Serotonin and Go modulate functional states of neurons and muscles controlling C. elegans egg-laying behavior

From nematodes to humans, animals employ neuromodulators like serotonin to regulate behavioral patterns and states. In the nematode C. elegans, serotonin has been shown to act in a modulatory fashion to increase the rate and alter the temporal pattern of egg laying. Though many candidate effectors and regulators of serotonin have been identified in genetic studies, their effects on specific neurons and muscles in the egg-laying circuitry have been difficult to determine. Using the genetically encoded Ca(2+) indicator cameleon, we found that serotonin acts directly on the vulval muscles to increase the frequency of Ca(2+) transients. In contrast, we found that the spontaneous activity of the egg-laying motorneurons was silenced by serotonin. Mutations in G protein alpha subunit genes altered the responses of both vulval muscles and egg-laying neurons to serotonin; specifically, mutations in the G(q)alpha homolog egl-30 blocked serotonin stimulation of vulval muscle Ca(2+) transients, while mutations in the G(o)alpha homolog goa-1 prevented the silencing of motorneuron activity by serotonin. These data indicate that serotonin stimulates egg laying by directly modulating the functional state of the vulval muscles. In addition, serotonin inhibits the activity of the motorneurons that release it, providing a feedback regulatory effect that may contribute to serotonin adaptation.     

Fibroblast growth factor receptor 2-IIIb acts upstream of Shh and Fgf4 and is required for limb bud maintenance but not for the induction of Fgf8, Fgf10, Msx1, or Bmp4

Mice deficient for FgfR2-IIIb were generated by placing translational stop codons and an IRES-LacZ cassette into exon IIIb of FgfR2. Expression of the alternatively spliced receptor isoform, FgfR2-IIIc, was not affected in mice deficient for the IIIb isoform. FgfR2-IIIb(-/-) (lac)(Z) mice survive to term but show dysgenesis of the kidneys, salivary glands, adrenal glands, thymus, pancreas, skin, otic vesicles, glandular stomach, and hair follicles, and agenesis of the lungs, anterior pituitary, thyroid, teeth, and limbs. Detailed analysis of limb development revealed an essential role for FgfR2-IIIb in maintaining the AER. Its absence did not prevent expression of Fgf8, Fgf10, Bmp4, and Msx1, but did prevent induction of Shh and Fgf4, indicating that they are downstream targets of FgfR2-IIIb activation. In the absence of FgfR2-IIIb, extensive apoptosis of the limb bud ectoderm and mesenchyme occurs between E10 and E10.5, providing evidence that Fgfs act primarily as survival factors. We propose that FgfR2-IIIb is not required for limb bud initiation, but is essential for its maintenance and growth.     

Models of sexual selection on a quantitative genetic trait when preference is acquired by sexual imprinting

The evolution of a quantitative genetic trait under stabilizing viability selection and sexual selection is modeled for a polygynous species in which female mating preferences are acquired by sexual imprinting on the parents and by exposure to the surviving population at large. Stabilizing viability selection acts equally on both sexes in the case of a sexually monomorphic trait and on males only in the case of a dimorphic trait. A genetically fixed sensory or perceptual bias defines the origin of the scale on which the trait is measured, and the possibility is incorporated that female preferences may deviate asymmetrically from the familiar-either toward or away from this origin. When viability selection is strong relative to sexual selection, the models predict that the mean trait value will evolve to the viability optimum. With intermediate ratios of the strength of viability to sexual selection, a stable equilibrium can occur on either side of this viability optimum, depending on the direction of asymmetry in female preferences. When viability selection is relatively weak and certain other conditions are also satisfied, runaway selection is predicted.     

Mapping of a region within the N terminus of Jak1 involved in cytokine receptor interaction

Janus kinase 1 (Jak1) is a cytoplasmic tyrosine kinase that noncovalently associates with a variety of cytokine receptors. Here we show that the in vitro translated N-terminal domains of Jak1 are sufficient for binding to a biotinylated peptide comprising the membrane-proximal 73 amino acids of gp130, the signal-transducing receptor chain of interleukin-6-type cytokines. By the fold recognition approach amino acid residues 36-112 of Jak1 were predicted to adopt a beta-grasp fold, and a structural model was built using ubiquitin as a template. Substitution of Tyr(107) to alanine, a residue conserved among Jaks and involved in hydrophobic core interactions of the proposed beta-grasp domain, abrogated binding of full-length Jak1 to gp130 in COS-7 transfectants. By further mutagenesis we identified the loop 4 region of the Jak1 beta-grasp domain as essential for gp130 association and gp130-mediated signal transduction. In Jak1-deficient U4C cells reconstituted with the loop 4 Jak1 mutants L80A/Y81A and Delta(Tyr(81)-Ser(84)), the interferon-gamma, interferon-alpha, and interleukin-6 responses were similarly impaired. Thus, loop 4 of the beta-grasp domain plays a role in the association of Jak1 with both class I and II cytokine receptors. Taken together the structural model and the mutagenesis data provide further insight into the interaction of Janus kinases with cytokine receptors.     

Estimating genotypes with independently sampled descent graphs

A method for estimating genotypic and identity-by-descent probabilities in complex pedigrees is described. The method consists of an algorithm for drawing independent genotype samples which are consistent with the pedigree and observed genotype. The probability distribution function for samples obtained using the algorithm can be evaluated up to a normalizing constant, and combined with the likelihood to produce a weight for each sample. Importance sampling is then used to estimate genotypic and identity-by-descent probabilities. On small but complex pedigrees, the genotypic probability estimates are demonstrated to be empirically unbiased. On large complex pedigrees, while the algorithm for obtaining genotype samples is feasible, importance sampling may require an infeasible number of samples to estimate genotypic probabilities with accuracy.     

Statistical design and the analysis of gene expression microarray data

Gene expression microarrays are an innovative technology with enormous promise to help geneticists explore and understand the genome. Although the potential of this technology has been clearly demonstrated, many important and interesting statistical questions persist. We relate certain features of microarrays to other kinds of experimental data and argue that classical statistical techniques are appropriate and useful. We advocate greater attention to experimental design issues and a more prominent role for the ideas of statistical inference in microarray studies.     

What is altruism?

Altruism is generally understood to be behavior that benefits others at a personal cost to the behaving individual. However, within evolutionary biology, different authors have interpreted the concept of altruism differently, leading to dissimilar predictions about the evolution of altruistic behavior. Generally, different interpretations diverge on which party receives the benefit from altruism and on how the cost of altruism is assessed. Using a simple trait-group framework, we delineate the assumptions underlying different interpretations and show how they relate to one another. We feel that a thorough examination of the connections between interpretations not only reveals why different authors have arrived at disparate conclusions about altruism, but also illuminates the conditions that are likely to favor the evolution of altruism.