Article
Biochemistry & Molecular Biology
Jonathan Rosen, Lindsay Lee, Armen Abnousi, Jiawen Chen, Jia Wen, Ming Hu, Yun Li
Summary: High-throughput chromatin conformation capture technologies like Hi-C and Micro-C have provided a genome-wide perspective on chromatin spatial organization. Recently, HiC-derived enrichment-based methods such as HiChIP and PLAC-seq have become popular due to their high signal-to-noise ratio and affordability. However, specific computational methods tailored for analyzing HiChIP and PLAC-seq data are still being developed. In this study, we present HPTAD, a computational method for identifying topologically associating domains (TADs) from HiChIP and PLAC-seq data, which outperforms existing TAD calling methods designed for Hi-C data. HPTAD is freely available at https://github.com/yunliUNC/HPTAD.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Review
Cell Biology
Juan J. Tena, Jose M. Santos-Pereira
Summary: TADs in animal genomes serve as structural scaffolds for gene regulation, influencing the establishment of regulatory landscapes. Recent advancements have shed light on the roles of TADs in gene regulation and development, with restructuring TADs potentially leading to pathological conditions.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
Article
Biochemical Research Methods
Jhen Yuan Yang, Jia-Ming Chang
Summary: Recent evidence shows that the three-dimensional chromosome structure is important for genomic function. This study proposes a novel approach using convolutional and residual neural networks to recognize topologically associating domains (TADs) as image patterns. The results demonstrate high performance across species and cell types, indicating the practicality of the TAD recognition model.
BMC BIOINFORMATICS
(2022)
Article
Genetics & Heredity
Christophe Tav, Eric Fournier, Michele Fournier, Fatemeh Khadangi, Audrey Baguette, Maxime C. Cote, Maruhen A. D. Silveira, Felix-Antoine Berube-Simard, Guillaume Bourque, Arnaud Droit, Steve Bilodeau
Summary: Transcription-factor binding and reorganization of coregulators can regulate gene expression. Hormone-induced gene response can be mediated by changes in the distribution of coregulators in chromatin regions. These results support a model where signal-induced transcription factors induce regional effects, redefining the concept of direct and indirect effects on target genes.
FRONTIERS IN GENETICS
(2023)
Article
Biotechnology & Applied Microbiology
Yuexuan Long, Zhenping Liu, Pengcheng Wang, Hang Yang, Yuejin Wang, Sainan Zhang, Xianlong Zhang, Maojun Wang
Summary: Structural variations (SVs) play a significant role in transcriptional regulation, with some SVs affecting TAD boundary regions and disrupting TAD organization; SVs tend to occur in TAD interior, possibly due to relaxed evolutionary selection pressure; Tetraploid cottons show biased evolution in SV-mediated disruption of 3D genome structure relative to diploids.
Article
Biochemical Research Methods
Xiaoqing Peng, Yiming Li, Mengxi Zou, Xiangyan Kong, Yu Sheng
Summary: In this study, a method named CATAD is proposed to identify topologically associating domains (TADs) based on the core-attachment structure model. The CATAD method identifies the core of TADs based on local density and cosine similarity and determines the surrounding attachments based on boundary insulation. The results show that CATAD outperforms other methods in identifying TAD boundaries and is robust to different resolutions of Hi-C matrices.
BRIEFINGS IN BIOINFORMATICS
(2023)
Review
Genetics & Heredity
Samuel Jianjie Yeo, Chen Ying, Melissa Jane Fullwood, Vinay Tergaonkar
Summary: This review discusses the roles of noncoding RNAs (ncRNAs) in regulating the form and function of topologically associating domains (TADs), including moderating loop extrusion through interactions with architectural proteins and facilitating TAD phase separation. The article also proposes future studies and directions to investigate these phenomena.
TRENDS IN GENETICS
(2023)
Article
Virology
Mel Campbell, Chanikarn Chantarasrivong, Yuichi Yanagihashi, Tomoki Inagaki, Ryan R. Davis, Kazushi Nakano, Ashish Kumar, Clifford G. Tepper, Yoshihiro Izumiya
Summary: This study reveals the 3D structure of the KSHV genome and presents a 3D genomic structural model for the virus. The KSHV genome exhibits similar structural features and undergoes reorganization during reactivation, facilitating viral gene transcription.
JOURNAL OF VIROLOGY
(2022)
Article
Genetics & Heredity
Chenguang Zhao, Tong Liu, Zheng Wang
Summary: This study investigates the functional similarities of protein-coding genes within topologically associating domains (TADs) and gap regions. It is found that genes within the same TAD or gap region are more likely to share similar protein functions. A network model based on Hi-C contacts and TAD relationships shows better performance in predicting gene functions.
Article
Immunology
Wenliang Wang, Aditi Chandra, Naomi Goldman, Sora Yoon, Emily K. Ferrari, Son. C. Nguyen, Eric F. Joyce, Golnaz Vahedi
Summary: The study shows that TCF-1 plays a role in controlling the global genome organization during T cell development. It alters the structure of topologically associating domains and promotes interactions between previously insulated regulatory elements and target genes.
Article
Biochemical Research Methods
Jian Liu, Pingjing Li, Jialiang Sun, Jun Guo
Summary: With the development of the chromosome conformation capture technique, the study of genome spatial conformation based on the Hi-C technique has significantly advanced. Previous research has shown that genomes are folded into a hierarchy of 3D structures associated with topologically associating domains (TADs), and detecting TAD boundaries is crucial for analyzing the 3D genome architecture. This paper introduces a novel TAD identification method called LPAD, which extracts node correlations from chromosome interactions using the random walk with restart and builds an undirected graph from Hi-C contact matrix. LPAD utilizes label propagation to discover communities and generate TADs, demonstrating high accuracy in TAD detection compared to existing methods. Experimental evaluation also confirms LPAD's effectiveness in identifying TAD boundaries through enrichment of histone modifications.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Hao Wu, Pengyu Zhang, Zhaoheng Ai, Leyi Wei, Hongming Zhang, Fan Yang, Lizhen Cui
Summary: This study proposes a novel ensemble learning framework called StackTADB for predicting the boundaries of TADs. Through data analysis and performance comparison, StackTADB is shown to have superior performance in predicting TAD boundaries. Additionally, Kmers-based features play an important role in predicting TAD boundaries in fruit flies.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemistry & Molecular Biology
Yi Liao, Xinwen Zhang, Mahul Chakraborty, J. J. Emerson
Summary: Research on the molecular evolution of TADs in Drosophila species reveals that a significant proportion of their genomes retain conserved TADs. Comparative genomic analysis shows that chromosomal rearrangement breakpoints are enriched at TAD boundaries, while genes within conserved TADs exhibit lower expression divergence. Structural variants (SVs) identified from different Drosophila strains demonstrate evidence of selection acting on SVs at TAD boundaries, with different types of selection for deletions and tandem duplications.
Article
Computer Science, Information Systems
Xuemin Zhao, Ran Duan, Shaowen Yao
Summary: Topologically associated domains (TADs) are essential units in chromatin's three-dimensional organization, influencing various biological processes. This study proposes an optimization method for TAD identification using empirical mode decomposition and compares its results with five commonly used TAD detection methods. The proposed method demonstrates universality and efficiency, highlighting its potential as a valuable tool in TAD identification.
Article
Biochemistry & Molecular Biology
Guifang Du, Hao Li, Yang Ding, Shuai Jiang, Hao Hong, Jingbo Gan, Longteng Wang, Yuanping Yang, Yinyin Li, Xin Huang, Yu Sun, Huan Tao, Yaru Li, Xiang Xu, Yang Zheng, Junting Wang, Xuemei Bai, Kang Xu, Yaoshen Li, Qi Jiang, Cheng Li, Hebing Chen, Xiaochen Bo
Summary: Recent studies have shown the association between the 3D structure of chromatin and cancer progression. This study investigates the hierarchical TAD structures in cancers and their dynamic changes in relation to transcriptional abnormalities, revealing the significant impact on cancer prognosis. The results emphasize the importance of hierarchical chromatin organization in cancer development.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2021)
Article
Genetics & Heredity
Kun Xiong, Mark Gerstein, Joanna Masel
Summary: Transcriptional regulatory networks (TRNs) exhibit certain motifs, with type 1 incoherent feed-forward loops (I1FFLs) and negative feedback loops (NFBLs) being common solutions. The evolution of these motifs is influenced by selection conditions, with I1FFLs generally evolving more frequently than NFBLs. The evolutionary accessibility and not just relative functionality shape motif evolution in TRNs, with the expression levels of specific genes playing a crucial role.
Correction
Genetics & Heredity
Gamze Guersoy, Tianxiao Li, Susanna Liu, Eric Ni, Charlotte M. Brannon, Mark B. Gerstein
NATURE REVIEWS GENETICS
(2022)
Review
Genetics & Heredity
Gamze Gursoy, Tianxiao Li, Susanna Liu, Eric Ni, Charlotte M. Brannon, Mark B. Gerstein
Summary: Sharing functional genomics data is crucial for research advancement, but poses notable privacy challenges, including leakage of genotype and phenotype information from different data types and their summarization steps. Techniques enabling broad sharing and analysis while maintaining privacy are being developed.
NATURE REVIEWS GENETICS
(2022)
Article
Multidisciplinary Sciences
Zhanlin Chen, Jeremy Goldwasser, Philip Tuckman, Jason Liu, Jing Zhang, Mark Gerstein
Summary: Forest Fire Clustering is an efficient and interpretable method for extracting insights from single-cell data in the era of single-cell sequencing. It computes a non-parametric posterior probability for each data point and enables the discovery of rare cell types with label confidence and entropy computation.
NATURE COMMUNICATIONS
(2022)
Editorial Material
Genetics & Heredity
Dov Greenbaum, Mark Gerstein
Summary: GATTACA, a film released 25 years ago, portrays a credible near future where societal inequalities based on race and class have been replaced by new prejudices arising from genetic determinism. This article compares the fictional technologies in GATTACA with the current state of the art, examining the legal protections against the dystopian future portrayed in the film, where personal freedom and privacy rights are greatly curtailed by genomic innovations. It further discusses the continued relevance of GATTACA's prescient warnings in light of the ongoing advancements in genomic science and technology.
Article
Biochemistry & Molecular Biology
Guangda Shi, Claire Song, Jaylissa Torres Robles, Leonidas Salichos, Hua Jane Lou, Tukiet T. Lam, Mark Gerstein, Benjamin E. Turk
Summary: This study used a yeast-based genetic screening system to analyze a large amount of MAPK docking sequences, and identified key features for binding to JNK1 and p38 alpha, as well as specific docking groove residues that mediate selective binding. Furthermore, it verified the substrate recruitment function of the screened docking sequences in vitro and in cultured cells.
Article
Genetics & Heredity
Shuang Liu, Hyejung Won, Declan Clarke, Nana Matoba, Saniya Khullar, Yudi Mu, Daifeng Wang, Mark Gerstein
Summary: This study investigates the transcriptional regulatory structure of the human brain, revealing the coordination of both cis- and trans-regulatory variants. By analyzing large datasets, the researchers identified candidate trans-eQTLs that influence the expression of target genes and found overlap with known cis-eQTLs. Through colocalization and mediation analyses, they identified mediators in trans-regulation and linked trans-eQTLs to schizophrenia risk genes. The findings demonstrate the importance of trans-regulatory mechanisms in understanding psychiatric disorders.
Article
Multidisciplinary Sciences
Zhanlin Chen, William C. King, Aheyon Hwang, Mark Gerstein, Jing Zhang
Summary: Recent advances in single-cell sequencing technologies have led to new opportunities for studying the gene expression profile and transcriptome dynamics of individual cells. In this study, the authors propose DeepVelo, a neural network-based method that models complex transcriptome dynamics by simulating continuous changes in gene expression over time within cells. DeepVelo was applied to analyze transcriptome dynamics at different time scales and identify developmental driver genes through perturbation analysis.
Article
Health Care Sciences & Services
William U. Meyerson, Sarah K. Fineberg, Ye Kyung Song, Adam Faber, Garrett Ash, Fernanda C. Andrade, Philip Corlett, Mark B. Gerstein, Rick H. Hoyle
Summary: Researchers estimated the bedtimes of Reddit users based on their posting times and tested the accuracy using survey data. They developed an R package to apply the model and share with the research community. This model provides a passive way to infer sleep parameters of frequent social media users without the need for active surveys.
JMIR FORMATIVE RESEARCH
(2023)
Review
Genetics & Heredity
Sushant Kumar, Mark Gerstein
Summary: Genomic studies of human disorders are performed by different research communities, including rare diseases, common diseases, and cancer. Despite differences in origin, these studies aim to identify causal genomic events critical for disease manifestation. Challenges faced include understanding genetic architecture, deciphering variant impact, and interpreting noncoding mutations. A unified vocabulary and approach across disease communities is necessary to address these challenges effectively.
TRENDS IN GENETICS
(2023)
Article
Biochemical Research Methods
Shaoke Lou, Mingjun Yang, Tianxiao Li, Weihao Zhao, Hannah Cevasco, Yucheng T. Yang, Mark Gerstein
Summary: By using the statistical modeling approach MLCrosstalk, the researchers identified linkages between SARS-CoV-2, human genes, miRNAs, and microbes. They found certain human genes and microbial species that are linked to SARS-CoV-2. The findings offer potential insights for developing new treatments for COVID-19.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Multidisciplinary Sciences
Koon-Kiu Yan, Jose Condori, Zhijun Ma, Jean-Yves Metais, Bensheng Ju, Liang Ding, Yogesh Dhungana, Lance E. Palmer, Deanna M. Langfitt, Francesca Ferrara, Robert Throm, Hao Shi, Isabel Risch, Sheetal Bhatara, Bridget Shaner, Timothy D. Lockey, Aimee C. Talleur, John Easton, Michael M. Meagher, Jennifer M. Puck, Morton J. Cowan, Sheng Zhou, Ewelina Mamcarz, Stephen Gottschalk, Jiyang Yu
Summary: Lentiviral vector (LV)-based gene therapy shows promise in treating various diseases. By analyzing patient samples, we found LV integrome signatures related to genomics, epigenomics, and the 3D structure of the genome. These signatures were validated in cellular therapies and differences in 3D genome signatures between LV and gamma retrovirus integromes were identified, potentially explaining the lower risk of mutations in LV-based gene therapy.
Article
Biotechnology & Applied Microbiology
Gamze Gursoy, Charlotte M. Brannon, Eric Ni, Sarah Wagner, Amol Khanna, Mark Gerstein
Summary: Researchers have developed a private blockchain network to store genomic variants and reference-aligned reads on-chain, addressing the challenges of data ownership and integrity in genomics.
Article
Biotechnology & Applied Microbiology
Gamze Gursoy, Nancy Lu, Sarah Wagner, Mark Gerstein
Summary: With the rise of RNA sequencing efforts using large cohorts and the surveying of allele-specific gene expression, it has become common to recover key variants and link individuals back to their genotypes and phenotypes using a list of known allele-specific genes. This poses a privacy conundrum despite not explicitly containing variant information.
Article
Computer Science, Information Systems
Esha Sarkar, Eduardo Chielle, Gamze Gursoy, Oleg Mazonka, Mark Gerstein, Michail Maniatakos
Summary: Recent advances in genome sequencing technologies have provided unprecedented opportunities to understand the relationship between human genetic variation and diseases, but genotyping whole genomes remains costly. This study investigates solutions for fast, scalable, and accurate privacy-preserving genotype imputation using Machine Learning and a standardized homomorphic encryption scheme.