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Li K, Zhang P, Wang Z, Shen W, Sun W, Xu J, Wen Z, Li L. iEnhance: a multi-scale spatial projection encoding network for enhancing chromatin interaction data resolution. Brief Bioinform 2023; 24:bbad245. [PMID: 37381618 DOI: 10.1093/bib/bbad245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 06/06/2023] [Accepted: 06/12/2023] [Indexed: 06/30/2023] Open
Abstract
Although sequencing-based high-throughput chromatin interaction data are widely used to uncover genome-wide three-dimensional chromatin architecture, their sparseness and high signal-noise-ratio greatly restrict the precision of the obtained structural elements. To improve data quality, we here present iEnhance (chromatin interaction data resolution enhancement), a multi-scale spatial projection and encoding network, to predict high-resolution chromatin interaction matrices from low-resolution and noisy input data. Specifically, iEnhance projects the input data into matrix spaces to extract multi-scale global and local feature sets, then hierarchically fused these features by attention mechanism. After that, dense channel encoding and residual channel decoding are used to effectively infer robust chromatin interaction maps. iEnhance outperforms state-of-the-art Hi-C resolution enhancement tools in both visual and quantitative evaluation. Comprehensive analysis shows that unlike other tools, iEnhance can recover both short-range structural elements and long-range interaction patterns precisely. More importantly, iEnhance can be transferred to data enhancement of other tissues or cell lines of unknown resolution. Furthermore, iEnhance performs robustly in enhancement of diverse chromatin interaction data including those from single-cell Hi-C and Micro-C experiments.
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Affiliation(s)
- Kai Li
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Ping Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Zilin Wang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Wei Shen
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Weicheng Sun
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Jinsheng Xu
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Zi Wen
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Li Li
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
- Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
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Dall'Agnese G, Dall'Agnese A, Banani SF, Codrich M, Malfatti MC, Antoniali G, Tell G. Role of condensates in modulating DNA repair pathways and its implication for chemoresistance. J Biol Chem 2023:104800. [PMID: 37164156 DOI: 10.1016/j.jbc.2023.104800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 05/03/2023] [Accepted: 05/04/2023] [Indexed: 05/12/2023] Open
Abstract
For cells, it is important to repair DNA damage, such as double strand and single strand DNA breaks, because unrepaired DNA can compromise genetic integrity, potentially leading to cell death or cancer. Cells have multiple DNA damage repair pathways that have been the subject of detailed genetic, biochemical, and structural studies. Recently, the scientific community has started to gain evidence that the repair of DNA double strand breaks may occur within biomolecular condensates and that condensates may also contribute to DNA damage through concentrating genotoxic agents used to treat various cancers. Here, we summarize key features of biomolecular condensates and note where they have been implicated in the repair of DNA double strand breaks. We also describe evidence suggesting that condensates may be involved in the repair of other types of DNA damage, including single strand DNA breaks, nucleotide modifications (e.g., mismatch and oxidized bases) and bulky lesions, among others. Finally, we discuss old and new mysteries that could now be addressed considering the properties of condensates, including chemoresistance mechanisms.
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Affiliation(s)
- Giuseppe Dall'Agnese
- Laboratory of Molecular Biology and DNA repair, Department of Medicine, University of Udine, 33100 Udine, Italy; Whitehead Institute for Biomedical Research, 455 Main Street, Cambridge, MA 02142, USA
| | | | - Salman F Banani
- Whitehead Institute for Biomedical Research, 455 Main Street, Cambridge, MA 02142, USA; Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Marta Codrich
- Laboratory of Molecular Biology and DNA repair, Department of Medicine, University of Udine, 33100 Udine, Italy
| | - Matilde Clarissa Malfatti
- Laboratory of Molecular Biology and DNA repair, Department of Medicine, University of Udine, 33100 Udine, Italy
| | - Giulia Antoniali
- Laboratory of Molecular Biology and DNA repair, Department of Medicine, University of Udine, 33100 Udine, Italy
| | - Gianluca Tell
- Laboratory of Molecular Biology and DNA repair, Department of Medicine, University of Udine, 33100 Udine, Italy.
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Pu J, Wang B, Liu X, Chen L, Li SC. SMURF: embedding single-cell RNA-seq data with matrix factorization preserving self-consistency. Brief Bioinform 2023; 24:7008800. [PMID: 36715274 DOI: 10.1093/bib/bbad026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 12/17/2022] [Accepted: 01/09/2023] [Indexed: 01/31/2023] Open
Abstract
The advance in single-cell RNA-sequencing (scRNA-seq) sheds light on cell-specific transcriptomic studies of cell developments, complex diseases and cancers. Nevertheless, scRNA-seq techniques suffer from 'dropout' events, and imputation tools are proposed to address the sparsity. Here, rather than imputation, we propose a tool, SMURF, to extract the low-dimensional embeddings from cells and genes utilizing matrix factorization with a mixture of Poisson-Gamma divergent as objective while preserving self-consistency. SMURF exhibits feasible cell subpopulation discovery efficacy with obtained cell embeddings on replicated in silico and eight web lab scRNA datasets with ground truth cell types. Furthermore, SMURF can reduce the cell embedding to a 1D-oval space to recover the time course of cell cycle. SMURF can also serve as an imputation tool; the in silico data assessment shows that SMURF parades the most robust gene expression recovery power with low root mean square error and high Pearson correlation. Moreover, SMURF recovers the gene distribution for the WM989 Drop-seq data. SMURF is available at https://github.com/deepomicslab/SMURF.
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Affiliation(s)
- Juhua Pu
- State Key Laboratory of Software Development Environment, Beihang University, Beijing, China
- Beihang Hangzhou Innovation Institute Yuhang, Xixi Octagon City, Yuhang District, Hangzhou 310023, China
| | - Bingchen Wang
- State Key Laboratory of Software Development Environment, Beihang University, Beijing, China
- Beihang Hangzhou Innovation Institute Yuhang, Xixi Octagon City, Yuhang District, Hangzhou 310023, China
| | - Xingwu Liu
- School of Mathematical Sciences, Dalian University of Technology, Dalian, Liaoning, China
| | - Lingxi Chen
- Department of Computer Science, City University of Hong Kong, 83 Tat Chee Ave, Kowloon Tong, Hong Kong, China
| | - Shuai Cheng Li
- Department of Computer Science, City University of Hong Kong, 83 Tat Chee Ave, Kowloon Tong, Hong Kong, China
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Kołat D, Zhao LY, Kciuk M, Płuciennik E, Kałuzińska-Kołat Ż. AP-2δ Is the Most Relevant Target of AP-2 Family-Focused Cancer Therapy and Affects Genome Organization. Cells 2022; 11:cells11244124. [PMID: 36552887 PMCID: PMC9776946 DOI: 10.3390/cells11244124] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 11/26/2022] [Accepted: 12/15/2022] [Indexed: 12/24/2022] Open
Abstract
Formerly hailed as "undruggable" proteins, transcription factors (TFs) are now under investigation for targeted therapy. In cancer, this may alter, inter alia, immune evasion or replicative immortality, which are implicated in genome organization, a process that accompanies multi-step tumorigenesis and which frequently develops in a non-random manner. Still, targeting-related research on some TFs is scarce, e.g., among AP-2 proteins, which are known for their altered functionality in cancer and prognostic importance. Using public repositories, bioinformatics tools, and RNA-seq data, the present study examined the ligandability of all AP-2 members, selecting the best one, which was investigated in terms of mutations, targets, co-activators, correlated genes, and impact on genome organization. AP-2 proteins were found to have the conserved "TF_AP-2" domain, but manifested different binding characteristics and evolution. Among them, AP-2δ has not only the highest number of post-translational modifications and extended strands but also contains a specific histidine-rich region and cleft that can receive a ligand. Uterine, colon, lung, and stomach tumors are most susceptible to AP-2δ mutations, which also co-depend with cancer hallmark genes and drug targets. Considering AP-2δ targets, some of them were located proximally in the spatial genome or served as co-factors of the genes regulated by AP-2δ. Correlation and functional analyses suggested that AP-2δ affects various processes, including genome organization, via its targets; this has been eventually verified in lung adenocarcinoma using expression and immunohistochemistry data of chromosomal conformation-related genes. In conclusion, AP-2δ affects chromosomal conformation and is the most appropriate target for cancer therapy focused on the AP-2 family.
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Affiliation(s)
- Damian Kołat
- Department of Experimental Surgery, Medical University of Lodz, 90-136 Lodz, Poland
- Correspondence:
| | - Lin-Yong Zhao
- Gastric Cancer Center and Laboratory of Gastric Cancer, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, and Collaborative Innovation Centre for Biotherapy, Chengdu 610041, China
| | - Mateusz Kciuk
- Department of Molecular Biotechnology and Genetics, University of Lodz, 90-237 Lodz, Poland
- Doctoral School of Exact and Natural Sciences, University of Lodz, 90-237 Lodz, Poland
| | - Elżbieta Płuciennik
- Department of Functional Genomics, Medical University of Lodz, 90-752 Lodz, Poland
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Chen L, Li S. Incorporating cell hierarchy to decipher the functional diversity of single cells. Nucleic Acids Res 2022; 51:e9. [PMID: 36373664 PMCID: PMC9881154 DOI: 10.1093/nar/gkac1044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 10/13/2022] [Accepted: 10/21/2022] [Indexed: 11/16/2022] Open
Abstract
Cells possess functional diversity hierarchically. However, most single-cell analyses neglect the nested structures while detecting and visualizing the functional diversity. Here, we incorporate cell hierarchy to study functional diversity at subpopulation, club (i.e., sub-subpopulation), and cell layers. Accordingly, we implement a package, SEAT, to construct cell hierarchies utilizing structure entropy by minimizing the global uncertainty in cell-cell graphs. With cell hierarchies, SEAT deciphers functional diversity in 36 datasets covering scRNA, scDNA, scATAC, and scRNA-scATAC multiome. First, SEAT finds optimal cell subpopulations with high clustering accuracy. It identifies cell types or fates from omics profiles and boosts accuracy from 0.34 to 1. Second, SEAT detects insightful functional diversity among cell clubs. The hierarchy of breast cancer cells reveals that the specific tumor cell club drives AREG-EGFT signaling. We identify a dense co-accessibility network of cis-regulatory elements specified by one cell club in GM12878. Third, the cell order from the hierarchy infers periodic pseudo-time of cells, improving accuracy from 0.79 to 0.89. Moreover, we incorporate cell hierarchy layers as prior knowledge to refine nonlinear dimension reduction, enabling us to visualize hierarchical cell layouts in low-dimensional space.
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Affiliation(s)
- Lingxi Chen
- Department of Computer Science, City University of Hong Kong, 83 Tat Chee Ave, Kowloon Tong, Hong Kong, China,City University of Hong Kong Shenzhen Research Institute, Shenzhen, 518057, Guangdong, China
| | - Shuai Cheng Li
- To whom correspondence should be addressed. Tel: +852 34429412; Fax: +852 34420503;
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