The transcription factor transcriptome of wall ingrowth deposition in phloem parenchyma transfer cells of Arabidopsis thaliana

Y Wu1, J Hou1, F Yu1,2, T Nguyen1 and D McCurdy1

  1. School of Environmental and Life Sciences, The University of Newcastle, Callaghan, NSW 2308, Australia
  2. College of Forestry, Jiangxi Agricultural University, Jiangxi Province 330045, China

Phloem parenchyma (PP) cells of Arabidopsis leaf veins trans-differentiate to become PP transfer cells (TCs) which are thought to aid phloem loading by facilitating unloading of photoassimilates into the apoplasm for subsequent energy-dependent uptake into the sieve element/companion cell (SE/CC) complex. We are using PP TCs in Arabidopsis as a genetic model to identify transcription factors putatively involved in coordinating the deposition of the wall ingrowth network. Detailed analysis of wall ingrowth deposition by confocal microscopy of modified pseudo-Schiff-propidium iodide-stained tissue shows that wall ingrowths are absent in PP cells of 5-day-old cotyledons but abundant in cotyledons at 10 days, and similarly absent in leaf 1 of 10-day-old seedlings but abundant in leaf 1 at 16 days. Using these observations, we have undertaken transcript profiling (RNA-Sequencing) of wall ingrowth deposition in PP TCs and identified 41 differentially expressed (FDR-corrected P values ≤0.05) transcription factors that are commonly up- or down-regulated when comparing 5-day vs 10-day cotyledons, 10-day vs 16-day leaf 1, and 10-day cotyledons vs 10-day leaf 1. Among them, the 22 transcription factors commonly up-regulated were characterized by members of the NAC-domain, MYB and ERF families. Several of the NAC-domain transcription factors, including the paralogs AtNAC56 and AtNAC18 have been identified as genes involved in secondary wall formation. We report results from co-expression network analysis to further refine a subset of transcription factors likely to participate in genetic regulation of wall ingrowth deposition and test these predictions by phenotypic analysis of relevant mutants.