Literarische Berichte

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Genome analysis of African swine fever virus isolated in Italy in 1983

An African Swine Fever virus (ASFV) isolated in an 1983 outbreak of the disease in Piemonte, Italy, was related by restriction endonuclease analysis of the viral genome to ASFV strains isolated in the Dominican Republic (1978), Haiti (1981) and Cameroon (1982).     

Population Structure of Phytophthora cinnamomi in South Africa

ABSTRACT Phytophthora cinnamomi isolates collected from 1977 to 1986 and 1991 to 1993 in two regions in South Africa were analyzed using isozymes. A total of 135 isolates was analyzed for 14 enzymes representing 20 putative loci, of which four were polymorphic. This led to the identification of nine different multilocus isozyme genotypes. Both mating types of P. cinnamomi occurred commonly in the Cape region, whereas, predominantly, the A2 mating type occurred in the Mpumalanga region of South Africa. A2 mating type isolates could be resolved into seven multilocus isozyme genotypes, compared with only two multilocus isozyme genotypes for the A1 mating type isolates. Low levels of gene (0.115) and genotypic (2.4%) diversity and a low number of alleles per locus (1.43) were observed for the South African P. cinnamomi population. The genetic distance between the Cape and Mpumalanga P. cinnamomi populations was relatively low (D(m) = 0.165), and no specific pattern in regional distribution of multilocus isozyme genotypes could be observed. The genetic distance between the "old" (isolated between 1977 and 1986) and "new" (isolated between 1991 and 1993) P. cinnamomi populations from the Cape was low (D(m) = 0.164), indicating a stable population over time. Three of the nine multilocus isozyme genotypes were specific to the "old" population, and only one multilocus isozyme genotype was specific to the "new" population. Significant differences in allele frequencies, a high genetic distance (D(m) = 0.581) between the Cape A1 and A2 mating type isolates, significant deviations from Hardy-Weinberg equilibrium, a low overall level of heterozygosity, and a high fixation index (0.71) all indicate that sexual reproduction occurs rarely, if at all, in the South African P. cinnamomi population.     

Inheritance of virulence in Fusarium circinatum,the cause of pitch canker in pines

Wildtype strains of Fusarium circinatum, the causal agent of pitch canker, were crossed to obtain an F₁ generation. Progeny of this cross were tested for virulence by inoculating Pinus radiata seedlings, and were found to induce a wide range of lesion lengths. Two strains from the F₁ generation that induced long lesions (= high virulence) were used as parents to produce an F₂ generation, followed by a second round of selection for high virulence to obtain an F₃ generation. Mean lesion lengths were not significantly different between the three generations (P ≥ 0.196). A parallel set of crosses was performed to select for low virulence by using progeny in the F₁ and F₂ generations that induced short lesions as parents for F₂ and F₃ generations, respectively. In this case, both rounds of selection resulted in a significant reduction in mean lesion length, from 33.8 ± 0.8 mm in the F₁ generation, to 19.7 ± 0.7 and 12.9 ± 0.7 mm in the F₂ and F₃ generations, respectively. Thus it is apparent that F. circinatum retains the genetic capacity for avirulence to pines, which could reflect a lack of strong selection for virulence in nature. Progeny of a cross between high and low virulence parents manifested nearly continuous variation in lesion lengths, consistent with virulence being a quantitatively inherited trait. Based on this cross, broad‐sense heritability (H²) was determined to be 0.74, which suggests that virulence is under strong genetic control.     

A linear functional relationship model for circular data with an application to the assessment of ocean wave measurements

This article suggests a linear functional relationship model for comparing two sets of circular data subject to unobservable errors. Unlike the corresponding and relatively well-studied model for linear data, maximum likelihood estimation for this model is very complicated and no explicit solutions are possible. Using a numerical approximation, we are able to solve the likelihood equations approximately, and to obtain good approximations to the likelihood estimates of the parameters. The quality of our estimates and the feasibility of the estimation method are illustrated via simulation. By establishing a parallel with the model for linear data, we are able to explain the various problems occurring in the process of estimation and to substantiate our numerical results. The interest in the model arose in connection with the study of ocean wave data; an application to such data is also given.