Phylogenomics Laboratory, EA 3781 Evolution Biologique, Université de Provence, 13331 Marseille, France.
Evol Bioinform Online. 2008 May 8;4:121-37. doi: 10.4137/ebo.s597.
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.
大量模式生物的完整基因组序列的最近可得性,以及新的高通量技术所产生的巨大数据量,意味着我们现在可以开始进行比较分析,以了解基因组进化中涉及的机制及其在生物系统研究中的后果。系统发生方法为对所有这些数据进行比较分析、在不同系统之间传播信息以及预测或推断新知识提供了独特的概念框架。因此,基于系统发生的推断系统现在在高通量基因组学的大多数领域中发挥着越来越重要的作用,包括启动子研究(系统发生足迹分析)、相互作用组(基于相互作用蛋白的存在和保守程度)以及转录组或蛋白质组的比较(系统发生接近度和共调节/共表达)。在这里,我们回顾了最近的发展,旨在使大规模项目中自动、可靠的基于系统发生的推断成为可能。我们还讨论了如何利用进化概念和基于系统发生的推断策略来理解生物系统的进化和功能。这些进展对于系统生物学和合成生物学这两个新兴学科的成功将是至关重要的,并将在生物技术、医学和药理学等应用领域产生广泛的影响。