Enhancing stress resistance in plants by targeted epigenome manipulation

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.

Role of 3D Chromatin Configuration on Environmental Memory

Project Outline

Living creatures depend on signals from their surroundings to navigate the various stages of their lives. Yet, the ever-changing nature of these environmental cues poses a significant challenge in precisely timing critical life decisions. What's fascinating is that many organisms, including plants, have developed remarkable resilience in responding to these environmental signals, even though they lack centralized information-processing systems, like our brains.

Compared to animals, somatic cells of plants can be much more easily reprogrammed to regenerate whole new organs and, sometimes, entire individuals. This unique biological property has enabled plants to reproduce either sexually or asexually according to their habitat. The ability of plant cells to readily acquire a totipotent state has been attributed to their flexible epigenetic states. As a result, plant totipotency has been traditionally exploited by humans for the clonal propagation and genetic manipulation of economically important species. We have recently found that clonal plants have the capacity to remember previous exposures to environmental insults, which we termed “environmental memory”. This memory is linked to the accumulation of epigenetic modifications that allow clonal plants to become more resistant to environmental stress. The aim of this project is to define the impact that stress-mediated epigenetic changes have on chromatin 3D conformation and the role of these changes stress adaptation in plants.

References

Wibowo, A., Becker, C., Durr, J., Price, J., Papareddy, R., Saintain, Q., Spaepen, S., Hilton, S., Bending.,G., Schulze-Lefert, P., Weigel., D. and Gutierrez-Marcos J.F. (2018) Incomplete reprogramming of cell-specific epigenetic marks during asexual reproduction leads to heritable phenotypic variation in plants PNAS 116:8037-8042

Techniques

The student will investigate the molecular changes associated with stress memory in Arabidopsis using a multidisciplinary approach (microscopy, next-generation-sequencing data analysis and epi/genome editing). The groups of JGM and LF have developed all the material and methodology required for their analysis. The student will also use customized computational models (machine learning) to enable the high-throughput analysis of chromatin dynamics.

Lab-Techniques

Confocal Microscopy, cell culture, genome sequencing.

Computational techniques

computational tools for image data and genomic analysis.

The molecular basis of glial cell heterogeneity in human brain

Project Outline

Glial cells constitute a large fraction of the mammalian brain. Although initially considered as non-functional supporter for neuron function, recent studies have revealed that glial cells have critical roles in the brain under both physiological and pathological conditions. Glial-cell pathology is increasingly recognized in several neurodegenerative diseases and in the occurrence of brain tumours. However, the existences of highly heterogeneous glial populations in the brain have limited functional studies.

The aim of this project is (i) to determine the genetic heterogeneity of glial cells in different brain tissues and (ii) identify the genetic factors determining the identity of distinct glial populations. Using computational and experimental approaches, the student will investigate the transcriptional profile of glial-cell populations, determine the genetic pathway(s) implicated in distinct glial identity and use targeted genome editing to reveal their function.

References

Krishnaswami, S.R. et al., Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons (2016) Nature Protocols 11:499-524

Techniques

The student will gain skills in single-cell transcriptomic analysis of message RNA and non-coding RNAs. The student will be able to analyse next-generation sequencing (NGS) data to generate hypothesis that will be tested in the laboratory using established CRISPR/Cas9 genome targeting methods. The student is expected to obtain basic training on computational and statistical tools for analysis of genome-wide data.

Lab Techniques

scRNA-seq, cell culture, CRISPR. Computational-techniques: Wide range of bioinformatics tools for Next-Generation-Sequence data analysis.