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Fly genetics in the 1900s succeeded in deciphering the logic of disc development. Its vaunted offspring – the field of fly genomics – is faster and sexier but no more powerful in its ability to solve the remaining riddles of circuitry and control. Curt Stern warned us about this irony in his essay, “The journey, not the goal”:
One of the fundamental aspects of science is its lack of purpose. … Science, during the last one hundred or more years, has been in the dangerous position of a successful poet who started by composing songs of joy and sorrow to lighten the burden of his own soul only to find that they became best-sellers. … Science has become a profession. … The later comers [have] forgotten the beginnings of the highway. Dreamy followers of crooked paths [were] their predecessors. … We should encourage anew the roaming after knowledge for the sake of the joyful adventure.
Industrialization and commercialization notwithstanding, the Fly World still offers many mysteries for aimless explorers with curiosity alone to fill their sails.
Before launching the field of fly genetics, Thomas Hunt Morgan's passion was embryology. In the preface to his 1934 book, Embryology and Genetics, Tom waxed lyrical about the promise of developmental genetics as a burgeoning hybrid field:
Since 1900, when the discovery of Mendel's work became known, one of the most amazing developments in the whole history of biology has taken place. […]
In parentheses after each gene name are the salivary gland map location and the origin of the name. The PHENOTYPES section only lists bristle-related phenotypes (see Fig. 2.8). The PROTEIN section presents available data on function, length, subcellular location, domains, and binding partners. For further information, see FlyBase and The Interactive Fly.
Abbreviations: CS (chemosensory), DS (downstream in causation; “+” activated or “–” inhibited by US gene), GOF (gain of function), LOF (partial loss of function), MS (mechanosensory), US (upstream). Evidence for the hierarchical order of genes in a pathway (US or DS) is given from a DS perspective only. Protein domains are defined in Appendix 1. Numbers of repeats (e.g., “6x”) are in parentheses. Other genes whose embryonic mutant phenotypes suggest that they may belong to this group are BarH1 and BarH2. Certain sensilla campaniformia on the wing are transformed to bristles by ash2 (a member of the Trithorax Group of regulators; cf. Ch. 8).
absent solo-MD neurons and olfactory sensilla (amos, 36F; “MD” stands for multiple dendritic). Pathway: DS(+) of lozenge; interacts positively (dosedependent) with daughterless. PHENOTYPES: Null: unknown. LOF: fewer sensilla basiconica and trichodea on the antenna. GOF: extra sensilla basiconica, trichodea, and coeloconica on the antenna, ectopic olfactory sensilla elsewhere, and conversions of bristles into olfactory sensilla. PROTEIN: Function: transcription factor (198 a.a.). Location: unknown (presumably nuclear). Domains: bHLH (C-terminal).
The progeny of Drosophila females doubly-mated to males from the same and a closely related species are mostly sired by conspecific males. We examined the genetic basis for conspecific mating preference and sperm precedence by using 186 Drosophila lines in which random chromosomal fragments of D. sechellia were introgressed into D. simulans. Sperm competition was measured for each of these lines by crossing ebony D. simulans female with ebony D. simulans males followed by wild-type males from the introgressed lines. Variation in sperm competition (proportion of progeny sired by the second male), mating discrimination (proportion of introgressed males that failed to remate), and male fecundity (proportion of progeny sired by introgressed males) were scored. The introgressed lines exhibited highly significant heterogeneity in the three phenotypes scored, motivating an analysis to locate quantitative trait loci (QTLs) responsible for the differences. Applying composite interval mapping, we found eight QTLs that explain a significant level of variation among introgressed lines in the phenotypes scored. Cytological position overlapped among some QTLs suggesting possible pleiotropic effects. Analysis of the joint effects of simulans/sechellia genetic composition at different QTLs and markers suggests that complex interactions among alleles are partially responsible for interspecific differences in sexual traits.
Most current linkage analyses assume identical fractions of meiotic recombination between homologous marker loci of the two sexes. This assumption is not realistic, because considerable sex-related differences have been observed in recombination fraction. In this paper, a general EM-based algorithm is presented to estimate sex-specific recombination fractions for a mixed set of molecular markers segregating differently in a full-sib family derived from two heterozygous parents. The asymptotic variances of the estimates of linkage specifically for each of the parents are evaluated using a numerical analysis based on information functions. This approach will have important implications for precise gene mapping based on sex-specific linkage maps.
Previous studies have noted that the estimated positions of a large proportion of mapped quantitative trait loci (QTLs) coincide with marker locations and have suggested that this indicates a bias in the mapping methodology. In this study we predict the expected proportion of QTLs with positions estimated to be at the location of a marker and further examine the problem using simulated data. The results show that the higher proportion of putative QTLs estimated to be at marker positions compared with non-marker positions is an expected consequence of the estimation methods. The study initially focused on a single interval with no QTLs and was extended to include multiple intervals and QTLs of large effect. Further, the study demonstrated that the larger proportion of estimated QTL positions at the location of markers was not unique to linear regression mapping. Maximum likelihood produced similar results, although the accumulation of positional estimates at outermost markers was reduced when regions outside the linkage group were also considered. The bias towards marker positions is greatest under the null hypothesis of no QTLs or when QTL effects are small. This study discusses the impact the findings could have on the calculation of thresholds and confidence intervals produced by bootstrap methods.
When 41 populations from Africa (south of the Sahara) and Indian Ocean islands were analysed for their chromosomal inversion polymorphism, 34 rearrangements were found, including the four common cosmopolitans (In(2L)t, In(2R)NS, In(3L)P and In(3R)P), four rare cosmopolitans (In(2L)NS, In(3R)C, In(3R)Mo and In(3R)K) and six African polymorphic (‘recurrent’) endemics. Mean inversion frequencies per major autosome arm were positively and, generally, highly correlated to each other. There was no altitudinal nor latitudinal cline of inversion frequency, except for one African polymorphic endemic. Significant longitudinal clines were detected for In(2L)t, In(3L)P and In(3R)K; in all cases, inversion frequencies decreased eastward. Principal components analysis and ANOVA made it possible to distinguish three groups of populations. A high level of polymorphism was found in populations from west tropical Africa. The other low altitude populations from the mainland were moderately polymorphic, whereas the lowest levels of polymorphism were those of high altitude populations and of Indian Ocean islands. Moreover, some regional and local differentiation was also found. The frequency of unique autosomal inversions was not different from those found in Asia, Australia and America, but was significantly higher than that in Europe and North Africa. A West–East differentiation was also observed for the African polymorphic endemics. The present geographic pattern suggests a long, patchy evolution with restricted gene flow, followed by the modern period with numerous recent migrations linked to human transportation.
In Drosophila melanogaster, the main cuticular hydrocarbons (HCs) are some of the pheromones involved in mate discrimination. These are sexually dimorphic in both their occurrence and their effects. The production of predominant HCs has been measured in male and female progeny of 220 PGal4 lines mated with the feminising UAS-transformer transgenic strain. In 45 lines, XY flies were substantially or totally feminised for their HCs. Surprisingly, XX flies of 14 strains were partially masculinised. Several of the PGal4 enhancer-trap variants screened here seem to interact with sex determination mechanisms involved in the control of sexually dimorphic characters. We also found a good relationship between the degree of HC transformation and GAL4 expression in oenocytes. The fat body was also involved in the switch of sexually dimorphic cuticular hydrocarbons but its effect was different between the sexes.
Emperical evidence for intraclonal genetic variation is described here for clonal systems using a variety of molecular techniques and implicating a diversity of mechanisms. However, clonal systems are still generally perceived as having strict genetic fidelity. As concepts of genetic variability move from primary sequence data to include epigenetic and structural influences on genetic expression, the ability to detect changes in the genome at short intervals allows precedence to be given to inherent biological variation that is often analytically ignored. Therefore, the advent of powerful molecular techniques, like genome mapping, mean that our concepts of genetic fidelity within eukaryotic clones and the whole philosophy of the ‘clone’ needs to be re-evaluated and re-defined to replace old unproven dogma in this aspect of science.
Here, we introduce the idea of probabilities of line origins for alleles in general pedigrees as found in crosses between outbred lines. We also present software for calculating these probabilities. The proposed algorithm is based on the linear regression method of Haley, Knott and Elsen (1994) combined with the Markov chain Monte Carlo (MCMC) method for estimating quantitative trait locus coefficients used as regressors. We compared the relative precision of our method and the original method as proposed by Haley et al. (1994). The scenarios studied varied in the allelic distribution of marker alleles in parental lines and in the frequency of missing marker genotypes. We found that the MCMC method achieves a higher accuracy in all scenarios considered. The benefits of using MCMC approximation are substantial if the frequency of missing marker data is high or the number of marker alleles is low and the allelic frequency distribution is similar in both parental lines.
Chromatin integrity is maintained throughout the cell cycle through repair mechanisms and intrinsically by the ordered packaging of DNA in association with histone proteins; however, aberrant rearrangements within and between chromosomes do occur. The role of the nuclear matrix protein topoisomerase II (TopoII) in generating chromosome breakpoints has been a focus of recent investigations. TopoII preferentially binds in vitro to scaffold-associated regions (SARs) and is involved in many DNA processing activities that require chromosome untangling. SARs, biochemically defined DNA elements rich in A+T, have been proposed to serve as structural boundaries for chromatin loops and to delineate functional domains. In our investigation of gene compartmentalization in a eukaryotic genome, SAR-associated nucleotide motifs from Drosophila were mapped in the regions of three histone gene clusters in an in silico analysis of the genome of Caenorhabditis elegans. Sites with similarity to the 15 bp consensus for TopoII cleavage were found predominantly in A+T enriched intergenic regions. Reiteration of sites matching the TopoII core consensus led to the identification of a novel core histone gene on chromosome IV and provided evidence for duplication and inversion in each of the three histone gene clusters. Breakpoint analysis of DNA flanking reiterated regions revealed potential sites for TopoII cleavage and a base composition phenomenon suggestive of a trigger for inversion events.
Resistance to organophosphorus insecticides (OP) in Culex pipiens mosquitoes represents a convenient model for investigating the fitness cost of resistance genes and its origin, since both the environmental changes in nature and the adaptive genes are clearly identified. Two loci are involved in this resistance – the super-locus Ester and the locus Ace.1 – each displaying several resistance alleles. Population surveys have shown differences in fitness cost between these resistance genes and even between resistance alleles of the same locus. In order to better understand this fitness cost and its variability, the effects of these resistance genes on several fitness-related traits are being studied. Here, through competition experiments between two males for the access to one female, we analysed the effect on paternity success associated with three resistance alleles – Ester4, Ester1 and Ace.1R – relative to susceptible males and relative to one another. The eventual effect of female genotype on male mating success was also studied by using susceptible and resistant females. The strains used in this experiment had the same genetic background. Susceptible males had a mating advantage when competing with any of the resistant males, suggesting a substantial cost of resistance genes to this trait. When competing against susceptible males, the paternity success did not vary among resistant males, whatever the genotype of the female. When competing against other resistant males, no difference in paternity success was apparent, except when the female was Ester1.
Since our objective in conservation genetics is to preserve species as dynamic entities, capable of evolving to adapt with environmental change, it is essential to understand the natural forces determining evolutionary change. Such information is indispensable if we are to understand how to genetically manage threatened and endangered populations. Since evolution at its most basic level is a change in the genetic composition of a population, it only occurs when there is genetic diversity. Consequently, we need to appreciate how genetic diversity arises, how it is lost, and what forms of genetic diversity exist.
Extent of genetic diversity
Chapter 3 introduces methods for measuring genetic diversity for DNA, proteins, deleterious alleles and quantitative characters, and documents levels of genetic diversity for them. Most large populations of animals and plants contain extensive genetic diversity. However, levels of genetic diversity are often reduced in small populations, island populations and endangered species.
Genetic constitution of populations
To evaluate changes in genetic diversity, we must have means for quantifying it. Chapter 4 covers the estimation of allele (gene) frequencies and heterozygosity that are used to describe diversity at single loci. Chapter 5 describes the measures used to characterize genetic diversity for quantitative characters, especially the concept of heritability. Quantitative characters are centrally involved in the major areas of conservation concern, evolutionary potential, the deleterious effects of inbreeding and the deleterious effects that sometimes occur when different populations are mixed.