Fly wing evolution explained by a neutral model with mutational pleiotropy

To what extent the speed of mutational production of phenotypic variation determines the rate of long‐term phenotypic evolution is a central question. Houle et al. recently addressed this question by studying the mutational variances, additive genetic variances, and macroevolution of locations of vein intersections on fly wings, reporting very slow phenotypic evolution relative to the rates of mutational input, high phylogenetic signals, and a strong, linear relationship between the mutational variance of a trait and its rate of evolution. Houle et al. found no existing model of phenotypic evolution to be consistent with all these observations, and proposed the improbable scenario of equal influence of mutational pleiotropy on all traits. Here, we demonstrate that the purported linear relationship between mutational variance and evolutionary divergence is artifactual. We further show that the data are explainable by a simple model in which the wing traits are effectively neutral at least within a range of phenotypic values but their evolutionary rates are differentially reduced because mutations affecting these traits are purged owing to their different pleiotropic effects on other traits that are under stabilizing selection. Thus, the evolutionary patterns of fly wing morphologies are explainable under the existing theoretical framework of phenotypic evolution.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/162712/3/evo14076.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162712/2/evo14076-sup-0001-SuppMat.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162712/1/evo14076_am.pd

Proto-Tethys magmatic evolution along northern Gondwana: Insights from Late Silurian–Middle Devonian A-type magmatism, East Kunlun Orogen, Northern Tibetan Plateau, China

The East Kunlun Orogen records the geological evolutions of the Neoproterozoic – Early Paleozoic Proto-Tethyan Ocean and Late Paleozoic–Mesozoic Paleo-Tethys Ocean along northern Gondwana. However, the late-stage evolution of the Proto-Tethyan Ocean and the configuration of peri-Gondwana microcontinents during the Silurian – Devonian is under debate. Here we report new geochronological and geochemical data of A-type granites from the western Wulonggou and the eastern Gouli areas in the East Kunlun Orogen to deepen our understanding of these problems. Zircon LA-ICP-MS UPb data reveal that the Danshuigou monzogranite and Shenshuitan syenogranite from the western Wulonggou area were emplaced simultaneously at 418 ± 3 Ma, while the Niantang syenogranite from the eastern Gouli area was emplaced at 403 ± 2 Ma. All these rocks display high-K calcic-alkalic to shoshonitic and metaluminous to slight peraluminous signatures, with relatively low CaO, Al2O3, MgO and Sr, and high FeOt/MgO, Ga/Al, Zr, and Nb, indicating their A-type affinity. Their moderate whole-rock εNd(t) (−5.3 to −0.6) and zircon εHf(t) (−6.3–6.4) are different from those of depleted mantle and old basement rocks, but similar to those of the Ordovician–Silurian granitoids in the East Kunlun Orogen. These chemical signatures, together with the anhydrous, low-pressure and high-temperature characteristics of the magmas, indicate that partial melting of the Ordovician–Silurian granitoids generated these A-type granites. Regionally, these A-type granites and previously reported A-type granites in the East Kunlun Orogen compose a Late Silurian – Middle Devonian A-type granite belt. This belt, together with the regionally coeval molasse formation and mafic-ultramafic rocks, indicate a post-collisional extensional regime for the East Kunlun Orogen during the Late Silurian – Middle Devonian. Given that extensive contemporaneous post-collision-related magmatic rocks have also been revealed in the neighboring West Kunlun, Altyn, Qilian and Qinling blocks/terranes, we contend that the Neoproterozoic – Early Paleozoic Proto-Tethyan Ocean that separated these blocks/terranes from Gondwana had closed by the Late Silurian – Middle Devonian, which]resulted in the re-welding of the above blocks/terranes to northern Gondwana or Gondwana-derived microcontinents

Effect of “Jian-Pi-Zhi-Dong Decoction” on Gamma-Aminobutyric Acid in a Mouse Model of Tourette Syndrome

The purpose of this study was to explore the positive effects of Jian-Pi-Zhi-Dong Decoction (JPZDD) on Tourette syndrome (TS) by investigating the expression of gamma-aminobutyric acid (GABA) and its type A receptor (GABAAR) in the striatum of a TS mice model. The model was induced by 3,3′-iminodipropionitrile (IDPN) treatment; then mice were divided into 4 groups (n=22, each); control and IDPN groups were gavaged with saline and the remaining 2 groups were gavaged with tiapride and JPZDD. We recorded the stereotypic behaviors of TS mice and measured the content of GABA in striatum by HPLC and GABAAR expression by immunohistochemistry and real-time PCR. Our results showed that JPZDD inhibited the abnormal behaviors of TS model mice and decreased GABA levels and GABAAR protein and mRNA expression in the striatum of TS model mice. In brief, the mechanism by which JPZDD alleviates TS symptoms may be associated with GABAAR expression downregulation in striatum which may regulate GABA metabolism

Detecting natural selection in trait-trait coevolution

Abstract No phenotypic trait evolves independently of all other traits, but the cause of trait-trait coevolution is poorly understood. While the coevolution could arise simply from pleiotropic mutations that simultaneously affect the traits concerned, it could also result from multivariate natural selection favoring certain trait relationships. To gain a general mechanistic understanding of trait-trait coevolution, we examine the evolution of 220 cell morphology traits across 16 natural strains of the yeast Saccharomyces cerevisiae and the evolution of 24 wing morphology traits across 110 fly species of the family Drosophilidae, along with the variations of these traits among gene deletion or mutation accumulation lines (a.k.a. mutants). For numerous trait pairs, the phenotypic correlation among evolutionary lineages differs significantly from that among mutants. Specifically, we find hundreds of cases where the evolutionary correlation between traits is strengthened or reversed relative to the mutational correlation, which, according to our population genetic simulation, is likely caused by multivariate selection. Furthermore, we detect selection for enhanced modularity of the yeast traits analyzed. Together, these results demonstrate that trait-trait coevolution is shaped by natural selection and suggest that the pleiotropic structure of mutation is not optimal. Because the morphological traits analyzed here are chosen largely because of their measurability and thereby are not expected to be biased with regard to natural selection, our conclusion is likely general

Abundances of S, Ga, Ge, Cd, In, Tl and 32 other major to trace elements in high-temperature (350–700 °C) magmatic-hydrothermal fluids

This study reports concentration data for Li, B, Na, Mg, Al, S, Cl, K, Ca, Mn, Fe, Cu, Zn, Ga, Ge, As, Br, Se, Rb, Sr, Nb, Mo, Ag, Cd, In, Sn, Sb, Te, Cs, Ba, Ce, Ta, W, Tl, Pb, Bi, Th and U in 124 high-temperature (350–700 °C) magmatic-hydrothermal fluids investigated from five barren, six sub-economically Mo- or Cu-mineralized, and five economically Sn-, W-, Cu, Mo- or REE-mineralized granodioritic to granitic intrusions, based on Laser-ablation ICP-MS analysis of 304 individual fluid inclusions hosted in quartz. Most of the analyzed fluid inclusions were large and well-preserved, and careful corrections for ablated host were made for Li, Al, S, Cl, Ge, Br and Sn, assuring high-quality data. The discussion in this contribution is focused on S, Ga, Ge, Cd, In and Tl, for which elements only few data have been available for high-temperature magmatic-hydrothermal fluids so far. Sulfur concentrations are mostly in the range of 0.1 to 2 wt%, but can reach up to 13 wt% in some hypersaline brines. Gallium, Ge, Cd, In and Tl concentrations are mostly within the range of 0.6–3 µg/g, 10–200 µg/g, 2–70 µg/g, 0.2–20 µg/g, and 2–80 µg/g, respectively. If normalized to the concentration of sodium (which has a similar effect as normalizing to a constant fluid salinity), the abundances of Ge, Cd and In show a distinct correlation with Zn, whereas Ga correlates with Ba, Tl correlates with Rb, and S correlates with Mg and Th. The observed correlations are in agreement with metal transport dominated by chloride complexes in the case of Cd and Tl, dominant hydroxy-complexes in the case of Ga and Ge, and with an incompatible behavior of In and Tl during magma differentiation