A DNA shape-based regulatory score improves position-weight matrix-based recognition of transcription factor binding sites
A DNA shape-based regulatory score improves position-weight matrix-based recognition of transcription factor binding sites
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DOI：
10.1093/bioinformatics/btv391
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发表时间：
2015-11
期刊：
影响因子：
5.8
通讯作者：
Jichen Yang;S. Ramsey
中科院分区：
文献类型：
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作者：
Jichen Yang;S. Ramsey
位置权重矩阵（PWM）是转录因子结合位点（TFBS）序列模式的有用表示，因为PWM可以从少量代表性TFBS序列估计。然而，由于PWM概率模型假设各个核苷酸位置之间的独立性，因此一些TF的PWM很难区分具有相似序列内容的结合位点与非结合位点。由于局部三维DNA结构（“形状”）是TF结合特异性的决定因素，并且由于DNA形状具有显著的序列依赖性，因此我们将DNA形状衍生的特征组合成TF广义调节评分，并测试该评分是否可以改善基于PWM的TFBS与非结合位点的区分。结果：我们比较了传统的PWM模型与PWM与基于DNA形状特征的调控潜力评分相结合的模型，以准确检测75种脊椎动物转录因子的结合位点。PWM+形状模型比仅PWM模型更准确，对于45%的测试TF，其余TF的准确性没有显著损失。可用性和实现基于形状的模型可以作为开源R包在上获得，该包在GitHub软件存储库https://github.com/ramseylab/regshape/上存档。oregonstate.edu补充数据可在生物信息学在线获得。
MOTIVATION The position-weight matrix (PWM) is a useful representation of a transcription factor binding site (TFBS) sequence pattern because the PWM can be estimated from a small number of representative TFBS sequences. However, because the PWM probability model assumes independence between individual nucleotide positions, the PWMs for some TFs poorly discriminate binding sites from non-binding-sites that have similar sequence content. Since the local three-dimensional DNA structure ('shape') is a determinant of TF binding specificity and since DNA shape has a significant sequence-dependence, we combined DNA shape-derived features into a TF-generalized regulatory score and tested whether the score could improve PWM-based discrimination of TFBS from non-binding-sites. RESULTS We compared a traditional PWM model to a model that combines the PWM with a DNA shape feature-based regulatory potential score, for accuracy in detecting binding sites for 75 vertebrate transcription factors. The PWM+shape model was more accurate than the PWM-only model, for 45% of TFs tested, with no significant loss of accuracy for the remaining TFs. AVAILABILITY AND IMPLEMENTATION The shape-based model is available as an open-source R package at that is archived on the GitHub software repository at https://github.com/ramseylab/regshape/. CONTACT stephen.ramsey@oregonstate.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.