Variation among intact tissue samples reveals the core transcriptional features of human CNS cell classes
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Abstract
It is widely assumed that cells must be physically isolated to study their molecular profiles. However, intact tissue samples naturally exhibit variation in cellular composition, which drives covariation of cell-class-specific molecular features. By analyzing transcriptional covariation in 7,221 intact CNS samples from 840 neurotypical individuals, representing billions of cells, we reveal the core transcriptional identities of major CNS cell classes in humans. By modeling intact CNS transcriptomes as a function of variation in cellular composition, we identify cell-class-specific transcriptional differences in Alzheimer's disease, among brain regions, and between species. Among these, we show that PMP2 is expressed by human but not mouse astrocytes and significantly increases mouse astrocyte size upon ectopic expression in vivo, causing them to more closely resemble their human counterparts. Our work is available as an online resource ( http://oldhamlab.ctec.ucsf.edu/ ) and provides a generalizable strategy for determining the core molecular features of cellular identity in intact biological systems.
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Other studies have also found that microglial expression, in general, is particularly underrepresented in bulk transcriptomes, relative to that of other brain cell types.
“Other studies have also found that microglial expression, in general, is particularly underrepresented in bulk transcriptomes, relative to that of other brain cell types (8,42) .”
From Single cell transcriptome profiling of the human alcohol-dependent brain (2020) · cites this paper as [42]
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WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252 · see citing works
Tissue-based map of the human proteome
Uhlén, M., Fagerberg, L., Hallström, B. M., Lindskog, C., Oksvold, P., Mardinoglu, A., Sivertsson, Å., Kampf, C., Sjöstedt, E., Asplund, A., et al. (2015) · Science · doi:10.1126/science.1260419 · Cited by 15,286 · see citing works
ggplot2: Elegant Graphics for Data Analysis
Wickham, H. (2009) · doi:10.1007/978-0-387-98141-3 · Cited by 14,447 · see citing works
Robust enumeration of cell subsets from tissue expression profiles
Newman, A. M., Liu, C. L., Green, M. R., Gentles, A. J., Feng, W., Xu, Y., Hoang, C. D., Diehn, M., & Alizadeh, A. A. (2015) · Nature Methods · doi:10.1038/nmeth.3337 · Cited by 12,116 · see citing works
Exploration, normalization, and summaries of high density oligonucleotide array probe level data
Irizarry, R. A. (2003) · Biostatistics · doi:10.1093/biostatistics/4.2.249 · Cited by 10,603 · see citing works
STRING v10: protein–protein interaction networks, integrated over the tree of life
Szklarczyk, D., Franceschini, A., Wyder, S., Forslund, K., Heller, D., Huerta-Cepas, J., Simonovic, M., Roth, A., Santos, A., Tsafou, K. P., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gku1003 · Cited by 10,436 · see citing works
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692 · see citing works
Analysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587 · see citing works
Adjusting batch effects in microarray expression data using empirical Bayes methods
Johnson, W. E., Li, C., & Rabinovic, A. (2007) · Biostatistics · doi:10.1093/biostatistics/kxj037 · Cited by 8,658 · see citing works
Bolstad, B. M., Irizarry, R. A., Åstrand, M., & Speed, T. P. (2003) · Bioinformatics · doi:10.1093/bioinformatics/19.2.185 · Cited by 8,185 · see citing works
Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314 · see citing works
Genome-wide atlas of gene expression in the adult mouse brain
Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) · Nature · doi:10.1038/nature05453 · Cited by 5,572 · see citing works
affy—analysis of Affymetrix GeneChip data at the probe level
Gautier, L., Cope, L., Bolstad, B. M., & Irizarry, R. A. (2004) · Bioinformatics · doi:10.1093/bioinformatics/btg405 · Cited by 5,221 · see citing works
The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science · doi:10.1126/science.1262110 · Cited by 5,062 · see citing works
Zhang, Y., Chen, K., Sloan, S. A., Bennett, M. L., Scholze, A. R., O'Keeffe, S., Phatnani, H. P., Guarnieri, P., Caneda, C., Ruderisch, N., et al. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.1860-14.2014 · Cited by 4,875 · see citing works
Missing Value Estimation Methods for DNA Microarrays
Troyanskaya, O., Cantor, M., Sherlock, G., Brown, P., Hastie, T., Tibshirani, R., Botstein, D., & Altman, R. B. (2001) · Bioinformatics · doi:10.1093/bioinformatics/17.6.520 · Cited by 4,230 · see citing works
GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor
Davis, S. R., & Meltzer, P. S. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm254 · Cited by 3,289 · see citing works
Cahoy, J. D., Emery, B., Kaushal, A., Foo, L. C., Zamanian, J. L., Christopherson, K. S., Xing, Y., Lubischer, J. L., Krieg, P. A., Krupenko, S. A., et al. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.4178-07.2008 · Cited by 3,129 · see citing works
Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq
Zeisel, A., Muñoz-Manchado, A. B., Codeluppi, S., Lönnerberg, P., La Manno, G., Juréus, A., Marques, S., Munguba, H., He, L., Betsholtz, C., et al. (2015) · Science · doi:10.1126/science.aaa1934 · Cited by 3,124 · see citing works
ToppGene Suite for gene list enrichment analysis and candidate gene prioritization
Chen, J., Bardes, E. E., Aronow, B. J., & Jegga, A. G. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp427 · Cited by 2,952 · see citing works
Cellular Scaling Rules for the Brains of Marsupials: Not as “Primitive” as Expected
Santos, S. E. D., Porfírio, J., Cunha, F., Manger, P. R., Tavares, W. C., Pessôa, L. M., Raghanti, M. A., Sherwood, C. C., & Herculano‐Houzel, S. (2017) · Brain Behavior and Evolution · doi:10.1159/000452856 · Cited by 2,651 · see citing works
Identification of a unique TGF-β–dependent molecular and functional signature in microglia
Butovsky, O., Jedrychowski, M. P., Moore, C. S., Cialic, R., Lanser, A. J., Gabriely, G., Koeglsperger, T., Dake, B., Wu, P. M., Doykan, C. E., et al. (2014) · Nature Neuroscience · doi:10.1038/nn.3599 · Cited by 2,543 · see citing works
Azevedo, F. A. C., Carvalho, L. R. B., Grinberg, L. T., Farfel, J. M., Ferretti, R. E. L., Leite, R. E. P., Filho, W. J., Lent, R., & Herculano‐Houzel, S. (2009) · Journal of Comparative Neurology · doi:10.1002/cne.21974 · Cited by 2,337 · see citing works
Zhang, Y., Sloan, S. A., Clarke, L. E., Caneda, C., Plaza, C. A., Blumenthal, P. D., Vogel, H., Steinberg, G. K., Edwards, M. S. B., Li, G., et al. (2016) · Neuron · doi:10.1016/j.neuron.2015.11.013 · Cited by 2,295 · see citing works
Spatio-temporal transcriptome of the human brain
Kang, H. J., Kawasawa, Y. I., Cheng, F., Zhu, Y., Xu, X., Li, M., Sousa, A. M. M., Pletikos, M., Meyer, K. A., Sedmak, G., et al. (2011) · Nature · doi:10.1038/nature10523 · Cited by 2,084 · see citing works
Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data
Dai, M. (2005) · Nucleic Acids Research · doi:10.1093/nar/gni179 · Cited by 1,797 · see citing works
Adult mouse cortical cell taxonomy revealed by single cell transcriptomics
Tasic, B., Menon, V., Nguyen, T. N., Kim, T. K., Jarsky, T., Yao, Z., Levi, B., Gray, L. T., Sorensen, S. A., Dolbeare, T., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4216 · Cited by 1,714 · see citing works
Integrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer’s Disease
Zhang, B., Gaiteri, C., Bodea, L.-G., Wang, Z., McElwee, J., Podtelezhnikov, A. A., Zhang, C., Xie, T., Tran, L., Dobrin, R., et al. (2013) · Cell · doi:10.1016/j.cell.2013.03.030 · Cited by 1,657 · see citing works
Statistical Methods for Research Workers.
Hotelling, H., & Fisher, R. A. (1930) · Journal of the American Statistical Association · doi:10.2307/2278215 · Cited by 1,565 · see citing works
The microglial sensome revealed by direct RNA sequencing
Hickman, S. E., Kingery, N. D., Ohsumi, T. K., Borowsky, M. L., Wang, L.-C., Means, T. K., & El Khoury, J. (2013) · Nature Neuroscience · doi:10.1038/nn.3554 · Cited by 1,511 · see citing works
Statistical Methods for Research Workers
Fisher, R. A. (1992) · Springer series in statistics · doi:10.1007/978-1-4612-4380-9_6 · Cited by 1,464 · see citing works
A survey of human brain transcriptome diversity at the single cell level
Darmanis, S., Sloan, S. A., Zhang, Y., Enge, M., Caneda, C., Shuer, L. M., Hayden Gephart, M. G., Barres, B. A., & Quake, S. R. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1507125112 · Cited by 1,401 · see citing works
Massively parallel single-nucleus RNA-seq with DroNc-seq
Habib, N., Avraham-Davidi, I., Basu, A., Burks, T., Shekhar, K., Hofree, M., Choudhury, S. R., Aguet, F., Gelfand, E., Ardlie, K., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4407 · Cited by 1,069 · see citing works
Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain
Lake, B. B., Chen, S., Sos, B. C., Fan, J., Kaeser, G. E., Yung, Y. C., Duong, T. E., Gao, D., Chun, J., Kharchenko, P. V., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4038 · Cited by 983 · see citing works
Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain
Lake, B. B., Ai, R., Kaeser, G. E., Salathia, N. S., Yung, Y. C., Liu, R., Wildberg, A., Gao, D., Fung, H.-L., Chen, S., et al. (2016) · Science · doi:10.1126/science.aaf1204 · Cited by 957 · see citing works
Application of a translational profiling approach for the comparative analysis of CNS cell types
Doyle, J. P., Dougherty, J. D., Heiman, M., Schmidt, E. F., Stevens, T. R., Ma, G., Bupp, S., Shrestha, P., Shah, R. D., Doughty, M. L., et al. (2008) · Cell · doi:10.1016/j.cell.2008.10.029 · Cited by 912 · see citing works
Geometric Interpretation of Gene Coexpression Network Analysis
Horvath, S., & Dong, J. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000117 · Cited by 849 · see citing works
Intra- and Interspecific Variation in Primate Gene Expression Patterns
Enard, W., Khaitovich, P., Klose, J., Zöllner, S. K., Heißig, F., Giavalisco, P., Nieselt, K., Muchmore, E. A., Varki, A. P., Ravid, R., et al. (2002) · Science · doi:10.1126/science.1068996 · Cited by 845 · see citing works
Molecular diversity of midbrain development in mouse, human, and stem cells
La Manno, G., Gyllborg, D., Codeluppi, S., Nishimura, K., Salto, C., Zeisel, A., Borm, L. E., Stott, S. R. W., Toledo, E. M., Villaescusa, J. C., et al. (2016) · Cell · doi:10.1016/j.cell.2016.09.027 · Cited by 835 · see citing works
Regional and cellular gene expression changes in human Huntington's disease brain
Hodges, A., Strand, A. D., Aragaki, A. K., Kuhn, A., Sengstag, T., Hughes, G., Elliston, L. A., Hartog, C., Goldstein, D. R., Thu, D., et al. (2006) · Human Molecular Genetics · doi:10.1093/hmg/ddl013 · Cited by 804 · see citing works
Functional organization of the transcriptome in human brain
Oldham, M. C., Konopka, G., Iwamoto, K., Langfelder, P., Kato, T., Horvath, S., & Geschwind, D. H. (2008) · Nature Neuroscience · doi:10.1038/nn.2207 · Cited by 752 · see citing works
Self-citationCanonical genetic signatures of the adult human brain
Hawrylycz, M., Miller, J. A., Menon, V., Feng, D., Dolbeare, T., Guillozet-Bongaarts, A. L., Jegga, A. G., Aronow, B. J., Lee, C.-K., Bernard, A., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4171 · Cited by 663 · see citing works
COMPARTMENTS: unification and visualization of protein subcellular localization evidence
Binder, J. X., Pletscher-Frankild, S., Tsafou, K., Stolte, C., O’Donoghue, S. I., Schneider, R., & Jensen, L. J. (2014) · Database · doi:10.1093/database/bau012 · Cited by 649 · see citing works
Altered brain microRNA biogenesis contributes to phenotypic deficits in a 22q11-deletion mouse model
Stark, K. L., Xu, B., Bagchi, A., Lai, W.-S., Liu, H., Hsu, R., Wan, X., Pavlidis, P., Mills, A. A., Karayiorgou, M., et al. (2008) · Nature Genetics · doi:10.1038/ng.138 · Cited by 648 · see citing works
Genetic variability in the regulation of gene expression in ten regions of the human brain
UK Brain Expression Consortium, Ramasamy, A., North American Brain Expression Consortium, Trabzuni, D., Guelfi, S., Varghese, V., Smith, C., Walker, R., De, T., Coin, L., et al. (2014) · Nature Neuroscience · doi:10.1038/nn.3801 · Cited by 644 · see citing works
Heterogeneity of astrocytic form and function.
Oberheim, N. A., Goldman, S. A., & Nedergaard, M. (2012) · Methods in Molecular Biology · doi:10.1007/978-1-61779-452-0_3 · Cited by 638 · see citing works
Gene expression changes in the course of normal brain aging are sexually dimorphic
Berchtold, N. C., Cribbs, D. H., Coleman, P. D., Rogers, J., Head, E., Kim, R., Beach, T., Miller, C., Troncoso, J., Trojanowski, J. Q., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0806883105 · Cited by 626 · see citing works
Parallel Patterns of Evolution in the Genomes and Transcriptomes of Humans and Chimpanzees
Khaitovich, P., Hellmann, I., Enard, W., Nowick, K., Leinweber, M., Franz, H., Weiß, G., Lachmann, M., & Pääbo, S. (2005) · Science · doi:10.1126/science.1108296 · Cited by 590 · see citing works
Circadian patterns of gene expression in the human brain and disruption in major depressive disorder
Li, J. Z., Bunney, B. G., Meng, F., Hagenauer, M. H., Walsh, D. M., Vawter, M. P., Evans, S. J., Choudary, P. V., Cartagena, P., Barchas, J. D., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1305814110 · Cited by 589 · see citing works
Cribbs, D. H., Berchtold, N. C., Perreau, V., Coleman, P. D., Rogers, J., Tenner, A. J., & Cotman, C. W. (2012) · Journal of Neuroinflammation · doi:10.1186/1742-2094-9-179 · Cited by 499 · see citing works
Elevated gene expression levels distinguish human from non-human primate brains
Cáceres, M., Lachuer, J., Zapala, M. A., Redmond, J. C., Kudo, L., Geschwind, D. H., Lockhart, D. J., Preuss, T. M., & Barlow, C. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2135499100 · Cited by 491 · see citing works
Cell type–specific gene expression differences in complex tissues
Shen-Orr, S. S., Tibshirani, R. J., Khatri, P., Bodian, D. L., Staedtler, F., Perry, N. M., Hastie, T. J., Sarwal, M., Davis, M. M., & Butte, A. J. (2010) · Nature Methods · doi:10.1038/nmeth.1439 · Cited by 489 · see citing works
Mittelbronn, M., Dietz, K., Schluesener, H. J., & Meyermann, R. (2001) · Acta Neuropathologica · doi:10.1007/s004010000284 · Cited by 482 · see citing works
Comparison of co-expression measures: mutual information, correlation, and model based indices
Song, L., Langfelder, P., & Horvath, S. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-328 · Cited by 460 · see citing works
Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNA-Seq
Gokce, O., Stanley, G. M., Treutlein, B., Neff, N. F., Camp, J. G., Malenka, R. C., Rothwell, P. E., Fuccillo, M. V., Südhof, T. C., & Quake, S. R. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.06.059 · Cited by 430 · see citing works
Abbas, A. R., Wolslegel, K., Seshasayee, D., Modrusan, Z. D., & Clark, H. F. (2009) · PLoS ONE · doi:10.1371/journal.pone.0006098 · Cited by 418 · see citing works
Transcriptional neoteny in the human brain
Somel, M., Franz, H., Zheng, Y., Lorenc, A., Guo, S., Giger, T., Kelso, J. F., Nickel, B., Dannemann, M., Bahn, S., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0900544106 · Cited by 409 · see citing works
Macromolecule biosynthesis: a key function of sleep
Mackiewicz, M., Shockley, K. R., Romer, M. A., Galante, R. J., Zimmerman, J. E., Naidoo, N. N., Baldwin, D. A., Jensen, S. T., Churchill, G. A., & Pack, A. I. (2007) · Physiological Genomics · doi:10.1152/physiolgenomics.00275.2006 · Cited by 378 · see citing works
A comprehensive transcriptional map of primate brain development
Bakken, T. E., Miller, J. A., Ding, S., Sunkin, S. M., Smith, K. A., Ng, L., Szafer, A., Dalley, R. A., Royall, J. J., Lemon, T. A., et al. (2016) · Nature · doi:10.1038/nature18637 · Cited by 376 · see citing works
Altered Expression of Diabetes-Related Genes in Alzheimer's Disease Brains: The Hisayama Study
Hokama, M., Oka, S., Leon, J., Ninomiya, T., Honda, H., Sasaki, K., Iwaki, T., Ohara, T., Sasaki, T., LaFerla, F. M., et al. (2013) · Cerebral Cortex · doi:10.1093/cercor/bht101 · Cited by 319 · see citing works
Regional Patterns of Gene Expression in Human and Chimpanzee BrainsPreprint
Khaitovich, P., Muetzel, B., She, X., Lachmann, M., Hellmann, I., Dietzsch, J., Steigele, S., Do, H.-H., Weiß, G., Enard, W., et al. (2004) · Genome Research · doi:10.1101/gr.2538704 · Cited by 311 · see citing works
Gong, T., & Szustakowski, J. D. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt090 · Cited by 295 · see citing works
Matarin, M., Salih, D. A., Yasvoina, M., Cummings, D. M., Guelfi, S., Liu, W., Nahaboo Solim, M. A., Moens, T. G., Paublete, R. M., Ali, S. S., et al. (2015) · Cell Reports · doi:10.1016/j.celrep.2014.12.041 · Cited by 290 · see citing works
High-performance probes for light and electron microscopy
Viswanathan, S., Williams, M. E., Bloss, E. B., Stasevich, T. J., Speer, C. M., Nern, A., Pfeiffer, B. D., Hooks, B. M., Li, W., English, B. P., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3365 · Cited by 255 · see citing works
Analysis of the brain mural cell transcriptome
He, L., Vanlandewijck, M., Raschperger, E., Andaloussi Mäe, M., Jung, B., Lebouvier, T., Ando, K., Hofmann, J., Keller, A., & Betsholtz, C. (2016) · Scientific Reports · doi:10.1038/srep35108 · Cited by 233 · see citing works
Yu, W., Clyne, M., Khoury, M. J., & GWINN, M. L. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp618 · Cited by 230 · see citing works
Single-cell transcriptome sequencing: recent advances and remaining challenges
Liu, S., & Trapnell, C. (2016) · F1000Research · doi:10.12688/f1000research.7223.1 · Cited by 230 · see citing works
Transcriptional Architecture of the Primate Neocortex
Bernard, A., Lubbers, L. S., Tanis, K. Q., Luo, R., Podtelezhnikov, A. A., Finney, E. M., McWhorter, M. M. E., Serikawa, K., Lemon, T., Morgan, R., et al. (2012) · Neuron · doi:10.1016/j.neuron.2012.03.002 · Cited by 224 · see citing works
Digital sorting of complex tissues for cell type-specific gene expression profiles
田中, 義., Wan, Y., Pang, K., Chow, L. M. L., & Liu, Z. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-89 · Cited by 207 · see citing works
The Adult Human Brain Harbors Multipotent Perivascular Mesenchymal Stem Cells
Paul, G., Özen, Í., Christophersen, N. S., Reinbothe, T. M., Bengzon, J., Visse, E., Jansson, K., Dannaeus, K., Henriques-Oliveira, C., Roybon, L., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0035577 · Cited by 201 · see citing works
Population-specific expression analysis (PSEA) reveals molecular changes in diseased brain
Kuhn, A., Thu, D., Waldvogel, H. J., Faull, R. L. M., & Luthi-Carter, R. (2011) · Nature Methods · doi:10.1038/nmeth.1710 · Cited by 195 · see citing works
Aging and Gene Expression in the Primate Brain
Fraser, H. B., Khaitovich, P., Plotkin, J. B., Pääbo, S., & Eisen, M. B. (2005) · PLoS Biology · doi:10.1371/journal.pbio.0030274 · Cited by 172 · see citing works
Estimating R 2 Shrinkage in Multiple Regression: A Comparison of Different Analytical Methods
Yin, P., & Fan, X. (2001) · The Journal of Experimental Education · doi:10.1080/00220970109600656 · Cited by 166 · see citing works
Radial glia require PDGFD-PDGFRβ signalling in human but not mouse neocortex
Lui, J. H., Nowakowski, T. J., Pollen, A. A., Javaherian, A., Kriegstein, A. R., & Oldham, M. C. (2014) · Nature · doi:10.1038/nature13973 · Cited by 166 · see citing works
Self-citationOldham, M. C., Langfelder, P., & Horvath, S. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-63 · Cited by 154 · see citing works
Self-citationStevens, S. L., Leung, P. Y., Vartanian, K. B., Gopalan, B., Yang, T., Simon, R. P., & Stenzel‐Poore, M. P. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.0821-11.2011 · Cited by 151 · see citing works
Mancarci, B. O., Toker, L., Tripathy, S. J., Li, B., Rocco, B. R., Sibille, E. L., & Pavlidis, P. (2017) · eNeuro · doi:10.1523/eneuro.0212-17.2017 · Cited by 138 · see citing works
Hernandez, D. G., Nalls, M. A., Moore, M., Chong, S., Dillman, A., Trabzuni, D., Gibbs, J. R., Ryten, M., Arepalli, S., Weale, M. E., et al. (2012) · Neurobiology of Disease · doi:10.1016/j.nbd.2012.03.020 · Cited by 128 · see citing works
Ponomarev, I., Rau, V., Eger, E. I., Harris, R. A., & Fanselow, M. S. (2010) · Neuropsychopharmacology · doi:10.1038/npp.2010.10 · Cited by 109 · see citing works
Wes, P. D., Easton, A. E., Corradi, J., Barten, D. M., Devidze, N., DeCarr, L. B., Truong, A. B., He, A., Barrezueta, N. X., Polson, C. T., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0106050 · Cited by 105 · see citing works
Hilliard, A. T., Miller, J. E., Fraley, E., Horvath, S., & White, S. A. (2012) · Neuron · doi:10.1016/j.neuron.2012.01.005 · Cited by 105 · see citing works
Bozek, K., Wei, Y., Yan, Z., Liu, X., Xiong, J., Sugimoto, M., Tomita, M., Pääbo, S., Pieszek, R., Sherwood, C. C., et al. (2014) · PLoS Biology · doi:10.1371/journal.pbio.1001871 · Cited by 93 · see citing works
A robust measure of correlation between two genes on a microarray
Hardin, J., Mitani, A., Hicks, L., & Koten, B. V. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-220 · Cited by 91 · see citing works
Memory acquisition and retrieval impact different epigenetic processes that regulate gene expression
Peixoto, L., Wimmer, M. E., Poplawski, S. G., Tudor, J. C., Kenworthy, C. A., Liu, S., Mizuno, K., Garcia, B. A., Zhang, N. R., Giese, K.-P., et al. (2015) · BMC Genomics · doi:10.1186/1471-2164-16-s5-s5 · Cited by 89 · see citing works
Wolen, A. R., Phillips, C., Langston, M. A., Putman, A. H., Vorster, P. J., Bruce, N. A., York, T. P., Williams, R. W., & Miles, M. F. (2012) · PLoS ONE · doi:10.1371/journal.pone.0033575 · Cited by 82 · see citing works
A role of peripheral myelin protein 2 in lipid homeostasis of myelinating schwann cells
Zenker, J., Stettner, M., Ruskamo, S., Domènech‐Estévez, E., Baloui, H., Médard, J., Verheijen, M. H. G., Brouwers, J. F. H. M., Kursula, P., Kieseier, B. C., et al. (2014) · Glia · doi:10.1002/glia.22696 · Cited by 77 · see citing works
Ling, K., Hewitt, C., Tan, K.-L., Cheah, P.-S., Vidyadaran, S., Lai, M. I., Lee, H.-C., Simpson, K., Hyde, L., Pritchard, M. A., et al. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-624 · Cited by 66 · see citing works
Molofsky, A., Glasgow, S. M., Chaboub, L. S., Tsai, H.-H., Murnen, A. T., Kelley, K. W., Fancy, S., Yuen, T. J., Madireddy, L., Baranzini, S., et al. (2013) · Glia · doi:10.1002/glia.22538 · Cited by 65 · see citing works
Self-citationDetecting false expression signals in high-density oligonucleotide arrays by an in silico approach
Zhang, J., Finney, R. P., Clifford, R., Derr, L. K., & Buetow, K. H. (2004) · Genomics · doi:10.1016/j.ygeno.2004.11.004 · Cited by 64 · see citing works
Laminar and Temporal Expression Dynamics of Coding and Noncoding RNAs in the Mouse Neocortex
Fertuzinhos, S., Li, M., Kawasawa, Y. I., Ivić, V., Franjic, D., Singh, D., Crair, M. C., & Šestan, N. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.01.036 · Cited by 62 · see citing works
Quantitative Expression Profile of Distinct Functional Regions in the Adult Mouse Brain
Kasukawa, T., Masumoto, K., Nikaido, I., Nagano, M., Uno, K. D., Tsujino, K., Hanashima, C., Shigeyoshi, Y., & Ueda, H. R. (2011) · PLoS ONE · doi:10.1371/journal.pone.0023228 · Cited by 62 · see citing works
Cosplicing network analysis of mammalian brain RNA-Seq data utilizing WGCNA and Mantel correlations
Iancu, O. D., Colville, A., Oberbeck, D., Darakjian, P., McWeeney, S. K., & Hitzemann, R. (2015) · Frontiers in Genetics · doi:10.3389/fgene.2015.00174 · Cited by 57 · see citing works
Positive selection on gene expression in the human brain
Khaitovich, P., Tang, K., Franz, H., Kelso, J. F., Hellmann, I., Enard, W., Lachmann, M., & Pääbo, S. (2006) · Current Biology · doi:10.1016/j.cub.2006.03.082 · Cited by 54 · see citing works
Yu, W., Clyne, M., Dolan, S. M., Yesupriya, A., Wulf, A., Liu, T., Khoury, M. J., & GWINN, M. L. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-205 · Cited by 52 · see citing works
Benton, C. S., Miller, B. H., Skwerer, S., Suzuki, O., Schultz, L. E., Cameron, M. D., Marron, J. S., Pletcher, M. T., & Wiltshire, T. (2011) · Psychopharmacology · doi:10.1007/s00213-011-2574-z · Cited by 48 · see citing works
Cell population-specific expression analysis of human cerebellum
Kuhn, A., Kumar, A., Beilina, A. G., Dillman, A., Cookson, M., & Singleton, A. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-610 · Cited by 46 · see citing works
Parente, M. K., Rozen, R., Cearley, C. N., & Wolfe, J. H. N. (2012) · PLoS ONE · doi:10.1371/journal.pone.0032419 · Cited by 45 · see citing works
Analysis of Body-wide Unfractionated Tissue Data to Identify a Core Human Endothelial Transcriptome
Butler, L. M., Hallström, B. M., Fagerberg, L., Pontén, F., Uhlén, M., Renné, T., & Odeberg, J. (2016) · Cell Systems · doi:10.1016/j.cels.2016.08.001 · Cited by 43 · see citing works
Jiang, P., Scarpa, J. R., Fitzpatrick, K., Losic, B., Gao, V., Hao, K., Summa, K. C., Yang, H. S., Zhang, B., Allada, R., et al. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.04.003 · Cited by 40 · see citing works
Comt1 genotype and expression predicts anxiety and nociceptive sensitivity in inbred strains of mice
Segall, S. K., Nackley, A. G., Diatchenko, L. B., Lariviere, W. R., Lu, X., Marron, J. S., Grabowski-Boase, L., Walker, J. R., Slade, G. D., Gauthier, J., et al. (2010) · Genes Brain & Behavior · doi:10.1111/j.1601-183x.2010.00633.x · Cited by 37 · see citing works
Systematic analysis of gene expression in human brains before and after death
Franz, H., Ullmann, C., Becker, A. J., Ryan, M., Bahn, S., Arendt, T., Simon, M., Pääbo, S., & Khaitovich, P. (2005) · Genome biology · doi:10.1186/gb-2005-6-13-r112 · Cited by 36 · see citing works
A Self-Directed Method for Cell-Type Identification and Separation of Gene Expression Microarrays
Zuckerman, N. S., Noam, Y., Goldsmith, A. J., & Lee, P. P. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003189 · Cited by 33 · see citing works
Vanderlinden, L. A., Saba, L. M., Kechris, K. J., Miles, M. F., Hoffman, P. L., & Tabakoff, B. (2013) · PLoS ONE · doi:10.1371/journal.pone.0068878 · Cited by 30 · see citing works
A novel genetic locus modulates infarct volume independently of the extent of collateral circulation
Chu, P., Keum, S., & Marchuk, D. A. (2013) · Physiological Genomics · doi:10.1152/physiolgenomics.00063.2013 · Cited by 26 · see citing works
Kleiman, R. J., Lanz, T. A., Finley, J. E., Bove, S. E., Majchrzak, M. J., Becker, S. L., Carvajal‐Gonzalez, S., Kuhn, A. M., Wood, K. M., Mariga, A., et al. (2010) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2010.05.1922 · Cited by 15 · see citing works
Transcriptomics: From Differential Expression to Coexpression
Oldham, M. C. (2013) · Oxford University Press eBooks · doi:10.1093/med/9780199855452.003.0006 · Cited by 10 · see citing works
Self-citationBenoit, J. D., Ayoub, A. E., & RAKIC, P. T. (2015) · Brain Structure and Function · doi:10.1007/s00429-015-1138-0 · Cited by 3 · see citing works
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An atlas of the protein-coding genes in the human, pig, and mouse brain
Sjöstedt, E., Zhong, W., Fagerberg, L., Karlsson, M., Mitsios, N., Adori, C., Oksvold, P., Edfors, F., Limiszewska, A., Hikmet, F., et al. (2020) · Science · doi:10.1126/science.aay5947 · Cited by 1,151 · see citing works
Comprehensive functional genomic resource and integrative model for the human brain
Wang, D., Liu, S., Warrell, J., Won, H., Shi, X., Navarro, F. C. P., Clarke, D., Gu, M., Emani, P., Yang, Y. T., et al. (2018) · Science · doi:10.1126/science.aat8464 · Cited by 965 · see citing works
Tumor Cell Biodiversity Drives Microenvironmental Reprogramming in Liver Cancer
Ma, L., Hernandez, M. O., Zhao, Y., Mehta, M., Tran, B. Q., Kelly, M. C., Rae, Z., Hernandez, J. M., Davis, J. L., Martin, S. P., et al. (2019) · Cancer Cell · doi:10.1016/j.ccell.2019.08.007 · Cited by 847 · see citing works
Identification of region-specific astrocyte subtypes at single cell resolution
Batiuk, M. Y., Martirosyan, A., Wahis, J., de Vin, F., Marneffe, C., Kusserow, C., Koeppen, J., Viana, J. F., Oliveira, J. F., Voet, T., et al. (2020) · Nature Communications · doi:10.1038/s41467-019-14198-8 · Cited by 805 · see citing works
Microglial Remodeling of the Extracellular Matrix Promotes Synapse Plasticity
Nguyen, P. T., Dorman, L. C., Pan, S., Vainchtein, I. D., Han, R. T., Nakao-Inoue, H., Taloma, S. E., Barron, J. J., Molofsky, A. B., Kheirbek, M. A., et al. (2020) · Cell · doi:10.1016/j.cell.2020.05.050 · Cited by 615 · see citing works
Self-citationMolecular basis of astrocyte diversity and morphology across the CNS in health and disease
Endo, F., Kasai, A., Soto, J. S., Yu, X., Qu, Z., Hashimoto, H., Gradinaru, V., Kawaguchi, R., & Khakh, B. S. (2022) · Science · doi:10.1126/science.adc9020 · Cited by 560 · see citing works
Nagy, C., Maitra, M., Tanti, A., Suderman, M., Théroux, J.-F., Davoli, M. A., Perlman, K., Yerko, V., Wang, Y. C., Tripathy, S. J., et al. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0621-y · Cited by 532 · see citing works
The Emerging Nature of Astrocyte Diversity
Khakh, B. S., & Deneen, B. (2019) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-070918-050443 · Cited by 485 · see citing works
Astrocytes and microglia: In sickness and in health
Vainchtein, I. D., & Molofsky, A. V. (2020) · Trends in Neurosciences · doi:10.1016/j.tins.2020.01.003 · Cited by 450 · see citing works
Self-citationCrosstalk Between Astrocytes and Microglia: An Overview
Matejuk, A., & Ransohoff, R. M. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.01416 · Cited by 445 · see citing works
Hyperactivity with Disrupted Attention by Activation of an Astrocyte Synaptogenic Cue
Nagai, J., Rajbhandari, A. K., Gangwani, M. R., Hachisuka, A., Coppola, G., Masmanidis, S. C., Fanselow, M. S., & Khakh, B. S. (2019) · Cell · doi:10.1016/j.cell.2019.03.019 · Cited by 322 · see citing works
Behaviorally consequential astrocytic regulation of neural circuits
Nagai, J., Yu, X., Papouin, T., Cheong, E., Freeman, M. R., Monk, K. R., Hastings, M. H., Haydon, P. G., Rowitch, D. H., Shaham, S., et al. (2020) · Neuron · doi:10.1016/j.neuron.2020.12.008 · Cited by 311 · see citing works
Improved tools to study astrocytes
Yu, X., Nagai, J., & Khakh, B. S. (2020) · Nature Reviews Neuroscience · doi:10.1038/s41583-020-0264-8 · Cited by 298 · see citing works
Deep learning–based cell composition analysis from tissue expression profiles
Menden, K., Marouf, M., Oller, S., Dalmia, A., Magruder, D. S., Kloiber, K., Heutink, P., & Bonn, S. (2020) · Science Advances · doi:10.1126/sciadv.aba2619 · Cited by 258 · see citing works
Questions and (some) answers on reactive astrocytes
Escartin, C., Guillemaud, O., & Carrillo‐de Sauvage, M. (2019) · Glia · doi:10.1002/glia.23687 · Cited by 275 · see citing works
Glioblastoma evolution and heterogeneity from a 3D whole-tumor perspective
Mathur, R., Wang, Q., Schupp, P. G., Nikolić, A., Hilz, S., Hong, C., Grishanina, N. R., Kwok, D. W., Stevers, N. O., Jin, Q., et al. (2024) · Cell · doi:10.1016/j.cell.2023.12.013 · Cited by 243 · see citing works
Self-citationHuman brain organogenesis: Toward a cellular understanding of development and disease
Kelley, K. W., & Pașca, S. P. (2021) · Cell · doi:10.1016/j.cell.2021.10.003 · Cited by 233 · see citing works
Self-citationNeuroimmune signaling in alcohol use disorder
Erickson, E. K., Grantham, E. K., Warden, A. S., & Harris, R. A. (2018) · Pharmacology Biochemistry and Behavior · doi:10.1016/j.pbb.2018.12.007 · Cited by 224 · see citing works
Astrocyte-immune cell interactions in physiology and pathology
Han, R. T., Kim, R. D., Molofsky, A. V., & Liddelow, S. A. (2021) · Immunity · doi:10.1016/j.immuni.2021.01.013 · Cited by 223 · see citing works
Self-citationMicroenvironmental Regulation of Tumor Progression and Therapeutic Response in Brain Metastasis
Schulz, M., Salamero‐Boix, A., Niesel, K., Alekseeva, T., & Sevenich, L. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.01713 · Cited by 220 · see citing works
A single-nuclei RNA sequencing study of Mendelian and sporadic AD in the human brain
Del-Aguila, J. L., Li, Z., Dube, U., Mihindukulasuriya, K. A., Budde, J. P., Fernandez, M. V., Ibanez, L., Bradley, J., Wang, F., Bergmann, K., et al. (2019) · Alzheimer's Research & Therapy · doi:10.1186/s13195-019-0524-x · Cited by 183 · see citing works
Genetic mapping of etiologic brain cell types for obesity
Timshel, P. N., Thompson, J. J., & Pers, T. H. (2020) · eLife · doi:10.7554/elife.55851 · Cited by 194 · see citing works
Astrocyte morphogenesis is dependent on BDNF signaling via astrocytic TrkB.T1
Holt, L. M., Hernandez, R. D., Pacheco, N. L., Ceja, B. T., Hossain, M., & Olsen, M. L. (2019) · eLife · doi:10.7554/elife.44667 · Cited by 170 · see citing works
Molecular design of hypothalamus development
Romanov, R. A., Tretiakov, E. O., Kastriti, M. E., Zupančič, M., Häring, M., Korchynska, S., Popadin, K. Y., Benevento, M., Rebernik, P., Lallemend, F., et al. (2020) · Nature · doi:10.1038/s41586-020-2266-0 · Cited by 172 · see citing works
Molecular and cellular mechanisms underlying brain metastasis of breast cancer
Hosonaga, M., Saya, H., & Arima, Y. (2020) · Cancer and Metastasis Reviews · doi:10.1007/s10555-020-09881-y · Cited by 162 · see citing works
Leng, K., Rose, I. V. L., Kim, H., Xia, W., Romero‐Fernandez, W., Rooney, B., Koontz, M., Li, E., Ao, Y., Wang, S., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01180-9 · Cited by 154 · see citing works
Humphrey, J., Venkatesh, S., Hasan, R., Herb, J. T., de Paiva Lopes, K., Küçükali, F., Byrska-Bishop, M., Evani, U. S., Narzisi, G., Fagegaltier, D., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-022-01205-3 · Cited by 138 · see citing works
Sorrells, S., Paredes, M. F., Zhang, Z.-Z., Kang, G., Pastor-Alonso, O., Biagiotti, S., Page, C. E., Sandoval, K., Knox, A., Connolly, A., et al. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.0676-20.2020 · Cited by 112 · see citing works
Self-citationAstrocyte–neuron subproteomes and obsessive–compulsive disorder mechanisms
Soto, J. S., Jami‐Alahmadi, Y., Chacon, J., Moye, S. L., Castro, B. D., Wohlschlegel, J. A., & Khakh, B. S. (2023) · Nature · doi:10.1038/s41586-023-05927-7 · Cited by 132 · see citing works
Context-Specific Striatal Astrocyte Molecular Responses Are Phenotypically Exploitable
Yu, X., Nagai, J., Martí-Solano, M., Soto, J. S., Coppola, G., Babu, M. M., & Khakh, B. S. (2020) · Neuron · doi:10.1016/j.neuron.2020.09.021 · Cited by 121 · see citing works
Comprehensive evaluation of deconvolution methods for human brain gene expression
Sutton, G. J., Poppe, D., Simmons, R. K., Walsh, K., Nawaz, U., Lister, R., Gagnon-Bartsch, J. A., & Voineagu, I. (2022) · Nature Communications · doi:10.1038/s41467-022-28655-4 · Cited by 117 · see citing works
Single cell transcriptome profiling of the human alcohol-dependent brain
Brenner, E., Tiwari, G. R., Kapoor, M., Liu, Y., Brock, A., & Mayfield, R. D. (2020) · Human Molecular Genetics · doi:10.1093/hmg/ddaa038 · Cited by 118 · see citing works
Astrocyte–Neuron Interactions in the Striatum: Insights on Identity, Form, and Function
Khakh, B. S. (2019) · Trends in Neurosciences · doi:10.1016/j.tins.2019.06.003 · Cited by 112 · see citing works
Chamling, X., Kallman, A., Fang, W., Berlinicke, C. A., Mertz, J. L., Devkota, P., Pantoja, I. E. M., Smith, M. D., Ji, Z., Chang, C. K. W., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-20892-3 · Cited by 99 · see citing works
Romero-García, R., Seidlitz, J., Whitaker, K. J., Morgan, S. E., Fonagy, P., Dolan, R. J., Jones, P. B., Goodyer, I. M., John Suckling, A., Bullmore, E. T., et al. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.12.005 · Cited by 102 · see citing works
Primate cell fusion disentangles gene regulatory divergence in neurodevelopment
Agoglia, R. M., Sun, D., Birey, F., Yoon, S., Miura, Y., Sabatini, K., Pașca, S. P., & Fraser, H. B. (2021) · Nature · doi:10.1038/s41586-021-03343-3 · Cited by 102 · see citing works
Central Nervous System Responses to Simulated Galactic Cosmic Rays
Cekanaviciute, E., Rosi, S., & Costes, S. V. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19113669 · Cited by 99 · see citing works
Microglia and astrocyte involvement in neurodegeneration and brain cancer
Vandenbark, A. A., Offner, H., Matejuk, S., & Matejuk, A. (2021) · Journal of Neuroinflammation · doi:10.1186/s12974-021-02355-0 · Cited by 97 · see citing works
Ravi, V. M., Joseph, K., Wurm, J., Behringer, S. P., Garrelfs, N. W. C., d’Errico, P., Naseri, Y., Franco, P., Meyer‐Luehmann, M., Sankowski, R., et al. (2019) · Life Science Alliance · doi:10.26508/lsa.201900305 · Cited by 96 · see citing works
Rexach, J. E., Polioudakis, D., Yin, A., Swarup, V., Chang, T. S., Nguyen, T., Sarkar, A., Chen, L., Huang, J., Lin, L.-C., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108398 · Cited by 94 · see citing works
Glia in neurodegeneration: Drivers of disease or along for the ride?
Gleichman, A. J., & Carmichael, S. T. (2020) · Neurobiology of Disease · doi:10.1016/j.nbd.2020.104957 · Cited by 90 · see citing works
No Longer Underappreciated: The Emerging Concept of Astrocyte Heterogeneity in Neuroscience
Pestana, F., Edwards‐Faret, G., Belgard, T. G., Martirosyan, A., & Holt, M. G. (2020) · Brain Sciences · doi:10.3390/brainsci10030168 · Cited by 86 · see citing works
Turelli, P., Playfoot, C. J., Grun, D., Raclot, C., Pontis, J., Coudray, A., Thorball, C. W., Duc, J., Pankevich, E. V., Deplancke, B., et al. (2020) · Science Advances · doi:10.1126/sciadv.aba3200 · Cited by 81 · see citing works
Immune checkpoint TIM-3 regulates microglia and Alzheimer’s disease
Kimura, K., Subramanian, A., Yin, Z., Khalilnezhad, A., Wu, Y., He, D., Dixon, K. O., Chitta, U. K., Ding, X., Adhikari, N., et al. (2025) · Nature · doi:10.1038/s41586-025-08852-z · Cited by 85 · see citing works
Hartl, C., Ramaswami, G., Pembroke, W. G., Muller, S., Pintacuda, G., Saha, A., Parsana, P., Battle, A. J., Lage, K., & Geschwind, D. H. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00887-5 · Cited by 82 · see citing works
Galea, E., Weinstock, L. D., Larramona-Arcas, R., Pybus, A. F., Giménez-Llort, L., Escartin, C., & Wood, L. B. (2022) · Neurobiology of Disease · doi:10.1016/j.nbd.2022.105655 · Cited by 83 · see citing works
Evolutionary conservation and divergence of the human brain transcriptome
Pembroke, W. G., Hartl, C., & Geschwind, D. H. (2021) · Genome biology · doi:10.1186/s13059-020-02257-z · Cited by 78 · see citing works
Cross-Talk of the CNS With Immune Cells and Functions in Health and Disease
Matejuk, A., Vandenbark, A. A., & Offner, H. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.672455 · Cited by 79 · see citing works
Diagnostic blood RNA profiles for human acute spinal cord injury
Kyritsis, N., Espin, A. T., Schupp, P. G., Huie, J. R., Chou, A., Fernandez, X. D., Thomas, L. H., Tsolinas, R. E., Hemmerle, D. D., Pascual, L. U., et al. (2020) · The Journal of Experimental Medicine · doi:10.1084/jem.20201795 · Cited by 80 · see citing works
Self-citationMérienne, N., Meunier, C., Schneider‐Anthony, A., Séguin, J., Nair, S. S., Rocher, A. B., Gras, S. L., Keime, C., Faull, R. L. M., Pellerin, L., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.02.003 · Cited by 72 · see citing works
An update on human astrocytes and their role in development and disease
de Majo, M., Koontz, M., Rowitch, D. H., & Ullian, E. M. (2020) · Glia · doi:10.1002/glia.23771 · Cited by 66 · see citing works
Common gene expression signatures in Parkinson’s disease are driven by changes in cell composition
Nido, G. S., Dick, F., Toker, L., Petersen, K., Alves, G. W., Tysnes, O., Jonassen, I., Haugarvoll, K., & Tzoulis, C. (2020) · Acta Neuropathologica Communications · doi:10.1186/s40478-020-00932-7 · Cited by 66 · see citing works
Mencacci, N. E., Reynolds, R. H., García-Ruiz, S., Vandrovcová, J., Forabosco, P., Sánchez‐Ferrer, Á., Volpato, V., Botía, J. A., D’Sa, K., Forabosco, P., et al. (2020) · Brain · doi:10.1093/brain/awaa217 · Cited by 64 · see citing works
A systems‐level analysis highlights microglial activation as a modifying factor in common epilepsies
Altmann, A., Ryten, M., Nunzio, M. D., Ravizza, T., Tolomeo, D., Reynolds, R. H., Somani, A., Bacigaluppi, M., Iori, V., Micotti, E., et al. (2021) · Neuropathology and Applied Neurobiology · doi:10.1111/nan.12758 · Cited by 58 · see citing works
Transcriptomic Insight Into the Polygenic Mechanisms Underlying Psychiatric Disorders
Hernandez, L. M., Kim, M., Hoftman, G. D., Haney, J. R., de la Torre-Ubieta, L., Paşaniuc, B., & Gandal, M. J. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.06.005 · Cited by 57 · see citing works
Foundations and implications of astrocyte heterogeneity during brain development and disease
Schober, A. L., Wicki‐Stordeur, L. E., Murai, K. K., & Swayne, L. A. (2022) · Trends in Neurosciences · doi:10.1016/j.tins.2022.06.009 · Cited by 60 · see citing works
Depalmitoylation by Palmitoyl-Protein Thioesterase 1 in Neuronal Health and Degeneration
Koster, K. P., & Yoshii, A. (2019) · Frontiers in Synaptic Neuroscience · doi:10.3389/fnsyn.2019.00025 · Cited by 55 · see citing works
Lozano, D. C., Choe, T. E., Cepurna, W. O., Morrison, J., & Johnson, E. (2019) · Investigative Ophthalmology and Visual Science · doi:10.1167/iovs.18-25700 · Cited by 56 · see citing works
Omics-based biomarkers discovery for Alzheimer's disease
Aerqin, Q., Wang, Z.-T., Wu, K., He, X., Dong, Q., & Yu, J. (2022) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-022-04614-6 · Cited by 55 · see citing works
Limone, F., Mordes, D. A., Couto, A., Joseph, B. J., Mitchell, J. M., Therrien, M., Ghosh, S. D., Meyer, D., Zhang, Y., Goldman, M., et al. (2024) · Nature Aging · doi:10.1038/s43587-024-00640-0 · Cited by 54 · see citing works
Activated microglia facilitate the transmission of α-synuclein in Parkinson's disease
Zheng, T., & Zhang, Z. (2021) · Neurochemistry International · doi:10.1016/j.neuint.2021.105094 · Cited by 53 · see citing works
Enhancing GAT-3 in thalamic astrocytes promotes resilience to brain injury in rodents
Cho, F. S., Vainchtein, I. D., Voskobiynyk, Y., Morningstar, A. R., Aparicio, F., Higashikubo, B. T., Ciesielska, A., Broekaart, D. W. M., Anink, J. J., van Vliet, E. A., et al. (2022) · Science Translational Medicine · doi:10.1126/scitranslmed.abj4310 · Cited by 55 · see citing works
Self-citationNests of dividing neuroblasts sustain interneuron production for the developing human brain
Paredes, M. F., Mora, C., Flores-Ramirez, Q., Cebrián‐Silla, A., Dosso, A. D., Larimer, P., Chen, J., Kang, G., González-Granero, S., Garcia, E., et al. (2022) · Science · doi:10.1126/science.abk2346 · Cited by 50 · see citing works
Self-citationTumor Immune Microenvironment of Brain Metastases: Toward Unlocking Antitumor Immunity
Strickland, M. R., Alvarez-Breckenridge, C. A., Gainor, J. F., & Brastianos, P. K. (2022) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-0976 · Cited by 51 · see citing works
Human Astrocytes Exhibit Tumor Microenvironment-, Age-, and Sex-Related Transcriptomic Signatures
Krawczyk, M. C., Haney, J. R., Pan, L., Caneda, C., Khankan, R. R., Reyes, S. D., Chang, J. W., Morselli, M., Vinters, H. V., Wang, A., et al. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.0407-21.2021 · Cited by 50 · see citing works
Employing core regulatory circuits to define cell identity
Almeida, N., Chung, M. W. H., Drudi, E. M., Engquist, E. N., Hamrud, E., Isaacson, A., Tsang, V. S. K., Watt, F. M., & Spagnoli, F. M. (2021) · The EMBO Journal · doi:10.15252/embj.2020106785 · Cited by 49 · see citing works
Physiological and Epigenetic Features of Yoyo Dieting and Weight Control
Contreras, R. E., Schriever, S. C., & Pfluger, P. T. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.01015 · Cited by 52 · see citing works
Cross-disorder and disease-specific pathways in dementia revealed by single-cell genomics
Rexach, J. E., Cheng, Y., Chen, L., Polioudakis, D., Lin, L., Mitri, V., Elkins, A., Han, X., Yamakawa, M., Yin, A., et al. (2024) · Cell · doi:10.1016/j.cell.2024.08.019 · Cited by 56 · see citing works
Untangling the effects of cellular composition on coexpression analysisPreprint
Farahbod, M., & Pavlidis, P. (2020) · Genome Research · doi:10.1101/gr.256735.119 · Cited by 46 · see citing works
Granulin loss of function in human mature brain organoids implicates astrocytes in TDP-43 pathology
de Majo, M., Koontz, M., Marsan, E., Salinas, N., Ramsey, A., Kuo, Y.-M., Seo, K., Li, H., Dräger, N., Leng, K., et al. (2023) · Stem Cell Reports · doi:10.1016/j.stemcr.2023.01.012 · Cited by 44 · see citing works
FAIR SCI Ahead: The Evolution of the Open Data Commons for Pre-Clinical Spinal Cord Injury Research
Fouad, K., Bixby, J. L., Callahan, A., Grethe, J. S., Jakeman, L. B., Lemmon, V., Magnuson, D. S. K., Martone, M. E., Nielson, J. L., Schwab, J. M., et al. (2019) · Journal of Neurotrauma · doi:10.1089/neu.2019.6674 · Cited by 40 · see citing works
Tutorial: Guidelines for Single-Cell RT-qPCR
Žucha, D., Kubista, M., & Valihrach, L. (2021) · Cells · doi:10.3390/cells10102607 · Cited by 39 · see citing works
Harris, B. D., Crow, M., Fischer, S., & Gillis, J. A. (2021) · Cell Systems · doi:10.1016/j.cels.2021.04.010 · Cited by 38 · see citing works
Regional transcriptional architecture of Parkinson’s disease pathogenesis and network spread
Freeze, B. S., Pandya, S., Zeighami, Y., & Raj, A. (2019) · Brain · doi:10.1093/brain/awz223 · Cited by 33 · see citing works
Challenges and Opportunities of Targeting Astrocytes to Halt Neurodegenerative Disorders
Valori, C. F., Possenti, A., Brambilla, L., & Rossi, D. (2021) · Cells · doi:10.3390/cells10082019 · Cited by 37 · see citing works
Solomon‐Lane, T. K., & Hofmann, H. A. (2019) · Hormones and Behavior · doi:10.1016/j.yhbeh.2019.06.016 · Cited by 34 · see citing works
Satoh, M., Nomura, S., Harada, M., Yamaguchi, T., Ko, T., Sumida, T. S., Toko, H., Naito, A. T., Takeda, N., Tobita, T., et al. (2019) · Journal of Molecular and Cellular Cardiology · doi:10.1016/j.yjmcc.2018.12.018 · Cited by 34 · see citing works
Dusart, P., Hallström, B. M., Renné, T., Odeberg, J., Uhlén, M., & Butler, L. M. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.09.088 · Cited by 34 · see citing works
Northcutt, A. J., Kick, D. R., Otopalik, A. G., Goetz, B. M., Harris, R. M., Santin, J. M., Hofmann, H. A., Marder, E., & Schulz, D. J. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1911413116 · Cited by 33 · see citing works
The heterogeneity of astrocytes in glaucoma
Tang, Y., Chen, Y., & Chen, D. (2022) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2022.995369 · Cited by 33 · see citing works
Identification of cell-type-specific marker genes from co-expression patterns in tissue samples
Qiu, Y., Wang, J., Lei, J., & Roeder, K. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab257 · Cited by 32 · see citing works
Glial ER and GAP junction mediated Ca2+ waves are crucial to maintain normal brain excitability
Weiss, S., Clamon, L. C., Manoim, J. E., Ormerod, K. G., Parnas, M., & Littleton, J. T. (2021) · Glia · doi:10.1002/glia.24092 · Cited by 31 · see citing works
Zhan, T., Tang, S., Du, J., Liu, J., Yu, B., Yang, Y., Xie, Y., Qiu, Y., Li, G., & Gao, Y. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25021186 · Cited by 30 · see citing works
Assessing Gq-GPCR–induced human astrocyte reactivity using bioengineered neural organoids
Cvetkovic, C., Patel, R., Shetty, A. J., Hogan, M., Anderson, M., Basu, N., Aghlara-Fotovat, S., Ramesh, S., Sardar, D., Omid Veiseh, A., et al. (2022) · The Journal of Cell Biology · doi:10.1083/jcb.202107135 · Cited by 29 · see citing works
Using multiple measurements of tissue to estimate subject- and cell-type-specific gene expression
Wang, J., Devlin, B., & Roeder, K. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz619 · Cited by 30 · see citing works
Schneider, A. L., Martins-Silva, R., Kaizeler, A., Saraiva-Agostinho, N., & Barbosa‐Morais, N. L. (2023) · eLife · doi:10.7554/elife.88623 · Cited by 29 · see citing works
Mazumder, A. G., Julé, A. M., Cullen, P. F., & Sun, D. (2022) · iScience · doi:10.1016/j.isci.2022.105568 · Cited by 26 · see citing works
Transcriptional cartography integrates multiscale biology of the human cortex
Wagstyl, K., Adler, S., Seidlitz, J., Vandekar, S., Mallard, T. T., Dear, R., DeCasien, A. R., Satterthwaite, T. D., Liu, S., Vértes, P. E., et al. (2024) · eLife · doi:10.7554/elife.86933.3 · Cited by 26 · see citing works
Understanding Molecular Mechanisms of the Brain Through Transcriptomics
Wang, W., & Wang, G. (2019) · Frontiers in Physiology · doi:10.3389/fphys.2019.00214 · Cited by 25 · see citing works
Wang, N., Langfelder, P., Stricos, M., Ramanathan, L., Richman, J., Vaca, R., Plascencia, M., Gu, X., Zhang, S., Tamai, K. T., et al. (2022) · Neuron · doi:10.1016/j.neuron.2022.09.028 · Cited by 25 · see citing works
On astrocyte-neuron interactions: broad insights from the striatum
Khakh, B. S. (2025) · Neuron · doi:10.1016/j.neuron.2025.08.009 · Cited by 23 · see citing works
Li, J., Pan, L., Godoy, M. I., Pembroke, W. G., Rexach, J. E., Condro, M. C., Alvarado, A. G., Harteni, M., Chen, Y.-W., Stiles, L., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.17.044222 · Cited by 23 · see citing works
Huang, Y., Liu, H., Hu, J., Han, C., Zhong, Z., Luo, W., Zhang, Y., & Ling, F. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.686066 · Cited by 20 · see citing works
Romero-García, R., Hook, R. W., Tiego, J., Bethlehem, R. A. I., Goodyer, I. M., Jones, P. B., Dolan, R. J., Grant, J. E., Bullmore, E. T., Yücel, M., et al. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-00848-9 · Cited by 19 · see citing works
Transcriptional cartography integrates multiscale biology of the human cortex
Wagstyl, K., Adler, S., Seidlitz, J., Vandekar, S., Mallard, T. T., Dear, R., DeCasien, A. R., Satterthwaite, T. D., Liu, S., Vértes, P. E., et al. (2023) · eLife · doi:10.7554/elife.86933 · Cited by 42 · see citing works
Gedik, H., Nguyen, T. H., Peterson, R. E., Chatzinakos, C., Riley, B. P., Vladimirov, V. I., & Bacanu, S. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1191264 · Cited by 16 · see citing works
Spatial transcriptomic analysis of adult hippocampal neurogenesis in the human brain
Simard, S., Rahimian, R., Davoli, M., Théberge, S., Matosin, N., Turecki, G., Nagy, C., & Mechawar, N. (2023) · bioRxiv · doi:10.1503/jpn.240026 · Cited by 19 · see citing works
CRISPRi screens in human astrocytes elucidate regulators of distinct inflammatory reactive statesPreprint
Leng, K., Rose, I. V. L., Kim, H., Xia, W., Romero‐Fernandez, W., Rooney, B., Koontz, M., Li, E., Ao, Y., Wang, S., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.08.23.457400 · Cited by 18 · see citing works
Wu, L., Pandey, V., Hull, V. L., Qu, Z., Jami‐Alahmadi, Y., Gradinaru, V., Wohlschlegel, J. A., & Khakh, B. S. (2025) · Neuron · doi:10.1016/j.neuron.2025.05.019 · Cited by 18 · see citing works
PMP2 regulates myelin thickening and ATP production during remyelination
Hong, J., Garfolo, R., Kabre, S., Humml, C., Velanac, V., Roué, C., Beck, B., Jeanette, H., Haslam, S., Bach, M. D., et al. (2024) · Glia · doi:10.1002/glia.24508 · Cited by 17 · see citing works
- Authors
- Kelley, K. W., Nakao-Inoue, H., Molofsky, A. V., & Oldham, M. C.
- Affiliations
- University of California, San Francisco (US)
- Corresponding author
- Oldham, Michael C.
- Venue
- Nature Neuroscience
- Published
- 2018-08-28
- Volume
- 21
- Issue
- 9
- Pages
- 1171-1184
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC6192711
- OpenAlex
- W2951890520
- Cited by
- 198
- References
- 109
- Citations by year
- 2026: 10 · 2025: 12 · 2024: 22 · 2023: 30 · 2022: 26 · 2021: 26 · 2020: 35 · 2019: 29 · 2018: 7
- FWCI
- 8.62
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nc-nd
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Sandler Foundation
- University of California, San Francisco
- National Institute of Mental Health (K08MH104417, R01MH113896, DP2MH116507)
- National Institute of General Medical Sciences (T32GM007618)
- Weill Institute for Neurosciences, University of California, San Francisco
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- astrocytes, Alzheimer's disease, regional brain differences, cross-species comparison, gene expression deconvolution, cell identity
- MeSH terms
- Alzheimer Disease, Animals, Astrocytes, Brain, Central Nervous System, Humans, Models, Genetic, Transcription, Genetic, Sequence Analysis, RNA, Myelin P2 Protein, Gene Expression Profiling, Databases, Genetic, Cell Size, Mice, Transcriptome
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