Sex chromosome translocation and speciation : a Drosophila genetic model

Although exceptions may be readily identified, two generalizations concerning genetic differences among species may be drawn from the available allozyme and chromosome data. First, structural gene differences among species vary widely. In many cases, species pairs do not differ more than intraspecific populations. This suggests that either very few or no gene substitutions are required to produce barriers to reproduction (Avise 1976). Second, chromosome form and/or number differs among even closely related species (White 1963; 1978; Fredga 1977; Wright 1970). Many of the observed chromosomal differences involve translocational rearrangements; these produce severe fitness depression in heterozygotes and were, thus, long considered unlikely candidates for the fixation required of genetic changes leading to speciation (Wright 1977). Nonetheless, the fact that species differences are frequently translocational argues convincingly for their fixation despite prejudices to the contrary. Haldane's rule states that in the F of interspecific crosses, the heterogametic sex is absent or sterile in the preponderance of cases (Haldane 1932). This rule definitely applies in the genus Dr°sophila (Ehrman 1962). Sex chromosome translocations do not impose a fitness depression as severe as that imposed by autosomal translocations, and X-Y translocations may account for Haldane's rule (Haldane 1932). Consequently a study of the fit ness parameters of an X·yL and a yS chromosome in Drosophila melanogaster populations was initiated by Tracey (1972). Preliminary results suggested that x.yL//YSmales enjoyed a mating advantage with X·yL//X·yL females, that this advantage was frequency dependent, that the translocation produced sexual isolation and that interactions between the yL, yS and a yellow marker contributed to the observed isolation (Tracey and Espinet 1976; Espinet and Tracey 1976). Encouraged by the results of these prelimimary studies, further experiments were performed to clarify the genetic nature of the observed sexual isolation, S the reality of the y frequency dependent fitness .and the behavioural changes, if any, produced by the translocation. The results of this work are reported herein. Although the marker genes used in earlier studies, sparkling poliert an d yellow have both been found to affect activity,but only yellow effects asymmetric sexual isolation. In addition yellow effects isolation through an interaction with the T(X-y) chromosomes, yS also effects isolation, and translocational strains are isolated from those of normal karyotype in the absence of marker gene differences. When yS chromosomes are in competition with y chromosomes on an X.yL background, yS males are at a distinct advantage only when their frequency is less than 97%. The sex chromosome translocation alters the normal courtship pattern by the incorporation of circling between vibration and licking in the male repertoire. Finally a model of speciation base on the fixation of this sex chromosome translocation in a geographically isolated gene pool is proposed.

Investigating Player Salaries and Performance in the National Hockey League

This thesis examines salary structure types (hierarchical or compressed) as predictors of team performance in the National Hockey League (NHL). Additionally, an analysis of goalie statistics is completed in order to determine what, if any, performance measures relate to salary. Data in this research were collected from the 2005-06 season up to the 2010-11 season. Salary inequality/equality (Gini coefficient) was used in a regression analysis to determine if it was an effective predictor of team performance (n = 178) (winning percentage). The results indicated that a hierarchical salary structure increased team performance, although the amount of variability explained was very small. Another regression analysis was completed to determine if any goalie performance measures (n = 245) were effective predictors of individual salary. A regression analysis was employed and indicated that goalie performance measures predicted 19.8% of variance to salary. The only statistical significant variable was games played.

The genetics of glucosamine resistance in yeast /

Thesis (M. Sc.) - Brock University, 1975.

The genetics of glucosamine in yeast : cytoplasmic determinants conferring resistance

Two cytoplasmic, glucosamine resistant mutants of Saccharomyces cerevisiae, GR6 and GR10, were examined to determine whether or not the lesions involved were located on mitochondrial DNA. Detailed investigation of crosses of GR6 and GR10 or their derivatives to strains bearing known mitochondrial markers demonstrated that: 1. the frequency of glucos~~ine resistance in diploids was independent of factors influencing mitochondrial marker output. 2. upon tetrad analysis a variety of tetrad ratios was observed for glucosamine resistance whereas mitochondrial markers segregated 4:0 or 0:4 (resistant:sensitive). 3. glucosamine resistance and mitochondrial markers segregated differentially with time. 4. glucosamine resistance persisted following treatment of a GRIO derivative with ethidium bromide at concentrations high enough to eliminate all mitochondrial DNA. 5. haploid spore clones displayed two degrees of glucosamine resistance, weak and strong, while growth due to mitochondrial mutations was generally thick and confluent. 6. a number of glucosamine resistant diploids and haploids, which also possessed a mithchondrial resistance mutation, were unable to grow on medium containing both glucosamine and the particular drug involved. 3 These observations 1~ 6 provided strong evidence that the cytoplasmic glucosamine resistant mutations present in GR6 and GRiO were not situated on mitochondrial DNA. Comparison of the glucosamine resistance mutations to some other known cytoplasmic determinants revealed that: 7. glucosamine resistance and the expression of the killer phenotype were separate phenomena. 8. unlike yeast carrying resistance conferring episomes GR6 and GR10 were not resistant to venturicidin or oligomycin and the GR factor exhibited genetic behaviour different from that of the episomal determinants. These results 7--+8 suggested that glucosamine resistance was not associated with the killer determinant nor with alleged yeast episomes. It is therefore proposed that a yeast plasmid(s), previously undescribed, is responsible for glucosamine resistance. The evidence to date is compatible with the hypothesis that GR6 and GR10 carry allelic mutations of the same plasmid which is tentatively designated (GGM).

Automatic Inference of Graph Models for Complex Networks with Genetic Programming

Complex networks can arise naturally and spontaneously from all things that act as a part of a larger system. From the patterns of socialization between people to the way biological systems organize themselves, complex networks are ubiquitous, but are currently poorly understood. A number of algorithms, designed by humans, have been proposed to describe the organizational behaviour of real-world networks. Consequently, breakthroughs in genetics, medicine, epidemiology, neuroscience, telecommunications and the social sciences have recently resulted. The algorithms, called graph models, represent significant human effort. Deriving accurate graph models is non-trivial, time-intensive, challenging and may only yield useful results for very specific phenomena. An automated approach can greatly reduce the human effort required and if effective, provide a valuable tool for understanding the large decentralized systems of interrelated things around us. To the best of the author's knowledge this thesis proposes the first method for the automatic inference of graph models for complex networks with varied properties, with and without community structure. Furthermore, to the best of the author's knowledge it is the first application of genetic programming for the automatic inference of graph models. The system and methodology was tested against benchmark data, and was shown to be capable of reproducing close approximations to well-known algorithms designed by humans. Furthermore, when used to infer a model for real biological data the resulting model was more representative than models currently used in the literature.