Single-cell methylomes identify neuronal subtypes and regulatory elements in mammalian cortex

Luo, Chongyuan; Keown, Christopher L.; Kurihara, Laurie; Zhou, Jingtian; He, Yiping; Li, Junhao; Castanon, Rosa; Lucero, Jacinta; Nery, Joseph R.; Sandoval, Justin P.; Bui, Brian; Sejnowski, Terrence J.; Harkins, Timothy T.; Mukamel, Eran A.; Behrens, M. Margarita; Ecker, Joseph R.

doi:10.1126/science.aan3351

Cited by 485 publications

(683 citation statements)

References 41 publications

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“…Immune-enrichment methods using antibodies against native proteins such as NeuN (Lister et al, 2013) or transgenic methods as shown by the Ecker and Allen Institute groups (Gray et al, 2017; Mo et al, 2015) followed by FACS or affinity purification have allowed construction of high resolution epigenomic maps of purified populations from human and mouse brains including excitatory, inhibitory as well as non-neuronal cells. More recently, the Ecker group developed a new single-nucleus methylome sequencing method called snmC-seq, which allowed a direct comparison of cell-type composition in mouse and human cortices using ~6000 cells and identified 16 mouse and 21 human neuronal subpopulations in the frontal cortex along with regulatory elements with differential methylation across neuron types (Luo et al, 2017). …”

Section: Single-cell Epigenomicsmentioning

confidence: 99%

The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas

Ecker

Geschwind

Kriegstein

et al. 2017

Neuron

Self Cite

258

199

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A comprehensive characterization of neuronal cell types, their distributions and patterns of connectivity is critical for understanding the properties of neural circuits and how they generate behaviors. Here we review the experiences of the BRAIN Initiative Cell Census Consortium – ten pilot projects funded by the U.S. BRAIN Initiative – in developing, validating and scaling up emerging genomic and anatomical mapping technologies for creating a complete inventory of neuronal cell types and their connections in multiple species and during development. These projects lay the foundation for a larger and longer-term effort to generate whole-brain cell atlases in species including mice and humans.

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Section: Single-cell Epigenomicsmentioning

confidence: 99%

The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas

Ecker

Geschwind

Kriegstein

et al. 2017

Neuron

Self Cite

258

199

View full text Add to dashboard Cite

show abstract

“…This method takes advantages of random priming and extension, after which the samples are end‐tailed and ligated to adaptor in one‐pot. snmC‐seq has the capability to classify large‐scale cell types through multiplex reactions with higher mapping ratesequencing and single‐cell post bisulfite adaptor tagging sequencing.…”

Section: Single‐cell Profiling Methods For Dna Modificationsmentioning

confidence: 99%

Advances in the Profiling of Single‐Cell DNA Modifications

Bai

2019

Small Methods

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Epigenetic modifications on DNA include canonical 5‐methylcytosine (5mC) and its iteratively oxidized derivatives mediated by TET dioxygenase: 5‐hydroxymethylcytosine (5hmC), 5‐formylcytosine (5fC), and 5‐carboxycytosine (5caC). All of them have been recognized to play important roles in gene expression regulation and to be indispensable for normal mammalian reproduction and development. In order to understand the mechanisms underlying these roles, over the past few decades, technical advances have been made to comprehensively profile the distribution pattern of bulk epigenetic modifications in genomic DNA. Recently, single‐cell methods have identified the epigenetic patterns even within an individual cell. This review focuses on single‐cell DNA epigenetic modifications sequencing technologies and their applications, and gives prospects on the development of single‐cell methods based on bisulfite‐free strategy.

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“…Several groups including those lead by Reik (Angermueller et al 2016;Clark et al 2016;Clark et al 2017), Vijg (Gravina et al 2015Gravina et al 2016;Yu et al 2017), Adey (Mulqueen et al 2017), and Eckardt (Luo et al 2017) have also demonstrated that methylation patterns can be generated from single cells. However, the principle caveat to these methods is that only a small amount of the genome is analyzed (often around 5%) and the same genomic regions are not analyzed in each cell, making cell-to-cell comparisons of specific loci difficult.…”

Section: Single Cell/cell-type Analysesmentioning

confidence: 99%

Analysis of DNA modifications in aging research

et al. 2018

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As geroscience research extends into the role of epigenetics in aging and age-related disease, researchers are being confronted with unfamiliar molecular techniques and data analysis methods that can be difficult to integrate into their work. In this review, we focus on the analysis of DNA modifications, namely cytosine methylation and hydroxymethylation, through nextgeneration sequencing methods. While older techniques for modification analysis performed relative quantitation across regions of the genome or examined average genome levels, these analyses lack the desired specificity, rigor, and genomic coverage to firmly establish the nature of genomic methylation patterns and their response to aging. With recent methodological advances, such as whole genome bisulfite sequencing (WGBS), bisulfite oligonucleotide capture sequencing (BOCS), and bisulfite amplicon sequencing (BSAS), cytosine modifications can now be readily analyzed with base-specific, absolute quantitation at both cytosine-guanine dinucleotide (CG) and non-CG sites throughout the genome or within specific regions of interest by next-generation sequencing. Additional advances, such as oxidative bisulfite conversion to differentiate methylation from hydroxymethylation and analysis of limited input/single-cells, have great promise for continuing to expand epigenomic capabilities. This review provides a background on DNA modifications, the current state-of-theart for sequencing methods, bioinformatics tools for converting these large data sets into biological insights, and perspectives on future directions for the field.

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Single-cell methylomes identify neuronal subtypes and regulatory elements in mammalian cortex

Cited by 485 publications

References 41 publications

The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas

The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas

Advances in the Profiling of Single‐Cell DNA Modifications

Analysis of DNA modifications in aging research

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