Using genetic markers for disease resistance to improve production under constant infection pressure

Animals will show reduced production when exposed to a constant infection pressure unless they are fully resistant, the size of the reduction depending on the degree of resistance and the severity of infection. In this article, the use of QTL for disease resistance for improving productivity under constant infection pressure is investigated using stochastic simulation. A previously published model was used with two thresholds for resistance: a threshold below which production is not possible and a threshold above which production is not affected by the infection. Between thresholds, observed production under constant infection is a multiplicative function of underlying potential production and level of resistance. Some simplifications of reality were adopted in the model, such as no genetic correlation between potential production and resistance, the absence of influence of lack of resistance on reproductive capacity, and the availability of phenotypes in both sexes. Marker-assisted selection was incorporated by assuming a proportion of the genetic variance to be explained by the QTL, which thus is defined as a continuous trait. Phenotypes were available for production, not for resistance. The infection pressure may vary across time. Results were compared to mass selection on production under constant as well as intermittent infection pressure, where the infection pressure varied between but not within years. Selection started in a population with a very poor level of resistance. Incorporation of QTL information is valuable (i.e., the increase in observed production relative to mass selection) when a large proportion of the additive genetic variance is explained by the QTL (50% genetic variance explained) and when the heritability for resistance is low (h2R = 0.1). Under constant infection pressure, incorporating QTL information does not increase selection responses in observed production when the QTL effect explains less than 25% of the genetic variance. Under intermittent selection pressure, the use of QTL information gives a slightly greater increase in observed production in early generations, relative to mass selection on observed production, but still only when the QTL effect is large or the heritability for resistance is low. The additional advantage of incorporating QTL information is that use of (preventive) medical treatment is possible, or animals may be evaluated in uninfected environments

Genetic control of resistance to gastro-intestinal parasites in crossbred cashmere-producing goats: responses to selection, genetic parameters and relationships with production traits

AbstractThis paper investigates the genetic control of the resistance of goats to nematode parasites, and relationships between resistance and production traits. The data set comprised faecal egg counts (FECs) measured on 830 naturally challenged (predominant species Teladorsagia circumcincta), crossbred cashmere-producing goats over 5 years (1993-1997) and production traits (fibre traits and live weight) on 3100 goats from the same population in Scotland, over 11 years (1987-1997). Egg counts comprised repeated measurements (4 to 11) taken at 12 to 18 months of age and production traits, i.e. live weight and fibre traits, were measured at approximately 5 months of age. The goats for which FECs were available were subdivided into a line selected for decreased FECs, using the geometric mean FEC across the measurement period and goats not selected on the basis of FECs, acting as controls. The selected line had significantly lower FECs, compared with the control, in 4 out of 5 years (back transformed average proportional difference of 0·23). The heritability of a single FEC measurement (after cubic root transformation) was 0·17 and the heritability of the mean FEC was 0·32. The heritabilities of the fibre traits were moderate to high with the majority in excess of 0·5. The heritability of live weight was 0·22. Genetic correlations between FECs and production traits were slightly positive but not significantly different from zero. Phenotypic and environmental correlations were very close to zero with the environmental correlations always being negative. It is concluded that selection for reduced FEC is possible for goats. Benefits of such selection will be seen when animals are kept for more than 1 year of productive life.</jats:p

How hosts control worms

No abstract available

Validation of Ultrahigh Dependability for Software-Based Systems

Modern society depends on computers for a number of critical tasks in which failure can have very high costs. As a consequence, high levels of dependability (reliability, safety, etc.) are required from such computers, including their software. Whenever a quantitative approach to risk is adopted, these requirements must be stated in quantitative terms, and a rigorous demonstration of their being attained is necessary. For software used in the most critical roles, such demonstrations are not usually supplied. The fact is that the dependability requirements often lie near the limit of the current state of the art, or beyond, in terms not only of the ability to satisfy them, but also, and more often, of the ability to demonstrate that they are satisfied in the individual operational products (validation). We discuss reasons why such demonstrations cannot usually be provided with the means available: reliability growth models, testing with stable reliability, structural dependability modelling, as well as more informal arguments based on good engineering practice. We state some rigorous arguments about the limits of what can be validated with each of such means. Combining evidence from these different sources would seem to raise the levels that can be validated; yet this improvement is not such as to solve the problem. It appears that engineering practice must take into account the fact that no solution exists, at present, for the validation of ultra-high dependability in systems relying on complex software