Combined Genetic and Modeling Approaches Reveal That Epidermal Cell Area and Number in Leaves Are Controlled by Leaf and Plant Developmental Processes in Arabidopsis

Abstract

Both leaf production and leaf expansion are tightly linked to cell expansion and cell division, but the functional relationships between all these variables are not clearly established. To get insight into these relationships, a quantitative genetic analysis was performed in 118 recombinant inbred lines derived from a cross between the Landsberg erecta and Antwerp accessions and was combined with a structural equation modeling approach. Main effects and epistatic interactions at the quantitative trait locus (QTL) level were detected for rosette area, rosette leaf number, leaf 6 area, epidermal cell area and number. A QTL at ERECTA marker (ER) controlled cell expansion and cell division, in interaction with two other QTLs at SNP295 and SNP21 markers. Moreover, both the screening for marker association involved in the variation of the relationships between leaf growth variables and the test of alternative functional models by structural equation modeling revealed that the allelic value at ER controlled epidermal cell area and epidermal cell number in a leaf. These effects are driven both by a whole plant mechanism associated with leaf production and by a single leaf mechanism associated with leaf expansion. The complex effects of the QTL at ER were validated in selected heterogeneous inbred families. The ERECTA gene, which is mutated in the Landsberg erecta parental line, was found to be a putative candidate responsible for these mapped effects by phenotyping mutants of this gene at the cellular level. Together, these results give insight into the complex determination of leaf epidermal cell number and area.

Leaf Growth Response to Mild Drought: Natural Variation in Arabidopsis Sheds Light on Trait Architecture

“…Polyploidy has been related to an increase in organ sizes; however, the relationship is elusive. The trade-off between epidermal cell area and cell number has also been observed in a Ler 3 An-1 recombinant inbred line (RIL) population, but only for RILs that lacked the erecta mutation (Tisné et al, 2008). The erecta mutation has a strong effect on cell division, resulting in a positive correlation between both cellular traits for RILs with the mutation and an extremely high number of pavement cells in the Ler accession in our study.…”

Downregulation of chloroplast protease AtDeg5 leads to changes in chronological progression of ontogenetic stages, leaf morphology and chloroplast ultrastructure in Arabidopsis

“…3) since epidermal cell area is controlled by mechanisms associated with the onset of flowering [40] with two highly conserved miRNA -miR156 and miR172 and their targets regarded as key components in reproductive phase change [41]. The final leaf area was demonstrated to be strongly correlated with epidermal cell number and epidermal cell area [38,40] and AtDeg5 must be engaged in respective regulatory events since fully expanded leaves, both juvenile and mature ones were significantly affected in their morphological features as a result of AtDeg5 repression (Fig. 4).…”

“…1). Leaf production (development) and growth were shown to be controlled by genetic factors [38,39] linked to epidermal cell expansion and cell division with a key role of QTL at ERECTA marker in interaction with SNP295 and SNP21. Since functional relationships between these factors are complicated and far from clear it is not easy to imagine how AtDeg5 may influence these network.…”

PaCeQuant: A Tool for High-Throughput Quantification of Pavement Cell Shape Characteristics

“…The algorithms used to track and measure growth in these model systems cannot directly be applied to quantify PC characteristics, as they oversimplify PC shape geometry, and comparable quantification methods suitable for robust analysis of PCs are lacking. In most existing studies that analyzed PC characteristics, differences in PC shape between mutants and wild type were quantified by the analysis of single shape parameters only (Tisné et al, 2008;Xu et al, 2010;Li et al, 2013) or by a combination of a few select shape parameters (Fu et al, 2005;Guo et al, 2015). Although sufficient for direct comparison of phenotypes, the limited shape information reduces the informational value of the individual measurements and hampers a comprehensive comparison of phenotypes identified in different studies and from different laboratories (Ivakov and Persson, 2013;Wu et al, 2016).…”