Inferring fitness landscapes and selection on phenotypic states from single-cell genealogical data.

ABSTRACT: Recent advances in single-cell time-lapse microscopy have revealed non-genetic heterogeneity and temporal fluctuations of cellular phenotypes. While different phenotypic traits such as abundance of growth-related proteins in single cells may have differential effects on the reproductive success of cells, rigorous experimental quantification of this process has remained elusive due to the complexity of single cell physiology within the context of a proliferating population. We introduce and apply a practical empirical method to quantify the fitness landscapes of arbitrary phenotypic traits, using genealogical data in the form of population lineage trees which can include phenotypic data of various kinds. Our inference methodology for fitness landscapes determines how reproductivity is corre

SUBMITTER: Nozoe T 

PROVIDER: S-EPMC5360348 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature