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SFB 680:  Molecular Basis of Evolutionary Innovations

Subject Area Biology
Medicine
Term from 2006 to 2017
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 13532522
 
Final Report Year 2018

Final Report Abstract

The research of CRC 680 took place amidst rapidly increasing data of genome sequences, gene regulation, and metabolic networks in cells. The new molecular data opened unprecedented opportunities to answer core questions of evolution. We endeavored to understand how differences between species build upon variation within species. By comparative sequence and functional analysis, we showed how functional innovations arise from changes of gene interactions in regulatory and metabolic networks. Repeatable network changes explain, for example, the convergent evolution of photosynthesis, the emergence of new flowering cycles and leaf shapes in plants, and the evolution of embryonal developmental patterns in insects. We also found a complementary mode of innovation: novel genes, which sometimes arise from noncoding genome sequence, can generate lineage-specific biological functions. Of equal importance, CRC 680 developed new, quantitative links between evolutionary experiment, data analysis, and theory. These advances made critical use of time-resolved data from microbial and viral systems, where evolution can be followed in real time. We showed that many such systems have a fast-paced mode of evolution, in which several beneficial mutations compete for success. Which mutations are beneficial is captured by empirical fitness landscapes that we deduced from observed time courses of evolution. But understanding why mutations are beneficial rests on the physical basis of evolution, which was a core theme of the CRC. We studied how mutations affect key biophysical phenotypes in a cell, such as binding affinities, protein stability, and metabolic fluxes, and we quantified how these phenotypes impact organismic functions and fitness. The resulting evolutionary dynamics reveals far-reaching links to statistical physics: equilibrium systems obey a Boltzmann statistics of fitness, while time- dependent fitness drives non-equilibrium adaptive changes. Together, our research lead to a better understanding of fast-evolving systems, including important human pathogens, and paved the way for new applications of evolutionary biology to medicine and public health. More about our research can be found on the CRC 680 website.

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