DNA entropy reveals a significant difference in complexity between housekeeping and tissue specific gene promoters. (October 2015)

• Record Type: Journal Article
• Authors: Thomas, David; Finan, Chris; Newport, Melanie J.; Jones, Susan
• Is Part Of: Computational biology and chemistry. Volume 58(2015)
• Page Start: 19
• Page End: 24
• Publication Date: 2015-10
• Subjects: 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.2015.05.001
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: DNA complexity can be quantified using entropy profiles. Gene promoter complexity is influenced by non-random patterns in the DNA sequence. Housekeeping (HK) and tissue specific (TS) gene promoters have different DNA entropy profiles. TS promoters have lower DNA entropies than HK promoters. Lower entropies of TS promoters can be explained by higher densities of regulatory elements. Abstract: Background: The complexity of DNA can be quantified using estimates of entropy. Variation in DNA complexity is expected between the promoters of genes with different transcriptional mechanisms; namely housekeeping (HK) and tissue specific (TS). The former are transcribed constitutively to maintain general cellular functions, and the latter are transcribed in restricted tissue and cells types for specific molecular events. It is known that promoter features in the human genome are related to tissue specificity, but this has been difficult to quantify on a genomic scale. If entropy effectively quantifies DNA complexity, calculating the entropies of HK and TS gene promoters as profiles may reveal significant differences. Results: Entropy profiles were calculated for a total dataset of 12, 003 human gene promoters and for 501 housekeeping (HK) and 587 tissue specific (TS) human gene promoters. The mean profiles show the TS promoters have a significantly lower entropy ( p < 2.2e − 16) than HK gene promoters. The entropy distributions for the 3 datasets show that promoter entropies could be used to identify novel HK genes. Conclusion: Functional features comprise DNA sequence patterns that are non-random and hence they have lower entropies. The lower entropy of TS gene promoters can be explained by a higher density of positive and negative regulatory elements, required for genes with complex spatial and temporary expression.