Plasticity of genetic regulation during cellular learning
Heistinger, L.; Parfenova, I.; Damenikan, A.; Michel, A.; Kornmann, B.; Sintsova, A.; Barral, Y.
Show abstract
Even under physiological conditions, cells are exposed to multiple, spatially and temporally complex signals and need to regularly adjust their response to survive and function. At least in some cases, identifying the appropriate response relies on the ability cells to learn from experience. For example, budding yeast cells learn to ignore futile mating signals. Using this paradigm, we investigated the genetic requirements supporting learning in single cells. We show that it arises from the dynamics of a large, highly redundant and plastic genetic network, where the contribution of most genes to learning varies across experimental replicates. Furthermore, this network is highly resistant to genetic perturbations and involves a broad panel of cellular functions and sensing pathways, suggesting that it can integrate a large diversity of inputs. Together, our data support the notion that cellular learning is an emerging feature of the information storage capability inherent to large sets of interacting genes, indicating that it should be widely conserved across cell types.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- A crucial role for dynamic expression of components encoding the negative arm of the circadian clock 96%
- Changes in the distribution of fitness effects and adaptive mutational spectra following a single first step towards adaptation 95%
- Differential regulation of mRNA stability modulates transcriptional memory and facilitates environmental adaptation 95%
Similar papers in this journal
Similar papers in this journal
- Evolutionary diversification reveals distinct somatic versus germline cytoskeletal functions of the Arp2 branched actin nucleator protein 94%
- Rediversification Following Ecotype Isolation Reveals Hidden Adaptive Potential 94%
- Dopey-dependent regulation of extracellular vesicles maintains neuronal morphology 94%
"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.