Tissue-specific transcriptome profiling of the Arabidopsis inflorescence stem reveals local cellular signatures

Genome-wide gene expression maps with a high spatial resolution have substantially accelerated plant molecular science. However, the number of characterized tissues and growth stages is still small due to the limited accessibility of most tissues for protoplast isolation. Here, we provide gene expression profiles of the mature inflorescence stem of Arabidopsis thaliana covering a comprehensive set of distinct tissues. By combining fluorescence-activated nucleus sorting and laser-capture microdissection with next-generation RNA sequencing, we characterized the transcriptomes of xylem vessels, fibers, the proximal and distal cambium, phloem, phloem cap, pith, starch sheath, and epidermis cells. Our analyses classified more than 15,000 genes as being differentially expressed among different stem tissues and revealed known and novel tissue-specific cellular signatures. By determining overrepresented transcription factor binding regions in the promoters of differentially expressed genes, we identified candidate tissue-specific transcriptional regulators. Our datasets predict the expression profiles of an exceptional number of genes and allow hypotheses to be generated about the spatial organization of physiological processes. Moreover, we demonstrate that information about gene expression in a broad range of mature plant tissues can be established at high spatial resolution by nuclear mRNA profiling.

Automated summary

The study presents gene expression profiles of distinct tissues in the mature inflorescence stem of Arabidopsis thaliana using advanced techniques like fluorescence-activated nucleus sorting and RNA sequencing. They identified over 15,000 genes with differential expression in different stem tissues, revealing tissue-specific cellular signatures and potential transcriptional regulators. The datasets generated in this study provide insights into the spatial organization of physiological processes in plants at a high resolution.