Clustering of DNA words and biological function: A proof of principle
Metadatos
Mostrar el registro completo del ítemAutor
Hackenberg, Michael; Rueda, Antonio; Carpena, Pedro; Bernaola-Galván, Pedro; Barturen, Guillermo; Oliver Jiménez, José LutgardoEditorial
Elsevier
Materia
DNA-words Word clustering Enrichment/depletion experiments
Fecha
2011-12-30Referencia bibliográfica
Hackenberg, M.; Rueda, A.; Carpena, P. [et al]. (2012). Clustering of DNA words and biological function: A proof of principle. Journal of Theoretical Biology 297 (2012) 127–136. doi:10.1016/j.jtbi.2011.12.024
Patrocinador
Ministry of Innovation and Science of the Spanish Government [BIO2008-01353 and BIO2010-20219]; Juan de la Cierva grant; Basque country ‘AE’ grantResumen
Relevant words in literary texts (key words) are known to be clustered, while common words are randomly distributed. Given the clustered distribution of many functional genome elements, we hypothesize that the biological text per excellence, the DNA sequence, might behave in the same way: k-length words (k-mers) with a clear function may be spatially clustered along the one-dimensional chromosome sequence, while less-important, non-functional words may be randomly distributed. To explore this linguistic analogy, we calculate a clustering coefficient for each k-mer (k=2–9 bp) in human and mouse chromosome sequences, then checking if clustered words are enriched in the functional part of the genome. First, we found a positive general trend relating clustering level and word enrichment within exons and Transcription Factor Binding Sites (TFBSs), while a much weaker relation exists for repeats, and no relation at all exists for introns. Second, we found that 38.45% of the 200 top-clustered 8-mers, but only 7.70% of the non-clustered words, are represented in known motif databases. Third, enrichment/depletion experiments show that highly clustered words are significantly enriched in exons and TFBSs, while they are depleted in introns and repetitive DNA. Considering exons and TFBSs together, 1417 (or 72.26%) in human and 1385 (or 72.97%) in mouse of the top-clustered 8-mers showed a statistically significant association to either exons or TFBSs, thus strongly supporting the link between word clustering and biological function. Lastly, we identified a subset of clustered, diagnostic words that are enriched in exons but depleted in introns, and therefore might help to discriminate between these two gene regions. The clustering of DNA words thus appears as a novel principle to detect functionality in genome sequences. As evolutionary conservation is not a prerequisite, the proof of principle described here may open new ways to detect species-specific functional DNA sequences and the improvement of gene and promoter predictions, thus contributing to the quest for function in the genome.





