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Review
. 2005 May 3;102 Suppl 1(Suppl 1):6630-5.
doi: 10.1073/pnas.0501984102. Epub 2005 Apr 25.

Genomes, phylogeny, and evolutionary systems biology

Mónica Medina  1
Affiliations
Review

Genomes, phylogeny, and evolutionary systems biology

Mónica Medina. Proc Natl Acad Sci U S A. .

Abstract

With the completion of the human genome and the growing number of diverse genomes being sequenced, a new age of evolutionary research is currently taking shape. The myriad of technological breakthroughs in biology that are leading to the unification of broad scientific fields such as molecular biology, biochemistry, physics, mathematics, and computer science are now known as systems biology. Here, I present an overview, with an emphasis on eukaryotes, of how the postgenomics era is adopting comparative approaches that go beyond comparisons among model organisms to shape the nascent field of evolutionary systems biology.

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Figures

Fig. 1.
Fig. 1.
Current consensus eukaryotic tree. (A) The large subclades within Unikonts and Bikonts are recovered by a combination of multiple gene phylogenies, EST data, and genomic level characters (1, 80, 81). Six major eukaryotic groups are now recognized although resolution within them is still lacking. The placement of the root is based on two gene fusion events (1, 2). Lineages where whole-genome projects are in progress are marked with asterisks. Lineages being studied by large postgenomic initiatives are shadowed. (B) Metazoan consensus phylogeny of major branches (82-84) and a conservative estimate of finished and ongoing genome projects (highlighted in black). (C) Fungal consensus phylogeny (13, 14) and estimate of ongoing genome projects (www.broad.mit.edu/annotation/fungi/fgi) (highlighted in black). (D) Consensus phylogeny of green plants (13, 20) and estimate of ongoing genome projects (highlighted in black).
Fig. 2.
Fig. 2.
Overview of systems biology. Hierarchical information from the genome (DNA) to the phenome (phenotype) is integrated to predict mathematical models. These models can then be tested by “synthetic biology” (de novo design of biological modules) and/or by system perturbations that generate a cycle of hypothesis-driven science (26, 27, 32).
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