Human Genome Sciences (United States)

Moyamoya disease (MMD) has a strong genetic basis, with the rare RNF213 p.Arg4810Lys variant (rs112735431) representing a major risk factor, while the broader genetic architecture and disease-relevant vascular cell types remain incompletely understood. We conducted a genome-wide association study in Japanese individuals (n=47 656; 401 MMD cases and 47 255 controls). Population-level features at MMD risk loci were examined by regional allele frequency and haplotype analyses. We performed single-nucleus RNA-seq of superficial temporal arteries from patients with MMD (n=3). Cell type-specific enrichment of genome-wide association study signals was assessed using the Single-Cell Disease Relevance Score. Endothelial signatures were validated by integration with publicly available single-cell data sets from controls (n=5) and immunohistochemistry for candidate markers (n=1). Beyond rs112735431, we identified a genome-wide significant signal in the HDAC9-TWIST1 region (rs12530920; P=3.3×10-14; odds ratio, 1.77). Conditional analysis on rs112735431 revealed a protective RNF213 missense variant, p.Asp1331Gly (rs8074015; P=3.7×10-9; odds ratio, 0.53), whose minor allele was mutually exclusive with rs112735431-A on haplotypes. Population analysis revealed geographic variation and extended haplotype structure of the rs112735431-A allele in Japan. Single-nucleus RNA-seq identified a mesenchymal-like endothelial cell (MEC) population with selective FN1 expression. Genome-wide association study-prioritized disease genes were strongly enriched in MECs. MECs showed mesenchymal pathway activation with a regulatory program distinct from canonical endothelial states. The proportion of MECs was markedly increased in MMD (72% versus 28% in controls), and fibronectin 1 (FN1) expression in endothelial regions was confirmed by immunohistochemistry. Our findings identify a protective RNF213 p.Asp1331Gly variant (rs8074015) that is mutually exclusive with the known rs112735431-A allele. Genetic risk converges on an MEC state markedly expanded in MMD.

Predicting genetic perturbation responses at a single-cell level is central to building models for cell state and disease. However, existing approaches are limited on predicting phenotypic outcomes beyond expression changes and generalizing predictions across genome-scale perturbations in biologically relevant contexts. Here we introduce pertTF, a transformer-based single-cell genetic perturbation model. pertTF was trained from a unique dataset capturing single cell expressions profiles of 30 full gene knockouts across 14 relevant cell types during human pancreatic development and beta-cell differentiation. pertTF outperforms current methods in predicting expression changes of perturbing unseen genes in unseen cellular contexts. In addition, pertTF infers perturbation-induced shifts in cell identity and population composition, an important phenotypic outcome of perturbation in many physiology and disease settings. Through transfer learning, pertTF operates in physiologically relevant systems, including primary human islets, where large-scale perturbation experiments are challenging. The generalizability of pertTF is further demonstrated by in silico pooled and single-cell CRISPR screens, capturing critical regulators of stem cells and early pancreatic cell development. These results establish pertTF as a framework for integrating large-scale single-cell perturbation data with AI models to predict genetic perturbation effects across cellular systems and disease contexts.

Abstract Peanut smut, caused by the fungus Thecaphora frezzii , is a significant disease of peanuts in Argentina. Infected plants have seeds replaced by a mass of dark teliospores, reducing yield and seed quality. To prevent the spread of the pathogen, several countries have limited import of raw peanuts from Argentina, a major grower and exporter. Following successful in vitro culture of the fungus in its haploid stage, we produced a chromosome-level genome assembly of the species for the first time. We compare this genome with those of 49 other species of true smut fungi, or Ustilaginomycetes, including species of medical, agricultural, and industrial importance, some of which are known as pathogens and others only as saprotrophic yeasts. At almost 39 Mb, T. frezzii has the largest genome of the smut fungi sequenced to date and the highest repetitive content. While it shares some core effectors with species of the distantly related and better studied Ustilago and related fungi, predicted effectors only found in T. frezzii or in Thecaphora suggest unique infection strategies. Comparisons among the 50 smut genomes also show that the 14 smut fungi observed only as yeasts share genomic traits such as low repeat content and generally smaller genomes. This supports the hypothesis that some smut fungi are adapted to saprotrophic growth as yeasts. The high-quality, annotated genome for T. frezzii will be a valuable resource for investigating the population dynamics and evolution of an economically important pathogen, as well as illuminating an understudied clade of smut fungi. Article summary Peanut smut is a destructive and costly disease of peanuts in Argentina. For the first time, a high quality, annotated genome is presented for the causal agent, Thecaphora frezzii . This fungus has the largest and most repetitive genome of the true smut fungi, thus prompting comparison with 49 other species of smut fungi with available genomes, including non-pathogenic ones. While it shares some likely pathogenicity factors with well-studied smuts, it has many unique genes, a trait reflective of its evolutionary distance and likely novel mechanism for infection. This important genomic resource will benefit research regarding the evolution and adaption of T. frezzii , the development of diagnostic tools that enable rapid detection of it, and the study of smut fungi broadly.

Abstract Oscillatory processes such as the cell cycle play critical roles in cell fate determination and disease development, yet existing gene regulatory network (GRN) inference methods often fail to account for their dynamic nature. We propose CycleGRN , a novel framework that treats cell cycle gene expression observations as an invariant measure of a stochastic differential equation and learns from data a dynamical system that fits cycling biological processes. Using a directed graph constructed along the inferred flow field in the cell space, we estimate Lie derivatives for all genes, enabling velocity inference beyond the cell cycle subspace. To quantify regulatory interactions, we introduce a time-lagged correlation operator between any pair of genes supported on the flow-aligned directed graph, which respects the intrinsic geometry of the data manifold and allows temporal ordering consistent with the underlying oscillatory process. The method requires only raw gene expression data at single-cell resolution and a list of cycle genes, without temporal binning or splicing dynamics. We evaluate our method on four synthetic datasets generated from mechanistic models with known network structures with oscillatory subnetworks, and on a mouse retinal progenitor single-cell RNA-seq dataset spanning three cell types and a knockout condition. Across all settings, our method outperforms existing methods, demonstrating its ability to recover causal and oscillatory interactions from static single-cell RNA-seq datasets.

Chronic dermatological conditions such as acne vulgaris, androgenetic alopecia (AGA), and alopecia areata (AA) affect hundreds of millions worldwide and contribute substantially to quality-of-life impairment. Despite the availability of systemic retinoids, anti-androgens, and JAK inhibitors, therapeutic responses remain heterogeneous and relapse is common, underscoring the need for biologically grounded stratification. Over the past decade, large genome-wide association studies and functional analyses have clarified disease-specific and cross-cutting mechanisms. In AA, multiple independent HLA class II signals and immune-regulatory loci such as BCL2L11 and LRRC32 establish antigen presentation and interferon-γ/JAK–STAT signalling as central drivers, consistent with clinical responses to JAK inhibition. AGA is driven by variation at the androgen receptor and 5-α-reductase genes alongside WNT/TGF-β regulators (WNT10A, LGR4, RSPO2, DKK2), explaining follicular miniaturisation and enabling polygenic risk prediction. Acne genetics highlight an immune–morphogenesis–lipid triad, with loci in TGFB2, WNT10A, LGR6, FASN, and FADS2 linking follicle repair, innate sensing, and sebocyte lipid metabolism. Barrier modulators such as FLG and OVOL1, first described in atopic dermatitis, further shape inflammatory thresholds across acne and related phenotypes. Together, these findings position genetics not as an abstract catalogue of risk alleles but as a map of tractable biological pathways. They provide the substrate for patient-stratified interventions ranging from JAK inhibitors in AA, to endocrine versus morphogenesis-targeted strategies in AGA, to lipid- and barrier-directed therapies in acne, while also informing cosmetic practices focused on barrier repair, sebaceous balance, and follicle health.

Rationale: High-attenuation area (HAA) is a computed tomography (CT) tool that correlates with lung inflammation and fibrosis. Systemic molecular correlates of HAA (e.g., plasma proteins) may inform biological processes involved in interstitial lung disease. Objectives: To identify plasma proteins that associate with HAA and correlate with a higher probability of developing new-onset fibrotic or subpleural interstitial lung abnormalities (ILAs). Methods: Plasma protein levels were measured using a semiquantitative aptamer-based platform in MESA (the Multi-Ethnic Study of Atherosclerosis; N = 5,486) and SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study; N = 1,781). Linear regression models identified HAA-associated proteins after adjustment for demographic and socioeconomic factors, CT scanner parameters, study center, and batch. Associations of HAA-related proteins with new-onset fibrotic or subpleural ILAs were examined in MESA participants with ILA assessments on full-lung CT 10 years later. Immunohistochemical staining of select proteins was performed in lung tissue from pulmonary fibrosis cases. Measurements and Main Results: There were 75 proteins detected that were significantly associated with HAA in MESA and SPIROMICS. Gene Ontology analysis of these proteins identified processes involved in immune cell chemotaxis and cellular growth and apoptosis. Seven proteins were associated with a higher probability of new-onset fibrotic or subpleural ILAs in MESA, and two of these, junctional adhesion molecule-like protein and GTP cyclohydrolase 1 feedback regulatory protein, stained in areas of fibrosis in lung tissue from patients with interstitial lung disease. Conclusions: Plasma proteins associated with more HAA are involved in immune and cellular processes and associate with new-onset fibrotic-subpleural ILA.

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Background:Recent studies suggest measles-induced immune amnesia could have long-term immunosuppressive effects via preferential depletion of memory CD150+ lymphocytes, and associations with a 2–3 year period of increased mortality and morbidity from infectious diseases other than measles has been shown in children from wealthy and low-income countries. To further examine the associations previous measles virus infection may have on immunologic memory among children in the Democratic Republic of the Congo (DRC), we assessed tetanus antibody levels among fully vaccinated children, with and without a history of measles.Methods:We assessed 711 children 9–59 months of age whose mothers were selected for interview in the 2013–2014 DRC Demographic and Health Survey. History of measles was obtained by maternal report and classification of children who had measles in the past was completed using maternal recall and measles IgG serostatus obtained from a multiplex chemiluminescent automated immunoassay dried blood spot analysis. Tetanus IgG antibody serostatus was similarly obtained. A logistic regression model was used to identify association of measles and other predictors with subprotective tetanus IgG antibody.Results:Subprotective geometric mean concentration tetanus IgG antibody values were seen among fully vaccinated children 9–59 months of age, who had a history of measles. Controlling for potential confounding variables, children classified as measles cases were less likely to have seroprotective tetanus toxoid antibody (odds ratio: 0.21; 95% confidence interval: 0.08–0.55) compared with children who had not had measles.Conclusions:History of measles was associated with subprotective tetanus antibody among this sample of children in the DRC who were 9–59 months of age and fully vaccinated against tetanus.

ABSTRACTMany mutations in genes for ribosomal proteins (r-proteins) and assembly factors cause cell stress and altered cell fate, resulting in congenital diseases collectively called ribosomopathies. Even though all such mutations depress the cell’s protein synthesis capacity, they generate many different phenotypes, suggesting that the diseases are not due simply to insufficient protein synthesis capacity. To learn more, we investigated how the global transcriptome in Saccharomyces cerevisiae responds to reduced protein synthesis generated in two different ways: abolishing the assembly of new ribosomes and inhibiting ribosomal function. Our results showed that the mechanism by which protein synthesis is obstructed affects the ribosomal protein transcriptome differentially: ribosomal protein mRNA abundance increases during the abolition of ribosome formation but decreases during the inhibition of ribosome function. Interestingly, the ratio between mRNAs from some, but not all, pairs of paralogous ribosomal protein genes encoding slightly different versions of a given r-protein changed differently during the two types of stress, suggesting that expression of specific ribosomal protein paralogous mRNAs may contribute to the stress response. Unexpectedly, the abundance of transcripts for ribosome assembly factors and translation factors remained relatively unaffected by the stresses. On the other hand, the state of the translation apparatus did affect cell physiology: mRNA levels for some other proteins not directly related to the translation apparatus also changed differentially, though not coordinately with the r-protein genes, in response to the stresses.IMPORTANCE Mutations in genes for ribosomal proteins or assembly factors cause a variety of diseases called ribosomopathies. These diseases are typically ascribed to a reduction in the cell’s capacity for protein synthesis. Paradoxically, ribosomal mutations result in a wide variety of disease phenotypes, even though they all reduce protein synthesis. Here, we show that the transcriptome changes differently depending on how the protein synthesis capacity is reduced. Most strikingly, inhibiting ribosome formation and ribosome function had opposite effects on the abundance of mRNA for ribosomal proteins, while genes for ribosome translation and assembly factors showed no systematic responses. Thus, the process by which the protein synthesis capacity is reduced contributes decisively to global mRNA composition. This emphasis on process is a new concept in understanding ribosomopathies and other stress responses.