title: Simple phenotypic sweeps hide complex genetic changes in populations.
abstract: Changes in allele frequencies and the fixation of beneficial mutations are central to evolution. The precise relationship between mutational and phenotypic sweeps is poorly described however, especially when multiple alleles are involved. Here, we investigate these relationships in a bacterial population over 60 days in a glucose-limited chemostat in a large population. High coverage metagenomic analysis revealed a disconnection between smooth phenotypic sweeps and the complexity of genetic changes in the population. Phenotypic adaptation was due to convergent evolution and involved soft sweeps by 7-26 highly represented alleles of several genes in different combinations. Allele combinations spread from undetectably low baselines, indicating that minor subpopulations provide the basis of most innovations. A hard sweep was also observed, involving a single combination of rpoS, mglD, malE, sdhC, and malT mutations sweeping to greater than 95% of the population. Other mutant genes persisted but at lower abundance, including hfq, consistent with its demonstrated frequency-dependent fitness under glucose limitation. Other persistent, newly identified low-frequency mutations were in the aceF, galF, ribD and asm genes, in noncoding regulatory regions, three large indels and a tandem duplication; these were less affected by fluctuations involving more dominant mutations indicating separate evolutionary paths. Our results indicate a dynamic subpopulation structure with a minimum of 42 detectable mutations maintained over 60 days. We also conclude that the massive population-level mutation supply in combination with clonal interference leads to the soft sweeps observed, but not to the exclusion of an occasional hard sweep.
authors.affiliation: School of Molecular Bioscience, University of Sydney, New South Wales, Australia.
authors.forename: Ram P
authors.initials: RP
authors.lastname: Maharjan
authors.affiliation: TEDA Institute of Biological Sciences and Biotechnology, Nankai University, Tianjin, People's Republic of China Key Laboratory of Molecular Microbiology and Technology, Ministry of Education, Tianjin, People's Republic of China.
authors.forename: Bin
authors.initials: B
authors.lastname: Liu
authors.affiliation: TEDA Institute of Biological Sciences and Biotechnology, Nankai University, Tianjin, People's Republic of China Key Laboratory of Molecular Microbiology and Technology, Ministry of Education, Tianjin, People's Republic of China.
authors.forename: Lu
authors.initials: L
authors.lastname: Feng
authors.affiliation: School of Molecular Bioscience, University of Sydney, New South Wales, Australia.
authors.forename: Thomas
authors.initials: T
authors.lastname: Ferenci
authors.affiliation: TEDA Institute of Biological Sciences and Biotechnology, Nankai University, Tianjin, People's Republic of China Key Laboratory of Molecular Microbiology and Technology, Ministry of Education, Tianjin, People's Republic of China State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, People's Republic of China wanglei@nankai.edu.cn.
authors.forename: Lei
authors.initials: L
authors.lastname: Wang
mesh_terms: D000222:Adaptation, Physiological / Q000235:genetics; D005075:Biological Evolution; D048168:Escherichia coli K12 / Q000166:cytology* / Q000235:genetics*; D020440:Gene Duplication; D005787:Gene Frequency / Q000235:genetics; D005798:Genes, Bacterial; D005838:Genotype; D054643:INDEL Mutation / Q000235:genetics; D010641:Phenotype; D017422:Sequence Analysis, DNA
keywords: E. coli genome; experimental evolution; metagenomics; mutational sweeps; periodic selection