University of Wisconsin-Madison

About: University of Wisconsin-Madison is a education organization based out in Madison, Wisconsin, United States. It is known for research contribution in the topics: Population & Gene. The organization has 108707 authors who have published 237594 publications receiving 11883575 citations.

FLOWERING LOCUS C Encodes a Novel MADS Domain Protein That Acts as a Repressor of Flowering

Abstract: Winter-annual ecotypes of Arabidopsis are relatively late flowering, unless the flowering of these ecotypes is promoted by exposure to cold (vernalization). This vernalization-suppressible, late-flowering phenotype results from the presence of dominant, late-flowering alleles at two loci, FRIGIDA (FRI) and FLOWERING LOCUS C (FLC). In this study, we report that flc null mutations result in early flowering, demonstrating that the role of active FLC alleles is to repress flowering. FLC was isolated by positional cloning and found to encode a novel MADS domain protein. The levels of FLC mRNA are regulated positively by FRI and negatively by LUMINIDEPENDENS. FLC is also negatively regulated by vernalization. Overexpression of FLC from a heterologous promoter is sufficient to delay flowering in the absence of an active FRI allele. We propose that the level of FLC activity acts through a rheostat-like mechanism to control flowering time in Arabidopsis and that modulation of FLC expression is a component of the vernalization response.

RNA-dependent DNA polymerase in virions of Rous sarcoma virus.

Abstract: Viral RNA-dependent DNA Polymerase: RNA-dependent DNA Polymerase in Virions of Rous Sarcoma Virus

Microbial stress‐response physiology and its implications for ecosystem function

Abstract: Microorganisms have a variety of evolutionary adaptations and physiological acclimation mechanisms that allow them to survive and remain active in the face of environmental stress. Physiological responses to stress have costs at the organismal level that can result in altered ecosystem-level C, energy, and nutrient flows. These large-scale impacts result from direct effects on active microbes' physiology and by controlling the composition of the active microbial community. We first consider some general aspects of how microbes experience environmental stresses and how they respond to them. We then discuss the impacts of two important ecosystem-level stressors, drought and freezing, on microbial physiology and community composition. Even when microbial community response to stress is limited, the physiological costs imposed on soil microbes are large enough that they may cause large shifts in the allocation and fate of C and N. For example, for microbes to synthesize the osmolytes they need to survive a single drought episode they may consume up to 5% of total annual net primary production in grassland ecosystems, while acclimating to freezing conditions switches Arctic tundra soils from immobilizing N during the growing season to mineralizing it during the winter. We suggest that more effectively integrating microbial ecology into ecosystem ecology will require a more complete integration of microbial physiological ecology, population biology, and process ecology.

Model selection and estimation in the Gaussian graphical model

Abstract: SUMMARY We propose penalized likelihood methods for estimating the concentration matrix in the Gaussian graphical model. The methods lead to a sparse and shrinkage estimator of the concentration matrix that is positive definite, and thus conduct model selection and estimation simultaneously. The implementation of the methods is nontrivial because of the positive definite constraint on the concentration matrix, but we show that the computation can be done effectively by taking advantage of the efficient maxdet algorithm developed in convex optimization. We propose a BIC-type criterion for the selection of the tuning parameter in the penalized likelihood methods. The connection between our methods and existing methods is illustrated. Simulations and real examples demonstrate the competitive performance of the new methods.