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RegCyanoDB: a database of regulatory interactions in cyanobacteria

View ORCID ProfileAjay Nair, Madhu Chetty, Nguyen Xuan Vinh
doi: https://doi.org/10.1101/117127
Ajay Nair
1IITB-Monash Research Academy, Indian Institute of Technology Bombay, Mumbai, 400 076, India
2Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia
3Chemical Engineering Department, Indian Institute of Technology Bombay, Mumbai, 400 076, India
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  • For correspondence: ajaynair@iitb.ac.in
Madhu Chetty
4Faculty of Science and Technology, Federation University, VIC 3841, Australia
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Nguyen Xuan Vinh
5School of Computing and Information Systems, The University of Melbourne, VIC 3010, Australia
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Abstract

Background Cyanobacteria are photoautotrophic organisms with environmental, evolutionary, and industrial importance. Knowledge of its regulatory interactions are important to predict, optimise, and engineer their characteristics. However, at present, very few of their regulatory interactions are known. The regulatory interactions are known only for a few model organisms such as Escherichia coli due to technical and economical constraints, which are unlikely to change soon. Thus, mapping of regulatory interactions from well-studied organisms to less-studied organisms by using computational techniques is widely used. Reverse Best Hit (RBH), with appropriate algorithm parameters, is a simple and efficient method for detecting functional homologs.

Description We predict the regulatory interactions in 30 strains of cyanobacteria using the known regulatory interactions from the best-studied organism, E. coli. RBH method with appropriate parameters is used to identify the functional homologs. An interaction is mapped to a cyanobacterial strain if functional homologs exist for a known transcription factor and its target gene. The confidence of the detected homologs and interactions are also provided. Since RBH is a conservative method, homolog-grouping is performed to recover lost putative interactions. A database of the predicted interactions from all the 30 strains of cyanobacteria is constructed.

Conclusion RegcyanoDB contains 20,280 interactions with confidence levels for 30 cyanobacterial strains. The predicted regulatory interactions exhibit a scale free network topology as observed in model organisms. The interacting genes in E. coli and cyanobacteria are mostly found to have the same gene annotation. This database can be used for posing novel hypotheses and validation studies in wet-lab and computational domains.

The database is available at http://www.che.iitb.ac.in/grn/RegCyanoDB/

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted March 20, 2017.
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RegCyanoDB: a database of regulatory interactions in cyanobacteria
Ajay Nair, Madhu Chetty, Nguyen Xuan Vinh
bioRxiv 117127; doi: https://doi.org/10.1101/117127
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RegCyanoDB: a database of regulatory interactions in cyanobacteria
Ajay Nair, Madhu Chetty, Nguyen Xuan Vinh
bioRxiv 117127; doi: https://doi.org/10.1101/117127

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