Predicting AID off-targets: A step forward.

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.