A unified framework for measuring selection on cellular lineages and traits
| Autor: | Edo Kussell, Yuichi Wakamoto, Takashi Nozoe, Shunpei Yamauchi, Reiko Okura |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Mammals
General Immunology and Microbiology Genetic heterogeneity Lineage (evolution) General Neuroscience General Medicine Biology Phenotype Biological Evolution General Biochemistry Genetics and Molecular Biology Evolutionary biology Skewness Trait Population growth Animals Cell Lineage Selection Genetic Selection (genetic algorithm) Function (biology) Retrospective Studies |
| Zdroj: | eLife. 11 |
| ISSN: | 2050-084X |
| Popis: | Intracellular states probed by gene expression profiles and metabolic activities are intrinsically noisy, causing phenotypic variations among cellular lineages. Understanding the adaptive and evolutionary roles of such variations requires clarifying their linkage to population growth rates. Extending a cell lineage statistics framework, here we show that a population’s growth rate can be expanded by the cumulants of a fitness landscape that characterize how fitness distributes in a population. The expansion enables quantifying the contribution of each cumulant, such as variance and skewness, to population growth. We introduce a function that contains all the essential information of cell lineage statistics, including mean lineage fitness and selection strength. We reveal a relation between fitness heterogeneity and population growth rate response to perturbation. We apply the framework to experimental cell lineage data from bacteria to mammalian cells, revealing distinct levels of growth rate gain from fitness heterogeneity across environments and organisms. Furthermore, third or higher order cumulants’ contributions are negligible under constant growth conditions but could be significant in regrowing processes from growth-arrested conditions. We identify cellular populations in which selection leads to an increase of fitness variance among lineages in retrospective statistics compared to chronological statistics. The framework assumes no particular growth models or environmental conditions, and is thus applicable to various biological phenomena for which phenotypic heterogeneity and cellular proliferation are important. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|