Back

High rates of spontaneous chromosomal duplications unravel dosage compensation by translational regulation

Krasovec, M.; Merret, R.; Sanchez, F.; Sanchez-Brosseau, S.; Piganeau, G.

2022-12-19 evolutionary biology
10.1101/2022.02.03.478961 bioRxiv
Show abstract

While duplications have long been recognized as a fundamental process driving major evolutionary innovations, direct estimations of spontaneous chromosome duplication rates, leading to aneuploid karyotypes, are scarce. Here, we provide the first estimations of spontaneous chromosome duplication rates in six unicellular eukaryotic species from mutation accumulation (MA) experiments. The spontaneous chromosome duplication rates reach 1x10-4 to 1x10-3 per genome per generation, which is ~4 to ~50 times less frequent than spontaneous point mutations per genome, whereas chromosome duplication events can affect 1 to 7% of the total genome size. Comparative transcriptomics between MA lines with different chromosome duplications reveals a strong positive correlation between RNA expression rate and DNA copy number. However, comparative analyses of the translation rate of mRNAs estimated by polysome profiling unravel a chromosome specific dosage compensation mechanism. In particular, one chromosome with a gene average of 2.1 excess of mRNAs is compensated by an average of ~0.7 decrease in translation rates. Altogether, our results are consistent with previous observations of a chromosome dependent effect of dosage compensation and provide evidence that it may occur during translation. These results support the existence of a yet unknown post-transcriptional mechanism orchestrating the modification of translation of hundreds of transcripts from genes located on duplicated regions in eukaryotes.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.