ArticleGenetics2017
Statistical Methods for Identifying Sequence Motifs Affecting Point Mutations.
Article in Genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 33 citations in OpenAlex.
- Sodium azide mutagenesis induces a unique pattern of mutations.PLoS genetics · 2025Article
- CDMAP/CDVIS: context-dependent mutation analysis package and visualization software.G3 (Bethesda, Md.) · 2023Article
- Substitution rate heterogeneity across hexanucleotide contexts in noncoding chloroplast DNA.G3 (Bethesda, Md.) · 2022Article
- Non-random genetic alterations in the cyanobacterium Nostoc sp. exposed to space conditions.Scientific reports · 2022Article
- Fast neutron mutagenesis in soybean enriches for small indels and creates frameshift mutations.G3 (Bethesda, Md.) · 2022Article
- Context-Dependent Substitution Dynamics in Plastid DNA Across a Wide Range of Taxonomic Groups.Journal of molecular evolution · 2022Article
- Context-Dependent Mutation Dynamics, Not Selection, Explains the Codon Usage Bias of Most Angiosperm Chloroplast Genes.Journal of molecular evolution · 2022Article
- Whole-Genome Analysis of De Novo Somatic Point Mutations Reveals Novel Mutational Biomarkers in Pancreatic Cancer.Cancers · 2021Article
- Quantifying Influences on Intragenomic Mutation Rate.G3 (Bethesda, Md.) · 2020Article
- EvoLSTM: context-dependent models of sequence evolution using a sequence-to-sequence LSTM.Bioinformatics (Oxford, England) · 2020Article
- Machine Learning Techniques for Classifying the Mutagenic Origins of Point Mutations.Genetics · 2020Article
- A Bayesian Framework for Inferring the Influence of Sequence Context on Point Mutations.Molecular biology and evolution · 2020Article
- Signals of Variation in Human Mutation Rate at Multiple Levels of Sequence Context.Molecular biology and evolution · 2019Article
- The cytidine deaminase under-representation reporter (CDUR) as a tool to study evolution of sequences under deaminase mutational pressure.BMC bioinformatics · 2018Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mutation processes differ between types of point mutation, genomic locations, cells, and biological species. For some point mutations, specific neighboring bases are known to be mechanistically influential. Beyond these cases, numerous questions remain unresolved, including: what are the sequence motifs that affect point mutations? How large are the motifs? Are they strand symmetric? And, do they vary between samples? We present new log-linear models that allow explicit examination of these questions, along with sequence logo style visualization to enable identifying specific motifs. We demonstrate the performance of these methods by analyzing mutation processes in human germline and malignant melanoma. We recapitulate the known CpG effect, and identify novel motifs, including a highly significant motif associated with A[Formula: see text]G mutations. We show that major effects of neighbors on germline mutation lie within [Formula: see text] of the mutating base. Models are also presented for contrasting the entire mutation spectra (the distribution of the different point mutations). We show the spectra vary significantly between autosomes and X-chromosome, with a difference in T[Formula: see text]C transition dominating. Analyses of malignant melanoma confirmed reported characteristic features of this cancer, including statistically significant strand asymmetry, and markedly different neighboring influences. The methods we present are made freely available as a Python library https://bitbucket.org/pycogent3/mutationmotif.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.