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:

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:, 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

Google Analytics

Targeted advertising cookies


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 or by post at:

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

Dernière mise à jour : Mai 2018

Menu Logo Principal Logo GAFL Logo GAFL

Home page GAFL

Allele mining for new resistances to PVY in tomato using transcriptomic data

Allele mining for new resistances to PVY in tomato using transcriptomic data
Lebaron, C., Rosado, A., Sauvage, C., Gauffier, C., German-Retana, S., Moury B. and Gallois JL.

Developing genetic resistance to pathogens is a major goal for plant breeding. In many crops, the translation initiation factors eIF4E are susceptibility factors to many RNA viruses, including PVY –Potato virus Y- and allelic variants from those genes are a source of genetic resistances. Natural variability issued from the crop wild relatives constitutes a large reservoir of such resistances but methods have yet to be developed in order to efficiently tap for alleles of interest.

In this work, we show that transcriptomic data can be mined for resistance alleles of a target gene. Using RNAseq data collected in the ARCAD project we isolated a new eIF4E resistance allele from an accession close to the cultivated tomato. Moreover, the analysis of this new allele, that is associated with a resistance easily overcome by PVY, allows us to better characterize the amino acid substitutions in eIF4E associated with an efficient resistance to PVY in crops.

This work stems from the collaboration between several INRA unit (Génétique et Amélioration des Fruits et Légumes-AVIGNON, Pathologie Végétale-AVIGNON, Biologie du Fruit et Pathologie-BORDEAUX). It can be extended to mine for new resistances, in a cross-crop manner, by looking at the many susceptibility host genes on which the virus rely to successfully infect plants.