Bias, accuracy, and impact of indirect genetic effects in infectious diseases

Selection for improved host response to infectious disease offers a desirable alternative to chemical treatment but has proven difficult in practice, due to low heritability estimates of disease traits. Disease data from field studies is often binary, indicating whether an individual has become infected or not following exposure to an infectious disease. Numerous studies have shown that from this data one can infer genetic variation in individuals’ underlying susceptibility. In a previous study, we showed that with an indirect genetic effect (IGE) model it is possible to capture some genetic variation in infectivity, if present, as well as in susceptibility. Infectivity is the propensity of transmitting infection upon contact with a susceptible individual. It is an important factor determining the severity of an epidemic. However, there are severe shortcomings with the Standard IGE models as they do not accommodate the dynamic nature of disease data. Here we adjust the Standard IGE model to (1) make expression of infectivity dependent on the individuals’ disease status (Case Model) and (2) to include timing of infection (Case-ordered Model). The models are evaluated by comparing impact of selection, bias, and accuracy of each model using simulated binary disease data. These were generated for populations with known variation in susceptibility and infectivity thus allowing comparisons between estimated and true breeding values. Overall the Case Model provided better estimates for host genetic susceptibility and infectivity compared to the Standard Model in terms of bias, impact, and accuracy. Furthermore, these estimates were strongly influenced by epidemiological characteristics. However, surprisingly, the Case-Ordered model performed considerably worse than the Standard and the Case Models, pointing toward limitations in incorporating disease dynamics into conventional variance component estimation methodology and software used in animal breeding

Genetic parameters for social effects on survival in cannibalistic layers: Combining survival analysis and a linear animal model

<p>Abstract</p> <p>Background</p> <p>Mortality due to cannibalism in laying hens is a difficult trait to improve genetically, because censoring is high (animals still alive at the end of the testing period) and it may depend on both the individual itself and the behaviour of its group members, so-called associative effects (social interactions). To analyse survival data, survival analysis can be used. However, it is not possible to include associative effects in the current software for survival analysis. A solution could be to combine survival analysis and a linear animal model including associative effects. This paper presents a two-step approach (2STEP), combining survival analysis and a linear animal model including associative effects (LAM).</p> <p>Methods</p> <p>Data of three purebred White Leghorn layer lines from Institut de Sélection Animale B.V., a Hendrix Genetics company, were used in this study. For the statistical analysis, survival data on 16,780 hens kept in four-bird cages with intact beaks were used. Genetic parameters for direct and associative effects on survival time were estimated using 2STEP. Cross validation was used to compare 2STEP with LAM. LAM was applied directly to estimate genetic parameters for social effects on observed survival days.</p> <p>Results</p> <p>Using 2STEP, total heritable variance, including both direct and associative genetic effects, expressed as the proportion of phenotypic variance, ranged from 32% to 64%. These results were substantially larger than when using LAM. However, cross validation showed that 2STEP gave approximately the same survival curves and rank correlations as LAM. Furthermore, cross validation showed that selection based on both direct and associative genetic effects, using either 2STEP or LAM, gave the best prediction of survival time.</p> <p>Conclusion</p> <p>It can be concluded that 2STEP can be used to estimate genetic parameters for direct and associative effects on survival time in laying hens. Using 2STEP increased the heritable variance in survival time. Cross validation showed that social genetic effects contribute to a large difference in survival days between two extreme groups. Genetic selection targeting both direct and associative effects is expected to reduce mortality due to cannibalism in laying hens.</p

The ‘algebra of evolution’: the Robertson–Price identity and viability selection for body mass in a wild bird population

By the Robertson–Price identity, the change in a quantitative trait owing to selection, is equal to the trait’s covariance with relative fitness. In this study, we applied the identity to long-term data on superb fairy-wrens Malurus cyaneus, to estimate phenotypic and genetic change owing to juvenile viability selection. Mortality in the four-week period between fledging and independence was 40%, and heavier nestlings were more likely to survive, but why? There was additive genetic variance for both nestling mass and survival, and a positive phenotypic covariance between the traits, but no evidence of additive genetic covariance. Comparing standardized gradients, the phenotypic selection gradient was positive, βP = 0.108 (0.036, 0.187 95% CI), whereas the genetic gradient was not different from zero, βA = −0.025 (−0.19, 0.107 95% CI). This suggests that factors other than nestling mass were the cause of variation in survival. In particular, there were temporal correlations between mass and survival both within and between years. We suggest that use of the Price equation to describe cross-generational change in the wild may be challenging, but a more modest aim of estimating its first term, the Robertson–Price identity, to assess within-generation change can provide valuable insights into the processes shaping phenotypic diversity in natural populations. This article is part of the theme issue ‘Fifty years of the Price equation’G.K.H. was supported by the U.K. Natural Environment Research Council (grant no. NE/L002558/1) through the University of Edinburgh’s E3 Doctoral Training Partnership, and L.E.B.K. was funded by an ARC Future Fellowship FT110100453. The long-term superb fairy-wren study research has been facilitated by a series of Discovery Project grants from the Australian Research Council to A.C. and L.E.B.K., most recently DP150100298

Effects of ocean acidification on invertebrate settlement at volcanic CO<inf>2</inf> vents

We present the first study of the effects of ocean acidification on settlement of benthic invertebrates and microfauna. Artificial collectors were placed for 1 month along pH gradients at CO2 vents off Ischia (Tyrrhenian Sea, Italy). Seventy-nine taxa were identified from six main taxonomic groups (foraminiferans, nematodes, polychaetes, molluscs, crustaceans and chaetognaths). Calcareous foraminiferans, serpulid polychaetes, gastropods and bivalves showed highly significant reductions in recruitment to the collectors as pCO2 rose from normal (336-341 ppm, pH 8.09-8.15) to high levels (886-5,148 ppm) causing acidified conditions near the vents (pH 7.08-7.79). Only the syllid polychaete Syllis prolifera had higher abundances at the most acidified station, although a wide range of polychaetes and small crustaceans was able to settle and survive under these conditions. A few taxa (Amphiglena mediterranea, Leptochelia dubia, Caprella acanthifera) were particularly abundant at stations acidified by intermediate amounts of CO2 (pH 7. 41-7.99). These results show that increased levels of CO2 can profoundly affect the settlement of a wide range of benthic organisms. © 2010 Springer-Verlag

Relationship between mineralogy and minor element partitioning in limpets from an Ischia CO 2 vent site provides new insights into their biomineralization pathway

It has long since been noted that minor element (Me) partitioning into biogenic carbonates is sometimes different from Me partitioning into inorganically precipitated carbonates. The prime example is the partitioning coefficient, which might be lower or even higher than the one of inorganically precipitated carbonate. Such a difference is usually termed “vital effect” and is seen as indicative of a biologically modified minor element partitioning. Over the last three decades interest in conceptual biomineralization models compatible with minor element and isotope fractionation has been steadily increasing. However, inferring features of a biomineralization mechanism from Me partitioning is complicated, because not all partitioning coefficients show vital effects in every calcium carbonate producing organism. Moreover, the partitioning coefficient is not the only aspect of Me partitioning. Other aspects include polymorph specificity and rate dependence. Patellogastropod limpets are ideally suited for analysing Me partitioning in terms of biomineralization models, because they feature both aragonitic and calcitic shell parts, so that polymorph specificity can be tested. In this study, polymorph-specific partitioning of the minor elements Mg, Li, B, Sr, and U into shells of the patellogastropod limpet Patella caerulea from within and outside a CO2 vent site at Ischia (Italy) was investigated by means of LA-ICP-MS. The partitioning coefficients of U, B, Mg, and Sr (in aragonite) differed from the respective inorganic ones, while the partitioning coefficients of Li and Sr (in calcite) fell within the range of published values for inorganically precipitated carbonates. Polymorph specificity of Me partitioning was explicable in terms of inorganic precipitation in the case of Sr and Mg, but not Li and B. Seawater carbon chemistry did not have the effect on B partitioning that was expected on the basis of data on inorganic precipitates and foraminifera. Carbon chemistry did affect Mg (in aragonite) and Li, but only the effect on Mg was explicable in terms of calcification rate. On the one hand, these results show that Me partitioning in P. caerulea is incompatible with a direct precipitation of shell calcium carbonate from the extrapallial fluid. On the other hand, our results are compatible with precipitation from a microenvironment formed by the mantle. Such a microenvironment was proposed based on data other than Me partitioning. This is the first study which systematically employs a multi-element, multi-aspect approach to test the compatibility of Me partitioning with different conceptual biomineralization models

Selective advantage of implementing optimal contributions selection and timescales for the convergence of long-term genetic contributions

Additional file 1: Figure S1. Accumulation of long-term genetic contributions over time with a line of best fit