Kavi K.P.B.,Osmania University |
Bandopadhyay R.,Birla Institute of Technology |
Suravajhala P.,Bioclues Organization
Agricultural Bioinformatics | Year: 2014
A common approach to understanding the functional repertoire of a genome is through functional genomics. With systems biology burgeoning, bioinformatics has grown to a larger extent for plant genomes where several applications in the form of protein-protein interactions (PPI) are used to predict the function of proteins. With plant genes evolutionarily conserved, the science of bioinformatics in agriculture has caught interest with myriad of applications taken from bench side to in silico studies. A multitude of technologies in the form of gene analysis, biochemical pathways and molecular techniques have been exploited to an extent that they consume less time and have been cost-effective to use. As genomes are being sequenced, there is an increased amount of expression data being generated from time to time matching the need to link the expression profiles and phenotypic variation to the underlying genomic variation. This would allow us to identify candidate genes and understand the molecular basis/phenotypic variation of traits. While many bioinformatics methods like expression and whole genome sequence data of organisms in biological databases have been used in plants, we felt a common reference showcasing the reviews for such analysis is wanting. We envisage that this dearth would be facilitated in the form of this Springer book on Agricultural Bioinformatics. We thank all the authors and the publishers Springer, Germany for providing us an opportunity to review the bioinformatics works that the authors have carried in the recent past and hope the readers would find this book attention grabbing. © Springer India 2014. All rights reserved.
Kumar A.,Advance Center for Computational & Applied Biotechnology |
Kumar S.,Bioinformatics Center |
Kumar U.,Center for Excellence in Mountain Biology |
Suravajhala P.,Bioclues Organization |
Gajula M.N.V.P.,Rajendra Agricultural University
Computational Biology and Chemistry | Year: 2016
Triticum aestivum L. known as common wheat is one of the most important cereal crops feeding a large and growing population. Various environmental stress factors including drought, high salinity and heat etc. adversely affect wheat production in a significant manner. Dehydration-responsive element-binding (DREB1A) factors, a class of transcription factors (TF) play an important role in combating drought stress. It is known that DREB1A specifically interacts with the dehydration responsive elements (DRE/CRT) inducing expression of genes involved in environmental stress tolerance in plants. Despite its critical interplay in plants, the structural and functional aspects of DREB1A TF in wheat remain unresolved. Previous studies showed that wheat DREBs (DREB1 and DREB2) were isolated using various methods including yeast two-hybrid screens but no extensive structural models were reported. In this study, we made an extensive in silico study to gain insight into DREB1A TF and reported the location of novel DREB1A in wheat chromosomes. We inferred the three-dimensional structural model of DREB1A using homology modelling and further evaluated them using molecular dynamics(MD) simulations yielding refined modelled structures. Our biochemical function predictions suggested that the wheat DREB1A orthologs have similar biochemical functions and pathways to that of AtDREB1A. In conclusion, the current study presents a structural perspective of wheat DREB1A and helps in understanding the molecular basis for the mechanism of DREB1A in response to environmental stress. © 2016 Elsevier Ltd
Panchangam S.S.,Indian International Crops Research Institute for the Semi Arid Tropics |
Mallikarjuna N.,Indian International Crops Research Institute for the Semi Arid Tropics |
Gaur P.M.,Indian International Crops Research Institute for the Semi Arid Tropics |
Suravajhala P.,Bioclues Organization
Indian Journal of Experimental Biology | Year: 2014
Double haploid technique is not routinely used in legume breeding programs, though recent publications report haploid plants via anther culture in chickpea (Cicer arietinum L.). The focus of this study was to develop an efficient and reproducible protocol for the production of double haploids with the application of multiple stress pre-treatments such as centrifugation and osmotic shock for genotypes of interest in chickpea for their direct use in breeding programs. Four genotypes, ICC 4958, WR315, ICCV 95423 and Arearti were tested for anther culture experiments. The yield was shown to be consistent with 3-5 nucleate microspores and 2-7 celled structures with no further growth. To gain a further insight into the molecular mechanism underlying the switch from microsporogenesis to androgenesis, bioinformatics tools were employed. The challenges on the roles of such genes were reviewed while an attempt was made to find putative candidates for androgenesis using Expressed Sequenced Tags (EST) and interolog based protein interaction analyses.
Anil Kumar S.,Osmania University |
Hima Kumari P.,Osmania University |
Shravan Kumar G.,Osmania University |
Mohanalatha C.,Bioclues Organization |
Kavi Kishor P.B.,Osmania University
Frontiers in Plant Science | Year: 2015
Osmotin is a stress responsive antifungal protein belonging to the pathogenesis-related (PR)-5 family that confers tolerance to both biotic and abiotic stresses in plants. Protective efforts of osmotin in plants range from high temperature to cold and salt to drought. It lyses the plasma membrane of the pathogens. It is widely distributed in fruits and vegetables. It is a differentially expressed and developmentally regulated protein that protects the cells from osmotic stress and invading pathogens as well, by structural or metabolic alterations. During stress conditions, osmotin helps in the accumulation of the osmolyte proline, which quenches reactive oxygen species and free radicals. Osmotin expression results in the accumulation of storage reserves and increases the shelf-life of fruits. It binds to a seven-transmembrane-domain receptorlike protein and induces programmed cell death in Saccharomyces cerevisiae through RAS2/cAMP signaling pathway. Adiponectin, produced in adipose tissues of mammals, is an insulin-sensitizing hormone. Strangely, osmotin acts like the mammalian hormone adiponectin in various in vitro and in vivo models. Adiponectin and osmotin, the two receptor binding proteins do not share sequence similarity at the amino acid level, but interestingly they have a similar structural and functional properties. In experimental mice, adiponectin inhibits endothelial cell proliferation and migration, primary tumor growth, and reduces atherosclerosis. This retrospective work examines the vital role of osmotin in plant defense and as a potential targeted therapeutic drug for humans. © 2015 2015 Anil Kumar, Hima Kumari, Shravan Kumar, Mohanalatha and Kavi Kishor.
Ur Rehman H.,Polytechnic University of Turin |
Benso A.,Polytechnic University of Turin |
Di Carlo S.,Polytechnic University of Turin |
Politane G.,Polytechnic University of Turin |
And 2 more authors.
Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2012 | Year: 2012
Uncharacterized proteins pose a challenge not just to functional genomics, but also to biology in general. The knowledge of biochemical functions of such proteins is very critical for designing efficient therapeutic techniques. The bottleneck in hypothetical proteins annotation is the difficulty in collecting and aggregating enough biological information about the protein itself. In this paper, we propose and evaluate a protein annotation technique that aggregates different biological information conserved across many hypothetical proteins. To enhance the performance and to increase the prediction accuracy, we incorporate term specific relationships based on Gene Ontology (GO). Our method combines PPI (Protein Protein Interactions) data, protein motifs information, protein sequence similarity and protein homology data, with a context similarity measure based on Gene Ontology, to accurately infer functional information for unannotated proteins. We apply our method on Saccharomyces Cerevisiae species proteins. The aggregation of different sources of evidence with GO relationships increases the precision and accuracy of prediction compared to other methods reported in literature. We predicted with a precision and accuracy of 100% for more than half proteins of the input set and with an overall 81.35% precision and 80.04% accuracy. © 2012 IEEE.