Benign epithelial ovarian tumours - cancer precursors or markers for ovarian cancer risk?

The natural history of the development of epithelial ovarian cancer remains obscure and no effective screening test exists. In several human malignancies progression from benign to invasive tumour occurs, but this sequence has not been established for epithelial ovarian cancer. We have reviewed epidemiological, histopathological and molecular studies of benign epithelial ovarian tumours to assess the evidence for and against such a progression in ovarian cancer. These data suggest that a diagnosis of a benign ovarian cyst or tumour is associated with an increased risk of ovarian cancer later in life. Current evidence also suggests that benign serous tumours can progress to low-grade serous cancer and that benign mucinous tumours can progress to mucinous cancer. The more common high-grade serous ovarian cancers are likely to arise de novo.

Legume nodulation: successful symbiosis through short- and long-distance signalling

Nodulation in legumes provides a major conduit of available nitrogen into the biosphere. The development of nitrogen-fixing nodules results from a symbiotic interaction between soil bacteria, commonly called rhizobia, and legume plants. Molecular genetic analysis in both model and agriculturally important legume species has resulted in the identification of a variety of genes that are essential for the establishment, maintenance and regulation of this symbiosis. Autoregulation of nodulation (AON) is a major internal process by which nodule numbers are controlled through prior nodulation events. Characterisation of AON-deficient mutants has revealed a novel systemic signal transduction pathway controlled by a receptor-like kinase. This review reports our present level of understanding on the short- and long-distance signalling networks controlling early nodulation events and AON.

Power of the joint segregation analysis method for testing mixed major-gene and polygene inheritance models of quantitative traits

Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.

Genetic linkage analysis of the lesser grain borer Rhyzopertha dominica identifies two loci that confer high-level resistance to the fumigant phosphine

High levels of inheritable resistance to phosphine in Rhyzopertha dominica have recently, been detected in Australia and hi art effort to isolate the genes responsible For resistance we have used random amplified DNA fingerprinting (RAF) to produce a genetic linkage map of R. dominica. The map consists of 94 dominant DNA markers with art average distance between markers of 4.6 cM and defines nine linkage groups with a total recombination distance of 390.1 cM. We have identified two loci that are responsible for high-level resistance. One provides similar to50x resistance to phosphine while the other provides 12.5x resistance and in combination, the two genes act synergistically to provide a resistance level 250 x greater than that of fully susceptible beetles. The haploid genome size has been determined to be 4.76 x 10(8) bp, resulting in an average physical distance of 1.2 Mbp per map unit. No recombination has been observed between either of the two resistance loci and their adjacent DNA markers in a population of 44 fully resistant F-5 individuals, which indicates that the genes are likely to reside within 0.91 cM (1.1 Mbp) of the DNA markers.