Investigating microRNA control of nodulation in single cell types
Explain the overall aim of the project, including the biological question being addressed
To improve food security we need to gain an in-depth understanding of how the environment
controls plant development. To deal with low nitrogen levels in the soil, leguminous plants form a
symbiosis with nitrogen fixing Rhizobia soil bacteria in root nodules. If we can understand nodulation we
could transfer it to our major non-legume crops such as rice or wheat with massive benefit. To do this we
must identify the molecular mechanisms controlling how a nodule is formed but also, critically for
transferability, pinpoint molecules that recognise the bacteria as a compatible symbiont activating genes
to switch on development of a nodule, rather than a pathogen, activating expression of defense genes.
To identify master regulators of symbiosis we are currently generating single root cell type
timeseries of microarray expression data in Medicago (a legume) as it responds during nodulation and
during lateral root development responses to nitrogen influx. As well as transcription factors we know
from our own previous work in Arabidopsis (Gifford et al 2008 PNAS) and from work in other groups (e.g.
Zhou et al 2011 Genes & Development) that microRNAs (miRs) play many major regulatory roles in root
responses to the environment, acting in a highly cell-specific manner. In particular miRs have recently
been found to regulate specific defense genes and thus might be involved in differentiating defense and
symbiosis responses (Shivaprasad et al 2012 Plant Cell). This project aims to identify miRs as master
regulators of nodulation and predict whether they could be used to develop nodulation outside legumes.
What biological techniques will the student use?
Fluorescence-Activated Cell Sorting (FACS) is used to isolate single cell types followed by whole
genome expression profiling using microarrays and the student will be trained in these 'omic techniques
since we have all facilities for these within our lab. As well as generating new FACS RNA samples they
will use existing lab Medicago single cell type gene expression data with the aim of identifying genes that
control nodulation, mediate nitrogen and symbiont recognition responses and identify miRs that are
predicted to control these genes as putative master regulators. These miRs will then be profiled in the
same FACS RNA samples to test the predictions and develop miR-gene regulatory modules. The
TaqMan kits allow us to accurately assay individual isoforms of miRs in the small amounts of total RNA
generated from individual cell types. We could also use RNAseq for global miR level analysis but the
value of predicting specific miRs to test from our existing FACS data means that we can drill down on
the most important miRs straight away.
For miRs that we have expression evidence for we will create miR perturbation lines to analyse
the functional and phenotypic effects, predicting altered nodulation or lateral root development
phenotypes. This work will involve developing your basic molecular biology and genetics skills and
techniques in tissue culture and physiological investigation. To understand whether the miRs act to
control conserved developmental processes we will make use of our parallel timeseries data for nitrogen
and Rhizobium responses in the non-nodulating Arabidopsis within the prediction process.
What theoretical methods will be developed and/or used?
A range of bioinformatic techniques will be used to identify groups of nodulation and lateral root
development-controlling genes from the gene expression data in both Medicago and Arabidopsis. The
genes will then be analysed to identify miR recognition sites and the controlling miRs. To compare the
sets of genes and controlling miRs between species the student will use existing methods to find
orthologous genes between the species studied. Where we have sequenced genomes available we can
make use of the gene position information to improve the quality of orthology assignments. Given
expression data for different species, different cell types, and different time points we will identify groups
of genes that share their temporal and spatial expression pattern across species. We will hypothesise
that such sets of genes are regulated by a common miR regulatory mechanism.
Why is this Systems Biology?
One cycle of systems biology will be identifying regulated genes, predicting controlling miRs and
then analysing the expression of the miRs to see if they fit the predictions. The second cycle revolves
around the hypothesis that orthologous miRs will be regulated in similar ways during nodulation/lateral
root responses across different species, again to be tested using miR assays. The final cycle postulates
that if the miR regulates nodulation/lateral root development in Medicago, that perturbing it will affect that
process phenotypically, and furthermore that it will affect parallel or similar developmental processes
across legumes and non-legumes.