Incipient speciation by sexual isolation in Drosophila: Concurrent evolution at multiple loci

Drosophila melanogaster from Zimbabwe and nearby regions shows strong but asymmetric sexual isolation from its cosmopolitan counterparts. By creating stable chromosome-substitution lines, earlier studies were able to show that the two major autosomes have very large effects on both male mating success and female mating preference. In this study, we genetically dissect this sexual isolation by recombination analysis between a whole-chromosome substitution line (which carries a Zimbabwe-derived third chromosome) and a strain with seven visible markers on that chromosome. Four loci are responsible for male mating success and three others are found to control female mating preference. Because male and female traits are not closely linked, their strong association among isofemale lines is most likely a reflection of sexual selection in nature. The results suggest that a large number of behavioral loci may evolve concurrently in the incipient stage of speciation before other aspects of reproductive isolation (such as hybrid sterility) have become evident. The results shed light on the population genetic processes underlying the formation of nascent species, as well as modes of speciation.

Estimating Photosynthesis and Concurrent Export Rates in C3 and C4 Species at Ambient and Elevated CO21 2

The ability of 21 C3 and C4 monocot and dicot species to rapidly export newly fixed C in the light at both ambient and enriched CO2 levels was compared. Photosynthesis and concurrent export rates were estimated during isotopic equilibrium of the transport sugars using a steady-state 14CO2-labeling procedure. At ambient CO2 photosynthesis and export rates for C3 species were 5 to 15 and 1 to 10 μmol C m−2 s−1, respectively, and 20 to 30 and 15 to 22 μmol C m−2 s−1, respectively, for C4 species. A linear regression plot of export on photosynthesis rate of all species had a correlation coefficient of 0.87. When concurrent export was expressed as a percentage of photosynthesis, several C3 dicots that produced transport sugars other than Suc had high efflux rates relative to photosynthesis, comparable to those of C4 species. At high CO2 photosynthetic and export rates were only slightly altered in C4 species, and photosynthesis increased but export rates did not in all C3 species. The C3 species that had high efflux rates relative to photosynthesis at ambient CO2 exported at rates comparable to those of C4 species on both an absolute basis and as a percentage of photosynthesis. At ambient CO2 there were strong linear relationships between photosynthesis, sugar synthesis, and concurrent export. However, at high CO2 the relationships between photosynthesis and export rate and between sugar synthesis and export rate were not as strong because sugars and starch were accumulated.

Structure-activity relationships derived by machine learning: the use of atoms and their bond connectivities to predict mutagenicity by inductive logic programming.

We present a general approach to forming structure-activity relationships (SARs). This approach is based on representing chemical structure by atoms and their bond connectivities in combination with the inductive logic programming (ILP) algorithm PROGOL. Existing SAR methods describe chemical structure by using attributes which are general properties of an object. It is not possible to map chemical structure directly to attribute-based descriptions, as such descriptions have no internal organization. A more natural and general way to describe chemical structure is to use a relational description, where the internal construction of the description maps that of the object described. Our atom and bond connectivities representation is a relational description. ILP algorithms can form SARs with relational descriptions. We have tested the relational approach by investigating the SARs of 230 aromatic and heteroaromatic nitro compounds. These compounds had been split previously into two subsets, 188 compounds that were amenable to regression and 42 that were not. For the 188 compounds, a SAR was found that was as accurate as the best statistical or neural network-generated SARs. The PROGOL SAR has the advantages that it did not need the use of any indicator variables handcrafted by an expert, and the generated rules were easily comprehensible. For the 42 compounds, PROGOL formed a SAR that was significantly (P < 0.025) more accurate than linear regression, quadratic regression, and back-propagation. This SAR is based on an automatically generated structural alert for mutagenicity.