WhichTF is functionally important in your open chromatin data?
WhichTF is functionally important in your open chromatin data?
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DOI：
10.1371/journal.pcbi.1010378
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发表时间：
2022-08
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
--
作者：
我们提出了WhichTF，一种从染色质可及性测量中识别功能重要转录因子(TF)的计算方法。为了对TF进行排名，WhichTF应用了本体论指导的功能方法来计算新的富集物，方法是整合可及性测量、高度可信的预先计算的保守的TF结合位点和假定的基因调控模型。与以往纯粹基于丰度的方法相比，WhichTF具有独特的能力来识别与功能相关的上下文特定的TF，包括淋巴细胞中的NF-κB家族成员和心肌细胞中的GATA因子。为了区分密切相关样本中的转录调控格局，我们应用了差异分析，并证明了它在淋巴细胞、中胚层发育和疾病细胞中的作用。我们发现有提示意义的、特征不足的转录因子，如中胚层发育的RUNX3和系统性红斑狼疮的GLI1。我们还发现了以压力反应著称的TF，提出了值得仔细考虑的常规实验警告。WhichTF在不同的背景下，包括人类和小鼠的细胞类型、细胞命运轨迹和疾病相关细胞，对TF介导的转录调控的已知和新的分子机制提供了生物学见解。转录因子(转录因子)是一类DNA结合蛋白，调节特定组织和细胞类型的基因表达。确定特定细胞环境中的关键转录因子有助于研究发育、分化和疾病的分子调控机制。因为有1500多个人类转录因子，所以对所有转录因子全基因组占有率的实验测量一直是具有挑战性的。虽然计算方法发挥了关键作用，但大多数现有的方法依赖于统计丰富，要么专注于TF识别的序列基序相似性，要么关注感兴趣的基因组区域与先前表征的TF占有率的相似性。在这里，我们建议WhichTF作为一种替代方案，整合来自本体的精选生物医学知识，并将其与用户提供的感兴趣基因组区域中保守的TF结合位点的高置信度预测相结合。我们开发了一种新的WhichTF评分来对TF进行排名，并证明了它在人类和小鼠细胞类型、细胞分化轨迹和疾病相关细胞中的适用性。
We present WhichTF, a computational method to identify functionally important transcription factors (TFs) from chromatin accessibility measurements. To rank TFs, WhichTF applies an ontology-guided functional approach to compute novel enrichment by integrating accessibility measurements, high-confidence pre-computed conservation-aware TF binding sites, and putative gene-regulatory models. Comparison with prior sheer abundance-based methods reveals the unique ability of WhichTF to identify context-specific TFs with functional relevance, including NF-κB family members in lymphocytes and GATA factors in cardiac cells. To distinguish the transcriptional regulatory landscape in closely related samples, we apply differential analysis and demonstrate its utility in lymphocyte, mesoderm developmental, and disease cells. We find suggestive, under-characterized TFs, such as RUNX3 in mesoderm development and GLI1 in systemic lupus erythematosus. We also find TFs known for stress response, suggesting routine experimental caveats that warrant careful consideration. WhichTF yields biological insight into known and novel molecular mechanisms of TF-mediated transcriptional regulation in diverse contexts, including human and mouse cell types, cell fate trajectories, and disease-associated cells. Transcription factors (TFs), a class of DNA binding proteins, regulate tissue- and cell-type-specific expression of genes. Identifying the critical TFs in a given cellular context leads to investigating molecular regulatory mechanisms in development, differentiation, and disease. Because there are more than 1,500 human TFs, experimental measurements of genome-wide occupancy across all TFs have been challenging. While computational approaches play pivotal roles, most existing methods rely on statistical enrichment, focusing either on sequence motif similarity recognized by TFs or the similarity of the genomic region of interest with the previously characterized TF occupancy profile. Here we propose WhichTF as an alternative, incorporating curated biomedical knowledge from ontology and integrating it with the high-confidence prediction of conserved TF binding sites in user-provided genomic regions of interest. We develop a new WhichTF score to rank TFs and demonstrate its applicability across human and mouse cell types, cellular differentiation trajectories, and disease-associated cells.
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影响因子：
4.6
作者：
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通讯作者：
Burns, C. Geoffrey
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作者：
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通讯作者：
Pritchard, Jonathan K.