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Exploiting genetic variation to uncover rules of transcription factor binding and chromatin accessibility

Author

Listed:
  • Vivek Behera

    (University of Pennsylvania)

  • Perry Evans

    (Children’s Hospital of Philadelphia)

  • Carolyne J. Face

    (Children’s Hospital of Philadelphia)

  • Nicole Hamagami

    (Children’s Hospital of Philadelphia)

  • Laavanya Sankaranarayanan

    (Children’s Hospital of Philadelphia)

  • Cheryl A. Keller

    (Penn State University)

  • Belinda Giardine

    (Penn State University)

  • Kai Tan

    (Children’s Hospital of Philadelphia)

  • Ross C. Hardison

    (Penn State University)

  • Junwei Shi

    (University of Pennsylvania)

  • Gerd A. Blobel

    (Children’s Hospital of Philadelphia)

Abstract

Single-nucleotide variants that underlie phenotypic variation can affect chromatin occupancy of transcription factors (TFs). To delineate determinants of in vivo TF binding and chromatin accessibility, we introduce an approach that compares ChIP-seq and DNase-seq data sets from genetically divergent murine erythroid cell lines. The impact of discriminatory single-nucleotide variants on TF ChIP signal enables definition at single base resolution of in vivo binding characteristics of nuclear factors GATA1, TAL1, and CTCF. We further develop a facile complementary approach to more deeply test the requirements of critical nucleotide positions for TF binding by combining CRISPR-Cas9-mediated mutagenesis with ChIP and targeted deep sequencing. Finally, we extend our analytical pipeline to identify nearby contextual DNA elements that modulate chromatin binding by these three TFs, and to define sequences that impact kb-scale chromatin accessibility. Combined, our approaches reveal insights into the genetic basis of TF occupancy and their interplay with chromatin features.

Suggested Citation

  • Vivek Behera & Perry Evans & Carolyne J. Face & Nicole Hamagami & Laavanya Sankaranarayanan & Cheryl A. Keller & Belinda Giardine & Kai Tan & Ross C. Hardison & Junwei Shi & Gerd A. Blobel, 2018. "Exploiting genetic variation to uncover rules of transcription factor binding and chromatin accessibility," Nature Communications, Nature, vol. 9(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-03082-6
    DOI: 10.1038/s41467-018-03082-6
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    Cited by:

    1. Hillary Koch & Cheryl A. Keller & Guanjue Xiang & Belinda Giardine & Feipeng Zhang & Yicheng Wang & Ross C. Hardison & Qunhua Li, 2022. "CLIMB: High-dimensional association detection in large scale genomic data," Nature Communications, Nature, vol. 13(1), pages 1-15, December.

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