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International Journal of Computational Bioinformatics and In Silico Modeling
2013: Volume-2 Issue-1
ISSN: 2320-0634

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ABSTRACT   REFERENCES  
International Journal of Computational Bioinformatics and In Silico Modeling 2(1) 2013: 72-80

In Silico analysis of some least studied transcription factors/regulators in rice during abiotic stress


Archana Kumari, Ashutosh Kumar and Dev Mani Pandey*

Department of Biotechnology, Birla institute of Technology, Mesra, Ranchi, Jharkhand, India.

* To whom correspondence should be addressed. Email: dmpandey@bitmesra.ac.in

ABSTRACT

Abiotic stresses, such as salinity, drought, cold and adverse environmental conditions affect the growth of plants. Stresses are severe intimidation for cultivation and the usual status of the surroundings. The accessibility of Plant Transcription Factor Database and Rice Oligo Array Database create an achievable opportunity to recognize the least studied transcription factor/regulator genes in rice. On the basis of PCC (Pearson correlation co-efficient) cut-off value in the co-expression network analysis some least studied transcription factors/regulators were retrieved. Above retrieval has done by restricting the correlation co-efficient value for abiotic stress in Rice Oligo Array Database. The comparative analysis and evolutionary relationship of these transcription factors/regulators have been done using multiple sequence alignment and phylogenetic analysis, respectively. Depending on the co-expression networking in Rice Oligo Array Database, we have identified 39 genes having least information that belongs to 11 different transcription factors families and 7 transcription regulators in rice. Abundance of serine residue in protein sequences and transition substitution of Cytosine with Thymine in nucleotide sequences for all 39 transcription factors/regulators genes were noticed. Therefore, presence of serine might activate these transcription factors during drought and metal stress condition and have significant role in plant adaptation and stress response.

Copyright © 2013 | AIZEON publishers | All rights reserved

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Citation: Archana Kumari, Ashutosh Kumar and Dev Mani Pandey (2013). In Silico analysis of some least studied transcription factors/regulators in rice during abiotic stress. Int J Comput Bioinfo In Silico Model 2(1): 72-80

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