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The trajectory of evolution is impacted by molecular constraints and biases that are difficult to validate experimentally. Repeated evolution of similar traits across the Tree of Life serves as a natural experiment to discern common factors that drive the evolution of these traits. The architecture of genomes in one-dimensional, two-dimensional, and three-dimensional space is emerging as a potential factor that may predict repeated phenotypic evolution. For example, chromatin packaging and the 3D organization of the genome within the nucleus can impose evolutionary constraints by predisposing genomic regions for particular types of mutations, while the evolution of genome sequence can also drive reorganization of chromatin. With the explosion of new library preparation and sequencing technologies that are accessible for non-model species, we envision a great opportunity to understand how genome architecture across phylogenetically disparate species may impact repeated phenotypic evolution. We provide examples of the known and potential avenues of phenotypic convergence at each level of genome architecture and how integration of these data can provide unique insights into the constraints, trajectory, and predictability of evolution.
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HiCube: interactive visualization of multiscale and multimodal Hi-C and 3D genome data
Abstract Summary HiCube is a lightweight web application for interactive visualization and exploration of diverse types of genomics data at multiscale resolutions. Especially, HiCube displays synchronized views of Hi-C contact maps and 3D genome structures with user-friendly annotation and configuration tools, thereby facilitating the study of 3D genome organization and function. Availability and implementation HiCube is implemented in Javascript and can be installed via NPM. The source code is freely available at GitHub (https://github.com/wmalab/HiCube).
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- Award ID(s):
- 1751317
- PAR ID:
- 10419594
- Editor(s):
- Alkan, Can
- Date Published:
- Journal Name:
- Bioinformatics
- Volume:
- 39
- Issue:
- 4
- ISSN:
- 1367-4811
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1093/bioinformatics/btad154
