Identifying functional regulatory mutation blocks by integrating genome sequencing and transcriptome data

• Published in: iScience Vol. 26; no. 8; p. 107266
• Main Authors: Yang, Mingyi, Ali, Omer, Bjørås, Magnar, Wang, Junbai
• Format: Journal Article
• Language: English; Norwegian
• Published: United States Elsevier Inc 18.08.2023; Cell Press; Elsevier
• Subjects: Biocomputational method; Bioinformatics; Biological sciences; Biological sciences tools; Omics; Biological sciences; Biological sciences tools; Bioinformatics; Omics; Biocomputational method
• ISSN: 2589-0042; 2589-0042
• DOI: 10.1016/j.isci.2023.107266

Millions of single nucleotide variants (SNVs) exist in the human genome; however, it remains challenging to identify functional SNVs associated with diseases. We propose a non-encoding SNVs analysis tool bpb3, BayesPI-BAR version 3, aiming to identify the functional mutation blocks (FMBs) by integrating genome sequencing and transcriptome data. The identified FMBs display high frequency SNVs, significant changes in transcription factors (TFs) binding affinity and are nearby the regulatory regions of differentially expressed genes. A two-level Bayesian approach with a biophysical model for protein-DNA interactions is implemented, to compute TF-DNA binding affinity changes based on clustered position weight matrices (PWMs) from over 1700 TF-motifs. The epigenetic data, such as the DNA methylome can also be integrated to scan FMBs. By testing the datasets from follicular lymphoma and melanoma, bpb3 automatically and robustly identifies FMBs, demonstrating that bpb3 can provide insight into patho-mechanisms, and therapeutic targets from transcriptomic and genomic data. [Display omitted] •Integration of genome sequencing and transcriptome data for regulatory SNP analysis•A Bayesian approach with a biophysical model to estimate TF-DNA binding affinity•Use of DNA methylome data for identification of functional regulatory mutations•The tool robustly identifies functional non-coding mutation regions in diseases Biological sciences; Bioinformatics; Biocomputational method; Omics; Biological sciences tools