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Curated Papers > High-impact authoritative literature on "single-cell sequencing"

Single-Cell Sequencing of Brain Cell Transcriptomes and Epigenomes. ​

Literature Information ​

DOI10.1016/j.neuron.2020.12.010
PMID33412093
JournalNeuron
Impact Factor15.0
JCR QuartileQ1
Publication Year2021
Times Cited130
KeywordsATAC-seq, DNA methylation, cell state, cell type, epigenome
Literature TypeJournal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't, Review
ISSN0896-6273
Pages11-26
Issue109(1)
AuthorsEthan J Armand, Junhao Li, Fangming Xie, Chongyuan Luo, Eran A Mukamel

TL;DR ​

Single-cell sequencing technologies are revolutionizing neuroscience by enabling detailed characterization of diverse brain cell types through transcriptomic and epigenomic assays, revealing gene regulatory mechanisms that influence cellular identity and their developmental relationships. This research not only enhances our understanding of neural circuits but also facilitates the design of tools for targeted functional studies, bridging molecular signatures with anatomical and physiological aspects of brain function.

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ATAC-seq · DNA methylation · cell state · cell type · epigenome

Abstract ​

Single-cell sequencing technologies, including transcriptomic and epigenomic assays, are transforming our understanding of the cellular building blocks of neural circuits. By directly measuring multiple molecular signatures in thousands to millions of individual cells, single-cell sequencing methods can comprehensively characterize the diversity of brain cell types. These measurements uncover gene regulatory mechanisms that shape cellular identity and provide insight into developmental and evolutionary relationships between brain cell populations. Single-cell sequencing data can aid the design of tools for targeted functional studies of brain circuit components, linking molecular signatures with anatomy, connectivity, morphology, and physiology. Here, we discuss the fundamental principles of single-cell transcriptome and epigenome sequencing, integrative computational analysis of the data, and key applications in neuroscience.

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Primary Questions Addressed ​

  1. How do single-cell sequencing technologies specifically enhance our understanding of gene regulatory mechanisms in brain cells?
  2. What are the implications of single-cell sequencing findings for the study of neurodevelopmental disorders?
  3. In what ways can single-cell sequencing data inform the design of targeted therapies for neurological diseases?
  4. How does the integration of transcriptomic and epigenomic data improve our insights into brain cell diversity and function?
  5. What challenges exist in the computational analysis of single-cell sequencing data, and how can they be addressed?

Key Findings ​

Research Background and Objectives ​

Single-cell sequencing technologies have revolutionized the understanding of brain cell diversity and function by allowing researchers to analyze the transcriptomes and epigenomes of individual cells. This primer aims to outline the principles, methodologies, and applications of single-cell sequencing in neuroscience, emphasizing its potential to unveil gene regulatory mechanisms and enhance our understanding of neural circuits.

Main Methods/Materials/Experimental Design ​

The primer describes two primary approaches in single-cell sequencing: transcriptomic and epigenomic assays. Key methodologies include:

  1. Single-Cell RNA Sequencing (scRNA-seq): This technique captures mRNA from individual cells to analyze gene expression profiles.
  2. Single-Nucleus RNA Sequencing (snRNA-seq): A variant that isolates RNA from nuclei, useful for studying frozen or post-mortem tissues.
  3. Single-Cell Epigenome Sequencing: Techniques like single-nucleus ATAC-seq (snATAC-seq) and bisulfite sequencing assess chromatin accessibility and DNA methylation, respectively.

The process can be summarized in the following flowchart:

Mermaid diagram

Key Results and Findings ​

  1. Diversity of Brain Cell Types: Recent studies using scRNA-seq have identified thousands of distinct cell types across various brain regions, significantly expanding the understanding of cellular diversity.
  2. Gene Regulatory Mechanisms: The integration of transcriptomic and epigenomic data reveals complex regulatory networks governing cell identity and function.
  3. Applications in Disease: Single-cell techniques have uncovered disease-specific transcriptomic signatures, providing insights into conditions like Alzheimer's disease, depression, and autism.

Main Conclusions/Significance/Innovativeness ​

Single-cell sequencing is a powerful tool for elucidating the complexity of brain cell types and their functions. It enables researchers to link molecular signatures with anatomical and physiological data, paving the way for targeted functional studies. The ability to explore cellular diversity at unprecedented resolution marks a significant advancement in neuroscience.

Research Limitations and Future Directions ​

Despite its advantages, single-cell sequencing faces challenges such as:

  • Technical Limitations: Issues like doublets (two cells captured as one) and contamination can affect data quality.
  • Dynamic Measurements: Current methods primarily provide static snapshots of cellular states, lacking the ability to capture dynamic changes over time.

Future research should focus on developing methodologies that combine single-cell sequencing with functional assays, improving spatial resolution, and addressing computational challenges to integrate multi-omic data effectively. There is also a need for comprehensive studies that explore the evolutionary aspects of brain cell types across species.

References ​

  1. Complex multi-enhancer contacts captured by genome architecture mapping. - Robert A Beagrie;Antonio Scialdone;Markus Schueler;Dorothee C A Kraemer;Mita Chotalia;Sheila Q Xie;Mariano Barbieri;Inês de Santiago;Liron-Mark Lavitas;Miguel R Branco;James Fraser;Josée Dostie;Laurence Game;Niall Dillon;Paul A W Edwards;Mario Nicodemi;Ana Pombo - Nature (2017)
  2. Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain. - Bushra Raj;Daniel E Wagner;Aaron McKenna;Shristi Pandey;Allon M Klein;Jay Shendure;James A Gagnon;Alexander F Schier - Nature biotechnology (2018)
  3. Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data. - Hannah A Pliner;Jonathan S Packer;José L McFaline-Figueroa;Darren A Cusanovich;Riza M Daza;Delasa Aghamirzaie;Sanjay Srivatsan;Xiaojie Qiu;Dana Jackson;Anna Minkina;Andrew C Adey;Frank J Steemers;Jay Shendure;Cole Trapnell - Molecular cell (2018)
  4. Epigenomic diversity of cortical projection neurons in the mouse brain. - Zhuzhu Zhang;Jingtian Zhou;Pengcheng Tan;Yan Pang;Angeline C Rivkin;Megan A Kirchgessner;Elora Williams;Cheng-Ta Lee;Hanqing Liu;Alexis D Franklin;Paula Assakura Miyazaki;Anna Bartlett;Andrew I Aldridge;Minh Vu;Lara Boggeman;Conor Fitzpatrick;Joseph R Nery;Rosa G Castanon;Mohammad Rashid;Matthew W Jacobs;Tony Ito-Cole;Carolyn O'Connor;António Pinto-Duartec;Bertha Dominguez;Jared B Smith;Sheng-Yong Niu;Kuo-Fen Lee;Xin Jin;Eran A Mukamel;M Margarita Behrens;Joseph R Ecker;Edward M Callaway - Nature (2021)
  5. cisTopic: cis-regulatory topic modeling on single-cell ATAC-seq data. - Carmen Bravo González-Blas;Liesbeth Minnoye;Dafni Papasokrati;Sara Aibar;Gert Hulselmans;Valerie Christiaens;Kristofer Davie;Jasper Wouters;Stein Aerts - Nature methods (2019)
  6. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. - Erez Lieberman-Aiden;Nynke L van Berkum;Louise Williams;Maxim Imakaev;Tobias Ragoczy;Agnes Telling;Ido Amit;Bryan R Lajoie;Peter J Sabo;Michael O Dorschner;Richard Sandstrom;Bradley Bernstein;M A Bender;Mark Groudine;Andreas Gnirke;John Stamatoyannopoulos;Leonid A Mirny;Eric S Lander;Job Dekker - Science (New York, N.Y.) (2009)
  7. Analysis of intronic and exonic reads in RNA-seq data characterizes transcriptional and post-transcriptional regulation. - Dimos Gaidatzis;Lukas Burger;Maria Florescu;Michael B Stadler - Nature biotechnology (2015)
  8. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. - Patrik L Ståhl;Fredrik Salmén;Sanja Vickovic;Anna Lundmark;José Fernández Navarro;Jens Magnusson;Stefania Giacomello;Michaela Asp;Jakub O Westholm;Mikael Huss;Annelie Mollbrink;Sten Linnarsson;Simone Codeluppi;Åke Borg;Fredrik Pontén;Paul Igor Costea;Pelin Sahlén;Jan Mulder;Olaf Bergmann;Joakim Lundeberg;Jonas Frisén - Science (New York, N.Y.) (2016)
  9. Identification of transcription factor binding sites using ATAC-seq. - Zhijian Li;Marcel H Schulz;Thomas Look;Matthias Begemann;Martin Zenke;Ivan G Costa - Genome biology (2019)
  10. RNA velocity of single cells. - Gioele La Manno;Ruslan Soldatov;Amit Zeisel;Emelie Braun;Hannah Hochgerner;Viktor Petukhov;Katja Lidschreiber;Maria E Kastriti;Peter Lönnerberg;Alessandro Furlan;Jean Fan;Lars E Borm;Zehua Liu;David van Bruggen;Jimin Guo;Xiaoling He;Roger Barker;Erik Sundström;Gonçalo Castelo-Branco;Patrick Cramer;Igor Adameyko;Sten Linnarsson;Peter V Kharchenko - Nature (2018)

Literatures Citing This Work ​

  1. Functional Dissection of Glutamatergic and GABAergic Neurons in the Bed Nucleus of the Stria Terminalis. - Seong-Rae Kim;Sung-Yon Kim - Molecules and cells (2021)
  2. Single-Cell Transcriptomics Supports a Role of CHD8 in Autism. - Anke Hoffmann;Dietmar Spengler - International journal of molecular sciences (2021)
  3. Epigenetic regulation during human cortical development: Seq-ing answers from the brain to the organoid. - Emily M A Lewis;Komal Kaushik;Luke A Sandoval;Irene Antony;Sabine Dietmann;Kristen L Kroll - Neurochemistry international (2021)
  4. Single-Cell RNA Sequencing in Parkinson's Disease. - Shi-Xun Ma;Su Bin Lim - Biomedicines (2021)
  5. Dopamine Neuron Diversity: Recent Advances and Current Challenges in Human Stem Cell Models and Single Cell Sequencing. - Alessandro Fiorenzano;Edoardo Sozzi;Malin Parmar;Petter Storm - Cells (2021)
  6. Functional Genomics of Axons and Synapses to Understand Neurodegenerative Diseases. - Andres Di Paolo;Joaquin Garat;Guillermo Eastman;Joaquina Farias;Federico Dajas-Bailador;Pablo Smircich;José Roberto Sotelo-Silveira - Frontiers in cellular neuroscience (2021)
  7. Evolution of glutamatergic signaling and synapses. - Leonid L Moroz;Mikhail A Nikitin;Pavlin G Poličar;Andrea B Kohn;Daria Y Romanova - Neuropharmacology (2021)
  8. Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing - Review. - Gabriel Dorado;Sergio Gálvez;Teresa E Rosales;Víctor F Vásquez;Pilar Hernández - Biomolecules (2021)
  9. Chromatin Alterations in Neurological Disorders and Strategies of (Epi)Genome Rescue. - Marcin Janowski;Małgorzata Milewska;Peyman Zare;Aleksandra Pękowska - Pharmaceuticals (Basel, Switzerland) (2021)
  10. Development, Diversity, and Death of MGE-Derived Cortical Interneurons. - Rhîannan H Williams;Therese Riedemann - International journal of molecular sciences (2021)

... (120 more literatures)

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