Literature DB >> 33552135

Predicting Genome Architecture: Challenges and Solutions.

Polina Belokopytova1,2, Veniamin Fishman1,2.   

Abstract

Genome architecture plays a pivotal role in gene regulation. The use of high-throughput methods for chromatin profiling and 3-D interaction mapping provide rich experimental data sets describing genome organization and dynamics. These data challenge development of new models and algorithms connecting genome architecture with epigenetic marks. In this review, we describe how chromatin architecture could be reconstructed from epigenetic data using biophysical or statistical approaches. We discuss the applicability and limitations of these methods for understanding the mechanisms of chromatin organization. We also highlight the emergence of new predictive approaches for scoring effects of structural variations in human cells.
Copyright © 2021 Belokopytova and Fishman.

Entities:  

Keywords:  Hi-C; machine learning; modeling; polymer physics; predicting approaches

Year:  2021        PMID: 33552135      PMCID: PMC7862721          DOI: 10.3389/fgene.2020.617202

Source DB:  PubMed          Journal:  Front Genet        ISSN: 1664-8021            Impact factor:   4.599


  108 in total

1.  The fractal globule as a model of chromatin architecture in the cell.

Authors:  Leonid A Mirny
Journal:  Chromosome Res       Date:  2011-01       Impact factor: 5.239

2.  Serial genomic inversions induce tissue-specific architectural stripes, gene misexpression and congenital malformations.

Authors:  Katerina Kraft; Andreas Magg; Verena Heinrich; Christina Riemenschneider; Robert Schöpflin; Julia Markowski; Daniel M Ibrahim; Rocío Acuna-Hidalgo; Alexandra Despang; Guillaume Andrey; Lars Wittler; Bernd Timmermann; Martin Vingron; Stefan Mundlos
Journal:  Nat Cell Biol       Date:  2019-02-11       Impact factor: 28.824

3.  DeepTACT: predicting 3D chromatin contacts via bootstrapping deep learning.

Authors:  Wenran Li; Wing Hung Wong; Rui Jiang
Journal:  Nucleic Acids Res       Date:  2019-06-04       Impact factor: 16.971

4.  Ultrastructural Details of Mammalian Chromosome Architecture.

Authors:  Nils Krietenstein; Sameer Abraham; Sergey V Venev; Nezar Abdennur; Johan Gibcus; Tsung-Han S Hsieh; Krishna Mohan Parsi; Liyan Yang; René Maehr; Leonid A Mirny; Job Dekker; Oliver J Rando
Journal:  Mol Cell       Date:  2020-03-25       Impact factor: 17.970

5.  Constructing 3D interaction maps from 1D epigenomes.

Authors:  Yun Zhu; Zhao Chen; Kai Zhang; Mengchi Wang; David Medovoy; John W Whitaker; Bo Ding; Nan Li; Lina Zheng; Wei Wang
Journal:  Nat Commun       Date:  2016-03-10       Impact factor: 14.919

6.  Predicting CTCF-mediated chromatin loops using CTCF-MP.

Authors:  Ruochi Zhang; Yuchuan Wang; Yang Yang; Yang Zhang; Jian Ma
Journal:  Bioinformatics       Date:  2018-07-01       Impact factor: 6.937

7.  Bottom-up modeling of chromatin segregation due to epigenetic modifications.

Authors:  Quinn MacPherson; Bruno Beltran; Andrew J Spakowitz
Journal:  Proc Natl Acad Sci U S A       Date:  2018-11-26       Impact factor: 11.205

8.  Machine learning and complex biological data.

Authors:  Chunming Xu; Scott A Jackson
Journal:  Genome Biol       Date:  2019-04-16       Impact factor: 13.583

9.  Multiplexed analysis of chromosome conformation at vastly improved sensitivity.

Authors:  James O J Davies; Jelena M Telenius; Simon J McGowan; Nigel A Roberts; Stephen Taylor; Douglas R Higgs; Jim R Hughes
Journal:  Nat Methods       Date:  2015-11-23       Impact factor: 28.547

10.  Chromatin organization by an interplay of loop extrusion and compartmental segregation.

Authors:  Johannes Nuebler; Geoffrey Fudenberg; Maxim Imakaev; Nezar Abdennur; Leonid A Mirny
Journal:  Proc Natl Acad Sci U S A       Date:  2018-07-02       Impact factor: 11.205

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  3 in total

1.  3DGenBench: a web-server to benchmark computational models for 3D Genomics.

Authors: 
Journal:  Nucleic Acids Res       Date:  2022-05-25       Impact factor: 19.160

2.  preciseTAD: A transfer learning framework for 3D domain boundary prediction at base-pair resolution.

Authors:  Spiro C Stilianoudakis; Maggie A Marshall; Mikhail G Dozmorov
Journal:  Bioinformatics       Date:  2021-11-06       Impact factor: 6.937

3.  Anopheles mosquitoes reveal new principles of 3D genome organization in insects.

Authors:  Varvara Lukyanchikova; Miroslav Nuriddinov; Polina Belokopytova; Alena Taskina; Jiangtao Liang; Maarten J M F Reijnders; Livio Ruzzante; Romain Feron; Robert M Waterhouse; Yang Wu; Chunhong Mao; Zhijian Tu; Igor V Sharakhov; Veniamin Fishman
Journal:  Nat Commun       Date:  2022-04-12       Impact factor: 14.919

  3 in total

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