Transcriptome and co-expression network analysis reveal molecular mechanisms of mucilage formation during seed development in Artemisia sphaerocephala.

Seed mucilage has significant economic value. However, the identification of key regulatory genes in mucilage formation and their molecular regulatory mechanism remain unknown. Artemisia sphaerocephala seeds are rich in mucilage. In this study, A. sphaerocephala seeds in 10, 20, 30, 40, 50, 60 and 70 days after flowering were used as materials to reveal their molecular regulatory mechanism in mucilage formation by RNA-sequencing and weighted gene co-expression network analysis (WGCNA). 21 key regulatory genes for mucilage formation were identified, including AsKNAT7 and AsTTG1 genes, as well as AsNAM and AsAP2 gene families. From 10-30 days after flowering, both AsNAM and AsAP2 supported mucilage formation. From 40-70 days after flowering, promotion by AsNAM and AsAP2 was weakened and the up-regulation of AsKNAT7 inhibited mucilage formation, leading to no further increases in mucilage content. This in depth elucidation of seed mucilage formation lays the foundation for the application of mucilage.

Variation in Expression of the HECT E3 Ligase UPL3 Modulates LEC2 Levels, Seed Size, and Crop Yields in Brassica napus.

Identifying genetic variation that increases crop yields is a primary objective in plant breeding. We used association analyses of oilseed rape/canola (Brassica napus) accessions to identify genetic variation that influences seed size, lipid content, and final crop yield. Variation in the promoter region of the HECT E3 ligase gene BnaUPL3 C03 made a major contribution to variation in seed weight per pod, with accessions exhibiting high seed weight per pod having lower levels of BnaUPL3 C03 expression. We defined a mechanism in which UPL3 mediated the proteasomal degradation of LEC2, a master transcriptional regulator of seed maturation. Accessions with reduced UPL3 expression had increased LEC2 protein levels, larger seeds, and prolonged expression of lipid biosynthetic genes during seed maturation. Natural variation in BnaUPL3 C03 expression appears not to have been exploited in current B napus breeding lines and could therefore be used as a new approach to maximize future yields in this important oil crop.

Production of a new mucilage compound in Lepidium sativum callus by optimizing in vitro growth conditions.

The mucilage in Lepidium sativum L. is considered a biologically active compound with diverse medicinal properties. Different explants (hypocotyls and leaf) were transferred to Murashige and Skoog (MS) medium supplemented with twelve different plant growth regulator combinations under two different incubations (light and dark). The best mucilage production from callus (36.76% g g-1 dry weight) was obtained in the MS medium supplemented with 1 mg L-1 of 2, 4-D and 2 mg L-1 of BAP under the light condition. The mucilage produced by callus culture was nearly three times more than the mucilage yield of the seeds. The glucose, arabinose + mannose and galactose were 43.4 (mg g-1 DW), 195.3 (mg g-1 DW) and 86.2 (mg g-1 DW) in the mucilage originated from seed, callus leaf and callus hypocotyl, respectively. The present study proposes an efficient method for producing large scales of mucilage with a favorable sugar aimed at food or pharmaceutical industries.

LASSO modeling of the Arabidopsis thaliana seed/seedling transcriptome: a model case for detection of novel mucilage and pectin metabolism genes.

Whole genome transcript correlation-based approaches have been shown to be enormously useful for candidate gene detection. Consequently, simple Pearson correlation has been widely applied in several web based tools. That said, several more sophisticated methods based on e.g. mutual information or Bayesian network inference have been developed and have been shown to be theoretically superior but are not yet commonly applied. Here, we propose the application of a recently developed statistical regression technique, the LASSO, to detect novel candidates from high throughput transcriptomic datasets. We apply the LASSO to a tissue specific dataset in the model plant Arabidopsis thaliana to identify novel players in Arabidopsis thaliana seed coat mucilage synthesis. We built LASSO models based on a list of genes known to be involved in a sub-pathway of Arabidopsis mucilage synthesis. After identifying a putative transcription factor, we verified its involvement in mucilage synthesis by obtaining knock-out mutants for this gene. We show that a loss of function of this putative transcription factor leads to a significant decrease in mucilage pectin.