Strategies for Reliable Exploitation of Evolutionary Concepts in High Throughput Biology

Author:

Levasseur Anthony1,Pontarotti Pierre1,Poch Olivier2,Thompson Julie D.2

Affiliation:

1. Phylogenomics Laboratory, EA 3781 Evolution Biologique, Université de Provence, 13331 Marseille, France.

2. Département de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Molculaire et Cellulaire, (CNRS/INSERM/ULP), BP 10142, 67404 Illkirch Cedex, France.

Abstract

The recent availability of the complete genome sequences of a large number of model organisms, together with the immense amount of data being produced by the new high-throughput technologies, means that we can now begin comparative analyses to understand the mechanisms involved in the evolution of the genome and their consequences in the study of biological systems. Phylogenetic approaches provide a unique conceptual framework for performing comparative analyses of all this data, for propagating information between different systems and for predicting or inferring new knowledge. As a result, phylogeny-based inference systems are now playing an increasingly important role in most areas of high throughput genomics, including studies of promoters (phylogenetic footprinting), interactomes (based on the presence and degree of conservation of interacting proteins), and in comparisons of transcriptomes or proteomes (phylogenetic proximity and co-regulation/co-expression). Here we review the recent developments aimed at making automatic, reliable phylogeny-based inference feasible in large-scale projects. We also discuss how evolutionary concepts and phylogeny-based inference strategies are now being exploited in order to understand the evolution and function of biological systems. Such advances will be fundamental for the success of the emerging disciplines of systems biology and synthetic biology, and will have wide-reaching effects in applied fields such as biotechnology, medicine and pharmacology.

Publisher

SAGE Publications

Subject

Computer Science Applications,Genetics,Ecology, Evolution, Behavior and Systematics

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