Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Molecular and functional variation in iPSC-derived sensory neurons

Nature Genetics volume 50, pages 54–61 (2018)Cite this article

Subjects

A Publisher Correction to this article was published on 03 June 2019

This article has been updated

Abstract

Induced pluripotent stem cells (iPSCs), and cells derived from them, have become key tools for modeling biological processes, particularly in cell types that are difficult to obtain from living donors. Here we present a map of regulatory variants in iPSC-derived neurons, based on 123 differentiations of iPSCs to a sensory neuronal fate. Gene expression was more variable across cultures than in primary dorsal root ganglion, particularly for genes related to nervous system development. Using single-cell RNA-sequencing, we found that the number of neuronal versus contaminating cells was influenced by iPSC culture conditions before differentiation. Despite high differentiation-induced variability, our allele-specific method detected thousands of quantitative trait loci (QTLs) that influenced gene expression, chromatin accessibility, and RNA splicing. On the basis of these detected QTLs, we estimate that recall-by-genotype studies that use iPSC-derived cells will require cells from at least 20–80 individuals to detect the effects of regulatory variants with moderately large effect sizes.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Characterization of molecular phenotypes in iPSC-derived sensory neurons.
Fig. 2: Single-cell sequencing of IPSDSN cells.
Fig. 3: Gene expression variability in IPSDSNs is influenced by differentiation conditions.
Fig. 4: Splicing QTLs overlapping GWAS associations.
Fig. 5: Power to detect a genetic effect in a single-variant single-gene test depends on sample size, allelic effect size, and gene expression variability.

Change history

  • 03 June 2019

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

References

  1. Itzhaki, I. et al. Modelling the long QT syndrome with induced pluripotent stem cells. Nature 471, 225–229 (2011).

    CAS  PubMed  Google Scholar 

  2. Liu, G.-H. et al. Recapitulation of premature ageing with iPSCs from Hutchinson-Gilford progeria syndrome. Nature 472, 221–225 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Wainger, B. J. et al. Intrinsic membrane hyperexcitability of amyotrophic lateral sclerosis patient-derived motor neurons. Cell Rep. 7, 1–11 (2014).

    CAS  PubMed  Google Scholar 

  4. Lee, G. et al. Modelling pathogenesis and treatment of familial dysautonomia using patient-specific iPSCs. Nature 461, 402–406 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Cao, L. et al. Pharmacological reversal of a pain phenotype in iPSC-derived sensory neurons and patients with inherited erythromelalgia. Sci. Transl. Med 8, 335ra56 (2016).

    PubMed  Google Scholar 

  6. Warren, C. R., Jaquish, C. E. & Cowan, C. A. The NextGen Genetic Association Studies Consortium: a foray into in vitro population genetics. Cell. Stem. Cell. 20, 431–433 (2017).

    CAS  PubMed  Google Scholar 

  7. Young, G. T. et al. Characterizing human stem cell-derived sensory neurons at the single-cell level reveals their ion channel expression and utility in pain research. Mol. Ther. 22, 1530–1543 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Kilpinen, H. et al. Common genetic variation drives molecular heterogeneity in human iPSCs. Nature 546, 370–375 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Melé, M. et al. The human transcriptome across tissues and individuals. Science 348, 660–665 (2015).

    PubMed  PubMed Central  Google Scholar 

  10. Soldner, F. et al. Parkinson-associated risk variant in distal enhancer of α-synuclein modulates target gene expression. Nature 533, 95–99 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Pashos, E. E. et al. Large, diverse population cohorts of hiPSCs and derived hepatocyte-like cells reveal functional genetic variation at blood lipid-associated loci. Cell. Stem. Cell. 20, 558–570 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Warren, C. R. et al. Induced pluripotent stem cell differentiation enables functional validation of GWAS variants in metabolic disease. Cell. Stem. Cell. 20, 547–557 (2017).

    CAS  PubMed  Google Scholar 

  13. Sala, L., Bellin, M. & Mummery, C. L. Integrating cardiomyocytes from human pluripotent stem cells in safety pharmacology: has the time come? Br. J. Pharmacol. 174, 3749–3765 (2017).

    CAS  PubMed  Google Scholar 

  14. Kiselev, V. Y. et al. SC3: consensus clustering of single-cell RNA-seq data. Nat. Methods. 14, 483–486 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Newman, A. M. et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 12, 453–457 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Kléber, M. et al. Neural crest stem cell maintenance by combinatorial Wnt and BMP signaling. J. Cell. Biol. 169, 309–320 (2005).

    PubMed  PubMed Central  Google Scholar 

  17. Ongen, H., Buil, A., Brown, A. A., Dermitzakis, E. T. & Delaneau, O. Fast and efficient QTL mapper for thousands of molecular phenotypes. Bioinformatics. 32, 1479–1485 (2016).

    CAS  PubMed  Google Scholar 

  18. Kumasaka, N., Knights, A. J. & Gaffney, D. J. Fine-mapping cellular QTLs with RASQUAL and ATAC-seq. Nat. Genet. 48, 206–213 (2016).

    CAS  PubMed  Google Scholar 

  19. Li, Y. I. et al. RNA splicing is a primary link between genetic variation and disease. Science 352, 600–604 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Li, Y. I., Knowles, D. A. & Pritchard, J. K. LeafCutter: annotation-free quantification of RNA splicing. Preprint available at https://www.biorxiv.org/content/early/2016/03/16/044107 (2016).

  21. Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods. 10, 1213–1218 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Sheffield, N. C. & Bock, C. LOLA: enrichment analysis for genomic region sets and regulatory elements in R and Bioconductor. Bioinformatics 32, (587–589 (2016).

    Google Scholar 

  23. Lessard, J. et al. An essential switch in subunit composition of a chromatin remodeling complex during neural development. Neuron. 55, 201–215 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Hunt, S. P., Pini, A. & Evan, G. Induction of c-Fos-like protein in spinal cord neurons following sensory stimulation. Nature 328, 632–634 (1987).

    CAS  PubMed  Google Scholar 

  25. Kohno, T., Moore, K. A., Baba, H. & Woolf, C. J. Peripheral nerve injury alters excitatory synaptic transmission in lamina II of the rat dorsal horn. J. Physiol. (Lond.) 548, 131–138 (2003).

    CAS  Google Scholar 

  26. Peters, M. J. et al. Genome-wide association study meta-analysis of chronic widespread pain: evidence for involvement of the 5p15.2 region. Ann. Rheum. Dis. 72, 427–436 (2013).

    CAS  PubMed  Google Scholar 

  27. Pers, T. H., Timshel, P. & Hirschhorn, J. N. SNPsnap: a Web-based tool for identification and annotation of matched SNPs. Bioinformatics. 31, 418–420 (2015).

    CAS  PubMed  Google Scholar 

  28. Gregory, A. P. et al. TNF receptor 1 genetic risk mirrors outcome of anti-TNF therapy in multiple sclerosis. Nature 488, 508–511 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Probert, L. TNF and its receptors in the CNS: the essential, the desirable and the deleterious effects. Neuroscience. 302, 2–22 (2015).

    CAS  PubMed  Google Scholar 

  30. Spilker, C. & Kreutz, M. R. RapGAPs in brain: multipurpose players in neuronal Rap signalling. Eur. J. Neurosci. 32, 1–9 (2010).

    PubMed  Google Scholar 

  31. Jordan, J. D. et al. Cannabinoid receptor-induced neurite outgrowth is mediated by Rap1 activation through G(α)o/i-triggered proteasomal degradation of Rap1GAPII. J. Biol. Chem. 280, 11413–11421 (2005).

    CAS  PubMed  Google Scholar 

  32. Melchionda, L. et al. Mutations in APOPT1, encoding a mitochondrial protein, cause cavitating leukoencephalopathy with cytochrome C oxidase deficiency. Am. J. Hum. Genet. 95, 315–325 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Dianat, N., Steichen, C., Vallier, L., Weber, A. & Dubart-Kupperschmitt, A. Human pluripotent stem cells for modelling human liver diseases and cell therapy. Curr. Gene. Ther. 13, 120–132 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Smith, B. W. et al. The aryl hydrocarbon receptor directs hematopoietic progenitor cell expansion and differentiation. Blood. 122, 376–385 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Handel, A. E. et al. Assessing similarity to primary tissue and cortical layer identity in induced pluripotent stem cell-derived cortical neurons through single-cell transcriptomics. Hum. Mol. Genet. 25, 989–1000 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Hu, B.-Y. et al. Neural differentiation of human induced pluripotent stem cells follows developmental principles but with variable potency. Proc. Natl. Acad. Sci. USA 107, 4335–4340 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Cacchiarelli, D. et al. Aligning single-cell developmental and reprogramming trajectories identifies molecular determinants of reprogramming outcome. Preprint available at https://www.biorxiv.org/content/early/2017/03/30/122531 (2017).

  38. Musunuru, K. et al. From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus. Nature 466, 714–719 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Chambers, S. M. et al. Combined small-molecule inhibition accelerates developmental timing and converts human pluripotent stem cells into nociceptors. Nat. Biotechnol. 30, 715–720 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Jun, G. et al. Detecting and estimating contamination of human DNA samples in sequencing and array-based genotype data. Am. J. Hum. Genet. 91, 839–848 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 30, 923–930 (2014).

    CAS  PubMed  Google Scholar 

  42. Hansen, K. D., Irizarry, R. A. & Wu, Z. Removing technical variability in RNA-seq data using conditional quantile normalization. Biostatistics. 13, 204–216 (2012).

    PubMed  PubMed Central  Google Scholar 

  43. Castel, S. E., Levy-Moonshine, A., Mohammadi, P., Banks, E. & Lappalainen, T. Tools and best practices for data processing in allelic expression analysis. Genome. Biol. 16, 195 (2015).

    PubMed  PubMed Central  Google Scholar 

  44. Davis, J. R. et al. An efficient multiple-testing adjustment for eQTL studies that accounts for linkage disequilibrium between variants. Am. J. Hum. Genet. 98, 216–224 (2016).

    CAS  PubMed  Google Scholar 

  45. Sheffield, N. C. et al. Patterns of regulatory activity across diverse human cell types predict tissue identity, transcription factor binding, and long-range interactions. Genome Res. 23, 777–788 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Danecek, P. et al. The variant call format and VCFtools. Bioinformatics. 27, 2156–2158 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The iPSC lines were generated under the Human Induced Pluripotent Stem Cell Initiative (HIPSCI) funded by a grant from the Wellcome Trust and Medical Research Council (WT098503), supported by the Wellcome Trust (WT098051) and the NIHR/Wellcome Trust Clinical Research Facility. HIPSCI funding was used for sensory neuron RNA-sequencing. We acknowledge Life Science Technologies Corporation as the provider of Cytotune. Pfizer Neuroscience (Pfizer Ltd.) funded neuronal differentiation, functional assays, single-cell RNA-sequencing, and collection and sequencing of dorsal root ganglion samples. The authors gratefully acknowledge N. Kumasaka for help with RASQUAL. We thank F. Merkle for comments on the manuscript. J.S. gratefully acknowledges support from the Wellcome Trust for his PhD studentship. We also thank three anonymous reviewers whose feedback greatly improved this manuscript.

Author information

Author notes

  1. A list of members and affiliations appears in Supplementary Note 1.

Authors and Affiliations

  1. Wellcome Trust Sanger Institute, Hinxton, UK

    Jeremy Schwartzentruber, Julia Rodrigues, Kaur Alasoo, Andrew J. Knights, Minal Patel, Angela Goncalves & Daniel J. Gaffney

  2. Pfizer Neuroscience and Pain Research Unit, Pfizer Ltd., Cambridge, UK

    Stefanie Foskolou, Rita Ferreira, Caroline Louise Benn, Anna Wilbrey, Magda Bictash, Emma Impey, Lishuang Cao, Sergio Lainez, Alexandre Julien Loucif, Paul John Whiting & Alex Gutteridge

  3. European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK

    Helena Kilpinen

  4. AR-UK Drug Discovery Institute, Institute of Neurology, University College London, London, UK

    Paul John Whiting

  5. European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK

    Jeremy Schwartzentruber

Authors
  1. Jeremy Schwartzentruber
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Stefanie Foskolou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Helena Kilpinen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Julia Rodrigues
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kaur Alasoo
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Andrew J. Knights
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Minal Patel
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Angela Goncalves
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Rita Ferreira
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Caroline Louise Benn
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Anna Wilbrey
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Magda Bictash
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Emma Impey
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Lishuang Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Sergio Lainez
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Alexandre Julien Loucif
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Paul John Whiting
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Alex Gutteridge
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Daniel J. Gaffney
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

HIPSCI Consortium

Contributions

J.S. analyzed data, and J.S. and D.J.G. wrote the manuscript. S.F. performed all differentiations. A. Gutteridge analyzed data. A. Gutteridge, D.J.G., and P.J.W. conceived and supervised the project. H.K. compared eQTLs with GTEx and identified tissue-specific eQTLs. J.R. and M.P. cultured iPSC samples. A.J.K. performed all ATAC-seq. K.A. and A. Goncalves assisted with data analysis. A.W. performed single-cell RNA work and assisted with data analysis. R.F. and C.L.B. performed RNA extraction and quantification. E.I. performed cell culture and Ca2+ flux assays. M.B. assisted with experimental design and Ca2+ flux assays. L.C., S.L., and A.J.L. performed electrophysiology measurements. All authors reviewed the manuscript.

Corresponding authors

Correspondence to Jeremy Schwartzentruber, Alex Gutteridge or Daniel J. Gaffney.

Ethics declarations

Competing interests

S.F., R.F., C.L.B., A.W., M.B., E.I., L.C., S.L., A.J.L., P.J.W., and A. Gutteridge were all employees of Pfizer at the time the experiments were performed.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Combined Supplementary Figures and Supplementary Note

Supplementary Figures 1–25 and Supplementary Note 1.

Life Sciences Reporting Summary

Supplementary Tables

Supplementary Tables 1–11.

Supplementary Tables

Supplementary Tables 12–22.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Schwartzentruber, J., Foskolou, S., Kilpinen, H. et al. Molecular and functional variation in iPSC-derived sensory neurons. Nat Genet 50, 54–61 (2018). https://doi.org/10.1038/s41588-017-0005-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41588-017-0005-8

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing