Transcription Factor Binding Affinities and DNA Shape Readout
نویسندگان
چکیده
منابع مشابه
DNA sequence correlations shape nonspecific transcription factor-DNA binding affinity.
Transcription factors (TFs) are regulatory proteins that bind DNA in promoter regions of the genome and either promote or repress gene expression. Here, we predict analytically that enhanced homooligonucleotide sequence correlations, such as poly(dA:dT) and poly(dC:dG) tracts, statistically enhance nonspecific TF-DNA binding affinity. This prediction is generic and qualitatively independent of ...
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DNA binding specificities of transcription factors (TFs) are a key component of gene regulatory processes. Underlying mechanisms that explain the highly specific binding of TFs to their genomic target sites are poorly understood. A better understanding of TF-DNA binding requires the ability to quantitatively model TF binding to accessible DNA as its basic step, before additional in vivo compone...
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Accurately modeling the DNA sequence preferences of transcription factors (TFs), and using these models to predict in vivo genomic binding sites for TFs, are key pieces in deciphering the regulatory code. These efforts have been frustrated by the limited availability and accuracy of TF binding site motifs, usually represented as position-specific scoring matrices (PSSMs), which may match large ...
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Transcription factors (TFs) achieve DNA-binding specificity through contacts with functional groups of bases (base readout) and readout of structural properties of the double helix (shape readout). Currently, it remains unclear whether DNA shape readout is utilized by only a few selected TF families, or whether this mechanism is used extensively by most TF families. We resequenced data from pre...
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Recent experimental and theoretical efforts have highlighted the fact that binding of transcription factors to DNA can be more accurately described by continuous measures of their binding affinities, rather than a discrete description in terms of binding sites. While the binding affinities can be predicted from a physical model, it is often desirable to know the distribution of binding affiniti...
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ژورنال
عنوان ژورنال: iScience
سال: 2020
ISSN: 2589-0042
DOI: 10.1016/j.isci.2020.101694