Dataset built from the Dryad depository entry associated with the article "Protein degradation rate in Arabidopsis thaliana leaf growth and development" by Li et al. (2017)
li2017li2017 is the main dataset and is a tibble with columns:
Protein identifier. Can be matched to a more explicit
protein description in li2017_prots.
Sample identity. Different samples were used for relative abundance measurements and labelled fraction measurements.
Relative abundance compared to a reference sample.
Proportion of 15N in the protein.
Time elapsed since growth medium switch to 15N, in days.
Leaf identity (3rd, 5th, or 7th leaf of individual plants).
li2017_prots maps protein identifiers to protein descriptions
and is a tibble with columns:
Protein identifier. Can be matched with the same column in
li2017.
Protein description
li2017_counts is a summary table counting the number of
available data points for relative abundance and labelled fraction for
each protein in li2017. It is a tibble with columns:
Protein identifier. Can be matched with the same column in
li2017.
Number of relative abundance data points for a given protein.
Number of labelled fraction data points for a given protein.
In this study, the authors used a growth medium containing 15N to grow 21-day old Arabidopsis plants which were grown on a natural 14N/15N medium until that day. The third, fifth and seventh leaves were sampled from individuals at different time points after the medium switch (0, 1, 3 and 5 days). Proteins were identified and labelled fractions were measured using mass spectrometry. Relative protein abundances were determined in comparison with a reference sample.
The aim of the authors was to quantify in vivo degradation rates for as many proteins as possible (1228 proteins in the original paper) and examine which determinants had an effect or not on protein degradation rates (e.g. protein domains, protein complex membership, ...).
Three datasets were extracted from the large dataset available on Dryad for
packaging inside isotracer: li2017, li2017_prots, and
li2017_counts.