Integrated analysis of multimodal single-cell data

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2020, Volume and Issue: unknown

Published: Oct. 12, 2020

Abstract The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on data types. Here, we introduce ‘weighted-nearest neighbor’ unsupervised framework to learn the relative utility each type in cell, enabling integrative analysis modalities. We apply our procedure a CITE-seq dataset hundreds thousands human white blood cells alongside panel 228 antibodies construct reference atlas circulating immune system. demonstrate substantially improves ability resolve cell validate presence previously unreported lymphoid subpopulations. Moreover, how leverage this rapidly map datasets, interpret responses vaccination COVID-19. Our approach broadly applicable strategy analyze including paired measurements RNA chromatin state, look beyond transcriptome towards unified definition identity. Availability Installation instructions, documentation, tutorials, datasets are available at http://www.satijalab.org/seurat

Language: Английский

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Advances and Trends in Omics Technology Development

Frontiers in Medicine, Journal Year: 2022, Volume and Issue: 9

Published: July 1, 2022

The human history has witnessed the rapid development of technologies such as high-throughput sequencing and mass spectrometry that led to concept “omics” methodological advancement in systematically interrogating a cellular system. Yet, ever-growing types molecules regulatory mechanisms being discovered have been persistently transforming our understandings on machinery. This renders cell omics seemingly, like universe, expand with no limit goal toward complete harness system merely impossible. Therefore, it is imperative review what done predict can be translation information disease control minimal perturbation. With focus “four big omics,” i.e., genomics, transcriptomics, proteomics, metabolomics, we delineate hierarchies these together their epiomics interactomics, developed for interrogation. We predict, among others, redoxomics an emerging layer views decision physiological or pathological state fine-tuned redox balance.

Language: Английский

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Single-Nucleus RNA-Seq Is Not Suitable for Detection of Microglial Activation Genes in Humans

Cell Reports, Journal Year: 2020, Volume and Issue: 32(13), P. 108189 - 108189

Published: Sept. 1, 2020

Single-nucleus RNA sequencing (snRNA-seq) is used as an alternative to single-cell RNA-seq, it allows transcriptomic profiling of frozen tissue. However, unclear whether snRNA-seq able detect cellular state in human Indeed, analyses brain samples have failed a consistent microglial activation signature Alzheimer's disease. Our comparison microglia from single cells and nuclei four subjects reveals that, although most genes show similar relative abundances nuclei, small population (∼1%) depleted compared whole cells. This enriched for previously implicated activation, including APOE, CST3, SPP1, CD74, comprising 18% identified microglial-disease-associated genes. Given the low sensitivity many genes, we conclude that not suited detecting

Language: Английский

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Single-cell analysis of human non-small cell lung cancer lesions refines tumor classification and patient stratification

Cancer Cell, Journal Year: 2021, Volume and Issue: 39(12), P. 1594 - 1609.e12

Published: Nov. 11, 2021

Language: Английский

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Direct Comparative Analyses of 10X Genomics Chromium and Smart-Seq2

Genomics Proteomics & Bioinformatics, Journal Year: 2021, Volume and Issue: 19(2), P. 253 - 266

Published: March 2, 2021

Abstract Single-cell RNA sequencing (scRNA-seq) is generally used for profiling transcriptome of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently scRNA-seq platforms, yet there only a few thorough systematic comparisons their advantages limitations. Here, by directly comparing data generated these platforms from same samples CD45− cells, we systematically evaluated features using wide spectrum analyses. detected more genes in cell, especially low abundance transcripts as well alternatively spliced transcripts, but captured higher proportion mitochondrial genes. composite also resembled bulk RNA-seq more. For 10X-based data, observed noise mRNAs with expression levels. Approximately 10%−30% all both were non-coding genes, long RNAs (lncRNAs) accounting 10X. displayed severe dropout problem, lower However, 10X-data can detect rare cell types given its ability to cover large number In addition, each platform distinct groups differentially expressed between clusters, indicating different characteristics technologies. Our study promotes better understanding offers basis an informed choice widely

Language: Английский

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The triumphs and limitations of computational methods for scRNA-seq

Nature Methods, Journal Year: 2021, Volume and Issue: 18(7), P. 723 - 732

Published: June 21, 2021

Language: Английский

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Single cell transcriptomic landscape of diabetic foot ulcers

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

Published: Jan. 10, 2022

Abstract Diabetic foot ulceration (DFU) is a devastating complication of diabetes whose pathogenesis remains incompletely understood. Here, we profile 174,962 single cells from the foot, forearm, and peripheral blood mononuclear using single-cell RNA sequencing. Our analysis shows enrichment unique population fibroblasts overexpressing MMP1, MMP3, MMP11, HIF1A, CHI3L1 , TNFAIP6 increased M1 macrophage polarization in DFU patients with healing wounds. Further, spatially separated samples same patient spatial transcriptomics reveal preferential localization these associated toward wound bed as compared to edge or unwounded skin. Spatial also validates our findings higher abundance macrophages healers M2 non-healers. provides deep insights into microenvironment, identifying cell types that could be critical promoting healing, may inform novel therapeutic approaches for treatment.

Language: Английский

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Hybridization-based in situ sequencing (HybISS) for spatially resolved transcriptomics in human and mouse brain tissue

Nucleic Acids Research, Journal Year: 2020, Volume and Issue: 48(19), P. e112 - e112

Published: Sept. 11, 2020

Abstract Visualization of the transcriptome in situ has proven to be a valuable tool exploring single-cell RNA-sequencing data, providing an additional spatial dimension investigate multiplexed gene expression, cell types, disease architecture or even data driven discoveries. In sequencing (ISS) method based on padlock probes and rolling circle amplification been used spatially resolve transcripts tissue sections various origins. Here, we describe next iteration ISS, HybISS, hybridization-based sequencing. Modifications probe design allows for new barcoding system via sequence-by-hybridization chemistry improved detection RNA transcripts. Due probes, amplicons can visualized with standard epifluorescence microscopes high-throughput efficiency removes limitations bound by sequence-by-ligation ISS. HybISS increased flexibility multiplexing, signal-to-noise, all without compromising throughput imaging large fields view. Moreover, current protocol is demonstrated work human brain samples, source that difficult image-based analysis techniques. Overall, technology works as targeted transcriptomic visualization, importantly, ease implementation.

Language: Английский

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Second-Strand Synthesis-Based Massively Parallel scRNA-Seq Reveals Cellular States and Molecular Features of Human Inflammatory Skin Pathologies

Immunity, Journal Year: 2020, Volume and Issue: 53(4), P. 878 - 894.e7

Published: Oct. 1, 2020

High-throughput single-cell RNA-sequencing (scRNA-seq) methodologies enable characterization of complex biological samples by increasing the number cells that can be profiled contemporaneously. Nevertheless, these approaches recover less information per cell than low-throughput strategies. To accurately report expression key phenotypic features cells, scRNA-seq platforms are needed both high fidelity and throughput. address this need, we created Seq-Well S3 ("Second-Strand Synthesis"), a massively parallel protocol uses randomly primed second-strand synthesis to complementary DNA (cDNA) molecules were successfully reverse transcribed but which second oligonucleotide handle, necessary for subsequent whole transcriptome amplification, was not appended due inefficient template switching. increased efficiency transcript capture gene detection compared with previous iterations up 10- 5-fold, respectively. We used chart transcriptional landscape five human inflammatory skin diseases, thus providing resource further study inflammation.

Language: Английский

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Applications of single-cell RNA sequencing in drug discovery and development

Nature Reviews Drug Discovery, Journal Year: 2023, Volume and Issue: 22(6), P. 496 - 520

Published: April 28, 2023

Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods, together with associated computational tools and the growing availability of public data resources, are transforming drug discovery development. New opportunities emerging in target identification owing to improved disease understanding through cell subtyping, highly multiplexed functional genomics screens incorporating scRNA-seq enhancing credentialling prioritization. ScRNA-seq is also aiding selection relevant preclinical models providing new insights into mechanisms action. In clinical development, can inform decision-making via biomarker for patient stratification more precise monitoring response progression. Here, we illustrate how methods being applied key steps discuss ongoing challenges their implementation pharmaceutical industry. There have been significant recent advances development remarkable Ferran colleagues primarily pipeline, from decision-making. Ongoing potential future directions discussed.

Language: Английский

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