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Larger cells have relatively smaller nuclei across the Tree of Life


Malerba, Martino E. (2021), Larger cells have relatively smaller nuclei across the Tree of Life, Dryad, Dataset,


Larger cells have larger nuclei, but the precise relationship between cell size and nucleus size remains unclear, and the evolutionary forces that shape this relationship are debated. We compiled data for almost 900 species – from yeast to mammals – at three scales of biological organisation: among‐species, within‐species, and among‐lineages of a species that was artificially selected for cell size. At all scales, we showed that the ratio of nucleus size to cell size (the ‘N: C’ ratio) decreased systematically in larger cells. Size evolution appears more constrained in nuclei than cells: cell size spans across six orders of magnitude, whereas nucleus size varies by only three. The next important challenge is to determine the drivers of this apparently ubiquitous relationship in N:C ratios across such a diverse array of organisms.


We compiled from the scientific litterature an among‐species dataset on cell size and nucleus size covering 879 species, ranging from prokaryotes to mammals and also including the nucleoid (c.f. nucleus) of prokaryotes. For the within‐species dataset, we compiled from scientific articles 7929 observations across 20 species, ranging from yeast to plants to metazoans. Finally, we evolved in the laboratory 72 lineages of the green alga Dunaliella tertiolecta for 500 generations (ca. 3 years), artificially selecting for different cell sizes while tracking the fate of their N:C ratios.

Usage Notes


There are three main folders:

(1) “Among-species (DNA and Nucleus)” generates Fig. 1

(2) "Within-species" generates Fig. 2 

(3) “Dunaliella tertiolecta” generates Fig. 3

In each subfolder, open the .R script using the statistical software R. Within the script file: (1) check that all packages are installed in the computer (otherwise install before running the script), and (2) set the directory where the script is located in the computer. After having done that, everything else should work by simply running the file in R. The script will read all data, calculate statistics, plot images, and save the images in the same folder. The file is designed to run in Mac computers.