Hi-C

Single-cell brain organoid screening identifies developmental defects in autism

The paper uses CRISPR and single-cell transcriptomics to screen ASD risk genes in brain organoids, identifying developmental defects and regulatory modules linked to autism.

Topologically associating domains can arise from stochastic folding of heterogeneous fluidlike chromatin

This study shows that stochastic folding of fluidlike chromatin with DNA-packing density heterogeneity can form TADs without cohesin-mediated extrusion, and predicts TAD dynamics during T cell differentiation.

PfMORC protein regulates chromatin accessibility and transcriptional repression in the human malaria parasite, Plasmodium falciparum

This study shows PfMORC regulates chromatin structure and gene repression in Plasmodium falciparum, essential for parasite survival and a potential target for antimalarial drugs.

SnapATAC2: a fast, scalable and versatile tool for single-cell omics analysis

SnapATAC2 is a fast, scalable dimensionality reduction tool for single-cell omics data that improves accuracy and efficiency in capturing cellular heterogeneity across multiple modalities.

Integration of genetic fine-mapping and multi-omics data reveals candidate effector genes for hypertension

The paper integrates genetic fine-mapping with multi-omics data to identify candidate effector genes and new drug targets for hypertension.

Sashimi.py: a flexible toolkit for combinatorial analysis of genomic data

Sashimi.py provides a flexible and scalable tool for visualizing genomic data across multiple assays and formats, enabling combinatorial analysis of regulatory mechanisms.

Multi-omics comparison of malignant and normal uveal melanocytes reveals novel molecular features of uveal melanoma.

The paper uses multi-omics analysis to compare malignant and normal uveal melanocytes, identifying genomic instability and a BAP1 promoter deletion as key features of uveal melanoma.

High-resolution diploid 3D genome reconstruction using Pore-C data

This paper introduces Dip3D, a method to reconstruct high-resolution diploid 3D human genomes from Pore-C data, achieving better performance than existing methods.

AutoHiC: a deep-learning method for automatic and accurate chromosome-level genome assembly

AutoHiC improves chromosome-level genome assembly accuracy using deep learning to detect and correct errors in Hi-C data.

Examining dynamics of three-dimensional genome organization with multi-task matrix factorization

This paper introduces TGIF, a multi-task NMF method for analyzing 3D genome dynamics across Hi-C datasets, identifying structural changes linked to regulatory signals and gene expression.

Uncovering the lung cancer mechanisms through the chromosome structural ensemble characteristics

This study develops a chromosome dynamic structural model to analyze the structural ensemble characteristics of normal and lung cancer cells, revealing links between chromosome structure, epigenetics, and gene expression.

EagleC Explorer: A desktop application for interactively detecting and visualizing SVs and enhancer hijacking on Hi-C contact maps

EagleC Explorer is a desktop tool for visualizing and detecting structural variations and enhancer hijacking in Hi-C data, enabling interactive analysis in cancer studies.

Chrombus-XMBD: A Graph Generative Model Predicting 3D-Genome, ab initio from Chromatin Features

Chrombus-XMBD predicts 3D-genome structures from chromatin features using a graph generative model, outperforming existing methods and showing cross-species generalizability.

Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features

The paper identifies differential chromatin loops during megakaryocyte differentiation and shows their association with gene expression changes and histone modifications.

Ultra-long-range interactions between active regulatory elements

The paper identifies ultra-long-range chromatin interactions between active regulatory elements in vertebrate and invertebrate genomes, showing they are driven by three distinct mechanisms independent of RNA polymerase II and some cofactors.

Quantifying the large-scale chromosome structural dynamics during the mitosis-to-G1 phase transition of cell cycle

This study quantifies chromosome structural dynamics during the mitosis-to-G1 phase transition using a data-driven model and nonequilibrium landscape-switching model, revealing asynchronous structural changes and TAD dynamics.

RNA polymerase II pausing contributes to maintain chromatin organization in erythrocytes

The paper shows that RNA polymerase II pausing maintains chromatin organization in chicken erythrocytes by repositioning euchromatin and preserving paused promoters.

Organization and replicon interactions within the highly segmented genome of Borrelia burgdorferi

This study characterizes the organization of Borrelia burgdorferi's segmented genome and interactions between replicons using Hi-C, revealing chromosome structure and plasmid interactions.

Enhancer plasticity in endometrial tumorigenesis demarcates non-coding somatic mutations and 3D-genome alterations boosting the oncogenic driver ESR1

The paper identifies enhancer plasticity and 3D-genome alterations in endometrial cancer that boost ESR1 expression through non-coding mutations and risk variants.

Tracing the evolution of single-cell cancer 3D genomes: an atlas for cancer gene discovery

The paper maps 3D genome structures in cancer tissues to identify structural changes and potential biomarkers across cancer progression stages.

Detection of new pioneer transcription factors as cell-type specific nucleosome binders

The paper develops a computational method to predict cell-type-specific nucleosome-binding abilities of transcription factors using ChIP-seq, MNase-seq, and DNase-seq data, identifying new potential pioneer transcription factors.

Concurrent profiling of multiscale 3D genome organization and gene expression in single mammalian cells

This paper introduces GAGE-seq, a single-cell method that simultaneously profiles 3D genome structure and gene expression, revealing their relationship in defining cell identity and lineage commitment.

Enhanced performance of gene expression predictive models with protein-mediated spatial chromatin interactions

The paper improves gene expression prediction models by incorporating protein-mediated spatial chromatin interactions, resulting in significant performance gains across multiple cell lines.

BL-Hi-C reveals the 3D genome structure of Brassica crops with high efficiency and sensitivity

BL-Hi-C improves Hi-C for plant 3D genomics by simplifying protocols, reducing noise, and increasing sensitivity for detecting gene loops in Brassica species.

Transcription regulates the spatio-temporal dynamics of genes through micro-compartmentalization

The paper uses Micro-C data from mouse embryonic stem cells to show that transcriptional activity influences 3D gene folding through Pol II-mediated micro-compartmentalization.

The super-pangenome of Populus unveil genomic facets for adaptation and diversification in widespread forest trees

The paper constructs a super-pangenome of 19 Populus species to explore genomic factors driving adaptation and diversification in forest trees.

Phase separation of ecDNA aggregates establishes in-trans contact domains boosting selective MYC regulatory interactions

The paper investigates how ecDNA clusters form through phase separation, creating regulatory contacts that boost MYC expression, and shows how JQ1 disrupts this process.

Schizophrenia Risk Mapping and Functional Engineering of the 3D Genome in Three Neuronal Subtypes

The paper maps 3D chromatin structures in neuronal subtypes and shows how schizophrenia risk loci reorganize during differentiation, linking regulatory loops to gene function.

EpiGePT: a Pretrained Transformer model for epigenomics

EpiGePT is a transformer-based model that predicts epigenomic signals and chromatin contacts by incorporating transcription factor activities and 3D genome interactions, outperforming existing methods in cross-cell-type prediction.

DeepChIA-PET: Accurately predicting ChIA-PET from Hi-C and ChIP-seq with deep dilated networks

DeepChIA-PET predicts ChIA-PET interactions from Hi-C and ChIP-seq data using deep dilated networks, outperforming existing methods and generalizing to non-CTCF interactions.