Supatcharee Netrphan

Evaluation of a morphological marker selection and excision system to generate marker-free transgenic cassava plants

The efficacy of the ipt-type Multi-Auto-Transformation (MAT) vector system to transform the extensively grown cassava cultivar “KU50” was evaluated. This system utilizes the isopentenyltransferase (ipt) gene as morphological marker for visual selection of transgenic lines. The extreme shooty phenotype (ESP) of transgenic lines is lost due to the removal of ipt gene mediated by the yeast Rint/RS system. As a result, phenotypically normal shoots, considered marker-free transgenic plants, could be obtained. When transforming KU50 cassava cultivar with two different ipt-type MAT vectors, transformation frequency at 19–21% was observed. Among the total number of ESP explants, 32–38% regained normal extended shoot phenotype and 88–96% of which were confirmed to represent the marker-free transgenic plants. This is the first demonstration of the efficacy of Rint/RS system in promoting excision of ipt marker gene in cassava specie, with the consequent rapid production of marker-free transgenic plants. The high efficiency of this system should facilitate pyramiding a number of transgenes by repeated transformation without having to undergo through laborious, expensive and time-consuming processes of sexual crossing and seed production. The generation of marker-free, thus environmentally safe, genetically modified cassava clones should also ease the public concerns regarding the use of transgenic cassava in both food and nonfood industries.

Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model

BackgroundStarch serves as a temporal storage of carbohydrates in plant leaves during day/night cycles. To study transcriptional regulatory modules of this dynamic metabolic process, we conducted gene regulation network analysis based on small-sample inference of graphical Gaussian model (GGM).ResultsTime-series significant analysis was applied for Arabidopsis leaf transcriptome data to obtain a set of genes that are highly regulated under a diurnal cycle. A total of 1,480 diurnally regulated genes included 21 starch metabolic enzymes, 6 clock-associated genes, and 106 transcription factors (TF). A starch-clock-TF gene regulation network comprising 117 nodes and 266 edges was constructed by GGM from these 133 significant genes that are potentially related to the diurnal control of starch metabolism. From this network, we found that β-amylase 3 (b-amy3: At4g17090), which participates in starch degradation in chloroplast, is the most frequently connected gene (a hub gene). The robustness of gene-to-gene regulatory network was further analyzed by TF binding site prediction and by evaluating global co-expression of TFs and target starch metabolic enzymes. As a result, two TFs, indeterminate domain 5 (AtIDD5: At2g02070) and constans-like (COL: At2g21320), were identified as positive regulators of starch synthase 4 (SS4: At4g18240). The inference model of AtIDD5-dependent positive regulation of SS4 gene expression was experimentally supported by decreased SS4 mRNA accumulation in Atidd5 mutant plants during the light period of both short and long day conditions. COL was also shown to positively control SS4 mRNA accumulation. Furthermore, the knockout of AtIDD5 and COL led to deformation of chloroplast and its contained starch granules. This deformity also affected the number of starch granules per chloroplast, which increased significantly in both knockout mutant lines.ConclusionsIn this study, we utilized a systematic approach of microarray analysis to discover the transcriptional regulatory network of starch metabolism in Arabidopsis leaves. With this inference method, the starch regulatory network of Arabidopsis was found to be strongly associated with clock genes and TFs, of which AtIDD5 and COL were evidenced to control SS4 gene expression and starch granule formation in chloroplasts.

Starch biosynthesis in cassava: a genome-based pathway reconstruction and its exploitation in data integration

BackgroundCassava is a well-known starchy root crop utilized for food, feed and biofuel production. However, the comprehension underlying the process of starch production in cassava is not yet available.ResultsIn this work, we exploited the recently released genome information and utilized the post-genomic approaches to reconstruct the metabolic pathway of starch biosynthesis in cassava using multiple plant templates. The quality of pathway reconstruction was assured by the employed parsimonious reconstruction framework and the collective validation steps. Our reconstructed pathway is presented in the form of an informative map, which describes all important information of the pathway, and an interactive map, which facilitates the integration of omics data into the metabolic pathway. Additionally, to demonstrate the advantage of the reconstructed pathways beyond just the schematic presentation, the pathway could be used for incorporating the gene expression data obtained from various developmental stages of cassava roots. Our results exhibited the distinct activities of the starch biosynthesis pathway in different stages of root development at the transcriptional level whereby the activity of the pathway is higher toward the development of mature storage roots.ConclusionsTo expand its applications, the interactive map of the reconstructed starch biosynthesis pathway is available for download at the SBI group’s website (http://sbi.pdti.kmutt.ac.th/?page_id=33). This work is considered a big step in the quantitative modeling pipeline aiming to investigate the dynamic regulation of starch biosynthesis in cassava roots.

Transcriptomic Data Integration Inferring the Dominance of Starch Biosynthesis in Carbon Utilization of Developing Cassava Roots

Abstract Carbon metabolism, which is an important process underlying the plant development, has been extensively studied in model plant Arabidopsis, however the understanding in this process for cassava root crop is very little. To enhance our understanding into the process, we studied carbon partitioning during cassava root development at the transcriptional level via transciptomic data integration into the metabolic pathways. The transcriptome data of three different developmental stages of cassava roots—fibrous root (FR), developing storage root (DR), and mature storage root (MR) from Yang et al. [1] —was integrated into the key carbon metabolism pathways reconstructed following the protocol of Rongsirikul et al. [2] . According to the 43 differentially expressed genes (56 proteins IDs) mapped into the pathways, we found that the genes involved in starch biosynthesis are more up-regulated, in contrast to the expression of genes in the cell wall biosynthesis and respiration. The results may imply the significance of starch biosynthesis among the carbon utilization processes in the developing cassava roots. In other words, the carbon source from α-D-glucose-1-phosphate (G1P) might be mostly used for starch biosynthesis rather than cell wall biosynthesis and respiration pathways during cassava root development.

Cassava root membrane proteome reveals activities during storage root maturation.

Cassava (Manihot esculenta Crantz) is one of the most important crops of Thailand. Its storage roots are used as food, feed, starch production, and be the important source for biofuel and biodegradable plastic production. Despite the importance of cassava storage roots, little is known about the mechanisms involved in their formation. This present study has focused on comparison of the expression profiles of cassava root proteome at various developmental stages using two-dimensional gel electrophoresis and LC-MS/MS. Based on an anatomical study using Toluidine Blue, the secondary growth was confirmed to be essential during the development of cassava storage root. To investigate biochemical processes occurring during storage root maturation, soluble and membrane proteins were isolated from storage roots harvested from 3-, 6-, 9-, and 12-month-old cassava plants. The proteins with differential expression pattern were analysed and identified to be associated with 8 functional groups: protein folding and degradation, energy, metabolism, secondary metabolism, stress response, transport facilitation, cytoskeleton, and unclassified function. The expression profiling of membrane proteins revealed the proteins involved in protein folding and degradation, energy, and cell structure were highly expressed during early stages of development. Integration of these data along with the information available in genome and transcriptome databases is critical to expand knowledge obtained solely from the field of proteomics. Possible role of identified proteins were discussed in relation with the activities during storage root maturation in cassava.

Reconstruction of Starch Biosynthesis Pathway in Cassava Using Comparative Genomic Approach

Cassava is one of the most attractive crops nowadays because it can produce and accumulate large amount of starch in its roots. Cassava starch is widely used as food, feed and raw materials for biochemical industries. Due to the increasing demand of cassava starch, the starch biosynthesis pathway is thus of interest for metabolic engineering, aiming at strain improvement. However, the uncertainties in the metabolic pathway of starch biosynthesis in cassava retard the rate of achievement. Availability of recently released cassava genome motivates us to reconstruct the starch biosynthesis pathway in cassava using comparative genomic approach. Here, nucleotide sequences of the template plants (i.e. Arabidopsis and potato) were compared with the sequence of cassava collected from three sources: Phytozome (genomic sequence), Cassava full-length cDNA and Cassava genome (ESTs) databases. The metabolic pathway of approximately 34 enzymes was constructed, including pathway from sucrose metabolism to amylose and amylopectin synthesis. The resulting pathway is a good initial point toward the complete pathway reconstruction.

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.