Construction of gene coexpression networks and transcriptomic analysis for Rhizobium leguminosarum

Rhizobium leguminosarum is a soil bacteria which infects plants of the legume family such as peas, lentils, and beans. When associated with the plant, R. leguminosarum fixes atmospheric nitrogen (biological nitrogen fixation), producing ammonium that is assimilated by the plant, improving plant growth. This symbiotic relationship is very important for agriculture; increasing the knowledge of plant infection and nitrogen fixation processes might lead to a decrease in the use of chemical fertilisers. In this thesis, I combine R. leguminosarum gene expression data from previous experiments to produce gene coexpression networks and increase the functional annotation of this bacterium. Gene coexpression networks are networks in which nodes represent genes and edges represent coexpression (i.e. two genes are connected if they have a similar expression pattern). Unfortunately, there is no standard method to generate gene coexpression networks from gene expression data. I introduce signed distance correlation as a measure of dependency between two variables and use it to generate self-consistent, unweighted and weighted, gene coexpression networks that are more stable and capture more biological information than those obtained from Pearson correlation or mutual information. Subsequently, I present a pipeline that combines novel scores from gene coexpression network analysis in a principled way to identify the genes that are associated with certain growth conditions or highly coexpressed with a predefined set of genes of interest. This association can lead to putative functional annotation or to a prioritised list of genes for further study. Lastly, I provide a detailed analysis of the transcriptome of R. leguminosarum. For this purpose, I generate different knock-out mutants lacking transcriptional regulators which are reported to be important in the nitrogen-fixing state of the bacteria and perform RNA-Seq experiments. I also carry out a preliminary study of the molecular signals that may affect the changes in gene expression between the free-living and the plant associated bacteria.