Skip to main content
ARS Home » Southeast Area » Stoneville, Mississippi » Crop Genetics Research » Research » Publications at this Location » Publication #304057
Title: Computational discovery of soybean promoter cis-regulatory elements for the construction of soybean cyst nematode inducible synthetic promoters

Author
item LIU, W - University Of Tennessee
item MAZAREI, M - University Of Tennessee
item PENG, Y - University Of Tennessee
item FETHE, M - University Of Tennessee
item RUDIS, M - University Of Tennessee
item LIN, J - University Of Tennessee
item MILLWOOD, R - University Of Tennessee
item Arelli, Prakash
item STEWART, JR, C - University Of Tennessee

Submitted to: Plant Biotechnology Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/23/2014
Publication Date: 6/3/2014
Citation: Liu, W., Mazarei, M., Peng, Y., Fethe, M.H., Rudis, M.R., Lin, J., Millwood, R.J., Arelli, P.R., Stewart, Jr, C.N. 2014. Computational discovery of soybean promoter cis-regulatory elements for the construction of soybean cyst nematode inducible synthetic promoters. Plant Biotechnology Journal. doi: 10.1111/pbi. 12206.

Interpretive Summary: Soybean yields worldwide are limited by the soybean cyst nematode (SCN), a microscopic size round worm attaching the roots of the plant and absorbing the nutrition from the soybean plant. Resistant cultivars have been the most effective means of controlling the pest. Nematode populations are variable and over time, will adapt to reproduce on resistant cultivars rendering once resistant cultivar a susceptible one. Therefore, breeding is a constant challenge for developing more durable resistance. Novel biotechnological approaches especially computational methods offer great opportunity in the prediction of regulatory genes and gene components and/or mechanisms of a given trait including SCN. Several bioinformatic tools were identified in this research. Using synthetic gene components called as promoters specific to this research, a high throughput production potential has been synthesized for trait discovery. If applied, this technology can result in genetic engineering of transgenic resistant soybean plants. Combined with traditional method of breeding, production of novel resistant plants which can withstand SCN damage may be a boon to farmers protecting yields and increasing profit margin.

Technical Abstract: Computational methods offer great hope but limited accuracy in the prediction of functional cis-regulatory elements; improvements are needed to enable synthetic promoter design. We applied an ensemble strategy for de novo soybean cyst nematode (SCN)-inducible motif discovery among promoters of 18 co-expressed soybean genes which were selected from six reported microarray studies involving a compatible soybean – soybean cyst nematode (SCN) interaction. A total of 116 overlapping motif regions (OMRs) were discovered bioinformatically that were identified by at least 4 out of 7 bioinformatic tools. Using synthetic promoters, the inducibility of each OMR or motif itself was evaluated by co-localization of gain-of-function of an orange fluorescent protein reporter and the presence of SCN in transgenic soybean hairy roots. Among 16 OMRs detected from 2 experimentally confirmed SCN-inducible promoters, 11 OMRs (i.e., 68.75 %) were experimentally confirmed to be SCN-inducible, leading to the discovery of 23 core motifs of 5-7 bp length; of which 14 are novel in plants. We found that a combination of the 3 best tools (i.e., SCOPE, W-AlignACE, and Weeder) could detect all 23 core motifs. Thus, this strategy is a high throughput approach for de novo motif discovery in soybean and offers great potential for novel motif discovery and synthetic promoter engineering for any plant and trait in crop biotechnology.