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.
Polymer models are a versatile tool to study chromatin 3d organization / Esposito, A.; Bianco, S.; Fiorillo, L.; Conte, M.; Abraham, A.; Musella, F.; Nicodemi, M.; Prisco, A.; Chiariello, A. M.. - In: BIOCHEMICAL SOCIETY TRANSACTIONS. - ISSN 0300-5127. - 49:4(2021), pp. 1675-1684. [10.1042/BST20201004]
Polymer models are a versatile tool to study chromatin 3d organization
Esposito A.;Bianco S.;Abraham A.;Nicodemi M.;Chiariello A. M.Ultimo
2021
Abstract
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.File | Dimensione | Formato | |
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