The Genetic Basis of Mutation Rate Variation in Yeast.

Mutations are the root source of genetic variation and underlie the process of evolution. Although the rates at which mutations occur vary considerably between species, little is known about differences within species, or the genetic and molecular basis of these differences. Here, we leveraged the power of the yeast Saccharomyces cerevisiae as a model system to uncover natural genetic variants that underlie variation in mutation rate. We developed a high-throughput fluctuation assay and used it to quantify mutation rates in seven natural yeast isolates and in 1040 segregant progeny from a cross between BY, a laboratory strain, and RM, a wine strain. We observed that mutation rate varies among yeast strains and is heritable (H 2 = 0.49). We performed linkage mapping in the segregants and identified four quantitative trait loci underlying mutation rate variation in the cross. We fine-mapped two quantitative trait loci to the underlying causal genes, RAD5 and MKT1, that contribute to mutation rate variation. These genes also underlie sensitivity to the DNA-damaging agents 4NQO and MMS, suggesting a connection between spontaneous mutation rate and mutagen sensitivity

Multiparameter behavioral profiling reveals distinct thermal response regimes in Caenorhabditis elegans.

BackgroundResponding to noxious stimuli by invoking an appropriate escape response is critical for survival of an organism. The sensations of small and large changes in temperature in most organisms have been studied separately in the context of thermotaxis and nociception, respectively. Here we use the nematode C. elegans to address the neurogenetic basis of responses to thermal stimuli over a broad range of intensities.ResultsC. elegans responds to aversive temperature by eliciting a stereotypical behavioral sequence. Upon sensation of the noxious stimulus, it moves backwards, turns and resumes forward movement in a new direction. In order to study the response of C. elegans to a broad range of noxious thermal stimuli, we developed a novel assay that allows simultaneous characterization of multiple aspects of escape behavior elicited by thermal pulses of increasing amplitudes. We exposed the laboratory strain N2, as well as 47 strains with defects in various aspects of nervous system function, to thermal pulses ranging from ΔT = 0.4°C to 9.1°C and recorded the resulting behavioral profiles.ConclusionsThrough analysis of the multidimensional behavioral profiles, we found that the combinations of molecules shaping avoidance responses to a given thermal pulse are unique. At different intensities of aversive thermal stimuli, these distinct combinations of molecules converge onto qualitatively similar stereotyped behavioral sequences

Graded-index magnonics

This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics or Institute for Low Temperature Physics and Engineering (Kharkov, Ukraine).The published version can be found at http://hdl.handle.net/10871/22077The wave solutions of the Landau–Lifshitz equation (spin waves) are characterized by some of the most complex and peculiar dispersion relations among all waves. For example, the spin-wave (“magnonic”) dispersion can range from the parabolic law (typical for a quantum-mechanical electron) at short wavelengths to the nonanalytical linear type (typical for light and acoustic phonons) at long wavelengths. Moreover, the long-wavelength magnonic dispersion has a gap and is inherently anisotropic, being naturally negative for a range of relative orientations between the effective field and the spin-wave wave-vector. Nonuniformities in the effective field and magnetization configurations enable the guiding and steering of spin waves in a deliberate manner and there-fore represent landscapes of graded refractive index (graded magnonic index). By analogy to the fields of graded-index photonics and transformation optics, the studies of spin waves in graded magnonic landscapes can be united under the umbrella of the graded-index magnonics theme and are reviewed here with focus on the chal-lenges and opportunities ahead of this exciting research direction.Engineering and Physical Sciences Research Council (EPSRC

Accounting for genetic interactions improves modeling of individual quantitative trait phenotypes in yeast.

Experiments in model organisms report abundant genetic interactions underlying biologically important traits, whereas quantitative genetics theory predicts, and data support, the notion that most genetic variance in populations is additive. Here we describe networks of capacitating genetic interactions that contribute to quantitative trait variation in a large yeast intercross population. The additive variance explained by individual loci in a network is highly dependent on the allele frequencies of the interacting loci. Modeling of phenotypes for multilocus genotype classes in the epistatic networks is often improved by accounting for the interactions. We discuss the implications of these results for attempts to dissect genetic architectures and to predict individual phenotypes and long-term responses to selection