Project Outline

Plants are sessile organisms that are known for their adaptive plasticity to the changing environment. Environmental changes cannot only influence gene expression patterns but also affect the stability of the genome. Both of these responses seem to involve epigenetic mechanisms. We have discovered that environmental signals, in addition to the direct influence on plant growth, can also cause phenotypic changes that can be transmitted to the progeny, and sometimes remaining stable for several generations.

Environmental stress has a major influence on plant growth and survival, limiting the geographical distribution of natural species and the yield and growing season of agricultural crops. The natural priming response can be elicited experimentally by exposing plants to a short period of extreme abiotic and biotic stress. Using this strategy we have identified regions of the Arabidopsis genome sensitive to epigenetic modification in response to stress that modulate the expression of neighboring genes. However, the precise mechanisms implicated in this process and the phenotypic consequences remain unknown.

Specific objectives:

1. Identification of genome regions targeted epigenetically by stress. This objective will use whole-genome sequencing to identify sequences undergoing epigenetic modification.
2. Functional characterization of epigenetically targeted genome regions. This objective will use CRISPR/Cas9 genome editing tools to direct genetic and epigenetic changes and assess their effects on gene expression.
3. Phenotypic characterization of engineer genome modification. This objective will develop a methodology for the high-throughput phenotypic analysis of engineered plants.

References

Golicz et al., (2016) The pangenome of an agronomically important crop plant Brassica oleracea. Nature Communications, 7:13390

Durr et al., (2018) Highly efficient targeted genomic deletions in plants using CRISPR/Cas9 Sci Rep 8,4443

Techniques

The student will gain skills in molecular biology, gene expression and DNA methylation coupled to next-generation sequencing (NGS). In addition, the student is expected to develop computational skills for the analysis of NGS data using support present in both groups.

Lab-Techniques: CRISPR, RNA-seq and ChIP-seq. Computational-techniques: Wide range of bioinformatics tools for Next-Generation-Sequence data analysis.