Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California, United States of America.
Stanford Institute for Theoretical Physics, Stanford University, Stanford, California, United States of America.
PLoS Comput Biol. 2022 Aug 30;18(8):e1010378. doi: 10.1371/journal.pcbi.1010378. eCollection 2022 Aug.
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.
我们提出了 WhichTF，这是一种从染色质可及性测量中识别功能重要的转录因子 (TF) 的计算方法。为了对 TF 进行排名，WhichTF 应用了一种基于本体论的功能方法，通过整合可及性测量、高可信度预先计算的保守感知 TF 结合位点和假定的基因调控模型来计算新的富集。与之前纯粹基于丰度的方法相比，WhichTF 具有独特的能力，可以识别具有功能相关性的特定于上下文的 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景观，我们应用差异分析并证明其在淋巴细胞、中胚层发育和疾病细胞中的实用性。我们发现了一些有提示性但特征不明显的 TF，例如中胚层发育中的 RUNX3 和系统性红斑狼疮中的 GLI1。我们还发现了已知的应激反应 TF，这表明常规的实验注意事项值得仔细考虑。WhichTF 提供了对 TF 介导的转录调控在不同背景下的已知和新的分子机制的生物学见解，包括人类和小鼠细胞类型、细胞命运轨迹和与疾病相关的细胞。
