Alignment-free sequence comparison using N-dimensional similarity space.

Several alignment free sequence comparison methods are available and they use similarity, based on a particular numerical descriptor of biological sequences. Any loss of information incurred in the transformation of a sequence into a numerical descriptor affects the results. A pool of descriptors that use different algorithms in their computation is expected to suffer minimum loss of information and an attempt is made in this direction to study the similarity of DNA sequences that are homogenous or heterogeneous. Several numerical descriptors for the characterization of DNA sequences are described, based on information theoretic approach, connectivity of vertex weighted line-graphs and those derived from the matrices obtained from the graphs constructed by depicting DNA sequences as a random walk on a Euclidean plane. The information theoretic descriptors were obtained based on the L-tuple approach for the combination of different numbers of bases. The connectivity type descriptors were calculated by converting the DNA sequence into vertex weighted graphs in which vertices (nucleotide) were assigned weights based on the pKa of the bases. The graphical representations were converted into numerical descriptors by constructing matrices. Computer programs were developed to calculate seventy DNA descriptors; 560 sequences of different types of organisms were used. After initial data analysis to eliminate almost perfectly correlated descriptors, orthogonal descriptors were obtained by performing principal component analysis. Principal components (PCs) were used to construct an N-dimensional similarity space wherein the 560 sequences were clustered by k-means cluster algorithm. Five principal components (orthogonal descriptors) were extracted and found to explain 92% of data variance. The PCs were used to cluster the sequences in a five-dimensional similarity space. The similarity-based dissimilarity clustering procedure using numerical descriptors was found to be effective for studying similarity/ dissimilarity of large number of sequences.

Novel calcium-binding GTPase (AtCBG) involved in ABA-mediated salt stress signaling in Arabidopsis.

We have identified a novel Ca(2+)-signal sensing GTPase (643 amino acid residues with an estimated molecular mass of 79 kDa) from the Arabidopsis genome database. This protein contains a RHO-like GTPase domain at the N-terminus (15-184 amino acids) and two calcium-binding EF-hand motifs (199-227 and 319-347 amino acids, respectively). It has the capability to bind calcium and hydrolyze GTP; in addition, its GTPase activity is regulated by changes in Ca(2+) concentration. The expression of this gene was induced by ABA and salt stresses, and specific knock-out mutants were highly sensitive to ABA and salt treatments. These findings suggest that this protein is a novel ABA- and salt stress-related Ca(2+) signal transducer.

Drought-induced responses of photosynthesis and antioxidant metabolism in higher plants.

Environmental stresses trigger a wide variety of plant responses, ranging from altered gene expression and cellular metabolism to changes in growth rates and crop yields. A plethora of plant reactions exist to circumvent the potentially harmful effects caused by a wide range of both abiotic and biotic stresses, including light, drought, salinity, high temperatures, and pathogen infections. Among the environmental stresses, drought stress is one of the most adverse factors of plant growth and productivity. Understanding the biochemical and molecular responses to drought is essential for a holistic perception of plant resistance mechanisms to water-limited conditions. Drought stress progressively decreases CO2 assimilation rates due to reduced stomatal conductance. Drought stress also induces reduction in the contents and activities of photosynthetic carbon reduction cycle enzymes, including the key enzyme, ribulose-1,5-bisphosphate carboxylase/oxygenase. The critical roles of proline and glycine-betaine, as well as the role of abscisic acid (ABA), under drought stress conditions have been actively researched to understand the tolerance of plants to dehydration. In addition, drought stress-induced generation of active oxygen species is well recognized at the cellular level and is tightly controlled at both the production and consumption levels in vivo, through increased antioxidative systems. Knowledge of sensing and signaling pathways, including ABA-mediated changes in response to drought stress, is essential to improve crop management. This review focuses on the ability and strategies of higher plants to respond and adapt to drought stress.