Coordinated changes in gene expression kinetics underlie both mouse and human erythroid maturation

被引:34
作者
Barile, Melania [1 ,2 ]
Imaz-Rosshandler, Ivan [1 ,2 ]
Inzani, Isabella [3 ,4 ]
Ghazanfar, Shila [5 ]
Nichols, Jennifer [2 ,6 ]
Marioni, John C. [5 ,7 ,8 ]
Guibentif, Carolina [1 ,2 ,9 ]
Gottgens, Berthold [1 ,2 ]
机构
[1] Univ Cambridge, Dept Haematol, Cambridge CB2 0AW, England
[2] Univ Cambridge, Wellcome Med Res Council Cambridge Stem Cell Inst, Cambridge CB2 0AW, England
[3] Univ Cambridge, Metab Res Labs, Cambridge CB2 0QQ, England
[4] Univ Cambridge, MRC Metab Dis Unit, Cambridge CB2 0QQ, England
[5] Univ Cambridge, Canc Res UK Cambridge Inst, Cambridge CB2 0RE, England
[6] Univ Cambridge, Dept Physiol Dev & Neurosci, Cambridge CB2 3DY, England
[7] Wellcome Sanger Inst, Wellcome Genome Campus, Cambridge CB10 1SA, England
[8] European Bioinformat Inst EMBL EBI, European Mol Biol Lab, Wellcome Genome Campus, Cambridge CB10 1SD, England
[9] Univ Gothenburg, Sahlgrenska Ctr Canc Res, Dept Microbiol & Immunol, S-41390 Gothenburg, Sweden
基金
英国惠康基金; 瑞典研究理事会; 英国医学研究理事会;
关键词
RNA velocity; Gastrulation; Erythropoiesis; Gata1; TRANSCRIPTION FACTOR GATA-1; INTRON RETENTION PROGRAM; GLOBIN GENE; DOWN-SYNDROME; MEGAKARYOCYTE; PROTEIN; CELLS; DIFFERENTIATION; IDENTIFICATION; LANDSCAPE;
D O I
10.1186/s13059-021-02414-y
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background Single-cell technologies are transforming biomedical research, including the recent demonstration that unspliced pre-mRNA present in single-cell RNA-Seq permits prediction of future expression states. Here we apply this RNA velocity concept to an extended timecourse dataset covering mouse gastrulation and early organogenesis. Results Intriguingly, RNA velocity correctly identifies epiblast cells as the starting point, but several trajectory predictions at later stages are inconsistent with both real-time ordering and existing knowledge. The most striking discrepancy concerns red blood cell maturation, with velocity-inferred trajectories opposing the true differentiation path. Investigating the underlying causes reveals a group of genes with a coordinated step-change in transcription, thus violating the assumptions behind current velocity analysis suites, which do not accommodate time-dependent changes in expression dynamics. Using scRNA-Seq analysis of chimeric mouse embryos lacking the major erythroid regulator Gata1, we show that genes with the step-changes in expression dynamics during erythroid differentiation fail to be upregulated in the mutant cells, thus underscoring the coordination of modulating transcription rate along a differentiation trajectory. In addition to the expected block in erythroid maturation, the Gata1-chimera dataset reveals induction of PU.1 and expansion of megakaryocyte progenitors. Finally, we show that erythropoiesis in human fetal liver is similarly characterized by a coordinated step-change in gene expression. Conclusions By identifying a limitation of the current velocity framework coupled with in vivo analysis of mutant cells, we reveal a coordinated step-change in gene expression kinetics during erythropoiesis, with likely implications for many other differentiation processes.
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页数:22
相关论文
共 61 条
[1]   Aging, Clonality, and Rejuvenation of Hematopoietic Stem Cells [J].
Akunuru, Shailaja ;
Geiger, Hartmut .
TRENDS IN MOLECULAR MEDICINE, 2016, 22 (08) :701-712
[2]   MOFA plus : a statistical framework for comprehensive integration of multi-modal single-cell data [J].
Argelaguet, Ricard ;
Arnol, Damien ;
Bredikhin, Danila ;
Deloro, Yonatan ;
Velten, Britta ;
Marioni, John C. ;
Stegle, Oliver .
GENOME BIOLOGY, 2020, 21 (01)
[3]   Gene Ontology: tool for the unification of biology [J].
Ashburner, M ;
Ball, CA ;
Blake, JA ;
Botstein, D ;
Butler, H ;
Cherry, JM ;
Davis, AP ;
Dolinski, K ;
Dwight, SS ;
Eppig, JT ;
Harris, MA ;
Hill, DP ;
Issel-Tarver, L ;
Kasarskis, A ;
Lewis, S ;
Matese, JC ;
Richardson, JE ;
Ringwald, M ;
Rubin, GM ;
Sherlock, G .
NATURE GENETICS, 2000, 25 (01) :25-29
[4]  
Barile M, 2021, COORDINATED CHANGES
[5]  
Barile M, GSE167576 GEN EXPR O
[6]  
Barile M, COORDINATED CHANGES, DOI [10.5281/zenodo.4954417(2021, DOI 10.5281/ZENODO.4954417(2021]
[7]   Generalizing RNA velocity to transient cell states through dynamical modeling [J].
Bergen, Volker ;
Lange, Marius ;
Peidli, Stefan ;
Wolf, F. Alexander ;
Theis, Fabian J. .
NATURE BIOTECHNOLOGY, 2020, 38 (12) :1408-1414
[8]   Transient Abnormal Myelopoiesis and AML in Down Syndrome: an Update [J].
Bhatnagar, Neha ;
Nizery, Laure ;
Tunstall, Oliver ;
Vyas, Paresh ;
Roberts, Irene .
CURRENT HEMATOLOGIC MALIGNANCY REPORTS, 2016, 11 (05) :333-341
[9]   Single-Cell Profiling Shows Murine Forebrain Neural Stem Cells Reacquire a Developmental State when Activated for Adult Neurogenesis [J].
Borrett, Michael J. ;
Innes, Brendan T. ;
Jeong, Danielle ;
Tahmasian, Nareh ;
Storer, Mekayla A. ;
Bader, Gary D. ;
Kaplan, David R. ;
Miller, Freda D. .
CELL REPORTS, 2020, 32 (06)
[10]   The Gene Ontology Resource: 20 years and still GOing strong [J].
Carbon, S. ;
Douglass, E. ;
Dunn, N. ;
Good, B. ;
Harris, N. L. ;
Lewis, S. E. ;
Mungall, C. J. ;
Basu, S. ;
Chisholm, R. L. ;
Dodson, R. J. ;
Hartline, E. ;
Fey, P. ;
Thomas, P. D. ;
Albou, L. P. ;
Ebert, D. ;
Kesling, M. J. ;
Mi, H. ;
Muruganujian, A. ;
Huang, X. ;
Poudel, S. ;
Mushayahama, T. ;
Hu, J. C. ;
LaBonte, S. A. ;
Siegele, D. A. ;
Antonazzo, G. ;
Attrill, H. ;
Brown, N. H. ;
Fexova, S. ;
Garapati, P. ;
Jones, T. E. M. ;
Marygold, S. J. ;
Millburn, G. H. ;
Rey, A. J. ;
Trovisco, V. ;
dos Santos, G. ;
Emmert, D. B. ;
Falls, K. ;
Zhou, P. ;
Goodman, J. L. ;
Strelets, V. B. ;
Thurmond, J. ;
Courtot, M. ;
Osumi-Sutherland, D. ;
Parkinson, H. ;
Roncaglia, P. ;
Acencio, M. L. ;
Kuiper, M. ;
Laegreid, A. ;
Logie, C. ;
Lovering, R. C. .
NUCLEIC ACIDS RESEARCH, 2019, 47 (D1) :D330-D338