Cassava root membrane proteome reveals activities during storage root maturation

Transcriptome profiling reveals the genes involved in tuberous root expansion in Pueraria (Pueraria montana var. thomsonii)

BACKGROUND

Pueraria is a dry root commonly used in Traditional Chinese Medicine or as food and fodder, and tuberous root expansion is an important agronomic characteristic that influences its yield. However, no specific genes regulating tuberous root expansion in Pueraria have been identified. Therefore, we aimed to explore the expansion mechanism of Pueraria at six developmental stages (P1-P6), by profiling the tuberous roots of an annual local variety "Gange No.1" harvested at 105, 135, 165, 195, 225, and 255 days after transplanting.

RESULTS

Observations of the tuberous root phenotype and cell microstructural morphology revealed that the P3 stage was a critical boundary point in the expansion process, which was preceded by a thickening diameter and yield gain rapidly of the tuberous roots, and followed by longitudinal elongation at both ends. A total of 17,441 differentially expressed genes (DEGs) were identified by comparing the P1 stage (unexpanded) against the P2-P6 stages (expanded) using transcriptome sequencing; 386 differential genes were shared across the six developmental stages. KEGG pathway enrichment analysis showed that the DEGs shared by P1 and P2-P6 stages were mainly involved in pathways related to the "cell wall and cell cycle", "plant hormone signal transduction", "sucrose and starch metabolism", and "transcription factor (TF)". The finding is consistent with the physiological data collected on changes in sugar, starch, and hormone contents. In addition, TFs including bHLHs, AP2s, ERFs, MYBs, WRKYs, and bZIPs were involved in cell differentiation, division, and expansion, which may relate to tuberous root expansion. The combination of KEGG and trend analyses revealed six essential candidate genes involved in tuberous root expansion; of them, CDC48, ARF, and EXP genes were significantly upregulated during tuberous root expansion while INV, EXT, and XTH genes were significantly downregulated.

CONCLUSION

Our findings provide new insights into the complex mechanisms of tuberous root expansion in Pueraria and candidate target genes, which can aid in increasing Pueraria yield.

Set up from the beginning: The origin and early development of cassava storage roots

Despite the importance of storage root (SR) organs for cassava and the other root crops yield, their developmental origin is poorly understood. Here we use multiple approaches to shed light on the initial stages of root development demonstrating that SR and fibrous roots (FR) follow different rhizogenic processes. Transcriptome analysis carried out on roots collected before, during and after root bulking highlighted early and specific activation of a number of functions essential for root swelling and identified root-specific genes able to effectively discriminate emerging FR and SR. Starch and sugars start to accumulate at a higher rate in SR before they swell but only after parenchyma tissue has been produced. Finally, using non-destructive computed tomography measurements, we show that SR (but not FR) contain, since their emergence from the stem, an inner channel structure in continuity with the stem secondary xylem, indicating that SR derive from a distinct rhizogenic process compared with FR.

Transcriptome integrated metabolic modeling of carbon assimilation underlying storage root development in cassava

The existing genome-scale metabolic model of carbon metabolism in cassava storage roots, rMeCBM, has proven particularly resourceful in exploring the metabolic basis for the phenotypic differences between high and low-yield cassava cultivars. However, experimental validation of predicted metabolic fluxes by carbon labeling is quite challenging. Here, we incorporated gene expression data of developing storage roots into the basic flux-balance model to minimize infeasible metabolic fluxes, denoted as rMeCBMx, thereby improving the plausibility of the simulation and predictive power. Three different conceptual algorithms, GIMME, E-Flux, and HPCOF were evaluated. The rMeCBMx-HPCOF model outperformed others in predicting carbon fluxes in the metabolism of storage roots and, in particular, was highly consistent with transcriptome of high-yield cultivars. The flux prediction was improved through the oxidative pentose phosphate pathway in cytosol, as has been reported in various studies on root metabolism, but hardly captured by simple FBA models. Moreover, the presence of fluxes through cytosolic glycolysis and alanine biosynthesis pathways were predicted with high consistency with gene expression levels. This study sheds light on the importance of prediction power in the modeling of complex plant metabolism. Integration of multi-omics data would further help mitigate the ill-posed problem of constraint-based modeling, allowing more realistic simulation.

Exploring dynamic protein-protein interactions in cassava through the integrative interactome network

Protein-protein interactions (PPIs) play an essential role in cellular regulatory processes. Despite, in-depth studies to uncover the mystery of PPI-mediated regulations are still lacking. Here, an integrative interactome network (MePPI-Ux) was obtained by incorporating expression data into the improved genome-scale interactome network of cassava (MePPI-U). The MePPI-U, constructed by both interolog- and domain-based approaches, contained 3,638,916 interactions and 24,590 proteins (59% of proteins in the cassava AM560 genome version 6). After incorporating expression data as information of state, the MePPI-U rewired to represent condition-dependent PPIs (MePPI-Ux), enabling us to envisage dynamic PPIs (DPINs) that occur at specific conditions. The MePPI-Ux was exploited to demonstrate timely PPIs of cassava under various conditions, namely drought stress, brown streak virus (CBSV) infection, and starch biosynthesis in leaf/root tissues. MePPI-Ux_drought and MePPI-Ux_CBSV suggested involved PPIs in response to stress. MePPI-Ux_SB,leaf and MePPI-Ux_SB,root suggested the involvement of interactions among transcription factor proteins in modulating how leaf or root starch is synthesized. These findings deepened our knowledge of the regulatory roles of PPIs in cassava and would undeniably assist targeted breeding efforts to improve starch quality and quantity.

Prediction of cassava protein interactome based on interolog method

Cassava is a starchy root crop whose role in food security becomes more significant nowadays. Together with the industrial uses for versatile purposes, demand for cassava starch is continuously growing. However, in-depth study to uncover the mystery of cellular regulation, especially the interaction between proteins, is lacking. To reduce the knowledge gap in protein-protein interaction (PPI), genome-scale PPI network of cassava was constructed using interolog-based method (MePPI-In, available at http://bml.sbi.kmutt.ac.th/ppi). The network was constructed from the information of seven template plants. The MePPI-In included 90,173 interactions from 7,209 proteins. At least, 39 percent of the total predictions were found with supports from gene/protein expression data, while further co-expression analysis yielded 16 highly promising PPIs. In addition, domain-domain interaction information was employed to increase reliability of the network and guide the search for more groups of promising PPIs. Moreover, the topology and functional content of MePPI-In was similar to the networks of Arabidopsis and rice. The potential contribution of MePPI-In for various applications, such as protein-complex formation and prediction of protein function, was discussed and exemplified. The insights provided by our MePPI-In would hopefully enable us to pursue precise trait improvement in cassava.