No abstract

In several organisms, particular functional categories of genes, such as regulatory and complex-forming genes, are preferentially retained after whole-genome multiplications but rarely duplicate through small-scale duplication, a pattern referred to as reciprocal retention. This peculiar duplication behavior is hypothesized to stem from constraints on the dosage balance between the genes concerned and their interaction context. However, the evidence for a relationship between reciprocal retention and dosage balance sensitivity remains fragmentary. Here, we identified which gene families are most strongly reciprocally retained in the angiosperm lineage and studied their functional and evolutionary characteristics. Reciprocally retained gene families exhibit stronger sequence divergence constraints and lower rates of functional and expression divergence than other gene families, suggesting that dosage balance sensitivity is a general characteristic of reciprocally retained genes. Gene families functioning in regulatory and signaling processes are much more strongly represented at the top of the reciprocal retention ranking than those functioning in multiprotein complexes, suggesting that regulatory imbalances may lead to stronger fitness effects than classical stoichiometric protein complex imbalances. Finally, reciprocally retained duplicates are often subject to dosage balance constraints for prolonged evolutionary times, which may have repercussions for the ease with which genome multiplications can engender evolutionary innovation.

The identification of modules in protein structures has major relevance in structural biology, with consequences in protein stability and functional classification, adding new perspectives in drug design. In this work, we present the comparison between a topological (spectral clustering) and a geometrical (k-means) approach to module identification, in the frame of a multiscale analysis of the protein architecture principles. The global consistency of an adjacency matrix based technique (spectral clustering) and a method based on full rank geometrical information (k-means) give a proof-of-concept of the relevance of protein contact networks in structure determination. The peculiar "small-world" character of protein contact graphs is established as well, pointing to average shortest path as a mesoscopic crucial variable to maximize the efficiency of within-molecule signal transmission. The specific nature of protein architecture indicates topological approach as the most proper one to highlight protein functional domains, and two new representations linking sequence and topological role of aminoacids are demonstrated to be of use for protein structural analysis. Here we present a case study regarding azurin, a small copper protein implied in the Pseudomonas aeruginosa respiratory chain. Its pocket molecular shape and its electron transfer function have challenged the method, highlighting its potentiality to catch jointly the structure and function features of protein structures through their decomposition into modules.