Analysis tools for the interplay between genome layout and regulation

• Published in: BMC bioinformatics 2016-06, Vol.17 Suppl 5 (Suppl 5), p.191-191, Article 191
• Main Authors: Bouyioukos, Costas, Elati, Mohamed, Képès, François
• Format: Article
• Language: English
• Subjects: Binding Sites; Computer Science; Escherichia coli; Escherichia coli - genetics; Escherichia coli - metabolism; Escherichia coli Proteins - genetics; Escherichia coli Proteins - metabolism; Gene Regulatory Networks - genetics; Genetic aspects; Genetic regulation; Genetic transcription; Genome; Life Sciences; Machine Learning; Physiological aspects; Quantitative Methods; Software; Transcription Factors - chemistry; Transcription Factors - metabolism
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-016-1047-0

Genome layout and gene regulation appear to be interdependent. Understanding this interdependence is key to exploring the dynamic nature of chromosome conformation and to engineering functional genomes. Evidence for non-random genome layout, defined as the relative positioning of either co-functional or co-regulated genes, stems from two main approaches. Firstly, the analysis of contiguous genome segments across species, has highlighted the conservation of gene arrangement (synteny) along chromosomal regions. Secondly, the study of long-range interactions along a chromosome has emphasised regularities in the positioning of microbial genes that are co-regulated, co-expressed or evolutionarily correlated. While one-dimensional pattern analysis is a mature field, it is often powerless on biological datasets which tend to be incomplete, and partly incorrect. Moreover, there is a lack of comprehensive, user-friendly tools to systematically analyse, visualise, integrate and exploit regularities along genomes. Here we present the Genome REgulatory and Architecture Tools SCAN (GREAT:SCAN) software for the systematic study of the interplay between genome layout and gene expression regulation. SCAN is a collection of related and interconnected applications currently able to perform systematic analyses of genome regularities as well as to improve transcription factor binding sites (TFBS) and gene regulatory network predictions based on gene positional information. We demonstrate the capabilities of these tools by studying on one hand the regular patterns of genome layout in the major regulons of the bacterium Escherichia coli. On the other hand, we demonstrate the capabilities to improve TFBS prediction in microbes. Finally, we highlight, by visualisation of multivariate techniques, the interplay between position and sequence information for effective transcription regulation.