Neuron, Journal Year: 2025, Volume and Issue: unknown
Published: April 1, 2025
Language: Английский
Neuron, Journal Year: 2025, Volume and Issue: 113(1), P. 82 - 108
Published: Jan. 1, 2025
SummaryBrain aging leads to a decline in cognitive function and concomitant increase the susceptibility neurodegenerative diseases such as Alzheimer's Parkinson's diseases. A key question is how changes within individual cells of brain give rise age-related dysfunction. Developments single-cell "omics" technologies, transcriptomics, have facilitated high-dimensional profiling cells. These technologies led new comprehensive characterizations at resolution. Here, we review insights gleaned from omics studies aging, starting with cell-type-centric overview age-associated followed by discussion cell-cell interactions during aging. We highlight provide an unbiased view different rejuvenation interventions comment on promise combinatorial approaches for brain. Finally, propose directions, including models neural stem focal point rejuvenation.
Language: Английский
Citations
0
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 14, 2025
Single-omics approaches often provide a limited view of complex biological systems, whereas multiomics integration offers more comprehensive understanding by combining diverse data views. However, integrating heterogeneous types and interpreting the intricate relationships between features-both within across different views-remains bottleneck. To address these challenges, we introduce COSIME (Cooperative Multi-view Integration Scalable Interpretable Model Explainer). uses backpropagation Learnable Optimal Transport (LOT) to deep neural networks, enabling learning latent features from multiple views predict disease phenotypes. In addition, incorporates Monte Carlo sampling efficiently estimate Shapley values Shapley-Taylor indices, assessment both feature importance their pairwise interactions-synergistically or antagonistically-in predicting We applied simulated real-world datasets, including single-cell transcriptomics, spatial epigenomics, metabolomics, specifically for Alzheimer's disease-related Our results demonstrate that significantly improves prediction performance while offering enhanced interpretability relationships. For example, identified synergistic interactions microglia astrocyte genes associated with AD are likely be active at edges middle temporal gyrus as indicated locations. Finally, is open-source available general use.
Language: Английский
Citations
0
medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 19, 2025
Abstract Population-scale single-cell transcriptomic technologies (scRNA-seq) enable characterizing variant effects on gene regulation at the cellular level (e.g., eQTLs; sc-eQTLs). However, existing sc-eQTL mapping approaches are either not designed for analyzing sparse counts in scRNA-seq data or can become intractable extremely large datasets. Here, we propose jaxQTL, a flexible and efficient framework using highly count-based models given pseudobulk data. Using extensive simulations, demonstrated that jaxQTL with negative binomial model outperformed other identifying sc-eQTLs, while maintaining calibrated type I error. We applied across 14 cell types of OneK1K ( N =982), identified 11-16% more eGenes compared approaches, primarily driven by ability to identify lowly expressed eGenes. observed fine-mapped sc-eQTLs were further from transcription starting site (TSS) than eQTLs all cells (bulk-eQTLs; P =1×10 −4 ) enriched cell-type-specific enhancers =3×10 −10 ), suggesting improve our distal missed bulk tissues. Overall, genetic effect largely shared types, cell-type-specificity increasing distance TSS. Lastly, explain SNP-heritability h 2 bulk-eQTLs (9.90 ± 0.88% vs. 6.10 0.76% when meta-analyzed 16 blood immune-related traits), improving but closing missing link between GWAS eQTLs. As an example, highlight T (unlike bulk-eQTLs) successfully nominate IL6ST as candidate rheumatoid arthritis. provides powerful approach disease-associated
Language: Английский
Citations
0
Trends in Genetics, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 1, 2025
Language: Английский
Citations
0
Advanced Science, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 23, 2025
Abstract The primate cerebral cortex, the major organ for cognition, consists of an immense number neurons. However, organizational principles governing these neurons remain unclear. By accessing single‐cell spatial transcriptome over 25 million neuron cells across entire macaque it is discovered that distribution within cortical layers highly non‐random. Strikingly, three‐quarters are located in distinct neuronal clusters. Within clusters, different cell types tend to collaborate rather than function independently. Typically, excitatory clusters mainly consist excitatory‐excitatory combinations, while inhibitory primarily contain excitatory‐inhibitory combinations. Both cluster have roughly equal numbers each layer. Importantly, most and form partnerships, indicating a balanced local network correlating with specific functional regions. These conserved mouse findings suggest brain regions cortex may exhibit similar mechanisms at population level.
Language: Английский
Citations
0
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 31, 2025
Changes in cell type composition play an important role human health and disease. Recent advances single-cell technology have enabled the measurement of at increasing lineage resolution across large cohorts individuals. Yet this raises new challenges for statistical analysis these compositional data to identify changes frequency. We introduce crumblr ( DiseaseNeurogenomics.github.io/crumblr ), a scalable method analyzing count ratio using precision-weighted linear mixed models incorporating random effects complex study designs. Uniquely, performs testing multiple levels hierarchy multivariate approach increase power over tests one type. In simulations, increases compared existing methods while controlling false positive rate. demonstrate application published RNA-seq datasets aging, tuberculosis infection T cells, bone metastases from prostate cancer, SARS-CoV-2 infection.
Language: Английский
Citations
0
Communications Biology, Journal Year: 2025, Volume and Issue: 8(1)
Published: Feb. 5, 2025
Oligodendrocytes are the myelinating cells within central nervous system, but mechanisms by which transcription factors (TFs) cooperate for gene regulation in oligodendrocytes remain unclear. We introduce coTF-reg, an analytical framework that integrates scRNA-seq and scATAC-seq data to identify cooperative TFs co-regulating target (TG). First, we co-binding TF pairs same oligodendrocyte-specific regulatory regions. Next, train a deep learning model predict each TG expression using TFs' expressions. Shapley interaction scores reveal high interactions between pairs, such as SOX10-TCF12. Validation oligodendrocyte eQTLs their eGenes regulated these show potential roles genetic variants. Experimental validation ChIP-seq confirms some SOX10-OLIG2. Prediction performance of our models is evaluated through holdout additional datasets, ablation study also conducted. The results demonstrate stable consistent performance. authors regulate genes cooperatively oligodendrocytes.
Language: Английский
Citations
0
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 6, 2025
Summary Not only the abundance of gene expression but also its cell-to-cell variation, referred to as “transcriptional noise”, is known have certain biological significance. However, mechanistic basis transcriptional noise, particularly how it regulated by genetic variants, remains elusive. In this study, we analyzed single-cell RNA sequencing (scRNA- seq) data human induced pluripotent stem cell (iPSC)-derived midbrain cells (795,661 in 17 conditions) from 155 individuals with their genotypes perform genome-wide mapping quantitative trait loci for noise (tnQTLs). Our analyses controlling confounding factors such identified a total 101,024 significant tnQTL-gene pairs. A comparison QTLs levels (i.e. eQTLs) detected an equivalent pipeline revealed that majority (81%) tnQTLs were eQTLs, while no eQTL effects observed others, and small portion (7%) eQTLs tnQTL effects. The showed distinctive patterns sharing across cellular conditions, where often more condition-specific than those eQTLs. particular, without (termed tn>eQTLs) dramatically altered rotenone-induced oxidative stress. tn>eQTLs exhibited unique enrichment various functional genomic elements, being frequently promoters non-QTL target genes. analysis using summary statistics association studies (GWAS) complex traits, found nominally heritability schizophrenia tn>eQTLs. Possible contributions risk supported signals We genes whose was implicated be causally associated Mendelian randomization analysis, including HLA YWHAE multiple autoimmune/psychiatric disorders. To further explore role dysregulation disease, scRNA-seq mouse model brains. Genes exhibiting differential between cases controls, i.e. differentially noisy (DNGs), abundant superficial deep layer excitatory neurons, GWAS enriched DNGs. Overall, our comprehensive provides resource new class regulatory deepens understanding variants regulate highlights roles traits.
Language: Английский
Citations
0
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 8, 2025
Abstract HIV infection exerts profound and long-lasting neurodegenerative effects on the central nervous system (CNS) that can persist despite antiretroviral therapy (ART). Here, we used single-nucleus multiome sequencing to map transcriptomic epigenetic landscapes of postmortem human brains from 13 healthy individuals 20 with who have a history treatment ART. Our study spanned three distinct regions—the prefrontal cortex, insular ventral striatum—enabling comprehensive exploration region-specific cross-regional perturbations. We found widespread persistent HIV-associated transcriptional alterations across multiple cell types. Detailed analyses microglia revealed state changes marked by immune activation metabolic dysregulation, while integrative multiomic profiling astrocytes identified subpopulations, including reactive subpopulation unique HIV-infected brains. These findings suggest cells people exhibit molecular shifts may underlie ongoing neuroinflammation CNS dysfunction. Furthermore, cell–cell communication uncovered dysregulated pro-inflammatory interactions among glial populations, underscoring multifaceted enduring impact brain milieu. Collectively, our atlas reveals states signatures signaling providing framework for developing targeted therapies neurological
Language: Английский
Citations
0
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 25, 2025
Single-cell transcriptomics has revolutionized our understanding of neurodevelopmental cell identities, yet, predicting a type's developmental state from its transcriptome remains challenge. We perform meta-analysis developing human brain datasets comprising over 2.8 million cells, identifying both tissue-level and cell-autonomous predictors age. While tissue composition predicts age within individual studies, it fails to generalize, whereas specific type proportions reliably track time across datasets. Training regularized regression models infer maturation, we find that type-agnostic model achieves the highest accuracy (error = 2.6 weeks), robustly capturing dynamics diverse types This generalizes neural organoids, accurately normal trajectories (R 0.91) disease-induced shifts in vitro . Furthermore, extends mouse brain, revealing an accelerated tempo relative humans. Our work provides unified framework for comparing neurodevelopment contexts, systems, species.
Language: Английский
Citations
0