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Drogaris C, Zhang Y, Zhang E, Nazarova E, Sarrazin-Gendron R, Wilhelm-Landry S, Cyr Y, Majewski J, Blanchette M, Waldispühl J. ARGV: 3D genome structure exploration using augmented reality. BMC Bioinformatics 2024; 25:277. [PMID: 39192184 DOI: 10.1186/s12859-024-05882-8] [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: 12/09/2023] [Accepted: 07/25/2024] [Indexed: 08/29/2024] Open
Abstract
Over the past two decades, scientists have increasingly realized the importance of the three-dimensional (3D) genome organization in regulating cellular activity. Hi-C and related experiments yield 2D contact matrices that can be used to infer 3D models of chromosome structure. Visualizing and analyzing genomes in 3D space remains challenging. Here, we present ARGV, an augmented reality 3D Genome Viewer. ARGV contains more than 350 pre-computed and annotated genome structures inferred from Hi-C and imaging data. It offers interactive and collaborative visualization of genomes in 3D space, using standard mobile phones or tablets. A user study comparing ARGV to existing tools demonstrates its benefits.
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Affiliation(s)
| | - Yanlin Zhang
- School of Computer Science, McGill University, Montréal, QC, H3A 0E9, Canada
| | - Eric Zhang
- School of Computer Science, McGill University, Montréal, QC, H3A 0E9, Canada
| | - Elena Nazarova
- School of Computer Science, McGill University, Montréal, QC, H3A 0E9, Canada
| | | | | | - Yan Cyr
- Beam Me Up Inc., 5925 Monkland Ave, Suite, 100, Montréal, H4A 1G7, Canada
| | - Jacek Majewski
- Department of Human Genetics, McGill University, Montréal, QC, H3A 1B1, Canada
| | - Mathieu Blanchette
- School of Computer Science, McGill University, Montréal, QC, H3A 0E9, Canada
| | - Jérôme Waldispühl
- School of Computer Science, McGill University, Montréal, QC, H3A 0E9, Canada.
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2
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Su X, Yan L, Si J, Wang Z, Liang C, Peng K, Shen J, Duan S. LINC00319: Unraveling the spectrum from gene regulation to clinical applications in cancer progression. Gene 2024; 896:148044. [PMID: 38042213 DOI: 10.1016/j.gene.2023.148044] [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: 10/06/2023] [Revised: 11/13/2023] [Accepted: 11/28/2023] [Indexed: 12/04/2023]
Abstract
LncRNAs are RNA transcripts that exceed 200 nucleotides in length and do not encode proteins. LINC00319 is a type of lncRNA that is highly expressed in various cancers and is regulated by CCL18 and MYC. High levels of LINC00319 are associated with poorer prognosis and more malignant clinical features in cancer patients. LINC00319 can regulate the expression of downstream genes, including 2 protein-coding genes and 11 miRNAs. It participates in controlling three signaling pathways and various cellular behaviors. LINC00319 and its downstream genes are potential targets for cancer therapy and are associated with common cancer treatments. This article reviews the abnormal expression of LINC00319 in human cancers and related molecular mechanisms, providing clues for further diagnosis and treatment.
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Affiliation(s)
- Xinming Su
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China; Department of Clinical Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Lingtao Yan
- Medical Genetics Center, Department of Medicine, Ningbo University, Ningbo, Zhejiang, China
| | - Jiahua Si
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China; Department of Clinical Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Zehua Wang
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China; Department of Clinical Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Chenhao Liang
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China; Department of Clinical Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Kehao Peng
- The Second School of Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Jinze Shen
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China; Department of Clinical Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Shiwei Duan
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China; Department of Clinical Medicine, Hangzhou City University, Hangzhou, Zhejiang, China.
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Sridhar A, More AS, Jadhav AR, Patil K, Mavlankar A, Dixit VM, Bapat SA. Pattern recognition in the landscape of seemingly random chimeric transcripts. Comput Struct Biotechnol J 2023; 21:5153-5164. [PMID: 37920814 PMCID: PMC10618115 DOI: 10.1016/j.csbj.2023.10.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 10/13/2023] [Accepted: 10/16/2023] [Indexed: 11/04/2023] Open
Abstract
The molecular and functional diversity generated by chimeric transcripts (CTs) that are derived from two genes is indicated to contribute to tumor cell survival. Several gaps yet exist. The present research is a systematic study of the spectrum of CTs identified in RNA sequencing datasets of 160 ovarian cancer samples in the The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov). Structural annotation revealed complexities emerging from chromosomal localization of partner genes, differential splicing and inclusion of regulatory, untranslated regions. Identification of phenotype-specific associations further resolved a dynamically modulated mesenchymal signature during transformation. On an evolutionary background, protein-coding CTs were indicated to be highly conserved, while non-coding CTs may have evolved more recently. We also realized that the current premise postulating structural alterations or neighbouring gene readthrough generating CTs is not valid in instances wherein the parental genes are genomically distanced. In addressing this lacuna, we identified the essentiality of specific spatiotemporal arrangements mediated gene proximities in 3D space for the generation of CTs. All these features together suggest non-random mechanisms towards increasing the molecular diversity in a cell through chimera formation either in parallel or with cross-talks with the indigenous regulatory network.
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Affiliation(s)
- Aksheetha Sridhar
- Open Health Systems Laboratory, 9601 Medical Centre Drive, Rockville, MD 20850, US
| | - Ankita S. More
- National Centre for Cell Science, Savitribai Phule Pune University, Ganeshkhind, Pune 411 007, Maharashtra, India
| | - Amruta R. Jadhav
- National Centre for Cell Science, Savitribai Phule Pune University, Ganeshkhind, Pune 411 007, Maharashtra, India
| | - Komal Patil
- National Centre for Cell Science, Savitribai Phule Pune University, Ganeshkhind, Pune 411 007, Maharashtra, India
| | - Anuj Mavlankar
- National Centre for Cell Science, Savitribai Phule Pune University, Ganeshkhind, Pune 411 007, Maharashtra, India
| | - Vaishnavi M. Dixit
- National Centre for Cell Science, Savitribai Phule Pune University, Ganeshkhind, Pune 411 007, Maharashtra, India
| | - Sharmila A. Bapat
- Open Health Systems Laboratory, 9601 Medical Centre Drive, Rockville, MD 20850, US
- National Centre for Cell Science, Savitribai Phule Pune University, Ganeshkhind, Pune 411 007, Maharashtra, India
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4
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Li P, Liu H, Sun J, Lu J, Liu J. HiBrowser: an interactive and dynamic browser for synchronous Hi-C data visualization. Brief Bioinform 2023; 24:bbad283. [PMID: 37544661 DOI: 10.1093/bib/bbad283] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/14/2023] [Accepted: 07/20/2023] [Indexed: 08/08/2023] Open
Abstract
With the development of chromosome conformation capture technology, the genome-wide investigation of higher-order chromatin structure by using high-throughput chromatin conformation capture (Hi-C) technology is emerging as an important component for understanding the mechanism of gene regulation. Considering genetic and epigenetic differences are typically used to explore the pathological reasons on the chromosome and gene level, visualizing multi-omics data and performing an intuitive analysis by using an interactive browser become a powerful and welcomed way. In this paper, we develop an effective sequence and chromatin interaction data display browser called HiBrowser for visualizing and analyzing Hi-C data and their associated genetic and epigenetic annotations. The advantages of HiBrowser are flexible multi-omics navigation, novel multidimensional synchronization comparisons and dynamic interaction system. In particular, HiBrowser first provides an out of the box web service and allows flexible and dynamic reconstruction of custom annotation tracks on demand during running. In order to conveniently and intuitively analyze the similarities and differences among multiple samples, such as visual comparisons of normal and tumor tissue samples, and pan genomes of multiple (consanguineous) species, HiBrowser develops a clone mode to synchronously display the genome coordinate positions or the same regions of multiple samples on the same page of visualization. HiBrowser also supports a pluralistic and precise search on correlation data of distal cis-regulatory elements and navigation to any region on Hi-C heatmap of interest according to the searching results. HiBrowser is a no-build tool, and could be easily deployed in local server. The source code is available at https://github.com/lyotvincent/HiBrowser.
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Affiliation(s)
- Pingjing Li
- College of Computer Science, Nankai University, Tianjin 300071, China
- Centre for Bioinformatics and Intelligent Medicine, Nankai University, Tianjin 300071, China
| | - Hong Liu
- The Second Surgical Department of Breast Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, China
| | - Jialiang Sun
- College of Computer Science, Nankai University, Tianjin 300071, China
- Centre for Bioinformatics and Intelligent Medicine, Nankai University, Tianjin 300071, China
| | - Jianguo Lu
- School of Marine Sciences, Sun Yat-sen University, China
| | - Jian Liu
- College of Computer Science, Nankai University, Tianjin 300071, China
- Centre for Bioinformatics and Intelligent Medicine, Nankai University, Tianjin 300071, China
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Hartley M, Iudin A, Padwardhan A, Sarkans U, Yoldaş AK, Kleywegt GJ. Providing open imaging data at scale: An EMBL-EBI perspective. Histochem Cell Biol 2023; 160:211-221. [PMID: 37537341 PMCID: PMC10492673 DOI: 10.1007/s00418-023-02216-2] [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] [Accepted: 05/30/2023] [Indexed: 08/05/2023]
Abstract
Biological imaging is one of the primary tools by which we understand living systems across scales from atoms to organisms. Rapid advances in imaging technology have increased both the spatial and temporal resolutions at which we examine those systems, as well as enabling visualisation of larger tissue volumes. These advances have huge potential but also generate ever increasing amounts of imaging data that must be stored and analysed. Public image repositories provide a critical scientific service through open data provision, supporting reproducibility of scientific results, access to reference imaging datasets and reuse of data for new scientific discovery and acceleration of image analysis methods development. The scale and scope of imaging data provides both challenges and opportunities for open sharing of image data. In this article, we provide a perspective influenced by decades of provision of open data resources for biological information, suggesting areas to focus on and a path towards global interoperability.
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Affiliation(s)
- Matthew Hartley
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK.
| | - Andrii Iudin
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Ardan Padwardhan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Ugis Sarkans
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Aybüke Küpcü Yoldaş
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Gerard J Kleywegt
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
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Dekker J, Alber F, Aufmkolk S, Beliveau BJ, Bruneau BG, Belmont AS, Bintu L, Boettiger A, Calandrelli R, Disteche CM, Gilbert DM, Gregor T, Hansen AS, Huang B, Huangfu D, Kalhor R, Leslie CS, Li W, Li Y, Ma J, Noble WS, Park PJ, Phillips-Cremins JE, Pollard KS, Rafelski SM, Ren B, Ruan Y, Shav-Tal Y, Shen Y, Shendure J, Shu X, Strambio-De-Castillia C, Vertii A, Zhang H, Zhong S. Spatial and temporal organization of the genome: Current state and future aims of the 4D nucleome project. Mol Cell 2023; 83:2624-2640. [PMID: 37419111 PMCID: PMC10528254 DOI: 10.1016/j.molcel.2023.06.018] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 06/10/2023] [Accepted: 06/12/2023] [Indexed: 07/09/2023]
Abstract
The four-dimensional nucleome (4DN) consortium studies the architecture of the genome and the nucleus in space and time. We summarize progress by the consortium and highlight the development of technologies for (1) mapping genome folding and identifying roles of nuclear components and bodies, proteins, and RNA, (2) characterizing nuclear organization with time or single-cell resolution, and (3) imaging of nuclear organization. With these tools, the consortium has provided over 2,000 public datasets. Integrative computational models based on these data are starting to reveal connections between genome structure and function. We then present a forward-looking perspective and outline current aims to (1) delineate dynamics of nuclear architecture at different timescales, from minutes to weeks as cells differentiate, in populations and in single cells, (2) characterize cis-determinants and trans-modulators of genome organization, (3) test functional consequences of changes in cis- and trans-regulators, and (4) develop predictive models of genome structure and function.
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Affiliation(s)
- Job Dekker
- University of Massachusetts Chan Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA.
| | - Frank Alber
- University of California, Los Angeles, Los Angeles, CA, USA
| | | | | | - Benoit G Bruneau
- Gladstone Institutes, San Francisco, CA, USA; University of California, San Francisco, San Francisco, CA, USA
| | | | | | | | | | | | | | | | | | - Bo Huang
- University of California, San Francisco, San Francisco, CA, USA
| | - Danwei Huangfu
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Reza Kalhor
- Johns Hopkins University, Baltimore, MD, USA
| | | | - Wenbo Li
- University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yun Li
- University of North Carolina, Gillings School of Global Public Health, Chapel Hill, NC, USA
| | - Jian Ma
- Carnegie Mellon University, Pittsburgh, PA, USA
| | | | | | | | - Katherine S Pollard
- Gladstone Institutes, San Francisco, CA, USA; University of California, San Francisco, San Francisco, CA, USA; Chan Zuckerberg Biohub, San Francisco, San Francisco, CA, USA
| | | | - Bing Ren
- University of California, San Diego, La Jolla, CA, USA
| | - Yijun Ruan
- Zhejiang University, Hangzhou, Zhejiang, China
| | | | - Yin Shen
- University of California, San Francisco, San Francisco, CA, USA
| | | | - Xiaokun Shu
- University of California, San Francisco, San Francisco, CA, USA
| | | | | | | | - Sheng Zhong
- University of California, San Diego, La Jolla, CA, USA.
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7
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Pancaldi V. Network models of chromatin structure. Curr Opin Genet Dev 2023; 80:102051. [PMID: 37245241 DOI: 10.1016/j.gde.2023.102051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 04/13/2023] [Accepted: 04/14/2023] [Indexed: 05/30/2023]
Abstract
Increasing numbers of datasets and experimental assays that capture the organization of chromatin inside the nucleus warrant an effort to develop tools to visualize and analyze these structures. Alongside polymer physics or constraint-based modeling, network theory approaches to describe 3D epigenome organization have gained in popularity. Representing genomic regions as nodes in a network enables visualization of 1D epigenomics datasets in the context of chromatin structure maps, while network theory metrics can be used to describe 3D epigenome organization and dynamics. In this review, we summarize the most salient applications of network theory to the study of chromatin contact maps, demonstrating its potential in revealing epigenomic patterns and relating them to cellular phenotypes.
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Affiliation(s)
- Vera Pancaldi
- CRCT, Université de Toulouse, Inserm, CNRS, Université Toulouse III-Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Toulouse, France.
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Maloshenok LG, Abushinova GA, Ryazanova AY, Bruskin SA, Zherdeva VV. Visualizing the Nucleome Using the CRISPR–Cas9 System: From in vitro to in vivo. BIOCHEMISTRY (MOSCOW) 2023; 88:S123-S149. [PMID: 37069118 PMCID: PMC9940691 DOI: 10.1134/s0006297923140080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/22/2023]
Abstract
One of the latest methods in modern molecular biology is labeling genomic loci in living cells using fluorescently labeled Cas protein. The NIH Foundation has made the mapping of the 4D nucleome (the three-dimensional nucleome on a timescale) a priority in the studies aimed to improve our understanding of chromatin organization. Fluorescent methods based on CRISPR-Cas are a significant step forward in visualization of genomic loci in living cells. This approach can be used for studying epigenetics, cell cycle, cellular response to external stimuli, rearrangements during malignant cell transformation, such as chromosomal translocations or damage, as well as for genome editing. In this review, we focused on the application of CRISPR-Cas fluorescence technologies as components of multimodal imaging methods for in vivo mapping of chromosomal loci, in particular, attribution of fluorescence signal to morphological and anatomical structures in a living organism. The review discusses the approaches to the highly sensitive, high-precision labeling of CRISPR-Cas components, delivery of genetically engineered constructs into cells and tissues, and promising methods for molecular imaging.
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Affiliation(s)
- Liliya G Maloshenok
- Bach Institute of Biochemistry, Federal Research Center for Biotechnology of the Russian Academy of Sciences, Moscow, 119071, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, 119991, Russia
| | - Gerel A Abushinova
- Bach Institute of Biochemistry, Federal Research Center for Biotechnology of the Russian Academy of Sciences, Moscow, 119071, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, 119991, Russia
| | - Alexandra Yu Ryazanova
- Bach Institute of Biochemistry, Federal Research Center for Biotechnology of the Russian Academy of Sciences, Moscow, 119071, Russia
| | - Sergey A Bruskin
- Bach Institute of Biochemistry, Federal Research Center for Biotechnology of the Russian Academy of Sciences, Moscow, 119071, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, 119991, Russia
| | - Victoria V Zherdeva
- Bach Institute of Biochemistry, Federal Research Center for Biotechnology of the Russian Academy of Sciences, Moscow, 119071, Russia.
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