New phenotypes for new breeding goals in dairy cattle

In modern dairy cattle breeding, genomic breeding programs have the potential to increase efficiency and genetic gain. At the same time, the requirements and the availability of genotypes and phenotypes present a challenge. The set-up of a large enough reference population for genomic prediction is problematic for numerically small breeds but also for hard to measure traits. The first part of this study is a review of the current literature on strategies to overcome the lack of reference data. One solution is the use of combined reference populations from different breeds, different countries, or different research populations. Results reveal that the level of relationship between the merged populations is the most important factor. Compiling closely related populations facilitates the accurate estimation of marker effects and thus results in high accuracies of genomic prediction. Consequently, mixed reference populations of the same breed, but from different countries are more promising than combining different breeds, especially if those are more distantly related. The use of female reference information has the potential to enlarge the reference population size. Including females is advisable for small populations and difficult traits, and maybe combined with genotyping females and imputing those that are un-genotyped.The efficient use of imputation for un-genotyped individuals requires a set of genotyped related animals and well-considered selection strategies which animals to choose for genotyping and phenotyping. Small populations have to find ways to derive additional advantages from the cost-intensive establishment of genomic breeding schemes. Possible solutions may be the use of genomic information for inbreeding control, parentage verification, within-herd selection, adjusted mating plans or conservation strategies.The second part of the paper deals with the issue of high-quality phenotypes against the background of new, difficult and hard to measure traits. The use of contracted herds for phenotyping is recommended, as additional traits, when compared to standard traits used in dairy cattle breeding can be measured at set moments in time. This can be undertaken even for the recording of health traits, thus resulting in complete contemporary groups for health traits. Future traits to be recorded and used in genomic breeding programs, at least partly will be traits for which traditional selection based on widespread phenotyping is not possible. Enabling phenotyping of sufficient numbers to enable genomic selection will rely on cooperation between scientists from different disciplines and may require multidisciplinary approaches.

Section: Additional Aspects For Small Populationsmentioning

confidence: 99%

“…Genomic selection has the potential to use new phenotypes (Boichard and Brochard, 2012;Calus et al, 2012). However, the quality and quantity of these phenotypes remains a critical issue (Boichard and Brochard, 2012).…”

Section: The Challenges Of Phenotypingmentioning

confidence: 99%

Review: Opportunities and challenges for small populations of dairy cattle in the era of genomics

Schöpke¹,

Swalve

2016

“…environmental efficiency and animal welfare) are promoted by society for inclusion in breeding programmes, genomic selection offers an interesting opportunity to add new selection criteria to breeding objectives (Boichard and Brochard, 2012). Indeed, selecting new phenotypes seems to be more feasible, especially for traits that cannot be recorded on a large scale because they are difficult or expensive to measure.…”

Section: Defining Selection Objectives and Integrating New Selection mentioning

confidence: 99%

“…Indeed, selecting new phenotypes seems to be more feasible, especially for traits that cannot be recorded on a large scale because they are difficult or expensive to measure. These new phenotypes are mainly related to health (lameness, disease resistance, metabolic and reproductive disorders), feed efficiency, milk composition or adaptation to different environments (Boichard and Brochard, 2012). Experimental herds, MOET herds or test stations could be exploited to record such phenotypes.…”

Section: Defining Selection Objectives and Integrating New Selection mentioning

confidence: 99%

Integrating genomic selection into dairy cattle breeding programmes: a review

Bouquet

Juga

2013

Extensive genetic progress has been achieved in dairy cattle populations on many traits of economic importance because of efficient breeding programmes. Success of these programmes has relied on progeny testing of the best young males to accurately assess their genetic merit and hence their potential for breeding. Over the last few years, the integration of dense genomic information into statistical tools used to make selection decisions, commonly referred to as genomic selection, has enabled gains in predicting accuracy of breeding values for young animals without own performance. The possibility to select animals at an early stage allows defining new breeding strategies aimed at boosting genetic progress while reducing costs. The first objective of this article was to review methods used to model and optimize breeding schemes integrating genomic selection and to discuss their relative advantages and limitations. The second objective was to summarize the main results and perspectives on the use of genomic selection in practical breeding schemes, on the basis of the example of dairy cattle populations. Two main designs of breeding programmes integrating genomic selection were studied in dairy cattle. Genomic selection can be used either for pre-selecting males to be progeny tested or for selecting males to be used as active sires in the population. The first option produces moderate genetic gains without changing the structure of breeding programmes. The second option leads to large genetic gains, up to double those of conventional schemes because of a major reduction in the mean generation interval, but it requires greater changes in breeding programme structure. The literature suggests that genomic selection becomes more attractive when it is coupled with embryo transfer technologies to further increase selection intensity on the dam-to-sire pathway. The use of genomic information also offers new opportunities to improve preservation of genetic variation. However, recent simulation studies have shown that putting constraints on genomic inbreeding rates for defining optimal contributions of breeding animals could significantly reduce achievable genetic gain. Finally, the article summarizes the potential of genomic selection to include new traits in the breeding goal to meet societal demands regarding animal health and environmental efficiency in animal production.Keywords: genomic selection, breeding programme, dairy cattle, genetic gain, inbreeding rates ImplicationsThe practical use of genomic information to select animals, or genomic selection, is currently revolutionizing the organization of dairy cattle breeding schemes. The success of this new technology is because of increased genetic progress on both the bull and cow genetic pathways by reducing costs compared with conventional selection schemes, but also by the potential of using this rich source of information to manage genetic resources. Practical results of the implementation of genomic selection in dairy cattle breeding schemes are of great importa...

“…Increasing survival and longevity is the first solution for reduction in replacement costs (Boichard and Brochard, 2012). Routine genetic evaluation for longevity (or length of productive life) of dairy cows is carried out in most developed countries now.…”

Section: Introductionmentioning

confidence: 99%

Comparison of piecewise Weibull baseline survival models for estimation of true and functional longevity in Brown cattle raised in small herds

Jenko

Ducrocq

Kovač

2013

Piecewise Weibull proportional hazard models were used to investigate the effect of genetic and nongenetic factors on functional and true longevity traits of the Slovenian Brown cattle breed. Records of 37 908 Brown cows from 2401 Slovenian herds were used. As these herds were characterised by a relatively small average herd size starting from 6.7 in 1999 and increasing to 8.7 Brown cows per herd in 2008, milk yield classification was made within different herd size groups. The hazard rate was the lowest in the first part of each lactation and was increasing for later stages. Culling risk was lower for cows from herds increasing in size, for cows with higher milk production and for cows from a region with smaller herd sizes and tougher conditions for cattle breeding. The latter result is surprising and may be related to better attention to maintain the animals, despite their lower milk production. The introduction of the milk quota system and drought was found to have an important effect on culling policy between the last seasons of the years 2001 and 2003. Seasonal effects were not related to the milk quota year (from April to March), but to the effect of shortage in fodder during the winter time. The effect of age at first calving and the interaction between year and milk yield class were not found to be significant. Heritability for functional and for true longevity were similar at around 10% each. Inclusion of a correction for class of milk yield to approximate functional longevity increased the herd-year random effect variance by 53%, whereas the sire variance increased by only 14%. The correlation coefficient between ranks of breeding values for functional and true longevity was high (0.91), whereas genetic trends were not found to be significant. To assess their predictive ability, models were compared looking at the survival rate of 4212 second-crop daughters not included in the initial models. The average correlation between estimated breeding values and survival at different stages was 0.39 for true longevity and 0.43 for functional longevity. Results showed that ranking milk yield at population level is appropriate to correct for voluntary culling on low production in small herds.