Research highlight by Kazuharu Arakawa and Masaru Tomita, Institute for Advanced Biosciences, Keio University, Japan

Gene duplications and mutations are central driving forces in the evolution of genomes. Genomes must be robust to such changes in order to be evolvable, and many studies have probed genome robustness using systematic gene knockouts or overexpression experiments. In a recent paper, Isalan et al. (2008) took a new approach to test the robustness of Escherichia coli gene circuitry by reconstructing gene duplication events by shuffling the promoter-ORF pairs for about 300 transcription factors and introducing 598 recombined pairs one-by-one into E. coli to rewire its transcriptional network. Surprisingly, ~95% of such additions are robustly tolerated, and some networks even exhibit greater fitness under various selection pressures. Moreover, the study shows that, in contrast to naive expectations, the introduction of positive or negative feedback loops has little effect on the protein expression levels of regulated ORFs.

Since radical rewiring of the gene circuitry appears to have only a limited impact on expression levels, this work suggests that gene regulatory networks are highly dynamic and underscores the potential importance of post-transcriptional mechanisms for the robustness of transcriptional regulation. Moreover, this work illustrates the fundamental robustness and evolvability of gene regulatory networks, which is reassuring news for synthetic biology.

Isalan M, Lemerle C, Michalodimitrakis K, Horn C, Beltrao P, Raineri E, Garriga-Canut M, Serrano L (2008) Evolvability and hierarchy in rewired bacterial gene networks. Nature 452:840

(via Gene Expression)

A few days ago, an exciting review by Michael Lynch was published in Nature Reviews Genetics (The evolution of genetic networks by non-adaptive processes, Lynch 2007a ), a close follow-up of another review, published in PNAS a few months ago (The frailty of adaptive hypotheses for the origins of organismal complexity, Lynch 2007b). Michael Lynch has also written a book on the topic: The Origins of Genome Architecture (read a review)

The architecture of biological networks are often hypothesized as being "shaped" by adaptive evolution to confer global properties such as redundancy, robustness, modularity, complexity and evolvability. Lynch has some robust comments (others have some too, see Jonathan Eisen's "adaptationomics awards") on the “vast majority of biologists engaged in evolutionary studies [who] interpret virtually every aspect of biodiversity in adaptive terms” (Lynch 2007b). In contrast to what he perceives as a widespread belief, Lynch states clearly:

It is an open question as to whether pathway complexity is a necessary prerequisite for the evolution of complex phenotypes, or whether the genome architectures of multicellular species are simply more conducive to the passive emergence of network connections.(Lynch 2007a)

Beyond its somewhat controversial tone, Lynch's central lesson is the need to adopt a population genetics viewpoint (“nothing in evolution makes sense except in light of population genetics”) and he reminds us that, beside natural selection, three additional non-adaptive processes drive the evolution of living organisms: genetic drift, mutation and recombination. By analyzing the interplay between relative rates of loss and gain of regulatory sites (which depend both on mutation rate and mutational target size such as non-coding DNA), population size and recombination frequency, he demonstrates that purely non-adaptive forces can, in principle, determine the level of connectivity of regulatory networks--for example, determine the predominance of highly connected network motifs over linear pathways--without invoking any inherent advantages of the respective architectures on biological functions related for example to development or metabolism. It appears thus that, depending on the population genetics parameters, network structure can be profoundly "shaped" by the mere physical processes of mutation and recombination. At the very least, Lynch proposes that such models should be considered as "null hypothesis" when claiming that selection is engaged in a given aspect of organisms complexity.

In his review of Lynch's book, Massimo Pigliucci draws our attention to the fact that "the genome is only part of the story, arguably the simplest part to figure out", and that one of the greatest current challenges is to explain how phenotypes evolve. Lynch also recognizes that his models are simplified and do not, for example, consider kinetic or dynamical properties of biological networks. But here is a naive question: would it be possible to design an experimental strategy to test directly, in the lab, the evolution of simple (synthetic?) genetic circuits and observe the trends in connectivity under non-selective conditions or are the timescales involved too unrealistic?