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Transcriptomic and epigenomic differences in human induced pluripotent stem cells generated from six reprogramming methods

Nature Biomedical Engineering volume 1, pages 826–837 (2017)Cite this article

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Abstract

Many reprogramming methods can generate human induced pluripotent stem cells (hiPSCs) that closely resemble human embryonic stem cells (hESCs). This has led to assessments of how similar hiPSCs are to hESCs, by evaluating differences in gene expression, epigenetic marks and differentiation potential. However, all previous studies were performed using hiPSCs acquired from different laboratories, passage numbers, culturing conditions, genetic backgrounds and reprogramming methods, all of which may contribute to the reported differences. Here, by using high-throughput sequencing under standardized cell culturing conditions and passage number, we compare the epigenetic signatures (H3K4me3, H3K27me3 and HDAC2 ChIP-seq profiles) and transcriptome differences (by RNA-seq) of hiPSCs generated from the same primary fibroblast population by using six different reprogramming methods. We found that the reprogramming method impacts the resulting transcriptome and that all hiPSC lines could terminally differentiate, regardless of the reprogramming method. Moreover, by comparing the differences between the hiPSC and hESC lines, we observed a significant proportion of differentially expressed genes that could be attributed to polycomb repressive complex targets.

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Fig. 1: RNA-seq expression differences between hiPSC lines, fibroblasts and hESCs.
Fig. 2: Comparison of RNA-seq expression differences among fibroblasts, hESCs and hiPSCs reprogrammed by different methods.
Fig. 3: Gene ontology (GO) enrichment, transcription factor target enrichment, and HDAC2 activity between hESCs and hiPSCs.
Fig. 4: Comparison of H3K4me3 and H3K27me3 ChIP-seq between each reprogramming method.
Fig. 5: X chromosome H3K27me3 and XIST differences in hiPSCs.
Fig. 6: Comparison of cardiac differentiation potential between each reprogramming method.

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Acknowledgements

This study was funded by the Canadian Institute of Health Research 201210MFE-289547 (J.M.C.), National Institutes of Health 1K99HL128906 (J.M.C.), PCBC_JS_2014/4_01 (J.M.C.), National Research Foundation of Korea 2012R1A6A3A03039821 (J.L.), the Burroughs Wellcome Foundation, National Institutes of Health R01 HL123968, HL128170, R01 HL126527 (J.C.W.), and P01 GM099130 (M.P.S.). The authors would like to thank the Stanford Stem Cell Institute Genome Center for their sequencing knowledge, V. Sebastiano for hESC culturing, and B. Huber for his help with the teratoma assay. We would also like to thank J. Brito and B. Wu for their help in editing the manuscript.

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Authors and Affiliations

  1. Institute of Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA

    Jared M. Churko, Jaecheol Lee, Mohamed Ameen, Mingxia Gu, Sebastian Diecke, Karim Sallam, Joseph D. Gold & Joseph C. Wu

  2. Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA

    Jared M. Churko, Jaecheol Lee, Mohamed Ameen, Mingxia Gu, Sebastian Diecke, Karim Sallam & Joseph C. Wu

  3. Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA

    Jared M. Churko, Jaecheol Lee, Mohamed Ameen, Mingxia Gu, Sebastian Diecke, Karim Sallam & Joseph C. Wu

  4. Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA

    Meenakshi Venkatasubramanian, Hogune Im & Nathan Salomonis

  5. Department of Genetics, Stanford University School of Medicine, Stanford, CA, 94305, USA

    Gavin Wang & Michael P. Snyder

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Contributions

J.D.G., N.S., M.P.S. and J.C.W. supervised and planned the project. J.M.C. wrote the manuscript, performed data analysis, generated and cultured hiPSC lines, and performed RNA-seq. N.S. and M.V. performed integration analysis. H.I. helped analyse RNA-seq. J.L. performed ChIP-seq experiments. M.A. and M.G. performed FACS analysis on differentiated cardiomyocytes. G.W. and K.S. helped to culture hiPSC and hESC lines. S.D. generated minicircle hiPSC lines.

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Correspondence to Joseph C. Wu.

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Supplementary Information

Supplementary figures

Life Sciences Reporting Summary

Supplementary Dataset 1

Reads per kilobase of transcript per million mapped reads of each Ensembl ID, calculated via AltAnalyze.

Supplementary Dataset 2

Gene-expression differences, calculated via a Bayes moderated t-test p-value (unpaired), assuming unequal variance, and p < 0.05 with two-fold difference.

Supplementary Dataset 3

Splicing events between hiPSCs and hESCs.

Supplementary Dataset 4

Differential peaks unique to the hESCs and peaks unique to hiPSCs, corresponding to HDAC2 localization.

Supplementary Dataset 5

Transcriptional-start-site peak-density differences within the H3K4me3 ChIP-seq set between hESCs and hiPSCs.

Supplementary Dataset 6

Transcriptional-start-site peak-density differences in the H3K27me3 ChIP-seq profile between hESCs and hiPSCs.

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Churko, J.M., Lee, J., Ameen, M. et al. Transcriptomic and epigenomic differences in human induced pluripotent stem cells generated from six reprogramming methods. Nat Biomed Eng 1, 826–837 (2017). https://doi.org/10.1038/s41551-017-0141-6

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