Literature DB >> 31515224

Loss of DNA methyltransferase activity in primed human ES cells triggers increased cell-cell variability and transcriptional repression.

Alexander M Tsankov1,2, Marc H Wadsworth2,3,4, Veronika Akopian5, Jocelyn Charlton5,6, Samuel J Allon2,3,4, Aleksandra Arczewska5,6, Benjamin E Mead2,3,4, Riley S Drake2,3,4, Zachary D Smith5, Tarjei S Mikkelsen7, Alex K Shalek8,3,4, Alexander Meissner8,5,6.   

Abstract

Maintenance of pluripotency and specification towards a new cell fate are both dependent on precise interactions between extrinsic signals and transcriptional and epigenetic regulators. Directed methylation of cytosines by the de novo methyltransferases DNMT3A and DNMT3B plays an important role in facilitating proper differentiation, whereas DNMT1 is essential for maintaining global methylation levels in all cell types. Here, we generated single-cell mRNA expression data from wild-type, DNMT3A, DNMT3A/3B and DNMT1 knockout human embryonic stem cells and observed a widespread increase in cellular and transcriptional variability, even with limited changes in global methylation levels in the de novo knockouts. Furthermore, we found unexpected transcriptional repression upon either loss of the de novo methyltransferase DNMT3A or the double knockout of DNMT3A/3B that is further propagated upon differentiation to mesoderm and ectoderm. Taken together, our single-cell RNA-sequencing data provide a high-resolution view into the consequences of depleting the three catalytically active DNMTs in human pluripotent stem cells.
© 2019. Published by The Company of Biologists Ltd.

Entities:  

Keywords:  DNA methylation; DNA methyltransferases; Pluripotency; Single-cell RNA-sequencing

Mesh:

Substances:

Year:  2019        PMID: 31515224      PMCID: PMC6803377          DOI: 10.1242/dev.174722

Source DB:  PubMed          Journal:  Development        ISSN: 0950-1991            Impact factor:   6.868


  50 in total

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2.  Diffusion maps for high-dimensional single-cell analysis of differentiation data.

Authors:  Laleh Haghverdi; Florian Buettner; Fabian J Theis
Journal:  Bioinformatics       Date:  2015-05-21       Impact factor: 6.937

3.  Mutational analysis of DNMT3A gene in acute leukemias and common solid cancers.

Authors:  Min S Kim; Yoo R Kim; Nam J Yoo; Sug H Lee
Journal:  APMIS       Date:  2012-07-03       Impact factor: 3.205

4.  Tracing the derivation of embryonic stem cells from the inner cell mass by single-cell RNA-Seq analysis.

Authors:  Fuchou Tang; Catalin Barbacioru; Siqin Bao; Caroline Lee; Ellen Nordman; Xiaohui Wang; Kaiqin Lao; M Azim Surani
Journal:  Cell Stem Cell       Date:  2010-05-07       Impact factor: 24.633

5.  Transcriptional and epigenetic dynamics during specification of human embryonic stem cells.

Authors:  Casey A Gifford; Michael J Ziller; Hongcang Gu; Cole Trapnell; Julie Donaghey; Alexander Tsankov; Alex K Shalek; David R Kelley; Alexander A Shishkin; Robbyn Issner; Xiaolan Zhang; Michael Coyne; Jennifer L Fostel; Laurie Holmes; Jim Meldrim; Mitchell Guttman; Charles Epstein; Hongkun Park; Oliver Kohlbacher; John Rinn; Andreas Gnirke; Eric S Lander; Bradley E Bernstein; Alexander Meissner
Journal:  Cell       Date:  2013-05-09       Impact factor: 41.582

Review 6.  Scaling single-cell genomics from phenomenology to mechanism.

Authors:  Amos Tanay; Aviv Regev
Journal:  Nature       Date:  2017-01-18       Impact factor: 49.962

7.  Targeted disruption of DNMT1, DNMT3A and DNMT3B in human embryonic stem cells.

Authors:  Jing Liao; Rahul Karnik; Hongcang Gu; Michael J Ziller; Kendell Clement; Alexander M Tsankov; Veronika Akopian; Casey A Gifford; Julie Donaghey; Christina Galonska; Ramona Pop; Deepak Reyon; Shengdar Q Tsai; William Mallard; J Keith Joung; John L Rinn; Andreas Gnirke; Alexander Meissner
Journal:  Nat Genet       Date:  2015-03-30       Impact factor: 38.330

8.  Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics.

Authors:  Kelly Street; Davide Risso; Russell B Fletcher; Diya Das; John Ngai; Nir Yosef; Elizabeth Purdom; Sandrine Dudoit
Journal:  BMC Genomics       Date:  2018-06-19       Impact factor: 3.969

9.  Molecular recording of mammalian embryogenesis.

Authors:  Michelle M Chan; Zachary D Smith; Stefanie Grosswendt; Helene Kretzmer; Thomas M Norman; Britt Adamson; Marco Jost; Jeffrey J Quinn; Dian Yang; Matthew G Jones; Alex Khodaverdian; Nir Yosef; Alexander Meissner; Jonathan S Weissman
Journal:  Nature       Date:  2019-05-13       Impact factor: 49.962

10.  Single-cell RNA-seq reveals dynamic paracrine control of cellular variation.

Authors:  Alex K Shalek; Rahul Satija; Joe Shuga; John J Trombetta; Dave Gennert; Diana Lu; Peilin Chen; Rona S Gertner; Jellert T Gaublomme; Nir Yosef; Schraga Schwartz; Brian Fowler; Suzanne Weaver; Jing Wang; Xiaohui Wang; Ruihua Ding; Raktima Raychowdhury; Nir Friedman; Nir Hacohen; Hongkun Park; Andrew P May; Aviv Regev
Journal:  Nature       Date:  2014-06-11       Impact factor: 49.962

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  5 in total

1.  Donor T cell DNMT3a regulates alloreactivity in mouse models of hematopoietic stem cell transplantation.

Authors:  Yiouli P Ktena; Michael A Koldobskiy; Michael I Barbato; Han-Hsuan Fu; Leo Luznik; Nicolas J Llosa; Azeb Haile; Orly R Klein; Chen Liu; Christopher J Gamper; Kenneth R Cooke
Journal:  J Clin Invest       Date:  2022-07-01       Impact factor: 19.456

2.  Multi-tissue DNA methylation microarray signature is predictive of gene function.

Authors:  Xiavan Renaldo Roopnarinesingh; Hunter Porter; Cory Giles; Chase Brown; Constantin Georgescu; Jonathan Wren
Journal:  Epigenetics       Date:  2022-02-13       Impact factor: 4.861

Review 3.  Smart-RRBS for single-cell methylome and transcriptome analysis.

Authors:  Hongcang Gu; Ayush T Raman; Xiaoxue Wang; Federico Gaiti; Ronan Chaligne; Arman W Mohammad; Aleksandra Arczewska; Zachary D Smith; Dan A Landau; Martin J Aryee; Alexander Meissner; Andreas Gnirke
Journal:  Nat Protoc       Date:  2021-07-09       Impact factor: 13.491

4.  Hydrogen sulfide facilitates reprogramming and trans-differentiation in 3D dermal fibroblast.

Authors:  Elena A Ostrakhovitch; Shin Akakura; Siamak Tabibzadeh
Journal:  PLoS One       Date:  2020-11-12       Impact factor: 3.240

5.  Estimating DNA methylation potential energy landscapes from nanopore sequencing data.

Authors:  Jordi Abante; Sandeep Kambhampati; Andrew P Feinberg; John Goutsias
Journal:  Sci Rep       Date:  2021-11-03       Impact factor: 4.379

  5 in total

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