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A network of epigenetic regulators guides developmental haematopoiesis in vivo

Abstract

The initiation of cellular programs is orchestrated by key transcription factors and chromatin regulators that activate or inhibit target gene expression. To generate a compendium of chromatin factors that establish the epigenetic code during developmental haematopoiesis, a large-scale reverse genetic screen was conducted targeting orthologues of 425 human chromatin factors in zebrafish. A set of chromatin regulators was identified that target different stages of primitive and definitive blood formation, including factors not previously implicated in haematopoiesis. We identified 15 factors that regulate development of primitive erythroid progenitors and 29 factors that regulate development of definitive haematopoietic stem and progenitor cells. These chromatin factors are associated with SWI/SNF and ISWI chromatin remodelling, SET1 methyltransferase, CBP–p300–HBO1–NuA4 acetyltransferase, HDAC–NuRD deacetylase, and Polycomb repressive complexes. Our work provides a comprehensive view of how specific chromatin factors and their associated complexes play a major role in the establishment of haematopoietic cells in vivo.

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Figure 1: Screen design for chromatin regulators of developmental haematopoiesis.
Figure 2: Classification of screen results.
Figure 3: Morpholino efficacy and secondary verification of screen phenotypes.
Figure 4: Chromatin factors regulate distinct steps of primitive erythroid development.
Figure 5: Chromatin factors regulate distinct steps of definitive HSPC development.
Figure 6: Identification of chromatin-modifying complexes using protein interaction data for the 44 validated primitive and definitive genes.
Figure 7: A protein–protein interaction network for the 425 human chromatin factors screened.
Figure 8: Genetic interaction of ISWI chromatin factors by combinatorial knockdown.

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Acknowledgements

We thank O. Tamplin, T. V. Bowman, P. Cahan and C. K. Kaufman for helpful discussions. The work was supported by NIH NIDDK 5R01DK053298-15, NIH NHLBI 5R01HL048801-21, NIH NIDDK 5P30 DK49216-19, NIH NIDDK DK53298-15, NIH NIDDK R24 DK092760-02, HHMI (to L.I.Z.), NIH NHLBI T32 HL066987-09 and NIH NIDDK 1F32DK089876-01 (to K.L.K).

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Authors and Affiliations

Authors

Contributions

H-T.H. and K.L.K. performed all experiments and data analysis. A.B. and Z.G. assisted with morpholino microinjection, WISH and data collection. Y-H.H. assisted with morpholino microinjection. T.P.W., Y.Z., A.S. and A.D. developed the screen database. Y.Z. initiated and assisted with bioinformatic analysis of chromatin factors. O.H. and W.H. generated the protein interaction network. S.T. performed the distribution analysis for the ChIP-seq data. H-T.H. and L.I.Z. conceived the study.

Corresponding author

Correspondence to Leonard I. Zon.

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Competing interests

L.I.Z. is a founder and stock holder of Fate, Inc. and Scholar Rock, and a scientific adviser for Stemgent.

Integrated supplementary information

Supplementary Figure 1 Efficacy of chromodomain family splice blocking morpholinos.

(a) Splicing activity for splice blocking morpholinos targeting chd genes that result in haematopoietic phenotype. (b) Splicing activity for splice blocking morpholinos targeting chd genes that do not result in a haematopoietic phenotype. chd6 had no expression detected. Filled in arrowheads indicate wild-type bands. Empty arrowheads indicate splice variants.

Supplementary Figure 2 Screen hits with morphological defects.

(a) Summary of primitive screen WISH results with morphological defects as determined by the abnormal patterning of the bilateral stripes of β −globine3+ erythroid cells. (b) Summary of definitive screen WISH results with morphological defects as determined by stunted embryonic growth in the tail. Representative WISH results are shown for each phenotypic category. “n” is the number of chromatin factors with the indicated phenotype. Blue downward arrows represent reduced marker expression and magenta upward arrows represent increased marker expression. One arrow indicates a mild change, two arrows an intermediate change, and three arrows a strong change. Scale bars: 100 μm for low magnification and 25 μm for high magnification.

Supplementary Figure 3 Protein interaction modules containing chromatin factors identified from primitive and definitive screens.

Subnetworks isolated from Fig. 6 are shown below including first neighboring interacting nodes. Each node annotated to a specific chromatin complex corresponding to those in Fig. 6 is indicated by uniquely colored borders. The entire complex is demarcated by dotted lines in the same color. Screen classifications for each chromatin factor are indicated by the color of each node.

Supplementary Figure 4 Chromatin factor hits from predicted protein complexes have overlapping target genes in K562 erythroleukemia cells.

Distribution plots of percent overlap of target genes for chromatin factor ChIP-seq datasets. Tickmarks along the x-axis represent each chromatin factor triplet combination. PRC1/PRC2 combinations are shown in blue. HDAC/NuRD combinations are shown in green. All others are shown in grey. (a) Distribution plot of triplets from 24 chromatin factor datasets excluding chromatin factors that bind to >8,000 genes (filtered). NuRD triplets containing HDAC1 and TAF1 were ignored PRC1/PRC2 and HDAC/NuRD combinations are significantly overrepresented in the top 5% of the distribution (Fisher’s exact test; p = 6.1×10−6 and 0.05*, respectively). (b) Distribution plot of triplets from 34 chromatin factor datasets (all). PPRC1/PRC2 and HDAC/NuRD combinations are significantly overrepresented in the top 20% of the distribution (Fisher’s exact test; p = 0.002 and 1×10−7, respectively). (c) Chart listing combinations for PRC1/PRC2 and HDAC/NuRD complexes. % overlap is the proportion of intersecting target genes over the total target genes for the 3 factors. Rank is ordered from highest to lowest % overlap. * Only one NuRD triplet was tested for this distribution based on the filtering criterion.

Supplementary Figure 5 Uncropped gel images from RT-PCRs.

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Huang, HT., Kathrein, K., Barton, A. et al. A network of epigenetic regulators guides developmental haematopoiesis in vivo. Nat Cell Biol 15, 1516–1525 (2013). https://doi.org/10.1038/ncb2870

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