Dynamic re-programming of the cold transcriptome in Arabidopsis

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Our experimental approaches and bioinformatics developments demonstrate that dynamic changes in the transcriptome depend on both transcription and AS and that AS forms an important part of re-programming of the transcriptome.

We will continue to use ultra-deep RNA-seq of time-courses of plants treated with low temperatures and exploit our developments in RNA-seq analysis. The dynamic transcript-specific profiles allow network modelling at both the gene (transcriptional) and splicing (AS) levels and, significantly, gives the opportunity to integrate these different layers of regulation. The most up-to-date approaches in network analysis will be applied to existing data and the new data (constant light; first 3 h at 4C) allowing causal inferences in the networks to be predicted.

Key hub genes (genes with many connections to other genes) are likely to be important in re-programming the cold transcriptome. Selected genes will be characterised for their physiological (freezing tolerance and acclimation) and molecular phenotypes (validation of network connections - effects on AS target genes of mutants/over-expression lines).

Immediate/early effects on AS may be important to priming the plant (transcriptome) for temperature change before establishing the full low temperature response. We will therefore exploit the extensive expertise in phosphoproteomics at Dundee to investigate immediate/early phosphorylation of splicing factors in response to low temperatures and will investigate specific kinases involved in cold signalling.

Finally, genes with AS events important in establishing the cold transcriptome and tolerant/acclimation are expected to show an altered phenotype when knocked out. Also, the different transcript isoforms (which may code for different protein isoforms) may be responsible for the phenotype. We will express specific AS isoforms in mutant backgrounds to demonstrate the functionality of specific AS isoforms.

The impact of this work will be the novel information on how gene expression is reprogrammed at the transcript, gene and network levels and how to apply the current technologies to perform such analyses in different plant and crop species. These approaches can be used by plant scientists examining gene function and gene expression of development, responses to external stimuli, metabolic pathways, biotechnology approaches, plant breeding etc. In particular, the approaches will benefit many areas of crop genomics and biology but translation to crops requires an understanding of the potential and action to focus on generation of the transcriptomic resources. As such the main beneficiaries and users are the research sector, both academic and industrial.

The main challenge to maximising impact is to raise awareness of its potential and utility with the people who are most likely to use it and benefit their research. This needs to be done in a timely fashion so that other researchers can plan and design RNA-seq experiments with the goal of analysing data using comprehensive RTDs and the best available programmes to quantify transcript levels and establish network models.

The main Impact Objectives are to:

- Publicise the value of transcript-specific expression and understanding the dynamic transcriptome
- Encourage the development of RTDs for other plant/crop species.
- Engage with crop scientists and industry

To achieve these objectives:
1) The PIs/Co-Is will ensure community awareness by contacting research groups in the plant community with details of the project and how it will benefit them

2) The PIs/Co-Is will present regular updates of progress at national and international conferences and meetings on plant biology and genomics such as SEB, ICAR conferences etc as well as through more focussed meetings on RNA splicing, gene networks and the circadian clock. The PIs/Co-Is will also present their findings at invited seminars.

4) The PI/Co-Is will develop a strategy for interacting with crop scientists developing genomics approaches and engaging with industry.

5) Tools and resources for RNA-seq and network analysis will be released on the most appropriate websites for rapid uptake; a "cold" expression website will be established where users can examine expression profiles of their gene of interest in our time-course series.

6) Results will be published in timely fashion.

6) Public engagement activities.

7) Training and mentoring of the PDRAs.