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Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure

BACKGROUND: Numerous genome-wide association studies (GWAS) conducted to date revealed genetic variants associated with various diseases, including breast and prostate cancers. Despite the availability of these large-scale data, relatively few variants have been functionally characterized, mainly be...

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Autores principales: Osman, Noha, Shawky, Abd-El-Monsif, Brylinski, Michal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8851830/
https://www.ncbi.nlm.nih.gov/pubmed/35176995
http://dx.doi.org/10.1186/s12863-021-01021-x
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author Osman, Noha
Shawky, Abd-El-Monsif
Brylinski, Michal
author_facet Osman, Noha
Shawky, Abd-El-Monsif
Brylinski, Michal
author_sort Osman, Noha
collection PubMed
description BACKGROUND: Numerous genome-wide association studies (GWAS) conducted to date revealed genetic variants associated with various diseases, including breast and prostate cancers. Despite the availability of these large-scale data, relatively few variants have been functionally characterized, mainly because the majority of single-nucleotide polymorphisms (SNPs) map to the non-coding regions of the human genome. The functional characterization of these non-coding variants and the identification of their target genes remain challenging. RESULTS: In this communication, we explore the potential functional mechanisms of non-coding SNPs by integrating GWAS with the high-resolution chromosome conformation capture (Hi-C) data for breast and prostate cancers. We show that more genetic variants map to regulatory elements through the 3D genome structure than the 1D linear genome lacking physical chromatin interactions. Importantly, the association of enhancers, transcription factors, and their target genes with breast and prostate cancers tends to be higher when these regulatory elements are mapped to high-risk SNPs through spatial interactions compared to simply using a linear proximity. Finally, we demonstrate that topologically associating domains (TADs) carrying high-risk SNPs also contain gene regulatory elements whose association with cancer is generally higher than those belonging to control TADs containing no high-risk variants. CONCLUSIONS: Our results suggest that many SNPs may contribute to the cancer development by affecting the expression of certain tumor-related genes through long-range chromatin interactions with gene regulatory elements. Integrating large-scale genetic datasets with the 3D genome structure offers an attractive and unique approach to systematically investigate the functional mechanisms of genetic variants in disease risk and progression. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12863-021-01021-x.
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spelling pubmed-88518302022-02-22 Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure Osman, Noha Shawky, Abd-El-Monsif Brylinski, Michal BMC Genom Data Research BACKGROUND: Numerous genome-wide association studies (GWAS) conducted to date revealed genetic variants associated with various diseases, including breast and prostate cancers. Despite the availability of these large-scale data, relatively few variants have been functionally characterized, mainly because the majority of single-nucleotide polymorphisms (SNPs) map to the non-coding regions of the human genome. The functional characterization of these non-coding variants and the identification of their target genes remain challenging. RESULTS: In this communication, we explore the potential functional mechanisms of non-coding SNPs by integrating GWAS with the high-resolution chromosome conformation capture (Hi-C) data for breast and prostate cancers. We show that more genetic variants map to regulatory elements through the 3D genome structure than the 1D linear genome lacking physical chromatin interactions. Importantly, the association of enhancers, transcription factors, and their target genes with breast and prostate cancers tends to be higher when these regulatory elements are mapped to high-risk SNPs through spatial interactions compared to simply using a linear proximity. Finally, we demonstrate that topologically associating domains (TADs) carrying high-risk SNPs also contain gene regulatory elements whose association with cancer is generally higher than those belonging to control TADs containing no high-risk variants. CONCLUSIONS: Our results suggest that many SNPs may contribute to the cancer development by affecting the expression of certain tumor-related genes through long-range chromatin interactions with gene regulatory elements. Integrating large-scale genetic datasets with the 3D genome structure offers an attractive and unique approach to systematically investigate the functional mechanisms of genetic variants in disease risk and progression. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12863-021-01021-x. BioMed Central 2022-02-17 /pmc/articles/PMC8851830/ /pubmed/35176995 http://dx.doi.org/10.1186/s12863-021-01021-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Osman, Noha
Shawky, Abd-El-Monsif
Brylinski, Michal
Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure
title Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure
title_full Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure
title_fullStr Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure
title_full_unstemmed Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure
title_short Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure
title_sort exploring the effects of genetic variation on gene regulation in cancer in the context of 3d genome structure
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8851830/
https://www.ncbi.nlm.nih.gov/pubmed/35176995
http://dx.doi.org/10.1186/s12863-021-01021-x
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