Most Associations Between Transcript Features and Gene Expression are Monotonic

Dozens of previous studies in the field have dealt with the relations between transcript features and their expression. Most of the models employed in this context assume that the effect of each transcript feature on gene expression is monotonic. In the current study we aim to understand, for the first time, if indeed the relations between transcript features (i.e., the UTRs and ORF) and measurements related to the different stages of gene expression are monotonic. To this end, we analyze 5,432 transcript features and gene expression measurements (mRNA levels, ribosomal densities, protein levels, etc.) of 4,367 S. cerevisiae genes. We use the Maximal Information Coefficient (MIC) in order to identify potential relations that are not necessarily linear or monotonic. Our analyses demonstrate that the relation between most transcript features and the examined gene expression measurements is monotonic. In the cases of deviation from monotonicity the relation/deviation is very weak. These results should help in guiding the development of computational gene expression modeling and engineering, improve the understating of this process and contribute towards better understanding of transcript evolution at the molecular level.