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SP06-05
Integrative approach for predicting transcription factors
controlling starch genes in cassava
Somkid Bumee1, Bandit Khampoosa2, Treenut Saithong1,2, and Saowalak Kalapanulak1,2*
1) Systems Biology and Bioinformatics Research Laboratory, Pilot Plant Development and Training Institute,
King Mongkut’s University of Technology Thonburi, Bangkhuntien, Bangkok, Thailand, 10150.
2) Bioinformatics and Systems Biology Program, School of Bioresources and Technology, School of Information
Technology, King Mongkut’s University of Technology Thonburi, Bangkhuntien, Bangkok, Thailand, 10150.
* [email protected]
Cassava (Manihot esculenta Crantz) is one of the most important starchy crops for human
diet, feed, and ethanol production. Improving both starch quantity and quality through gene
regulation and modification is being analyzed. This work aims to infer transcriptional
regulatory network (TRN) of starch metabolism in cassava by using integrative approach.
Firstly, TRN of Arabidopsis thaliana composed of transcription factors (TFs) and its gene
targets that function in starch metabolism, Calvin cycle, sucrose synthesis, and starch
synthesis pathways, has been collected from The Arabidopsis Gene Regulatory Information
Server (AGRIS). Not only was the TRN from AGRIS used as a template, but also the
constructed co-expression network of Arabidopsis using gene expression data from ATTED-II
database was applied for inferring TRN of starch metabolism in cassava. The reconstructed
TRN of cassava, composed of 242 interactions among 91 starch genes and 42 TFs, was
inferred by using reciprocal BLASTp based on comparative genomics approach. Secondly, all
predicted interactions between starch genes and TF genes were consolidated via upstream
sequences analysis through PlantPAN database. Finally, TRN consisted of 257 interactions,
among them 49 TFs and 91 starch genes, including additional 15 interactions from new 7
TFs identified from upstream sequences analysis. Interestingly, 67 interactions were
confirmed for binding possibilities between 23 TFs in the regulatory region of 39 starch
genes. In addition, microarray gene expression data of cassava under root development was
integrated to verify those interactions in the inferred TRN under the certain condition.
Pearson Correlation coefficient (PCC) was calculated in order to identify co-express gene
pairs among differentially expressed genes ( SDi  SD ). The result shows that putative sucrosephosphate synthase 4 (cassava4.1_000827m.g; SPS4) was confidently confirmed to be
regulated by C3H transcription factor family (cassava4.1_007787m.g; ZFN1) (PCC=060.0)
during cassava root development. Sucrose-phosphate synthase catalysing sucrose synthesis
in photosynthetic and non-photosynthetic tissues was proposed as one of the important
genes that enhances sucrose and starch biosynthesis in rice grain endosperm. ZFN1 was
classified in C3H transcription factor family which was reported to participate in plant
development and function in stress responses. These results may be useful for further
experimental validation in order to explore the transcriptional regulation of starch genes in
cassava.
Keywords: transcriptional regulatory network, starch metabolism, gene expression data