Equipartitioning by chromosome association and copy number correction by DNA amplification are at the heart of the evolutionary success of the selfish yeast 2-micron plasmid. The present analysis reveals frequent plasmid presence near telomeres (TELs) and centromeres (CENs) in mitotic cells, with a preference towards the former. Inactivation of Cdc14 causes plasmid missegregation, which is correlated to the non-disjunction of TELs (and of rDNA) under this condition. Induced missegregation of chromosome XII, one of the largest yeast chromosomes which harbors the rDNA array and is highly dependent on the condensin complex for proper disjunction, increases 2-micron plasmid missegregation. This is not the case when chromosome III, one of the smallest chromosomes, is forced to missegregate. Plasmid stability decreases when the condensin subunit Brn1 is inactivated. Brn1 is recruited to the plasmid partitioning locus (STB) with the assistance of the plasmid-coded partitioning proteins Rep1 and Rep2. Furthermore, in a dihybrid assay, Brn1 interacts with Rep1-Rep2. Taken together, these findings support a role for condensin and/or condensed chromatin in 2-micron plasmid propagation. They suggest that condensed chromosome loci are among favored sites utilized by the plasmid for its chromosome-associated segregation. By homing to condensed/quiescent chromosome locales, and not over-perturbing genome homeostasis, the plasmid may minimize fitness conflicts with its host. Analogous persistence strategies may be utilized by other extrachromosomal selfish genomes, for example, episomes of mammalian viruses that hitchhike on host chromosomes for their stable maintenance.

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Mutations provide the raw material for natural selection to act. Therefore, understanding the variety and relative frequency of different type of mutations is critical to understanding the nature of genetic diversity in a population. Mutation accumulation (MA) experiments have been used in this context to estimate parameters defining mutation rates, distribution of fitness effects (DFE), and spectrum of mutations. MA experiments can be performed with different effective population sizes. In MA experiments with bacteria, a single founder is grown to a size of a colony (~ 108). It is assumed that natural selection plays a minimal role in dictating the dynamics of colony growth. In this work, we simulate colony growth via a mathematical model, and use our model to mimic an MA experiment. We demonstrate that selection ensures that, in an MA experiment, fraction of all mutations that are beneficial is over-represented by a factor of almost two, and that the distribution of fitness effects of beneficial and deleterious mutations are inaccurately captured in an MA experiment. Given this, the estimate of mutation rates from MA experiments is non-trivial. We then perform an MA experiment with 160 lines of E. coli, and show that due to the effect of selection in a growing colony, the size and sector of a colony from which the experiment is propagated impacts the results. Overall, we demonstrate that the results of MA experiments need to be revisited taking into account the action of selection in a growing colony.

Mutations provide the raw material for natural selection to act. Therefore, understanding the variety and relative frequency of different type of mutations is critical to understanding the nature of genetic diversity in a population. Mutation accumulation (MA) experiments have been used in this context to estimate parameters defining mutation rates, distribution of fitness effects (DFE), and spectrum of mutations. MA experiments performed with organisms such as Drosophila have an effective population size of one. However, in MA experiments with bacteria and yeast, a single founder is allowed to grow to a size of a colony (~108). The effective population size in these experiments is of the order of 10. In this scenario, while it is assumed that natural selection plays a minimal role in dictating the dynamics of colony growth and therefore, the MA experiment; this effect has not been tested explicitly. In this work, we simulate colony growth and perform an MA experiment, and demonstrate that selection ensures that, in an MA experiment, fraction of all mutations that are beneficial is over represented by a factor greater than two. The DFE of beneficial and deleterious mutations are accurately captured in an MA experiment. We show that the effect of selection in a growing colony varies non-monotonically and that, in the face of natural selection dictating an MA experiment, estimates of mutation rate of an organism is not trivial. We perform experiments with 160 MA lines of E. coli, and demonstrate that rate of change of mean fitness is a non-monotonic function of the colony size, and that selection acts differently in different sectors of a growing colony. Overall, we demonstrate that the results of MA experiments need to be revisited taking into account the action of selection in a growing colony.

Understanding the basis of biological diversity remains a central problem in evolutionary biology. Using microbial systems, adaptive diversification has been studied in (a) spatially heterogeneous environments, (b) temporally segregated resources, and (c) resource specialization in a homogeneous environment. However, it is not well understood how adaptive diversification can take place in a homogeneous environment containing a single resource. Starting from an isogenic population of yeast Saccharomyces cerevisiae, we report rapid adaptive diversification, when propagated in an environment containing melibiose as the carbon source. The diversification is driven due to a public good enzyme α‐galactosidase, which hydrolyzes melibiose into glucose and galactose. The diversification is driven by mutations at a single locus, in the GAL3 gene in the S. cerevisiae GAL/MEL regulon. We show that metabolic co‐operation involving public resources could be an important mode of generating biological diversity. Our study demonstrates sympatric diversification of yeast starting from an isogenic population and provides detailed mechanistic insights into the factors and conditions responsible for generating and maintaining the population diversity.