A number of loci are associated with highly heritable schizophrenia and the prevalence of this mental illness has had considerable negative fitness effects on human populations. Here we focused on one particular schizophrenia-associated gene that encodes a sialyltransferase (ST8SIA2) and is expressed preferentially in the brain with the level being largely determined by three SNPs in the promoter region. It is suggested that the expression level of the ST8SIA2 gene is a genetic determinant of schizophrenia risk, and we found that a geographically differentiated non-risk SNP type (-type) has significantly reduced promoter activity. A newly developed method for detecting ongoing positive selection was applied to the ST8SIA2 genomic region with the identification of an unambiguous sweep signal in a rather restricted region of 18 kb length surrounding the promoter. We also found that while the -type emerged in anatomically modern humans in Africa over 100 thousand years ago, it has increased its frequency in Asia only during the past 20–30 thousand years. These findings support that the positive selection is driven by psychosocial stress due to changing social environments since around the last glacial maximum, and raise a possibility that schizophrenia extensively emerged during the Upper Paleolithic and Neolithic era.

Lysin motif (LysM) receptor-like kinase CERK1 is a co-receptor essential for plant immune responses against carbohydrate microbe-associated molecular patterns (MAMPs). Concerning the immediate downstream signaling components of CERK1, receptor-like cytoplasmic kinases such as PBL27 and other RLCK VII members have been reported to regulate immune responses positively. In this study, we report that a novel CERK1-interacting E3 ubiquitin ligase, PUB4, is also involved in the regulation of MAMP-triggered immune responses. Knockout of PUB4 resulted in the alteration of chitin-induced defense responses, indicating that PUB4 positively regulates reactive oxygen species generation and callose deposition but negatively regulates MAPK activation and defense gene expression. On the other hand, detailed analyses of a double knockout mutant of pub4 and sid2, a mutant of salicylic acid (SA) synthesis pathway, showed that the contradictory phenotype of the pub4 mutant was actually caused by abnormal accumulation of SA in this mutant and that PUB4 is a positive regulator of immune responses. The present and recent findings on the role of PUB4 indicate that PUB4 is a unique E3 ubiquitin ligase involved in the regulation of both plant immunity and growth/development.

An understanding of epidemiological dynamics is important for prevention and control of epidemic outbreaks. However, previous studies tend to focus only on specific areas, indicating that application to another area or intervention strategy requires a similar time-consuming simulation. Here, we study the epidemic dynamics of the disease-spread over a commute network, using the Tokyo metropolitan area as an example, in an attempt to elucidate the general properties of epidemic spread over a commute network that could be used for a prediction in any metropolitan area. The model is formulated on the basis of a metapopulation network in which local populations are interconnected by actual commuter flows in the Tokyo metropolitan area and the spread of infection is simulated by an individual-based model. We find that the probability of a global epidemic as well as the final epidemic sizes in both global and local populations, the timing of the epidemic peak, and the time at which the epidemic reaches a local population are mainly determined by the joint distribution of the local population sizes connected by the commuter flows, but are insensitive to geographical or topological structure of the network. Moreover, there is a strong relation between the population size and the time that the epidemic reaches this local population and we are able to determine the reason for this relation as well as its dependence on the commute network structure and epidemic parameters. This study shows that the model based on the connection between the population size classes is sufficient to predict both global and local epidemic dynamics in metropolitan area. Moreover, the clear relation of the time taken by the epidemic to reach each local population can be used as a novel measure for intervention; this enables efficient intervention strategies in each local population prior to the actual arrival.

No abstract