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Txci-ATAC-seq: a massive-scale single-cell technique to profile chromatin accessibility

ABSTRACT: We develop a large-scale single-cell ATAC-seq method (txci-ATAC-seq) by combining Tn5-based pre-indexing with 10X Genomics barcoding. Leveraging this molecular hashing strategy, we demonstrate that txci-ATAC-seq enables the indexing of up to 200,000 nuclei across multiple samples in a single emulsion reaction, representing a ~22-fold increase in throughput compared to the standard workflow at the same collision rate. To improve the multiplexing capability of this new technique, we further develop a "phased" protocol variant (Phased-txci-ATAC-seq) that effectively decouples sample processing from library preparation and has the potential to profile up to 96 samples simultaneously. In this study, we profile 449,953 nuclei across diverse tissues, including the human cortex, mouse brain, human lung, mouse lung, mouse liver, and lung tissue from a club cell secretory protein knockout (CC16-/-) model. Our study of CC16-/- nuclei uncovers previously underappreciated technical artifacts derived from remnant 129 mouse strain genetic material, which cause profound cell-type-specific changes in regulatory elements near many genes, thereby confounding the interpretation of this commonly referenced mouse model.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE231708 | GEO | 2023/10/25

REPOSITORIES: GEO

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txci-ATAC-seq: a massive-scale single-cell technique to profile chromatin accessibility

Project description:We develop a large-scale single-cell ATAC-seq method by combining Tn5-based pre-indexing with 10X Genomics barcoding, enabling the indexing of up to 200,000 nuclei across multiple samples in a single reaction. We profile 449,953 nuclei across diverse tissues, including the human cortex, mouse brain, human lung, mouse lung, mouse liver, and lung tissue from a club cell secretory protein knockout (CC16-/-) model. Our study of CC16-/- nuclei uncovers previously underappreciated technical artifacts derived from remnant 129 mouse strain genetic material, which cause profound cell-type-specific changes in regulatory elements near many genes, thereby confounding the interpretation of this commonly referenced mouse model.

2023-10-20 | GSE245957 | GEO

An integrated multi-omics analysis of identiﬁes distinct molecular characteristics in pulmonary infections of Pseudomonas aeruginosa

Project description:Pseudomonas aeruginosa (P. aeruginosa) can cause severe acute infections, including pneumonia and sepsis, and also cause chronic infections commonly in patients with structural respiratory diseases. However, the molecular and pathophysiological mechanisms of P. aeruginosa respiratory infection are largely unknown. Here, we profiled performed to assay for transposase-accessible chromatin using sequencing (ATAC-seq), transcriptomics, and quantitative mass spectrometry-based proteomics and ubiquitin-proteomics in P. aeruginosa-infected lung tissues for multi-omics analysis, while ATAC-seq and transcriptomics were also examined in P. aeruginosa-infected mouse macrophages. To find the pivotal transcription factors that are likely involved in host immune defense, we integrally investigated systematic changes in chromatin accessibility and gene expression in P. aeruginosa-infected lung tissues combined with proteomics and ubiquitin-proteomics studies. We discovered that Stat1 and Stat3 were altered in various omics and found similar results in mouse alveolar macrophages. Taken together, these findings indicate that these crucial transcription factors and their downstream signaling molecules play a critical role in the mobilization of host immune response against P. aeruginosa infection and may serve as potential targets for bacterial infections and inflammatory diseases, as well as provide clear insights and resources for using integrative histological analyses.

2023-07-27 | PXD038001 | Pride

An integrated multi-omics analysis of identiﬁes distinct molecular characteristics in pulmonary infections of Pseudomonas aeruginosa

2023-07-27 | PXD042381 | Pride

Ultra-high throughput single-cell RNA sequencing by combinatorial fluidic indexing

Project description:Cell atlas projects and high-throughput perturbation screens require single-cell sequencing at a scale that is challenging with current technology. To enable cost-effective single-cell sequencing for millions of individual cells, we developed “single-cell combinatorial fluidic indexing” (scifi). The scifi-RNA-seq assay combines one-step combinatorial pre-indexing of entire transcriptomes inside permeabilized cells with subsequent single-cell RNA-seq using microfluidics. Pre-indexing allows us to load multiple cells per droplet and bioinformatically demultiplex their individual expression profiles. Thereby, scifi-RNA-seq massively increases the throughput of droplet-based single-cell RNA-seq, and it provides a straightforward way of multiplexing thousands of samples in a single experiment. Compared to multi-round combinatorial indexing, scifi-RNA-seq provides an easier, faster, and more efficient workflow. In contrast to cell hashing methods, which flag and discard droplets containing more than one cell, scifi-RNA-seq resolves and retains individual transcriptomes from overloaded droplets.

2021-03-11 | GSE168620 | GEO

snATAC-seq of the developing mouse cerebellum across eleven stages

Project description:This study used droplet-based snATAC-seq to profile the chromatin accessibility landscape of 91,922 nuclei in the mouse cerebellum across eleven developmental stages, from the beginning of neurogenesis (e10.5) till adulthood (P63). The study included two biological replicates per stage, one from each sex. Cerebelli were dissected as whole or in two halves, nuclei were extracted and profiled using 10x single-cell ATAC reagent kit (v1.0) and a Chromium controller. Libraries were sequenced using paired-reads on Illumina NextSeq 550 and initial data processing was performed using Cellranger ATAC (1.1).

2021-09-07 | E-MTAB-9765 | biostudies-arrayexpress

Distinct chromatin signatures in plant male germline cells - ATAC-seq

Project description:ATAC-seq experiments of the sperm and vegetative nuclei from the Arabidopsis pollen.

2022-12-02 | E-MTAB-10967 | biostudies-arrayexpress

Comprehensive single cell transcriptional profiling of a multicellular organism by combinatorial indexing

Project description:We developed a combinatorial indexing strategy to profile the transcriptomes of large numbers of single cells or nuclei (Single cell Combinatorial Indexing RNA-seq or sci-RNA-seq). We applied sci-RNA-seq to profile nearly 50,000 cells from C. elegans at the L2 stage, effectively ~56-fold “shotgun cellular coverage” of its somatic cell composition.

2017-08-17 | GSE98561 | GEO

SPATAC-seq: split-pool ligation-based single cell ATAC-seq method

Project description:To establish an ultra-high-throughput single cell chromatin accessibility profiling method that is cost-effective and widely accessible, we built on sci-ATAC-seq (Cusanovich, D. A. et al. Science. 2015; Amini, S. et al. Nature Genetics. 2014) and SPLIT-seq (Rosenberg, A. B. et al. Science. 2018) to design SPATAC-seq, which in situ label chromatin fragment in the same single cell through combinatorial barcoding. Briefly, in SPATAC-seq, (1) fixed nuclei are transposed in 48 different wells by 48 unique Tn5 transposase, which containing barcoded adaptors and 5'-phosphorylation; (2) the nuclei from all wells are collected and redistributed into second and third 48-well plate in turn, where the next two rounds of indexing are achieved through into either end of the custom transposome, which result in the generation of more than 110,000 (48^3) unique barcode combinations. (3) the nuclei are pooled, split into sublibraries and lysed, and the DNA was amplified by polymerase chain reaction (PCR), which introduce illumina sequencing barcodes and complete libraries construction. (4) After sequencing, fastq files were demultiplexed according to the same four-barcode combinations. For profiling more cells in one sublibrary, we can increase the number of barcode combinations by increase the number of indexing of each round to 96, which can produce about 1 million combinations. To assess the fidelity of SPATAC-seq, we performed a species-mixing experiment with cultured human (K562) and mouse (Hepa) cells. Here, we tagged mixed permeabilized nuclei with only 8 barcoded transposome. In round 4, we generated eight sublibraries with different cell-recovery targets, which can be used to evaluating the stability of this method and the correlation between real doublet rates and theoretical value.

2024-04-14 | GSE215901 | GEO

scRNA-seq of mouse CD45+ aortic cells with CITE-seq and cell Hashing after continuous or alternate diet

Project description:scRNA-seq of mouse CD45+ aortic cells with CITE-seq and cell Hashing after continuous or alternate diet

2024-04-15 | GSE251907 | GEO

Epigenomic Signatures of Neuronal Diversity in the Mammalian Brain

Project description:We developed an affinity purification approach to isolate tagged nuclei in mice (similar to INTACT; [Deal R.B. and Henikoff S. A simple method for gene expression and chromatin profiling of individual cell types within a tissue. Dev. Cell 18,1030-1040. (2010)]) and used it to characterize genome-wide patterns of transcription, DNA methylation, and chromatin accessibility in 3 major neuron classes of the neocortex (excitatory pyramidal neurons, parvalbumin (PV)-positive GABAergic interneurons, and vasoactive intestinal peptide (VIP)-positive GABAergic interneurons). By combining cell purification and integrative analysis, our findings relate the phenotypic and functional complexity of neocortical neurons to their underlying transcriptional and epigenetic diversity. RNA-seq, MethylC-seq, ATAC-seq, and ChIP-seq for histone modifications using INTACT-purified nuclei from the mouse neocortex

2015-06-17 | E-GEOD-63137 | biostudies-arrayexpress

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