Single-cell network biology enabling cell-type-resolved disease genetics DOI Creative Commons
Junha Cha, Insuk Lee

Genomics & Informatics, Journal Year: 2025, Volume and Issue: 23(1)

Published: March 27, 2025

Abstract Gene network models provide a foundation for graph theory approaches, aiding in the novel discovery of drug targets, disease genes, and genetic mechanisms various biological functions. Disease genetics must be interpreted within cellular context disease-associated cell types, which cannot achieved with datasets consisting solely organism-level samples. Single-cell RNA sequencing (scRNA-seq) technology allows computational distinction states provides unique opportunity to understand biology that drives processes. Importantly, abundance samples their transcriptome-wide profile modeling systemic cell-type-specific gene networks (CGNs), offering insights into gene-cell-disease relationships. In this review, we present reference-based de novo inference functional interaction have recently developed using scRNA-seq datasets. We also introduce compendium CGNs as useful resource cell-type-resolved genetics. By leveraging these advances, envision single-cell key approach mapping axis.

Language: Английский

Multiplexed, image-based pooled screens in primary cells and tissues with PerturbView DOI
Takamasa Kudo, Ana M. Meireles, Reuben Moncada

et al.

Nature Biotechnology, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 7, 2024

Language: Английский

Citations

18
SAMPL-seq reveals micron-scale spatial hubs in the human gut microbiome DOI
Miles Richardson, Shijie Zhao, Liyuan Lin

et al.

Nature Microbiology, Journal Year: 2025, Volume and Issue: 10(2), P. 527 - 540

Published: Feb. 3, 2025

Language: Английский

Citations

2
Single-cell profiling of healthy human kidney reveals features of sex-based transcriptional programs and tissue-specific immunity DOI Creative Commons
Caitríona M. McEvoy, Julia Murphy, Lin Zhang

et al.

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: Dec. 10, 2022

Abstract Knowledge of the transcriptional programs underpinning functions human kidney cell populations at homeostasis is limited. We present a single-cell perspective healthy from 19 living donors, with equal contribution males and females, profiling transcriptome 27677 cells to map high resolution. Sex-based differences in gene expression within proximal tubular were observed, specifically, increased anti-oxidant metallothionein genes females aerobic metabolism-related males. Functional metabolism confirmed cells, male exhibiting higher oxidative phosphorylation levels energy precursor metabolites. identified kidney-specific lymphocyte unique profiles indicative kidney-adapted functions. Significant heterogeneity myeloid was MRC1 + LYVE1 FOLR2 C1QC population representing predominant kidney. This study provides detailed cellular kidney, explores complexity parenchymal kidney-resident immune cells.

Language: Английский

Citations

48
High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors DOI Creative Commons
Cheng-Kai Shiau,

Lina Lu,

Rachel E. Kieser

et al.

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: July 11, 2023

Abstract Single-cell nanopore sequencing of full-length mRNAs transforms single-cell multi-omics studies. However, challenges include high errors and dependence on short-reads and/or barcode whitelists. To address these, we develop scNanoGPS to calculate same-cell genotypes (mutations) phenotypes (gene/isoform expressions) without short-read nor whitelist guidance. We apply onto 23,587 long-read transcriptomes from 4 tumors 2 cell-lines. Standalone, deconvolutes error-prone long-reads into single-cells single-molecules, simultaneously accesses both individual cells. Our analyses reveal that tumor stroma/immune cells express distinct combination isoforms (DCIs). In a kidney tumor, identify 924 DCI genes involved in cell-type-specific functions such as PDE10A CCL3 lymphocytes. Transcriptome-wide mutation many mutations including VEGFA HLA-A immune cells, highlighting the critical roles different mutant populations tumors. Together, facilitates applications technologies.

Language: Английский

Citations

36
Perspectives on single-nucleus RNA sequencing in different cell types and tissues DOI Creative Commons
Nayoung Kim, Huiram Kang, Areum Jo

et al.

Journal of Pathology and Translational Medicine, Journal Year: 2023, Volume and Issue: 57(1), P. 52 - 59

Published: Jan. 10, 2023

Single-cell RNA sequencing has become a powerful and essential tool for delineating cellular diversity in normal tissues alterations disease states. For certain cell types conditions, there are difficulties isolating intact cells transcriptome profiling due to their fragility, large size, tight interconnections, other factors. Single-nucleus (snRNA-seq) is an alternative or complementary approach that difficult isolate. In this review, we will provide overview of the experimental analysis steps snRNA-seq understand methods characteristics general tissue-specific data. Knowing advantages limitations increase its use improve biological interpretation data generated using technique.

Language: Английский

Citations

29
Comparative analysis of 10X Chromium vs. BD Rhapsody whole transcriptome single-cell sequencing technologies in complex human tissues DOI Creative Commons
Stefan Salcher, Isabel Heidegger, Gerold Untergasser

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(7), P. e28358 - e28358

Published: March 19, 2024

The development of single-cell omics tools has enabled scientists to study the tumor microenvironment (TME) in unprecedented detail. However, each different techniques may have its unique strengths and limitations. Here we directly compared two commercially available high-throughput RNA sequencing (scRNA-seq) technologies - droplet-based 10X Chromium

Language: Английский

Citations

14
Adaptive immune receptor repertoire analysis DOI
Vanessa Mhanna, Habib Bashour, Khang Lê Quý

et al.

Nature Reviews Methods Primers, Journal Year: 2024, Volume and Issue: 4(1)

Published: Jan. 25, 2024

Language: Английский

Citations

12
Molecular and genetic insights into human ovarian aging from single-nuclei multi-omics analyses DOI Creative Commons
Chen Jin,

Xizhe Wang,

Jiping Yang

et al.

Nature Aging, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 22, 2024

The ovary is the first organ to age in human body, affecting both fertility and overall health. However, biological mechanisms underlying ovarian aging remain poorly understood. Here we present a comprehensive single-nuclei multi-omics atlas of four young (ages 23–29 years) reproductively aged 49–54 ovaries. Our analyses reveal coordinated changes transcriptomes chromatin accessibilities across cell types during aging, notably mTOR signaling being prominent ovary-specific pathway. Cell-type-specific regulatory networks enhanced activity transcription factor CEBPD ovary. Integration our data with genetic variants associated at natural menopause demonstrates global impact functional on gene types. We nominate non-coding variants, their target genes mechanisms. This provides valuable resource for understanding cellular, molecular basis aging. cellular are incompletely authors provide RNA ATAC-seq tissue from donors, revealing transcriptomic epigenomic highlighting role reproductive

Language: Английский

Citations

11
Comparative Analysis of Single-Cell RNA Sequencing Methods with and without Sample Multiplexing DOI Open Access
Yi Xie, Huimei Chen,

Vasuki Ranjani Chellamuthu

et al.

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(7), P. 3828 - 3828

Published: March 29, 2024

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful technique for investigating biological heterogeneity at the single-cell level in human systems and model organisms. Recent advances scRNA-seq have enabled pooling of cells from multiple samples into single libraries, thereby increasing sample throughput while reducing technical batch effects, library preparation time, overall cost. However, comparative analysis methods with without multiplexing is lacking. In this study, we benchmarked two representative platforms: Parse Biosciences (Parse; multiplexing) 10x Genomics (10x; multiplexing). By using peripheral blood mononuclear (PBMCs) obtained healthy individuals, demonstrate that demultiplexed data showed similar cell type frequencies compared to where were not multiplexed. Despite relatively lower capture affecting preparation, can detect rare types (e.g., plasmablasts dendritic cells) which likely due its higher sensitivity gene detection. Moreover, transcript quantification between platforms revealed platform-specific distributions length GC content. These results offer guidance researchers designing high-throughput studies.

Language: Английский

Citations

10
Gut microbiota in health and disease: advances and future prospects DOI Creative Commons
Y J Zhang, Hong Wang, Yingpeng Sang

et al.

MedComm, Journal Year: 2024, Volume and Issue: 5(12)

Published: Nov. 20, 2024

Abstract The gut microbiota plays a critical role in maintaining human health, influencing wide range of physiological processes, including immune regulation, metabolism, and neurological function. Recent studies have shown that imbalances composition can contribute to the onset progression various diseases, such as metabolic disorders (e.g., obesity diabetes) neurodegenerative conditions Alzheimer's Parkinson's). These are often accompanied by chronic inflammation dysregulated responses, which closely linked specific forms cell death, pyroptosis ferroptosis. Pathogenic bacteria trigger these death pathways through toxin release, while probiotics been found mitigate effects modulating responses. Despite insights, precise mechanisms influences diseases remain insufficiently understood. This review consolidates recent findings on impact immune‐mediated inflammation‐associated conditions. It also identifies gaps current research explores potential advanced technologies, organ‐on‐chip models microbiome–gut–organ axis, for deepening our understanding. Emerging tools, single‐bacterium omics spatial metabolomics, discussed their promise elucidating microbiota's disease development.

Language: Английский

Citations

10