SEE: A Method for Predicting the Dynamics of Chromatin Conformation Based on Single‐Cell Gene Expression DOI Creative Commons
Minghong Li, Yurong Yang, Rongfeng Wu

и другие.

Advanced Science, Год журнала: 2025, Номер unknown

Опубликована: Янв. 7, 2025

Abstract The dynamics of chromatin conformation involve continuous and reversible changes within the nucleus a cell, which participate in regulating processes such as gene expression, DNA replication, damage repair. Here, SEE is introduced, an artificial intelligence (AI) method that utilizes autoencoder transformer techniques to analyze using single‐cell RNA sequencing data limited number Hi‐C maps. employed investigate across different scales, enabling detection (i) rearrangements topologically associating domains (TADs), (ii) oscillations interactions at loci. Additionally, facilitates interpretation disease‐associated single‐nucleotide polymorphisms (SNPs) by leveraging dynamic features conformation. Overall, offers single‐cell, high‐resolution approach analyzing both developmental disease contexts.

Язык: Английский

LiMCA: Hi-C gets an RNA twist DOI

Jane Kawaoka,

Stavros Lomvardas

Nature Methods, Год журнала: 2024, Номер 21(6), С. 934 - 935

Опубликована: Апрель 15, 2024

Язык: Английский

Процитировано

3

Droplet Hi-C for Fast and Scalable Profiling of Chromatin Architecture in Single Cells DOI Creative Commons
Lei Chang, Yang Xie, Brett M. Taylor

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Апрель 22, 2024

Abstract Comprehensive analysis of chromatin architecture is crucial for understanding the gene regulatory programs during development and in disease pathogenesis, yet current methods often inadequately address unique challenges presented by heterogeneous tissue samples. Here, we introduce Droplet Hi-C, which employs a commercial microfluidic device high-throughput, single-cell conformation profiling droplets. Using mapped at resolution from mouse cortex analyzed major cortical cell types. Additionally, used this technique to detect copy number variation (CNV), structural variations (SVs) extrachromosomal DNA (ecDNA) cancer cells, revealing clonal dynamics other oncogenic events treatment. We further refined allow joint transcriptome single facilitating more comprehensive exploration links between expression both normal tissues tumors. Thus, Hi-C not only addresses critical gaps but also emerges as versatile tool enhancing our regulation health disease.

Язык: Английский

Процитировано

3

Boosting the detection of enhancer-promoter loops via novel normalization methods for chromatin interaction data DOI Open Access
Xiaotao Wang,

Detong Shi,

Feiyang Xue

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Abstract Accurately detecting enhancer-promoter loops from genome-wide interaction data, such as Hi-C, is crucial for understanding gene regulation. Current normalization methods, Iterative Correction and Eigenvector decomposition (ICE), are commonly used to remove biases in Hi-C data prior chromatin loop detection. However, while structural or CTCF-associated signals retained, often greatly diminished after ICE similar making these regulatory harder detect. To address this limitation, we developed Raichu, a novel method normalizing contact data. Raichu identifies nearly twice many ICE, recovering almost all detected by revealing thousands of additional missed ICE. With its enhanced sensitivity loops, detects more biologically meaningful differential between conditions the same cell type. Furthermore, performs consistently across different sequencing depths platforms, including HiChIP, single-cell it versatile tool uncovering new insights into three- dimensional (3D) genomic organization transcriptional

Язык: Английский

Процитировано

0

Gene Doping Detection From the Perspective of 3D Genome DOI
Xiaomei Ren, Yue Shi, Bo Xiao

и другие.

Drug Testing and Analysis, Год журнала: 2025, Номер unknown

Опубликована: Янв. 5, 2025

ABSTRACT Since the early 20th century, concept of doping was first introduced. To achieve better athletic performance, chemical substances were used. By mid‐20th it became gradually recognized that illegal use can seriously endangered athletes' health and compromised fairness sports competitions. Over past 30 years, World Anti‐Doping Agency (WADA) has established corresponding rules regulations to prohibit athletes from using or restrict certain drugs, isotope, chromatography, mass spectrometry techniques accredited detect substances. With development gene editing technology, many genetic diseases have been effectively treated, but enabled by same also potential pose a threat in form doping. WADA explicitly indicated Prohibited List as prohibited method (M3) approved qPCR detection. However, easily evade detection, if target genes' upstream regulatory elements are considered, task more challenging. Hi‐C experiment driven 3D genome through perspectives such topologically associating domain (TAD) chromatin loop, provides comprehensive in‐depth understanding regulation expression, thereby preventing level In this work, we will explore different perspective analyzing recent studies on related genes under genome.

Язык: Английский

Процитировано

0

SEE: A Method for Predicting the Dynamics of Chromatin Conformation Based on Single‐Cell Gene Expression DOI Creative Commons
Minghong Li, Yurong Yang, Rongfeng Wu

и другие.

Advanced Science, Год журнала: 2025, Номер unknown

Опубликована: Янв. 7, 2025

Abstract The dynamics of chromatin conformation involve continuous and reversible changes within the nucleus a cell, which participate in regulating processes such as gene expression, DNA replication, damage repair. Here, SEE is introduced, an artificial intelligence (AI) method that utilizes autoencoder transformer techniques to analyze using single‐cell RNA sequencing data limited number Hi‐C maps. employed investigate across different scales, enabling detection (i) rearrangements topologically associating domains (TADs), (ii) oscillations interactions at loci. Additionally, facilitates interpretation disease‐associated single‐nucleotide polymorphisms (SNPs) by leveraging dynamic features conformation. Overall, offers single‐cell, high‐resolution approach analyzing both developmental disease contexts.

Язык: Английский

Процитировано

0