Computing approximate monogenic model likelihoods in large pedigrees with loops

International audienc

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

Divergent selection for humoral immune responsiveness in chickens: distribution and effects of major histocompatibility complex types

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Reconstructing CNV genotypes using segregation analysis: combining pedigree information with CNV assay

<p>Abstract</p> <p>Background</p> <p>Repeated blocks of genome sequence have been shown to be associated with genetic diversity and disease risk in humans, and with phenotypic diversity in model organisms and domestic animals. Reliable tests are desirable to determine whether individuals are carriers of copy number variants associated with disease risk in humans and livestock, or associated with economically important traits in livestock. In some cases, copy number variants affect the phenotype through a dosage effect but in other cases, allele combinations have non-additive effects. In the latter cases, it has been difficult to develop tests because assays typically return an estimate of the sum of the copy number counts on the maternally and paternally inherited chromosome segments, and this sum does not uniquely determine the allele configuration. In this study, we show that there is an old solution to this new problem: segregation analysis, which has been used for many years to infer alleles in pedigreed populations.</p> <p>Methods</p> <p>Segregation analysis was used to estimate copy number alleles from assay data on simulated half-sib sheep populations. Copy number variation at the Agouti locus, known to be responsible for the recessive self-colour black phenotype, was used as a model for the simulation and an appropriate penetrance function was derived. The precision with which carriers and non-carriers of the undesirable single copy allele could be identified, was used to evaluate the method for various family sizes, assay strategies and assay accuracies.</p> <p>Results</p> <p>Using relationship data and segregation analysis, the probabilities of carrying the copy number alleles responsible for black or white fleece were estimated with much greater precision than by analyzing assay results for animals individually. The proportion of lambs correctly identified as non-carriers of the undesirable allele increased from 7% when the lambs were analysed alone to 80% when the lambs were analysed in half-sib families.</p> <p>Conclusions</p> <p>When a quantitative assay is used to estimate copy number alleles, segregation analysis of related individuals can greatly improve the precision of the estimates. Existing software for segregation analysis would require little if any change to accommodate the penetrance function for copy number assay data.</p

Suboptimal herd performance amplifies the spread of infectious disease in the cattle industry

Farms that purchase replacement breeding cattle are at increased risk of introducing many economically important diseases. The objectives of this analysis were to determine whether the total number of replacement breeding cattle purchased by individual farms could be reduced by improving herd performance and to quantify the effects of such reductions on the industry-level transmission dynamics of infectious cattle diseases. Detailed information on the performance and contact patterns of British cattle herds was extracted from the national cattle movement database as a case example. Approximately 69% of beef herds and 59% of dairy herds with an average of at least 20 recorded calvings per year purchased at least one replacement breeding animal. Results from zero-inflated negative binomial regression models revealed that herds with high average ages at first calving, prolonged calving intervals, abnormally high or low culling rates, and high calf mortality rates were generally more likely to be open herds and to purchase greater numbers of replacement breeding cattle. If all herds achieved the same level of performance as the top 20% of herds, the total number of replacement beef and dairy cattle purchased could be reduced by an estimated 34% and 51%, respectively. Although these purchases accounted for only 13% of between-herd contacts in the industry trade network, they were found to have a disproportionately strong influence on disease transmission dynamics. These findings suggest that targeting extension services at herds with suboptimal performance may be an effective strategy for controlling endemic cattle diseases while simultaneously improving industry productivity

Breeding Value and Variance Component Estimation from Data Containing Inbred Individuals: Application to Gynogenetic Families in Common Carp (Cyprinus Carpio L.)

Under gynogenetic reproduction, offspring receive genes only from their dams and completely homozygous offspring are produced within one generation. When gynogenetic reproduction is applied to fully inbred individuals, homozygous clone lines are produced. A mixed model method was developed for breeding value and variance component estimation in gynogenetic families, which requires the inverse of the numerator relationship matrix. A general method for creating the inverse for a population with unusual relationships between animals is presented, which reduces to simple rules as is illustrated for gynogenetic populations. The presence of clones in gynogenetic populations causes singularity of the numerator relationship matrix. However, clones can be regarded as repeated observations of the same genotype, which can be accommodated by modifying the incidence matrix, and by considering only unique genotypes in the estimation procedure. Optimum gynogenetic sib family sizes for estimating heritabilities and estimates of their accuracy were derived and compared to those for conventional full-sib designs. This was done by means of a deterministic derivation and by stochastic simulation using Gibbs sampling. Optimum family sizes were smallest for gynogenetic families. Only for low heritabilities, there was a small advantage in accuracy under the gynogenetic design