Selenoproteins are a group of proteins characterized by the presence of, at least, one Selenocysteine (Sec) residue in its chain. Since this residue is codified by UGA, which is normally considered as a stop codon, some of this proteins are dismissed in genome databases.
Moreover, the inclusion of Selenocysteine residue depends on the presence of an element called Selenocystein Insertion Sequence (SECIS), which is a secondary mRNA structure that allows the insertion of a selenocysteine instead of a stop codon.
The aim of our study is to predict the selenoproteins of Miichthys miiuy, a Japanese benthic fish, performing an homology-based in silico search. In order to assess the characteristics of the Miichthys miiuy's selenoproteome, we have compared the genome of this species with Danio rerio's and Homo sapiens's selenoproteins annotations obtained from SelenoDB. For the prediction, different bioinformatic tools such as BLAST, Exonerate, Genewise, T_coffee, Seblastian and SECISearch3 were needed. Additionally, we have designed an automatic program to speed up the process.
Our results show a high conservation between Zebrafish' and Miichthys miiuy' selenoproteome. We have found 33 selenoproteins, 8 Cys-containing homologous proteins, 5 machinery proteins and 11 proteins related to selenium metabolism.
This study contributes with the identification of selenoproteins in new-sequenciated organisms.