P. Boettcher

The combined use of embryos and semen for cryogenic conservation of mammalian livestock genetic resources

The objective of this empirical simulation study was to evaluate the use of a combination of semen and embryos in the creation of gene banks for reconstruction of an extinct breed. Such an approach was compared for banks with varying proportions of embryos on the basis of the amount of the material to be stored, time for reconstruction, maintenance of genetic variability, and probability of failure during reconstruction. Four types of populations were simulated, based on reproductive rate: single offspring, twinning, enhanced reproduction, and litter bearing. Reconstruction was simulated for banks consisting of different combinations of semen and reduced numbers of embryos (expressed as a percentage of the material needed for a bank containing exclusively embryos and ranging from 10 to 90%). The use of a combination of semen and embryos increased the number of insemination cycles needed for reconstruction and the level of genetic relatedness in the reconstructed population. The risk for extinction was unacceptably high when a very low proportion of embryos (< 20%) was used. However, combining semen with embryos could decrease costs, allowing for the conservation of more breeds, and specific strategies for semen use could decrease the level of relationships in the reconstructed breed.

The costs of breed reconstruction from cryopreserved material in mammalian livestock species

The aim of this work was to compare costs, in the horse, cattle, sheep, swine, and rabbit species, for the creation of gene banks for reconstruction of an extinct breed, using different strategies: embryos-only, embryos in combination with semen, and semen-only. Three cost measures were used: time required for population reconstruction, cost for creation of the gene bank, number of years-keeping-female to reach reconstruction. Semen costs were estimated across four scenarios: the presence or absence of a commercial market for semen, purchase of semen donors, and semen extracted from the epididymus. The number of cells were doubled to take into account the creation of two storage sites. The strategy embryos-only required the shortest time to reach reconstruction. With the strategy embryos + semen, time increased with decreasing proportions of embryos. With semen-only, reconstruction time varied from 2 to 21 years. A high variation of costs was observed across species and strategies, from 360 Euros in the rabbit to 1 092 300 in the horse. In all species, the embryos-only strategy was about 10% more expensive than using 90% embryos + semen. Decreasing the percentage of embryos further diminished costs. The number of years-keeping-female ranged across strategies, from 2 in the rabbit, to a maximum of 12 878 in the horse.

Breeding for improvement of functional traits in dairy cattle

Abstract Selection programs for increasing milk production per cow have been very successful over time. This success has been partially due to the consideration of few other traits. Unfortunately, many traits related to costs of production and cattle functionality (i.e., “functional traits”), such as fertility and health, are antagonistically correlated with milk yield. Therefore, the average merit for these traits has decreased over time. The decline in functionality, along with increased awareness of the costs of production and animal well-being, has spurred interest in breeding for improvement in functional traits. Unfortunately, factors such as low heritability and lack of data make the selection for functionality more difficult than for production. Research has been able to overcome some of these limitations, at least to some extent, through the development and application of advanced statistical analyses and through indirect selection on genetically correlated traits. Possibilities exist in the future for additional refinement of selection procedures for improvement of functional traits. Computing capacities are continually increasing and more complex but statistically appropriate analysis methods are being developed. Furthermore, genome scans have identified chromosomal regions that have putative associations with functional traits. The bovine genome has been recently sequenced, so the possibility to identify the genes affecting functional traits exists, at least in theory. With low heritabilities and difficulties in measurement, functional traits are the ideal candidates for the application of marker-assisted selection.

Genetic selection strategies to improve longevity in Chianina beef cattle

Abstract Longevity in beef cattle is an important economic trait. Including this trait in a breeding scheme increases profit and has a positive impact on the well-being and welfare of the animals. The aim of the present study was to evaluate the consequences of alternative selection strategies to include longevity in different breeding schemes using deterministic simulation. Different schemes were compared and economic (EcW) and empirical weights (EmW) were used to evaluate the responses. The empirical weights of average daily gain (ADG) and muscularity (MU) were identical because both traits have an identical importance for the breeders. Economic weights have been derived from profit equations. Traits used in the Base scenarios were: average daily gain pre-performance test (ADG1), average daily gain during the performance test (ADG2) and muscularity (MU); longevity (L) was included in the alternative schemes. When longevity was included both in the breeding index and in the breeding goal (scenario A-2), the total longevity response using EmW and EcW was +2.97 d/yr and +4.92 d/yr, respectively. The total economic response for scenario A-2 using EmW and EcW were 3.020 €/yr and 3.342 €/yr, respectively, and the total response in units of Bull Selection Index were +0.699 and +0.678, respectively. Longevity decreased when it was not included in either the breeding goal or in the breeding index (scenario Base), and economic response was the lowest found. The results of the current study indicate that the highest total response using either economic weights or empirical weights was found when information on longevity was included both in the breeding index and in the breeding goal (scenario A-2).

In silico candidate gene mining in livestock species

Abstract The identification of genes involved in livestock production and disease is a challenge due to the multi-genic, multifactorial nature of the traits and the complexity of integration of information from different studies. Genome-wide techniques such as microarray analysis, SAGE, linkage analysis and linkage disequilibrium analysis have been extensively used in livestock and have often identified a large number of candidate genes. Selection of the most probable candidate genes for further empirical analysis remains a challenge. Novel extensive biological databases (DB) provide an opportunity for candidate gene mining. Bioinformatic methods and tools to prioritize candidate genes underlying pathways or diseases have been presented mostly for application to human disease candidate gene search. These computational methods employ data from a variety of sources to identify the most likely candidate genes from genes sets. The objectives of the study were: 1. to test a set of existing gene prioritization computational methods on real and simulated livestock traits, namely mastitis susceptibility in cattle, production in cattle, litter size in swine, and tick resistance in cattle; 2. to develop a novel method for candidate prioritization that better suits the characteristics of genomic information of livestock species (lower level of annotation, different experimental designs, etc.). The algorithm performs distinct prioritizations from multiple heterogeneous data sources, which are then integrated into one global ranking using order statistics. Information about a trait or pathway is recorded, ordered and stored from a set of known genes using multiple data sources. Then, the candidate genes are ranked based on similarity with the training properties obtained in the first step, resulting in one prioritized list for each data source. Data for linkage and association analysis, and expression analysis (2 microarray studies) were simulated for a complex trait assigning the largest effects to known, well described genes in the Gene Ontology (GO), InterPro, MEDLINE, and Kegg databases. All the other simulated major genes were assigned to genes described in one of the databases for livestock species. Real data were selected from the literature, mainly from large QTL studies, or obtained from collaborators. Software used for the analysis were: Suspect (http://www.genetics.med.ed.ac.uk/software/prospectr.php), Endevour and COeXpress (http://coxpress.sf.net). Results using simulated data showed that where annotation is missing, the accuracy of the considered algorithms decreased drastically. A new prioritization method applied to simulated data correctly ranked candidate gene only when QTL information had a high level of accuracy. Further work is needed in defining methods of weighting QTL data information.