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New approaches for the analysis and utilization of wheat genetic diversity

Project description

New tool for wheat genetic variation analysis

To ensure food security amid the ongoing environmental crisis, it is necessary to breed new cultivars quickly. Enhancing genetic diversity and using improved tools for trait transfer from wild relatives, especially in wheat, is crucial. The ERC-funded NextWheat project will develop a computational tool to analyse genetic variation in modern and wild wheat genomes, with a specific focus on identifying harmful mutations that affect fitness. The project will develop genomic tools for the effective genotyping of these mutations in classical breeding programmes and assess their impact on yield. It will use genome-editing techniques to enhance genetic diversity by transferring genes from wild relatives into domestic wheat and repairing harmful mutations. All materials and tools produced will be made freely available.

Objective

Addressing the challenge of food security during the current environmental crisis will necessitate rapidly breeding a new generation of adapted cultivars. Genetic diversity and selection of natural variants are key to advances in breeding. However, there is a need for better tools to predict how natural variation impacts plant performances, to improve the precision and efficiency of gene modification, and transfer from wild relatives to crops. We will focus on wheat, one of the most important staple foods of humanity, and on the broad genetic pool of its wild relatives. Our goals are to develop a computational tool to analyze genetic variation in the genomes of modern and wild wheat and to identify deleterious mutations that impair fitness. We will build genomics tools for effective genotyping of deleterious mutations in classical breeding and we will test their effect on yield. Then, we will use genome editing tools to increase diversity via the precise transfer of genes from the wild into the domestic background and for targeted repair of deleterious mutations towards wheat improvement. We plan to achieve this by developing a machine-learning algorithm to predict the presence of deleterious mutations in whole genomes (WP1). Then, we will test how such mutations can affect crop fitness by designing a genotyping microarray for simple identification of deleterious mutations in segregating populations for use in classical breeding (WP2). We will also harness new breeding technologies to increase the genetic diversity in wheat through the precise transfer of genes or chromosomal segments from close and distant chromosomes of wild relatives to modern wheat and for repairing deleterious mutations through modification of the relevant genes (WP3). This project should provide a new understanding of how genetic diversity affects plant fitness and how better to exploit it in plant breeding. All materials and tools developed through this work will be freely available.

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HORIZON-ERC - HORIZON ERC Grants

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(opens in new window) ERC-2024-ADG

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Host institution

WEIZMANN INSTITUTE OF SCIENCE
Net EU contribution

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€ 2 498 500,00
Address
HERZL STREET 234
7610001 Rehovot
Israel

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Activity type
Higher or Secondary Education Establishments
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Total cost

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Beneficiaries (1)

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