A single-cell atlas of chromatin accessibility in the human genome

Zhang, Kai; Hocker, James D.; Miller, Michael; Hou, Xiaomeng; Chiou, Joshua; Poirion, Olivier; Qiu, Yunjiang; Li, Yang E.; Gaulton, Kyle J.; Wang, Allen; Preißl, Sebastian; Ren, Bing

doi:10.1016/j.cell.2021.10.024

Cited by 221 publications

(194 citation statements)

References 126 publications

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“…The advent of single-cell sequencing over the past decade has revolutionized several fields spanning across molecular and developmental biology by enabling stratification of the cellular, transcriptomic, and epigenetic heterogeneity in cell fate specification and within cell populations, leading to the taxonomic identification of novel cell types and to the inference of cell fate probabilities and developmental trajectories across pseudo-times [ 62 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 128 , 185 , 350 , 414 , 415 , 416 , 417 , 418 , 419 , 420 , 421 , 422 , 423 , 424 ].…”

Section: Conclusion and Future Perspectivesmentioning

confidence: 99%

Deciphering the Retinal Epigenome during Development, Disease and Reprogramming: Advancements, Challenges and Perspectives

Zibetti

2022

Cells

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Retinal neurogenesis is driven by concerted actions of transcription factors, some of which are expressed in a continuum and across several cell subtypes throughout development. While seemingly redundant, many factors diversify their regulatory outcome on gene expression, by coordinating variations in chromatin landscapes to drive divergent retinal specification programs. Recent studies have furthered the understanding of the epigenetic contribution to the progression of age-related macular degeneration, a leading cause of blindness in the elderly. The knowledge of the epigenomic mechanisms that control the acquisition and stabilization of retinal cell fates and are evoked upon damage, holds the potential for the treatment of retinal degeneration. Herein, this review presents the state-of-the-art approaches to investigate the retinal epigenome during development, disease, and reprogramming. A pipeline is then reviewed to functionally interrogate the epigenetic and transcriptional networks underlying cell fate specification, relying on a truly unbiased screening of open chromatin states. The related work proposes an inferential model to identify gene regulatory networks, features the first footprinting analysis and the first tentative, systematic query of candidate pioneer factors in the retina ever conducted in any model organism, leading to the identification of previously uncharacterized master regulators of retinal cell identity, such as the nuclear factor I, NFI. This pipeline is virtually applicable to the study of genetic programs and candidate pioneer factors in any developmental context. Finally, challenges and limitations intrinsic to the current next-generation sequencing techniques are discussed, as well as recent advances in super-resolution imaging, enabling spatio-temporal resolution of the genome.

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Section: Conclusion and Future Perspectivesmentioning

confidence: 99%

Deciphering the Retinal Epigenome during Development, Disease and Reprogramming: Advancements, Challenges and Perspectives

Zibetti

2022

Cells

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“…This is largely due to technical and predominantly downstream analysis hardships, including the high error rate of these platforms. Nevertheless, there are methods, which attempt to correct errors and integrate single cell long read sequencing (Volden et al, 2018;Singh et al, 2019;Lebrigand et al, 2020;Zhang et al, 2021). For example, the rolling circle to concatemeric consensus (R2C2) method can produce full-length cDNA sequences, achieving ~98% (Volden et al, 2018;Cole et al, 2020;Volden and Christopher, 2021) or Single-cell Nanopore sequencing with UMIs (ScNaUmi-seq) with ~99.8% accuracy (Lebrigand et al, 2020), compared to former ~50%.…”

Section: Sequencing Of Single-cellsmentioning

confidence: 99%

“…Immunological studies have benefitted from paired B-cell or T-cell receptors, surface protein expression together with gene expression from a single cell (DeBerge et al, 2021). Single nuclei sequencing can be combined with ATAC (Assay for Transposase Accessible Chromatin) allowing for the analysis of chromatin accessibility at the single cell level, thus providing insights into cell types and states, and deeper understanding of gene regulatory mechanisms (Zhang et al, 2021). Further applications include proteomics (Cheung et al, 2021) and DNA methylation (Galvão and Kelsey, 2021).…”

Section: Integrational Approachesmentioning

confidence: 99%

Perspectives on Bulk-Tissue RNA Sequencing and Single-Cell RNA Sequencing for Cardiac Transcriptomics

et al. 2022

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The heart has been the center of numerous transcriptomic studies in the past decade. Even though our knowledge of the key organ in our cardiovascular system has significantly increased over the last years, it is still not fully understood yet. In recent years, extensive efforts were made to understand the genetic and transcriptomic contribution to cardiac function and failure in more detail. The advent of Next Generation Sequencing (NGS) technologies has brought many discoveries but it is unable to comprehend the finely orchestrated interactions between and within the various cell types of the heart. With the emergence of single-cell sequencing more than 10 years ago, researchers gained a valuable new tool to enable the exploration of new subpopulations of cells, cell-cell interactions, and integration of multi-omic approaches at a single-cell resolution. Despite this innovation, it is essential to make an informed choice regarding the appropriate technique for transcriptomic studies, especially when working with myocardial tissue. Here, we provide a primer for researchers interested in transcriptomics using NGS technologies.

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“…A catalog of cell-specific cis -regulatory elements—from 222 different cell types—mapped disease-related likely causal variants. β cell-specific regulatory elements ranked highest for T2D, while variants enriched in CD4+/CD8+ T-cell-specific elements were more common for T1D-risk variants [ 272 ]. Some examples of these genetic variants are classified and described below.…”

Section: Classification Of the Genetic Drivers Of β Cell Dysfunctionmentioning

confidence: 99%

“…Enhancers are necessary for robust and correct spatiotemporal gene expression. Genome-wide survey of open chromatin accessibility by DNase-seq, ATAC-seq and histone modification ChIP-seq has identified unique regulatory elements that reveal tissue-specific features [ 272 , 287 ]. Studies integrated with T2D-GWAS found risk signals enriched at enhancers active in islets [ 72 , 230 , 288 , 289 ] or in hESC-derived progenitors [ 237 ].…”

Section: Classification Of the Genetic Drivers Of β Cell Dysfunctionmentioning

confidence: 99%

Stem Cell-Derived β Cells: A Versatile Research Platform to Interrogate the Genetic Basis of β Cell Dysfunction

Bartolomé

2022

IJMS

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Pancreatic β cell dysfunction is a central component of diabetes progression. During the last decades, the genetic basis of several monogenic forms of diabetes has been recognized. Genome-wide association studies (GWAS) have also facilitated the identification of common genetic variants associated with an increased risk of diabetes. These studies highlight the importance of impaired β cell function in all forms of diabetes. However, how most of these risk variants confer disease risk, remains unanswered. Understanding the specific contribution of genetic variants and the precise role of their molecular effectors is the next step toward developing treatments that target β cell dysfunction in the era of personalized medicine. Protocols that allow derivation of β cells from pluripotent stem cells, represent a powerful research tool that allows modeling of human development and versatile experimental designs that can be used to shed some light on diabetes pathophysiology. This article reviews different models to study the genetic basis of β cell dysfunction, focusing on the recent advances made possible by stem cell applications in the field of diabetes research.

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A single-cell atlas of chromatin accessibility in the human genome

Cited by 221 publications

References 126 publications

Deciphering the Retinal Epigenome during Development, Disease and Reprogramming: Advancements, Challenges and Perspectives

Deciphering the Retinal Epigenome during Development, Disease and Reprogramming: Advancements, Challenges and Perspectives

Perspectives on Bulk-Tissue RNA Sequencing and Single-Cell RNA Sequencing for Cardiac Transcriptomics

Stem Cell-Derived β Cells: A Versatile Research Platform to Interrogate the Genetic Basis of β Cell Dysfunction

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