, 46.1%, and 76.3% for CHOP, BDB, SSC, and SPARK, respectively, with improved performance over existing approaches. Notably, RankVar successfully identified X-linked and Y-linked disease-causal variants, such as KDM6A (p.N915Kfs5*) and SRY (p.W98X), as the top candidate variants. Moreover, we evaluated RankVar for genomic reinterpretation of 130 unsolved CHOP cases with hearing loss and successfully identified 61 candidate causal variants after manual review. In summary, RankVar performed favorably relative to existing methods in our evaluation, accommodated different genetic models and X/Y chromosome variants, and may provide a useful framework for prioritizing variants in monogenic or oligogenic diseases. We anticipate that RankVar may aid in primary genetic diagnosis, genome reinterpretation of previously unsolved cases, and the discovery of novel disease genes.
Bacterial transcription termination is a critical yet underexplored layer of gene regulation in microbial ecosystems. Existing computational tools, however, primarily focus on predicting transcript 3' ends generated by Rho-independent terminators (RITs) in a few model species, leaving gaps in understanding those generated by Rho-dependent terminators (RDTs) and their diversity across Bacteria. We developed BATTER (Bacteria Transcript Three Prime End Recognizer), a deep learning-based framework for predicting bacterial transcript 3' termini. BATTER leverages the observation that conserved stem-loop structures are frequently associated with 3' ends of primary transcripts terminated by both RIT and RDT mechanisms across diverse bacterial clades. Compared with existing approaches, BATTER demonstrated superior performance and scalability, enabling a comprehensive analysis of 42,905 representative bacterial genomes. This large-scale application revealed that stem-loop structures exhibit clade-specific properties with greater variations between species than between gene families. Notably, BATTER uncovered that certain Cyanobacteria lineages, despite lacking rho homologs, harbor Rho utilization (RUT)-like sequences near 3' ends, and preliminary experimental validation in E. coli supports their partial functionality in transcription termination. Additionally, BATTER systematically identified pervasive premature termination events in antimicrobial resistance (AMR) genes. BATTER enables large-scale comparative genomic analyses of transcription termination, providing a powerful framework to investigate termination-associated transcriptional regulation in microbial communities. The BATTER tool is available at https://github.com/xu-research-lab/BATTER. Video Abstract.
Sex differences in the incidence and outcomes of non-reproductive cancers persist across many tumor types, even after adjustment for major exposure- and care-related factors. This review examines how sex-hormone signaling may contribute to these patterns through tumor-intrinsic mechanisms and regulation of the tumor microenvironment. In tumor cells, ER, AR and PR mediate classical nuclear transcriptional programs, whereas membrane-associated or cytoplasmic receptor pools, together with GPER, support rapid non-genomic signaling through PI3K/AKT, MAPK/ERK and related kinase or second-messenger pathways. Intratumoral steroid handling can create local ligand conditions that differ from circulating hormone levels and modify context-specific receptor activity. Hormonal context may also influence vascular, stromal and immune phenotypes. Clinically, sex-hormone-related tumor states may be better captured by integrated activity-based readouts, including receptor status, pathway activation, local steroid availability and immune context, rather than receptor immunostaining alone. Overall, sex-hormone signaling offers a hypothesis-generating framework for understanding sex-biased tumor biology beyond traditional hormone-driven cancers, but its clinical relevance requires further mechanistic and prospective validation.
Neuronal differentiation is a highly regulated process in which morphogens establish cellular identities through coordinated transcriptional programs. However, the contribution of physiologically derived metabolites to human neural development remains poorly understood. β-hydroxybutyrate (bhb) has been recognized as an inflammatory, epigenetic, energetic, and neuroprotective regulator. We differentiated midbrain floor plate neural precursor cells (mfNPC) from human embryonic stem cells to generate midbrain organoids (MBOs), which were exposed to bhb. Although dopaminergic differentiation occurred in control MBOs, treatment with 1 mM bhb for 16 days significantly increased both the number of Tyrosine hydroxylase-positive (TH⁺) neurons, and the corresponding transcripts assessed by bulk RNA sequencing. Such transcriptomic profiling revealed modest but consistent bhb-associated changes in trophic, neuronal and dopaminergic transcripts. To further characterize these changes, we performed gene set enrichment analysis using curated cell phenotypes-associated transcriptional programs. These analyses indicated that bhb treatment is associated with shifts in the enrichment scores of dopaminergic programs in day 16 MBOs. At the epigenomic level, we used CUT&RUN assays to map H3K27 acetylation, and the selected candidates H3K27ac regions after bhb treatment were linked to their closest neighboring genes, suggesting positive enrichment of neural and dopaminergic gene ontology categories at both time points. Unsupervised analysis of H3K27ac-enriched regions revealed three major clusters detected across differentiation, although present in both control and bhb-treated MBOs. Motif enrichment analysis of clustering regions identified distinct predicted transcription factor binding motifs in mfNPC and MBOs. Finally, we integrated this motif analysis, enhancer annotation, and our transcriptomic data on a web platform, Enhancer Network Explorer, to explore relationships between H3K27ac profiles, transcriptional changes and bhb exposure during human MBOs differentiation. Together, our results indicate that bhb treatment is associated with increased TH-positive cell abundance and with population-level changes related to neurodevelopmental transcriptional programs. These findings suggest that bhb might support early human midbrain differentiation and provide a starting point for future studies addressing the mechanisms linking metabolic cues, chromatin-associated regulation and dopaminergic differentiation.
Canine distemper virus (CDV) can cause fatal viral infection in domestic and wild animals globally. Several lineages are known, originating from distinct geographical regions and hosts, and can spread naturally or through human intervention into new geographic areas. The Arctic lineage was first described in carnivores of the Arctic ecosystems and subsequently reported in several European and Asian countries, yet its origin, evolution, and ecology remain partially unresolved. In this study, we generated genome sequence data of (n = 16) CDV strains of Arctic lineage collected from dogs in Italy over a nearly 15-year period, providing an extensive dataset to investigate the evolution of this particular lineage. We also generated genome data of seven Europe strains of another major lineage collected during the same period from red foxes (n = 3) and dogs (n = 4). Inter-lineage recombination events were identified in two CDV sequences. Sequence 2008 of the European lineage acquired a fragment from an Arctic lineage virus between the N and P genes. Sequence 2015 of the Arctic lineage displayed a more complex recombination pattern with fragments from Europe, America-2, and Rockborn lineages across multiple genes and hosts. Phylogenetic tree showed that the oldest Italian Arctic lineage from 2006 was more similar to the oldest Arctic CDV isolates, whilst a well-defined sub-cluster circulated from 2009 onwards in domestic and wild carnivores. These results provide novel insights into CDV evolution in Europe and emphasize the importance of ongoing genomic monitoring.