A note on inbreeding in dairy cattle breeding

Starting from the study at the beginning of the East German "Heterosisfeldversuch", where PANICKE et al. (1975) considered the possibilities of a targeted use of inbreeding and heterotic effects, we show and discuss results of inbreeding studies in the USA dairy cattle breeding. Several research groups worldwide presented effective tools for managing inbreeding in dairy cattle. Their efforts underline the need of inbreeding studies. Contemplating inbreeding is necessary for any breeding decision to avoid inbreeding depression and for improved genetic analyses, e.g. in QTL- estimation. A novel methodology (HERNANDEZ-SANCHEZ et al., 2004a and b) is suggested for estimating inbreeding at the three levels of population, individual and locus.

Strategies to improve the efficiency of genomic selection in animal breeding programs

Pós-graduação em Zootecnia - FCAV

Future trends in Animal Breeding due to new genetic tecnologies

The Darwin theory of evolution by natural selection is based on three principles: (a) variation; (b) inheritance; and (c) natural selection. Here, I take these principles as an excuse to review some topics related to the future research prospects in Animal Breeding. With respect to the first principle I describe two forms of variation different from mutation that are becoming increasingly important: variation in copy number and microRNAs. With respect to the second principle I comment on the possible relevance of non-mendelian inheritance, the so-called epigenetic effects, of which the genomic imprinting is the best characterized in domestic species. Regarding selection principle I emphasize the importance of selection for social traits and how this could contribute to both productivity and animal welfare. Finally, I analyse the impact of molecular biology in Animal Breeding, the achievements and limitations of quantitative trait locus and classical marker-assisted selection and the future of genomic selection

A short critical history of the application of genomics to animal breeding

Two scientific schools have been in coexistence from the beginning of genetics, one of them searching for factors of inheritance and the other one applying biometrical models to study the relationships between relatives. With the development of molecular genetics, the possibilities of detecting genes having a noticeable effect in traits augmented. Some genes with large or medium effects were localized in animals, although the most common result was to detect markers linked to these genes, allowing the possibility of assisting selection programs with markers. When a large amount of simple and inexpensive markers were available, the SNPs, new possibilities were opened since they did not need the presence of genes of large or medium effect controlling a trait, because the whole genome was scanned. Using a large amount of SNPs permits having a prediction of the breeding value at birth accurate enough to be used in some cases, like dairy cattle, to halve its generation interval. In other animal breeding programs, the implementation of genomic selection is less clear and the way in which it can be useful should be carefully studied. The need for large populations for associating phenotypic data and markers, plus the need for repeating the process continuously, complicates its application in some cases. The implementation of the information provided by the SNPs in current genetic programs has led to the development of complex statistical tools, joining the efforts of the two schools, factorial and biometrical, that nowadays work closely related.

Principles and methods of animal breeding.

"References to literature": p. [366]-372.

Principles and methods of animal breeding /

Includes bibliographical references (p. 283-287) and index.

Fertility and animal-breeding ...

First edition, October 1925, published as Gt. Brit. Ministry of agriculture and fisheries. Research monograph no.2, with title: The physiology of animal breeding.

Heredity in relation to evolution and animal breeding,

"Based on a course of eight lectures delivered in November and December, 1910, before the Lowell institute, Boston, as well as on a course of five lectures delivered before the Graduate school of agriculture held under the auspices of the Association of agricultural colleges and experiment stations at Ames, Iowa, in July, 1910."--Pref.

Effect of family relatedness on characteristics of estimated IBD probabilities in relation to precision of QTL estimates

Background: A random QTL effects model uses a function of probabilities that two alleles in the same or in different animals at a particular genomic position are identical by descent (IBD). Estimates of such IBD probabilities and therefore, modeling and estimating QTL variances, depend on marker polymorphism, strength of linkage and linkage disequilibrium of markers and QTL, and the relatedness of animals in the pedigree. The effect of relatedness of animals in a pedigree on IBD probabilities and their characteristics was examined in a simulation study. Results: The study based on nine multi-generational family structures, similar to a pedigree structure of a real dairy population, distinguished by an increased level of inbreeding from zero to 28 % across the studied population. Highest inbreeding level in the pedigree, connected with highest relatedness, was accompanied by highest IBD probabilities of two alleles at the same locus, and by lower relative variation coefficients. Profiles of correlation coefficients of IBD probabilities along the marked chromosomal segment with those at the true QTL position were steepest when the inbreeding coefficient in the pedigree was highest. Precision of estimated QTL location increased with increasing inbreeding and pedigree relatedness. A method to assess the optimum level of inbreeding for QTL detection is proposed, depending on population parameters. Conclusions: An increased overall relationship in a QTL mapping design has positive effects on precision of QTL position estimates. But the relationship of inbreeding level and the capacity for QTL detection depending on the recombination rate of QTL and adjacent informative marker is not linear. © 2010 Freyer et al., licensee BioMed Central Ltd.

Mapping quantitative trait loci in a wild population using linkage and linkage disequilibrium analyses

Historical information can be used, in addition to pedigree, traits and genotypes, to map quantitative trait locus (QTL) in general populations via maximum likelihood estimation of variance components. This analysis is known as linkage disequilibrium (LD) and linkage mapping, because it exploits both linkage in families and LD at the population level. The search for QTL in the wild population of Soay sheep on St. Kilda is a proof of principle. We analysed the data from a previous study and confirmed some of the QTLs reported. The most striking result was the confirmation of a QTL affecting birth weight that had been reported using association tests but not when using linkage-based analyses. Copyright © Cambridge University Press 2010.

Mapping of multiple quantitative trait loci affecting bovine spongiform encephalopathy

A whole-genome scan was conducted to map quantitative trait loci (QTL) for BSE resistance or susceptibility. Cows from four half-sib families were included and 173 microsatellite markers were used to construct a 2835-cM (Kosambi) linkage map covering 29 autosomes and the pseudoautosomal region of the sex chromosome. Interval mapping by linear regression was applied and extended to a multiple-QTL analysis approach that used identified QTL on other chromosomes as cofactors to increase mapping power. In the multiple-QTL analysis, two genome-wide significant QTL (BTA17 and X/Y ps) and four genome-wide suggestive QTL (BTA1, 6, 13, and 19) were revealed. The QTL identified here using linkage analysis do not overlap with regions previously identified using TDT analysis. One factor that may explain the disparity between the results is that a more extensive data set was used in the present study. Furthermore, methodological differences between TDT and linkage analyses may affect the power of these approaches.

On the prediction of simultaneous inbreeding coefficients at multiple loci

A new deterministic method for predicting simultaneous inbreeding coefficients at three and four loci is presented. The method involves calculating the conditional probability of IBD (identical by descent) at one locus given IBD at other loci, and multiplying this probability by the prior probability of the latter loci being simultaneously IBD. The conditional probability is obtained applying a novel regression model, and the prior probability from the theory of digenic measures of Weir and Cockerham. The model was validated for a finite monoecious population mating at random, with a constant effective population size, and with or without selfing, and also for an infinite population with a constant intermediate proportion of selfing. We assumed discrete generations. Deterministic predictions were very accurate when compared with simulation results, and robust to alternative forms of implementation. These simultaneous inbreeding coefficients were more sensitive to changes in effective population size than in marker spacing. Extensions to predict simultaneous inbreeding coefficients at more than four loci are now possible.

Genome-wide search for markers associated with bovine spongiform encephalopathy

A genome-wide search for markers associated with BSE incidence was performed by using Transmission-Disequilibrium Tests (TDTs). Significant segregation distortion, i.e., unequal transmission probabilities of alleles within a locus, was found for three marker loci on Chromosomes (Chrs) 5, 10, and 20. Although TDTs are robust to false associations owing to hidden population substructures, it cannot distinguish segregation distortion caused by a true association between a marker and bovine spongiform encephalopathy (BSE) from a population-wide distortion. An interaction test and a segregation distortion analysis in half-sib controls were used to disentangle these two alternative hypotheses. None of the markers showed any significant interaction between allele transmission rates and disease status, and only the marker on Chr 10 showed a significant segregation distortion in control individuals. Nevertheless, the control group may have been a mixture of resistant and susceptible but unchallenged individuals. When new genotypes were generated in the vicinity of these three markers, evidence for an association with BSE was confirmed for the locus on Chr 5.

Genetic Heteroscedasticity for Domestic Animal Traits

Animal traits differ not only in mean, but also in variation around the mean. For instance, one sire’s daughter group may be very homogeneous, while another sire’s daughters are much more heterogeneous in performance. The difference in residual variance can partially be explained by genetic differences. Models for such genetic heterogeneity of environmental variance include genetic effects for the mean and residual variance, and a correlation between the genetic effects for the mean and residual variance to measure how the residual variance might vary with the mean. The aim of this thesis was to develop a method based on double hierarchical generalized linear models for estimating genetic heteroscedasticity, and to apply it on four traits in two domestic animal species; teat count and litter size in pigs, and milk production and somatic cell count in dairy cows. The method developed is fast and has been implemented in software that is widely used in animal breeding, which makes it convenient to use. It is based on an approximation of double hierarchical generalized linear models by normal distributions. When having repeated observations on individuals or genetic groups, the estimates were found to be unbiased. For the traits studied, the estimated heritability values for the mean and the residual variance, and the genetic coefficients of variation, were found in the usual ranges reported. The genetic correlation between mean and residual variance was estimated for the pig traits only, and was found to be favorable for litter size, but unfavorable for teat count.

Estudo de simulação de modelos lineares mistos com distribuição normal contaminada no melhoramento genético animal

Objetivou-se com esse trabalho comparar estimativas de componentes de variâncias obtidas por meio de modelos lineares mistos Gaussianos e Robustos, via Amostrador de Gibbs, em dados simulados. Foram simulados 50 arquivos de dados com 1.000 animais cada um, distribuídos em cinco gerações, em dois níveis de efeito fixo e três valores fenotípicos distintos para uma característica hipotética, com diferentes níveis de contaminação. Exceto para os dados sem contaminação, quando os modelos foram iguais, o modelo Robusto apresentou melhores estimativas da variância residual. As estimativas de herdabilidade foram semelhantes em todos os modelos, mas as análises de regressão mostraram que os valores genéticos preditos com uso do modelo Robusto foram mais próximos dos valores genéticos verdadeiros. Esses resultados sugerem que o modelo linear normal contaminado oferece uma alternativa flexível para estimação robusta em melhoramento genético animal.