scCircle-seq unveils the diversity and complexity of extrachromosomal circular DNAs in single cells.

Extrachromosomal circular DNAs (eccDNAs) have emerged as important intra-cellular mobile genetic elements that affect gene copy number and exert in trans regulatory roles within the cell nucleus. Here, we describe scCircle-seq, a method for profiling eccDNAs and unraveling their diversity and complexity in single cells. We implement and validate scCircle-seq in normal and cancer cell lines, demonstrating that most eccDNAs vary largely between cells and are stochastically inherited during cell division, although their genomic landscape is cell type-specific and can be used to accurately cluster cells of the same origin. eccDNAs are preferentially produced from chromatin regions enriched in H3K9me3 and H3K27me3 histone marks and are induced during replication stress conditions. Concomitant sequencing of eccDNAs and RNA from the same cell uncovers the absence of correlation between eccDNA copy number and gene expression levels, except for a few oncogenes, including MYC, contained within a large eccDNA in colorectal cancer cells. Lastly, we apply scCircle-seq to one prostate cancer and two breast cancer specimens, revealing cancer-specific eccDNA landscapes and a higher propensity of eccDNAs to form in amplified genomic regions. scCircle-seq is a scalable tool that can be used to dissect the complexity of eccDNAs across different cell and tissue types, and further expands the potential of eccDNAs for cancer diagnostics.

Compartmentalizing damaged DNA: A double-edged sword.

A recent publication in Nature by Arnould et al.1 describes a novel chromatin compartment, termed "damaged" or "D compartment," that facilitates the repair of DNA double-strand breaks but also increases the risk of potentially oncogenic translocation formation.

XPF interacts with TOP2B for R-loop processing and DNA looping on actively transcribed genes.

Co-transcriptional RNA-DNA hybrids can not only cause DNA damage threatening genome integrity but also regulate gene activity in a mechanism that remains unclear. Here, we show that the nucleotide excision repair factor XPF interacts with the insulator binding protein CTCF and the cohesin subunits SMC1A and SMC3, leading to R-loop-dependent DNA looping upon transcription activation. To facilitate R-loop processing, XPF interacts and recruits with TOP2B on active gene promoters, leading to double-strand break accumulation and the activation of a DNA damage response. Abrogation of TOP2B leads to the diminished recruitment of XPF, CTCF, and the cohesin subunits to promoters of actively transcribed genes and R-loops and the concurrent impairment of CTCF-mediated DNA looping. Together, our findings disclose an essential role for XPF with TOP2B and the CTCF/cohesin complex in R-loop processing for transcription activation with important ramifications for DNA repair-deficient syndromes associated with transcription-associated DNA damage.

Enhancers dysfunction in the 3D genome of cancer cells.

Eukaryotic genomes are spatially organized inside the cell nucleus, forming a threedimensional (3D) architecture that allows for spatial separation of nuclear processes and for controlled expression of genes required for cell identity specification and tissue homeostasis. Hence, it is of no surprise that mis-regulation of genome architecture through rearrangements of the linear genome sequence or epigenetic perturbations are often linked to aberrant gene expression programs in tumor cells. Increasing research efforts have shed light into the causes and consequences of alterations of 3D genome organization. In this review, we summarize the current knowledge on how 3D genome architecture is dysregulated in cancer, with a focus on enhancer highjacking events and their contribution to tumorigenesis. Studying the functional effects of genome architecture perturbations on gene expression in cancer offers a unique opportunity for a deeper understanding of tumor biology and sets the basis for the discovery of novel therapeutic targets.

Deficiency of the Heterogeneous Nuclear Ribonucleoprotein U locus leads to delayed hindbrain neurogenesis.

Genetic variants affecting Heterogeneous Nuclear Ribonucleoprotein U (HNRNPU) have been identified in several neurodevelopmental disorders (NDDs). HNRNPU is widely expressed in the human brain and shows the highest postnatal expression in the cerebellum. Recent studies have investigated the role of HNRNPU in cerebral cortical development, but the effects of HNRNPU deficiency on cerebellar development remain unknown. Here, we describe the molecular and cellular outcomes of HNRNPU locus deficiency during in vitro neural differentiation of patient-derived and isogenic neuroepithelial stem cells with a hindbrain profile. We demonstrate that HNRNPU deficiency leads to chromatin remodeling of A/B compartments, and transcriptional rewiring, partly by impacting exon inclusion during mRNA processing. Genomic regions affected by the chromatin restructuring and host genes of exon usage differences show a strong enrichment for genes implicated in epilepsies, intellectual disability, and autism. Lastly, we show that at the cellular level HNRNPU downregulation leads to an increased fraction of neural progenitors in the maturing neuronal population. We conclude that the HNRNPU locus is involved in delayed commitment of neural progenitors to differentiate in cell types with hindbrain profile.

A GC-centered view of 3D genome organization.

In the past two decades, our understanding of how the genome of mammalian cells is spatially organized in the three-dimensional (3D) space of the nucleus and how key nuclear processes are orchestrated in this space has drastically expanded. While genome organization has been extensively studied at the nanoscale, the higher-order arrangement of individual portions of the genome with respect to their intranuclear as well as reciprocal placement is less thoroughly characterized. Emerging evidence points to the existence of a complex radial arrangement of chromatin in the nucleus. However, what shapes this radial organization and whether it has any functional implications remain elusive. In this mini review, we first summarize our current knowledge on this rather overlooked aspect of mammalian genome organization. We then present a theoretical framework for explaining how the genome might be radially organized, focusing on the role of the guanine and cytosine density along the linear genome. Last, we discuss outstanding questions, hoping to inspire future experiments and spark interest in this topic within the 3D genome community.

Genomic Profiling Identifies Putative Pathogenic Alterations in NSCLC Brain Metastases.

Introduction: Brain metastases (BM) severely affect the prognosis and quality of life of patients with NSCLC. Recently, molecularly targeted agents were found to have promising activity against BM in patients with NSCLC whose primary tumors carry "druggable" mutations. Nevertheless, it remains critical to identify specific pathogenic alterations that drive NSCLC-BM and that can provide novel and more effective therapeutic targets. Methods: To identify potentially targetable pathogenic alterations in NSCLC-BM, we profiled somatic copy number alterations (SCNAs) in 51 matched pairs of primary NSCLC and BM samples from 33 patients with lung adenocarcinoma and 18 patients with lung squamous cell carcinoma. In addition, we performed multiregion copy number profiling on 15 BM samples and whole-exome sequencing on 40 of 51 NSCLC-BM pairs. Results: BM consistently had a higher burden of SCNAs compared with the matched primary tumors, and SCNAs were typically homogeneously distributed within BM, suggesting BM do not undergo extensive evolution once formed. By comparing focal SCNAs in matched NSCLC-BM pairs, we identified putative BM-driving alterations affecting multiple cancer genes, including several potentially targetable alterations in genes such as CDK12, DDR2, ERBB2, and NTRK1, which we validated in an independent cohort of 84 BM samples. Finally, we identified putative pathogenic alterations in multiple cancer genes, including genes involved in epigenome editing and 3D genome organization, such as EP300, CTCF, and STAG2, which we validated by targeted sequencing of an independent cohort of 115 BM samples. Conclusions: Our study represents the most comprehensive genomic characterization of NSCLC-BM available to date, paving the way to functional studies aimed at assessing the potential of the identified pathogenic alterations as clinical biomarkers and targets.

FRET-FISH probes chromatin compaction at individual genomic loci in single cells.

Chromatin compaction is a key biophysical property that influences multiple DNA transactions. Lack of chromatin accessibility is frequently used as proxy for chromatin compaction. However, we currently lack tools for directly probing chromatin compaction at individual genomic loci. To fill this gap, here we present FRET-FISH, a method combining fluorescence resonance energy transfer (FRET) with DNA fluorescence in situ hybridization (FISH) to probe chromatin compaction at select loci in single cells. We first validate FRET-FISH by comparing it with ATAC-seq, demonstrating that local compaction and accessibility are strongly correlated. FRET-FISH also detects expected differences in compaction upon treatment with drugs perturbing global chromatin condensation. We then leverage FRET-FISH to study local chromatin compaction on the active and inactive X chromosome, along the nuclear radius, in different cell cycle phases, and during increasing passage number. FRET-FISH is a robust tool for probing local chromatin compaction in single cells.

Deep learning-based tumor microenvironment segmentation is predictive of tumor mutations and patient survival in non-small-cell lung cancer.

BACKGROUND: Despite the fact that tumor microenvironment (TME) and gene mutations are the main determinants of progression of the deadliest cancer in the world - lung cancer, their interrelations are not well understood. Digital pathology data provides a unique insight into the spatial composition of the TME. Various spatial metrics and machine learning approaches were proposed for prediction of either patient survival or gene mutations from this data. Still, these approaches are limited in the scope of analyzed features and in their explainability, and as such fail to transfer to clinical practice. METHODS: Here, we generated 23,199 image patches from 26 hematoxylin-and-eosin (H&E)-stained lung cancer tissue sections and annotated them into 9 different tissue classes. Using this dataset, we trained a deep neural network ARA-CNN. Next, we applied the trained network to segment 467 lung cancer H&E images from The Cancer Genome Atlas (TCGA) database. We used the segmented images to compute human-interpretable features reflecting the heterogeneous composition of the TME, and successfully utilized them to predict patient survival and cancer gene mutations. RESULTS: We achieved per-class AUC ranging from 0.72 to 0.99 for classifying tissue types in lung cancer with ARA-CNN. Machine learning models trained on the proposed human-interpretable features achieved a c-index of 0.723 in the task of survival prediction and AUC up to 73.5% for PDGFRB in the task of mutation classification. CONCLUSIONS: We presented a framework that accurately predicted survival and gene mutations in lung adenocarcinoma patients based on human-interpretable features extracted from H&E slides. Our approach can provide important insights for designing novel cancer treatments, by linking the spatial structure of the TME in lung adenocarcinoma to gene mutations and patient survival. It can also expand our understanding of the effects that the TME has on tumor evolutionary processes. Our approach can be generalized to different cancer types to inform precision medicine strategies.

Integrative genomic and transcriptomic analyses illuminate the ontology of HER2-low breast carcinomas.

BACKGROUND: The "HER2-low" nomenclature identifies breast carcinomas (BCs) displaying a HER2 score of 1+/2+ in immunohistochemistry and lacking ERBB2 amplification. Whether HER2-low BCs (HLBCs) constitute a distinct entity is debated. METHODS: We performed DNA and RNA high-throughput analysis on 99 HLBC samples (n = 34 cases with HER2 score 1+/HLBC-1, n = 15 cases with HER2 score 2+ and ERBB2 not amplified/HLBC-2N, and n = 50 cases with score 2+ and ERBB2 copy number in the equivocal range/HLBC-2E). We compared the mutation rates with data from 1317 samples in the Memorial Sloan-Kettering Cancer Center (MSKCC) BC cohort and gene expression data with those from an internal cohort of HER2-negative and HER2-positive BCs. RESULTS: The most represented mutations affected PIK3CA (31/99, 31%), GATA3 (18/99, 18%), TP53 (17/99, 17%), and ERBB2 (8/99, 8%, private to HLBC-2E). Tumor mutational burden was significantly higher in HLBC-1 compared to HLBC-2E/N (P = 0.04). Comparison of mutation spectra revealed that HLBCs were different from both HER2-negative and HER2-positive BCs, with HLBC-1 resembling more HER2-negative tumors and HLBC-2 mutationally related to HER2-addicted tumors. Potentially actionable alterations (annotated by using OncoKB/ESCAT classes) affected 52 patients. Intra-group gene expression revealed overlapping features between HLBC-1 and control HER2-negative BCs, whereas the HLBC-2E tumors showed the highest diversity overall. The RNA-based class discovery analysis unveiled four subsets of tumors with (i) lymphocyte activation, (ii) unique enrichment in HER2-related features, (iii) stromal remodeling alterations, and (iv) actionability of PIK3CA mutations (LAURA classification). CONCLUSIONS: HLBCs harbor distinct genomic features when compared with HER2-positive and HER2-negative BCs; however, differences across IHC classes were also unveiled thus dissecting the full picture of heterogeneity across HER2-low disease. The HLBC-2E category harbors most distinctive features, whereas HLBC-1 seems superimposable to HER2-negative disease. Further studies are needed to ascertain whether the four genomic-driver classes of the LAURA classification hold prognostic and/or predictive implications.

An atlas of endogenous DNA double-strand breaks arising during human neural cell fate determination.

Endogenous DNA double-strand breaks (DSBs) occurring in neural cells have been implicated in the pathogenesis of neurodevelopmental disorders (NDDs). Currently, a genomic map of endogenous DSBs arising during human neurogenesis is missing. Here, we applied in-suspension Breaks Labeling In Situ and Sequencing (sBLISS), RNA-Seq, and Hi-C to chart the genomic landscape of DSBs and relate it to gene expression and genome architecture in 2D cultures of human neuroepithelial stem cells (NES), neural progenitor cells (NPC), and post-mitotic neural cells (NEU). Endogenous DSBs were enriched at the promoter and along the gene body of transcriptionally active genes, at the borders of topologically associating domains (TADs), and around chromatin loop anchors. NDD risk genes harbored significantly more DSBs in comparison to other protein-coding genes, especially in NEU cells. We provide sBLISS, RNA-Seq, and Hi-C datasets for each differentiation stage, and all the scripts needed to reproduce our analyses. Our datasets and tools represent a unique resource that can be harnessed to investigate the role of genome fragility in the pathogenesis of NDDs.

The era of 3D and spatial genomics.

Over a decade ago the advent of high-throughput chromosome conformation capture (Hi-C) sparked a new era of 3D genomics. Since then the number of methods for mapping the 3D genome has flourished, enabling an ever-increasing understanding of how DNA is packaged in the nucleus and how the spatiotemporal organization of the genome orchestrates its vital functions. More recently, the next generation of spatial genomics technologies has begun to reveal how genome sequence and 3D genome organization vary between cells in their tissue context. We summarize how the toolkit for charting genome topology has evolved over the past decade and discuss how new technological developments are advancing the field of 3D and spatial genomics.

Simultaneous visualization of DNA loci in single cells by combinatorial multi-color iFISH.

Single-molecule DNA fluorescence in situ hybridization (FISH) techniques enable studying the three-dimensional (3D) organization of the genome at the single cell level. However, there is a major unmet need for open access, high quality, curated and reproducible DNA FISH datasets. Here, we describe a dataset obtained by applying our recently developed iFISH method to simultaneously visualize 16 small (size range: 62-73 kilobases, kb) DNA loci evenly spaced on chromosome 2 in human cells, in a single round of hybridization. We show how combinatorial color coding can be used to precisely localize multiple loci in 3D within single cells, and how inter-locus distances scale inversely with chromosome contact frequencies determined by high-throughput chromosome conformation capture (Hi-C). We provide raw images and 3D coordinates for nearly 10,000 FISH dots. Our dataset provides a free resource that can facilitate studies of 3D genome organization in single cells and can be used to develop automatic FISH analysis algorithms.

RNA gradients: Shapers of 3D genome architecture.

A growing body of evidence points to a role of nuclear RNAs (nucRNAs) in shaping the three-dimensional (3D) architecture of the genome within the nucleus of a eukaryotic cell. nucRNAs are non-homogeneously distributed within the nucleus where they can form global and local gradients that might contribute to instructing the formation and coordinating the function of different types of 3D genome structures. In this article, we highlight the available literature supporting a role of nucRNAs as 3D genome shapers and propose that nucRNA gradients are key mediators of genome structure and function.

A recurrent chromosomal inversion suffices for driving escape from oncogene-induced senescence via subTAD reorganization.

Oncogene-induced senescence (OIS) is an inherent and important tumor suppressor mechanism. However, if not removed timely via immune surveillance, senescent cells also have detrimental effects. Although this has mostly been attributed to the senescence-associated secretory phenotype (SASP) of these cells, we recently proposed that "escape" from the senescent state is another unfavorable outcome. The mechanism underlying this phenomenon remains elusive. Here, we exploit genomic and functional data from a prototypical human epithelial cell model carrying an inducible CDC6 oncogene to identify an early-acquired recurrent chromosomal inversion that harbors a locus encoding the circadian transcription factor BHLHE40. This inversion alone suffices for BHLHE40 activation upon CDC6 induction and driving cell cycle re-entry of senescent cells, and malignant transformation. Ectopic overexpression of BHLHE40 prevented induction of CDC6-triggered senescence. We provide strong evidence in support of replication stress-induced genomic instability being a causative factor underlying "escape" from oncogene-induced senescence.

Interplay between copy number alterations and immune profiles in the early breast cancer Scandinavian Breast Group 2004-1 randomized phase II trial: results from a feasibility study.

Emerging data indicate that genomic alterations can shape immune cell composition in early breast cancer. However, there is a need for complementary imaging and sequencing methods for the quantitative assessment of combined somatic copy number alteration (SCNA) and immune profiling in pathological samples. Here, we tested the feasibility of three approaches-CUTseq, for high-throughput low-input SCNA profiling, multiplexed fluorescent immunohistochemistry (mfIHC) and digital-image analysis (DIA) for quantitative immuno-profiling- in archival formalin-fixed paraffin-embedded (FFPE) tissue samples from patients enrolled in the randomized SBG-2004-1 phase II trial. CUTseq was able to reproducibly identify amplification and deletion events with a resolution of 100 kb using only 6 ng of DNA extracted from FFPE tissue and pooling together 77 samples into the same sequencing library. In the same samples, mfIHC revealed that CD4 + T-cells and CD68 + macrophages were the most abundant immune cells and they mostly expressed PD-L1 and PD-1. Combined analysis showed that the SCNA burden was inversely associated with lymphocytic infiltration. Our results set the basis for further applications of CUTseq, mfIHC and DIA to larger cohorts of early breast cancer patients.

Topoisomerase 1 activity during mitotic transcription favors the transition from mitosis to G1.

As cells enter mitosis, chromatin compacts to facilitate chromosome segregation yet remains transcribed. Transcription supercoils DNA to levels that can impede further progression of RNA polymerase II (RNAPII) unless it is removed by DNA topoisomerase 1 (TOP1). Using ChIP-seq on mitotic cells, we found that TOP1 is required for RNAPII translocation along genes. The stimulation of TOP1 activity by RNAPII during elongation allowed RNAPII clearance from genes in prometaphase and enabled chromosomal segregation. Disruption of the TOP1-RNAPII interaction impaired RNAPII spiking at promoters and triggered defects in the post-mitotic transcription program. This program includes factors necessary for cell growth, and cells with impaired TOP1-RNAPII interaction are more sensitive to inhibitors of mTOR signaling. We conclude that TOP1 is necessary for assisting transcription during mitosis with consequences for growth and gene expression long after mitosis is completed. In this sense, TOP1 ensures that cellular memory is preserved in subsequent generations.

Somatic Copy Number Alterations in Human Cancers: An Analysis of Publicly Available Data From The Cancer Genome Atlas.

Somatic copy number alterations (SCNAs) are a pervasive trait of human cancers that contributes to tumorigenesis by affecting the dosage of multiple genes at the same time. In the past decade, The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) initiatives have generated and made publicly available SCNA genomic profiles from thousands of tumor samples across multiple cancer types. Here, we present a comprehensive analysis of 853,218 SCNAs across 10,729 tumor samples belonging to 32 cancer types using TCGA data. We then discuss current models for how SCNAs likely arise during carcinogenesis and how genomic SCNA profiles can inform clinical practice. Lastly, we highlight open questions in the field of cancer-associated SCNAs.

COVseq is a cost-effective workflow for mass-scale SARS-CoV-2 genomic surveillance.

While mass-scale vaccination campaigns are ongoing worldwide, genomic surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical to monitor the emergence and global spread of viral variants of concern (VOC). Here, we present a streamlined workflow-COVseq-which can be used to generate highly multiplexed sequencing libraries compatible with Illumina platforms from hundreds of SARS-CoV-2 samples in parallel, in a rapid and cost-effective manner. We benchmark COVseq against a standard library preparation method (NEBNext) on 29 SARS-CoV-2 positive samples, reaching 95.4% of concordance between single-nucleotide variants detected by both methods. Application of COVseq to 245 additional SARS-CoV-2 positive samples demonstrates the ability of the method to reliably detect emergent VOC as well as its compatibility with downstream phylogenetic analyses. A cost analysis shows that COVseq could be used to sequence thousands of samples at less than 15 USD per sample, including library preparation and sequencing costs. We conclude that COVseq is a versatile and scalable method that is immediately applicable for SARS-CoV-2 genomic surveillance and easily adaptable to other pathogens such as influenza viruses.