A Polymer Physics Model to Dissect Genome Organization in Healthy and Pathological Phenotypes

A Polymer Physics Model for Epigenetic Control of Chromatin Compaction

Biophysical Journal ◽

10.1016/j.bpj.2017.11.3080 ◽

2018 ◽

Vol 114 (3) ◽

pp. 563a ◽

Cited By ~ 1

Author(s):

Quinn MacPherson ◽

Sarah Sandholtz ◽

Andrew Spakowitz

Keyword(s):

Polymer Physics ◽

Chromatin Compaction ◽

Epigenetic Control ◽

Physics Model

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Genome organization via loop extrusion, insights from polymer physics models

Briefings in Functional Genomics ◽

10.1093/bfgp/elz023 ◽

2019 ◽

Vol 19 (2) ◽

pp. 119-127 ◽

Cited By ~ 4

Author(s):

Surya K Ghosh ◽

Daniel Jost

Keyword(s):

Genome Organization ◽

Extrusion Process ◽

Polymer Physics ◽

Modern Biology ◽

Precise Information ◽

Multi Scale ◽

Topologically Associated Domains ◽

Structural Maintenance Of Chromosome ◽

Smc Proteins

Abstract Understanding how genomes fold and organize is one of the main challenges in modern biology. Recent high-throughput techniques like Hi-C, in combination with cutting-edge polymer physics models, have provided access to precise information on 3D chromosome folding to decipher the mechanisms driving such multi-scale organization. In particular, structural maintenance of chromosome (SMC) proteins play an important role in the local structuration of chromatin, putatively via a loop extrusion process. Here, we review the different polymer physics models that investigate the role of SMCs in the formation of topologically associated domains (TADs) during interphase via the formation of dynamic loops. We describe the main physical ingredients, compare them and discuss their relevance against experimental observations.

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RNA structure prediction including pseudoknots through direct enumeration of states

10.1101/338921 ◽

2018 ◽

Author(s):

Ofer Kimchi ◽

Tristan Cragnolini ◽

Michael P. Brenner ◽

Lucy J. Colwell

Keyword(s):

Rna Structure ◽

Structure Prediction ◽

Secondary Structures ◽

Polymer Physics ◽

Rna Sequences ◽

Rna Structure Prediction ◽

Order Of Magnitude ◽

Np Complete ◽

Physics Model ◽

Physical Quantities

The accurate prediction of RNA secondary structure from primary sequence has had enormous impact on research from the past forty years. While many algorithms are available to make these predictions, the inclusion of non-nested loops, termed pseudoknots, still poses challenges. Here, we describe a new method to compute the entire free energy landscape of secondary structures of RNA resulting from a primary RNA sequence, by combining a polymer physics model for the entropy of pseudoknots with exhaustive enumeration of the set of possible structures. Our polymer physics model can address arbitrarily complex pseudoknots and has only two free loop entropy parameters that correspond to concrete physical quantities, over an order of magnitude fewer than even the sparsest state-of-the-art algorithms. Our model outperforms previously published methods in predicting pseudoknots, while performing on par with current methods in the prediction of non-pseudoknotted structures. For RNA sequences of ~ 45 nucleotides, or ~ 90 with minimal heuristics, the complet–e enumeration of possible secondary structures can be accomplished quickly despite the NP-complete nature of the problem.

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Two-Phase Dynamics of DNA Supercoiling Based on DNA Polymer Physics Model

Biophysical Journal ◽

10.1016/j.bpj.2020.11.1491 ◽

2021 ◽

Vol 120 (3) ◽

pp. 223a

Author(s):

Biao Wan ◽

Xinliang Xu ◽

Jin Yu

Keyword(s):

Dna Supercoiling ◽

Polymer Physics ◽

Two Phase ◽

Phase Dynamics ◽

Physics Model

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Polymer models are a versatile tool to study chromatin 3D organization

Biochemical Society Transactions ◽

10.1042/bst20201004 ◽

2021 ◽

Author(s):

Andrea Esposito ◽

Simona Bianco ◽

Luca Fiorillo ◽

Mattia Conte ◽

Alex Abraham ◽

...

Keyword(s):

Genome Organization ◽

Three Dimensional ◽

Polymer Physics ◽

Dynamics Simulation ◽

Structural Rearrangements ◽

Cell Level ◽

Architectural Elements ◽

Theoretical Approaches ◽

Versatile Tool ◽

Polymer Models

The development of new experimental technologies is opening the way to a deeper investigation of the three-dimensional organization of chromosomes inside the cell nucleus. Genome architecture is linked to vital functional purposes, yet a full comprehension of the mechanisms behind DNA folding is still far from being accomplished. Theoretical approaches based on polymer physics have been employed to understand the complexity of chromatin architecture data and to unveil the basic mechanisms shaping its structure. Here, we review some recent advances in the field to discuss how Polymer Physics, combined with numerical Molecular Dynamics simulation and Machine Learning based inference, can capture important aspects of genome organization, including the description of tissue-specific structural rearrangements, the detection of novel, regulatory-linked architectural elements and the structural variability of chromatin at the single-cell level.

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