4.7 Article

The spatial binding model of the pioneer factor Oct4 with its target genes during cell reprogramming

Journal

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
Volume 17, Issue -, Pages 1226-1233

Publisher

ELSEVIER
DOI: 10.1016/j.csbj.2019.09.002

Keywords

Spatial binding pattern; Cell reprogramming; Pioneer factor; Multivariate linear regression

Funding

  1. National Nature Scientific Foundation of China [61561036, 61702290]
  2. Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region [NJYT-18-B01]
  3. Fund for Excellent Young Scholars of Inner Mongolia [2017JQ04]
  4. Student's Platform for Innovation and Entrepreneurship Training Program of Inner Mongolia University [201714298]

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Understanding the target regulation between pioneer factor and its binding genes is crucial for improving the efficiency of TF-mediated reprogramming. Oct4 as the only one factor that cannot be substituted by other POU members, it is urgent need to develop a quantitative model for describing the spatial binding pattern with its target genes. The dynamic profiles of pioneer factor Oct4-binding showed that the major wave occurs at the intermediate stage of cell reprogramming (from day 7 to day 15), and the promoter is the preferred targeting regions. The Oct4-binding distributions perform significant chromosome bias. The overall enrichment on chromosome 1-11 is higher than that on the others. The dramatic event of TF-mediated reprogramming is mainly concentrated on autosomes. We also found that the spatial binding ability of Oct4 binding can be represented quantitatively by using three parameters of peaks (height, width and distance). The dynamic changes of Oct4-binding demonstrated that the width play more important roles in regulating expression of target genes. At last, a multivariate linear regression was introduced to establish the spatial binding model of the Oct4-binding. The evaluation results confirmed that the height and width is positively correlated with the gene expression. And the additive interaction terms of height and width can better optimize the model performance than the multiplicative terms. The best average coefficients of determination of improved model achieved to 81.38%. Our study will provide new insights into the cooperative regulation of spatial binding pattern of pioneer factors in cell reprogramming. (C) 2019 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.

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