Detecting genome regularities with GREAT (Genome REgulatory Architecture Tools)

Costas BOUYIOUKOS

Epigenetics and cell fate, Univ Paris-Diderot, FR.

  Abstract
    

   We offer a hands-on tutorial where we explain the usage and demonstrate comprehensive xase studies of an online suite of tools for Genome Regulatory Architecture (GREAT) that the MEGA (Modelling and Engineering of Genome Architecture) team of iSSB (institute of Systems & Synthetic Biology) has developed.

   We begin with a swift introduction to the the Solenoid Coordinate Model (SCM), a technique able to detect periodicities in gene positioning. We then introduce GREAT a suite of tools to exploit, expand and visualise SCM. GREAT:SCAN:patterns computes and visualises all the significant periods of a set of co-functional genes, performs clustering and maps their periodic regions into the genome. All three analysis steps will be explored using applications from the analysis of the major E.coli transcription factors as well as co-regulated effectors of plant pathogens.

   Following up the procaryotes examples we introduce GREAT analyses to the eucaryotes by using the multi-chromosome genome of yeast and conduct an analysis with the multipatterns tool.

   Finally, we demonstrate GREAT:SCAN:PreCisIon a tool which utilises positional information from patterns together with, sequence based, position weight matrices in a multi-view learning software that improves prediction of TFs binding sites.

   The tutorial aims in introducing researches from diverse backgrounds into a novel (non-sequence based) approach of studying genome organisation in a systematic way. It does not require any specific background knowledge in either biology, computer science, physics or mathematics and it is designed to be approachable by researchers from any science or engineering discipline.

References:

GREAT: a web portal for Genome REgulatory Architecture Tools.
Bouyioukos, C.; Bucchini, F.; Elati, M. & Képès, F.
Nucleic Acids Research, 2016, 44, W77-W82
http://dx.doi.org/10.1093/nar/gkw384