Molecular Biology and EvolutionEvolutionary BiologyPeer-reviewed journal article
Functional optimization in distinct tissues and conditions constrains the rate of protein evolution
Abstract
Understanding the main determinants of protein evolution is a fundamental challenge in biology. Despite many decades of active research, the molecular and cellular mechanisms underlying the substantial variability of evolutionary rates across cellular proteins are not currently well understood. It also remains unclear how protein molecular function is optimized in the context of multicellular species and why many proteins, such as enzymes, are only moderately efficient on average. Our analysis of genomics and functional datasets reveals in multiple organisms a strong inverse relationship between the optimality of protein molecular function and the rate of protein evolution. Furthermore, we find that highly expressed proteins tend to be substantially more functionally optimized. These results suggest that cellular expression costs lead to more pronounced functional optimization of abundant proteins, and that the purifying selection to maintain high levels of functional optimality significantly slows protein evolution. We observe that in multicellular species both the rate of protein evolution and the degree of protein functional efficiency are primarily affected by expression in several distinct cell types and tissues. Specifically, in developed neurons with upregulated synaptic processes in animals and in young and fast-growing tissues in plants. Overall, our analysis reveals how various constraints from the molecular, cellular, and species levels of biological organization jointly affect the rate of protein evolution and the level of protein functional adaptation.
- organism: human
- organism: mouse
- organism: plant (other)
- assay: protein sequence
- research focus: protein folding & dynamics
- research focus: chromatin & epigenetic regulation
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 7
- FWCI
- 1.46
- Field percentile
- top 18%
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