Spatial epigenome-transcriptome co-profiling of mammalian tissues.
Journal
Nature
ISSN: 1476-4687
Titre abrégé: Nature
Pays: England
ID NLM: 0410462
Informations de publication
Date de publication:
04 2023
04 2023
Historique:
received:
06
06
2022
accepted:
03
02
2023
medline:
7
4
2023
pubmed:
17
3
2023
entrez:
16
3
2023
Statut:
ppublish
Résumé
Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context
Identifiants
pubmed: 36922587
doi: 10.1038/s41586-023-05795-1
pii: 10.1038/s41586-023-05795-1
pmc: PMC10076218
doi:
Substances chimiques
Chromatin
0
Histones
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
113-122Subventions
Organisme : NCI NIH HHS
ID : U24 CA248453
Pays : United States
Organisme : NCI NIH HHS
ID : U54 CA274509
Pays : United States
Organisme : NIMH NIH HHS
ID : RF1MH128876
Pays : United States
Organisme : NIA NIH HHS
ID : U54AG076043
Pays : United States
Organisme : NIA NIH HHS
ID : U54AG079759
Pays : United States
Organisme : NCI NIH HHS
ID : UG3CA257393
Pays : United States
Organisme : NCI NIH HHS
ID : R01CA245313
Pays : United States
Organisme : NCI NIH HHS
ID : U54CA274509
Pays : United States
Commentaires et corrections
Type : CommentIn
Type : CommentIn
Informations de copyright
© 2023. The Author(s).
Références
Liu, Y. et al. High-spatial-resolution multi-omics sequencing via deterministic barcoding in yissue. Cell 183, 1665–1681 (2020).
pubmed: 33188776
pmcid: 7736559
doi: 10.1016/j.cell.2020.10.026
Deng, Y. et al. Spatial-CUT&Tag: spatially resolved chromatin modification profiling at the cellular level. Science 375, 681–686 (2022).
pubmed: 35143307
pmcid: 7612972
doi: 10.1126/science.abg7216
Deng, Y. et al. Spatial profiling of chromatin accessibility in mouse and human tissues. Nature 609, 375–383 (2022).
pubmed: 35978191
pmcid: 9452302
doi: 10.1038/s41586-022-05094-1
Chen, A. et al. Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays. Cell 185, 1777–1792 (2022).
pubmed: 35512705
doi: 10.1016/j.cell.2022.04.003
Lu, T., Ang, C. E. & Zhuang, X. Spatially resolved epigenomic profiling of single cells in complex tissues. Cell 185, 4448–4464 (2022).
pubmed: 36272405
doi: 10.1016/j.cell.2022.09.035
Allaway, K. C. et al. Genetic and epigenetic coordination of cortical interneuron development. Nature 597, 693–697 (2021).
pubmed: 34552240
pmcid: 9316417
doi: 10.1038/s41586-021-03933-1
Chen, S., Lake, B. B. & Zhang, K. High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell. Nat. Biotechnol. 37, 1452–1457 (2019).
pubmed: 31611697
pmcid: 6893138
doi: 10.1038/s41587-019-0290-0
Cao, J. et al. Joint profiling of chromatin accessibility and gene expression in thousands of single cells. Science 361, 1380–1385 (2018).
pubmed: 30166440
pmcid: 6571013
doi: 10.1126/science.aau0730
Trevino, A. E. et al. Chromatin and gene-regulatory dynamics of the developing human cerebral cortex at single-cell resolution. Cell 184, 5053–5069 (2021).
pubmed: 34390642
doi: 10.1016/j.cell.2021.07.039
Ma, S. et al. Chromatin potential identified by shared single-cell profiling of RNA and chromatin. Cell 183, 1103–1116 (2020).
pubmed: 33098772
pmcid: 7669735
doi: 10.1016/j.cell.2020.09.056
Ben-Chetrit, N. et al. Integration of whole transcriptome spatial profiling with protein markers. Nat. Biotechnol. https://doi.org/10.1038/s41587-022-01536-3 (2023).
doi: 10.1038/s41587-022-01536-3
pubmed: 36593397
Cao, J. et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019).
pubmed: 30787437
pmcid: 6434952
doi: 10.1038/s41586-019-0969-x
Granja, J. M. et al. ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis. Nat. Genet. 53, 403–411 (2021).
pubmed: 33633365
pmcid: 8012210
doi: 10.1038/s41588-021-00790-6
Gómez-López, S. et al. Sox2 and Pax6 maintain the proliferative and developmental potential of gliogenic neural stem cells In vitro. Glia 59, 1588–1599 (2011).
pubmed: 21766338
doi: 10.1002/glia.21201
Mihelec, M. et al. Novel SOX2 partner-factor domain mutation in a four-generation family. Eur. J. Hum. Genet. 17, 1417–1422 (2009).
pubmed: 19471311
pmcid: 2986670
doi: 10.1038/ejhg.2009.79
Chen, J. et al. A MYT1L syndrome mouse model recapitulates patient phenotypes and reveals altered brain development due to disrupted neuronal maturation. Neuron 109, 3775–3792 (2021).
pubmed: 34614421
pmcid: 8668036
doi: 10.1016/j.neuron.2021.09.009
Diacou, R., Zhao, Y., Zheng, D., Cvekl, A. & Liu, W. Six3 and Six6 are jointly required for the maintenance of multipotent retinal progenitors through both positive and negative regulation. Cell Rep. 25, 2510–2523 (2018).
pubmed: 30485816
doi: 10.1016/j.celrep.2018.10.106
Stelzer, G. et al. The GeneCards Suite: from gene data mining to disease genome sequence analyses. Curr. Protoc. Bioinformatics 54, 1.30.31–31.30.33 (2016).
doi: 10.1002/cpbi.5
Huang, D.-F. et al. Neuronal splicing regulator RBFOX3 mediates seizures via regulating Vamp1 expression preferentially in NPY-expressing GABAergic neurons. Proc. Natl Acad. Sci. USA 119, e2203632119 (2022).
pubmed: 35951651
pmcid: 9388145
doi: 10.1073/pnas.2203632119
Schep, A. N., Wu, B., Buenrostro, J. D. & Greenleaf, W. J. chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data. Nat. Methods 14, 975–978 (2017).
pubmed: 28825706
pmcid: 5623146
doi: 10.1038/nmeth.4401
Amador-Arjona, A. et al. SOX2 primes the epigenetic landscape in neural precursors enabling proper gene activation during hippocampal neurogenesis. Proc. Natl Acad. Sci. USA 112, E1936–E1945 (2015).
pubmed: 25825708
pmcid: 4403144
doi: 10.1073/pnas.1421480112
McLean, C. Y. et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 28, 495–501 (2010).
pubmed: 20436461
pmcid: 4840234
doi: 10.1038/nbt.1630
Yoshida, H. & Goedert, M. Phosphorylation of microtubule-associated protein tau by AMPK-related kinases. J. Neurochem. 120, 165–176 (2012).
pubmed: 21985311
doi: 10.1111/j.1471-4159.2011.07523.x
Zhao, S. et al. Expanding the mutation and phenotype spectrum of MYH3-associated skeletal disorders. NPJ Genom. Med. 7, 11 (2022).
pubmed: 35169139
pmcid: 8847563
doi: 10.1038/s41525-021-00273-x
Wu, T. et al. clusterProfiler 4.0: a universal enrichment tool for interpreting omics data. Innovation (Camb.) 2, 100141 (2021).
pubmed: 34557778
Zhu, C. et al. Joint profiling of histone modifications and transcriptome in single cells from mouse brain. Nat. Methods 18, 283–292 (2021).
pubmed: 33589836
pmcid: 7954905
doi: 10.1038/s41592-021-01060-3
Meijer, M. et al. Epigenomic priming of immune genes implicates oligodendroglia in multiple sclerosis susceptibility. Neuron 110, 1193–1210 (2022).
pubmed: 35093191
doi: 10.1016/j.neuron.2021.12.034
Kriegstein, A. & Alvarez-Buylla, A. The glial nature of embryonic and adult neural stem cells. Annu. Rev. Neurosci. 32, 149–184 (2009).
pubmed: 19555289
pmcid: 3086722
doi: 10.1146/annurev.neuro.051508.135600
Trapnell, C. et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32, 381–386 (2014).
pubmed: 24658644
pmcid: 4122333
doi: 10.1038/nbt.2859
Li, Y. E. et al. An atlas of gene regulatory elements in adult mouse cerebrum. Nature 598, 129–136 (2021).
pubmed: 34616068
pmcid: 8494637
doi: 10.1038/s41586-021-03604-1
Tasic, B. et al. Shared and distinct transcriptomic cell types across neocortical areas. Nature 563, 72–78 (2018).
pubmed: 30382198
pmcid: 6456269
doi: 10.1038/s41586-018-0654-5
Zeisel, A. et al. Molecular architecture of the mouse nervous system. Cell 174, 999–1014 (2018).
pubmed: 30096314
pmcid: 6086934
doi: 10.1016/j.cell.2018.06.021
Kartha, V. K. et al. Functional inference of gene regulation using single-cell multi-omics. Cell Genom. 2, 100166 (2022).
pubmed: 36204155
pmcid: 9534481
doi: 10.1016/j.xgen.2022.100166
Ma, C., Chitra, U., Zhang, S. & Raphael, B. J. Belayer: modeling discrete and continuous spatial variation in gene expression from spatially resolved transcriptomics. Cell Syst. 13, 786–797 (2022).
pubmed: 36265465
doi: 10.1016/j.cels.2022.09.002
Wu, S. J. et al. Single-cell CUT&Tag analysis of chromatin modifications in differentiation and tumor progression. Nat. Biotechnol. 39, 819–824 (2021).
pubmed: 33846646
pmcid: 8277750
doi: 10.1038/s41587-021-00865-z
Bartosovic, M., Kabbe, M. & Castelo-Branco, G. Single-cell CUT&Tag profiles histone modifications and transcription factors in complex tissues. Nat. Biotechnol. 39, 825–835 (2021).
pubmed: 33846645
pmcid: 7611252
doi: 10.1038/s41587-021-00869-9
Bartosovic, M. & Castelo-Branco, G. Multimodal chromatin profiling using nanobody-based single-cell CUT&Tag. Nat. Biotechnol. https://doi.org/10.1038/s41587-022-01535-4 (2022).
doi: 10.1038/s41587-022-01535-4
pubmed: 36536148
Marques, S. et al. Oligodendrocyte heterogeneity in the mouse juvenile and adult central nervous system. Science 352, 1326–1329 (2016).
pubmed: 27284195
pmcid: 5221728
doi: 10.1126/science.aaf6463
Marques, S. et al. Transcriptional convergence of oligodendrocyte lineage progenitors during development. Dev. Cell 46, 504–517 (2018).
pubmed: 30078729
pmcid: 6104814
doi: 10.1016/j.devcel.2018.07.005
Otte, C. et al. Major depressive disorder. Nat. Rev. Dis. Primers 2, 16065 (2016).
pubmed: 27629598
doi: 10.1038/nrdp.2016.65
Wagner, J. et al. Medin co-aggregates with vascular amyloid-β in Alzheimer’s disease. Nature 612, 123–131(2022).
pubmed: 36385530
pmcid: 9712113
doi: 10.1038/s41586-022-05440-3
Corces, M. R. et al. Single-cell epigenomic analyses implicate candidate causal variants at inherited risk loci for Alzheimer’s and Parkinson’s diseases. Nat. Genet. 52, 1158–1168 (2020).
pubmed: 33106633
pmcid: 7606627
doi: 10.1038/s41588-020-00721-x
Franjic, D. et al. Transcriptomic taxonomy and neurogenic trajectories of adult human, macaque, and pig hippocampal and entorhinal cells. Neuron 110, 452–469 (2022).
pubmed: 34798047
doi: 10.1016/j.neuron.2021.10.036
La Manno, G. et al. RNA velocity of single cells. Nature 560, 494–498 (2018).
pubmed: 30089906
pmcid: 6130801
doi: 10.1038/s41586-018-0414-6
Thornton, C. A. et al. Spatially mapped single-cell chromatin accessibility. Nat. Commun. 12, 1274 (2021).
pubmed: 33627658
pmcid: 7904839
doi: 10.1038/s41467-021-21515-7
Cho, C.-S. et al. Microscopic examination of spatial transcriptome using Seq-Scope. Cell 184, 3559–3572 (2021).
pubmed: 34115981
pmcid: 8238917
doi: 10.1016/j.cell.2021.05.010
Fu, X. et al. Polony gels enable amplifiable DNA stamping and spatial transcriptomics of chronic pain. Cell 185, 4621–4633 (2022).
pubmed: 36368323
doi: 10.1016/j.cell.2022.10.021
Fang, R. et al. Conservation and divergence of cortical cell organization in human and mouse revealed by MERFISH. Science 377, 56–62 (2022).
pubmed: 35771910
pmcid: 9262715
doi: 10.1126/science.abm1741
Takei, Y. et al. Integrated spatial genomics reveals global architecture of single nuclei. Nature 590, 344–350 (2021).
pubmed: 33505024
pmcid: 7878433
doi: 10.1038/s41586-020-03126-2
Chen, A. F. et al. NEAT-seq: simultaneous profiling of intra-nuclear proteins, chromatin accessibility and gene expression in single cells. Nat. Methods 19, 547–553 (2022).
pubmed: 35501385
doi: 10.1038/s41592-022-01461-y
Endicott, J., Spitzer, R. L., Fleiss, J. L. & Cohen, J. The Global Assessment Scale: a procedure for measuring overall severity of psychiatric disturbance. Arch. Gen. Psychiatry 33, 766–771 (1976).
pubmed: 938196
doi: 10.1001/archpsyc.1976.01770060086012
Su, G. et al. Spatial multi-omics sequencing for fixed tissue via DBiT-seq. STAR Protoc. 2, 100532 (2021).
pubmed: 34027489
pmcid: 8132129
doi: 10.1016/j.xpro.2021.100532
Navarro, J. F., Sjostrand, J., Salmen, F., Lundeberg, J. & Stahl, P. L. ST Pipeline: an automated pipeline for spatial mapping of unique transcripts. Bioinformatics 33, 2591–2593 (2017).
pubmed: 28398467
doi: 10.1093/bioinformatics/btx211
Stuart, T., Srivastava, A., Madad, S., Lareau, C. A. & Satija, R. Single-cell chromatin state analysis with Signac. Nat. Methods 18, 1333–1341 (2021).
pubmed: 34725479
pmcid: 9255697
doi: 10.1038/s41592-021-01282-5
Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420 (2018).
pubmed: 29608179
pmcid: 6700744
doi: 10.1038/nbt.4096
Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587 (2021).
pubmed: 34062119
pmcid: 8238499
doi: 10.1016/j.cell.2021.04.048