Know more

Our use of cookies

Cookies are a set of data stored on a user’s device when the user browses a web site. The data is in a file containing an ID number, the name of the server which deposited it and, in some cases, an expiry date. We use cookies to record information about your visit, language of preference, and other parameters on the site in order to optimise your next visit and make the site even more useful to you.

To improve your experience, we use cookies to store certain browsing information and provide secure navigation, and to collect statistics with a view to improve the site’s features. For a complete list of the cookies we use, download “Ghostery”, a free plug-in for browsers which can detect, and, in some cases, block cookies.

Ghostery is available here for free: https://www.ghostery.com/fr/products/

You can also visit the CNIL web site for instructions on how to configure your browser to manage cookie storage on your device.

In the case of third-party advertising cookies, you can also visit the following site: http://www.youronlinechoices.com/fr/controler-ses-cookies/, offered by digital advertising professionals within the European Digital Advertising Alliance (EDAA). From the site, you can deny or accept the cookies used by advertising professionals who are members.

It is also possible to block certain third-party cookies directly via publishers:

Cookie type

Means of blocking

Analytical and performance cookies

Realytics
Google Analytics
Spoteffects
Optimizely

Targeted advertising cookies

DoubleClick
Mediarithmics

The following types of cookies may be used on our websites:

Mandatory cookies

Functional cookies

Social media and advertising cookies

These cookies are needed to ensure the proper functioning of the site and cannot be disabled. They help ensure a secure connection and the basic availability of our website.

These cookies allow us to analyse site use in order to measure and optimise performance. They allow us to store your sign-in information and display the different components of our website in a more coherent way.

These cookies are used by advertising agencies such as Google and by social media sites such as LinkedIn and Facebook. Among other things, they allow pages to be shared on social media, the posting of comments, and the publication (on our site or elsewhere) of ads that reflect your centres of interest.

Our EZPublish content management system (CMS) uses CAS and PHP session cookies and the New Relic cookie for monitoring purposes (IP, response times).

These cookies are deleted at the end of the browsing session (when you log off or close your browser window)

Our EZPublish content management system (CMS) uses the XiTi cookie to measure traffic. Our service provider is AT Internet. This company stores data (IPs, date and time of access, length of the visit and pages viewed) for six months.

Our EZPublish content management system (CMS) does not use this type of cookie.

For more information about the cookies we use, contact INRA’s Data Protection Officer by email at cil-dpo@inra.fr or by post at:

INRA
24, chemin de Borde Rouge –Auzeville – CS52627
31326 Castanet Tolosan CEDEX - France

Dernière mise à jour : Mai 2018

Menu Logo Principal AgroParisTech Université Paris-Saclay

INRA GABI Unit

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

A Systems Biology Approach to identify the genes responsible for beef tenderness

Beef tenderness
A Systems Biology Approach allowed to explore the relations between traits associated with meat quality and to identify the gene network implicated. Using this approach, which was applied to three bovine populations (Charolais, Limousine and Blonde d’Aquitaine), 206 genes, whose variants explain 30% of tenderness variance, were identified.

Context and Stakes

Considering the difficult economic context where beef production is confronted with many challenges, the discovery of molecular markers that may be used to select animals with higher meat quality would provide the industry with the means to satisfy consumers and ensure meat of high quality with a guarantee of tenderness. Research carried forth up until now in France and elsewhere in the world have identified different regions of the genome and/or DNA polymorphisms associated with the differences of quality but without finding a coherency among the results.
By using a « Systems Biology » approach, we explored the relations between the traits associated with meat quality, we sought to identify the pleiotropic effects and deduce the gene networks associated with tenderness and other qualities of meat. We applied this approach to three bovine populations including Charolais, Limousine and Blonde d’Aquitaine to identify a group of genes that may potentially be used whatever the breed.

Results

Our results showed a group of 206 genes found in the three breeds. The variations (SNP) present in these genes explain between 28 and 30% of the phenotypic variation of the “shearing force” tenderness trait, however, these variations are rarely present in more than one breed. This result suggests that different mutations affect the same genes but in a different manner between the three breeds.
During this study, the genes known to be implicated in tenderness were identified and a group of 206 shared genes are located in QTL regions associated with tenderness that have already been described in other studies on other populations. The multiple-trait and multiple-breed analysis have also permitted the identification of new candidate genes.
This study shows that a systems biology approach allows the identification of candidate genes that, by a “classical” mono-trait analysis approach, would not have been found.   

Perspectives

This study provides a list of genes that are potentially implicated in tenderness. Through future studies, they should lead to the discovery of causal mutations.

References

Ramayo-Caldas Y., Renand G., Ballester M., Saintilan R., Rocha D. (2016). Multi-breed and multi-trait co-association analysis of meat tenderness and other meat quality traits in three French beef cattle breeds. Genet. Sel. Evol. 48: 37.