Formation of G-quadruplex (G4) DNA structures in key regulatory regions in the genome has emerged as a secondary structure-based epigenetic mechanism for regulating multiple biological processes including transcription, replication, and telomere maintenance. G4 formation (folding), stabilization, and unfolding must be regulated to coordinate G4-mediated biological functions; however, how cells regulate the spatiotemporal formation of G4 structures in the genome is largely unknown. Here, we demonstrate that endogenous oxidized guanine bases in G4 sequences and the subsequent activation of the base excision repair (BER) pathway drive the spatiotemporal formation of G4 structures in the genome. Genome-wide mapping of occurrence of Apurinic/apyrimidinic (AP) site damage, binding of BER proteins, and G4 structures revealed that oxidized base-derived AP site damage and binding of OGG1 and APE1 are predominant in G4 sequences. Loss of APE1 abrogated G4 structure formation in cells, which suggests an essential role of APE1 in regulating the formation of G4 structures in the genome. Binding of APE1 to G4 sequences promotes G4 folding, and acetylation of APE1, which enhances its residence time, stabilizes G4 structures in cells. APE1 subsequently facilitates transcription factor loading to the promoter, providing mechanistic insight into the role of APE1 in G4-mediated gene expression. Our study unravels a role of endogenous oxidized DNA bases and APE1 in controlling the formation of higher-order DNA secondary structures to regulate transcription beyond its well-established role in safeguarding the genomic integrity.
Pancreatic ductal adenocarcinoma (PDAC), one of the most aggressive types of cancer, is characterized by aberrant activity of oncogenic KRAS. A nuclease-hypersensitive GC-rich region in KRAS promoter can fold into a four-stranded DNA secondary structure called G-quadruplex (G4), known to regulate KRAS expression. However, the factors that regulate stable G4 formation in the genome and KRAS expression in PDAC are largely unknown. Here, we show that APE1 (apurinic/apyrimidinic endonuclease 1), a multifunctional DNA repair enzyme, is a G4-binding protein, and loss of APE1 abrogates the formation of stable G4 structures in cells. Recombinant APE1 binds to KRAS promoter G4 structure with high affinity and promotes G4 folding in vitro. Knockdown of APE1 reduces MAZ transcription factor loading onto the KRAS promoter, thus reducing KRAS expression in PDAC cells. Moreover, downregulation of APE1 sensitizes PDAC cells to chemotherapeutic drugs in vitro and in vivo. We also demonstrate that PDAC patients’ tissue samples have elevated levels of both APE1 and G4 DNA. Our findings unravel a critical role of APE1 in regulating stable G4 formation and KRAS expression in PDAC and highlight G4 structures as genomic features with potential application as a novel prognostic marker and therapeutic target in PDAC.
Single-cell sequencing enables us to better understand genetic diseases, such as cancer or autoimmune disorders, which are often affected by changes in rare cells. Currently, no existing software is aimed at identifying single nucleotide variations or micro (1-50bp) insertions and deletions in single-cell RNA sequencing (scRNA-seq) data. Generating high-quality variant data is vital to the study of the aforementioned diseases, among others. In this study, we report the design and implementation of Red Panda, a novel method to accurately identify variants in scRNA-seq data. Variants were called on scRNA-seq data from human articular chondrocytes, mouse embryonic fibroblasts (MEFs), and simulated data stemming from the MEF alignments. Red Panda had the highest Positive Predictive Value at 45.0%, while other tools-FreeBayes, GATK HaplotypeCaller, GATK UnifiedGenotyper, Monovar, and Platypus-ranged from 5.8%-41.53%. From the simulated data, Red Panda had the highest sensitivity at 72.44%. We show that our method provides a novel and improved mechanism to identify variants in scRNA-seq as compared to currently-existing software.Availability: Source code freely available under the MIT License at https://github.com/adambioi/red_panda, and is supported on Linux
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