Selenium is an important micronutrient that supports various important cellular and organismal functions (Yang R et al., 2017). Selenoproteins are proteins that include at least one selenocysteine (Sec) residue, which is similar to a normal cysteine amino acid but differs by the presence of selenium atom instead of a sulfur (Turanov AA et al., 2011).

It is a difficult task the prediction and annotation of selenoprotein genes because Sec is inserted while translating for a UGA codon, which function traditionally as a stop codon (Hua Chen et al., 2012). In order to distinguish between a seleneprotein and a STOP codon, it is necessary that the selenoprotein contains in the 3’UTR region a SECIS element.

Since most of these selenoproteins are incorrectly annotated, the main aim of our study is to predict and analyse the selenoproteins belonging to Laticauda laticaudata, by comparing it with an organism with the genome well-annotated. We have compared its genome to that of Homo sapiens which is commonly used as a reference organism. This project is focused on using bioinformatics methods as an approach to predicting selenoproteins present on Laticauda laticaudata and understanding their structure.

In this study a total number of 26 selenoproteins, 8 cysteine homologues of existing selenoproteins and 4 machinery proteins that synthesized the selenoproteins were predicted. We also provide additional information on the phylogenetic distribution of selenoprotein containing genome.