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Mutational Effects and Population Dynamics During Viral Adaptation Challenge Current Models
Author(s) -
Craig R. Miller,
Paul Joyce,
Holly A. Wichman
Publication year - 2010
Publication title -
genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.792
H-Index - 246
eISSN - 1943-2631
pISSN - 0016-6731
DOI - 10.1534/genetics.110.121400
Subject(s) - biology , bottleneck , adaptation (eye) , genetics , population bottleneck , selection (genetic algorithm) , population , genome , genetic variation , mutation , evolutionary dynamics , ploidy , fitness landscape , evolutionary biology , computational biology , allele , gene , computer science , microsatellite , demography , neuroscience , artificial intelligence , sociology , embedded system
Adaptation in haploid organisms has been extensively modeled but little tested. Using a microvirid bacteriophage (ID11), we conducted serial passage adaptations at two bottleneck sizes (10(4) and 10(6)), followed by fitness assays and whole-genome sequencing of 631 individual isolates. Extensive genetic variation was observed including 22 beneficial, several nearly neutral, and several deleterious mutations. In the three large bottleneck lines, up to eight different haplotypes were observed in samples of 23 genomes from the final time point. The small bottleneck lines were less diverse. The small bottleneck lines appeared to operate near the transition between isolated selective sweeps and conditions of complex dynamics (e.g., clonal interference). The large bottleneck lines exhibited extensive interference and less stochasticity, with multiple beneficial mutations establishing on a variety of backgrounds. Several leapfrog events occurred. The distribution of first-step adaptive mutations differed significantly from the distribution of second-steps, and a surprisingly large number of second-step beneficial mutations were observed on a highly fit first-step background. Furthermore, few first-step mutations appeared as second-steps and second-steps had substantially smaller selection coefficients. Collectively, the results indicate that the fitness landscape falls between the extremes of smooth and fully uncorrelated, violating the assumptions of many current mutational landscape models.

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