3Dwheat, A 3 Dimensional functional genomics approach to identify hidden targets controlling heat stress and priming in wheat

Introduction

In the global warming era, heat stress is a major threat for both yield stability and yield increase. Plants have evolved a variety of sophisticated mechanisms to adapt to challenging environments. Epigenetic regulations allow them to dynamically reprogram their transcription machinery to adapt to an ever-changing environment.

Chromatin Dynamics

Both histone marks and the 3D organization of the chromatin are instrumental for this coordinated regulation of gene expression according to environmental cues. Yet, the overwhelming majority of available data on chromatin dynamics in response to stress has been obtained in Arabidopsis and cannot be directly transferred to crops.

Technological Advancements

Due to the expansion of NGS technologies, we are currently facing a change of paradigm, empowering the development of genome-wide approaches on crops.

Focus on Wheat

In this project, we focus on wheat. Wheat is the 1st cereal worldwide for trade, and the demand is expected to increase by 60% by 2050. My main objective is a thorough understanding of the priming for heat stress resistance in wheat.

Proposed Approach

To this end, I propose to develop a new tri-dimensional (3D) functional genomics approach, integrating:

1. Epigenomic (1D) data
2. Transcriptomic (2D) data
3. Chromatin architecture (3D) data

This integration aims to elucidate the molecular basis for priming in wheat.

Broader Implications

Moreover, this project will go beyond addressing the challenge of deciphering epigenetic regulatory processes underlying priming. It also includes the development of innovative tools for novel breeding strategies that will harness epigenetic variability in addition to genetic diversity.

Development of Molecular Markers

We propose to generate a new generation of molecular markers that do not rely on DNA sequence polymorphisms, and that can be readily used in traditional breeding programs as such, or as complementary tools for efficient QTL introgression.

Applications of Markers

Such markers will be used to:

• Tag new traits
• Follow a new generation of alleles
• Unveil new types of genetic diversity in existing collections of germplasms.