Genome-Wide Detection of Condition-Sensitive Alternative Splicing in Arabidopsis Roots

Abstract

Iron (Fe) deficiency is a world-wide nutritional disorder in both plants and humans, resulting from its restricted bioavailability for plants and, subsequently, low Fe concentration in edible plant parts. Plants have evolved sophisticated mechanisms to alleviate Fe deficiency, with the aim of recalibrating metabolic fluxes and maintaining cellular Fe homeostasis. To analyze condition-sensitive changes in precursor mRNA (pre-mRNA) splicing pattern, we mapped the transcriptome of Fe-deficient and Fe-sufficient Arabidopsis (Arabidopsis thaliana) roots using the RNA sequencing technology and a newly developed software toolbox, the Read Analysis & Comparison Kit in Java (RACKJ). In alternatively spliced genes, stress-related Gene Ontology categories were overrepresented, while housekeeping cellular functions were mainly transcriptionally controlled. Fe deficiency increased the complexity of the splicing pattern and triggered the differential alternative splicing of 313 genes, the majority of which had differentially retained introns. Several genes with important functions in Fe acquisition and homeostasis were both differentially expressed and differentially alternatively spliced upon Fe deficiency, indicating a complex regulation of gene activity in Fe-deficient conditions. A comparison with a data set for phosphate-deficient plants suggests that changes in splicing patterns are nutrient specific and not or not chiefly caused by stochastic fluctuations. In sum, our analysis identified extensive posttranscriptional control, biasing the abundance and activity of proteins in a condition-dependent manner. The production of a mixture of functional and nonfunctional transcripts may provide a means to fine-tune the abundance of transcripts with critical importance in cellular Fe homeostasis. It is assumed that differential gene expression and nutrient deficiency-induced changes in pre-mRNA splicing represent parallel, but potentially interacting, regulatory mechanisms.