Cargando…

scGHOST: Identifying single-cell 3D genome subcompartments

New single-cell Hi-C (scHi-C) technologies enable probing of the genome-wide cell-to-cell variability in 3D genome organization from individual cells. Several computational methods have been developed to reveal single-cell 3D genome features based on scHi-C data, including A/B compartments, topologi...

Descripción completa

Detalles Bibliográficos
Autores principales: Xiong, Kyle, Zhang, Ruochi, Ma, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10245874/
https://www.ncbi.nlm.nih.gov/pubmed/37292994
http://dx.doi.org/10.1101/2023.05.24.542032
_version_ 1785054939132723200
author Xiong, Kyle
Zhang, Ruochi
Ma, Jian
author_facet Xiong, Kyle
Zhang, Ruochi
Ma, Jian
author_sort Xiong, Kyle
collection PubMed
description New single-cell Hi-C (scHi-C) technologies enable probing of the genome-wide cell-to-cell variability in 3D genome organization from individual cells. Several computational methods have been developed to reveal single-cell 3D genome features based on scHi-C data, including A/B compartments, topologically-associating domains, and chromatin loops. However, no scHi-C analysis method currently exists for annotating single-cell subcompartments, which are crucial for providing a more refined view of large-scale chromosome spatial localization in single cells. Here, we present scGhost, a single-cell subcompartment annotation method based on graph embedding with constrained random walk sampling. Applications of scGhost to scHi-C data and single-cell 3D genome imaging data demonstrate the reliable identification of single-cell subcompartments and offer new insights into cell-to-cell variability of nuclear subcompartments. Using scHi-C data from the human prefrontal cortex, scGhost identifies cell type-specific subcompartments that are strongly connected to cell type-specific gene expression, suggesting the functional implications of single-cell subcompartments. Overall, scGhost is an effective new method for single-cell 3D genome subcompartment annotation based on scHi-C data for a broad range of biological contexts.
format Online
Article
Text
id pubmed-10245874
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Cold Spring Harbor Laboratory
record_format MEDLINE/PubMed
spelling pubmed-102458742023-06-08 scGHOST: Identifying single-cell 3D genome subcompartments Xiong, Kyle Zhang, Ruochi Ma, Jian bioRxiv Article New single-cell Hi-C (scHi-C) technologies enable probing of the genome-wide cell-to-cell variability in 3D genome organization from individual cells. Several computational methods have been developed to reveal single-cell 3D genome features based on scHi-C data, including A/B compartments, topologically-associating domains, and chromatin loops. However, no scHi-C analysis method currently exists for annotating single-cell subcompartments, which are crucial for providing a more refined view of large-scale chromosome spatial localization in single cells. Here, we present scGhost, a single-cell subcompartment annotation method based on graph embedding with constrained random walk sampling. Applications of scGhost to scHi-C data and single-cell 3D genome imaging data demonstrate the reliable identification of single-cell subcompartments and offer new insights into cell-to-cell variability of nuclear subcompartments. Using scHi-C data from the human prefrontal cortex, scGhost identifies cell type-specific subcompartments that are strongly connected to cell type-specific gene expression, suggesting the functional implications of single-cell subcompartments. Overall, scGhost is an effective new method for single-cell 3D genome subcompartment annotation based on scHi-C data for a broad range of biological contexts. Cold Spring Harbor Laboratory 2023-05-25 /pmc/articles/PMC10245874/ /pubmed/37292994 http://dx.doi.org/10.1101/2023.05.24.542032 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Xiong, Kyle
Zhang, Ruochi
Ma, Jian
scGHOST: Identifying single-cell 3D genome subcompartments
title scGHOST: Identifying single-cell 3D genome subcompartments
title_full scGHOST: Identifying single-cell 3D genome subcompartments
title_fullStr scGHOST: Identifying single-cell 3D genome subcompartments
title_full_unstemmed scGHOST: Identifying single-cell 3D genome subcompartments
title_short scGHOST: Identifying single-cell 3D genome subcompartments
title_sort scghost: identifying single-cell 3d genome subcompartments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10245874/
https://www.ncbi.nlm.nih.gov/pubmed/37292994
http://dx.doi.org/10.1101/2023.05.24.542032
work_keys_str_mv AT xiongkyle scghostidentifyingsinglecell3dgenomesubcompartments
AT zhangruochi scghostidentifyingsinglecell3dgenomesubcompartments
AT majian scghostidentifyingsinglecell3dgenomesubcompartments