Materials and methods

In order to make this project, we relied on some of the Internet databases which offer free acces to the hughe amount of information related to the human genome

The selenoproteins were chosen from a list which included most of the human selenoproteins that have been already identified.

Even though approximately 30 selenoproteins have been already sequenced, the choice was limited up to 20 candidates, due to the homology existent among 2 of the selenoprotein families: GPx (6 members) and TR (3 members). This degree of homology made it difficult to study one of these proteins.

Here we present a list of the main databases used to find the gene sequences:

Genome Informatics Research Lab

Goldenpath: Human Genome Browser Gateway

Project Ensemble: Ensembl Genome Browser
National Center for Biotechnology Information: NCBI

Other links used in this project were:

SECISearch

Procedures:

Ensembl Genom Browser was used to find the sequences of the selected selenoproteins and all the SNPs related.
We were interested in finding SNPs which could alter the final protein. Concretly, we were looking for SNPs in the UAG codons which encode for the selenocysteines incorporation and also for SNPs in the critical positions of the SECIS element.
Presence of SNPs in the gene sequence was not the only condition established for each selenoprotein. In order to know whether or not the SNPs were affecting the secis element, we should be able to generate it from the original 3'UTR region of each gene. Once we knew the structure, we could compare the positions of the SNPs with the critical positions within the secis element sequence.
As we developed the project, we thought it might be interesting to study if the SNPs found in the DNA sequences followed some kind of tissue-dependent expression pattern.
In order to do so, we would blast the DNA sequences of the selected selenoproteins to human EST databases. From the resulting output, we would chose the ESTs which shared >95% homology with the query sequence to see whether the SNP was tissue specific.
SECISearch could be used to find out whether any SNP was affecting the structure of the secis element of each protein (this is discussed in Results).
Finally, we decided not to go further but to follow the original insturctions (to write a program which can alineate sequences and find specific SNPs was too difficult and would have required too much time).
However,as we will explain in Results, we generated a very simple program which would allow us to select ESTs that shared >95% homology with our query sequence using BLAST test outputs. We named this program ord.pl.

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