VitisGen2

Mapping the Way to the Next Generation of Grapes

grape breeder Bruce Reisch working with grape seedlings in the greenhouse

About VitisGen2

Robot phenotyping powdery mildew resistance

Major Accomplishments

VitisGen2 project team at team meeting in 2018

Team Members

A scientist emasculating a grape flower with a pair of tweezers

Videos

Image of a webinar screenshot

Webinars

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Articles in popular press

 

 In The News

 

    • New “Research In Plain English” article on foliar phylloxera resistance

      Lab members example grape leaves.

      The VitisGen2 team members at the University of Minnesota have been studying the genetic underpinnings of foliar phylloxera resistance. Rootstocks resistant to this important grape pest have been available for some time — and a new article by Matthew Clark et al. explains how their research helps breeders come closer to breeding resistance to foliar phylloxera as well. The RIPE article provides a “plain English” explanation of the research described in the full article, linked below.

      Quantitative trait loci identified for foliar phylloxera resistance in a hybrid grape population. Authors: Matthew D. Clark, Soon L. Teh, Eric Burkness, Laise Moreira, Grace Watson, Lu Yin, William D. Hutchison and James J. Luby. Australian Journal of Grape and Wine Research, 24 (3), pages 292-300.

 

    • VitisGen2 scientists train neural networks to identify Powdery Mildew

      phenotyping robot with a tray of grape leaf disks.

      ‘Practice makes perfect’ is undeniably cliché, but its truth is evident to everyone who has ever tried to learn a new skill.  Whether it’s hitting baseballs, pushing piano keys, or pipetting off supernatant, this inevitable cycle of trial and error eventually yields to increasing expertise. What’s true for humans is also true for computer systems.

      Learn more about machine learning in article by Anna Underhill: “VitisGen2 scientists train neural networks to identify Powdery Mildew”

 

    • Staff Spotlight on Mélanie Massonnet

      Melanie MassonetMélanie Massonnet, postdoctoral researcher in Dario Cantu’s lab at UC Davis, explains how she uses genome-wide transcriptional analyses of grape breeding populations for powdery mildew resistance gene stacking and improving wine grape quality, along with telling us how her background growing up in France influenced her decision to work with wine and much more.

 

    • Staff Spotlight on Cheng Zou

      Cheng Zou VitisGen2 team member Cheng Zou, postdoctoral researcher in Qi Sun’s lab at Cornell University, talks about finding a core-genome markers for comparing genotypic data across all grape species, and the applications for marker assisted selection and quantitative trait mapping! Don’t be intimidated though, she explains it in plain English.

      She also tells us what she enjoys about working with grapes, explains the amazing technology they use for finding genetic markers, and gives advice for someone beginning a career in genetics.

 

 

 

 

    • New Technology for Next-gen DNA Sequencing Validated by the VitisGen2 Project

      Illumina DNA processing cell, which looks similar to a computer chip, being held up for the camera.A new technology called rhAmpSeq™ is allowing grape geneticists and breeders to rapidly find and validate 2000 markers in diverse grape varieties and species.  These ‘core genome markers’ provide a new set of mileposts that were used during a pilot study by the USDA-funded VitisGen2 project to map traits in six unrelated ‘mapping populations’ representing the diversity of U.S. grape breeding programs, including numerous Vitis species.

      The rhAmpSeq technology, developed by Integrated DNA Technologies (IDT) and commercialized in March 2019, allows researchers to mix and amplify DNA from up to 4,000 individual samples and simultaneously sequence thousands of different markers of each sample.  This dramatically reduces the cost of DNA sequencing across the 19 grape chromosomes – and offers a detailed map of the entire genome for each of the 4000 individuals in one batch.

      Read more about this exciting new technology.