PhénoFinLait, a national integrated program to control the fine composition of ruminant milk

> Partners: CNIEL (French National Interprofessional Center for Dairy Productions), Institut de l’Elevage (French Breeding Institute), INRA-GABI, SAGA (INRA Animal Breeding unit), UMRPL (INRA and AgroCampusOuest Milk Production unit), URH (INRA Herbivore Research unit), UNCEIA (French National Union of Cooperatives for Animal Insemination), France Conseil Elevage (French Breeding Counselling), Actilait (French Technical Institute for Milk and Dairy Products), Créavia (French Union of Cooperatives for Bovine, Caprine and Equine Selection and Reproduction), Amelis (French Cooperative in animal reproduction specializing in cows, pigs and horses), Lilano (Interprofessional Laboratory for the Analysis of Milk in Normandy)

Milk is a complex product made up of lipids, proteins, carbohydrates and minerals and their relative concentrations depend on environmental (food, farming practices) and genetic (species, breed and genotype) factors. The composition of milk, taken individually, may have beneficial or negative effects on human health. It is therefore essential for the dairy industry to understand, qualify and control its composition. The actors involved in the dairy industry and in research and development on ruminant's genetics have founded the PhénoFinLait program for large-scale phenotyping and genotyping of milk composition of cattle, goats and sheep in order to detect and use QTL. These QTL are regions of the genome that significantly influence the composition of milk. The traits considered are individual fatty acids (FA) or families of fatty acids (saturated, unsaturated, polyunsaturated, trans, etc.) and 12 proteins (caseins, alpha-lactalbumin, beta-lactoglobuline, lactoferrin, serum albumin, etc.).

1. NEW STAKES, NEW TOOLS

A first step involves developing a method for large-scale measurement of milk components. The tool chosen to predict the composition of milk is Middle Infra-Red (MIR) spectroscopy since the spectra are produced in routine when performing dairy controls. We have shown that the statistical analysis of MIR spectra, provides a precise estimation of the composition of milk in terms of major fatty acids and the ratios between saturated/unsaturated and between omega 3/omega 6 lipids that are important for human health. This method will be applied on a large scale to phenotype the studied populations. The spectra should be conserved in the SIG database in the near future. The same approach will be used for proteins but one problem is the lack of a reference method, which we need to develop first using UMLC. Once established, the method will be used to assess the feasibility of predicting the protein composition of milk using MIR spectra. If this is impossible, we will explore whether it is possible to increase the capacity of the UPLC approach.

Progress in genomics and high-throughput genotyping, in particular using SNP arrays at a reasonable cost, leads to new perspectives on which the PhénoFinLait program is based. The SNP arrays will be chosen in 2010 in order to benefit from the latest technological advances and scientific knowledge. If budget ressources are sufficient, we will favor the use of high-throughput analysis with 50 000 SNP arrays.

2. PHENOTYPING AND GENOTYPING

The data collection phase (2009-2010) will concern 12 000 cows, 4 000 ewes and 4 000 goats belonging to seven different breeds, 1 500 farms and 26 departments. Milk samples will be taken from each individual four to six times per lactation for spectral analyses and each time, feeding and other farming factors will be recorded. In parallel, blood samples (for genotyping) and milk samples (for additional studies) will be collected and stored by Labogena (Laboratory for Animal Genetic Analyses) and by the National Biological Resources Center dedicated to Livestock (CRB-GADIE).

In 2011, approximately two thirds of the phenotyped animals will be genotyped using the SNP arrays i.e. approximately 8 000 cattle, 3 500 goats and 2 000 sheep. The animals will be chosen in order to maximise the phenotypic variability observed and to increase the power of QTL detection.

3. GENETIC AND ENVIRONMENTAL FACTORS

QTL detection combining linkage and disequilibrium linkage (Meuwissen and Goddard, 2000) will be carried out together with the analysis of environmental factors, in particular food ration contents. These analyses will include the study of the genotype x environment interactions. The data will lay the foundations for genomic selection on milk composition (fatty acids and proteins). They will simultaneously establish references and technical tools to help breeders perform an optimal valorisation of local genetic and food resources for the production of milk that corresponds to society's requests.

CONCLUSION

The PhénoFinLait project is ambitious both in terms of scale and objectives. Its aims are to provide leaders of the dairy industry with information to take the fundamental and most appropriate directions in terms of milk composition and the different actors of the dairy sector with tools using all available levers to improve milk quality.

Three of GABI's research teams are directly involved in the project: G2B (Bovine Genetics and Genomics), LGS (Milk, Genome, Health) and the CRB GADIE (National Biological Resources Center dedicated to Livestock).

> Financial support: ANR (French National Research Agency), Apis-Gène association, CASDAR (Financial support for Agricultural and Rural Development), FranceAgriMer (French Association for Agricultural and Sea Products), FGE (France Livestock Genetics), Ministry of Agriculture and the European Union

> Web Site: www.phenofinlait.fr/