CoChat
Sign Up
Cited by 51Pluripotent Stem Cells ResearchSingle-cell and spatial transcriptomicsGenomics and Chromatin Dynamics

Diversification of reprogramming trajectories revealed by parallel single-cell transcriptome and chromatin accessibility sequencing

Open access
Xing, Q. R., El Farran, C. A., Gautam, P., Chuah, Y. S., Warrier, T., Toh, C. X. D., Kang, N. Y., Sugii, S. +7 more·2020·Science Advances
DOI 10.1126/sciadv.aba1190PMC PMC7486102

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

Integrative single-cell analysis de-constructs the heterogeneity of human reprogramming and uncovers its stage-specific GRNs.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1126/sciadv.aba1190

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Cells which do not progress to the iPSC state bifurcate into an alternative fate compared to cells that progress to the iPSC state after the day 12 stage.

    “Cell embeddings suggested that cells which do not progress to the iPSC state bifurcate into an alternative fate compared to cells that progress to the iPSC state after the day 12 stage.”

    From Transfer learning enables predictions in network biology (2023) · cites this paper as [15]

    The Results section on pseudotemporal trajectories reports branching paths and distinguishes a non-reprogrammed state 8 from a successfully reprogrammed state 9. It also places unsuccessful and successful subgroups as early as day 8, so the copy does not establish that the bifurcation occurs after day 12. Page numbers are unavailable in the indexed copy. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • Pretrained Geneformer cell embeddings of cells undergoing iPSC reprogramming appropriately captured the temporal trajectory of reprogramming.

    “UMAP of pretrained Geneformer cell embeddings of cells undergoing iPSC reprogramming appropriately captured temporal trajectory of reprogramming”

    From Transfer learning enables predictions in network biology (2023) · cites this paper as [15]

    The Results section (‘Single-cell profiling of human cell fate reprogramming’; page unavailable) reports that UMAP clustering showed a dynamic transition from parental cells to successfully reprogrammed cells. The source thus supports the temporal reprogramming pattern, but it does not report an analysis of pretrained Geneformer cell embeddings or establish that those embeddings captured it. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

  • In silico reprogramming fibroblasts by artificially adding OCT4, SOX2, KLF4, and MYC to the front of their rank value encodings significantly shifted the remaining genes in the transcriptome's embedding towards the iPSC state.

    “When we in silico reprogrammed fibroblasts15 by artificially adding OCT4, SOX2, KLF4, and MYC to the front of their rank value encodings, the remaining genes in the transcriptome significantly shifted their embedding towards the iPSC state (Extended Data Fig. 2b–c).”

    From Transfer learning enables predictions in network biology (2023) · cites this paper as [15]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 37

  1. [1]Takahashi K., Tanabe K., Ohnuki M., Narita M., Ichisaka T., Tomoda K., Yamanaka S., Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell 131, 861– 872 (2007). 18035408
  2. [2]Seah Y. F. S., El Farran C. A., Warrier T., Xu J., Loh Y.-H., Induced pluripotency and gene editing in disease modelling: Perspectives and challenges. Int. J. Mol. Sci. 16, 28614– 28634 (2015). 26633382 PMC4691066
  3. [3]Cheow L. F., Courtois E. T., Tan Y., Viswanathan R., Xing Q., Tan R. Z., Tan D. S. W., Robson P., Loh Y.-H., Quake S. R., Burkholder W. F., Single-cell multimodal profiling reveals cellular epigenetic heterogeneity. Nat. Methods 13, 833– 836 (2016). 27525975
  4. [4]Stadtfeld M., Hochedlinger K., Induced pluripotency: History, mechanisms, and applications. Genes Dev. 24, 2239– 2263 (2010). 20952534 PMC2956203
  5. [5]Qin H., Diaz A., Blouin L., Lebbink R. J., Patena W., Tanbun P., LeProust E. M., McManus M. T., Song J. S., Ramalho-Santos M., Systematic identification of barriers to human iPSC generation. Cell 158, 449– 461 (2014). 25036638 PMC4130998
  6. [6]Toh C.-X. D., Chan J.-W., Chong Z.-S., Wang H. F., Guo H. C., Satapathy S., Ma D., Goh G. Y. L., Khattar E., Yang L., Tergaonkar V., Chang Y.-T., Collins J. J., Daley G. Q., Wee K. B., Farran C. A. E., Li H., Lim Y.-P., Bard F. A., Loh Y.-H., RNAi reveals phase-specific global regulators of human somatic cell reprogramming. Cell Rep. 15, 2597– 2607 (2016). 27292646
  7. [7]Yang C.-S., Chang K.-Y., Rana T. M., Genome-wide functional analysis reveals factors needed at the transition steps of induced reprogramming. Cell Rep. 8, 327– 337 (2014). 25043178 PMC4152236
  8. [8]Fang H.-T., El Farran C. A., Xing Q. R., Zhang L.-F., Li H., Lim B., Loh Y.-H., Global H3.3 dynamic deposition defines its bimodal role in cell fate transition. Nat. Commun. 9, 1537 (2018). 29670118 PMC5906632
  9. [9]Gawad C., Koh W., Quake S. R., Single-cell genome sequencing: Current state of the science. Nat. Rev. Genet. 17, 175– 188 (2016). 26806412
  10. [10]Buenrostro J. D., Wu B., Litzenburger U. M., Ruff D., Gonzales M. L., Snyder M. P., Chang H. Y., Greenleaf W. J., Single-cell chromatin accessibility reveals principles of regulatory variation. Nature 523, 486– 490 (2015). 26083756 PMC4685948
  11. [11]Ramsköld D., Luo S., Wang Y.-C., Li R., Deng Q., Faridani O. R., Daniels G. A., Khrebtukova I., Loring J. F., Laurent L. C., Schroth G. P., Sandberg R., Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells. Nat. Biotechnol. 30, 777– 782 (2012). 22820318 PMC3467340
  12. [12]Li H., Courtois E. T., Sengupta D., Tan Y., Chen K. H., Goh J. J. L., Kong S. L., Chua C., Hon L. K., Tan W. S., Wong M., Choi P. J., Wee L. J. K., Hillmer A. M., Tan I. B., Robson P., Prabhakar S., Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors. Nat. Genet. 49, 708– 718 (2017). 28319088
  13. [13]Ullah I., Subbarao R. B., Rho G. J., Human mesenchymal stem cells - Current trends and future prospective. Biosci. Rep. 35, e00191 (2015). 25797907 PMC4413017
  14. [14]Ruiz S., Panopoulos A. D., Herrerías A., Bissig K. D., Lutz M., Berggren W. T., Verma I. M., Izpisua Belmonte J. C., A high proliferation rate is required for cell reprogramming and maintenance of human embryonic stem cell identity. Curr. Biol. 21, 45– 52 (2011). 21167714 PMC3034649
  15. [15]Jiao J., Dang Y., Yang Y., Gao R., Zhang Y., Kou Z., Sun X.-F., Gao S., Promoting reprogramming by FGF2 reveals that the extracellular matrix is a barrier for reprogramming fibroblasts to pluripotency. Stem Cells 31, 729– 740 (2013). 23307593
  16. [16]Trapnell C., Cacchiarelli D., Grimsby J., Pokharel P., Li S., Morse M., Lennon N. J., Livak K. J., Mikkelsen T. S., Rinn J. L., The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32, 381– 386 (2014). 24658644 PMC4122333
  17. [17]Qiu X., Mao Q., Tang Y., Wang L., Chawla R., Pliner H. A., Trapnell C., Reversed graph embedding resolves complex single-cell trajectories. Nat. Methods 14, 979– 982 (2017). 28825705 PMC5764547
  18. [18]Schiebinger G., Shu J., Tabaka M., Cleary B., Subramanian V., Solomon A., Gould J., Liu S., Lin S., Berube P., Lee L., Chen J., Brumbaugh J., Rigollet P., Hochedlinger K., Jaenisch R., Regev A., Lander E. S., Optimal-transport analysis of single-cell gene expression identifies developmental trajectories in reprogramming. Cell 176, 928– 943.e22 (2019). 30712874 PMC6402800
  19. [19]Cacchiarelli D., Trapnell C., Ziller M. J., Soumillon M., Cesana M., Karnik R., Donaghey J., Smith Z. D., Ratanasirintrawoot S., Zhang X., Ho Sui S. J., Wu Z., Akopian V., Gifford C. A., Doench J., Rinn J. L., Daley G. Q., Meissner A., Lander E. S., Mikkelsen T. S., Integrative analyses of human reprogramming reveal dynamic nature of induced pluripotency. Cell 162, 412– 424 (2015). 26186193 PMC4511597
  20. [20]Watanabe K., Liu Y., Noguchi S., Murray M., Chang J.-C., Kishima M., Nishimura H., Hashimoto K., Minoda A., Suzuki H., OVOL2 induces mesenchymal-to-epithelial transition in fibroblasts and enhances cell-state reprogramming towards epithelial lineages. Sci. Rep. 9, 6490 (2019). 31019211 PMC6482152
  21. [21]Takaishi M., Tarutani M., Takeda J., Sano S., Mesenchymal to epithelial transition induced by reprogramming factors attenuates the malignancy of cancer cells. PLOS ONE 11, e0156904 (2016). 27258152 PMC4892607
  22. [22]Kanton S., Boyle M. J., He Z., Santel M., Weigert A., Sanchís-Calleja F., Guijarro P., Sidow L., Fleck J. S., Han D., Qian Z., Heide M., Huttner W. B., Khaitovich P., Pääbo S., Treutlein B., Camp J. G., Organoid single-cell genomic atlas uncovers human-specific features of brain development. Nature 574, 418– 422 (2019). 31619793
  23. [23]Petropoulos S., Edsgärd D., Reinius B., Deng Q., Panula S. P., Codeluppi S., Plaza Reyes A., Linnarsson S., Sandberg R., Lanner F., Single-cell RNA-seq reveals lineage and X chromosome dynamics in human preimplantation embryos. Cell 165, 1012– 1026 (2016). 27062923 PMC4868821
  24. [24]Yun S.-W., Leong C., Zhai D., Tan Y. L., Lim L., Bi X., Lee J.-J., Kim H. J., Kang N.-Y., Ng S. H., Stanton L. W., Chang Y.-T., Neural stem cell specific fluorescent chemical probe binding to FABP7. Proc. Natl. Acad. Sci. U.S.A. 109, 10214– 10217 (2012). 22689954 PMC3387064
  25. [25]Tan F., Qian C., Tang K., Abd-Allah S. M., Jing N., Inhibition of transforming growth factor β (TGF-β) signaling can substitute for Oct4 protein in reprogramming and maintain pluripotency. J. Biol. Chem. 290, 4500– 4511 (2015). 25548277 PMC4326853
  26. [26]van Dijk D., Sharma R., Nainys J., Yim K., Kathail P., Carr A. J., Burdziak C., Moon K. R., Chaffer C. L., Pattabiraman D., Bierie B., Mazutis L., Wolf G., Krishnaswamy S., Pe’er D., Recovering gene interactions from single-cell data using data diffusion. Cell 174, 716– 729.e27 (2018). 29961576 PMC6771278
  27. [27]Neph S., Stergachis A. B., Reynolds A., Sandstrom R., Borenstein E., Stamatoyannopoulos J. A., Circuitry and dynamics of human transcription factor regulatory networks. Cell 150, 1274– 1286 (2012). 22959076 PMC3679407
  28. [28]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). 29608179 PMC6700744
  29. [30]Shu J., Wu C., Wu Y., Li Z., Shao S., Zhao W., Tang X., Yang H., Shen L., Zuo X., Yang W., Shi Y., Chi X., Zhang H., Gao G., Shu Y., Yuan K., He W., Tang C., Zhao Y., Deng H., Induction of pluripotency in mouse somatic cells with lineage specifiers. Cell 153, 963– 975 (2013). 23706735 PMC4640445
  30. [31]Takahashi K., Tanabe K., Ohnuki M., Narita M., Sasaki A., Yamamoto M., Nakamura M., Sutou K., Osafune K., Yamanaka S., Induction of pluripotency in human somatic cells via a transient state resembling primitive streak-like mesendoderm. Nat. Commun. 5, 3678 (2014). 24759836
  31. [32]Gabut M., Samavarchi-Tehrani P., Wang X., Slobodeniuc V., O’Hanlon D., Sung H.-K., Alvarez M., Talukder S., Pan Q., Mazzoni E. O., Nedelec S., Wichterle H., Woltjen K., Hughes T. R., Zandstra P. W., Nagy A., Wrana J. L., Blencowe B. J., An alternative splicing switch regulates embryonic stem cell pluripotency and reprogramming. Cell 147, 132– 146 (2011). 21924763
  32. [34]Levine A. J., Brivanlou A. H., GDF3, a BMP inhibitor, regulates cell fate in stem cells and early embryos. Development 133, 209– 216 (2006). 16339188
  33. [36]Loh K. M., Lim B., A precarious balance: Pluripotency factors as lineage specifiers. Cell Stem Cell 8, 363– 369 (2011). 21474100
  34. [37]Montserrat N., Nivet E., Sancho-Martinez I., Hishida T., Kumar S., Miquel L., Cortina C., Hishida Y., Xia Y., Esteban C. R., Izpisua Belmonte J. C., Reprogramming of human fibroblasts to pluripotency with lineage specifiers. Cell Stem Cell 13, 341– 350 (2013). 23871606
  35. [38]Yang B. X., El Farran C. A., Guo H. C., Yu T., Fang H. T., Wang H. F., Schlesinger S., Seah Y. F. S., Goh G. Y. L., Neo S. P., Li Y., Lorincz M. C., Tergaonkar V., Lim T.-M., Chen L., Gunaratne J., Collins J. J., Goff S. P., Daley G. Q., Li H., Bard F. A., Loh Y.-H., Systematic identification of factors for provirus silencing in embryonic stem cells. Cell 163, 230– 245 (2015). 26365490 PMC4686136
  36. [39]McInnes L., Healy J., Saul N., Großberger L., UMAP: Uniform manifold approximation and projection. J. Open Source Softw. 3, 861 (2018).
  37. [40]Guo Y., Mahony S., Gifford D. K., High resolution genome wide binding event finding and motif discovery reveals transcription factor spatial binding constraints. PLOS Comput. Biol. 8, e1002638 (2012). 22912568 PMC3415389

Cited by

Sorted by citations

Authors
Xing, Q. R., El Farran, C. A., Gautam, P., Chuah, Y. S., Warrier, T., Toh, C. X. D., Kang, N. Y., Sugii, S., Chang, Y. T., Xu, J., Collins, J. J., Daley, G. Q., Li, H., Zhang, L. F., & Loh, Y. H.
Affiliations
  • Agency for Science, Technology and Research (SG)
  • Epigenetics and Cell Fates Laboratory, Programme in Stem Cell, Regenerative Medicine and Aging, Institute of Molecular and Cell Biology, A*STAR, Singapore 138673, Singapore.
  • Radboud University Nijmegen (NL)
  • Broad Institute (US)
  • Boston Children's Hospital (US)
  • Mayo Clinic (US)
  • Nanyang Technological University (SG)
Corresponding author
  • Xing, Q. R.
  • Li, H.
  • Zhang, L. F.
  • Loh, Y. H.
ORCID
Venue
Science Advances
Publisher
American Association for the Advancement of Science (AAAS)
Published
2020-09-11
Volume
6
Issue
37
ISSN
2375-2548 (ISSN-L)
DOI
10.1126/sciadv.aba1190
PMC
PMC7486102
OpenAlex
W3085530024
Cited by
51
References
4
Citations by year
2026: 4 · 2025: 5 · 2024: 6 · 2023: 11 · 2022: 8 · 2021: 16 · 2019: 1
FWCI
3.16
Type
journal article
Language
en
Open access
Licence
Locations
  • Science Advances (publishedVersion, cc-by-nc)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • Radboud Repository (Radboud University) (submittedVersion, other-oa)
  • National University of Singapore (submittedVersion, cc-by-nc)
  • DR-NTU (Nanyang Technological University) (submittedVersion, cc-by-nc)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
  • Open Access System for Information Sharing (Pohang University of Science and Technology) (submittedVersion)
  • Radboud Repository (Radboud University) (submittedVersion)
Funders
  • NRF Investigatorship Award (NRFI2018-02)
  • Singapore Ministry of Health’s National Medical Research Council (NMRC/CBRG/0092/2015)
  • JCO Development Programme Grant (1534n00153, 1334k00083)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Pluripotent Stem Cells Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
Keywords
cellular reprogramming, single-cell transcriptomics, single-cell chromatin accessibility, FOSL1, TEAD4, transcriptional regulatory networks, cell surface markers, fluorescent probes, reprogramming efficiency, human cells
MeSH terms
TEA Domain Transcription Factors, Chromatin, DNA-Binding Proteins, Humans, Muscle Proteins, Transcription Factors, Single-Cell Analysis, Transcriptome, Cellular Reprogramming

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review