Institut Necker-Enfants Malades, INSERM U1151-CNRS UMR 8253, Faculté de Médecine Paris Descartes, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.
J Exp Med. 2018 Mar 5;215(3):721-722. doi: 10.1084/jem.20180231. Epub 2018 Feb 15.
In this issue of JEM, Álvarez-Prado et al. (https://doi.org/10.1084/jem.20171738) designed a DNA capture library allowing them to identify 275 genes targeted by AID in mouse germinal center B cells. Using the molecular features of these genes to feed a machine-learning algorithm, they determined that high-density RNA PolII and Spt5 binding-found in 2.3% of the genes-are the best predictors of AID specificity.
在本期《实验医学杂志》中，Álvarez-Prado 等人（https://doi.org/10.1084/jem.20171738）设计了一种 DNA 捕获文库，使他们能够鉴定出在小鼠生发中心 B 细胞中被 AID 靶向的 275 个基因。他们利用这些基因的分子特征来为机器学习算法提供信息，确定了高密 RNA PolII 和 Spt5 结合——在 2.3%的基因中发现——是 AID 特异性的最佳预测因子。
