Rational targeting of a NuRD subcomplex guided by comprehensive in situ mutagenesis


Developmental silencing of fetal globins serves as both a paradigm of spatiotemporal gene regulation and an opportunity for therapeutic intervention of β-hemoglobinopathy. The nucleosome remodeling and deacetylase (NuRD) chromatin complex participates in γ-globin repression. We used pooled CRISPR screening to disrupt NuRD protein coding sequences comprehensively in human adult erythroid precursors. Essential for fetal hemoglobin (HbF) control is a non-redundant subcomplex of NuRD protein family paralogs, whose composition we corroborated by affinity chromatography and proximity labeling mass spectrometry proteomics. Mapping top functional guide RNAs identified key protein interfaces where in-frame alleles resulted in loss-of-function due to destabilization or altered function of subunits. We ascertained mutations of CHD4 that dissociate its requirement for cell fitness from HbF repression in both primary human erythroid precursors and transgenic mice. Finally we demonstrated that sequestering CHD4 from NuRD phenocopied these mutations. These results indicate a generalizable approach to discover protein complex features amenable to rational biochemical targeting.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Dense mutagenesis of NuRD genes by CRISPR-Cas9 pooled screening.
Fig. 2: NuRD subcomplex expression.
Fig. 3: Maps of functional NuRD subcomplex.
Fig. 4: In-frame deletions disrupt MTA2 function.
Fig. 5: Targeting CHD4 CHDCT2 uncouples HbF induction from cytotoxicity.
Fig. 6: GATAD2A ZF sequesters CHD4 from NuRD.

Data availability

The data that support the findings of this study are available from the corresponding author upon request. Data and analysis are included in the article and Supplementary Note. Mass spectrometery raw data is accessable from proteomecentral under accession no. PXD009793. Next-generation sequencing (NGS) data (RNA-seq and CRISPR screen) are available from NCBI SRA portal under accession No. PRJNA496556.

Code availability

For analysis and visualization of functional readout from tiled pooled CRISPR screen, we used a custom computational pipeline available at https://gitlab.com/bauerlab/crispro.


  1. 1.

    Modell, B. & Darlison, M. Global epidemiology of haemoglobin disorders and derived service indicators. Bull. World Health Organ 86, 480–487 (2008).

    Article  Google Scholar 

  2. 2.

    Piel, F. B. et al. Global epidemiology of sickle haemoglobin in neonates: a contemporary geostatistical model-based map and population estimates. Lancet 381, 142–151 (2013).

    Article  Google Scholar 

  3. 3.

    Darling, R. C., Smith, C. A., Asmussen, E. & Cohen, F. M. Some properties of human fetal and maternal blood. J. Clin. Invest. 20, 739–747 (1941).

    CAS  Article  Google Scholar 

  4. 4.

    Schroeder, W. A., Shelton, J. R., Shelton, J. B. & Cormick, J. The amino acid sequence of the alpha chain of human fetal hemoglobin. Biochemistry 2, 1353–1357 (1963).

    CAS  Article  Google Scholar 

  5. 5.

    Blau, C. A. & Stamatoyannopoulos, G. Hemoglobin switching and its clinical implications. Curr. Opin. Hematol. 1, 136–142 (1994).

    CAS  PubMed  Google Scholar 

  6. 6.

    Vinjamur, D. S., Bauer, D. E. & Orkin, S. H. Recent progress in understanding and manipulating haemoglobin switching for the haemoglobinopathies. Br. J. Haematol. 180, 630–643 (2017).

    Article  Google Scholar 

  7. 7.

    Bauer, D. E., Brendel, C. & Fitzhugh, C. D. Curative approaches for sickle cell disease: a review of allogeneic and autologous strategies. Blood Cells Mol. Dis. 67, 155–168 (2017).

    Article  Google Scholar 

  8. 8.

    Nuinoon, M. et al. A genome-wide association identified the common genetic variants influence disease severity in beta0-thalassemia/hemoglobin E. Hum. Genet 127, 303–314 (2010).

    CAS  Article  Google Scholar 

  9. 9.

    Lettre, G. et al. DNA polymorphisms at the BCL11A, HBS1L-MYB, and beta-globin loci associate with fetal hemoglobin levels and pain crises in sickle cell disease. Proc. Natl Acad. Sci. USA 105, 11869–11874 (2008).

    CAS  Article  Google Scholar 

  10. 10.

    Torchy, M. P., Hamiche, A. & Klaholz, B. P. Structure and function insights into the NuRD chromatin remodeling complex. Cell Mol. Life Sci. 72, 2491–2507 (2015).

    CAS  Article  Google Scholar 

  11. 11.

    Millard, C. J. et al. The structure of the core NuRD repression complex provides insights into its interaction with chromatin. eLife 5, e13941 (2016).

    Article  Google Scholar 

  12. 12.

    Kransdorf, E. P. et al. MBD2 is a critical component of a methyl cytosine-binding protein complex isolated from primary erythroid cells. Blood 108, 2836–2845 (2006).

    CAS  Article  Google Scholar 

  13. 13.

    Harju-Baker, S., Costa, F. C., Fedosyuk, H., Neades, R. & Peterson, K. R. Silencing of a gamma-globin gene expression during adult definitive erythropoiesis mediated by GATA-1-FOG-1-Mi2 complex binding at the −566 GATA site. Mol. Cell Biol. 28, 3101–3113 (2008).

    CAS  Article  Google Scholar 

  14. 14.

    Rupon, J. W., Wang, S. Z., Gaensler, K., Lloyd, J. & Ginder, G. D. Methyl binding domain protein 2 mediates gamma-globin gene silencing in adult human betaYAC transgenic mice. Proc. Natl Acad. Sci. USA 103, 6617–6622 (2006).

    CAS  Article  Google Scholar 

  15. 15.

    Gnanapragasam, M. N. et al. p66Alpha-MBD2 coiled-coil interaction and recruitment of Mi-2 are critical for globin gene silencing by the MBD2-NuRD complex. Proc. Natl Acad. Sci. USA 108, 7487–7492 (2011).

    CAS  Article  Google Scholar 

  16. 16.

    Xu, J. et al. Corepressor-dependent silencing of fetal hemoglobin expression by BCL11A. Proc. Natl Acad. Sci. USA 110, 6518–6523 (2013).

    CAS  Article  Google Scholar 

  17. 17.

    Costa, F. C., Fedosyuk, H., Chazelle, A. M., Neades, R. Y. & Peterson, K. R. Mi2beta is required for gamma-globin gene silencing: temporal assembly of a GATA-1-FOG-1-Mi2 repressor complex in beta-YAC transgenic mice. PLoS Genet. 8, e1003155 (2012).

    CAS  Article  Google Scholar 

  18. 18.

    Amaya, M. et al. Mi2beta-mediated silencing of the fetal gamma-globin gene in adult erythroid cells. Blood 121, 3493–3501 (2013).

    CAS  Article  Google Scholar 

  19. 19.

    Bradner, J. E. et al. Chemical genetic strategy identifies histone deacetylase 1 (HDAC1) and HDAC2 as therapeutic targets in sickle cell disease. Proc. Natl Acad. Sci. USA 107, 12617–12622 (2010).

    CAS  Article  Google Scholar 

  20. 20.

    Esrick, E. B., McConkey, M., Lin, K., Frisbee, A. & Ebert, B. L. Inactivation of HDAC1 or HDAC2 induces gamma globin expression without altering cell cycle or proliferation. Am. J. Hematol. 90, 624–628 (2015).

    CAS  Article  Google Scholar 

  21. 21.

    Shearstone, J. R. et al. Chemical inhibition of histone deacetylases 1 and 2 induces fetal hemoglobin through activation of GATA2. PLoS ONE 11, e0153767 (2016).

    Article  Google Scholar 

  22. 22.

    Uda, M. et al. Genome-wide association study shows BCL11A associated with persistent fetal hemoglobin and amelioration of the phenotype of beta-thalassemia. Proc. Natl Acad. Sci. USA 105, 1620–1625 (2008).

    CAS  Article  Google Scholar 

  23. 23.

    Menzel, S. et al. A QTL influencing F cell production maps to a gene encoding a zinc-finger protein on chromosome 2p15. Nat. Genet. 39, 1197–1199 (2007).

    CAS  Article  Google Scholar 

  24. 24.

    Bauer, D. E. et al. An erythroid enhancer of BCL11A subject to genetic variation determines fetal hemoglobin level. Science 342, 253–257 (2013).

    CAS  Article  Google Scholar 

  25. 25.

    Liu, N. et al. Direct promoter repression by BCL11A controls the fetal to adult hemoglobin switch. Cell 173, 430–442 e17 (2018).

    CAS  Article  Google Scholar 

  26. 26.

    Sankaran, V. G. et al. Human fetal hemoglobin expression is regulated by the developmental stage-specific repressor BCL11A. Science 322, 1839–1842 (2008).

    CAS  Article  Google Scholar 

  27. 27.

    Thein, S. L. et al. Intergenic variants of HBS1L-MYB are responsible for a major quantitative trait locus on chromosome 6q23 influencing fetal hemoglobin levels in adults. Proc. Natl Acad. Sci. USA 104, 11346–11351 (2007).

    CAS  Article  Google Scholar 

  28. 28.

    Sankaran, V. G. et al. Developmental and species-divergent globin switching are driven by BCL11A. Nature 460, 1093–1097 (2009).

    CAS  Article  Google Scholar 

  29. 29.

    Sankaran, V. G. et al. A functional element necessary for fetal hemoglobin silencing. N. Engl. J. Med. 365, 807–814 (2011).

    CAS  Article  Google Scholar 

  30. 30.

    Xu, J. et al. Transcriptional silencing of {gamma}-globin by BCL11A involves long-range interactions and cooperation with SOX6. Genes Dev. 24, 783–798 (2010).

    CAS  Article  Google Scholar 

  31. 31.

    Yi, Z. et al. Sox6 directly silences epsilon globin expression in definitive erythropoiesis. PLoS Genet. 2, e14 (2006).

    Article  Google Scholar 

  32. 32.

    Xu, J. et al. Correction of sickle cell disease in adult mice by interference with fetal hemoglobin silencing. Science 334, 993–996 (2011).

    CAS  Article  Google Scholar 

  33. 33.

    Masuda, T. et al. Transcription factors LRF and BCL11A independently repress expression of fetal hemoglobin. Science 351, 285–289 (2016).

    CAS  Article  Google Scholar 

  34. 34.

    Schoonenberg, V. A. C. et al. CRISPRO: identification of functional protein coding sequences based on genome editing dense mutagenesis. Genome Biol. 19, 169 (2018).

    Article  Google Scholar 

  35. 35.

    Aguirre, A. J. et al. Genomic copy number dictates a gene-independent cell response to CRISPR/Cas9 targeting. Cancer Discov. 6, 914–929 (2016).

    CAS  Article  Google Scholar 

  36. 36.

    Munoz, D. M. et al. CRISPR screens provide a comprehensive assessment of cancer vulnerabilities but generate false-positive hits for highly amplified genomic regions. Cancer Discov. 6, 900–913 (2016).

    CAS  Article  Google Scholar 

  37. 37.

    Morgens, D. W., Deans, R. M., Li, A. & Bassik, M. C. Systematic comparison of CRISPR/Cas9 and RNAi screens for essential genes. Nat. Biotechnol. 34, 634–636 (2016).

    CAS  Article  Google Scholar 

  38. 38.

    Morgens, D. W. et al. Genome-scale measurement of off-target activity using Cas9 toxicity in high-throughput screens. Nat. Commun. 8, 15178 (2017).

    CAS  Article  Google Scholar 

  39. 39.

    Laurent, J. M. et al. Protein abundances are more conserved than mRNA abundances across diverse taxa. Proteomics 10, 4209–4212 (2010).

    CAS  Article  Google Scholar 

  40. 40.

    Vogel, C. & Marcotte, E. M. Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat. Rev. Genet 13, 227–232 (2012).

    CAS  Article  Google Scholar 

  41. 41.

    Gautier, E. F. et al. Comprehensive proteomic analysis of human erythropoiesis. Cell Rep. 16, 1470–1484 (2016).

    CAS  Article  Google Scholar 

  42. 42.

    Shi, J. et al. Discovery of cancer drug targets by CRISPR-Cas9 screening of protein domains. Nat. Biotechnol. 33, 661–667 (2015).

    CAS  Article  Google Scholar 

  43. 43.

    Torrado, M. et al. Refinement of the subunit interaction network within the nucleosome remodelling and deacetylase (NuRD) complex. FEBS J. 284, 4216–4232 (2017).

    CAS  Article  Google Scholar 

  44. 44.

    Scarsdale, J. N., Webb, H. D., Ginder, G. D. & Williams, D. C. Jr. Solution structure and dynamic analysis of chicken MBD2 methyl binding domain bound to a target-methylated DNA sequence. Nucleic Acids Res. 39, 6741–6752 (2011).

    CAS  Article  Google Scholar 

  45. 45.

    Liu, K. et al. Structural basis for the ability of MBD domains to bind methyl-CG and TG sites in DNA. J. Biol. Chem. 293, 7344–7354 (2018).

    CAS  Article  Google Scholar 

  46. 46.

    Lauffer, B. E. et al. Histone deacetylase (HDAC) inhibitor kinetic rate constants correlate with cellular histone acetylation but not transcription and cell viability. J. Biol. Chem. 288, 26926–26943 (2013).

    CAS  Article  Google Scholar 

  47. 47.

    Kumar, R. & Wang, R. A. Structure, expression and functions of MTA genes. Gene 582, 112–121 (2016).

    CAS  Article  Google Scholar 

  48. 48.

    Yang, N. & Xu, R. M. Structure and function of the BAH domain in chromatin biology. Crit. Rev. Biochem. Mol. Biol. 48, 211–221 (2013).

    CAS  Article  Google Scholar 

  49. 49.

    Ding, Z., Gillespie, L. L. & Paterno, G. D. Human MI-ER1 alpha and beta function as transcriptional repressors by recruitment of histone deacetylase 1 to their conserved ELM2 domain. Mol. Cell Biol. 23, 250–258 (2003).

    CAS  Article  Google Scholar 

  50. 50.

    Wang, X. et al. SMARCB1-mediated SWI/SNF complex function is essential for enhancer regulation. Nat. Genet. 49, 289–295 (2017).

    CAS  Article  Google Scholar 

  51. 51.

    Low, J. K. et al. CHD4 is a peripheral component of the nucleosome remodeling and deacetylase complex. J. Biol. Chem. 291, 15853–15866 (2016).

    CAS  Article  Google Scholar 

  52. 52.

    Demaison, C. et al. High-level transduction and gene expression in hematopoietic repopulating cells using a human immunodeficiency [correction of imunodeficiency] virus type 1-based lentiviral vector containing an internal spleen focus forming virus promoter. Hum. Gene Ther. 13, 803–813 (2002).

    CAS  Article  Google Scholar 

  53. 53.

    Esrick, E. B. & Bauer, D. E. Genetic therapies for sickle cell disease. Semin. Hematol. 55, 76–86 (2018).

    Article  Google Scholar 

  54. 54.

    Kurita, R. et al. Establishment of immortalized human erythroid progenitor cell lines able to produce enucleated red blood cells. PLoS One 8, e59890 (2013).

    CAS  Article  Google Scholar 

  55. 55.

    Canver, M. C. et al. BCL11A enhancer dissection by Cas9-mediated in situ saturating mutagenesis. Nature 527, 192–197 (2015).

    CAS  Article  Google Scholar 

  56. 56.

    Wu, Y. et al. Highly efficient therapeutic gene editing of human hematopoietic stem cells. Nat. Med. 25, 776–783 (2019).

    CAS  Article  Google Scholar 

  57. 57.

    Shalem, O. et al. Genome-scale CRISPR-Cas9 knockout screening in human cells. Science 343, 84–87 (2014).

    CAS  Article  Google Scholar 

  58. 58.

    Sanjana, N. E., Shalem, O. & Zhang, F. Improved vectors and genome-wide libraries for CRISPR screening. Nat. Methods 11, 783–784 (2014).

    CAS  Article  Google Scholar 

  59. 59.

    Chen, S. et al. Genome-wide CRISPR screen in a mouse model of tumor growth and metastasis. Cell 160, 1246–1260 (2015).

    CAS  Article  Google Scholar 

  60. 60.

    Doench, J. G. et al. Rational design of highly active sgRNAs for CRISPR-Cas9-mediated gene inactivation. Nat. Biotechnol. 32, 1262–1267 (2014).

    CAS  Article  Google Scholar 

  61. 61.

    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  Google Scholar 

  62. 62.

    Cock, P. J. et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics 25, 1422–1423 (2009).

    CAS  Article  Google Scholar 

  63. 63.

    Cifani, P. & Kentsis, A. High sensitivity quantitative proteomics using automated multidimensional nano-flow chromatography and accumulated ion monitoring on quadrupole-orbitrap-linear ion trap mass spectrometer. Mol. Cell Proteom. 16, 2006–2016 (2017).

    CAS  Article  Google Scholar 

  64. 64.

    Cox, J. et al. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol. Cell Proteom. 13, 2513–2526 (2014).

    CAS  Article  Google Scholar 

  65. 65.

    Kim, D. I. et al. An improved smaller biotin ligase for BioID proximity labeling. Mol. Biol. Cell 27, 1188–1196 (2016).

    CAS  Article  Google Scholar 

  66. 66.

    Seruggia, D., Fernandez, A., Cantero, M., Pelczar, P. & Montoliu, L. Functional validation of mouse tyrosinase non-coding regulatory DNA elements by CRISPR-Cas9-mediated mutagenesis. Nucleic Acids Res. 43, 4855–4867 (2015).

    CAS  Article  Google Scholar 

  67. 67.

    Harms, D. W. et al. Mouse genome editing using the CRISPR/Cas system. Curr. Protoc. Hum. Genet. 83, 1–27 (2014).

    Google Scholar 

  68. 68.

    Pinello, L. et al. Analyzing CRISPR genome-editing experiments with CRISPResso. Nat. Biotechnol. 34, 695–697 (2016).

    CAS  Article  Google Scholar 

Download references


We thank X. Wang, C. Brendel, E. C. Smith, A. Gutierrez, G. D. Ginder and D. C. Williams for useful discussions and J. Desimini for graphical assistance. V.A.C.S. was supported by an Individual Travel Grant (ITG) from Radboud University. D.S.V. was supported by the Cooley’s Anemia Foundation. L.M.K.D. was supported by NHLBI (no. 5T32HL007574-36) and a Burroughs Wellcome Fund Postdoctoral Enrichment Grant (PDEP 1015098). S.A.W. and K.L. were supported by NIAID (no. R01AI117839) and NIGMS (no. R01GM115911). L.P. was supported by a National Human Genome Research Institute (NHGRI) Career Development Award (no. R00HG008399). T.M. was supported by NIH (no. 5R01DK111455) and JSPS Grant-in-Aid for Scientific Research A (no. 17H01567). A.K. is the Damon Runyon-Richard Lumsden Foundation Clinical Investigator and acknowledges support of the St. Baldrick’s Arceci Innovation Award, and NCI grant nos. R01 CA204396 and P30 CA008748. Generation of the mouse model was supported by a NIDDK Cooperative Centers of Excellence in Hematology (CCEH) award (no. U54DK110805) to S.H.O. S.H.O. was supported by the Doris Duke Charitable Foundation and is an Investigator of the Howard Hughes Medical Institute. D.E.B. was supported by NIDDK (grant nos. K08DK093705 and R03DK109232), NHLBI (nos. DP2OD022716 and P01HL032262), the Doris Duke Charitable Foundation, Burroughs Wellcome Fund, the American Society of Hematology and an Epigenetics Seed Grant from Harvard Medical School.

Author information




F.S., T.M. and D.E.B. conceptualized the study. F.S., M.H., D.S., L.P., T.M., A.K., S.H.S. and D.E.B. provided methodology. V.A.C.S., M.A.C., Q.Y., C.M.T., P.G.S., M.C.C., L.P. and D.E.B. provided software. F.S., M.H., D.S., D.S.V., C.R., P.C., L.M.K.D., K.L., C.M.G. and Y.F. validated the project. F.S., V.A.C.S., Q.Y., M.A.C., L.P., T.M., A.K., S.H.O. and D.E.B. performed formal analysis. F.S., M.H., D.S., D.S.V., L.M.K.D., C.R., C.M.G. and Y.F. were investigators. C.R., K.L., R.K., Y.N., S.A.W., L.P., T.M., A.K., S.H.O. and D.E.B. provided resources. F.S., M.H., D.S., Q.Y. and D.E.B. curated data. F.S. and D.E.B. wrote the original draft. All authors reviewed and edited the article. F.S., M.H., D.S., V.A.C.S., M.A.C., Q.Y. and D.E.B. provided visualization. L.P., T.M., A.K., S.H.O. and D.E.B. supervised the research. D.E.B. was the project administrator. T.M., A.K., S.H.O. and D.E.B acquired funding.

Corresponding author

Correspondence to Daniel E. Bauer.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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

Supplementary information

Supplementary Information

Supplementary Note and Supplementary Figs. 1–9

Reporting Summary

Supplementary Table 1

Quantitative analysis of mass spectrometery data.

Supplementary Table 2

Functional scores of CRISPR library (all sgRNAs) against various protein-level sequence annotations.

Supplementary Table 3

List of oligonucleotides and PCR primer sequences used in the study.

Supplementary Table 4

Key resources.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Sher, F., Hossain, M., Seruggia, D. et al. Rational targeting of a NuRD subcomplex guided by comprehensive in situ mutagenesis. Nat Genet 51, 1149–1159 (2019). https://doi.org/10.1038/s41588-019-0453-4

Download citation

Further reading