%0 Journal Article
%T Periodicity of SNP distribution around transcription start sites
%A Koichiro Higasa
%A Kenshi Hayashi
%J BMC Genomics
%D 2006
%I BioMed Central
%R 10.1186/1471-2164-7-66
%X A spectrum analysis of SNP density distribution in the genomic regions around transcription start sites (TSSs) revealed a remarkable periodicity of 146 nucleotides. This periodicity was observed in the regions that were associated with CpG islands (CGIs), but not in the regions without CpG islands (nonCGIs). An analysis of the sequence divergence of the same genomic regions between humans and chimpanzees also revealed a similar periodical pattern in CGI. The occurrences of any mono- or di-nucleotide sequences in these regions did not reveal such a periodicity, thus indicating that an interpretation of this periodicity solely based on the sequence-dependent susceptibility to mutation is highly unlikely.The periodical patterns of nucleotide variability suggest the location of nucleosomes that are phased at TSS, and can be viewed as the genetic footprint of the chromatin state that has been maintained throughout mammalian evolutionary history. The results suggest the possible involvement of the nucleosome structure in the promoter function, and also a fundamental functional/structural difference between the two promoter classes, i.e., those with and without CGIs.Several million single nucleotide polymorphisms (SNPs) have already been collected and deposited in public databases [1] and these are important resources not only for use as markers to identify disease-associated genes [2], but also for an understanding of the mechanisms that underlie the diversification of the organism. The nucleotide diversity of human genome sequence appears to fluctuate from region to region [3-5]. The majority of the SNPs are believed to have no biological consequence, and therefore their diversity is primarily determined by the mutation rate within the germ cells, although it may be affected by the selective pressure that operates at the individual level [6]. In this study, we used a spectral analysis approach to identify the pattern of nucleotide variability around the transcription sta
%U http://www.biomedcentral.com/1471-2164/7/66