Protein-protein interactions form the molecular basis for organismal development and function (1, 2). In cells, protein interactions are dynamic and subject to spatiotemporal regulations that are specific to the cell type and cell cycle phase. Mutations that abolish or rewire protein-protein interaction networks (the interactome) are often detrimental and manifest in developmental anomalies and diseases (3, 4). Recent advances in quantitative proteomics offer snapshots of cell type–specific proteomes, but scientific understanding of how protein-protein interactions vary between physiological and disease conditions is limited.
Primate cognition requires interaction processing. Interactions can reveal otherwise hidden properties of intentional agents, such as thoughts and feelings, and of inanimate objects, such as mass and material. Where and how interaction analyses are implemented in the brain is unknown. Using whole-brain functional magnetic resonance imaging in macaque monkeys, we discovered a network centered in the medial and ventrolateral prefrontal cortex that is exclusively engaged in social interaction analysis. Exclusivity of specialization was found for no other function anywhere in the brain.
Gene duplication within an organism is a relatively common event during evolution. However, we cannot predict the fate of the duplicated genes: Will they be lost, evolve, or overlap in function within an organismal lineage or species? Kuzmin et al. explored the fate of duplicated gene function within the yeast Saccharomyces cerevisiae (see the Perspective by Ehrenreich). They examined how experimental deletions of one or two duplicated genes (paralogs) affected yeast fitness and were able to determine which genes have likely evolved new essential functions and which retained functional overlap, a condition the authors refer to as entanglement. On the basis of these results, they propose how entanglement affects the evolutionary trajectory of gene duplications. Science , this issue p. [eaaz5667]; see also p.  ### INTRODUCTION Whole-genome duplication (WGD) events are pervasive in eukaryotes, shaping the genomes of simple single-celled organisms, such as yeast, as well as those of more complex metazoans, including humans. Most duplicated genes are eliminated after WGD because one copy accumulates deleterious mutations, leading to its loss. However, a significant proportion of duplicates persists, and factors that result in duplicate gene retention are poorly understood but critical for understanding the evolutionary forces that shape genomes. ### RATIONALE Quantifying the functional divergence of paralog pairs is of particular interest because of the strong selection against functional redundancy. Negative genetic interactions identify functional relationships between genes and provide a means to directly capture the functional relationship between duplicated genes. Genetic interactions occur when the phenotype associated with a combination of mutations in two or more different genes deviates from the expected combined effect of the individual mutations. A negative genetic interaction refers to a combination of mutations that generates a stronger fitness defect than expected, such as synthetic lethality. Here, we used systematic analysis of digenic and trigenic interaction profiles to assess the functional relationship of retained duplicated genes. ### RESULTS To map both digenic and trigenic interactions of duplicated genes, we profiled query strains carrying single-deletion mutations and the corresponding double-deletion mutations for 240 different dispensable paralog pairs originating from the yeast WGD event. In total, we tested ~550,000 double and ~260,000 triple mutants for genetic interactions, and identified ~4700 negative digenic interactions and ~2500 negative trigenic interactions. We quantified the trigenic interaction fraction, defined as the ratio of negative trigenic interactions to the total number of interactions associated with the paralog pair. The distribution of the resulting trigenic interaction fractions was distinctly bimodal, with two-thirds of paralogs exhibiting a low trigenic interaction fraction (diverged paralogs) and one-third showing a high trigenic interaction fraction (functionally redundant paralogs). Paralogs with a high trigenic interaction fraction showed a relatively low asymmetry in their number of digenic interactions, low rates of protein sequence divergence, and a negative digenic interaction within the gene pair. We correlated position-specific evolutionary rate patterns between paralogs to assess constraints acting on their evolutionary trajectories. Paralogs with a high trigenic interaction fraction showed more correlated evolutionary rate patterns and thus were more evolutionarily constrained than paralogs with a low trigenic interaction fraction. Computational simulations that modeled duplicate gene evolution revealed that as the extent of the initial entanglement (overlap of functions) of paralogs increased, so did the range of functional redundancy at steady state. Thus, the bimodal distribution of the trigenic interaction fraction may reflect that some paralogs diverged, primarily evolving distinct functions without redundancy, while others converged to an evolutionary steady state with substantial redundancy due to their structural and functional entanglement. ### CONCLUSION We propose that the evolutionary fate of a duplicated gene is dictated by an interplay of structural and functional entanglement. Paralog pairs with high levels of entanglement are more likely to revert to a singleton state. In contrast, unconstrained paralogs will tend to partition their functions and adopt divergent roles. Intermediately entangled paralog pairs may partition or expand nonoverlapping functions while also retaining some common, overlapping functions, such that they can both adopt paralog-specific roles and maintain functional redundancy at an evolutionary steady state. ![Figure] Complex genetic interaction analysis of duplicated genes. The trigenic interaction fraction, which incorporates digenic and trigenic interactions, captures the functional relationship of duplicated genes and follows a bimodal distribution. Paralogs with a high trigenic interaction fraction are under evolutionary constraints reflecting their structural and functional entanglement. Whole-genome duplication has played a central role in the genome evolution of many organisms, including the human genome. Most duplicated genes are eliminated, and factors that influence the retention of persisting duplicates remain poorly understood. We describe a systematic complex genetic interaction analysis with yeast paralogs derived from the whole-genome duplication event. Mapping of digenic interactions for a deletion mutant of each paralog, and of trigenic interactions for the double mutant, provides insight into their roles and a quantitative measure of their functional redundancy. Trigenic interaction analysis distinguishes two classes of paralogs: a more functionally divergent subset and another that retained more functional overlap. Gene feature analysis and modeling suggest that evolutionary trajectories of duplicated genes are dictated by combined functional and structural entanglement factors. : /lookup/doi/10.1126/science.aaz5667 : /lookup/doi/10.1126/science.abc1796 : pending:yes
One defining characteristic of species is reproductive incompatibility; hybrids between two species either do not form or have low fitness. The general explanation is the development of genetic incompatibilities that reduce fitness in hybrids. Such incompatibilities could occur if there is a deleterious interaction between two genetic variants that have previously not occurred in the same genetic background, commonly called Dobzhansky-Muller incompatibilities (1, 2). Identifying the genes underlying these incompatibilities is challenging; the more reproductively isolated two species are, the more difficult it is to cross them and map the incompatibility. As a result, very few such interactions have been identified (3, 4).
These agents are particularly effective for tasks in which long-term interactions and personal relationships are known to be important, such as in education, sales and marketing, and the helping professions. Of these, I have focused my recent work within the healthcare domain on health education and health behavior change applications. In order to accomplish this, I conduct communication studies of health provider-patient interactions, develop new approaches to dialogue planning that can address both the behavioral intervention and social aspects of the interactions, and develop animated agents that can use appropriate nonverbal behavior in their simulated conversations with patients, as well as conduct clinical trials to evaluate the efficacy of the resulting systems.