Research article

CpG islands or CpG clusters: how to identify functional GC-rich regions in a genome?

Leng Han^1,2,3 and Zhongming Zhao^2,4

¹State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, PR China

²Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA 23298, USA

³Graduate School, Chinese Academy of Sciences, Beijing 100039, PR China

⁴Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, VA 23284, USA

author email corresponding author email

BMC Bioinformatics 2009, 10:65doi:10.1186/1471-2105-10-65

Published:	20 February 2009

Abstract

Background

CpG islands (CGIs), clusters of CpG dinucleotides in GC-rich regions, are often located in the 5' end of genes and considered gene markers. Hackenberg et al. (2006) recently developed a new algorithm, CpGcluster, which uses a completely different mathematical approach from previous traditional algorithms. Their evaluation suggests that CpGcluster provides a much more efficient approach to detecting functional clusters or islands of CpGs.

Results

We systematically compared CpGcluster with the traditional algorithm by Takai and Jones (2002). Our comparisons of (1) the number of islands versus the number of genes in a genome, (2) the distribution of islands in different genomic regions, (3) island length, (4) the distance between two neighboring islands, and (5) methylation status suggest that Takai and Jones' algorithm is overall more appropriate for identifying promoter-associated islands of CpGs in vertebrate genomes.

Conclusion

The generation of genome sequence and DNA methylation data is expected to accelerate greatly. The information in this study is important for its extensive utility in gene feature analysis and epigenomics including gene prediction and methylation chip design in different genomes.