Dataset Information

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

ABSTRACT:

Background

Cassava 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.

Results

In 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.

Conclusions

To 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.

SUBMITTER: Saithong T

PROVIDER: S-EPMC3847483 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Saithong Treenut T Rongsirikul Oratai O Kalapanulak Saowalak S Chiewchankaset Porntip P Siriwat Wanatsanan W Netrphan Supatcharee S Suksangpanomrung Malinee M Meechai Asawin A Cheevadhanarak Supapon S

BMC systems biology 20130810

<h4>Background</h4>Cassava 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.<h4>Results</h4>In 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 emp ...[more]

PMID: 23938102

Similar Datasets

Project description:An understanding of cassava starch paste properties (CSPP) can contribute to the selection of clones with differentiated starches. This study aimed to identify genomic regions associated with CSPP using different genome-wide association study (GWAS) methods (MLM, MLMM, and Farm-CPU). The GWAS was performed using 23,078 single-nucleotide polymorphisms (SNPs). The rapid viscoanalyzer (RVA) parameters were pasting temperature (PastTemp), peak viscosity (PeakVisc), hot-paste viscosity (Hot-PVisc), cool-paste viscosity (Cold-PVisc), final viscosity (FinalVis), breakdown (BreDow), and setback (Setback). Broad phenotypic and molecular diversity was identified based on the genomic kinship matrix. The broad-sense heritability estimates (h2) ranged from moderate to high magnitudes (0.66 to 0.76). The linkage disequilibrium (LD) declined to between 0.3 and 2.0 Mb (r2 <0.1) for most chromosomes, except chromosome 17, which exhibited an extensive LD. Thirteen SNPs were found to be significantly associated with CSPP, on chromosomes 3, 8, 17, and 18. Only the BreDow trait had no associated SNPs. The regional marker-trait associations on chromosome 18 indicate a LD block between 2907312 and 3567816 bp and that SNP S18_3081635 was associated with SetBack, FinalVis, and Cold-PVisc (all three GWAS methods) and with Hot-PVisc (MLM), indicating that this SNP can track these four traits simultaneously. The variance explained by the SNPs ranged from 0.13 to 0.18 for SetBack, FinalVis, and Cold-PVisc and from 0.06 to 0.09 for PeakVisc and Hot-PVisc. The results indicated additive effects of the genetic control of Cold-PVisc, FinalVis, Hot-PVisc, and SetBack, especially on the large LD block on chromosome 18. One transcript encoding the glycosyl hydrolase family 35 enzymes on chromosome 17 and one encoding the mannose-p-dolichol utilization defect 1 protein on chromosome 18 were the most likely candidate genes for the regulation of CSPP. These results underline the potential for the assisted selection of high-value starches to improve cassava root quality through breeding programs.

Project description:Cassava (Manihot esculenta Crantz) is a root crop used as a foodstuff and as a starch source in industry. Starch functional properties are influenced by many structural features including the relative amounts of the two glucan polymers amylopectin and amylose, the branched structure of amylopectin, starch granule size and the presence of covalent modifications. Starch phosphorylation, where phosphates are linked either to the C3 or C6 carbon atoms of amylopectin glucosyl residues, is a naturally occurring modification known to be important for starch remobilization. The degree of phosphorylation has been altered in several crops using biotechnological approaches to change expression of the starch-phosphorylating enzyme GLUCAN WATER DIKINASE (GWD). Interestingly, this frequently alters other structural features of starch beside its phosphate content. Here, we aimed to alter starch phosphorylation in cassava storage roots either by manipulating the expression of the starch phosphorylating or dephosphorylating enzymes. Therefore, we generated transgenic plants in which either the wild-type potato GWD (StGWD) or a redox-insensitive version of it were overexpressed. Further plants were created in which we used RNAi to silence each of the endogenous phosphoglucan phosphatase genes STARCH EXCESS 4 (MeSEX4) and LIKE SEX4 2 (MeLSF), previously discovered by analyzing leaf starch metabolism in the model species Arabidopsis thaliana. Overexpressing the potato GWD gene (StGWD), which specifically phosphorylates the C6 position, increased the total starch-bound phosphate content at both the C6 and the C3 positions. Silencing endogenous LSF2 gene (MeLSF2), which specifically dephosphorylates the C3 position, increased the ratio of C3:C6 phosphorylation, showing that its function is conserved in storage tissues. In both cases, other structural features of starch (amylopectin structure, amylose content and starch granule size) were unaltered. This allowed us to directly relate the physicochemical properties of the starch to its phosphate content or phosphorylation pattern. Starch swelling power and paste clarity were specifically influenced by total phosphate content. However, phosphate position did not significantly influence starch functional properties. In conclusion, biotechnological manipulation of starch phosphorylation can specifically alter certain cassava storage root starch properties, potentially increasing its value in food and non-food industries.

Project description:The study of cancer, a highly heterogeneous disease with different causes and clinical outcomes, requires a multi-angle approach and the collection of large multi-omics datasets that, ideally, should be analyzed simultaneously. We present a new pathway relevance ranking method that is able to prioritize pathways according to the information contained in any combination of tumor related omics datasets. Key to the method is the conversion of all available data into a single comprehensive network representation containing not only genes but also individual patient samples. Additionally, all data are linked through a network of previously identified molecular interactions. We demonstrate the performance of the new method by applying it to breast and ovarian cancer datasets from The Cancer Genome Atlas. By integrating gene expression, copy number, mutation and methylation data, the method's potential to identify key pathways involved in breast cancer development shared by different molecular subtypes is illustrated. Interestingly, certain pathways were ranked equally important for different subtypes, even when the underlying (epi)-genetic disturbances were diverse. Next to prioritizing universally high-scoring pathways, the pathway ranking method was able to identify subtype-specific pathways. Often the score of a pathway could not be motivated by a single mutation, copy number or methylation alteration, but rather by a combination of genetic and epi-genetic disturbances, stressing the need for a network-based data integration approach. The analysis of ovarian tumors, as a function of survival-based subtypes, demonstrated the method's ability to correctly identify key pathways, irrespective of tumor subtype. A differential analysis of survival-based subtypes revealed several pathways with higher importance for the bad-outcome patient group than for the good-outcome patient group. Many of the pathways exhibiting higher importance for the bad-outcome patient group could be related to ovarian tumor proliferation and survival.

Dataset Information

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

Background

Results

Conclusions

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets