Transcription-associated DNA DSBs activate p53 during hiPSC-based neurogenesis

Abstract

Neurons are overproduced during cerebral cortical development. Neural progenitor cells (NPCs) divide rapidly and incur frequent DNA double-strand breaks (DSBs) throughout cortical neurogenesis. Although half of the neurons born during neurodevelopment die, many neurons with inaccurate DNA repair survive leading to brain somatic mosaicism. Recurrent DNA DSBs during neurodevelopment are associated with both gene expression level and gene length. We used imaging flow cytometry and a genome-wide DNA DSB capture approach to quantify and map DNA DSBs during human induced pluripotent stem cell (hiPSC)-based neurogenesis. Reduced p53 signaling was brought about by knockdown (p53KD); p53KD led to elevated DNA DSB burden in neurons that was associated with gene expression level but not gene length in neural progenitor cells (NPCs). Furthermore, DNA DSBs incurred from transcriptional, but not replicative, stress lead to p53 activation in neurotypical NPCs. In p53KD NPCs, DNA DSBs accumulate at transcription start sites of genes that are associated with neurological and psychiatric disorders. These findings add to a growing understanding of how neuronal genome dynamics are engaged by high transcriptional or replicative burden during neurodevelopment.

DNA fragility at topologically associated domain boundaries is promoted by alternative DNA secondary structure and topoisomerase II activity

“…High-throughput sequencing data used in this study were downloaded from Gene Expression Omnibus through Sequence Read Archive or from the ENCODE project ( 45 ); all datasets used in this study are listed in Supplementary Table S3 . The publicly available RNA sequencing (RNA-seq) data from HeLa ( 46 ), GM12878 ( 47 ), MCF10A ( 48 ) and NPCs ( 49 ) were aligned to the GRCh38/hg38 genome using HISAT2 aligner ( 50 ), and the gene expression [fragments per kilobase million (FPKM) values] was quantified using StringTie ( 51 ). The RNA-seq data from Jurkat cells generated from this study were aligned to the same human genome assembly using STAR aligner (v. 2.7.9) with RefGene annotation, downloaded from the University of California, Santa Cruz (UCSC) browser, and transcript quantification was performed with RSEM (v. 1.3.0) ( 52 , 53 ).…”