(SECIS) elements revealed a single SECIS element in these organisms (21). In the current study, we carried out bio- informatics analyses and identiﬁed four selenoproteins in Plasmodia. Interestingly, these selenoproteins showed no homology to either known selenoproteins in other species or to non-plasmodial proteins in general. MATERIALS AND METHODS Databases and programs P.falciparum, P.yoelii, P.knowlesi, P.berghei, P.vivax and P.chabaudi genomes were downloaded from PlasmoDB at www.plasmodb.org (Plasmodium Sequence Release November 04, 2003). The search for SECIS elements was carried out using SECISearch (17,22). Toxoplasma gondii genomic sequences were obtained from ToxoDB (www. toxodb.org, Data Release August 13, 2003). To identify Sec tRNA genes, we utilized COVE, tRNAscan-SE (23) and ARA- GORN (24) programs. BLAST searches were used to identify other components of the Sec insertion system. To predict the presence of signal peptides, we used SignalP 3.0 Server (25), which utilizes neural networks and hidden Markov models trained on eukaryotes. Search for SECIS elements The search for selenoproteins genes was carried out using the following algorithm: (1) Identification of potential SECIS elements by analyzing primary sequences. This step included the search for NTGA__AA__GA or NTGA__CC__GA motifs in nucleotide sequences with the distances between the Quartet (NTGA) and the unpaired AA in the apical loop of 10–13 nt, and between the AA to the GA of 15–39 nt. (2) Analyses of secondary structure features of SECIS ele- ments. Searches were performed to identify secondary structures consistent with the eukaryotic SECIS consensus. Additional filters were implemented to filter out candi- dates with unsuitable secondary structures (i.e. Y-shaped SECIS elements and SECIS elements with more than 2 unpaired nucleotides in a row within the first 7 nt pairs following NTGA). (3) Calculation of free energy for each candidate structure. Only thermodynamically stable structures were consi- dered. For that purpose, the free energies for the whole structure (with the threshold value of 12.6 kcal/mol) and the upper stem–loop (with the threshold of 3.7 kcal/mol) were calculated. (4) Identification of candidates for which homologs could be detected in other Plasmodia. The general approach was that, considering evolutionary distance among Plasmo- dia, candidates should be conserved in at least some species. Thus, the search was restricted to evolutionary conserved selenoproteins (the BLAST expect value below 0.001). (5) Analyses of SECIS location and identification of upstream open reading frames (ORFs). The purpose of this step was to filter out SECIS candidates, which were located within coding regions of known proteins. (6) Sequence analyses of predicted selenoprotein ORFs located upstream of candidate SECIS elements. This step Nucleic Acids Research, 2006, Vol. 34, No. 2 497 included identification of splice sites, ORFs, homologs in other species and searches against the Plasmodium EST database. SECIS candidates were filtered out if they were located within annotated ORFs or within introns of annotated genes. Searches for Sec insertion machinery To identify components of the Sec insertion machinery, we searched for homologs of known factors involved in Sec insertion. Decoding UGA as Sec requires a unique tRNA, a Sec-speciﬁc elongation factor EFSec, SECIS-binding protein SBP2 and selenophosphate synthetase (SelD, SPS). The presence of EFSec, SBP2 and SPS homologs in different Plasmodium species was determined using BLAST searches against human counterparts. Several approaches were attempted for the identiﬁcation of Sec tRNA in apicomplexan genomes. A common method relies on tRNAscan-SE (23), but this program, when used with the default settings, did not recognize Sec tRNA in P.falciparum. However, the ‘maximum sensitivity’ mode (COVE with a Sec-tRNA proﬁle) of tRNAscan-SE and ARAGORN programs (24) could identify this tRNA in both Plasmodium and Toxoplasma genomes. In addition, we have developed an algorithm to search for non-canonical tRNA sequences, which is described elsewhere (A.V. Lobanov, G.V. Krykov, D.L. Hatﬁeld and V.N. Gladyshev, manuscript submitted). Use of this program independently identiﬁed the same Sec tRNA. Phylogenetic analyses Amino acid and nucleotide sequence alignments were gener- ated using the ClustalW multiple sequence alignment pro- gram. Distances were calculated between each pair of sequences and these were used to construct the phylogenetic tree using the Neighbor Joining method of Saitou and Nei (26). TreeView was used for visualization of the trees. Transcription of P.falciparum selenoprotein genes PCR primers were obtained from MWG-Biotech (Ebersberg, Germany), Taq-polymerase was from Finnzymes (BioTec, Heidelberg, Germany), and the TA direct cloning vector pDrive was purchased from Qiagen (Hilden, Germany). A P.falciparum blood stage cDNA library from the strain 3D7 was used as template for the PCR ampliﬁcations. To verify the presence of selenoprotein mRNAs and to test PlasmoDB annotations and our predictions with regard to gene organiza- tion of the four Plasmodium selenoprotein genes (Figure 2), various primers were developed and employed in various com- binations in a PCR procedure. The ampliﬁed sections of the four genes were cloned into the cloning vector and veriﬁed by sequencing. The following oligonucleotide primers were used (Figure 2): Selenoprotein #1, N: 50-ATGGATGACAGAAAG- GAAAAC-30; s: 50-AAGACCCTACTTGGACAATC-30; C: 50-TCAGGTACTTCCCAAGCAGG-30; CU: 50-ATGTCG- GAAAAACATTTAACC-30. Selenoprotein #2, N: 50- ATGAAAGCTTATTACGTGGTG-30; C: 50-TTATTTAT- GAATATTTTTCAGATTTG-30; Ca: 50-TTAAATTGTAA- TATAATATAACTC-30; as: 50-ATGAATTTCATTTGTATT- ACATAG-30. Selenoprotein #3, N: 50-ATGATTTTAAAA- AAAGTGTATATAC-30; C: 50-TTATGTCCTTTTAAATT-