Surveying mutation density patterns around specific genomic features

Author:

Yu Hui,Ness Scott,Li Chung-I,Bai Yongsheng,Mao Peng,Guo Yan

Abstract

Mutation density patterns reveal unique biological properties of specific genomic regions and shed light on the mechanisms of carcinogenesis. Although previous studies reported insightful mutation density patterns associated with certain genomic regions such as transcription start sites and DNA replication origins, a tool that can systematically investigate mutational spatial patterns is still lacking. Thus, we developed MutDens, a bioinformatic tool for comprehensive analysis of mutation density patterns around genomic features, namely, genomic positions, in humans and model species. By scanning the bidirectional vicinity regions of given positions, MutDens systematically characterizes the mutation density for single-base substitution mutational classes after adjusting for total mutation burden and local nucleotide proportion. Analysis results using MutDens not only verified the previously reported transcriptional strand bias around transcription start sites and replicative strand bias around DNA replication origins, but also identified novel mutation density patterns around other genomics features, such as enhancers and retrotransposon insertion polymorphism sites. To our knowledge, MutDens is the first tool that systematically calculates, examines, and compares mutation density patterns, thus providing a valuable avenue for investigating the mutational landscapes associated with important genomic features.

Funder

The Rockefeller University

University of New Mexico

Cancer Center Support

National Cancer Institute

Analytical and Translational Genomics Shared Resource and Bioinformatics Shared Resource of the Comprehensive Cancer Center, University of New Mexico

Publisher

Cold Spring Harbor Laboratory

Subject

Genetics (clinical),Genetics

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Strand asymmetries across genomic processes;Computational and Structural Biotechnology Journal;2023

2. Mutation density analyses on long noncoding RNA reveal comparable patterns to protein-coding RNA and prognostic value;Computational and Structural Biotechnology Journal;2023

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