A Scalable Computational Approach for Simulating Complexes of Multiple Chromosomes |
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| Institution: | 1. Center for Theoretical Biological Physics, Rice University, Houston, TX, USA;2. ICTP South American Institute for Fundamental Research, Instituto de Física Teórica, UNESP – 01140-070, São Paulo, SP, Brazil;3. Instituto de Biociências, Letras e Ciências Exatas, UNESP - Univ. Estadual Paulista, Departamento de Física, São José do Rio Preto, SP, Brazil;4. Chemical Engineering Department, Military Institute of Engineering, Rio de Janeiro, RJ, Brazil;1. Izmir Biomedicine and Genome Center, Dokuz Eylül University Health Campus, Balçova, Izmir 35330, Turkey;2. Izmir Biomedicine and Genome Institute, Dokuz Eylül University Health Campus, Balçova, Izmir 35330, Turkey;3. Université Grenoble Alpes, CNRS UMR 5309, INSERM U1209, Institute for Advanced Biosciences (IAB), Site Santé – Allée des Alpes, 38700 La Tronche, France;1. Department of Mathematics and Statistics, Viral Information Institute and Computational Science Research Center, San Diego State University, San Diego, California;2. Department of Chemistry, New York University, New York, New York;3. Courant Institute of Mathematical Sciences, New York University, New York, New York;4. New York University-East China Normal University Center for Computational Chemistry at New York University Shanghai, Shanghai, China;1. Department of Chemistry, New York University, 1021 Silver, 100 Washington Square East, New York, NY, 10003, USA;2. Perelman School of Medicine, Department of Physiology, University of Pennsylvania, Clinical Research Building, 415 Curie Boulevard, Philadelphia, PA 19104, USA;3. Perelman School of Medicine, Department of Cell and Developmental Biology, University of Pennsylvania, Clinical Research Building, 415 Curie Boulevard, Philadelphia, PA 19104, USA;4. Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain;5. Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Spain;6. Institució Catalana de Recerca i Estudis Avançats (ICREA), Pg. Lluís Companys 23, 08010 Barcelona, Spain;7. Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou 510005, China;8. CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China;9. New York University-East China Normal University Center for Computational Chemistry at New York University Shanghai, Room 340, Geography Building, 3663 North Zhongshan Road, Shanghai, 200062, China;10. Courant Institute of Mathematical Sciences, New York University, 251 Mercer St, New York, NY, 10012, USA;1. Biophysics Program, Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742, United States;2. Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, United States;3. Department of Chemistry and Biochemistry, University of Maryland, College Park, MD 20742, United States |
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| Abstract: | Significant efforts have been recently made to obtain the three-dimensional (3D) structure of the genome with the goal of understanding how structures may affect gene regulation and expression. Chromosome conformational capture techniques such as Hi-C, have been key in uncovering the quantitative information needed to determine chromatin organization. Complementing these experimental tools, co-polymers theoretical methods are necessary to determine the ensemble of three-dimensional structures associated to the experimental data provided by Hi-C maps. Going beyond just structural information, these theoretical advances also start to provide an understanding of the underlying mechanisms governing genome assembly and function. Recent theoretical work, however, has been focused on single chromosome structures, missing the fact that, in the full nucleus, interactions between chromosomes play a central role in their organization. To overcome this limitation, MiChroM (Minimal Chromatin Model) has been modified to become capable of performing these multi-chromosome simulations. It has been upgraded into a fast and scalable software version, which is able to perform chromosome simulations using GPUs via OpenMM Python API, called Open-MiChroM. To validate the efficiency of this new version, analyses for GM12878 individual autosomes were performed and compared to earlier studies. This validation was followed by multi-chain simulations including the four largest human chromosomes (C1-C4). These simulations demonstrated the full power of this new approach. Comparison to Hi-C data shows that these multiple chromosome interactions are essential for a more accurate agreement with experimental results. Without any changes to the original MiChroM potential, it is now possible to predict experimentally observed inter-chromosome contacts. This scalability of Open-MiChroM allow for more audacious investigations, looking at interactions of multiple chains as well as moving towards higher resolution chromosomes models. |
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| Keywords: | genome architecture Hi-C OpenMM chromosome simulations |
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