
Project
WHEALBI – Improving European wheat and barley production
WHEALBI stands for the project ‘WHEAt and barley Legacy for Breeding Improvement’. The project originates from the principle that to improve wheat and barley production in order to face severe global changes, we need to better exploit knowledge from basic science to develop new varieties and innovative cropping systems.
The WHEALBI project will combine genomics, genetics and agronomy to improve European wheat and barley production in competitive and sustainable cropping systems. It will generate original data from expressed genome sequences of 1000 wheat and barley genetic resources and provide models and tools to integrate these data in breeding programmes and crop management.
The results will be disseminated to a broad user community, highlighting the benefits and issues associated with the adoption of what is considered sustainable and environmentally friendly wheat and barley crop production in a European context.
WHEALBI aims to help the EU remaining a major actor in small grain cereal production while addressing the pressing global priorities of increasing and stabilising primary production, improving food quality and safety, and reducing environmental impact.
The project
The project consists of 9 work packages (WP). Wageningen University & Research leads WP 4; Data integration and analysis tools.
WP 1: Identifying circa 1000 germplasm accessions representing genetic diversity in European agriculture
WP 2: Identify the nature and extent of gene sequence diversity in the wheat and barley genepool
The objectives of WP2 are to:
- Reveal the nature and extent of genome wide DNA sequence diversity in the exomes of >500 wheat and >500 barley accessions (from WP1)
- Establish robust pipelines for identifying and calling true sequence variations (including Quality Control of raw sequence data)
- Conduct genome wide analysis of the resulting data focussed on functional and adaptive variation and partitioning between different genepools.
WP 3: Phenotypic exploitation of the WHEALBI germplasm collection
WP3 relies on the germplasm selected and multiplied in WP1 and it will explore different phenotyping strategies designed to provide the phenotypic information required to complement the genomics data generated in WP2 and WP5.
A standard phenotypic approach based on nurseries across Europe will be established to test the wheat and barley collection for their adaptive capacity under different environmental conditions (referred to here as a “common garden” trial). Furthermore, precision phenotyping experiments dedicated to specific developmental traits, response to main biotic factors and response to drought will be carried out to exemplify the exploitation of the large phenotypic variability existing in germplasm. Field trials and advanced phenotyping platforms will be combined to achieve a precise determination of the phenotypes of interest.
WP 4: Data integration and analysis tools
Work package leader: Fred van Eeuwijk (WUR, the Netherlands)
The objectives of WP4 are to:
- Deploy a versatile infrastructure for storing, integrating and communicating massive amounts of heterogeneous data generated in the WHEALBI project; and provide machine and web-accessible interfaces to access, link and query data and data combinations.
URGI, partner of WHEALBI has released the database of the 1000 wheat and barley genotypes. Access is free for wheat, but needs registration for barley. Information about the database can be found here. - Develop and deploy efficient statistical tools to analyse single or multiple sources of data from within and beyond the WHEALBI project.
WP 5: Allele and pathway mining for adaptive traits and grain quality
WP 6: Genome-assisted pre-breeding and breeding methods
WP 7: Innovative crop management practices to identify wheat and barley ideotypes with enhanced performance
WP 8: Dissemination, training and technology transfer
WP 9: Project coordination and overall management
Selection of results:
- Characterization of population structure and genetic diversity for circa 400 barley accessions using Exome sequence data
- We propose statistical strategies that allow us combining information of multiple environments. That allowed us to identification of genomic regions (QTLs) underlying traits related to barley adaptation to diverse environments
- Allele mining for genes within the QTL regions
- Explore whether there is a relation between important alleles and the geographical origin of barley genotypes
