A model for the clustered distribution of SNPs in the human genome. (October 2016)

• Record Type: Journal Article
• Authors: Lee, Chang-Yong
• Is Part Of: Computational biology and chemistry. Volume 64(2016)
• Page Start: 94
• Page End: 98
• Publication Date: 2016-10
• Subjects: Single nucleotide polymorphism -- Mutation -- Human genome -- Probability distribution -- Hapmap; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2016.06.003
• Languages: English
• ISSNs: 1476-9271

Abstract

Abstract : Graphical abstract: Abstract : Highlights: A phenomenological model is introduced to account for clustering properties of SNPs. The model is based on a preferential mutation to the closer proximity of other SNPs. The model is applicable not only to autosomes but also to the X chromosome. The model supports the mutational non-independence hypothesis. Abstract: Motivated by a non-random but clustered distribution of SNPs, we introduce a phenomenological model to account for the clustering properties of SNPs in the human genome. The phenomenological model is based on a preferential mutation to the closer proximity of existing SNPs. With the Hapmap SNP data, we empirically demonstrate that the preferential model is better for illustrating the clustered distribution of SNPs than the random model. Moreover, the model is applicable not only to autosomes but also to the X chromosome, although the X chromosome has different characteristics from autosomes. The analysis of the estimated parameters in the model can explain the pronounced population structure and the low genetic diversity of the X chromosome. In addition, correlation between the parameters reveals the population-wise difference of the mutation probability. These results support the mutational non-independence hypothesis against random mutation.