Plant glutathione peroxidases are an important class of enzymes which play key roles in the stress adaptability of plants both in context of biotic and abiotic stress pathways. They have been over the years much studied in animals since the catalytic residues are comprised of selenocysteine a variant amino acid which is ribosomally encoded with the help of an RNA structural element known as SECIS. Various workers over the years have shown that plant glutathione peroxidases play active roles in ROS sequestration, lipid hydroperoxidation as well as regulate glutathione levels. However, each plant has various patterns of glutathione peroxidase expression and action and in some plants certain isoforms have not been detected at all. This work focuses on the prediction and identification of single nucleotide polymorphisms (SNPs) and INDELs in the coding regions of plant glutathione peroxidases, with the help of a Bayesian based algorithm subsequently validated. A large number of informative sites were detected 279 of which had variant frequency of ≥ 50 %. This data should be beneficial for future studies involving genetic manipulation and population based breeding experiments.
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