AIRE relies on Z-DNA to flag gene targets for thymic T cell tolerization.
Yuan FangKushagra BansalSara MostafaviChristophe BenoistDiane MathisPublished in: Nature (2024)
AIRE is an unconventional transcription factor that enhances the expression of thousands of genes in medullary thymic epithelial cells and promotes clonal deletion or phenotypic diversion of self-reactive T cells 1-4 . The biological logic of AIRE's target specificity remains largely unclear as, in contrast to many transcription factors, it does not bind to a particular DNA sequence motif. Here we implemented two orthogonal approaches to investigate AIRE's cis-regulatory mechanisms: construction of a convolutional neural network and leveraging natural genetic variation through analysis of F1 hybrid mice 5 . Both approaches nominated Z-DNA and NFE2-MAF as putative positive influences on AIRE's target choices. Genome-wide mapping studies revealed that Z-DNA-forming and NFE2L2-binding motifs were positively associated with the inherent ability of a gene's promoter to generate DNA double-stranded breaks, and promoters showing strong double-stranded break generation were more likely to enter a poised state with accessible chromatin and already-assembled transcriptional machinery. Consequently, AIRE preferentially targets genes with poised promoters. We propose a model in which Z-DNA anchors the AIRE-mediated transcriptional program by enhancing double-stranded break generation and promoter poising. Beyond resolving a long-standing mechanistic conundrum, these findings suggest routes for manipulating T cell tolerance.
Keyphrases
- transcription factor
- genome wide
- circulating tumor
- genome wide identification
- cell free
- dna methylation
- single molecule
- nucleic acid
- gene expression
- binding protein
- dna binding
- convolutional neural network
- copy number
- magnetic resonance
- poor prognosis
- circulating tumor cells
- magnetic resonance imaging
- single cell
- metabolic syndrome
- insulin resistance
- high resolution
- oxidative stress
- deep learning
- high fat diet induced