4.7 Article

Analysis of functional importance of binding sites in the Drosophila gap gene network model

期刊

BMC GENOMICS
卷 16, 期 -, 页码 -

出版社

BMC
DOI: 10.1186/1471-2164-16-S13-S7

关键词

transcription; thermodynamics; reaction-diffusion; drosophila

资金

  1. RFBR [13-01-00405]
  2. RSCF [14-14-00302]
  3. Dynasty Foundation Fellowship
  4. Russian Science Foundation [14-14-00302] Funding Source: Russian Science Foundation

向作者/读者索取更多资源

Background The statistical thermodynamics based approach provides a promising framework for construction of the genotype-phenotype map in many biological systems. Among important aspects of a good model connecting the DNA sequence information with that of a molecular phenotype (gene expression) is the selection of regulatory interactions and relevant transcription factor bindings sites. As the model may predict different levels of the functional importance of specific binding sites in different genomic and regulatory contexts, it is essential to formulate and study such models under different modeling assumptions. Results We elaborate a two-layer model for the Drosophila gap gene network and include in the model a combined set of transcription factor binding sites and concentration dependent regulatory interaction between gap genes hunchback and Kruppel. We show that the new variants of the model are more consistent in terms of gene expression predictions for various genetic constructs in comparison to previous work. We quantify the functional importance of binding sites by calculating their impact on gene expression in the model and calculate how these impacts correlate across all sites under different modeling assumptions. Conclusions The assumption about the dual interaction between hb and Kr leads to the most consistent modeling results, but, on the other hand, may obscure existence of indirect interactions between binding sites in regulatory regions of distinct genes. The analysis confirms the previously formulated regulation concept of many weak binding sites working in concert. The model predicts a more or less uniform distribution of functionally important binding sites over the sets of experimentally characterized regulatory modules and other open chromatin domains.

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