In the ClimBar project we will identify genome regions, genes, and alleles conferring the traits needed to breed resilient barley varieties adapted to the climatic conditions predicted for 2070 in different European environments.
Predicted conditions and adaptive plant traits for the northern Mediterranean Basin are also applicable to the southern, non-European side and will be relevant to Stakeholders representing farmers from that region. The phenotypic responses of a tailored barley germplasm diversity set that is relevant to resilience, sustainability, and quality will be determined under anticipated conditions of altered water and nutrients, CO2, and pathogen pressure. The set will include cultivated barley, landraces from key European production regions differing in aridity and pre-figuring climate change effects, and wild barley from the Fertile Crescent, which represents the gene pool from which domestication occurred and also carries resilience adaptations.
These responses will be connected to genes and genome regions by GWAS using extensive sequence variant, epigenome, and transcript abundance datasets, and by ecogeographic analysis. The genetic and genomic data sets will be leveraged from earlier (barley 9K SNP set; exome capture) and ongoing (WHEALBI exome capture) studies, which will serve to define the germplasm studied, and will be complemented by planned ClimBar studies (ChIP, small RNA). Therefore, a very large amount of mostly transcribed sequence information will be available to declare and use polymorphisms with a density of coverage and representativeness of germplasm exceeding all previous efforts in this species.
Plant phenotyping will be carried out under field conditions within regions expected to experience differing climate change scenarios, and under controlled greenhouse conditions where detailed physiological phenotypes will be collected. Genes, landraces and Crop Wild Relatives (CWR) associated with environmental conditions will be identified by ecogeographic analysis of genetic diversity. Based on observed plant responses and predicted climate scenarios, proposals for genomic selection (GS) and ideotype models for 2070 will be developed, and relevance to interim conditions assessed. Collaborative interactions with agro-economic modellers as well as climatic modellers will be set up to estimate harvests in 2070 and their impact on the agro-economy, based on data collected within ClimBar.
What we expect to achieve
Climate Smart Agriculture requires both the conservation of genetic resources and their effective use to develop regional varieties with sufficient resilience to deliver yield, quality and stability under increased and different seasonal stresses and decreased inputs. ClimBar will identify critical genes and alleles in the barley gene pool conferring resilience. It will use a structured diversity set of varieties, landraces, and CWR lines as the key to unlocking and conserving genetic diversity in much larger collections. Specifically, the project will produce: a set of agronomically important phenotypes linked to loci, chromosomal regions and alleles; detailed physiological profiles for the function of the alleles under climate-change scenarios; high-precision disease responses versus alleles and climate change; linkage between alleles, physiological response and the epigenetic and regulatory states behind trans-generational resilience. GWAS will serve to link genotype to phenotype and genotype to climate. Models for the relationship between loci and ecogeography will be used as a prediction tool for future barley breeding goals. Data will be fed forward into ago-economic modelling for policy decisions. These data will provide a platform for incorporating both in situ and ex situ allelic diversity into breeding programs, increasing genetic richness of the cultivar set, and forming a basis for multi-varietal cultivation. Adapted, resilient germplasm created using ClimBar data, tools and models will provide food-chain security, economic stability and environmental sustainability.
For further information on this project please contact Robbie Waugh (firstname.lastname@example.org) from the James Hutton Institute.