Nonhomologous end-joining (NHEJ) is a major repair pathway for DNA double-strand breaks (DSBs), involving synapsis and ligation of the broken strands. We describe the use of in vivo and in vitro single-molecule methods to define the organization and interaction of NHEJ repair proteins at DSB ends. Super-resolution fluorescence microscopy allowed the precise visualization of XRCC4, XLF, and DNA ligase IV filaments adjacent to DSBs, which bridge the broken chromosome and direct rejoining. We show, by singlemolecule FRET analysis of the Ku/XRCC4/XLF/DNA ligase IV NHEJ ligation complex, that end-to-end synapsis involves a dynamic positioning of the two ends relative to one another. Our observations form the basis of a new model for NHEJ that describes the mechanism whereby filament-forming proteins bridge DNA DSBs in vivo. In this scheme, the filaments at either end of the DSB interact dynamically to achieve optimal configuration and end-to-end positioning and ligation.genomic integrity | DNA repair | nonhomologous end-joining | super-resolution microscopy | single-molecule FRET C hromosomal double-strand breaks (DSBs), considered the most cytotoxic form of DNA damage, occur as a result of normal cellular processes (1, 2) as well as cancer therapies (3-5). The cellular DNA damage response (DDR) and repair pathways responsible for maintaining genomic integrity are highly regulated and synchronized processes, both temporally and spatially, involving the coordinated recruitment, assembly, and disassembly of numerous macromolecular complexes (6, 7). In mammalian cells, nonhomologous end-joining (NHEJ) is the primary DSB repair pathway; it is active throughout the cell cycle and is crucial for viability. Dysfunctional NHEJ is associated with several clinical conditions, including LIG4 syndrome and severe combined immunodeficiency (1,8). Despite its importance, however, the details of how the NHEJ complex assembles at DSBs, brings together a pair of breaks, and organizes subsequent catalytic repair steps remain unknown.In NHEJ, DSBs are initially recognized by the Ku 70/80 heterodimer (Ku), which encircles dsDNA ends (Ku:DNA) and serves as a molecular scaffold for recruitment of DNA-dependent protein kinase catalytic subunit (DNA-PKcs), XRCC4 (X-ray repair cross-complementing protein 4), XLF (XRCC4 like factor), and DNA ligase IV (LigIV) (1,(9)(10)(11)(12)(13)(14). Previous NHEJ models suggested that after binding of Ku to DNA ends, DNA-PKcs binds Ku:DNA to form a DNA-PK holoenzyme and bridges the broken ends (15-18); however, recent experiments indicate that DNAPKcs may have different roles in NHEJ, such as the stabilization of core NHEJ factors, recruitment and retention of accessory factors, involvement in the DDR signaling cascade, and repair of complex and clustered . In addition, recent structural studies have shown that XRCC4 and XLF form filamentous structures in vitro (26-28). Whether such filaments mediate repair in vivo has not yet been determined.Our present understanding of the cellular NHEJ response to DSBs ...

Chromosome conformation capture (3C) assays are used to map chromatin interactions genome-wide. Chromatin interaction maps provide insights into the spatial organization of chromosomes and the mechanisms by which they fold. Hi-C and Micro-C are widely used 3C protocols that differ in key experimental parameters including cross-linking chemistry and chromatin fragmentation strategy. To understand how the choice of experimental protocol determines the ability to detect and quantify aspects of chromosome folding we have performed a systematic evaluation of 3C experimental parameters. We identified optimal protocol variants for either loop or compartment detection, optimizing fragment size and cross-linking chemistry. We used this knowledge to develop a greatly improved Hi-C protocol (Hi-C 3.0) that can detect both loops and compartments relatively effectively. In addition to providing benchmarked protocols, this work produced ultra-deep chromatin interaction maps using Micro-C, conventional Hi-C and Hi-C 3.0 for key cell lines used by the 4D Nucleome project.

Electronic cigarettes (e-cigarettes), battery-powered devices containing nicotine, glycerin, propylene glycol, flavorings, and other substances, are increasing in popularity. They pose a potential threat to the developing brain, as nicotine is a known neurotoxicant. We hypothesized that exposure to e-cigarettes during early life stages induce changes in central nervous system (CNS) transcriptome associated with adverse neurobiological outcomes and long-term disease states. To test the hypothesis, pregnant C57BL/6 mice were exposed daily (via whole body inhalation) throughout gestation (3 h/day; 5 days/week) to aerosols produced from e-cigarettes either with nicotine (13–16 mg/mL) or without nicotine; following birth, pups and dams were exposed together to e-cigarette aerosols throughout lactation beginning at postnatal day (PND) 4–6 and using the same exposure conditions employed during gestational exposure. Following exposure, frontal cortex recovered from ~one-month-old male and female offspring were excised and analyzed for gene expression by RNA Sequencing (RNA-Seq). Comparisons between the treatment groups revealed that e-cigarette constituents other than nicotine might be partly responsible for the observed biological effects. Transcriptome alterations in both offspring sexes and treatment groups were all significantly associated with downstream adverse neurobiological outcomes. Results from this study demonstrate that e-cigarette exposure during early life alters CNS development potentially leading to chronic neuropathology.

Chromosome conformation capture (3C) technologies reveal the incredible complexity of genome organization. Maps of increasing size, depth, and resolution are now used to probe genome architecture across cell states, types, and organisms. Larger datasets add challenges at each step of computational analysis, from storage and memory constraints to researchers' time. Analysis tools that meet these increased resource demands have not kept pace. Furthermore, existing tools offer limited support for customizing analysis for specific use cases or new biology. Here we introduce cooltools (https://github.com/open2c/cooltools), a suite of computational tools that enables flexible, scalable, and reproducible analysis of high-resolution contact frequency data. Cooltools leverages the widely-adopted cooler format which handles storage and access for high-resolution datasets. Cooltools provides a paired command line interface (CLI) and Python application programming interface (API), which respectively facilitate workflows on high-performance computing clusters and in interactive analysis environments. In short, cooltools enables the effective use of the latest and largest genome folding datasets.