Research
In the Diaz-Garcia Lab, we focus on four major areas:
1. Integrative breeding
In modern times, the development of new sequencing and high-throughput phenotyping technologies allow us to gather massive amounts of data about any particular point in the plant genome-phenome space. Breeders’ experience and empirical knowledge, industry input, and consumer preferences are key components of the breeding process. In the Diaz-Garcia lab we aim to integrate the breeder’s eye with multidisciplinary, high-dimensional, high-scalable data for improving grapevine breeding efforts.
2. Functional genomics
New technologies allow the discovery of genes driving phenotypic variation. Our large germplasm collection spanning more than 40 Vitis species harbors tremendous phenotypic variation, some of which is still unexploited. Through a strong collaboration network, the Diaz-Garcia Lab aims to discover, understand, catalog, conserve, and exploit useful allelic variation to support grapevine breeding.
3. Phenomics
With the advances in genotyping methodologies, we have amassed an enormous amount of genomic sequences. Now, what do we do with that? Retrieving high-dimensional, high-quality, high-throughput phenotyping data (i.e. phenomics) could help us to make sense of the large genomic datasets, and decipher the genetic nature of the complex phenotype variation in grapes. On the other hand, phenomics approaches have the potential to increase our capabilities to evaluate and select more (and more rapidly) promising materials in our grapevine breeding program.
4. Breeding alliances
The Diaz-Garcia Lab conducts grapevine breeding based on industry, growers, nurseries, food processors, and consumer needs and priorities. All our efforts are focused on solving current problems in California and the US, and on preventing future difficulties in the light of climate change. We heavily rely on industry collaborations and on getting close to growers to better assess the needs, priorities, and areas of opportunity for grapevine breeding. We have a strong network of collaborations with breeders and scientists in other universities and government agencies as well. Our collaborative efforts span many different science areas, and it is built on many people. For example, we maximize our phenotyping capabilities through automated machines and cutting-edge vision technology. We have a more efficient breeding program thanks to the implementation of statistical prediction models based on DNA sequence data and genomics. Moreover, we focus our breeding efforts on traits that have been precisely curated based on consumer preferences, which increases the chance of new cultivar adoption.
Below you can find a list of Luis’s previous publications in cranberry and miscellaneous topics, as well as new publications on grape breeding, genetics, and genomics. For the complete list of publications, we invite to check our Google Scholar profile.
2022
2021
2020
2019
2018
