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Background: X-linked acrogigantism (X-LAG; MIM: 300942) is a severe form of pituitary gigantism caused by chromosome Xq26.3 duplications involving GPR101. X-LAG-associated duplications disrupt the integrity of the topologically associating domain (TAD) containing GPR101 and lead to the formation of a neo-TAD that drives pituitary GPR101 misexpression and gigantism. As X-LAG is fully penetrant and heritable, duplications involving GPR101 identified on prenatal screening studies, like amniocentesis, can pose an interpretation challenge for medical geneticists and raise important concerns for patients and families. Therefore, providing robust information on the functional genomic impact of such duplications has important research and clinical value with respect to gene regulation and triplosensitivity traits., Methods: We employed 4C/HiC-seq as a clinical tool to determine the functional impact of incidentally discovered GPR101 duplications on TAD integrity in three families. After defining duplications and breakpoints around GPR101 by clinical-grade and high-density aCGH, we constructed 4C/HiC chromatin contact maps for our study population and compared them with normal and active (X-LAG) controls., Results: We showed that duplications involving GPR101 that preserved the centromeric invariant TAD boundary did not generate a pathogenic neo-TAD and that ectopic enhancers were not adopted. This allowed us to discount presumptive/suspected X-LAG diagnoses and GPR101 misexpression, obviating the need for intensive clinical follow-up., Conclusions: This study highlights the importance of TAD boundaries and chromatin interactions in determining the functional impact of copy number variants and provides proof-of-concept for using 4C/HiC-seq as a clinical tool to acquire crucial information for genetic counseling and to support clinical decision-making in cases of suspected TADopathies., (© 2024. The Author(s).)

The hyperactive Tn5 transposase in the ATAC-seq method has been widely used to determine the open DNA regions and understand the overall epigenomic regulation in the chromatins of eukaryotic cells. Here, we describe POP-seq (Prokaryotic chromatin Openness Profiling sequencing), an adaptation of the ATAC-seq method, to interrogate changes in the openness of prokaryotic nucleoids., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Rhabdomyosarcoma (RMS) is a pediatric malignancy of the muscle with characteristics of cells blocked in differentiation. NOTCH1 is an oncogene that promotes self-renewal and blocks differentiation in the fusion negative-RMS sub-type. However, how NOTCH1 expression is transcriptionally maintained in tumors is unknown. Analyses of SNAI2 and CTCF chromatin binding and HiC analyses revealed a conserved SNAI2/CTCF overlapping peak downstream of the NOTCH1 locus marking a sub-topologically associating domain (TAD) boundary. Deletion of the SNAI2-CTCF peak showed that it is essential for NOTCH1 expression and viability of FN-RMS cells. Reintroducing constitutively activated NOTCH1 -ΔE in cells with the SNAI2-CTCF peak deleted restored cell-viability. Ablation of SNAI2 using CRISPR/Cas9 reagents resulted in the loss of majority of RD and SMS-CTR FN-RMS cells. However, the few surviving clones that repopulate cultures have recovered NOTCH1 . Cells that re-establish NOTCH1 expression after SNAI2 ablation are unable to differentiate robustly as SNAI2 shRNA knockdown cells; yet, SNAI2 -ablated cells continued to be exquisitely sensitive to ionizing radiation. Thus, we have uncovered a novel mechanism by which SNAI2 and CTCF maintenance of a sub-TAD boundary promotes rather than represses NOTCH1 expression. Further, we demonstrate that SNAI2 suppression of apoptosis post-radiation is independent of SNAI2 / NOTCH1 effects on self-renewal and differentiation.

Defining the genome-wide chromatin landscape has been a goal of experimentalists for decades. Here we review highlights of these efforts, from seminal experiments showing discontinuities in chromatin structure related to gene activation to extensions of these methods elucidating general features of chromatin related to gene states by exploiting deep sequencing methods. We also review chromatin conformational capture methods to identify patterns in long-range interactions between genomic loci., (© 2022 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.)

Within the nucleus, precise DNA folding and organization is mandatory for a tight control of gene expression. In the past 20 years, a wealth of molecular approaches has unraveled the existence of DNA territories. With the emergence of affordable deep-sequencing approaches, "Cs" techniques such as 4C, 5C, and HiC, to name a few, are now routinely performed by the scientific community in a large number of model systems. We have modified the HiC approach to a capture probe-based version named C-HiC. This updated assay has resulted in an improved throughput analysis, reduced input material, and good repeatability. The protocol described below details our procedure and notes for a C-HiC approach, designed to target only specific portion of a given genome.

Background: Enhancers play a fundamental role in orchestrating cell state and development. Although several methods have been developed to identify enhancers, linking them to their target genes is still an open problem. Several theories have been proposed on the functional mechanisms of enhancers, which triggered the development of various methods to infer promoter-enhancer interactions (PEIs). The advancement of high-throughput techniques describing the three-dimensional organization of the chromatin, paved the way to pinpoint long-range PEIs. Here we investigated whether including PEIs in computational models for the prediction of gene expression improves performance and interpretability., Results: We have extended our [Formula: see text] framework to include DNA contacts deduced from chromatin conformation capture experiments and compared various methods to determine PEIs using predictive modelling of gene expression from chromatin accessibility data and predicted transcription factor (TF) motif data. We designed a novel machine learning approach that allows the prioritization of TFs binding to distal loop and promoter regions with respect to their importance for gene expression regulation. Our analysis revealed a set of core TFs that are part of enhancer-promoter loops involving YY1 in different cell lines., Conclusion: We present a novel approach that can be used to prioritize TFs involved in distal and promoter-proximal regulatory events by integrating chromatin accessibility, conformation, and gene expression data. We show that the integration of chromatin conformation data can improve gene expression prediction and aids model interpretability.

Background: With the developments of DNA sequencing technology, large amounts of sequencing data have been produced that provides unprecedented opportunities for advanced association studies between somatic mutations and cancer types/subtypes which further contributes to more accurate somatic mutation based cancer typing (SMCT). In existing SMCT methods however, the absence of high-level feature extraction is a major obstacle in improving the classification performance., Results: We propose DeepCNA, an advanced convolutional neural network (CNN) based classifier, which utilizes copy number aberrations (CNAs) and HiC data, to address this issue. DeepCNA first pre-process the CNA data by clipping, zero padding and reshaping. Then, the processed data is fed into a CNN classifier, which extracts high-level features for accurate classification. Experimental results on the COSMIC CNA dataset indicate that 2D CNN with both cell lines of HiC data lead to the best performance. We further compare DeepCNA with three widely adopted classifiers, and demonstrate that DeepCNA has at least 78% improvement of performance., Conclusions: This paper demonstrates the advantages and potential of the proposed DeepCNA model for processing of somatic point mutation based gene data, and proposes that its usage may be extended to other complex genotype-phenotype association studies.

Germ cells reflect the evolutionary history and future potential of a species. Understanding how the genome is organised in gametocytes is fundamental to understanding fertility and its impact on genetic diversity and evolution of species. Here, we explore principles of chromatin remodelling during the formation of germ cells and how these are affected by genome reshuffling. [ABSTRACT FROM AUTHOR]