Expanding the repertoire of DNA shape features for genome-scale studies of transcription factor binding.
Expanding the repertoire of DNA shape features for genome-scale studies of transcription factor binding.
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DOI：
10.1093/nar/gkx1145
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发表时间：
2017-12-15
影响因子：
14.9
通讯作者：
Rohs R
中科院分区：
文献类型：
--
作者：
Li J;Sagendorf JM;Chiu TP;Pasi M;Perez A;Rohs R
揭示影响转录因子（tf）结合特异性的机制对于理解基因调控的原理至关重要。虽然基于序列的模型已经成功地用于预测TF结合特异性，但我们发现在这些模型中包含DNA形状信息可以提高其准确性和可解释性。此前，我们开发了一种基于从蒙特卡罗（MC）模拟中提取的DNA形状特征来建模DNA结合特异性的方法。然而，我们的模型的预测精度尚未与从x射线晶体学（XRC）数据或分子动力学（MD）模拟中提取DNA形状信息的模型的精度进行比较。在这里，我们将从MC或MD模拟和XRC数据中提取的DNA形状信息整合到TF结合的预测模型中，并比较了它们的性能。无论数据源如何，与基于序列的模型相比，包含结构信息的模型始终显示出更高的性能。此外，我们推导并验证了九个额外的DNA形状特征，超出了我们最初的四个特征集。扩展的13种不同的DNA形状特征，包括6个碱基对内和6个碱基对间参数和小槽宽度，可在我们的R/Bioconductor包DNAshapeR中获得，并能够在全基因组范围内对双螺旋进行全面的结构描述。
Uncovering the mechanisms that affect the binding specificity of transcription factors (TFs) is critical for understanding the principles of gene regulation. Although sequence-based models have been used successfully to predict TF binding specificities, we found that including DNA shape information in these models improved their accuracy and interpretability. Previously, we developed a method for modeling DNA binding specificities based on DNA shape features extracted from Monte Carlo (MC) simulations. Prediction accuracies of our models, however, have not yet been compared to accuracies of models incorporating DNA shape information extracted from X-ray crystallography (XRC) data or Molecular Dynamics (MD) simulations. Here, we integrated DNA shape information extracted from MC or MD simulations and XRC data into predictive models of TF binding and compared their performance. Models that incorporated structural information consistently showed improved performance over sequence-based models regardless of data source. Furthermore, we derived and validated nine additional DNA shape features beyond our original set of four features. The expanded repertoire of 13 distinct DNA shape features, including six intra-base pair and six inter-base pair parameters and minor groove width, is available in our R/Bioconductor package DNAshapeR and enables a comprehensive structural description of the double helix on a genome-wide scale.
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DOI：
10.1093/bioinformatics/btx336
发表时间：
2017-10-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
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作者：
Ma W;Yang L;Rohs R;Noble WS
通讯作者：
Noble WS
影响因子：
14.9
作者：
Peng PC;Sinha S
通讯作者：
Sinha S
影响因子：
46.9
作者：
Berger, Michael F.;Philippakis, Anthony A.;Bulyk, Martha L.
通讯作者：
Bulyk, Martha L.
影响因子：
3.4
作者：
BERMAN, HM;OLSON, WK;SCHNEIDER, B
通讯作者：
SCHNEIDER, B
DOI：
10.1093/bioinformatics/btv735
发表时间：
2016-04-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Chiu TP;Comoglio F;Zhou T;Yang L;Paro R;Rohs R
通讯作者：
Rohs R