Integrating whole genome sequencing, methylation, gene expression, topologically associated domain information in regulatory mutation prediction: A study of follicular lymphoma

被引:2
|
作者
Farooq, Amna [1 ]
Troen, Gunhild [1 ]
Delabie, Jan [3 ,4 ]
Wang, Junbai [2 ,5 ]
机构
[1] Norwegian Radium Hosp, Dept Pathol, Oslo Univ Hosp, Oslo, Norway
[2] Univ Oslo, Inst Clin Med, Dept Clin Mol Biol, Oslo, Norway
[3] Univ Hlth Network, Lab Med Program, Toronto, ON, Canada
[4] Univ Toronto, Toronto, ON, Canada
[5] Akershus Univ Hosp, Dept Clin Mol Biol EpiGen, Lorenskog, Norway
来源
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL | 2022年 / 20卷
关键词
Genome; Epigenome; 3D chromatin domain; Regulatory mutation; Cancer; Machine learning; Integrative data analysis; HI-C DATA; DNA METHYLATION; TRANSCRIPTION FACTORS; CANCER; ANNOTATION; DISCOVERY; BURKITT;
D O I
10.1016/j.csbj.2022.03.023
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
A major challenge in human genetics is of the analysis of the interplay between genetic and epigenetic factors in a multifactorial disease like cancer. Here, a novel methodology is proposed to investigate genome-wide regulatory mechanisms in cancer, as studied with the example of follicular Lymphoma (FL). In a first phase, a new machine-learning method is designed to identify Differentially Methylated Regions (DMRs) by computing six attributes. In a second phase, an integrative data analysis method is developed to study regulatory mutations in FL, by considering differential methylation information together with DNA sequence variation, differential gene expression, 3D organization of genome (e.g., topologically associated domains), and enriched biological pathways. Resulting mutation block-gene pairs are further ranked to find out the significant ones. By this approach, BCL2 and BCL6 were identified as top-ranking FL-related genes with several mutation blocks and DMRs acting on their regulatory regions. Two additional genes, CDCA4 and CTSO, were also found in top rank with significant DNA sequence variation and differential methylation in neighboring areas, pointing towards their potential use as biomarkers for FL. This work combines both genomic and epigenomic information to investigate genome-wide gene regulatory mechanisms in cancer and contribute to devising novel treatment strategies.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:1726 / 1742
页数:17
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