A human cell atlas of fetal chromatin accessibility

Domcke, Silvia; Hill, Andrew J.; Daza, Riza M.; Cao, Junyue; O’Day, Diana R.; Pliner, Hannah A.; Aldinger, Kimberly A.; Pokholok, Dmitry; Zhang, Fan; Milbank, Jennifer; Zager, Michael; Glass, Ian A.; Steemers, Frank J.; Doherty, Dan; Trapnell, Cole; Cusanovich, Darren A.; Shendure, Jay

doi:10.1126/science.aba7612

Cited by 330 publications

(399 citation statements)

References 120 publications

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“…Tissues were obtained from 28 fetuses ranging from 72 to 129 days in estimated postconceptual age. We applied a method for extracting nuclei directly from cryopreserved tissues that works across a variety of tissue types and produces homogenates suitable for both sci-RNA-seq3 and sci-ATAC-seq3 (singlecell combinatorial indexing assay for transposaseaccessible chromatin with high-throughput sequencing) (12). For most organs, extracted nuclei were fixed with paraformaldehyde.…”

Section: Resultsmentioning

confidence: 99%

A human cell atlas of fetal gene expression

Cao

O’Day

Pliner

et al. 2020

Science

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569

544

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The gene expression program underlying the specification of human cell types is of fundamental interest. We generated human cell atlases of gene expression and chromatin accessibility in fetal tissues. For gene expression, we applied three-level combinatorial indexing to >110 samples representing 15 organs, ultimately profiling ~4 million single cells. We leveraged the literature and other atlases to identify and annotate hundreds of cell types and subtypes, both within and across tissues. Our analyses focused on organ-specific specializations of broadly distributed cell types (such as blood, endothelial, and epithelial), sites of fetal erythropoiesis (which notably included the adrenal gland), and integration with mouse developmental atlases (such as conserved specification of blood cells). These data represent a rich resource for the exploration of in vivo human gene expression in diverse tissues and cell types.

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Section: Resultsmentioning

confidence: 99%

A human cell atlas of fetal gene expression

Cao

O’Day

Pliner

et al. 2020

Science

Self Cite

569

544

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“…Whereas earlier versions of sciATAC-seq require custom-made Tn5, the latest version has been adapted to work with commercially available Tn5 (reF. 152 ). The core idea behind combinatorial indexing is the repeated pooling and splitting of cells or nuclei coupled with labelling of DNA fragments at each step, in such a way that statistically each cell or nucleus is tagged with a unique combination of barcodes.…”

Section: Combinatorial Indexing (Sciatac-seq)mentioning

confidence: 99%

“…Notable applications of chromatin accessibility profiling to other cell types and organs include the analysis of cardiac development 292,293 , epidermal progenitor cells in the skin 294 and mammary gland development 295 . Finally, initial single-cell atlases of chromatin accessibility across tissues and organs are emerging 55,56,60,152 , which have the potential to discover new cell types and to define the chromatin states of cell types that are difficult to purify or enrich using flow cytometry. In summary, chromatin accessibility profiling has uncovered a transcription-regulatory landscape that is cell type-specific and organ-specific, and dynamically changes over the course of cellular differentiation and organ development.…”

Section: Cell Types and Organsmentioning

confidence: 99%

Chromatin accessibility profiling methods

Minnoye

Marinov

Krausgruber

et al. 2021

Nat Rev Methods Primers

122

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Chromatin accessibility refers to the level of physical compaction of chromatin, a complex formed by DNA and associated proteins consisting mainly of histones, transcription factors (TFs), chromatin-modifying enzymes and chromatin-remodelling complexes 1-3. Although eukaryotic genomes are generally packed into nucleosomes, which comprise ~147 bp of DNA wrapped around an octamer of histones 4,5 , nucleosome occupancy is not uniform in the genome, and varies across tissues and cell types. Nucleosomes are typically depleted at genomic locations that represent cis-regulatory elementsenhancers and promoters, among others-that interact with transcriptional regulators (for example, TFs), resulting in accessible chromatin 6-10. Profiling chromatin accessibility on a genome-wide scale is an excellent tool to map putative regulatory elements in a cell type or cell state. Post-translational chemical modifications of chromatin, including DNA methylation (in vertebrates) and histone methylation and acetylation, are dynamic and change between different cell states, similar to nucleosome positioning. These post-translational modifications are often correlated with chromatin accessibility and can reflect specific functionalities of genomic regions related to the regulation of gene expression 11,12. Changes in these post-translational modifications, such as increased or decreased histone methylation and acetylation, are affected by a large set of chromatin-modifying enzymes that can be recruited to chromatin regions by TFs. These modifications alter the physico-chemical properties of the chromatin, which in turn can influence the formation of transcriptional condensates 13,14. In addition, active chromatin remodelling impacts nucleosome occupancy; for example, the SWI/SNF complexes use ATP hydrolysis to alter histone-DNA contacts, thereby repositioning or removing nucleosomes 15. Dynamic changes in the chromatin structure, chemical modifications and nucleosome positioning form a crucial interplay with the TFs that drive differentiation of cells during development 16,17. Initial changes in chromatin accessibility are caused by the binding of TFs, which outcompete histones and recruit cofactors, including ATP-dependent chromatin remodellers 18,19 , or by TFs that preferentially bind to their recognition sequence in nucleosomal DNA 20,21. The binding of these initial TFs, known as pioneer factors, can recruit other TFs to co-bind and further stabilize the nucleosome-depleted

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“…Advances in high-throughput single-cell technology such as single-cell RNA-sequencing (scRNAseq) 1 and mass cytometry 2 have enabled systematic delineation of cell types based on thousands to millions of cells sampled from developing organisms or patient biopsies. For example, recent application of combinatorial indexing based technology has generated the transcriptomic and chromatin accessibility profiles of millions of cells in developing human fetus samples 3 . Rare cell types and complex cellular states, however, remain challenging to discover, which necessitates the development of multiomics technologies to simultaneously measure other cellular features, including DNA methylation 4,5 , chromatin accessibility [6][7][8] and spatial positions 9,10 in the same cells.…”

Section: Introductionsmentioning

confidence: 99%

Unbiased integration of single cell multi-omics data

Dou

Liang

Mohanty

et al. 2020

Preprint

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Acquiring accurate single-cell multiomics profiles often requires performing unbiased in silico integration of data matrices generated by different single-cell technologies from the same biological sample. However, both the rows and the columns can represent different entities in different data matrices, making such integration a computational challenge that has only been solved approximately by existing approaches. Here, we present bindSC, a single-cell data integration tool that realizes simultaneous alignment of the rows and the columns between data matrices without making approximations. Using datasets produced by multiomics technologies as gold standard, we show that bindSC generates accurate multimodal co-embeddings that are substantially more accurate than those generated by existing approaches. Particularly, bindSC effectively integrated single cell RNA sequencing (scRNA-seq) and single cell chromatin accessibility sequencing (scATAC-seq) data towards discovering key regulatory elements in cancer cell-lines and mouse cells. It achieved accurate integration of both common and rare cell types (<0.25% abundance) in a novel mouse retina cell atlas generated using the 10x Genomics Multiome ATAC+RNA kit. Further, it achieves unbiased integration of scRNA-seq and 10x Visium spatial transcriptomics data derived from mouse brain cortex samples. Lastly, it demonstrated efficacy in delineating immune cell types via integrating single-cell RNA and protein data. Thus, bindSC, available at https://github.com/KChen-lab/bindSC, can be applied in a broad variety of context to accelerate discovery of complex cellular and biological identities and associated molecular underpinnings in diseases and developing organisms.

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A human cell atlas of fetal chromatin accessibility

Cited by 330 publications

References 120 publications

A human cell atlas of fetal gene expression

A human cell atlas of fetal gene expression

Chromatin accessibility profiling methods

Unbiased integration of single cell multi-omics data

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