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24, chemin de Borde Rouge -Auzeville - CS52627 31326 Castanet Tolosan cedex - France

Last update: May 2021

Menu Logo Principal AgroParisTech Université Paris-Saclay


GABI : Génétique Animale et Biologie IntégrativeUnité Mixte de Recherche INRA - AgroParisTech

A new research highlight: "Genetic determinism for cheese-making ability of milk."

A new research highlight: "Genetic determinism for cheese-making ability of milk."
© @ INRA M.P. Sanchez
Prediction equations for cheese-making abilities using Middle-Infrared spectra of milk were developed and applied to several million spectra in the Monbeliard bovine breed. A genetic analysis shows that coagulation parameters and yield are heritable. An association analysis on the whole genome sequence level identified 59 QTL and a network of 736 co-regulated genes.

MOTS-CLES : Cattle; genetic determinism; cheese-making ability; Montbeliarde bovine breed

Cheese-making ability is a complex process to study since measuring it directly is difficult. Therefore controlling the cheese-making ability during the production phase is an important challenge, due to the importance of the cheese sector.


Mid-IR spectroscopy (MIR), which has been identified as a precise tool for identifying the fine composition of milk, was a good candidate for predicting the initial cheese-making characteristics, coagulation aptitude, acidification and yield. The From’MIR (2015-2018) project, coordinated by CEL25-90 and financed by Casdar, the Cniel and Urfac, was aimed at predicting the cheese-making aptitude of milk using MIR spectra, for genetic improvement and counseling in breeding. The storage of MIR spectra since 2011 and the development of cattle genotypes for genomic selection are two exceptionnal resources for a large scale study of these traits.

Prediction equations compiled from 420 reference cheese tests (24 parameters measured using two technologies: soft cheese and hard pressed cheese) with good to excellent precision were obtained using the PLS method for six coagulation parameters and three yield parameters; acidification aptitude was poorly predicted. These equations were then applied to more than 6 million spectra from more than 400 000 Montbeliard cows from Franch Comté, paving the way to large-scale genetic analyses.

An estimation of genetic parameters showed that these traits are heritable (between 0.37 and 0.48 on the scale for each monthly measurement) and that they have a stable determinism during lactation and between lactations. On the genetic level, all traits for yield and coagulation are favorably correlated amongst themselves, including between cheese-making technologies. Coagulation is strongly associated with the casein content and some minerals whereas yield is more associated with fat content. Cheese-making aptitude is not unfavorably associated with any currently selected traits and has experienced a rather favorable evolution over the last 10 years in this breed. An association analysis led to a device with 20 000 cows with phenotypes and genotypes imputed on the whole genome scale, using the population sequenced through the "1000 bovine genome" consortium as a reference. Fifty-nine QTL were detected as being significant on the genome scale, globally explaining between 12 and 30 % of the phenotypes for cheese trait variability. Most of the QTL known to affect milk composition also influence cheese aptitude and new QTL were detected, with causal mutation candidates. A network analysis showed a network of 736 genes that interact amongst themselves along with approximately 20 metabolic pathways, in particular for potassium and phosphates. This analysis identified several regulating genes including PPARA, ASXL3 and bta-mir-200c, strongly implicated in the regulation of these networks.

A pilot genomic evaluation indicates that the precision obtained is high, allowing for a very efficient selection on these cheese-making traits. 

This large-scale study shows the power of genetic approaches applied to a large scale of data issued from high-throughput phenotypings and genotypings. This progress will provide tools for both selection and counseling in breeding, so that cheese-making qualities may be controlled at the milk production scale. A genomic evaluation of these traits for cheese-making ability is currently being developed. Similar studies are underway with other regions and French breeds.



Scientific Contact(s):

INRA Division : Animal Genetics

Research center : Jouy-en-josas



 INRA priority in its Guidance Document

#3Perf-3 : Multicriteria assessment to measure performance

See also

Références bibliographiques

Sanchez M.P., Ramayo-Caldas Y., Wolf V., Laithier C., El Jabri M., Michenet A., Boussaha M., Taussat S., Fritz S., Delacroix-Buchet A., Brochard M., Boichard D. 2019. Sequence-based GWAS, network and pathway analyses reveal genes co-associated with milk cheese making properties and milk composition in Montbéliarde cows. Genet Sel Evol, 51, 34. DOI : 10.1186/s12711-019-0473-7, (feature paper).

El Jabri M., Sanchez M.P., Trossat P., Laithierc., Wolf V., Grosperrin P., Beuvier E., Rolet-Répécaud O., Gavoye S., Gauzere Y., Belysheva O., Notz E., Boichard D., Delacroix-Buchet A. 2019. Comparison of Bayesian and PLS regression methods for mid-infrared prediction of cheese-making properties in Montbéliarde cows. J Dairy Sci., ehead of print. DOI : 10.3168/jds.2019-16320.

Sanchez M.P., El Jabri M., Minery S., Wolf V., Beuvier E., Laithier C., Delacroix-Buchet A., Brochard M., Boichard D. 2018. Genetic parameters for cheese-making properties and milk composition predicted from mid-infrared spectra in a large dataset of Montbéliarde cows. J Dairy Sci, 101, 10048–10061. DOI : 10.3168/jds.2018-14878.

Sanchez M.P., Wolf V., El Jabri M., Beuvier E., Rolet-Repecaud O., Gauzere Y., Minery S., Brochard M., Michenet A., Taussat S., Barbat-Leterrier A., Delacroix-Buchet A., Laithier C., Fritz S., Boichard D. 2018. Short-communication: Confirmation of candidate causative variants on milk composition and cheese-making properties in Montbéliarde cows. J Dairy Sci, 101, 10076–10081. DOI : 10.3168/jds.2018-14986.

Sanchez M.P., Wolf V., Laithier C., El Jabri M., Beuvier E., Rolet-Repecaud O., Gaudilliere N., Minery S., Ramayo-Caldas Y., Tribout T., Michenet A., Boussaha M., Taussat S., Fritz S., Delacroix-Buchet A., Grosperrin P., Brochard M., Boichard D. 2019. Analyse génétique de la fromageabilité du lait de vache prédite par spectrométrie moyen infrarouge en race Montbéliarde. INRA Productions Animales, (synthèse soumise)