Developmental programs that generate the astonishing neuronal diversity of the nervous system are not completely understood and thus present a major challenge for clinical applications of guided cell differentiation strategies. Using direct neuronal programming of embryonic stem cells, we found that two main vertebrate proneural factors, Ascl1 and neurogenin 2 (Neurog2), induce different neuronal fates by binding to largely different sets of genomic sites. Their divergent binding patterns are not determined by the previous chromatin state, but are distinguished by enrichment of specific E-box sequences that reflect the binding preferences of the DNA-binding domains. The divergent Ascl1 and Neurog2 binding patterns result in distinct chromatin accessibility and enhancer activity profiles that differentially shape the binding of downstream transcription factors during neuronal differentiation. This study provides a mechanistic understanding of how transcription factors constrain terminal cell fates, and it delineates the importance of choosing the right proneural factor in neuronal reprogramming strategies.

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Data availability

All data (RNA–seq, ChIP–seq, ATAC–seq, and scRNA–seq) produced for this study are available from the GEO database under accession GSE114176. We performed a re-analysis of data sourced from GEO database entries GSE101397, GSE97715 and GSE43916.

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Journal peer review information: Nature Neuroscience thanks Diogo Castro, Carol Schuurmans, and other anonymous reviewer(s) for their contribution to the peer review of this work.

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


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This work is supported by the NICHD (R01HD079682) and Project ALS (A13-0416) to E.O.M. and by a NYSTEM pre-doctoral training grant (C026880) to B.A. S.M. is supported by the NIGMS (R01GM125722) and the National Science Foundation ABI Innovation grant no. DBI1564466. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. M.R. is supported by NYU MSTP (T32GM007308) and Developmental Genetics T32 (T32HD007520) grants. N.F. and M.M.-E. are supported by an ERC Starting Grant (ERC STG 2011–281920). The authors would like to thank L. Tejavibulya and A. Ashokkumar for their help with molecular biology, M. Khalfan for his help with scRNA-seq analysis, M. Cammer from the NYU Medical Center Microscopy Core for the ImageJ script used in calcium imaging analysis, and the NYU Genomics Core facility. Finally, the authors would like to thank S. Small, N. Konstantinidis, P. Onal, O. Wapinski, S. Ercan, C. Rushlow, C. Desplan, and Mazzoni Lab members for their helpful suggestions on the manuscript.

Author information


  1. Department of Biology, New York University, New York, NY, USA

    • Begüm Aydin
    • , Görkem Garipler
    •  & Esteban O. Mazzoni
  2. Neuroscience Institute, Department of Neuroscience and Physiology, NYU School of Medicine, New York, NY, USA

    • Begüm Aydin
    • , Görkem Garipler
    •  & Esteban O. Mazzoni
  3. Center for Eukaryotic Gene Regulation, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, USA

    • Akshay Kakumanu
    •  & Shaun Mahony
  4. Skirball Institute of Biomolecular Medicine, NYU School of Medicine, New York, NY, USA

    • Mary Rossillo
    •  & Niels Ringstad
  5. Developmental Neurobiology Unit, Instituto de Biomedicina de Valencia IBV-CSIC, Valencia, Spain

    • Mireia Moreno-Estellés
    •  & Nuria Flames


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B.A. performed cell differentiations, RNA-seq, ChIP-seq, ATAC-seq, scRNA-seq, immunohistochemistry experiments, and generated the inducible chimera line. Two replicates of iAscl1 48 h RNA-seq experiments were performed by M.M.-E. with guidance from N.F. M.R. performed calcium imaging of neurons with guidance from N.R. G.G provided the Tubb3::GFP line. A.K., B.A., and S.M. performed analysis of all sequencing data. B.A., S.M., and E.O.M. conceived the experiments and wrote the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare no competing interests.

Corresponding authors

Correspondence to Shaun Mahony or Esteban O. Mazzoni.

Integrated supplementary information

  1. Supplementary Figure 1 Ascl1 and Neurog2 induction programs neuronal fate.

    a, Immunocytochemistry of iASCL1 (iA - left panel) and iNEUROG2 (iN - right panel) embryoid bodies (EBs) showing the expression of neuronal Tubb3 and V5-tagged Ascl1 or FLAG-tagged Neurog2 transgene expression over time, respectively (scale bar: 1 µm). 0h time point (before induction of TFs) is used as a control. Similar results were observed in at least n = 2 cell differentiations. b, Schematic representation of time-series (bulk) RNA-seq experiments (not to scale) showing the overlap of the genes up or downregulated early (12 h) or late (48 h) between iA and iN neurons. c, Gene Ontology (GO-terms) biological process terms enriched at the early and late shared upregulated genes between iA and iN neurons (PANTHER- Fisher’s Exact test: FDR-corrected p-value < 0.05) (iA 12 h n = 2; iN 12 h n = 2; iA 48 h n = 5; iN 48 h n = 2 independent cell differentiations). d, Bulk RNA-seq heatmaps showing the expression of subtype-specific markers in iA and iN neurons 48h after induction (EB t = 0 n = 5; iA 48 h n = 5; iN 48 h n = 2 independent cell differentiations). log2(fold change) values are plotted with respect to before induction (EB t = 0) in magenta-orange heatmap. The ratio of iN (48 h) over iA (48 h) is plotted on the blue-green heatmap.

  2. Supplementary Figure 2 Divergent binding of Ascl1 and Neurog2 is not an artifact.

    ChIP-seq heatmap with all sites identified in 12 h Ascl1 and Neurog2 datasets shows the divergent binding pattern when 10 k (Fig. 2) or all sites are analyzed (n = 3). b, Ascl1 and Neurog2 bind to largely non-overlapping sites even at 48 h after induction. ChIP-seq heatmap with top 10k sites identified in 48 h Ascl1 and Neurog2 datasets shows that the late binding of Ascl1 and Neurog2 is also divergent (n = 2). c, ChIP-seq heatmap with all sites identified in 48 h Ascl1 and Neurog2 datasets showing that the late divergent binding is still retained when all sites are analyzed (n = 2). d, e, Comparison of Ascl1 ChIP-seq experiments across published datasets in mouse embryonic fibroblasts (MEFs) (d), and ESCs (e). Heatmaps display shared binding sites (that is peaks called in both experiments) and significantly differentially bound sites across experiments. f, ChIP-seq and RNA-seq genome browser snapshots displaying gene expression and differential binding of Ascl1 and Neurog2 at the Dll1 locus. g, Comparison of Ascl1 and Neurog2 binding across 12 h and 48 h time-points. Table displays counts of shared binding sites (that is peaks called in both experiments) and significantly differentially bound sites across experiments.

  3. Supplementary Figure 3 Nucleotides flanking the core E-box motif contribute to the binding specificity of Ascl1 and Neurog2.

    a, Nucleotides flanking the core “CAGNTG” k-mer also contribute to Ascl1 or Neurog2 differential binding (A > N or N > A) and shared binding (A = N) in vivo. b, DNA shape prediction at the Ascl1- and Neurog2-preferred sites around the core E-box motifs. Larger predicted propeller twist and minor groove width were noted at alternate sides of the core E-box motif in Ascl1-preferred sites (A > N).

  4. Supplementary Figure 4 The k-mer preference and the expression profile of the A[N]bHLH chimera.

    a, The A[N]bHLH chimera binding sites are enriched in Neurog2-preferred core and flanking k-mers. b, Volcano plot comparing the gene expression between iA and iA[N]bHLH at 48 h after induction by RNA-seq. Colored dots represent differentially expressed genes in iA (blue) or iA[N]bHLH(pink) (q-value cut-off < 0.01, Wald test) (iA 48 h n = 5; iA[N]bHLH 48 h n = 2 independent cell differentiations). c, Volcano plot comparing the gene expression between iN and iA[N]bHLH at 48 h after induction by RNA-seq. Colored dots represent differentially expressed genes in iN (green) or iA[N]bHLH(pink) (q-value cut-off < 0.01, Wald test) (iA[N]bHLH 48 h n = 2; iN 48 h n = 2 independent cell differentiations).

  5. Supplementary Figure 5 Global chromatin accessibility dynamics mimic the divergent-to-convergent gene expression dynamics in Ascl1- and Neurog2-induced neurogenesis.

    a, Global comparison of sites that differentially gained or lost accessibility at 12 h (top) and 48 h (bottom) iA and iN neurons with respect to EB 0 h. Note the increased shared changes by 48 h (p-val cut-off < 0.05) (n = 2 independent cell differentiations). b, Comparison of differentially accessible regions in iAscl1 EBs (this paper) to iAscl1 in MEFs (Wapinski et al45). c, Time-series ATAC-seq heatmaps showing the dynamics of the accessibility gain at the differentially bound and shared sites of Ascl1 and Neurog2 along with the accessibility dynamics in the iA[N]bHLH chimeric TF line. Note that the A[N]bHLH chimera has increased ATAC-seq read counts at the Neurog2-preferred sites (N > A) both at 12 h and 48 h.

  6. Supplementary Figure 6 Examples of shared targets that have differential Ascl1 or Neurog2 binding.

    a, Comparison of endogenous Brn2 ChIP-seq in mESC (this paper) with exogenous Brn2 in MEFs programming when expressed exogenously with Ascl1 and Myt1l (iBAM – Wapinski et al25). Heatmaps display shared binding sites (that is peaks called in both experiments) and significantly differentially bound sites across experiments. b, Maximum motif log-likelihood scores of downstream TFs shows weaker enrichment of their respective motifs in iA > iN (left) or iN > iA (right) sites that have E-box motifs as opposed to their top 10 K binding sites (150 bp window around sites) (n = 2 independent cell differentiations) c, tSNE plots showing the cells that express shared targets in iA (top cluster) and iN (bottom cluster) neuron clusters (top panel / n = 1 cell differentiation) that have differential Ascl1 or Neurog2 binding (genome browser shots – bottom panel / n = 3 independent cell differentiations).

  7. Supplementary Figure 7 Working model.

    Ascl1 and Neurog2 bind to their preferred sites in the genome mediated intrinsically by their bHLH DNA-binding domain. This divergent binding, in return, results in distinct chromatin landscapes that affect the activity of downstream TFs in establishing generic and neuron-specific phenotypes (TF, transcription factor).

Supplementary information

  1. Supplementary Figures 1–7.

  2. Reporting Summary

  3. Supplementary Table 1

    Summary of genes vs. peaks associations from GREAT analysis. The peaks are the same sets represented in Fig 2a,b. Gene sets evaluated in Fig. 7 represent genes that are significantly upregulated in both iA and iN compared with EBs (iA = iN), and genes that are significantly differentially expressed between iA and iN (iA > iN and iN > iA) for each relevant timepoint. Overrepresentation table shows the ratio between genes overlapped by real peaks versus genes overlapped by random peaks. P-value tables are calculated using GREAT’s binomial testing tool.

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