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Lasting impressions: Motifs in protein–protein maps may provide footprints of evolutionary events
Author(s) -
John Jeremy Rice,
Aaron Kershenbaum,
Gustavo Stolovitzky
Publication year - 2005
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.0500130102
Subject(s) - adaptive evolution , gene , biology , evolutionary biology , context (archaeology) , gene expression , genetics , molecular evolution , genetic variation , regulation of gene expression , computational biology , phylogenetics , paleontology
Imagine a paleontologist confronted with of a fossil of a single footprint. She could probably risk some conjectures about the imprinting creature, such as whether it possessed paws, claws, or feet, and estimate its weight, height, and other attributes. But the information contained in a single static print remains limited. The situation improves if a multitude of footprints from a population of creatures becomes available. Now, stride lengths can be calculated, variability between individuals can be assessed, and speeds can be estimated. Furthermore, correlating footprints from different geographies could lead to clues about the population's migration patterns. With appropriate assumptions, our paleontologist could begin to map how the population evolved over time. As this example illustrates, even though a footprint is a static entity, the sum of many footprints could in principle provide clues about the dynamics of a population. In this vein, the work of Middendorf, Ziv, and Wiggins in this issue of PNAS (1) seeks to understand the broad strokes of the evolutionary dynamics that shaped a species from a static network of protein–protein interactions. By way of “footprints,” Middendorf et al. (1) use substructures in the protein–protein network called network motifs whose count provides a window into the dynamics that left the record. These counts are the markers that the authors use to “learn” which motifs differentiate between competing hypothetical evolutionary schemes. The outcome of the study suggests a dominant evolutionary mechanism that shaped Drosophila melanogaster. Networks of all sorts evolve, and it is often possible to form hypotheses about such evolution by direct examination of the structure of the network (2–4). Consider the U.S. telephone network, which evolved over the past 100 years in response to changes in traffic load and advances in technology. The telephone network was originally engineered to carry …

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