An increment of diversity method for cell state trajectory inference of time-series scRNA-seq data

Fundamental Research, Journal Year: 2024, Volume and Issue: 4(4), P. 770 - 776

Published: Feb. 9, 2024

The increasing emergence of the time-series single-cell RNA sequencing (scRNA-seq) data, inferring developmental trajectory by connecting transcriptome similar cell states (i.e., types or clusters) has become a major challenge. Most existing computational methods are designed for individual cells and do not take into account available time series information. We present IDTI based on Increment Diversity Trajectory Inference, which combines information minimum increment diversity method to infer state scRNA-seq data. apply simulated three real diverse tissue development datasets, compare it with six other commonly used inference in terms topology similarity branching accuracy. results have shown that accurately constructs without requirement starting cells. In performance test, we further demonstrate advantages high accuracy strong robustness.

Language: Английский

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Crosstalk between Lipid Metabolism and Bone Homeostasis: Exploring Intricate Signaling Relationships

Research, Journal Year: 2024, Volume and Issue: 7

Published: Jan. 1, 2024

Bone is a dynamic tissue reshaped by constant bone formation and resorption to maintain its function. The skeletal system accounts for approximately 70% of the total volume body, continuous remodeling requires quantities energy material consumption. Adipose main storehouse body has strong adaptive capacity participate in regulation various physiological processes. Considering that obesity metabolic syndrome have become major public health challenges, while osteoporosis osteoporotic fractures other problems aging population, it would be interesting explore these 2 diseases together. Currently, an increasing number researchers are focusing on interactions between multiple systems, i.e., organs tissues functionally coordinated together pathologically interact with each body. However, there lack detailed reviews summarizing effects lipid metabolism homeostasis adipose tissue. This review provides summary recent advances understanding how molecules adipose-derived hormones affect homeostasis, tissue, as organ, affects metabolism, regulated bone-derived cytokines.

Language: Английский

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Reconstructing Waddington Landscape from Cell Migration and Proliferation

Interdisciplinary Sciences Computational Life Sciences, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 7, 2025

Language: Английский

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Metabolic Objectives and Trade-Offs: Inference and Applications

Metabolites, Journal Year: 2025, Volume and Issue: 15(2), P. 101 - 101

Published: Feb. 6, 2025

Background/Objectives: Determining appropriate cellular objectives is crucial for the system-scale modeling of biological networks metabolic engineering, reprogramming, and drug discovery applications. The mathematical representation can describe how cells manage limited resources to achieve goals within mechanistic environmental constraints. While rapidly proliferating like tumors are often assumed prioritize biomass production, mammalian cell types exhibit beyond growth, such as supporting tissue functions, developmental processes, redox homeostasis. Methods: This review addresses challenge determining trade-offs from multiomics data. Results: Recent advances in single-cell omics, modeling, machine/deep learning methods have enabled inference at both transcriptomic levels, bridging gene expression patterns with phenotypes. Conclusions: These silico models provide insights into adapt changing environments, treatments, genetic manipulations. We further explore potential application incorporating personalized medicine, discovery, systems biology.

Language: Английский

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Alternative splicing dynamics during gastrulation in mouse embryo

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 30, 2025

Alternative splicing (AS) plays an essential role in development, differentiation and carcinogenesis. However, the mechanisms underlying regulation during mouse embryo gastrulation remain unclear. Based on spatial-temporal transcriptome epigenome data, we detected dynamics of AS revealed its regulatory across primary germ layers gastrulation, spanning developmental stages from E6.5 to E7.5. Subsequently, dynamic expression factors (SFs) was characterized, while patterns functions layer-specific SFs were identified. The results indicate that differential alternative events (DASEs) exhibit changes are significantly abundant late stage gastrulation. Similarly, demonstrate stage-specific expression, with elevated levels observed middle Epigenetic signals associated sites significant enrichment undergo throughout Overall, this study offers a systematic analysis identifies events, characterizes epigenetic signals. These findings enhance understanding formation three mammalian focus pre-mRNA AS.

Language: Английский

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Transcriptome Analyses Reveal the Important miRNAs Involved in Immune Response of Gastric Cancer

IET Systems Biology, Journal Year: 2025, Volume and Issue: 19(1)

Published: Jan. 1, 2025

ABSTRACT MicroRNAs (miRNAs) are crucial factors in gene regulation, and their dysregulation plays important roles the immunity of gastric cancer (GC). However, finding specific effective miRNA markers is still a great challenge for GC immunotherapy. In this study, we computed analysed miRNA‐seq, RNA‐seq clinical data patients from TCGA database. With comparison tumour normal tissues GC, identified 2056 upregulated 2311 downregulated protein‐coding genes. Based on miRNet database, more than 2600 miRNAs interact with these Several key miRNAs, including hsa‐mir‐34a, hsa‐mir‐182 hsa‐mir‐23b, were to potentially play regulatory expression most genes GC. bioinformation approaches, expressions hsa‐mir‐34a closely linked stage, high hsa‐mir‐23b was correlated poor survival Moreover, three involved immune cell infiltration (such as activated memory CD4 T cells resting mast cells), particularly hsa‐mir‐23b. GSEA suggested that changes may possibly activate/inhibit immune‐related signal pathways, such chemokine signalling pathway CXCR4 pathway. These results will provide possible or targets combined immunotherapy

Language: Английский

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Deciphering Sequence Determinants of Zygotic Genome Activation Genes: Insights From Machine Learning and the ZGAExplorer Platform

Cell Proliferation, Journal Year: 2025, Volume and Issue: unknown

Published: April 18, 2025

ABSTRACT The mammalian life cycle initiates with the transition of genetic control from maternal to embryonic genome during zygotic activation (ZGA), which becomes pivotal for development. Nevertheless, understanding conservation genes and transcription factors (TFs) that underlie ZGA remains limited. Here, we compiled a comprehensive set mice, humans, pigs, bovines goats, including Nr5a2 TPRX1/2 . identification 111 homologous through comparative analyses was followed by discovery conserved coding region, suggesting potential sequence preferences genes. Notably, an interpretable machine learning model based on k ‐mer core features showed excellent performance in predicting (area under ROC curve [AUC] > 0.81), revealing abundant intricate 6‐base specific patterns binding TFs, motifs NR5A2 TPRX1/2. Further analysis demonstrated gene epigenetic modification play equally important roles regulating Ultimately, developed ZGAExplorer platform provide invaluable resource screening Our study unravels determinants across species multi‐omics data integration learning, yielding insights into regulatory mechanisms developmental arrest.

Language: Английский

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AtML: An Arabidopsis thaliana root cell identity recognition tool for medicinal ingredient accumulation

Methods, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 1, 2024

Arabidopsis thaliana synthesizes various medicinal compounds, and serves as a model plant for research. Single-cell transcriptomics technologies are essential understanding the developmental trajectory of roots, facilitating analysis synthesis accumulation patterns compounds in different cell subpopulations. Although methods interpreting single-cell data rapidly advancing Arabidopsis, challenges remain precisely annotating identity due to lack marker genes certain types. In this work, we trained machine learning system, AtML, using sequencing datasets from six subpopulations, comprising total 6000 cells, predict root stages identify biomarkers through complete interpretability. Performance testing an external dataset revealed that AtML achieved 96.50% accuracy 96.51% recall. Through interpretability provided by our identified 160 important genes, contributing type annotations. conclusion, efficiently stages, providing new tool elucidating mechanisms compound roots.

Language: Английский

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The intrinsic dimension of gene expression during cell differentiation

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 6, 2024

Abstract Waddington’s epigenetic landscape has long served as a conceptual framework for understanding cell fate decisions. The landscape’s geometry encodes the molecular mechanisms that guide gene expression profiles of uncommitted cells toward terminally differentiated types. In this study, we demonstrate applying concept intrinsic dimension to single-cell transcriptomic data can effectively capture trends in trajectories, supporting framework. This approach allows us define robust potency score without relying on prior biological information. By analyzing an extensive collection datasets from various species, experimental protocols, and differentiation processes, validate our method successfully reproduce established hierarchies type potency.

Language: Английский

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Rewriting cellular fate: epigenetic interventions in obesity and cellular programming

Molecular Medicine, Journal Year: 2024, Volume and Issue: 30(1)

Published: Oct. 10, 2024

External constraints, such as development, disease, and environment, can induce changes in epigenomic patterns that may profoundly impact the health trajectory of fetuses neonates into adulthood, influencing conditions like obesity. Epigenetic modifications encompass processes including DNA methylation, covalent histone modifications, RNA-mediated regulation. Beyond forward cellular differentiation (cell programming), terminally differentiated cells are reverted to a pluripotent or even totipotent state, is, reprogramming. modulators facilitate erase both vivo vitro during programming Noticeably, obesity is complex metabolic disorder driven by genetic environmental factors. Increasing evidence suggests epigenetic play critical role regulation gene expression involved adipogenesis, energy homeostasis, pathways. Hence, we discuss mechanisms which interventions influence obesity, focusing on non-coding RNAs. We also analyze methodologies have been pivotal uncovering these regulations, i.e., Large-scale screening has instrumental identifying genes pathways susceptible control, particularly context adipogenesis homeostasis; Single-cell RNA sequencing (scRNA-seq) provides high-resolution view at individual cell level, revealing heterogeneity dynamics reprogramming; Chromatin immunoprecipitation (ChIP) assays, focused candidate genes, crucial for characterizing transcription factor binding specific genomic loci, thereby elucidating govern programming; Somatic nuclear transfer (SCNT) fusion techniques employed study reprogramming accompanying cloning generation hybrid with characteristics, etc. These approaches marks implicated providing foundation developing targeted therapeutic interventions. Understanding dynamic interplay between advancing mechanism clinical management

Language: Английский

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