Abstract:
Models of learning, reciprocity and altruism cannot explain all aspects of observed contributions in the public good game. Here a new model is described in which players recognize a correlation between their own contribution and the likely contributions of other players. The correlation is calculated by treating a player's own conjectured contribution just like any other data point within a learning model. Although players recognize that this correlation is not causal, they nevertheless choose to maximize expected utility conditional on their own action rather than standard expected utility. Results from the model explain previously puzzling quantitative trends in the data. © 2006 Elsevier B.V. All rights reserved.
PMID: 23335336;PMCID: PMC3606098;Abstract:
Cryptic genetic sequences have attenuated effects on phenotypes. In the classic view, relaxed selection allows cryptic genetic diversity to build up across individuals in a population, providing alleles that may later contribute to adaptation when coopted- e.g., following a mutation increasing expression from a low, attenuated baseline. This view is described, for example, by the metaphor of the spread of a population across a neutral network in genotype space. As an alternative view, consider the fact that most phenotypic traits are affected by multiple sequences, including cryptic ones. Even in a strictly clonal population, the co-option of cryptic sequences at different loci may have different phenotypic effects and offer the population multiple adaptive possibilities. Here, we model the evolution of quantitative phenotypic characters encoded by cryptic sequences and compare the relative contributions of genetic diversity and of variation across sites to the phenotypic potential of a population. We show that most of the phenotypic variation accessible through co-option would exist even in populations with no polymorphism. This is made possible by a history of compensatory evolution, whereby the phenotypic effect of a cryptic mutation at one site was balanced by mutations elsewhere in the genome, leading to a diversity of cryptic effect sizes across sites rather than across individuals. Cryptic sequences might accelerate adaptation and facilitate large phenotypic changes even in the absence of genetic diversity, as traditionally defined in terms of alternative alleles. © 2013 by the Genetics Society of America.
Most students have difficulty reasoning about chance events, and misconceptions regarding probability can persist or even strengthen following traditional instruction. Many biostatistics classes sidestep this problem by prioritizing exploratory data analysis over probability. However, probability itself, in addition to statistics, is essential both to the biology curriculum and to informed decision making in daily life. One area in which probability is particularly important is medicine. Given the preponderance of pre health students, in addition to more general interest in medicine, we capitalized on students' intrinsic motivation in this area to teach both probability and statistics. We use the randomized controlled trial as the centerpiece of the course, because it exemplifies the most salient features of the scientific method, and the application of critical thinking to medicine. The other two pillars of the course are biomedical applications of Bayes' theorem and science and society content. Backward design from these three overarching aims was used to select appropriate probability and statistics content, with a focus on eliciting and countering previously documented misconceptions in their medical context. Pretest/posttest assessments using the Quantitative Reasoning Quotient and Attitudes Toward Statistics instruments are positive, bucking several negative trends previously reported in statistics education.
PMID: 16739451;Abstract:
Although many examples of trait loss exist in nature, the underlying population genetic mechanism responsible for the loss is usually unknown. Selective or neutral processes can result in the deterioration of a trait, and often one of these is inferred based on indirect evidence. Furthermore, selective pressures that are unique to particular environments and the effect these might have on the population genetic cause of trait loss are not well understood. Here we describe an experimental evolution system where two different environments were used for addressing the population genetic cause of trait loss throughout evolutionary time. We found that growth in minimal medium (i.e., prototrophy) was lost in all populations regardless of the experimental environment and that the pattern of trait loss in one environment was due to selection, whereas in the other environment the cause remains inconclusive. © 2006 The Society for the Study of Evolution. All rights reserved.
Abstract:
Hsp90 reveals phenotypic variation in the laboratory, but is Hsp90 depletion important in the wild? Recent work from Chen and Wagner in BMC Evolutionary Biology has discovered a naturally occurring Drosophila allele that downregulates Hsp90, creating sensitivity to cryptic genetic variation. Laboratory studies suggest that the exact magnitude of Hsp90 downregulation is important. Extreme Hsp90 depletion might reactivate transposable elements and/or induce aneuploidy, in addition to revealing cryptic genetic variation.See research article http://wwww.biomedcentral.com/1471-2148/12/25. © 2012 Siegal and Masel; licensee BioMed Central Ltd.
