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Title: Complexity and Entropy Analysis of DNMT1 Gene

Author
item XIE, XIAOLI - University Of Maryland
item YU, YING - University Of Maryland
item Liu, Ge - George
item YUAN, ZHIFA - University Of Maryland
item SONG, JIUZHOU - University Of Maryland

Submitted to: Journal of Data Mining in Genomics & Proteomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/27/2010
Publication Date: 12/30/2010
Citation: Xie, X., Yu, Y., Liu, G., Yuan, Z., Song, J. 2010. Complexity and Entropy Analysis of DNMT1 Gene. Journal of Data Mining in Genomics & Proteomics. 1:105.

Interpretive Summary: The information measure was introduced by C.E. Shannon. Theoretically, it reflects an uncertainty associated with a random variable and quantifies the information contained in a message. Using multiple information indices, we measured the information complexity of the DNMT1 gene in multiple ways. These included comparisons across species at both genomic DNA and mRNA levels, comparisons between introns and coding regions, and comparisons between domain and non-domain regions. We also applied these indices to study the methylation changes of the DNMT1 gene over aging in a chicken model. Although, the intrinsic mechanism is not yet clear, we successfully detected that the information complexity of DNMT1 gene is related to its genomic composition, which thereby associates to evolutionary and aging processing. By applying these entropy information methods to various functional genomic regions, we will have deeper insights on gene functions and genome annotations.

Technical Abstract: Background: The application of complexity information on DNA sequence and protein in biological processes are well established in this study. Available sequences for DNMT1 gene, which is a maintenance methyltransferase is responsible for copying DNA methylation patterns to the daughter strands during DNA replication in different species, were thoroughly explored in the information complexities. Results: We found that the entropy of DNMT1 gene in different species is DNA base composition dependent, and its complexity in mammals is lower in introns than in coding regions. We also demonstrated the impacts of entropy on domains and non-domain(s) of the DNMT1 gene. The results from DNA and protein sequences indicated that DNA evolution is a tendency towards complexity. Most interestingly, the methylation changes of the gene over aging in a unique chick model showed aging-driven entropy characteristics, which may give an explanation of aging processes. Conclusion: In summary, the information complexity of DNMT1 gene is related to its genomic composition, which thereby associates to evolutionary and aging processing. However, the intrinsic mechanism is not to be studied yet.