Journal Article

DZNE-2024-01398

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Opportunities and challenges of single-cell and spatially resolved genomics methods for neuroscience discovery.

Bonev, B. ; Gonçalo, C.-B. ; Chen, F. ; Codeluppi, S. ; Corces, M. R. ; Fan, J. ; Heiman, M. ; Harris, K. ; Inoue, F. ; Kellis, M. ; Levine, A. ; Lotfollahi, M. ; Luo, C. ; Maynard, K. R. ; Nitzan, M. ; Ramani, V. ; Satijia, R. ; Schirmer, L. ; Shen, Y. ; Sun, N. ; Green, G. S. ; Theis, F. ; Wang, X. ; Welch, J. D. ; Gokce, O.DZNE* ; Konopka, G. ; Liddelow, S. ; Macosko, E. ; Bayraktar, O. ; Habib, N. ; Nowakowski, T. J.

2024
Nature America New York, NY

This record in other databases:    

Please use a persistent id in citations: doi:10.1038/s41593-024-01806-0

Abstract: Over the past decade, single-cell genomics technologies have allowed scalable profiling of cell-type-specific features, which has substantially increased our ability to study cellular diversity and transcriptional programs in heterogeneous tissues. Yet our understanding of mechanisms of gene regulation or the rules that govern interactions between cell types is still limited. The advent of new computational pipelines and technologies, such as single-cell epigenomics and spatially resolved transcriptomics, has created opportunities to explore two new axes of biological variation: cell-intrinsic regulation of cell states and expression programs and interactions between cells. Here, we summarize the most promising and robust technologies in these areas, discuss their strengths and limitations and discuss key computational approaches for analysis of these complex datasets. We highlight how data sharing and integration, documentation, visualization and benchmarking of results contribute to transparency, reproducibility, collaboration and democratization in neuroscience, and discuss needs and opportunities for future technology development and analysis.

Keyword(s): Single-Cell Analysis: methods (MeSH) ; Humans (MeSH) ; Genomics: methods (MeSH) ; Neurosciences: methods (MeSH) ; Animals (MeSH) ; Epigenomics: methods (MeSH)

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Contributing Institute(s):

1. Spatial Dynamics of Neurodegeneration (AG Gokce)

Research Program(s):

1. 351 - Brain Function (POF4-351) (POF4-351)

Appears in the scientific report 2024

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Database coverage:
; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; DEAL Nature ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 20 ; JCR ; Nationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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Linked articles:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article (Erratum/Correction) Bonev, B. ; Castelo-Branco, G. ; Chen, F. ; Codeluppi, S. ; Corces, M. R. ; Fan, J. ; Heiman, M. ; Harris, K. ; Inoue, F. ; Kellis, M. ; Levine, A. ; Lotfollahi, M. ; Luo, C. ; Maynard, K. R. ; Nitzan, M. ; Ramani, V. ; Satijia, R. ; Schirmer, L. ; Shen, Y. ; Sun, N. ; Green, G. S. ; Theis, F. ; Wang, X. ; Welch, J. D. ; Gokce, O.DZNE* ; Konopka, G. ; Liddelow, S. ; Macosko, E. ; Ali Bayraktar, O. ; Habib, N. ; Nowakowski, T. J.
Author Correction: Opportunities and challenges of single-cell and spatially resolved genomics methods for neuroscience discovery.
Nature neuroscience 28(1), 216 (2025) [10.1038/s41593-024-01858-2]2025   Files BibTeX | EndNote: XML, Text | RIS

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