Hierarchy and extremes in selections from pools of randomized proteins

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Boyer, Sébastien | Biswas, Dipanwita | Kumar Soshee, Ananda | Scaramozzino, Natale | Nizak, Clément | Rivoire, Olivier

Edité par CCSD ; National Academy of Sciences -

International audience. Significance Evolution by natural selection requires populations to be sufficiently diverse, but merely counting the number of different individuals provides a poor indication of the potential of a population to satisfy a new selective constraint. To achieve a more relevant characterization of this selective potential, we performed in vitro experiments of selection with populations of partially randomized proteins and analyzed the results quantitatively by high-throughput sequencing. We find that selective potentials in these populations follow simple statistical laws, which can be interpreted with extreme value theory (the mathematical theory of extreme events—here, the rare finding of a protein meeting the selective constraints). Our results provide an approach to quantitatively measure the selective potential of a population.

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